62 results on '"De Fazio, R"'
Search Results
2. A retrospective, multicenter study on the management of macular holes without residual internal limiting membrane: the refractory macular hole (ReMaHo) study
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Lorenzi, U., Mehech, J., Caporossi, T., Romano, M. R., De Fazio, R., Parrat, E., Matonti, F., Mora, P., Sborgia, G., Forlini, M., Ventre, L., Soler, V., Sampo, M., Fiore, T., Van Overdam, K., Guigou, S., Rouhette, H., Rapizzi, E., Denion, E., Rebollo, O., Meyer, F., Uzzan, J., Mafrici, M., Bacherini, D., Favilla, S., Ricciotti, G., Tedesco, S. A., Gandolfi, S., and Muraine, M. more...
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Visual Acuity ,Retinal Perforations ,Sensory Systems ,Basement Membrane ,Retina ,Cellular and Molecular Neuroscience ,Ophthalmology ,No internal limiting membrane ,Vitrectomy ,Reconstructive surgery ,Humans ,Full thickness macular hole ,Prognostic variables ,Tomography, Optical Coherence ,Retrospective Studies - Abstract
Purpose To evaluate the surgical management, outcomes and prognostic factors of full thickness macular holes without residual internal limiting membrane (NO-ILM FTMHs). Methods We performed a multicenter, retrospective study of 116 NO-ILM FTMHs. Human amniotic membrane (hAM) plug, autologous ILM free flap transplantation (AILMT), and autologous retinal graft transplantation (ART) were performed in 58, 48, and 10 patients, respectively. Data were collected before and up to 12 months after surgery. The primary outcomes were hole closure and final best-corrected visual acuity (BCVA). Results The final BCVA (0.78 ± 0.51 logMAR) was significantly better than and correlated with the initial BCVA (p 680 μm had a higher closure rate with hAM than with AILMT (p = 0.02). Conclusions AILMT and hAM were the most frequently performed surgeries with both high closure rate and significant functional improvement. Preoperative BCVA was correlated with final BCVA. The minimum FTMH diameter may guide the treatment choice. more...
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- 2022
Catalog
3. An Innovative Green Process for the Stabilization and Valorization of Organic Fraction of Municipal Solid Waste (OFMSW) I Part
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Stefania Minosi, Francesca Ferrari, Antonio Greco, Raffaella Striani, Federica Paladini, Mauro Pollini, Paolo Visconti, Angelica Panico, Esposito Corcione C, De Fazio R, ESPOSITO CORCIONE, Carola, Ferrari, Francesca, Striani, Raffaella, Minosi, Stefania, Pollini, Mauro, Paladini, Federica, Panico, Angelica, DE FAZIO, Roberto, Visconti, Paolo, and Greco, Antonio more...
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Municipal solid waste ,Waste management ,Scientific method ,Environmental science ,biomedical_chemical_engineering ,Organic fraction - Abstract
This work is aimed at the development of innovative, easy and cheap methods for the stabilization, inertization and valorisation of the organic fraction of municipal solid waste (OFMSW). For the first time, two original processes for transforming the organic waste into an inert, odorless and sanitized material were here proposed. The first one, called dual step, starts with grinding of the OFMSW, by means of an industrial shredder. After being finely ground, the organic waste was exposed to a sterilization process by means of UV/ozone radiations or thermal treatment (stabilization phase) in order to obtain a complete removal of the OFMSW’s bacterial activity. By means of several microbiological analyses, the best sterilization method was chosen. The incorporation in a thermosetting matrix was, then, carried out through mixing the sterilized and finely ground organic waste into a water soluble urea formaldehyde (UF) based resin, with a formaldehyde content less than 1% wt, followed by a thermal treatment for UF-resin crosslinking (inertization phase). An alternative cheaper and easier process, called one step, was also proposed and investigated, by combining the sterilization with the curing thermal process (at higher temperature) of the thermosetting matrix. The preliminary experimental results reported in this paper suggest that both the proposed methods could be considered suitable for the production of high valorized innovative OFMSW-derived panels or bricks, that could find application in several fields, such as building or constructions materials. Finally a brief description of the prototype machinery is reported properly designed for implementing OFMSW stabilization and valorisation processes developed in this research work. more...
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- 2019
4. Electronic Control System of LED-Induced CNTs Photo-Ignition for Improved Fuels Combustion in Advanced Engines
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VISCONTI, Paolo, CARLUCCI, Antonio Paolo, PRIMICERI, PATRIZIO, de Fazio, R., GENERAL CHAIR: Andrea Lacaita. COORDINATOR: Alessandro Busacca, Visconti, Paolo, Carlucci, Antonio Paolo, Primiceri, Patrizio, and de Fazio, R. more...
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The use of carbon nanotubes (CNTs) in the combustion and propulsion sector, which is the object of this work, is due to the discovery of photo-ignition properties of such nano-material, when they are exposed to an intense luminous flash [1]. This phenomenon allows obtaining fuels combustion system more efficient and clean (HCCI engine) [2]. Most of the literature studies involve a Xe-lamp to ignite the CNTs mixed with metal catalyst; the use of this light source is not without criticism because it requires very high supply voltages, has an intrinsic mechanical instability, and it can’t work at frequencies required by an automotive engine running [3]. A LED-based ignition system can be considered the optimum solution, because LEDs have high luminous efficiency, higher mechanical stability and for the absence of frequency limitations. In this work, a LEDs-based experimental setup used to perform combustion tests of gaseous fuels, by means of photo-ignition of MWCNTs/FeCp2, has been proposed (Fig. 1). The setup uses a multi-LED ignition-system, placed outside the combustion chamber, convoying the light emitted by each LED source into the chamber by a fiber optic. The electronic section drives and controls the LED sources, synchronizing temporally them with the input of the enriched air-fuel mixture. Moreover, it will also handle and monitor all physical / environmental parameters involved in the combustion process, such as temperature and pressure inside the combustion chamber, etc. In order to obtain a light pulse of controlled duration, a driving and control electronic system was realized (Fig. 2). The white power LEDs (Cree XHP70) were driven by proper LED drivers; to generate a single light pulse, a pulsed signal is applied to the enable control input of each LED driver. This last signal is obtained on PC audio channel by proper LabVIEW application and after conditioning by an interface board. A four LEDs source was used to perform ignition tests on the dry mixtures MWCNTs/FeCp2 to obtain energy density comparable to which obtained with the Xe lamp. In the Figs. 3a and b, the setup used to perform ignition tests on dry mixtures MWCNTs/FeCp2, is shown; the driving and control unit is constituted by four LED drivers, the interface board and the PC with LabVIEW application (Fig. 3a), whereas tests area with the four LEDs source and the power/energy meter (Thorlabs PM100D) equipped with pyroelectric sensor (Thorlabs ES145C) are shown in Fig. 3b. The light source is placed at 1cm at least from the pyroelectric sensor and then from CNTs sample (Fig. 3b). Using this experimental setup, the minimum pulse durations needed to ignite the MWCNTs/FeCp2 samples for the different concentrations by weight, are determined. Known the light source intensity, the minimum ignition energy of the MWCNTs/FeCp2 samples for the considered concentrations, are calculated (Fig. 4). more...
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- 2017
5. A Solar-Powered Fertigation System Based on Low-Cost Wireless Sensor Network Remotely Controlled by Farmer for Irrigation Cycles and Crops Growth Optimization.
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Visconti, P., de Fazio, R., Primiceri, P., Cafagna, D., Strazzella, S., and Giannoccaro, N. I.
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PRECISION farming , *INFORMATION storage & retrieval systems , *WIRELESS sensor networks , *INTERNET of things , *FERTIGATION - Abstract
Nowadays, the technological innovations affect all human activities; also the agriculture field heavily benefits of technologies as informatics, electronic, telecommunication, allowing huge improvements of productivity and resources exploitation. This manuscript presents an innovative low cost fertigation system for assisting the cultures by using dataprocessing electronic boards and wireless sensors network (WSN) connected to a remote software platform. The proposed system receives information related to air and soil parameters, by a custom solar-powered WSN. A control unit elaborates the acquired data by using dynamic agronomic models implemented on a cloud platform, for optimizing the amount and typology of fertilizers as well as the irrigations frequency, as function also of weather forecasts got by on-line weather service. [ABSTRACT FROM AUTHOR] more...
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- 2020
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6. Arduino-Based Solution for In-Car-Abandoned Infants' Controlling Remotely Managed by Smartphone Application.
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Visconti, P., de Fazio, R., Costantini, P., Miccoli, S., and Cafagna, D.
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MOBILE apps ,SMART cities ,INFANTS ,TELECOMMUNICATION systems ,APPLICATION software ,AUTOMOTIVE telematics - Abstract
This manuscript deals with V2V/V2I (Vehicle-to-Vehicle and Vehicle-to-Infrastructure) communication systems developed for smart city applications, with the aim to provide new services and tools for making driving safer and improving the human lifestyle. The considered systems can be supported by suitable software applications for making the services more accessible. In this context, research groups and automotive companies are currently developing systems against children abandonment in unattended vehicles and are installing them on new car models. In this paper, an innovative Arduino-based control system against children abandonment in cars is described. It introduces new functionalities respect to systems reported in literature or already on the market, in order to improve safety and reliability. The proposed system integrates a mobile app, which gives the possibilities of receiving alert or status messages, along with images directly acquired from car cockpit. In addition, the app allows to remotely control several car functionalities, such as horn activation, windows lowering and doors locking/unlocking. The wide set of employed sensors allows to solve some shortcomings of detectability presented by similar detection systems, thanks to a proper cross-checking of the acquired information. [ABSTRACT FROM AUTHOR] more...
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- 2019
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7. Mesenchymal stem cells isolated from amniotic fluid differentiate in neuronal cells
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Rustichelli, D, Mareschi, Katia, Ferrero, Ivana, Manetta, T, De Fazio, R, Anselmino, A, Morterra, G, Gunetti, M, Comunanza, Valentina, Carbone, Emilio, and Fagioli, F.
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neuronal cells ,amniotic fluid ,Stem cells - Published
- 2007
8. Musculoskeletal and injuries 3
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Mehlum, I. S., primary, Kristensen, P., additional, Wergeland, E., additional, Kjuus, H., additional, Bonzin, M., additional, Palmer, K. T., additional, Inskip, H. M., additional, Coggon, D., additional, Madan, I., additional, Reading, I., additional, Coggon, D. C., additional, Lucas, M., additional, Wellman, H. M., additional, Leamon, T. B., additional, Tuyet, B. T. T., additional, Nguyen, B. D., additional, Kriebel, D. K., additional, Wegman, D. H., additional, Mattioli, S., additional, De Fazio, R., additional, Buiatti, E., additional, Truffelli, D., additional, Zanardi, F., additional, Miglietta, B., additional, Curti, S., additional, Baldasseroni, A., additional, Tassinari, G., additional, and Violante, F. S., additional more...
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- 2007
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9. Social Media Devices’ Influence on User Neck Pain during the COVID-19 Pandemic: Collaborating Vertebral-GLCM Extracted Features with a Decision Tree
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Bassam Al-Naami, Bashar E. A. Badr, Yahia Z. Rawash, Hamza Abu Owida, Roberto De Fazio, Paolo Visconti, Al-Naami, B., Badr, B., Rawash, Y., Abu Owida, H., De Fazio, R., and Visconti, P.
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Social media usage, smartphones, neck pain, GLCM, decision tree algorithm ,Radiology, Nuclear Medicine and imaging ,Computer Vision and Pattern Recognition ,Electrical and Electronic Engineering ,social media usage ,smartphones ,neck pain ,GLCM ,decision tree algorithm ,Computer Graphics and Computer-Aided Design - Abstract
The prevalence of neck pain, a chronic musculoskeletal disease, has significantly increased due to the uncontrollable use of social media (SM) devices. The use of SM devices by younger generations increased enormously during the COVID-19 pandemic, being—in some cases—the only possibility for maintaining interpersonal, social, and friendship relationships. This study aimed to predict the occurrence of neck pain and its correlation with the intensive use of SM devices. It is based on nine quantitative parameters extracted from the retrospective X-ray images. The three parameters related to angle_1 (i.e., the angle between the global horizontal and the vector pointing from C7 vertebra to the occipito-cervical joint), angle_2 (i.e., the angle between the global horizontal and the vector pointing from C1 vertebra to the occipito-cervical joint), and the area between them were measured from the shape of the neck vertebrae, while the rest of the parameters were extracted from the images using the gray-level co-occurrence matrix (GLCM). In addition, the users’ ages and the duration of the SM usage (H.mean) were also considered. The decision tree (DT) machine-learning algorithm was employed to predict the abnormal cases (painful subjects) against the normal ones (no pain). The results showed that angle_1, area, and the image contrast significantly increased statistically with the time of SM-device usage, precisely in the range of 2 to 9 h. The DT showed a promising result demonstrated by classification accuracy and F1-scores of 94% and 0.95, respectively. Our findings confirmed that the objectively detected parameters, which elucidate the negative impacts of SM-device usage on neck pain, can be predicted by DT machine learning. more...
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- 2023
10. Wearable Sensors and Smart Devices to Monitor Rehabilitation Parameters and Sports Performance: An Overview
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Roberto De Fazio, Vincenzo Mariano Mastronardi, Massimo De Vittorio, Paolo Visconti, De Fazio, R., Mastronardi, V. M., De Vittorio, M., and Visconti, P.
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Advanced diagnostics, bio-vital markers, e-healthcare, injury-prevention, mini-invasive monitoring, rehabilitation parameters, sports performance tracking, wearable sensors ,Electrical and Electronic Engineering ,Biochemistry ,Instrumentation ,Atomic and Molecular Physics, and Optics ,Analytical Chemistry - Abstract
A quantitative evaluation of kinetic parameters, the joint’s range of motion, heart rate, and breathing rate, can be employed in sports performance tracking and rehabilitation monitoring following injuries or surgical operations. However, many of the current detection systems are expensive and designed for clinical use, requiring the presence of a physician and medical staff to assist users in the device’s positioning and measurements. The goal of wearable sensors is to overcome the limitations of current devices, enabling the acquisition of a user’s vital signs directly from the body in an accurate and non–invasive way. In sports activities, wearable sensors allow athletes to monitor performance and body movements objectively, going beyond the coach’s subjective evaluation limits. The main goal of this review paper is to provide a comprehensive overview of wearable technologies and sensing systems to detect and monitor the physiological parameters of patients during post–operative rehabilitation and athletes’ training, and to present evidence that supports the efficacy of this technology for healthcare applications. First, a classification of the human physiological parameters acquired from the human body by sensors attached to sensitive skin locations or worn as a part of garments is introduced, carrying important feedback on the user’s health status. Then, a detailed description of the electromechanical transduction mechanisms allows a comparison of the technologies used in wearable applications to monitor sports and rehabilitation activities. This paves the way for an analysis of wearable technologies, providing a comprehensive comparison of the current state of the art of available sensors and systems. Comparative and statistical analyses are provided to point out useful insights for defining the best technologies and solutions for monitoring body movements. Lastly, the presented review is compared with similar ones reported in the literature to highlight its strengths and novelties. more...
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- 2023
11. Human-Machine Interaction through advanced haptic sensors: a piezoelectric sensory glove with edge machine learning for gesture and object recognition
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Roberto De Fazio, Vincenzo Mariano Mastronardi, Matteo Petruzzi, Massimo De Vittorio, Paolo Visconti, De Fazio, R., Petruzzi, M., Mastronardi, V. M., De Vittorio, M., and Visconti, P.
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haptic interfaces, human–machine interfaces, virtual reality, tactile feedback, sensors, actuators, virtual interaction model ,Computer Networks and Communications ,haptic interfaces ,human–machine interfaces ,virtual reality ,tactile feedback ,sensors ,actuators ,virtual interaction model - Abstract
Human–machine interaction (HMI) refers to systems enabling communication between machines and humans. Systems for human–machine interfaces have advanced significantly in terms of materials, device design, and production methods. Energy supply units, logic circuits, sensors, and data storage units must be flexible, stretchable, undetectable, biocompatible, and self-healing to act as human–machine interfaces. This paper discusses the technologies for providing different haptic feedback of different natures. Notably, the physiological mechanisms behind touch perception are reported, along with a classification of the main haptic interfaces. Afterward, a comprehensive overview of wearable haptic interfaces is presented, comparing them in terms of cost, the number of integrated actuators and sensors, their main haptic feedback typology, and their future application. Additionally, a review of sensing systems that use haptic feedback technologies—specifically, smart gloves—is given by going through their fundamental technological specifications and key design requirements. Furthermore, useful insights related to the design of the next-generation HMI devices are reported. Lastly, a novel smart glove based on thin and conformable AlN (aluminum nitride) piezoelectric sensors is demonstrated. Specifically, the device acquires and processes the signal from the piezo sensors to classify performed gestures through an onboard machine learning (ML) algorithm. Then, the design and testing of the electronic conditioning section of AlN-based sensors integrated into the smart glove are shown. Finally, the architecture of a wearable visual-tactile recognition system is presented, combining visual data acquired by a micro-camera mounted on the user’s glass with the haptic ones provided by the piezoelectric sensors. more...
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- 2023
12. Innovative complete solution for health safety of children unintentionally forgotten in a car: a smart Arduino‐based system with user app for remote control
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Donato Cafagna, Roberto de Fazio, Paolo Visconti, P. Costantini, Simone Miccoli, Visconti, P., de Fazio, R., Costantini, P., Miccoli, S., and Cafagna, D.
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Short Message Service ,Computer science ,Real-time computing ,02 engineering and technology ,Software application ,01 natural sciences ,law.invention ,Data acquisition ,law ,Arduino-based solution ,Arduino ,0103 physical sciences ,0202 electrical engineering, electronic engineering, information engineering ,Electrical and Electronic Engineering ,Sensor ,010302 applied physics ,Measurement ,business.industry ,Remote control ,020208 electrical & electronic engineering ,Atomic and Molecular Physics, and Optics ,Microcontroller ,Electrical testing ,Transmission (telecommunications) ,Health safety system ,Control system ,Global Positioning System ,business - Abstract
This study describes an innovative complete car control system against children abandonment in unattended vehicles. Even if systems of this kind are already available in the automotive market, other solutions are currently object of intense researches by several important Research and Development centres or under patent procedure. In this study, a description of the technologies already adopted in the currently used car control systems and in those that are in research and testing phase too is provided. Then, it will be introduced to the proposed control system, which enables to improve all the described systems by providing innovative technologies and functionalities. The proposed system implements a microwave motion sensor, two infrared sensors, a carbon dioxide sensor, a temperature/humidity sensor, a vocal detector and a micro-camera. These acquisition devices are connected to a microcontroller board that is able to combine all acquired data for detecting the alarm scenario and consequently acting some warning procedures: alarm short message service transmission with vehicle Global Positioning System position, vehicle's horn activation and/or car windows lowering. Thanks to such a wide set of sensors, the system can correlate the acquired information in order to ensure a good detection capability in every condition in which it can operate. more...
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- 2020
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13. IoT-oriented software platform applied to sensors-based farming facility with smartphone farmer app
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Paolo Visconti, R. de Fazio, S. Strazzella, Nicola Ivan Giannoccaro, Donato Cafagna, Visconti, P., Giannoccaro, I., de Fazio, R., Strazzella, S., and Cafagna, D.
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0209 industrial biotechnology ,Control and Optimization ,Computer Networks and Communications ,Computer science ,Greenhouse ,02 engineering and technology ,Agricultural engineering ,law.invention ,020901 industrial engineering & automation ,Software ,law ,Sustainable agriculture ,0202 electrical engineering, electronic engineering, information engineering ,Computer Science (miscellaneous) ,Wireless ,Wireless sensor Network ,Electrical and Electronic Engineering ,Instrumentation ,IoT device ,business.industry ,Solar-powered sensor node ,Data processing ,Precise Farming ,Work (electrical) ,Cloud software platform ,Hardware and Architecture ,Control and Systems Engineering ,020201 artificial intelligence & image processing ,IoT devices ,business ,Wireless sensor network ,Cropping ,Remote control ,Information Systems - Abstract
This work describes the design of innovative IoT-oriented farm management system that employs low-cost WSN for detecting soil, environmental and crops parameters that properly processed, in combination with weather forecasts, are used to determine future farming activities based on agronomic models implemented in the software platform. Goals of carried out research activity are to guarantee production both qualitatively and quantitatively of cultivated crops, to increase company income and reduce environmental impacts; achieving these objectives is a prerequisite for implementing of sustainable agriculture. Connection between traditional cropping systems and innovative technologies is achieved through the utilization of low-cost wireless electronic modules for acquiring data from connected sensors. The fertigation system operation is supported by solar-powered low-cost WSN capable of constantly monitoring soil and environmental parameters; thanks to sensor nodes properly positioned in cultivated land or greenhouse, interest parameters of both air and soil are detected and transmitted to on-cloud database, to allow monitoring and remote control from enabled users (farmer or agronomist). For this aim, an application specifically realized and tested during the different fertigation system’s functional tests, allows users to visualize and eventually remotely intervene by using a smart-phone or tablet. more...
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- 2020
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14. Light-Induced ignition of Carbon Nanotubes and energetic nano-materials: a review on methods and advanced technical solutions for nanoparticles-enriched fuels combustion
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Antonio Ficarella, Antonio Paolo Carlucci, Paolo Visconti, Roberto de Fazio, Luciano Strafella, Patrizio Primiceri, Visconti, P., Primiceri, P., de Fazio, R., Strafella, L., Ficarella, Antonio, and Carlucci, A. P. more...
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nano-particles ,laser-plug ,Technology ,Materials science ,020209 energy ,Nanoparticle ,light ignition ,Nanotechnology ,02 engineering and technology ,Carbon nanotube ,TP1-1185 ,Combustion ,Nanomaterials ,law.invention ,law ,internal combustion engine ,0202 electrical engineering, electronic engineering, information engineering ,General Materials Science ,Chemical technology ,021001 nanoscience & nanotechnology ,Condensed Matter Physics ,Ignition system ,Light ignition, Nano-particles, Laser-plug, Light absorption, Internal combustion engine ,Internal combustion engine ,light absorption ,Light induced ,0210 nano-technology ,Porous medium - Abstract
Aim of the present manuscript is to provide an overview of all possible methods and light source typologies used by the different research groups for obtaining the energetic nano-materials’ photo-ignition, showing the latest progress related to such phenomenon employing, also, alternative radiation sources to the common Xe lamp. In fact, the employment of a different source typology can open new usage prospects respect to those enabled by the Xe lamp, mainly due to its technological limitations. Therefore, several studies are faced to test light sources, such as lasers and LEDs, for igniting the nano-energetic materials (as CNTs mixed with metallic catalyzers, Al / CuO nano-particles, etc); these nano-materials are usefully employed for starting, in volumetric and controlled way, the combustion of air-fuel mixtures inside internal combustion engines, leading to significant benefits to the combustion process also in terms of efficiency, reliability, and emissions of pollutants. Several research works are presented in literature concerning the ignition of liquid / gaseous fuels, without nano-particles, employing laser sources (i.e laser-based plugs in place of the common spark plugs); therefore, an innovative solution is proposed that employs multi-point laser-plugs for inducing the ignition of nano-materials dispersed into the air-fuel mixture inside the cylinder, so further improving the combustion of the fuel in an internal combustion engine. more...
- Published
- 2020
15. Wearable sensing smart solutions for workers' remote control in health-risk activities
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Paolo Visconti, Roberto de Fazio, Ramiro Velazquez, Bassam Al-Naami, Amir Aminzadeh Ghavifekr, University of Tabriz (Iran), de Fazio, R., Al-Naami, B., Velazquez, R., Ghavifekr, A. A., and Visconti, P. more...
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Wearable device, Energy harvesting, Microcontrollers, Sensors, Cloud applications - Abstract
This paper presents a smart garment to monitor the environmental parameters and user’s vital signs; the wearable application is meant to monitor workers’ conditions in harsh workplaces. The smart jacket integrates a multisource harvesting section for gathering energy from sources associated with the human body (light, heat, movements), guaranteeing the energy autonomy of the sensing unit. This last relies on a custom microcontroller board to acquire and process biophysical and environmental data from several sensors distributed on the garment. Also, it wirelessly sends the acquired data towards the IBM Cloud platform, allowing remote monitoring of worker’s conditions, real-time anomalies detection, and decentralized storing of acquired data. The tests indicated that the harvesting section could provide up to 217 mW mean power, fully covering the energy requirements of the sensing unit in all tested scenarios. However, the 380 mAh LiPo battery, charged by the harvesting system, allows the device about 16 days lifetime when no further energy contribution is available. more...
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- 2022
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16. Self-powered WiFi-connected monitoring stations for environmental pollution app-based control in urban and industrial areas
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Paolo Visconti, Roberto de Fazio, Ramiro Velazquez, Bassam Al-Naami, Amir Aminzadeh Ghavifekr, University of Tabriz (Iran), de Fazio, R., Al-Naami, B., Ghavifekr, A. A., Velazquez, R., and Visconti, P. more...
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Pollution monitoring, Energy harvesting, Microcontroller, Sensors, Cloud applications - Abstract
This paper presents the design of a sensing device for monitoring and storing the atmospheric and noise pollution data, using technology with zero impact on the environment. The system consists of an eco-friendly sensor pitch equipped with a multi-sources harvesting system used to scavenge energy from renewable sources (wind and solar light), making it suitable to be accumulated into a storage device. The harvested energy is used to feed a sensing section, which samples the environmental parameters (i.e. PM2.5, PM10, NH3, CO2, NO2, CO) at regular intervals. The hardware and firmware development of the sensor node is discussed; this last is based on the Arduino Pro Micro microcontroller board, which acquires, processes and stores the data from sensors and manages their transmissions towards the cloud platform. Finally, the test results of the developed sensor pitch are presented, demonstrating the correct operation of all system sections. more...
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- 2022
17. Explainabilty Comparison between Random Forests and Neural Networks—Case Study of Amino Acid Volume Prediction
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Roberta De Fazio, Rosy Di Giovannantonio, Emanuele Bellini, Stefano Marrone, De Fazio, R., Di Giovannantonio, R., Bellini, E., and Marrone, S.
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random forest ,multi-layer perceptron ,explainable AI ,protein data bank ,neural network ,machine learning ,Information Systems - Abstract
As explainability seems to be the driver for a wiser adoption of Artificial Intelligence in healthcare and in critical applications, in general, a comprehensive study of this field is far from being completed. On one hand, a final definition and theoretical measurements of explainability have not been assessed, yet, on the other hand, some tools and frameworks for the practical evaluation of this feature are now present. This paper aims to present a concrete experience in using some of these explainability-related techniques in the problem of predicting the size of amino acids in real-world protein structures. In particular, the feature importance calculation embedded in Random Forest (RF) training is compared with the results of the Eli-5 tool applied to the Neural Network (NN) model. Both the predictors are trained on the same dataset, which is extracted from Protein Data Bank (PDB), considering 446 myoglobins structures and process it with several tools to implement a geometrical model and perform analyses on it. The comparison between the two models draws different conclusions about the residues’ geometry and their biological properties. more...
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- 2022
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18. An Overview of Wearable Piezoresistive and Inertial Sensors for Respiration Rate Monitoring
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Paolo Visconti, Marco Stabile, Massimo De Vittorio, Ramiro Velazquez, Roberto de Fazio, de Fazio, R., Stabile, M., De Vittorio, M., Velazquez, R., and Visconti, P.
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inertial sensor ,TK7800-8360 ,Computer Networks and Communications ,Computer science ,internet of thing ,Real-time computing ,Wearable computer ,Transduction (psychology) ,Accelerometer ,biophysical parameters ,law.invention ,wearable devices ,law ,Inertial measurement unit ,biophysical parameter ,respiration rate ,Electrical and Electronic Engineering ,Sports activity ,Wearable technology ,piezoresistive sensors ,business.industry ,Gyroscope ,Piezoresistive effect ,inertial sensors ,internet of things ,piezoresistive sensor ,Hardware and Architecture ,Control and Systems Engineering ,Signal Processing ,Respiration rate ,Electronics ,business - Abstract
The demand for wearable devices to measure respiratory activity is constantly growing, finding applications in a wide range of scenarios (e.g., clinical environments and workplaces, outdoors for monitoring sports activities, etc.). Particularly, the respiration rate (RR) is a vital parameter since it indicates serious illness (e.g., pneumonia, emphysema, pulmonary embolism, etc.). Therefore, several solutions have been presented in the scientific literature and on the market to make RR monitoring simple, accurate, reliable and noninvasive. Among the different transduction methods, the piezoresistive and inertial ones satisfactorily meet the requirements for smart wearable devices since unobtrusive, lightweight and easy to integrate. Hence, this review paper focuses on innovative wearable devices, detection strategies and algorithms that exploit piezoresistive or inertial sensors to monitor the breathing parameters. At first, this paper presents a comprehensive overview of innovative piezoresistive wearable devices for measuring user’s respiratory variables. Later, a survey of novel piezoresistive textiles to develop wearable devices for detecting breathing movements is reported. Afterwards, the state-of-art about wearable devices to monitor the respiratory parameters, based on inertial sensors (i.e., accelerometers and gyroscopes), is presented for detecting dysfunctions or pathologies in a non-invasive and accurate way. In this field, several processing tools are employed to extract the respiratory parameters from inertial data; therefore, an overview of algorithms and methods to determine the respiratory rate from acceleration data is provided. Finally, comparative analysis for all the covered topics are reported, providing useful insights to develop the next generation of wearable sensors for monitoring respiratory parameters. more...
- Published
- 2021
19. FPGA based technical solutions for high throughput data processing and encryption for 5G communication: A review
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Paolo Visconti, R. de Fazio, Ramiro Velazquez, Carolina Del-Valle Soto, Visconti, P., Velazquez, R., del-Valle-Soto, C., and de Fazio, R.
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Field Programmable Gate Array, 5G communication, Xilinx ZCU102, High-Speed Processing, Advanced Encryption Standard ,Radio access network ,Signal processing ,Advanced encryption standard ,business.industry ,Computer science ,Advanced Encryption Standard ,Field programmable gate array ,Cloud computing ,MPSoC ,Encryption ,Xilinx ZCU102 ,Parallel processing (DSP implementation) ,Embedded system ,5G communication ,Electrical and Electronic Engineering ,High-speed processing ,business ,Field-programmable gate array - Abstract
The field programmable gate array (FPGA) devices are ideal solutions for high-speed processing applications, given their flexibility, parallel processing capability, and power efficiency. In this review paper, at first, an overview of the key applications of FPGA-based platforms in 5G networks/systems is presented, exploiting the improved performances offered by such devices. FPGA-based implementations of cloud radio access network (C-RAN) accelerators, network function virtualization (NFV)-based network slicers, cognitive radio systems, and multiple input multiple output (MIMO) channel characterizers are the main considered applications that can benefit from the high processing rate, power efficiency and flexibility of FPGAs. Furthermore, the implementations of encryption/decryption algorithms by employing the Xilinx Zynq Ultrascale+MPSoC ZCU102 FPGA platform are discussed, and then we introduce our high-speed and lightweight implementation of the wellknown AES-128 algorithm, developed on the same FPGA platform, and comparing it with similar solutions already published in the literature. The comparison results indicate that our AES-128 implementation enables efficient hardware usage for a given data-rate (up to 28.16 Gbit/s), resulting in higher efficiency (8.64 Mbps/slice) than other considered solutions. Finally, the applications of the ZCU102 platform for high-speed processing are explored, such as image and signal processing, visual recognition, and hardware resource management. more...
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- 2021
20. An overview of technologies and devices against COVID-19 pandemic diffusion: virus detection and monitoring solutions
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Paolo Visconti, A. Sponziello, R. de Fazio, Donato Cafagna, Ramiro Velazquez, de Fazio, R., Sponziello, A., Cafagna, D., Velazquez, R., and Visconti, P.
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2019-20 coronavirus outbreak ,IoT frameworks ,Coronavirus disease 2019 (COVID-19) ,Pandemic ,Computer science ,SARS-CoV-2 ,lcsh:T ,Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) ,Virology ,lcsh:Technology ,Virus detection ,RT-PCR assay ,Control and Systems Engineering ,lcsh:Technology (General) ,SARS-CoV-2, Pandemic, Tracking devices, RT-PCR assay, Magnetic biosensors, IoT frameworks, Spike protein, Antibodies, Remote monitoring systems ,lcsh:T1-995 ,Magnetic biosensors ,Electrical and Electronic Engineering ,Diffusion (business) ,Tracking devices - Abstract
The year 2020 will remain in the history for the diffusion of the COVID-19 virus, originating a pandemic on a world scale with over a million deaths. From the onset of the pandemic, the scientific community has made numerous efforts to design systems to detect the infected subjects in ever-faster times, allowing both to intervene on them, to avoid dangerous complications, and to contain the pandemic spreading. In this paper, we present an overview of different innovative technologies and devices fielded against the SARS-CoV-2 virus. The various technologies applicable to the rapid and reliable detection of the COVID-19 virus have been explored. Specifically, several magnetic, electrochemical, and plasmonic biosensors have been proposed in the scientific literature, as an alternative to nucleic acid-based real-time reverse transcription Polymerase Chain Reaction (PCR) (RT-qPCR) assays, overcoming the limitations featuring this typology of tests (the need for expensive instruments and reagents, as well as of specialized staff, and their reliability). Furthermore, we investigated the IoT solutions and devices, reported on the market and in the scientific literature, to contain the pandemic spreading, by avoiding the contagion, acquiring the parameters of suspected users, and monitoring them during the quarantine period. more...
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- 2021
21. A Survey on Ageing Mechanisms in II and III-Generation PV Modules: Accurate Matrix-Method Based Energy Prediction Through Short-Term Performance Measures
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P. Visconti, R. de Fazio, D. Cafagna, R. Velazquez, A. Lay-Ekuakille, Visconti, P., de Fazio, R., Cafagna, D., Velazquez, R., and Lay-Ekuakille, A.
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Photovoltaic panels, energy prediction, sensors, maximum power point tracker, measurement system - Abstract
Solar energy utilization has been triggered by advances in new technology to reduce the cost of photovoltaic (PV) panels with an increase of efficiency. To improve the energy production quality, it is necessary to undergo the PV panels to characterization both in the indoor and outdoor scenarios; these latter characterizations generally require all seasons-based measurements. Therefore, it is essential to find models for characterizing PV panels in terms of energy production but also production and operating mode tolerance. The paper illustrates the findings of global research dedicated to PV panels ageing and their impact on energy production in the years. At first, an in-depth analysis of the ageing mechanisms affecting II and III generations' PV panels has been presented when exposed to atmospheric agents. Afterwards, the PV panels' characterization, conducted in a short time (i.e. a total of seven days), has been reported, performing outdoor measurements in conjunction with an electronic calibrator able to measure currents and voltages. The MPPT (Maximum Power Point Tracker) device is the core instrumentation of the employed measurement system. Obtained results are convincing since they have been compared with simultaneous measurements of PV panels located in the same place. more...
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- 2021
22. Sensors-based Mobile Robot for Harsh Environments: Functionalities, Energy Consumption Analysis and Characterization
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Roberto de Fazio, Aimè Lay Ekuakille, Ramiro Velazquez, Simon Kidiamboko, Miguel Joseph Ferreira, Nicola Ivan Giannoccaro, Paolo Visconti, Dany Mpoi Katamba, De Fazio, R., Katamba, D. M., Lay Ekuakille, A., Ferreira, M. J., Kidiamboko, S., Giannoccaro, N. I., Velazquez, R., and Visconti, P. more...
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business.industry ,Computer science ,Mechanical Engineering ,Embedded system ,Mobile robot ,Energy consumption ,Electrical and Electronic Engineering ,business ,Instrumentation ,mobile robots, photovoltaic system, electronic control, energy consumption measurements, sensors, instrumentation, autonomous vehicles ,Characterization (materials science) - Abstract
Mobile robots, especially, mini-robots and mini-rovers are playing an important role in different industrial applications. Under certain constraints, they are mostly suitable for harsh environments where hard conditions take place such as to be unfit for the protracted human activity, or even where this latter is not allowed. In many circumstances, the energy issues for autonomous and wheeled mobile robots need to be optimized taking into account the mechanical and electrical consumptions. The paper illustrates the design of a semi-custom wheeled mobile robot with integrated a photovoltaic (PV) system on the roof, namely a high-efficiency mono- or poly-crystalline PV panel, for supporting the Li-Ion batteries during particular tasks (rough terrain, obstacles or paths with steep slopes), in order to extend the robot autonomy. An electronic control has been designed and data acquisitions, related to power consumption, have been performed by means of a specific experimental setup. The robot was used for detecting different parameters such as temperature, humidity, concentrations of toxic gas species, and presence of flames, therefore particularly suitable for contaminated environments or industrial plants. For this aim, the mobile robot has been equipped with a wide range of commercial sensors and a Global Positioning System (GPS) receiver for keeping track of the robotic vehicle position. In addition, the robot is equipped with a HC-06 Bluetooth transceiver for sending the acquired data to the developed IoTool smartphone application where they are displayed to be analyzed by the user, and for receiving commands and instructions. more...
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- 2021
23. A stake-out prototype system based on GNSS-RTK technology for implementing accurate vehicle reliability and performance tests
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Paolo Visconti, Nicola Ivan Giannoccaro, Francesco Iaia, Roberto de Fazio, Visconti, P., Iaia, F., de Fazio, R., and Giannoccaro, I.
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Technology ,Control and Optimization ,ISO 3888-1 test preparation ,Computer science ,Energy Engineering and Power Technology ,Track (rail transport) ,Software ,Position (vector) ,Range (aeronautics) ,Electrical and Electronic Engineering ,UTM projection mode ,MATLAB ,Engineering (miscellaneous) ,Simulation ,Reliability (statistics) ,computer.programming_language ,GNSS-RTK technology ,sensor-based stake-out system ,centimeter positioning accuracy ,software user application ,Renewable Energy, Sustainability and the Environment ,business.industry ,GNSS-RTK technology, sensor-based stake-out system, centimetre positioning accuracy, software user application, UTM projection mode, ISO 3888-1 test preparation ,Geolocation ,GNSS applications ,business ,computer ,Energy (miscellaneous) - Abstract
There are many car tests regulated by European and international standards and carried out on tracks to assess vehicle performance. The test preparation phase usually consists of placing road cones on the track with a specific configuration defined by the considered standard; this phase is performed by human operators using imprecise and slow methods, mainly due to the large required distances. In this paper, a new geolocation stake-out system based on GNSS RTK technology was realized and tested, supported by a Matlab-based software application to allow the user to quickly and precisely locate the on-track points on which to position the road cones. The realized stake-out system, innovative and very simple to use, produced negligible average errors (i.e., 2.4–2.9 cm) on the distance between the staked-out points according to the reference standards (distance percentage error 0.29–0.47%). Furthermore, the measured average angular error was also found to be very low, in the range 0.04–0.18°. Finally, ISO 3888-1 and ISO 3888-2 test configurations were reproduced on the proving ground of the Porsche Technical Center by utilizing the realized stake-out system to perform a double lane-change maneuver on car prototypes. more...
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- 2021
24. High-performance AES-128 algorithm implementation by FPGA-based SoC for 5G communications
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Ramiro Velazquez, Paolo Visconti, Stefano Capoccia, Roberto de Fazio, Visconti, P., Velazquez, R., Capoccia, S., and de Fazio, R.
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Advanced encryption standard ,General Computer Science ,business.industry ,Network packet ,Cycles per instruction ,Computer science ,Advanced Encryption Standard ,Field programmable gate array ,5G communications ,Encryption ,Synchronization ,VHDL ,Advanced Encryption Standard, Field Programmable Gate Array, 5G communications, Xilinx ZCU102 platform, VHDL ,Xilinx ZCU102 platform ,Electrical and Electronic Engineering ,Hardware_ARITHMETICANDLOGICSTRUCTURES ,business ,Field-programmable gate array ,Throughput (business) ,Algorithm ,computer ,computer.programming_language - Abstract
In this research work, a fast and lightweight AES-128 cypher based on the Xilinx ZCU102 FPGA board is presented, suitable for 5G communications. In particular, both encryption and decryption algorithms have been developed using a pipelined approach, so enabling the simultaneous processing of the rounds on multiple data packets at each clock cycle. Both the encryption and decryption systems support an operative frequency up to 220 MHz, reaching 28.16 Gbit/s maximum data throughput; besides, the encryption and decryption phases last both only ten clock periods. To guarantee the interoperability of the developed encryption/decryption system with the other sections of the 5G communication apparatus, synchronization and control signals have been integrated. The encryption system uses only 1631 CLBs, whereas the decryption one only 3464 CLBs, ascribable, mainly, to the Inverse Mix Columns step. The developed cypher shows higher efficiency (8.63 Mbps/slice) than similar solutions present in literature. more...
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- 2021
25. Solar-Powered Deep Learning-Based Recognition System of Daily Used Objects and Human Faces for Assistance of the Visually Impaired
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Paolo Visconti, Nicola Ivan Giannoccaro, Carolina Del-Valle-Soto, Ramiro Velazquez, Bernardo Calabrese, Roberto de Fazio, Calabrese, B., Velázquez, R., del-Valle-Soto, C., De Fazio, R., Giannoccaro, N. I., and Visconti, P. more...
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Control and Optimization ,convolutional neural networks (CNN) ,Computer science ,mobile computing ,Mobile computing ,Energy Engineering and Power Technology ,Wearable computer ,Image processing ,Context (language use) ,02 engineering and technology ,01 natural sciences ,Convolutional neural network ,lcsh:Technology ,object recognition ,assistive technology, convolutional neural networks (CNN), deep learning, faster R-CNN, mobile computing, object recognition, person recognition, wearable system ,assistive technology ,0202 electrical engineering, electronic engineering, information engineering ,Computer vision ,Electrical and Electronic Engineering ,Engineering (miscellaneous) ,deep learning ,faster R-CNN ,person recognition ,wearable system ,Renewable Energy, Sustainability and the Environment ,business.industry ,lcsh:T ,Deep learning ,010401 analytical chemistry ,Cognitive neuroscience of visual object recognition ,Process (computing) ,Object (computer science) ,0104 chemical sciences ,020201 artificial intelligence & image processing ,Artificial intelligence ,business ,Energy (miscellaneous) - Abstract
This paper introduces a novel low-cost solar-powered wearable assistive technology (AT) device, whose aim is to provide continuous, real-time object recognition to ease the finding of the objects for visually impaired (VI) people in daily life. The system consists of three major components: a miniature low-cost camera, a system on module (SoM) computing unit, and an ultrasonic sensor. The first is worn on the user’s eyeglasses and acquires real-time video of the nearby space. The second is worn as a belt and runs deep learning-based methods and spatial algorithms which process the video coming from the camera performing objects’ detection and recognition. The third assists on positioning the objects found in the surrounding space. The developed device provides audible descriptive sentences as feedback to the user involving the objects recognized and their position referenced to the user gaze. After a proper power consumption analysis, a wearable solar harvesting system, integrated with the developed AT device, has been designed and tested to extend the energy autonomy in the different operating modes and scenarios. Experimental results obtained with the developed low-cost AT device have demonstrated an accurate and reliable real-time object identification with an 86% correct recognition rate and 215 ms average time interval (in case of high-speed SoM operating mode) for the image processing. The proposed system is capable of recognizing the 91 objects offered by the Microsoft Common Objects in Context (COCO) dataset plus several custom objects and human faces. In addition, a simple and scalable methodology for using image datasets and training of Convolutional Neural Networks (CNNs) is introduced to add objects to the system and increase its repertory. It is also demonstrated that comprehensive trainings involving 100 images per targeted object achieve 89% recognition rates, while fast trainings with only 12 images achieve acceptable recognition rates of 55%. more...
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- 2020
26. A Prosthetic Limb Managed by Sensors-Based Electronic System: Experimental Results on Amputees
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F. Gaetani, G. A. Zappatore, R. de Fazio, Paolo Visconti, Gaetani, F., De Fazio, R., Zappatore, G. A., and Visconti, P.
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0209 industrial biotechnology ,Control and Optimization ,Computer Networks and Communications ,Computer science ,System testing ,Cloud computing ,02 engineering and technology ,Myoelectric signals ,01 natural sciences ,law.invention ,020901 industrial engineering & automation ,Touchscreen ,Software ,Prosthetic limb ,law ,Inertial measurement unit ,Arduino ,Sensors and electronic boards ,Computer Science (miscellaneous) ,Gestures recognition algorithm, Myoelectric signals, Prosthetic limb, Sensors and electronic boards, Signals acquisition and processing, System testing, Wireless connectivity ,Electrical and Electronic Engineering ,Instrumentation ,Signals acquisition and processing ,Simulation ,business.industry ,010401 analytical chemistry ,Wireless connectivity ,0104 chemical sciences ,Hardware and Architecture ,Control and Systems Engineering ,Transceiver ,business ,Information Systems ,Gesture ,Gestures recognition algorithm - Abstract
Taking the advantages offered by smart high-performance electronic devices, transradial prosthesis for upper-limb amputees was developed and tested. It is equipped with sensing devices and actuators allowing hand movements; myoelectric signals are detected by Myo armband with 8 ElectroMyoGraphic (EMG) electrodes, a 9-axis Inertial Measurement Unit (IMU) and Bluetooth Low Energy (BLE) module. All data are received through HM-11 BLE transceiver by Arduino board which processes them and drives actuators. Raspberry Pi board controls a touchscreen display, providing user a feedback related to prosthesis functioning and sends EMG and IMU data, gathered via the armband, to cloud platform thus allowing orthopedic during rehabilitation period, to monitor users’ improvements in real time. A GUI software integrating a machine learning algorithm was implemented for recognizing flexion/extension/rest gestures of user fingers. The algorithm performances were tested on 9 male subjects (8 able-bodied and 1 subject affected by upper-limb amelia), demonstrating high accuracy and fast responses. more...
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- 2020
27. Limitations and Characterization of Energy Storage Devices for Harvesting Applications
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Paolo Visconti, Roberto de Fazio, Giorgio Marcuccio, Donato Cafagna, de Fazio, R., Cafagna, D., Marcuccio, G., and Visconti, Paolo
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energy harvesting ,storage devices ,super-capacitors ,LiPo batteries ,self-discharge ,Control and Optimization ,Materials science ,Energy Engineering and Power Technology ,02 engineering and technology ,Internal resistance ,lcsh:Technology ,Energy storage ,Automotive engineering ,Reduction (complexity) ,LiPo batterie ,0202 electrical engineering, electronic engineering, information engineering ,Storage device ,Electrical and Electronic Engineering ,Engineering (miscellaneous) ,Super-capacitor ,Renewable Energy, Sustainability and the Environment ,Open-circuit voltage ,lcsh:T ,Energy harvesting ,020208 electrical & electronic engineering ,Time constant ,Self-discharge ,021001 nanoscience & nanotechnology ,lipo batteries ,0210 nano-technology ,Voltage drop ,Energy (miscellaneous) - Abstract
This paper aims to study the limitations and performances of the main energy storage devices commonly used in energy harvesting applications, namely super-capacitors (SC) and lithium polymer (LiPo) batteries. The self-discharge phenomenon is the main limitation to the employment of SCs to store energy for a long time, thus reducing efficiency and autonomy of the energy harvesting system. Therefore, the analysis of self-discharge trends was carried out for three different models of commercial SCs, describing the phenomenon in terms of self-discharge rate and internal resistance. In addition, physical interpretations concerning the self-discharge mechanism based on the experimental data are provided, thus explaining the two super-imposed phenomena featured by distinct time constants. Afterwards, the dependence of self-discharge phenomenon from the charging time duration (namely, SCs charged at 5 V and then kept under charge for one or five hours) was analyzed; by comparing the voltage drop during the self-discharge process, a self-discharge reduction for longer charging durations was obtained and the physical interpretation provided (at best −6.8% after 24 h and −13.4% after 120 h). Finally, self-discharge trends of two commercial 380 mAh LiPo batteries (model LW 752035) were acquired and analyzed; the obtained results show an open circuit voltage reduction of only 0.59% in the first 24 h and just 1.43% after 124 h. more...
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- 2020
28. Development of a Self-Powered Piezo-Resistive Smart Insole Equipped with Low-Power BLE Connectivity for Remote Gait Monitoring
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Paolo Visconti, Ramiro Velazquez, Roberto de Fazio, Elisa Perrone, Massimo De Vittorio, de Fazio, R., Perrone, E., Velazquez, R., De Vittorio, M., and Visconti, P.
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Smart insole ,Computer science ,Walking ,TP1-1185 ,02 engineering and technology ,Smart material ,01 natural sciences ,Biochemistry ,Multiplexer ,Article ,Analytical Chemistry ,Electric Power Supplies ,Gait (human) ,health monitoring ,Arduino ,Low-power electronics ,Electrical and Electronic Engineering ,Gait ,Instrumentation ,Resistive touchscreen ,business.industry ,Chemical technology ,010401 analytical chemistry ,Electrical engineering ,plantar pressure distribution ,021001 nanoscience & nanotechnology ,Pressure sensor ,Piezoresistive effect ,Atomic and Molecular Physics, and Optics ,Shoes ,0104 chemical sciences ,BLE ,smart insole ,piezoresistivity ,Gait Analysis ,0210 nano-technology ,business - Abstract
The evolution of low power electronics and the availability of new smart materials are opening new frontiers to develop wearable systems for medical applications, lifestyle monitoring, and performance detection. This paper presents the development and realization of a novel smart insole for monitoring the plantar pressure distribution and gait parameters, indeed, it includes a piezoresistive sensing matrix based on a Velostat layer for transducing applied pressure into an electric signal. At first, an accurate and complete characterization of Velostat-based pressure sensors is reported as a function of sizes, support material, and pressure trend. The realization and testing of a low-cost and reliable piezoresistive sensing matrix based on a sandwich structure are discussed. This last is interfaced with a low power conditioning and processing section based on an Arduino Lilypad board and an analog multiplexer for acquiring the pressure data. The insole includes a 3-axis capacitive accelerometer for detecting the gait parameters (swing time and stance phase time) featuring the walking. A Bluetooth Low Energy (BLE) 5.0 module is included for transmitting in real-time the acquired data toward a PC, tablet or smartphone, for displaying and processing them using a custom Processing® application. Moreover, the smart insole is equipped with a piezoelectric harvesting section for scavenging energy from walking. The onfield tests indicate that for a walking speed higher than 1 ms−1, the device’s power requirements (i.e., ) was fulfilled. However, more than 9 days of autonomy are guaranteed by the integrated 380-mAh Lipo battery in the total absence of energy contributions from the harvesting section. more...
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- 2021
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29. A Multi-Source Harvesting System Applied to Sensor-Based Smart Garments for Monitoring Workers’ Bio-Physical Parameters in Harsh Environments
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Alessandro Minerba, Roberto de Fazio, Paolo Visconti, Donato Cafagna, Giorgio Marcuccio, de Fazio, R., Cafagna, D., Marcuccio, G., Minerba, A., and Visconti, P.
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energy harvesting ,Wearable device. Microcontroller, Energy harvesting, Piezoelectric harvester, Thermo-electric generator, Flexible solar panel ,Control and Optimization ,thermo-electric generator ,Maximum power principle ,Computer science ,Energy Engineering and Power Technology ,Wearable computer ,wearable device ,02 engineering and technology ,computer.software_genre ,lcsh:Technology ,01 natural sciences ,Automotive engineering ,microcontroller ,piezoelectric harvester ,flexible solar panel ,ComputerApplications_MISCELLANEOUS ,Cloud database ,Electrical and Electronic Engineering ,Engineering (miscellaneous) ,lcsh:T ,Renewable Energy, Sustainability and the Environment ,Firmware ,010401 analytical chemistry ,021001 nanoscience & nanotechnology ,0104 chemical sciences ,Microcontroller ,ComputingMethodologies_PATTERNRECOGNITION ,0210 nano-technology ,Energy harvesting ,computer ,Energy (miscellaneous) - Abstract
This paper describes the development and characterization of a smart garment for monitoring the environmental and biophysical parameters of the user wearing it; the wearable application is focused on the control to workers’ conditions in dangerous workplaces in order to prevent or reduce the consequences of accidents. The smart jacket includes flexible solar panels, thermoelectric generators and flexible piezoelectric harvesters to scavenge energy from the human body, thus ensuring the energy autonomy of the employed sensors and electronic boards. The hardware and firmware optimization allowed the correct interfacing of the heart rate and SpO2 sensor, accelerometers, temperature and electrochemical gas sensors with a modified Arduino Pro mini board. The latter stores and processes the sensor data and, in the event of abnormal parameters, sends an alarm to a cloud database, allowing company managers to check them via a web app. The characterization of the harvesting subsection has shown that ≈ 265 mW maximum power can be obtained in a real scenario, whereas the power consumption due to the acquisition, processing and BLE data transmission functions determined that a 10 mAh/day charge is required to ensure the device’s proper operation. By charging a 380 mAh Lipo battery in a few hours by means of the harvesting system, an energy autonomy of 23 days was obtained, in the absence of any further energy contribution. more...
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- 2020
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30. Sensors-based treatment system of the organic waste with RFID identification and on-cloud traceability
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Raffaella Striani, Francesca Ferrari, Luca Catarinucci, P. Pastore, A. Fornaro, M. Caiazzo, Francesco P. Chietera, R. de Fazio, L. Abruzzese, Riccardo Colella, O. Ivtchenko, Eugenio Venere, Paolo Visconti, M. Pucciarelli, C. Esposito Corcione, Antonio Greco, Ilaria Sergi, Luigi Patrono, Vincenzo Mighali, Workshop Chair Prof.ssa De Venuto, D. (Politecnico di Bari and INFN, Italy), de Fazio, R., Esposito Corcione, C., Greco, A., Ferrari, F., Striani, R., Catarinucci, L., Chietera, FRANCESCO PAOLO, Colella, R., Patrono, L., Mighali, Vincenzo, Sergi, Ilaria, Visconti, Paolo, Venere, E., Pucciarelli, M., Caiazzo, M., Pastore, P., Ivtchenko, O., Abruzzese, L., and Fornaro, A. more...
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Treatment system ,Traceability ,business.industry ,Computer science ,Supply chain ,010401 analytical chemistry ,020206 networking & telecommunications ,Cloud computing ,02 engineering and technology ,Biodegradable waste ,Arduino board, analog and digital sensors, sensors data acquisition ,01 natural sciences ,0104 chemical sciences ,Software ,Arduino ,Waste material ,material caracterization ,0202 electrical engineering, electronic engineering, information engineering ,Systems engineering ,UHF RFID traceability ,Radio-frequency identification ,business - Abstract
Aim of the present manuscript is to summarize the multi-disciplinary activities related to the research project called POIROT that proposes to design a platform for transforming the organic waste into an inert, odorless and sanitized material, employable for building applications or as thermal acoustic insulator. The platform prototype is equipped with Arduino-based electronic sensing stations for characterizing the material during the different steps of the transformation process. Further innovation introduced by the proposed system is the integration of the platform with a RFID (radio frequency identification)-based user-recognition and products traceability system, allowing both to identify the enabled users and to track the produced panels/bricks along the whole supply chain. Therefore, a proper software on-cloud application was developed for supporting the products’ traceability functionality. more...
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- 2019
31. Quasi-real time acquisition and processing for biomedical IR and conventional imaging in surgery applications
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Aime Lay-Ekuakille, Paolo Visconti, R. de Fazio, D. Veneziano, Lay-Ekuakille, A., Visconti, P., de Fazio, R., and Veneziano, D.
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Computer science ,Real-time computing ,methods and algorithms, computer-aided diagnosi [Medical-image reconstruction] ,computer-aided software ,Instrumentation ,Mathematical Physics ,Quasi real time - Abstract
Surgery decision making is almost basically adopted by imaging, and for internal organs, imaging is the only tool for proceeding on. Interested imaging is obtained by as Xrays, CT (Computer Tomography), MRI (Magnetic Resonance Imaging), NMR (Nuclear Magnetic Resonance), ultrasound, scintigraphy, and PET (Positron Emission Tomography). All the above techniques are correlated to specific instrumentation, and their manufacturers include dedicated software to output high quality images. However, despite advances in biomedical instrumentation technology, new issues, regarding insurgence of pathologies so far unknown, require as much techniques to be developed. In this spirit, infrared thermography, for instance, can ride to help us to solve this thorny issue. Infrared images have been used to discriminate interested organs with respect to tissues and adherences that must be taken in consideration for continuing and optimizing the surgery process. Modified linear and circular Hough transform have been used to process captured images. This paper illustrates findings related to quasi-real time acquisition and processing during surgery. Infrared processing has been compared to another technique based on atomic force microscopy-based algorithm. Hough technique is also treated. more...
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- 2019
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32. Design and testing of an electronic control system based on STM X-Nucleo board for detection and wireless transmission of sensors data applied to a single-seat Formula SAE car
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P. Visconti, B. Sbarro, P. Primiceri, R. de Fazio, A. Lay-Ekuakille, Visconti, P., Sbarro, B., Primiceri, P., de Fazio, R., and Lay-Ekuakille, A.
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Telemetry, sensors, wireless monitoring, data communication, firmware, electronic modules - Abstract
The emerged potentials and opportunities in the electronics field, which facilitate the creation of complex projects with innovative functionalities and high performances, while maintaining low costs, are becoming even more appreciated by designers, engineers and users. In this research work, a telemetry system was realized in order to monitor and control the principal physical and mechanical parameters of a racing vehicle by employing devices, available on the market, at very low cost. The used STM32 Nucleo development board, heart of realized telemetry system, properly programmed with the developed firmware, acquires data from sensors installed on vehicle and, by means of a WiFi module, sends them to a base station. A CAN module interfaces the engine control unit with the Nucleo board, allowing to control the engine parameters by proper sensors. All detected sensors data are both sent wirelessly and stored on a SD memory card for avoiding data losses and to implement a system robust and reliable. Experimental results show that all received data from base station are in accordance between themselves, reporting vehicle parameters for different driving and track conditions. more...
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- 2019
33. Development and Characterization of a White LED-based spectrophotometer for UV/VIS gaseous pollutants detection employing Michelson interferometer and an optical filtering system
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R. de Fazio, Paolo Visconti, Patrizio Primiceri, Aime Lay-Ekuakille, Visconti, P., Primiceri, P., de Fazio, R., and Lay-Ekuakille, A.
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Led-Based Spectrophotometer, sensors, experimetal apparaturs, mesurements, electronic design, gaseous pollutants detection, Michelson interferometer, optical filtering system ,Analyte ,Materials science ,business.industry ,010401 analytical chemistry ,Control unit ,Michelson interferometer ,010501 environmental sciences ,01 natural sciences ,0104 chemical sciences ,law.invention ,Coherence length ,Optics ,law ,Light beam ,Luminous efficacy ,business ,Absorption (electromagnetic radiation) ,Optical filter ,Instrumentation ,0105 earth and related environmental sciences - Abstract
Aim of this paper is the design of an absorption spectrophotometer based on LED technology presenting several advantages such as high luminous efficiency, reliability, long operating duration, low maintenance and low power consumption besides the reduction of analyte temperature variations which occur if Xenon light source is used. An optical filtering system was realized to detect analyte absorption for each wavelength range selected by proper optical filters; also to characterize filtered light beam in terms of its coherence length, thus correlating measured absorption spectrum with light source characteristics, the Michelson interferometer was used. Realized white LED-based spectrophotometer can be used to monitor air quality in hospital rooms or to detect atmospheric pollution deriving from vehicular traffic and different typology of pollutants (e.g., heavy metals deriving by industrial activities). A PC-interfaced control unit acquires and processes raw data provided by sensors (pressure, temperature, humidity, luminosity) and manages the optical filtering system motion by actuating a stepper motor. Whole system operation was tested and obtained results confirm the proper functioning and correct interaction, through PC terminal, between user and control unit. more...
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- 2018
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34. Improved Photo-Ignition of Carbon Nanotubes/Ferrocene Using a Lipophilic Porphyrin under White Power LED Irradiation
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Paolo Visconti, Patrizio Primiceri, Roberto de Fazio, Selma Mazzetto, Giuseppe Mele, Antonio Carlucci, Visconti, P., Primiceri, P., de Fazio, R., Carlucci, A. P., Mazzetto, S. E., and Mele, G.
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Materials science ,Analytical chemistry ,chemistry.chemical_element ,metal nanoparticle ignitors ,02 engineering and technology ,Carbon nanotube ,multiwalled carbon nanotubes ,lcsh:Technology ,01 natural sciences ,ferrocene ,LED source ,photo-induced ignition ,porphyrin ,Article ,law.invention ,chemistry.chemical_compound ,Xenon ,law ,General Materials Science ,Irradiation ,lcsh:Microscopy ,lcsh:QC120-168.85 ,lcsh:QH201-278.5 ,lcsh:T ,010405 organic chemistry ,Pulse duration ,021001 nanoscience & nanotechnology ,Porphyrin ,0104 chemical sciences ,Photoexcitation ,Ignition system ,Minimum ignition energy ,chemistry ,lcsh:TA1-2040 ,Multi-walled carbon nanotubes, Ferrocene, Metal nano-particle ignitors, LED source, Photo-induced ignition, Porphyrin, Measurements, Experimental setup, Electronic driving boards ,lcsh:Descriptive and experimental mechanics ,lcsh:Electrical engineering. Electronics. Nuclear engineering ,lcsh:Engineering (General). Civil engineering (General) ,0210 nano-technology ,lcsh:TK1-9971 - Abstract
The aim of this work is to investigate and characterize the photo-ignition process of dry multi-walled carbon nanotubes (MWCNTs) mixed with ferrocene (FeCp2) powder, using an LED (light-emitting diode) as the light source, a combination that has never been used, to the best of our knowledge. The ignition process was improved by adding a lipophilic porphyrin (H2Pp) in powder to the MWCNTs/FeCp2 mixtures—thus, a lower ignition threshold was obtained. The ignition tests were carried out by employing a continuous emission and a pulsed white LED in two test campaigns. In the first, two MWCNT typologies, high purity (HP) and industrial grade (IG), were used without porphyrin, obtaining, for both, similar ignition thresholds. Furthermore, comparing ignition thresholds obtained with the LED source with those previously obtained with a Xenon (Xe) lamp, a significant reduction was observed. In the second test campaign, ignition tests were carried out by means of a properly driven and controlled pulsed XHP70 LED source. The minimum ignition energy (MIE) of IG-MWCNTs/FeCp2 samples was determined by varying the duration of the light pulse. Experimental results show that ignition is obtained with a pulse duration of 110 ms and a MIE density of 266 mJ/cm2. The significant reduction of the MIE value (10–40%), observed when H2Pp in powder form was added to the MWCNTs/FeCp2 mixtures, was ascribed to the improved photoexcitation and charge transfer properties of the lipophilic porphyrin molecules. more...
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- 2018
35. Occupational lifting tasks and retinal detachment in non-myopics and myopics: extended analysis of a case-control study
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Andrea Farioli, Rocco De Fazio, Roberta Bonfiglioli, Robin M. T. Cooke, Francesco Saverio Violante, Stefano Mattioli, Francesca Zanardi, Stefania Curti, DIPARTIMENTO DI SCIENZE MEDICHE E CHIRURGICHE, Facolta' di MEDICINA e CHIRURGIA, Mattioli S., Curti S., De Fazio R., Cooke R.M.T., Zanardi F., Bonfiglioli R., Farioli A., and Violante F.S. more...
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Intraocular pressure ,medicine.medical_specialty ,Selected Papers from International Conference: International Conference on New Occupational Diseases ,Socio-culturale ,Logistic regression ,LIFTING ,Economica ,RETINAL DETACHMENT ,OCCUPATIONAL EXPOSURE ,OCCUPATIONAL DISEASES ,CASE-CONTROL STUDIES ,Ophthalmology ,medicine ,Risk factor ,Safety, Risk, Reliability and Quality ,Chemical Health and Safety ,business.industry ,lcsh:Public aspects of medicine ,Public Health, Environmental and Occupational Health ,Retinal detachment ,lcsh:RA1-1270 ,Odds ratio ,medicine.disease ,Confidence interval ,Population study ,Original Article ,business ,Safety Research ,Body mass index - Abstract
none 8 Objectives: Lifting heavy weights involves the Valsalva manoeuvre, which leads to intraocular pressure spikes. We used data from a case-control study to further investigate the hypothesis that occupational lifting is a risk factor for retinal detachment. Methods: The study population included 48 cases (patients operated for retinal detachment) and 84 controls (outpatients attending an eye clinic). The odds ratios (OR) of idiopathic retinal detachment were estimated with a logistic regression model (adjusted for age, sex and body mass index). Three indexes were used to examine exposure to lifting; 1) maximum load lifted, 2) average weekly lifting, 3) lifelong cumulative lifting. Results: For all indexes, the most exposed subjects showed an increased risk of retinal detachment compared with the unexposed (index 1: OR 3.57, 95% confidence interval [CI] 1.21-10.48; index 2: OR 3.24, 95% CI 1.32-7.97; index 3: OR 2.23, 95% CI 1.27-8.74) and dose-response relationships were apparent. Conclusion: These results reinforce the hypothesis that heavy occupational lifting may be a relevant risk factor for retinal detachment. Mattioli S.; Curti S.; De Fazio R.; Cooke R.M.T.; Zanardi F.; Bonfiglioli R.; Farioli A.; Violante F.S. Mattioli S.; Curti S.; De Fazio R.; Cooke R.M.T.; Zanardi F.; Bonfiglioli R.; Farioli A.; Violante F.S. more...
- Published
- 2012
36. MEMS-based Micro-scale Wind Turbines as Energy Harvesters of the Convective Airflows in Microelectronic Circuits
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Varona, J., Fazio, R., Velazquez, R., Giannoccaro, N., Miguel Carrasco, Visconti, P., Varona, J., De Fazio, R., Velázquez, R., Giannoccaro, N. I., Carrasco, M., and Visconti, P.
- Subjects
Energy harvesting, micro-electro-mechanical system (MEMS), micro-turbine, silicon-based fabrication process - Abstract
As an alternative to conventional batteries and other energy scavenging techniques, this paper introduces the idea of using micro-turbines to extract energy from wind forces at the microscale level and to supply power to battery-less microsystems. Fundamental research efforts on the design, fabrication, and test of micro-turbines with blade lengths of just 160 μm are presented in this paper along with analytical models and preliminary experimental results. The proof-of-concept prototypes presented herein were fabricated using a standard polysilicon surface micro-machining silicon technology (PolyMUMPs) and could effectively transform the kinetic energy of the available wind into a torque that might drive an electric generator or directly power supply a micro-mechanical system. Since conventional batteries do not scale-down well to the microscale, wind micro-turbines have the potential for becoming a practical alternative power source for microsystems, as well as for extending the operating range of devices running on batteries. more...
37. Innovative Driver Monitoring Systems and On-Board-Vehicle Devices in a Smart-Road Scenario Based on the Internet of Vehicle Paradigm: A Literature and Commercial Solutions Overview.
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Visconti P, Rausa G, Del-Valle-Soto C, Velázquez R, Cafagna D, and De Fazio R
- Abstract
In recent years, the growing number of vehicles on the road have exacerbated issues related to safety and traffic congestion. However, the advent of the Internet of Vehicles (IoV) holds the potential to transform mobility, enhance traffic management and safety, and create smarter, more interconnected road networks. This paper addresses key road safety concerns, focusing on driver condition detection, vehicle monitoring, and traffic and road management. Specifically, various models proposed in the literature for monitoring the driver's health and detecting anomalies, drowsiness, and impairment due to alcohol consumption are illustrated. The paper describes vehicle condition monitoring architectures, including diagnostic solutions for identifying anomalies, malfunctions, and instability while driving on slippery or wet roads. It also covers systems for classifying driving style, as well as tire and emissions monitoring. Moreover, the paper provides a detailed overview of the proposed traffic monitoring and management solutions, along with systems for monitoring road and environmental conditions, including the sensors used and the Machine Learning (ML) algorithms implemented. Finally, this review also presents an overview of innovative commercial solutions, illustrating advanced devices for driver monitoring, vehicle condition assessment, and traffic and road management. more...
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- 2025
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38. Detection of Antimicrobial Proteins/Peptides and Bacterial Proteins Involved in Antimicrobial Resistance in Raw Cow's Milk from Different Breeds.
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Piras C, De Fazio R, Di Francesco A, Oppedisano F, Spina AA, Cunsolo V, Roncada P, Cramer R, and Britti D
- Abstract
Proteins involved in antibiotic resistance (resistome) and with antimicrobial activity are present in biological specimens. This study aims to explore the presence and abundance of antimicrobial peptides (AMPs) and resistome proteins in bovine milk from diverse breeds and from intensive (Pezzata rossa, Bruna alpina, and Frisona) and non-intensive farming (Podolica breeds). Liquid atmospheric pressure matrix-assisted laser desorption/ionization (LAP-MALDI) mass spectrometry (MS) profiling, bottom-up proteomics, and metaproteomics were used to comprehensively analyze milk samples from various bovine breeds in order to identify and characterize AMPs and to investigate resistome proteins. LAP-MALDI MS coupled with linear discriminant analysis (LDA) machine learning was employed as a rapid classification method for Podolica milk recognition against the milk of other bovine species. The results of the LAP-MALDI MS analysis of milk coupled with the linear discriminant analysis (LDA) demonstrate the potential of distinguishing between Podolica and control milk samples based on MS profiles. The classification accuracy achieved in the training set is 86% while it reaches 98.4% in the test set. Bottom-up proteomics revealed approximately 220 quantified bovine proteins (identified using the Bos taurus database), with cathelicidins and annexins exhibiting higher abundance levels in control cows (intensive farming breeds). On the other hand, the metaproteomics analysis highlighted the diversity within the milk's microbial ecosystem with interesting results that may reflect the diverse environmental variables. The bottom-up proteomics data analysis using the Comprehensive Antibiotic Resistance Database (CARD) revealed beta-lactamases and tetracycline resistance proteins in both control and Podolica milk samples, with no relevant breed-specific differences observed. more...
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- 2024
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39. Plants with Antimicrobial Activity against Escherichia coli , a Meta-Analysis for Green Veterinary Pharmacology Applications.
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De Fazio R, Oppedisano F, Caioni G, Tilocca B, Piras C, and Britti D
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Antimicrobial resistance (AMR) poses a critical global health threat, necessitating innovative strategies to combat infectious diseases. Plants and their extracts offer alternatives/support to traditional antibiotics, and their diverse phytocomplexes with antimicrobial properties can be exploited. The Mediterranean hosts a high number of biodiverse plant species known for their bioactive compounds. This study focuses on identifying plant species and phytochemical constituents with antimicrobial activity against Escherichia coli ( E. coli ). Utilizing a systematic literature review and meta-analysis approach, we screened 3037 entries, yielding 70 studies suitable for MIC (minimum inhibitory concentration) annotation. The results highlighted Lavandula spp., Plectranthus spp. and Lupinus jaimehintoniana as the most effective plants with average MICs of, respectively, 0.144 mg/mL, 0.260 mg/mL, and 0.140 mg/mL. These results might help to fight AMR via the discovery of complementary natural antimicrobial agents to support the development of green veterinary pharmacology. Further exploration of these resources promises valuable insights for future support to antimicrobial strategies. more...
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- 2024
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40. Deltamethrin's Effect on Nitrogen-Fixing Nodules in Medicago truncatula .
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De Fazio R, Piras C, and Britti D
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Deltamethrin is used against plant pests (e.g., mites and ants) and, in farm animals, against biting insects because of its acaricidal and repellent effects against ticks, thus protecting the sheep and cattle from the transmission of pathogens. However, its impact on the environment still needs to be fully evaluated. This study evaluates the impact of this pyrethroid on the nitrogen-fixing nodules in Medicago truncatula , a model legume. This research compares nodular biomass and root weight between a deltamethrin-treated section and an untreated control section of this legume. Our results indicate a significant reduction in the biomass of nitrogen-fixing nodules in the treated grove, suggesting that deltamethrin negatively affects the symbiotic relationship between M. truncatula and nitrogen-fixing bacteria. This reduction in nodule formation can impair soil fertility and plant growth, highlighting an ecological risk associated with pyrethroid's use in livestock farming. These findings underscore the need for a shift towards Green Veterinary Pharmacology (GVP), which promotes environmentally sustainable practices in managing livestock health. By minimizing our reliance on harmful chemical treatments, GVP offers viable solutions to protect and enhance ecosystem services such as biological nitrogen fixation that are essential for maintaining soil health and agricultural productivity. more...
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- 2024
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41. Automated Lung Cancer Diagnosis Applying Butterworth Filtering, Bi-Level Feature Extraction, and Sparce Convolutional Neural Network to Luna 16 CT Images.
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Gharaibeh NY, De Fazio R, Al-Naami B, Al-Hinnawi AR, and Visconti P
- Abstract
Accurate prognosis and diagnosis are crucial for selecting and planning lung cancer treatments. As a result of the rapid development of medical imaging technology, the use of computed tomography (CT) scans in pathology is becoming standard practice. An intricate interplay of requirements and obstacles characterizes computer-assisted diagnosis, which relies on the precise and effective analysis of pathology images. In recent years, pathology image analysis tasks such as tumor region identification, prognosis prediction, tumor microenvironment characterization, and metastasis detection have witnessed the considerable potential of artificial intelligence, especially deep learning techniques. In this context, an artificial intelligence (AI)-based methodology for lung cancer diagnosis is proposed in this research work. As a first processing step, filtering using the Butterworth smooth filter algorithm was applied to the input images from the LUNA 16 lung cancer dataset to remove noise without significantly degrading the image quality. Next, we performed the bi-level feature selection step using the Chaotic Crow Search Algorithm and Random Forest (CCSA-RF) approach to select features such as diameter, margin, spiculation, lobulation, subtlety, and malignancy. Next, the Feature Extraction step was performed using the Multi-space Image Reconstruction (MIR) method with Grey Level Co-occurrence Matrix (GLCM). Next, the Lung Tumor Severity Classification (LTSC) was implemented by using the Sparse Convolutional Neural Network (SCNN) approach with a Probabilistic Neural Network (PNN). The developed method can detect benign, normal, and malignant lung cancer images using the PNN algorithm, which reduces complexity and efficiently provides classification results. Performance parameters, namely accuracy, precision, F-score, sensitivity, and specificity, were determined to evaluate the effectiveness of the implemented hybrid method and compare it with other solutions already present in the literature. more...
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- 2024
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42. Machine Learning Algorithms for Processing and Classifying Unsegmented Phonocardiographic Signals: An Efficient Edge Computing Solution Suitable for Wearable Devices.
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De Fazio R, Spongano L, De Vittorio M, Patrono L, and Visconti P
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- Humans, Phonocardiography methods, Machine Learning, Signal Processing, Computer-Assisted, Algorithms, Neural Networks, Computer, Wearable Electronic Devices, Support Vector Machine
- Abstract
The phonocardiogram (PCG) can be used as an affordable way to monitor heart conditions. This study proposes the training and testing of several classifiers based on SVMs (support vector machines), k-NN (k-Nearest Neighbor), and NNs (neural networks) to perform binary ("Normal"/"Pathologic") and multiclass ("Normal", "CAD" (coronary artery disease), "MVP" (mitral valve prolapse), and "Benign" (benign murmurs)) classification of PCG signals, without heart sound segmentation algorithms. Two datasets of 482 and 826 PCG signals from the Physionet/CinC 2016 dataset are used to train the binary and multiclass classifiers, respectively. Each PCG signal is pre-processed, with spike removal, denoising, filtering, and normalization; afterward, it is divided into 5 s frames with a 1 s shift. Subsequently, a feature set is extracted from each frame to train and test the binary and multiclass classifiers. Concerning the binary classification, the trained classifiers yielded accuracies ranging from 92.4 to 98.7% on the test set, with memory occupations from 92.7 kB to 11.1 MB. Regarding the multiclass classification, the trained classifiers achieved accuracies spanning from 95.3 to 98.6% on the test set, occupying a memory portion from 233 kB to 14.1 MB. The NNs trained and tested in this work offer the best trade-off between performance and memory occupation, whereas the trained k-NN models obtained the best performance at the cost of large memory occupation (up to 14.1 MB). The classifiers' performance slightly depends on the signal quality, since a denoising step is performed during pre-processing. To this end, the signal-to-noise ratio (SNR) was acquired before and after the denoising, indicating an improvement between 15 and 30 dB. The trained and tested models occupy relatively little memory, enabling their implementation in resource-limited systems. more...
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- 2024
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43. Spectral Profiling (Fourier Transform Infrared Spectroscopy) and Machine Learning for the Recognition of Milk from Different Bovine Breeds.
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Spina AA, Ceniti C, De Fazio R, Oppedisano F, Palma E, Gugliandolo E, Crupi R, Raza SHA, Britti D, Piras C, and Morittu VM
- Abstract
The Podolica cattle breed is widespread in southern Italy, and its productivity is characterized by low yields and an extraordinary quality of milk and meats. Most of the milk produced is transformed into "Caciocavallo Podolico" cheese, which is made with 100% Podolica milk. Fourier Transform Infrared Spectroscopy (FTIR) is the technique that, in this research work, was applied together with machine learning to discriminate 100% Podolica milk from contamination of other Calabrian cattle breeds. The analysis on the test set produced a misclassification percentage of 6.7%. Among the 15 non-Podolica samples in the test set, 2 were misclassified and recognized as Podolica milk even though the milk was from other species. The correct classification rate improved to 100% when the same method was applied to the recognition of Podolica and Pezzata Rossa milk produced by the same farm. Furthermore, this technique was tested for the recognition of Podolica milk mixed with milk from other bovine species. The multivariate model and the respective confusion matrices obtained showed that all the 14 Podolica samples (test set) mixed with 40% non-Podolica milk were correctly classified. In addition, Pezzata Rossa milk produced by the same farm was detected as a contaminant in Podolica milk from the same farm down to concentrations as little as 5% with a 100% correct classification rate in the test set. The method described yielded higher accuracy values when applied to the discrimination of milks from different breeds belonging to the same farm. One of the reasons for this phenomenon could be linked to the elimination of the environmental variable. However, the results obtained in this work demonstrate the possibility of using FTIR to discriminate between milks from different breeds. more...
- Published
- 2024
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44. Mediterranean Plants with Antimicrobial Activity against Staphylococcus aureus , a Meta-Analysis for Green Veterinary Pharmacology Applications.
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Oppedisano F, De Fazio R, Gugliandolo E, Crupi R, Palma E, Abbas Raza SH, Tilocca B, Merola C, Piras C, and Britti D
- Abstract
Antimicrobial resistance (AMR) has emerged as a global health crisis, necessitating the search for innovative strategies to combat infectious diseases. The unique biodiversity of Italian flora offers a treasure trove of plant species and their associated phytochemicals, which hold immense potential as a solution to address AMR. By investigating the antimicrobial properties of Italian flora and their phytochemical constituents, this study aims to shed light on the potential of phyto-complexes as a valuable resource for developing novel or supportive antimicrobial agents useful for animal production. more...
- Published
- 2023
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45. IoT Solutions and AI-Based Frameworks for Masked-Face and Face Recognition to Fight the COVID-19 Pandemic.
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Al-Nabulsi J, Turab N, Owida HA, Al-Naami B, De Fazio R, and Visconti P
- Subjects
- Humans, Pandemics prevention & control, Algorithms, COVID-19, Facial Recognition, Internet of Things
- Abstract
A global health emergency resulted from the COVID-19 epidemic. Image recognition techniques are a useful tool for limiting the spread of the pandemic; indeed, the World Health Organization (WHO) recommends the use of face masks in public places as a form of protection against contagion. Hence, innovative systems and algorithms were deployed to rapidly screen a large number of people with faces covered by masks. In this article, we analyze the current state of research and future directions in algorithms and systems for masked-face recognition. First, the paper discusses the importance and applications of facial and face mask recognition, introducing the main approaches. Afterward, we review the recent facial recognition frameworks and systems based on Convolution Neural Networks, deep learning, machine learning, and MobilNet techniques. In detail, we analyze and critically discuss recent scientific works and systems which employ machine learning (ML) and deep learning tools for promptly recognizing masked faces. Also, Internet of Things (IoT)-based sensors, implementing ML and DL algorithms, were described to keep track of the number of persons donning face masks and notify the proper authorities. Afterward, the main challenges and open issues that should be solved in future studies and systems are discussed. Finally, comparative analysis and discussion are reported, providing useful insights for outlining the next generation of face recognition systems. more...
- Published
- 2023
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46. Wearable Sensors and Smart Devices to Monitor Rehabilitation Parameters and Sports Performance: An Overview.
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De Fazio R, Mastronardi VM, De Vittorio M, and Visconti P
- Subjects
- Humans, Health Status, Heart Rate, Kinetics, Athletes, Athletic Performance
- Abstract
A quantitative evaluation of kinetic parameters, the joint's range of motion, heart rate, and breathing rate, can be employed in sports performance tracking and rehabilitation monitoring following injuries or surgical operations. However, many of the current detection systems are expensive and designed for clinical use, requiring the presence of a physician and medical staff to assist users in the device's positioning and measurements. The goal of wearable sensors is to overcome the limitations of current devices, enabling the acquisition of a user's vital signs directly from the body in an accurate and non-invasive way. In sports activities, wearable sensors allow athletes to monitor performance and body movements objectively, going beyond the coach's subjective evaluation limits. The main goal of this review paper is to provide a comprehensive overview of wearable technologies and sensing systems to detect and monitor the physiological parameters of patients during post-operative rehabilitation and athletes' training, and to present evidence that supports the efficacy of this technology for healthcare applications. First, a classification of the human physiological parameters acquired from the human body by sensors attached to sensitive skin locations or worn as a part of garments is introduced, carrying important feedback on the user's health status. Then, a detailed description of the electromechanical transduction mechanisms allows a comparison of the technologies used in wearable applications to monitor sports and rehabilitation activities. This paves the way for an analysis of wearable technologies, providing a comprehensive comparison of the current state of the art of available sensors and systems. Comparative and statistical analyses are provided to point out useful insights for defining the best technologies and solutions for monitoring body movements. Lastly, the presented review is compared with similar ones reported in the literature to highlight its strengths and novelties. more...
- Published
- 2023
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47. Social Media Devices' Influence on User Neck Pain during the COVID-19 Pandemic: Collaborating Vertebral-GLCM Extracted Features with a Decision Tree.
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Al-Naami B, Badr BEA, Rawash YZ, Owida HA, De Fazio R, and Visconti P
- Abstract
The prevalence of neck pain, a chronic musculoskeletal disease, has significantly increased due to the uncontrollable use of social media (SM) devices. The use of SM devices by younger generations increased enormously during the COVID-19 pandemic, being-in some cases-the only possibility for maintaining interpersonal, social, and friendship relationships. This study aimed to predict the occurrence of neck pain and its correlation with the intensive use of SM devices. It is based on nine quantitative parameters extracted from the retrospective X-ray images. The three parameters related to angle_1 (i.e., the angle between the global horizontal and the vector pointing from C7 vertebra to the occipito-cervical joint), angle_2 (i.e., the angle between the global horizontal and the vector pointing from C1 vertebra to the occipito-cervical joint), and the area between them were measured from the shape of the neck vertebrae, while the rest of the parameters were extracted from the images using the gray-level co-occurrence matrix (GLCM). In addition, the users' ages and the duration of the SM usage (H.mean) were also considered. The decision tree (DT) machine-learning algorithm was employed to predict the abnormal cases (painful subjects) against the normal ones (no pain). The results showed that angle_1, area, and the image contrast significantly increased statistically with the time of SM-device usage, precisely in the range of 2 to 9 h. The DT showed a promising result demonstrated by classification accuracy and F1-scores of 94% and 0.95, respectively. Our findings confirmed that the objectively detected parameters, which elucidate the negative impacts of SM-device usage on neck pain, can be predicted by DT machine learning. more...
- Published
- 2023
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48. A Differential Inertial Wearable Device for Breathing Parameter Detection: Hardware and Firmware Development, Experimental Characterization.
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De Fazio R, Greco MR, De Vittorio M, and Visconti P
- Subjects
- Humans, Respiration, Respiratory Rate, Exhalation, Wearable Electronic Devices, Sleep Apnea Syndromes
- Abstract
Breathing monitoring is crucial for evaluating a patient's health status. The technologies commonly used to monitor respiration are costly, bulky, obtrusive, and inaccurate, mainly when the user moves. Consequently, efforts have been devoted to providing new solutions and methodologies to overcome these limitations. These methods have several uses, including healthcare monitoring, measuring athletic performance, and aiding patients with respiratory diseases, such as COPD (chronic obtrusive pulmonary disease), sleep apnea, etc. Breathing-induced chest movements can be measured noninvasively and discreetly using inertial sensors. This research work presents the development and testing of an inertia-based chest band for breathing monitoring through a differential approach. The device comprises two IMUs (inertial measurement units) placed on the patient's chest and back to determine the differential inertial signal, carrying out information detection about the breathing activity. The chest band includes a low-power microcontroller section to acquire inertial data from the two IMUs and process them to extract the breathing parameters (i.e., RR-respiration rate; TI/TE-inhalation/exhalation time; IER-inhalation-to-exhalation time; V-flow rate), using the back IMU as a reference. A BLE transceiver wirelessly transmits the acquired breathing parameters to a mobile application. Finally, the test results demonstrate the effectiveness of the used dual-inertia solution; correlation and Bland-Altman analyses were performed on the RR measurements from the chest band and the reference, demonstrating a high correlation (r¯ = 0.92) and low mean difference (MD¯ = -0.27 BrPM (breaths per minute)), limits of agreement (LoA¯ = +1.16/-1.75 BrPM), and mean absolute error (MAE¯ = 1.15%). Additionally, the experimental results demonstrated that the developed device correctly measured the other breathing parameters (TI, TE, IER, and V), keeping an MAE of ≤5%. The obtained results indicated that the developed chest band is a viable solution for long-term breathing monitoring, both in stationary and moving users. more...
- Published
- 2022
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49. Methodologies and Wearable Devices to Monitor Biophysical Parameters Related to Sleep Dysfunctions: An Overview.
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De Fazio R, Mattei V, Al-Naami B, De Vittorio M, and Visconti P
- Abstract
Sleep is crucial for human health from metabolic, mental, emotional, and social points of view; obtaining good sleep in terms of quality and duration is fundamental for maintaining a good life quality. Over the years, several systems have been proposed in the scientific literature and on the market to derive metrics used to quantify sleep quality as well as detect sleep disturbances and disorders. In this field, wearable systems have an important role in the discreet, accurate, and long-term detection of biophysical markers useful to determine sleep quality. This paper presents the current state-of-the-art wearable systems and software tools for sleep staging and detecting sleep disorders and dysfunctions. At first, the paper discusses sleep's functions and the importance of monitoring sleep to detect eventual sleep disturbance and disorders. Afterward, an overview of prototype and commercial headband-like wearable devices to monitor sleep is presented, both reported in the scientific literature and on the market, allowing unobtrusive and accurate detection of sleep quality markers. Furthermore, a survey of scientific works related the effect of the COVID-19 pandemic on sleep functions, attributable to both infection and lifestyle changes. In addition, a survey of algorithms for sleep staging and detecting sleep disorders is introduced based on an analysis of single or multiple biosignals (EEG-electroencephalography, ECG-electrocardiography, EMG-electromyography, EOG-electrooculography, etc.). Lastly, comparative analyses and insights are provided to determine the future trends related to sleep monitoring systems. more...
- Published
- 2022
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50. Sensors Allocation and Observer Design for Discrete Bilateral Teleoperation Systems with Multi-Rate Sampling.
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Ghavifekr AA, De Fazio R, Velazquez R, and Visconti P
- Abstract
This study addresses sensor allocation by analyzing exponential stability for discrete-time teleoperation systems. Previous studies mostly concentrate on the continuous-time teleoperation systems and neglect the management of significant practical phenomena, such as data-swap, the effect of sampling rates of samplers, and refresh rates of actuators on the system's stability. A multi-rate sampling approach is proposed in this study, given the isolation of the master and slave robots in teleoperation systems which may have different hardware restrictions. This architecture collects data through numerous sensors with various sampling rates, assuming that a continuous-time controller stabilizes a linear teleoperation system. The aim is to assign each position and velocity signals to sensors with different sampling rates and divide the state vector between sensors to guarantee the stability of the resulting multi-rate sampled-data teleoperation system. Sufficient Krasovskii-based conditions will be provided to preserve the exponential stability of the system. This problem will be transformed into a mixed-integer program with LMIs (linear matrix inequalities). These conditions are also used to design the observers for the multi-rate teleoperation systems whose estimation errors converge exponentially to the origin. The results are validated by numerical simulations which are useful in designing sensor networks for teleoperation systems. more...
- Published
- 2022
- Full Text
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