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Systems for cardiorespiratory monitoring hold tremendous promise for many applications in clinical settings, harsh environments, sports science and telemonitoring. However, the translation in the real world is challenging because it is difficult to develop unobtrusive and comfortable systems with high metrological performance. Recent advances in fiber optic technology in the field of sensing and their application to instrument wearable systems can tackle the main issues in this field. In this work, we focused on the recent advances in cardiorespiratory monitoring of fiber Bragg grating (FBGs) sensors which are one of the most popular sensors based on fiber optic technology. We provide an overview of the FBGs working principle and performance. We also describe the most popular and promising configurations based on FBGs used for cardiorespiratory monitoring.

Workers experiencing high levels of stress may suffer from poor motivation, low level of attention, and physical disorders which, in turn, may lead to work injuries. Respiratory frequency (fR) is considered one of the most reliable indicators of the mental load and fatigue state of workers. Monitoring this parameter through wearable devices represents an efficient solution for the maintenance of Occupational Health and Safety. We developed an innovative wearable system equipped with flexible sensors based on fiber Bragg gratings (FBGs) to monitor fR in static and dynamic conditions characterizing occupational settings. This article provides a description of the system and of the metrological characteristics of the flexible sensors in terms of response to strain and temperature changes, and hysteresis error. The performances of the device, evaluated in a laboratory during the execution of tasks mimicking real work activity, are also reported. The obtained promising results encourage the engineering of the system for use in real workplaces to collect quantitative information on the psychophysical state of workers and its relation to stress level.

Temperature monitoring inside tissue undergoing minimally invasive thermal ablation is a primary goal to improve the clinical outcomes. Existing techniques for temperature measurements, classified as invasive or contactless, have limited clinical practice applications due to several practical issues. Fiber Bragg grating sensors (FBG) can be a valid solution since they can perform accurate and multi-point temperature measurements by inserting a single and small fiber optic within the tissue. Notwithstanding, their cross-sensitivity to strain may cause measurement errors during thermal procedures. Indeed, several organs (e.g., lungs, liver, pancreas) can strain gratings due to movements caused by breathing. To date, only a few studies have specifically addressed this concern, despite the wide use of FBGs in this field. To overcome this lack, we estimated the artefact of the FBGs output in response to lungs’ movements induced by breathing. This investigation was carried out by inserting FBGs within a manually ventilated lung model ( ex vivo swine lungs). We measured both the lungs’ movements during breathing by a Motion Capture system and the related fluctuations of the FBGs’ output. Moreover, we performed the same experiments during thermal ablation of lungs to assess the mentioned artefact’s influence. In this study, we demonstrated the relevance of the respiratory artefact on FBGs, and also the possibility to correct this error during thermal ablation.

Recent advances in understanding the importance of respiratory frequency ( ${ f}_{ R}$ ) as a sensitive marker of a variety of physiopathological stressors are fostering growing interest in respiratory monitoring. This interest is further stimulated by the ever-increasing efforts that companies are devoting to the development of systems measuring ${ f}_{ R}$ . There are a variety of techniques based on different sensors and technologies for ${ f}_{ R}$ monitoring. These techniques are commonly classified as contact-based or contactless, depending on whether the system which embeds the sensor is in contact with the body or not. This review is focused on the contactless methods for ${ f}_{ R}$ monitoring. We have introduced the main fields of use where contactless respiratory monitoring is important and provided a taxonomy to classify the most popular contactless techniques for ${ f}_{ R}$ monitoring. Finally, we have described the performances of the most popular methods, the main open challenges, and the main perspectives.

Recently, the ever-growing interest in the continuous monitoring of heart function in out-of-laboratory settings for an early diagnosis of cardiovascular diseases has led to the investigation of innovative methods for cardiac monitoring. Among others, wearables recording seismic waves induced on the chest surface by the mechanical activity of the heart are becoming popular. For what concerns wearable-based methods, cardiac vibrations can be recorded from the thorax in the form of acceleration, angular velocity, and/or displacement by means of accelerometers, gyroscopes, and fiber optic sensors, respectively. The present paper reviews the currently available wearables for measuring precordial vibrations. The focus is on sensor technology and signal processing techniques for the extraction of the parameters of interest. Lastly, the explored application scenarios and experimental protocols with the relative influencing factors are discussed for each technique. The goal is to delve into these three fundamental aspects (i.e., wearable system, signal processing, and application scenario), which are mutually interrelated, to give a holistic view of the whole process, beyond the sensor aspect alone. The reader can gain a more complete picture of this context without disregarding any of these 3 aspects.

In recent years, soft and flexible strain sensors have found application in wearable devices for monitoring human motion and physiological parameters. Conductive textile-based sensors are good candidates for developing these sensors. However, their robust electro-mechanical connection and susceptibility to environmental factors are still an open challenge to date. In this work, the manufacturing process of a silicone-textile composite resistive strain sensor based on a conductive resistive textile encapsulated into a dual-layer of silicone rubber is reported. In the working range typical of biomedical applications (up to 50%), the proposed flexible, skin-safe and moisture resistant strain sensor exhibited high sensitivity (gauge factor of −1.1), low hysteresis (maximum hysteresis error 3.2%) and ease of shaping in custom designs through a facile manufacturing process. To test the developed flexible sensor, two applicative scenarios covering the whole working range have been considered: the recording of the chest wall expansion during respiratory activity and the capture of the elbow flexion/extension movements.

Rotator cuff tears are a frequent cause of shoulder pain that often require arthroscopic repair. After surgery an intense and well-studied rehabilitation protocol is needed to obtain the complete recovery of shoulder function. Fifty patients, who sustained arthroscopic rotator cuff repair for symptomatic, atraumatic and full-thickness supraspinatus tendon tear, were involved. According to our rehabilitation protocol, during the first four postoperative weeks, the arm was supported with an abduction sling pillow, and pendulum exercises, table slide and active elbow extension and flexion were conceded. Outcome measures (Oxford shoulder score (OSS), simple shoulder test (SST), patient-reported satisfaction), shoulder function (range of motion (ROM) and muscle strength), and MRI examination were evaluated. The mean OSS score and SST score increased from 16 to 30.2 and from 5.3 to 11.4, respectively. Patient-reported satisfaction was 96%. At 12 months, patients improved ROM and muscle strength. Postoperative passive anterior elevation was 176, external rotation averaged 47, internal rotation was 90. Postoperative muscle strength during anterior elevation was 8.3 &plusmn, 2.2 kg, internal rotation 6.8 &plusmn, 3 kg, external rotation 5.5 &plusmn, 2.3 kg. Five out of seven patients with recurrent tears evaluated their results as satisfactory. They reported improvements in terms of OSS and SST mean scores despite recurrent tears, therefore, they did not undergo revision surgery. The delayed postoperative physical therapy protocol was associated with improvements in the outcome measures and shoulder function compared to the preoperatory state and rotator cuff healing demonstrated by MRI.

Heart rate (HR) and respiratory rate (fR) can be estimated by processing videos framing the upper body and face regions without any physical contact with the subject. This paper proposed a technique for continuously monitoring HR and fR via a multi-ROI approach based on the spectral analysis of RGB video frames recorded with a mobile device (i.e., a smartphone’s camera). The respiratory signal was estimated by the motion of the chest, whereas the cardiac signal was retrieved from the pulsatile activity at the level of right and left cheeks and forehead. Videos were recorded from 18 healthy volunteers in four sessions with different user-camera distances (i.e., 0.5 m and 1.0 m) and illumination conditions (i.e., natural and artificial light). For HR estimation, three approaches were investigated based on single or multi-ROI approaches. A commercially available multiparametric device was used to record reference respiratory signals and electrocardiogram (ECG). The results demonstrated that the multi-ROI approach outperforms the single-ROI approach providing temporal trends of both the vital parameters comparable to those provided by the reference, with a mean absolute error (MAE) consistently below 1 breaths·min−1 for fR in all the scenarios, and a MAE between 0.7 bpm and 6 bpm for HR estimation, whose values increase at higher distances.

The continuous monitoring of an individual's breathing can be an instrument for the assessment and enhancement of human wellness. Specific respiratory features are unique markers of the deterioration of a health condition, the onset of a disease, fatigue and stressful circumstances. The early and reliable prediction of high-risk situations can result in the implementation of appropriate intervention strategies that might be lifesaving. Hence, smart wearables for the monitoring of continuous breathing have recently been attracting the interest of many researchers and companies. However, most of the existing approaches do not provide comprehensive respiratory information. For this reason, a meta-learning algorithm based on LSTM neural networks for inferring the respiratory flow from a wearable system embedding FBG sensors and inertial units is herein proposed. Different conventional machine learning approaches were implemented as well to ultimately compare the results. The meta-learning algorithm turned out to be the most accurate in predicting respiratory flow when new subjects are considered. Furthermore, the LSTM model memory capability has been proven to be advantageous for capturing relevant aspects of the breathing pattern. The algorithms were tested under different conditions, both static and dynamic, and with more unobtrusive device configurations. The meta-learning results demonstrated that a short one-time calibration may provide subject-specific models which predict the respiratory flow with high accuracy, even when the number of sensors is reduced. Flow RMS errors on the test set ranged from 22.03 L/min, when the minimum number of sensors was considered, to 9.97 L/min for the complete setting (target flow range: 69.231 ± 21.477 L/min). The correlation coefficient r between the target and the predicted flow changed accordingly, being higher (r = 0.9) for the most comprehensive and heterogeneous wearable device configuration. Similar results were achieved even with simpler settings which included the thoracic sensors (r ranging from 0.84 to 0.88; test flow RMSE = 10.99 L/min, when exclusively using the thoracic FBGs). The further estimation of respiratory parameters, i.e., rate and volume, with low errors across different breathing behaviors and postures proved the potential of such approach. These findings lay the foundation for the implementation of reliable custom solutions and more sophisticated artificial intelligence-based algorithms for daily life health-related applications.

The devastating effects of global climate change on crop production and exponential population growth pose a major challenge to agricultural yields. To cope with this problem, crop performance monitoring is becoming increasingly necessary. In this scenario, the use of sensors and biosensors capable of detecting changes in plant fitness and predicting the evolution of their morphology and physiology has proven to be a useful strategy to increase crop yields. Flexible sensors and nanomaterials have inspired the emerging fields of wearable and on-plant portable devices that provide continuous and accurate long-term sensing of morphological, physiological, biochemical, and environmental parameters. This review provides an overview of novel plant sensing technologies by discussing wearable and integrated devices proposed for engineering plant and monitoring its morphological traits and physiological processes, as well as plant-environment interactions. For each application scenario, the state-of-the-art sensing solutions are grouped according to the plant organ on which they have been installed highlighting their main technological advantages and features. Finally, future opportunities, challenges and perspectives are discussed. We anticipate that the application of this technology in agriculture will provide more accurate measurements for farmers and plant scientists with the ability to track crop performance in real time. All of this information will be essential to enable rapid optimization of plants development through tailored treatments that improve overall plant health even under stressful conditions, with the ultimate goal of increasing crop productivity in a more sustainable manner.

Radiofrequency catheter ablation (RFCA) is the mainstream treatment for drug-refractory cardiac fibrillation. Multiple studies demonstrated that incorrect dosage of radiofrequency energy to the myocardium could lead to uncontrolled tissue damage or treatment failure, with the consequent need for unplanned reoperations. Monitoring tissue temperature during thermal therapy and predicting the extent of lesions may improve treatment efficacy. Cardiac computational modeling represents a viable tool for identifying optimal RFCA settings, though predictability issues still limit a widespread usage of such a technology in clinical scenarios. We aim to fill this gap by assessing the influence of the intrinsic myocardial microstructure on the thermo-electric behavior at the tissue level. By performing multi-point temperature measurements on

Low back pain represents a significant socioeconomic burden. Several nonsurgical medical treatments have been proposed for the treatment of this disabling condition. Epidural steroid injections (ESIs) are commonly used to treat lumbosacral radicular pain and to avoid surgery. Even though it is still not clear which type of conservative intervention is superior, several studies have proved that ESIs are able to increase patients’ quality of life, relieve lumbosacral radicular pain and finally, reduce or delay more invasive interventions, such as spinal surgery. The aim of this narrative review is to analyze the mechanism of action of ESIs in patients affected by low back pain and investigate their current application in treating this widespread pathology.

The measurement of physiological parameters is fundamental to assess the health status of an individual. The contactless monitoring of vital signs may provide benefits in various fields of application, from healthcare and clinical setting to occupational and sports scenarios. Recent research has been focused on the potentiality of camera-based systems working in the visible range (380–750 nm) for estimating vital signs by capturing subtle color changes or motions caused by physiological activities but invisible to human eyes. These quantities are typically extracted from videos framing some exposed body areas (e.g., face, torso, and hands) with adequate post-processing algorithms. In this review, we provided an overview of the physiological and technical aspects behind the estimation of vital signs like respiratory rate, heart rate, blood oxygen saturation, and blood pressure from digital images as well as the potential fields of application of these technologies. Per each vital sign, we provided the rationale for the measurement, a classification of the different techniques implemented for post-processing the original videos, and the main results obtained during various applications or in validation studies. The available evidence supports the premise of digital cameras as an unobtrusive and easy-to-use technology for physiological signs monitoring. Further research is needed to promote the advancements of the technology, allowing its application in a wide range of population and everyday life, fostering a biometrical holistic of the human body (BHOHB) approach.

Inappropriate posture and the presence of spinal disorders require specific monitoring systems. In clinical settings, posture evaluation is commonly performed with visual observation, electrogoniometers or motion capture systems (MoCaps). Developing a measurement system that can be easily used also in non-structured environments would be highly beneficial for accurate posture monitoring. This work proposes a system based on three magneto-inertial measurement units (MIMU), placed on the backs of seventeen volunteers on the T3, T12 and S1 vertebrae. The reference system used for validation is a stereophotogrammetric motion capture system. The volunteers performed forward bending and sit-to-stand tests. The measured variables for identifying the posture were the kyphosis and the lordosis angles, as well as the range of movement (ROM) of the body segments. The comparison between MIMU and MoCap provided a maximum RMSE of 5.6° for the kyphosis and the lordosis angles. The average lumbo-pelvic contribution during forward bending (41.8 ± 8.6%) and the average lumbar ROM during sit-to-stand (31.8 ± 9.8° for sitting down, 29.6 ± 7.6° for standing up) obtained with the MIMU system agree with the literature. In conclusion, the MIMU system, which is wearable, inexpensive and easy to set up in non-structured environments, has been demonstrated to be effective in posture evaluation.

Respiratory diseases are common in post-stroke hemiplegic patients and represent a major social problem as they worsen the quality of life and reduce the life span. As a consequence, being able to monitor respiratory parameters such as the respiratory rate (RR) and assess the presence of respiratory asynchronies could be of paramount importance to define hemiplegics’ health status. Moreover, RR is a useful parameter to investigate the level of fatigue and distress that these patients undergo during rehabilitation processes. Although motion capture systems and flowmeters are the leading instruments for respiratory pattern evaluation, smart wearable systems are gaining ever more acceptance since they allow continuous monitoring by detecting chest wall breathing displacements, ensuring reduced costs and no need for dedicated spaces. Among other sensing technologies, fiber Bragg grating (FBG) sensors have emerged thanks to their high sensitivity to strain, lightness, and multiplexing capability. In this work, a wearable system composed of four flexible dumbbell-shaped sensing modules is proposed for respiratory monitoring in hemiplegic patients. The system is light and easy to wear and can be adapted to any anthropometry thanks to the modular anchoring system. Its feasibility assessment in RR evaluation was performed on seven hemiplegic volunteers in eupnea and tachypnea breathing conditions. In addition, an explorative investigation was conducted to assess the system’s ability to detect asynchronies between torso compartments. The good results suggest that this device could be a useful instrument to support clinicians and operators in hemiplegic patients’ management.

Plants are primary resources for oxygen and foods whose production is fundamental for our life. However, diseases and pests may interfere with plant growth and cause a significant reduction of both the quality and quantity of agriculture products. Increasing agricultural productivity is crucial for poverty reduction and food security improvements. For this reason, the 2030 Agenda for Sustainable Development gives a central role to agriculture by promoting a strong technological innovation for advancing sustainable practices at the plant level. To accomplish this aim, recently, wearable sensors and flexible electronics have been extended from humans to plants for measuring elongation, microclimate, and stressing factors that may affect the plant’s healthy growth. Unexpectedly, fiber Bragg gratings (FBGs), which are very popular in health monitoring applications ranging from civil infrastructures to the human body, are still overlooked for the agriculture sector. In this work, for the first time, plant wearables based on FBG technology are proposed for the continuous and simultaneous monitoring of plant growth and environmental parameters (i.e., temperature and humidity) in real settings. The promising results demonstrated the feasibility of FBG-based sensors to work in real situations by holding the promise to advance continuous and accurate plant health growth monitoring techniques.

Epidural analgesia represents a clinical common practice aiming at pain mitigation. This loco-regional technique is widely used in several applications such as labor, surgery and lower back pain. It involves the injections of anesthetics or analgesics into the epidural space (ES). The ES detection is still demanding and is usually performed by the techniques named loss of resistance (LOR). In this study, we propose a novel soft system (SS) based on one fiber Bragg grating sensor (FBG) embedded in a soft polymeric matrix for LOR detection during the epidural puncture. The SS was designed to allow instrumenting the syringe’s plunger without relevant modifications of the anesthetist’s sensations during the procedure. After the metrological characterization of the SS, we assessed the capability of this solution in detecting LOR by carrying it out in silico and in clinical settings. For both trials, results revealed the capability of the proposed solutions in detecting the LOR and then in recording the force exerted on the plunger.

Respiratory monitoring is receiving growing interest in different fields of use, ranging from healthcare to occupational settings. Only recently, non-contact measuring systems have been developed to measure the respiratory rate (fR) over time, even in unconstrained environments. Promising methods rely on the analysis of video-frames features recorded from cameras. In this work, a low-cost and unobtrusive measuring system for respiratory pattern monitoring based on the analysis of RGB images recorded from a consumer-grade camera is proposed. The system allows (i) the automatized tracking of the chest movements caused by breathing, (ii) the extraction of the breathing signal from images with methods based on optical flow (FO) and RGB analysis, (iii) the elimination of breathing-unrelated events from the signal, (iv) the identification of possible apneas and, (v) the calculation of fR value every second. Unlike most of the work in the literature, the performances of the system have been tested in an unstructured environment considering user-camera distance and user posture as influencing factors. A total of 24 healthy volunteers were enrolled for the validation tests. Better performances were obtained when the users were in sitting position. FO method outperforms in all conditions. In the fR range 6 to 60 breaths/min (bpm), the FO allows measuring fR values with bias of −0.03 ± 1.38 bpm and −0.02 ± 1.92 bpm when compared to a reference wearable system with the user at 2 and 0.5 m from the camera, respectively.

AIMS: Real-time monitoring of tissue temperature during percutaneous tumor ablation improves treatment efficacy, leading clinicians in adjustment of treatment settings. This study aims at assessing feasibility of ultrasound thermometry during laser ablation of biological tissue using a specific ultrasound imaging techniques based on elastography acoustic radiation force impulse (ARFI). METHODS: ARFI uses high-intensity focused ultrasound pulses to generate ‘radiation force’ in tissue; this provokes tissue displacements trackable using correlation-based ultrasound methods: the sensitivity of shear waves velocity is able to detect temperature changes. Experiments were carried out using a Nd:YAG laser (power: 5 W) in three non-perfused ex vivo pig livers. In each organ, a thermocouple was placed close to the applicator tip (distance range 1.5–2.5 cm) used to record a reference temperature. Positioning of laser applicator and thermocouple was eco-guided. The organ was scanned by an echography system equipped with ARFI; propagation velocity was measured in a region of interest of 1 × 0.5 cm located close to thermocouple, to investigate influence of tissue temperature on shear waves velocity. RESULTS: Shear wave velocity has a very low sensitivity to temperature up to 55–60 °C, and in all cases, velocity is 55–60 °C, velocity shows a steep increment. The system measures a value “over limit”, meaning a velocity > 5 m s(−1). CONCLUSIONS: Ultrasound thermometry during laser ablation of biological tissue based on elastography shows an abrupt output change at temperatures > 55–60 °C. This issue can have a relevant clinical impact, considering tumor necrosis when temperature crosses 55 °C to define the boundary of damaged volume. GRAPHIC ABSTRACT: [Image: see text]

This paper investigates the performances of a head-mounted wearable device for the breath-by-breath monitoring of respiratory frequency ( ${f}_{{R}}$ ) during exercise. The device exploits a new algorithm to estimate ${f}_{{R}}$ from the breathing-related pressure drops ( ${\Delta } {P}$ ) recorded at the nostrils level. Performances of the wearable device in measuring the breath-by-breath and 30-s average ${f}_{{R}}$ values were evaluated during two high-intensity cycling exercise tests performed in the laboratory. ${\Delta } {P}$ signals were collected from ten volunteers with the wearable device, and the simultaneous measurements with a reference instrument were performed for validation purposes. In addition, numerical simulations were carried out to reproduce the conditions expected in applied settings. Bland–Altman analysis, linear regression ( ${r}^{2}$ ), and percentage error (% $E$ ) were used for comparing the two instruments. Experimental tests demonstrate the robustness and validity of the proposed wearable device and the related algorithm to measure the breath-by-breath ${f}_{R}$ (overall $\%{E} = {4.03\%}$ ) and 30-s average ${f}_{R}$ (overall ${\%E} = {2.38\%}$ ) values. Biases obtained with the breath-by-breath analysis (max. −0.06 ± 6.27 breaths/min) were higher than those obtained in the 30-s window analysis (max. −0.03 ± 1.60 breaths/min). In the simulated conditions, $\%E$ increased up to 6.65%. The proposed wearable device is suitable for a wide variety of indoor applications where the ${f}_{R}$ monitoring during exercise at reduced invasiveness is of great value.

The importance of humidity control is spreading through a broad spectrum of applications, from food and pharmaceutical industries to biomedical and chemical fields. During the last decades, the growing interest in fiber Bragg gratings (FBG) led to new approaches and applications for the humidity measurement by means of the deposition of hygroscopic materials on gratings. The influence of the coating material and its features such us coating thickness (tk) and concentration (wt%) on static and dynamic metrological properties have been investigated in this paper. In this paper, four agar-coated FBG sensors for humidity measurements have been fabricated, and the influence of tk and wt% on the sensors’ sensitivity and response time has been experimentally assessed. Sensitivity increases with tk and wt%: for instance, at 1 wt% it was $0.0024\,\,\text {nm}\cdot {\%}^{\mathrm {-1}}$ and $0.0052\,\,\text {nm}\cdot {\%}^{\mathrm {-1}}$ for $\text {tk}=87\,\,\mu \text{m}$ and $\text {tk} = 212\,\,\mu \text{m}$ , respectively. Results showed that also the response time increased with tk and wt%: for instance, at 1 wt% it was 56.7 s and 107.6 s for $\text {tk} = 87\,\,\mu \text{m}$ and $\text {tk}=212\,\,\mu \text{m}$ , respectively.

Quantitatively assessing personal health status is gaining increasing attention due to the improvement of diagnostic technology and the increasing occurrence of chronic pathologies. Monitoring physiological parameters allows for retrieving a general overview of the personal health status. Respiratory activity can provide relevant information, especially when pathologies affect the muscles and organs involved in breathing. Among many technologies, wearables may represent a valid solution for continuous and remote monitoring of respiratory activity, thus reducing healthcare costs. The most popular wearables used in this arena are based on detecting the breathing-induced movement of the chest wall. Therefore, their use in patients with impaired chest wall motion and abnormal respiratory kinematics can be challenging, but literature is still in its infancy. This study investigates the performance of a custom wearable device for respiratory monitoring in post-stroke patients. We tested the device on six hemiplegic patients under different respiratory regimes. The estimated respiratory parameters (i.e., respiratory frequency and the timing of the respiratory phase) demonstrated good agreement with the ones provided by a gold standard device. The promising results of this pilot study encourage the exploitation of wearables on these patients that may strongly impact the treatment of chronic diseases, such as hemiplegia.

In recent years, the market dedicated to wearable devices has undergone a strong expansion due to the increasingly development of innovative and personalized technologies for monitoring vital parameters. The COVID-19 pandemic has led the change in daily habits through the introduction of personal protective equipment (e.g., face mask) into everyday routine. The use of an instrumented face mask to monitor heart rate (HR) and respiratory rate (RR) of workers in occupational settings may be useful to better understand the physiological conditions and the presence of environmental and physical stressors.Among many methods used to estimate these two vital signs, photoplethysmography has gained broad acceptance in the scientific community. Several sites have been used to place the photoplethysmographic sensor (e.g., ear lobe and finger-tip) to estimate the above-mentioned physiological parameters. In this paper, we proposed a smart face mask (SFM) instrumented by a photoplethysmographic sensor. This configuration is particularly adequate to be used in those occupational settings which require the use of common input peripherals (e.g., mouse and keyboard) which prompt to fast movement of hands and fingers, limiting the performance of common measurement systems (e.g., smartwatches) due to motion artifacts. The proof of concept of SFM has been conducted by mimicking conditions close to the mentioned occupational settings through the use of a low computational power algorithm. The proposed system showed promising results by returning values in agreement with the reference system mimicking RR in a wide range of values.

Recognition of occupational stressors is a goal of primary importance to improve the psycho-physical health of workers. Many studies agree in considering the respiratory rate (RR) as a key parameter to be monitored since changes from normal physiological ranges can be closely related to states of mental and physical stress. Despite the wide availability of solutions devoted to RR detection, the utilization of light and unobtrusive wearable systems exploiting several sensing technologies is becoming more and more popular in recent years. Among others, fiber Bragg gratings (FBGs) are gaining momentum due to their valuable properties (e.g., lightness, multiplexing capability, high sensitivity etc.) which make them suitable to be integrated into garments and appropriate for RR monitoring purpose. In this work, the feasibility assessment of an FBG-based wearable system for RR detection in a static occupational scenario is presented. A chest strap instrumented with two flexible sensors based on an FBG technology was exploited to perform 40 min of RR tracking on two video terminal workers. The proposed system was able to measure the respiratory signal over a prolonged time and showed high capability to estimate RR when compared to a reference instrument, as evinced by the obtained values of mean absolute error (MAE), always ≤ 1 bpm.

The aim of this work was to investigate the use Principal Component Analysis (PCA) applied to signals recorded by 4 textile piezoresistive sensors embedded within a smart garment (SG) to estimate respiratory rate (RR) during walking/running tasks. To this aim, we enrolled 6 subjects who were asked to perform 7 trials on a treadmill at different speeds: one static condition (quiet breathing at rest), three walking trials at 1.6 km/h, 3.0 km/h and 5.0 km/h, and three running trials at 8.0 km/h, 10.0 km/h and 12.0 km/h. We recorded breathing activity using both the SG embedding 4 piezoresistive sensors, located on lower thorax and abdomen, and a reference flowmeter. We estimated RR using three different signals from SG: i) the average along sensors of the band-pass filtered piezoresistive signals (Xbp), the first principal component (P1st) and the average along components of the sub-set of principal components needed to obtain an accounted variance of 0.95 (P95). On the basis of the RR computed with the reference flowmeter, we obtained that, on average, the error committed relying on P95 is 1.02 bpm, the error obtained considering Xbp is 1.04 bpm and the error obtained using P1st is 1.13 bpm. However, the use of P95 allows obtaining a better estimation at high speed tasks than both Xbp and P1st. This finding may suggest that the use of PCA and, specifically, of the signal obtained as the average along all those components required to obtain an accounted variance of 0.95 may be conveniently used to selectively discard breathing-unrelated components, thus improving the estimation of RR.

Strain sensors based on conductive and flexible textiles are gaining great relevance in research applications, rehabilitation, and sports medicine for monitoring human joints movements, thanks to their flexibility, negligible weight, and easy integration into substrates and wearable systems. The purpose of this work was twofold: i) to carry out the static characterization and to analyze the hysteresis of two textile-based strain sensors integrated into a polymeric matrix, and ii) to evaluate the feasibility of these sensors in monitoring scapular movements during bilateral arms abduction-adduction and flexion-extension. Results showed a comparable range of resistance variation at 0-20% strain during static characterization, with a mean absolute gauge factor of 2.65 (sensor A) and 2.12 (sensor B). The maximum hysteresis error was always lower than 31% for sensor A and lower than 27% for sensor B. Both sensors showed promising results in monitoring scapular motion during the two selected single-plane upper limb movements.

This study proposes a new methodology to evaluate the entrainment between music and breathing during exercise. We provided a detailed description of how the respiratory and music signals were collected, synchronized and processed. Music-breathing entrainment was computed by adapting to the context of music a common methodology used in physiology to compute locomotor-ventilatory entrainment. Preliminary data on two participants suggest the existence of the music-breathing entrainment phenomenon during exercise, with potential implications for exercise adherence and monitoring with wearable sensors.

Epidural injection represents a widely accepted clinical practice in the management of pain relief caused by musculoskeletal disorders, labour and during surgery. The main purpose of this technique is to mitigate the painful feeling in the affected area by injecting anaesthetics and analgesics in the epidural space (the area between the ligamentum flavum and the dura mater). Correct epidural space detection is still challenging because of the small size, and the failure rate is not negligible. Including the existing techniques employed for identifying the epidural space, loss of resistance (LOR) is the most popular method used in clinical practice. It is based on the LOR feeling experienced by the anesthesiologist when the Tuohy needle moves from the ligamentum flavum to the epidural space due to the different density of these two tissues. In the last decades, several systems have been developed to support clinicians during the procedure. Recently, fiber Bragg grating sensors (FBG) have shown promising results for developing techniques able to detect the LOR. In this study, we proposed a novel FBG-based system for LOR detection during epidural puncture. We instrumented the syringe plunger with a flexible polymeric matrix. To assess its performance in LOR detection, we enrolled five users who performed the epidural procedure using a commercial simulator. The results obtained showed the ability of our system to detect LOR.

The use of face masks as respiratory protective equipment (RPE) is considered key to maintaining the quality of life during emergency situations, long-term care and working conditions. Face masks can reduce the virus spread and bacterial infections as well as prevent the inhalation of industrial waste gases. Individuals who wear a facial mask over a prolonged time often reported uncomfortable feelings due to breathing resistance, heat, tightness, and overall discomfort. One of the main indicators used to quantify the level of discomfort induced by RPE is the respiratory rate (RR). In fact, RR can be directly associated with RPE-related unease since the presence of facial masks might intuitively modify the breathing pattern of the users. Unfortunately, still little is known about RR and its variability in response to wearing RPE. In the last year, the massive use of face masks due to COVID-19 pandemic fosters the development of sensors to measure RR once mounted into the medical mask. Among other, fiber Bragg grating sensors (FBGs) have gained growing attention since the intrinsic advantages of small size, lightweight, high metrological properties, and safety. In the present study, a single-use FFP2 surgical mask was instrumented by a soft sensor based on FBG to perform a longterm acquisition (i.e., 20 min) of the respiratory signal during ordinary work activities at the video terminal. The promising results confirmed the high accuracy of the proposed system in the estimation of RR with a maximum discrepancy of −0.69 breaths per minute and mean absolute percentage error of 2.88% when compared to a reference instrument. Moreover, no saturation of the sensor output occurred during the usage time.

Wearable devices are finding their use from activities of daily living to clinical evaluations for monitoring different physiological parameters. Among others, estimation and tracking of limb movements are crucial especially in rehabilitation medicine and in supporting the worker's health. The purpose of this works is to develop and test a wearable system based on an encapsulated conductive sensor, able to track the elbow joint flexion-extension movements, to count the number of movement repetitions, and to estimate the elbow joint angles during the movement. The feasibility assessment of the proposed system has been carried out on 2 healthy volunteers mimicking a rehabilitation task and occupation setting one. A motion capture system has been used as reference system for the elbow movements. Results showed a good agreement between the data collected by the wearable system and the ones provided by the reference one. Indeed, the output of the two systems during the trials was similar, highlighting the capability of the wearable to follow the elbow flexion-extensions. In addition, the two systems tracked the same number of flexion-extensions. Finally, promising results were also obtained in the most challenging task, which is the estimation of the elbow angle. Indeed, the agreement, calculated in terms of mean absolute error, has been always lower than 7.5°.

Instrumented objects (e.g., smart mattress) are attractive technologies in the field of long-term vital signs monitoring because of their unobtrusiveness. Among the existing sensors that can be employed to develop smart mattress, Fiber Bragg grating sensors (FBGs) are one of the most promising ones. Their particular characteristics (i.e., high-sensitivity, flexibility, multiplexing capability and immunity to electromagnetic fields) allowed the widespread use in the field of cardiorespiratory monitoring. In the present study, we developed a mattress embedding an array of five FBGs to record breathing-related body movements for respiratory rate (RR). We evaluated the feasibility of the proposed mattress for RR monitoring during quiet breathing and tachypnea in two different positions (i.e., supine and prone). In both the positions and under the two breathing conditions, all the FBGs allow the RR monitoring with mean absolute error (MAE) lower than 0.26 bpm compared against RR estimated from the reference instrument.

Early diagnosis can be crucial to limit both the mortality and economic burden of cardiovascular diseases. Recent developments have focused on the continuous monitoring of cardiac activity for a prompt diagnosis. Nowadays, wearable devices are gaining broad interest for a continuous monitoring of the heart rate (HR). One of the most promising methods to estimate HR is the seismocardiography (SCG) which allows to record the thoracic vibrations with high non-invasiveness in out-of-laboratory settings. Despite significant progress on SCG, the current state-of-the-art lacks both information on standardized sensor positioning and optimization of wearables design. Here, we introduce a soft wearable system (SWS), whose novel design, based on a soft polymer matrix embedding an array of fiber Bragg gratings, provides a good adhesion to the body and enables the simultaneous recording of SCG signals from multiple measuring sites. The feasibility assessment on healthy volunteers revealed that the SWS is a suitable wearable solution for HR monitoring and its performance in HR estimation is strongly influenced by sensor positioning and improved by a multi-sensor configuration. These promising characteristics open the possibility of using the SWS in monitoring patients with cardiac pathologies in clinical (e.g., during cardiac magnetic resonance procedures) and everyday life settings.

The interest in wearable devices has tremendously increased in recent years, thanks the wide range of possible applications in which they can be used. As the employed sensors are able to capture relevant physiological signals, it has been lately proposed to exploit data collected by these instruments for automatic biometric recognition purposes. In this regard, a significant amount of studies has been conducted on the discriminative characteristics of the hearth activity. Within this context, in this paper we investigate the feasibility of recognizing people exploiting measurements of the mechanical vibrations of the chest, induced by the heart activity. To this aim, the effectiveness of combining signals acquired through seismocardiography and gyrocardiography is here evaluated. In order to evaluate the existence of discriminative characteristics within the considered signals, deep learning techniques relying on transfer learning have been applied on the considered measurements. Tests performed on ten subjects have been conducted in order to assess the influence on recognition performance of the positioning on the chest of the employed sensors, as well as the dependence on the posture assumed by the subjects while taking the employed recordings. The obtained results testify that promising recognition rates could be actually achieved when properly placing the considered devices.

Rotator cuff (RC) disease is a common musculoskeletal disorder of the shoulder entailing pain, with reduced functionality and quality of life. The main objective of this study was to present a perspective of the current scientific evidence about personalized, predictive, participatory, precision, and preventive approaches in the management of RC diseases. The personalized, predictive, participatory, precision and preventive (P5) medicine model is an interdisciplinary and multidisciplinary approach that will provide researchers and clinicians with a comprehensive patrimony of knowledge in the management of RC diseases. The ability to define genetic predispositions in conjunction with the evaluation of lifestyle and environmental factors may boost the tailoring of diagnosis and therapy in patients suffering from RC diseases.

Cardiac radiofrequency ablation (RFA) has received substantial attention for the treatment of multiple arrhythmias. In this scenario, there is an ever-growing demand for monitoring the temperature trend inside the tissue as it may allow an accurate control of the treatment effects, with a consequent improvement of the clinical outcomes. There are many methods for monitoring temperature in tissues undergoing RFA, which can be divided into invasive and non-invasive. This paper aims to provide an overview of the currently available techniques for temperature detection in this clinical scenario. Firstly, we describe the heat generation during RFA, then we report the principle of work of the most popular thermometric techniques and their features. Finally, we introduce their main applications in the field of cardiac RFA to explore the applicability in clinical settings of each method.

BackgroundOur previous study on the 2016/2017 Serie A season showed that a greater likelihood of reaching the top positions in the Italian league “Serie A” seemed to be mainly related to sprint activity, goal attempts, total throws, target shots and assists. Therefore, we aim to evaluate the following season data in the same league to compare, confirm, and improve these results.MethodsThe data of all the matches played during the “Serie A” 2017–2018 season were obtained from the Italian soccer league. The teams’ analysis was performed in terms of total distance covered in km, jogging, running and sprint activities, average speed, and match statistics (total shots, shots on target, goal attempts, assists, turnovers, and steals).ResultsTeams that reached the first four positions revealed a lower percentage of running (65.98 ± 1.51 vs. 66.84 ± 2.18;p p = 0.037) and sprint activities (8.41 ± 1.04 vs. 7.86 ± 0.82;p R = 0.906;p R = 0.850;p ConclusionsOur results suggest that high-level teams have a lower running rate and a higher percentage of jogging and sprinting than other teams.

This work aims at selecting the number and the body location of piezoresistive sensors to instrument wearable systems for respiratory rate (RR) estimation. We tested a novel method based on Principal Component Analysis on 10 healthy male subjects, who were asked to perform six trials on a treadmill (at rest, during walking and low speed running). We monitored RR using both a smart garment composed of six piezoresistive sensors and a flowmeter, used as reference signal. On the basis of the results, we propose the following guidelines: i) breathing assessment at rest requires one sensor, placed on the lower thorax; ii) low speed walking assessment requires three sensors, placed on upper thorax, lower thorax and abdomen; iii) high speed walking and running assessment requires a four-sensor configuration (one sensor placed on the upper thorax, one on the lower thorax and two on the abdomen); iv) an effective assessment can be performed at all speeds using the above-mentioned four-sensor configuration, denoted as General Purpose Configuration.

Improper posture, presence of spinal disorders or assessment of postural stability require specific monitoring systems, applicable in static and dynamic conditions. Different methods are available for the analysis of the posture, ranging from the visual observation in clinical practice to the tridimensional reconstruction of the spine with optical motion capture systems. Wearable devices based on inertial sensors may be adopted for the continuous measurement of the subject posture, not only during rehabilitative exercises, but also during daily activities. Equal attention should be reserved both to the choice of the sensor and to the understanding of which physiological parameters are best being monitored. In this work, we propose a system consisting of a magneto-inertial measurement unit (MIMU) to monitor the velocity profile of the cervicothoracic spine segment while performing forward bending and backward return task. The MIMU was placed on the back of four volunteers (two women and two men). The time series of the angular velocity of the cervicothoracic region has been compared with the data provided by a motion capture system (MoCap), which is able to track the tridimensional positions of the reflective markers attached to the skin at specific anatomical landmarks, ensuring adaptation to the gender-related anatomy. The proposed system, compared to the reference, presents a relative root mean square error (RMSE) spanning from 3.6% to 4.8% of the total measured range of velocities. These results show that the proposed wearable system could be used for the health assessment of the posture of any subject without gender and age restrictions during daily activities.

Among the existing thermal ablation techniques, microwave ablation (MWA) is gaining momentum due to its great potentialities in the treatment of several organs. MWA effectiveness is influenced by several factors, such as ablation system design and patients' anatomical characteristics. The presence of large blood vessel in the proximity of tumor masses dissipates heat by convection (phenomenon known in the literature as heat sink effect). The potential consequence is the risk of incomplete tumor ablation. In this study, we experimentally investigated such phenomenon in ex vivo swine liver during MWA. The blood vessel was mimicked through a silicone tube inserted within the organ. To evaluate the influence of the heat sink effect on MWA, we measured the tissue temperature by fiber Bragg grating sensors (FBGs) in two different configurations (i.e., with and without blood vessel nearby the MW applicator). The notable differences in terms of temperature recorded in the two different scenarios demonstrated the cooling effect caused by blood vessel.

In recent years, wearable devices for physiological parameter monitoring in sports and physical activities have been gaining momentum. In particular, some studies have focused their attention on using available commercial monitoring systems mainly on horses during training sessions or competitions. Only a few studies have focused on the jockey’s physiological and kinematic parameters. Although at a glance, it seems jockeys do not make a lot of effort during riding, it is quite the opposite. Indeed, especially during competitions, they profuse a short but high intensity effort. To this extend, we propose a wearable system integrating conductive textiles and an M-IMU to simultaneously monitor the respiratory rate (RR) and kinematic parameters of the riding activity. Firstly, we tested the developed wearable system on a healthy volunteer mimicking the typical riding movements of jockeys and compared the performances with a reference instrument. Lastly, we tested the system on two gallop jockeys during the “137∘ Derby Italiano di Galoppo”. The proposed system is able to track both the RR and the kinematic parameters during the various phases of the competition both at rest and during the race.

BACKGROUND The detection of epidural space is usually performed by the technique of loss of resistance (LOR) without technological support, although there are few commercial options. In this work, we aimed to assess the feasibility of a new, non-invasive, mechatronic system for LOR detection in clinical settings. The system allows monitoring the pressure exerted on the syringe plunger by the clinician during the puncture. The LOR is related to the mentioned pressure. METHODS Pressure exerted on the syringe plunger by an expert anesthesiologist was monitored using the proposed system. 58 epidural punctures were performed on 34 patients using six configurations with different sensitivities and ranges of measurements. The system capability in LOR detection was evaluated comparing the LOR detected by the system with the feedback provided by the clinician. The procedure time was estimated using the system and without its use. RESULTS The detection of LOR is strongly related to the system configuration; it ranged from 93.3% to 27.7%, while 3 configurations never detected it. The procedure time showed a non-significant increase (p=0.56) using the proposed system (average time 71 s vs. 62 s). CONCLUSIONS The proposed mechatronic system successfully detected the LOR in the large part of cases using the configurations characterized by the best trade-off between system sensitivity and range of measurements. A non-significant increment of the procedure time is related to the use of the system.

Low back pain (LBP) is one of the musculoskeletal disorders that most affects workers. Among others, one of the working categories which mainly experiences such disease are video terminal workers. As it causes exploitation of the National Health Service and absenteeism in workplaces, LBP constitutes a relevant socio-economic burden. In such a scenario, a prompt detection of wrong seating postures can be useful to prevent the occurrence of this disorder. To date, many tools capable of monitoring the spinal range of motions (ROMs) are marketed, but most of them are unusable in working environments due to their bulkiness, discomfort and invasiveness. In the last decades, fiber optic sensors have made their mark allowing the creation of light and compact wearable systems. In this study, a novel wearable device embedding a Fiber Bragg Grating sensor for the detection of lumbar flexion-extensions (F/E) in seated subjects is proposed. At first, the manufacturing process of the sensing element was shown together with its mechanical characterization, that shows linear response to strain with a high correlation coefficient (R2 &gt, 0.99) and a sensitivity value (S&epsilon, ) of 0.20 nm∙m&epsilon, &minus, 1. Then, the capability of the wearable device in measuring F/E in the sagittal body plane was experimentally assessed on a small population of volunteers, using a Motion Capture system (MoCap) as gold standard showing good ability of the system to match the lumbar F/E trend in time. Additionally, the lumbar ROMs were evaluated in terms of intervertebral lumbar distances (&Delta, d L 3 &minus, L 1 ) and angles, exhibiting moderate to good agreement with the MoCap outputs (the maximum Mean Absolute Error obtained is ~16% in detecting &Delta, L 1 ). The proposed wearable device is the first attempt for the development of FBG-based wearable systems for workers&rsquo, safety monitoring.

In the present study, we assessed the performances of a smart t-shirt embedding twelve fiber-optic sensors located in different areas of the trunk during a cycling incremental exercise test. Four volunteers were asked to wear simultaneously our t-shirt and a reference instrument based on airflow measurement with the purpose of validating the measure of respiratory frequency (f R ). The study aimed to identify the areas of the trunk which are most suitable for measuring f R , with important implications for the design of sports respiratory wearables specifically developed for monitoring f R , during cycling exercise.

Wearable devices are extensively used for monitoring physiological parameters both in clinical settings and in sports science. Among others, respiratory rate is mostly neglected but is a valid index to assess athletes' performance. The purpose of this work was to test a wearable device composed of two elastic bands embedding conductive textiles during a running session of approximately 9.5 km. The test has been carried out by a young healthy volunteer who worn two bands on the rib cage (one on the upper thorax and one on the umbilicus). The frequency-domain analysis allowed estimating both respiratory parameters (i.e., the average respiratory rate, $\overline{f_{R}})$ and running related parameters (i.e., estimated running distance and average running pace). The wearable system was able to perform a good estimation of both respiratory and gait parameters allowing a better understanding of the relationship between the fatigue and the respiratory activity, enabling a more accurate running performance evaluation.

Wearable strain sensors potentially hold great significance in several areas, such as rehabilitation, research, sports. Conductive textile elements are excellent candidates for the development of wearable devices as human motion capture systems because of their intrinsic properties of lightweight, compliance, flexibility, and stretchability. Herein, the metrological characterization of sensing elements based on a conductive textile intended for joint motion monitoring is presented.The aim of this study is twofold: (i) analyzing the influence of the shape on the metrological properties of conductive textiles, (ii) providing a preliminary assessment of the performance of a custom-made wearable device (i.e., a glove) embedding a conductive textile element to monitor wrist joint movements. The static characterization and the hysteresis analysis were performed on two samples of conductive textile elements, i.e., the zig-zag pattern and the rectangular one. The feasibility assessment of a glove embedding one sensing element for wrist flexion-extension monitoring was performed on a single volunteer.Results showed that the zig-zag patterned conductive element had a resistance change range comparable to the rectangular one (i.e., 100 kΩ – 170 kΩ vs. 40 kΩ – 80 kΩ), higher averaged sensitivity (i.e., -3.96 kΩ•%-1 vs. -2.42 kΩ•%-1), and a lower hysteresis error, 6.83%). the % (i.e., averaged 5.22% vs. Regarding feasibility assessment of %the wearable device, results showed good performance in tracking wrist flexion-extension in real-time. The proposed wearable device embedding a conductive textile element seems to be suitable for wrist motions monitoring with promising applications in contexts as rehabilitation, sports, and clinical research.

Wearable stretchable sensors are gaining significant interest in application related to joint motion monitoring. Stretchable strain sensors are a promising technological solution to develop wearable systems for several applications (e.g., sports, rehabilitation, health science) thanks to their flexibility, lightweight, compliance, and ease to wear. The aim of this study is twofold: i) to perform the metrological characterization of a stretchable sensing element based on a conductive textile fabric for developing a wearable sensor intended for joint motion monitoring and ii) to provide a preliminary assessment of the developed sensor in shoulder motion monitoring. The static characterization and the hysteresis analysis at different speeds (i.e., 50 mm.min−1, 100 mm.min−1, 200 mm.min−1, 400 mm.min−1and 600 mm.min−1) were carried out to assess the sensor's characteristics to mechanical strain. An explorative test to assess the sensor feasibility in monitoring horizontal flexion-extension of the shoulder was performed on one healthy volunteer. Results showed that the sensor's resistance decreased from $75 k \Omega$ at 0% strain level to $52 k \Omega$ at 10% strain level during static characterization. Moreover, the maximum hysteresis error $e_{H}\%$ was always lower than 2.59% during loading-unloading hysteresis cycles at different speeds. The developed stretchable sensor seems to be a promising solution for monitoring shoulder range of motion in applications were unobtrusiveness and wearability are key factors.