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In this work, electrodes based on laser-scribed reduced graphene oxide were fabricated using filter paper as the substrate. To fabricate the electrodes, a water suspension of graphene oxide was filtered to produce a continuous and uniform film of graphene oxide on the filter paper surface. Subsequently, a CO2 laser was used to "write" the working, counter and reference eelctroes by reducing graphene oxide in specific areas to define complete sensors. Referecnce electrodes were then coated with a commercial Ag/AgCl conductive paste to produce a quasi Ag/AgCl reference. As fabricated devices were employed as electrochemical sensors for detection of phosphate ions in water by employing the molybdenum blue method. This method exploits the reaction between molybdate and phosphate ions in acidic media leading to a Keggin-type complex (PMo12O3 40) which, being electrochemically active, enables the indiret detection of phosphate ions. Sensors exhibited high selectivity and sensitive detection of phosphate ions in a wide linear range, from 1 to 20 & mu;M; with a limit of detection of 0.4 & mu;M. To demonstrate that sensors could be utilized for in-situ phosphate ion detection, paper substrate was first pre-loaded with sul-phuric acid and molybdate ions. During analysis, these chemicals were then desorbed directly into the test sample eliminating the need for any kind of external manipulation or reagent addition. Thus, this paper presents the fabrication of a portable, easy-to-use, biodegradable and fast phosphate ions sensor for in situ and real-time monitoring of water quality.

We present a novel configuration for an axial virtual cathode oscillator (Vircator) operating in the C-band and designed for high output power applications. In order to enhance the efficiency, we have employed a geometry with up to seven reflectors along the drift space. While in previous research works this optimization process has been performed only varying the reflectors radii while using a fixed distance between reflectors,in our work we propose an optimization in terms of both reflectors radii and distances. Our optimized structure for the axial Vircator is able to provide an efficiency up to 15.6% and an output power of 1.6 GW in the C-band, with a working voltage of 510 kV and a cathodic current of 24 kA.

In this work, we study ultra-short term (UST) complexity of Heart Rate Variability (HRV) and its agreement with analysis of standard short-term (ST) HRV recordings obtained at rest and during orthostatic stress. Conditional Entropy (CE) measures have been computed using both a linear Gaussian approximation and a more accurate model-free approach based on nearest neighbors. The agreement between UST and ST indices has been compared via statistical tests and correlation analysis, suggesting the feasibility of exploiting faster algorithms and shorter time series for detecting changes in cardiovascular control during various states.

This paper proposes a control system for a quadratic boost DC/DC converter in a wide range of operations, based on an inner loop with a sliding mode controller, for reaching a desired equilibrium state, and an outer loop with integral-type controller, for assuring robustness against load and input voltage variations and converter parameter uncertainties. The sliding mode controller is designed with the extended linearization method and assures local asymptotic stability, whereas the integral controller is designed using classical frequency methods, and assures input–output stability. It is shown that the proposed controller also deals with the sudden changes in the nominal operating conditions; thus, if a change of the operating conditions takes place, the proposed control scheme automatically creates a sliding regime which stabilizes the converter trajectories to the new equilibrium point. Experimental results carried out on a suitably developed test set up show the effectiveness of the proposed approach.

In recent years, the attention to the health and comfort of the individual, together with the electronic miniaturization progress, have led to an increased interest in the development of biomedical devices that are able to acquire a multitude of biomedical signals. Such devices should be wearable and comfortable during daily use, to be thus suitable for continuously monitoring psychophysical health states. In this context, we have designed and realized a portable biomedical device capable of real-time acquisition of electrocardiographic (ECG), photoplethysmographic (PPG), breathing and galvanic skin response (GSR) signals, for a noninvasive monitoring of multiple physiological parameters. This work shows the architecture of our system, which integrates a Bluetooth module for wireless communication with the central computer and novel analog sensors capable of carrying out breathing and GSR measurements. Preliminary measurements carried out using our system during a controlled breathing protocol illustrated how the simultaneous measurement of ECG, PPG, GSR and respiration allows tracking changes not only in heart rate, but also in epidermal tissue sweating, thus confirming that the device can be successfully employed for monitoring health status and, in perspective, also for assessing the individual’s stress level.

The amount of information exchanged per unit of time between two dynamic processes is an important concept for the analysis of complex systems. Theoretical formulations and data-efficient estimators have been recently introduced for this quantity, known as the mutual information rate (MIR), allowing its continuous-time computation for event-based data sets measured as realizations of coupled point processes. This work presents the implementation of MIR for point process applications in Network Physiology and cardiovascular variability, which typically feature short and noisy experimental time series. We assess the bias of MIR estimated for uncoupled point processes in the frame of surrogate data, and we compensate it by introducing a corrected MIR (cMIR) measure designed to return zero values when the two processes do not exchange information. The method is first tested extensively in synthetic point processes including a physiologically-based model of the heartbeat dynamics and the blood pressure propagation times, where we show the ability of cMIR to compensate the negative bias of MIR and return statistically significant values even for weakly coupled processes. The method is then assessed in real point-process data measured from healthy subjects during different physiological conditions, showing that cMIR between heartbeat and pressure propagation times increases significantly during postural stress, though not during mental stress. These results document that cMIR reflects physiological mechanisms of cardiovascular variability related to the joint neural autonomic modulation of heart rate and arterial compliance.

High speed electrical drives and machines represent a promising solution to cope with the increasing electrification in several fields, e.g. industrial electronics and mobility. According to that, power electronics is going more and more towards innovative technologies of semiconductor devices, such as Gallium-Nitride (GaN) and Silicon-Carbide (SiC), providing the opportunity of faster switching transients and therefore of higher switching frequencies. A challenging perspective is represented by gaining higher and higher switching frequencies while keeping high voltage and low power losses. In this scenario, the Cascode (CC) configuration can represent a reliable solution in order to reach notable levels of dV/dt without losing efficiency. In this paper, a three-phase Pulse Width Modulated (PWM) inverter based on a CC connection for each of its six switches is proposed and some promising experimental results are provided. SiC technology has been used for each power MOSFET.

Multilevel Power Inverters (MPIs) represent a valid solution to improve the performances of energy production systems from renewable energy sources. Furthermore, the use of novel FPGA control systems allows simplifying the implementation of multicarrier PWM techniques for MPIs with computational benefits. This paper describes the implementation of several multicarrier PWM techniques on NI-SOM sbRIO-9651 for the control of a three-phase five-level cascaded H-bridge inverter. In detail, sbRIO-9651 is a control system in the field of Power Electronics and Drives (PED) programmable in the LabVIEW graphical programming environment. The paper is focused on modulation techniques implementation, testing, and experimental validation.

Background and objective: Recently, various algorithms have been introduced using wrist-worn photo-plethysmography (PPG) to provide high accuracy of instantaneous heart rate (HR) estimation, including during high-intensity exercise. Most studies focus on using acceleration and/or gyroscope signals for the motion artifact (MA) reference, which attenuates or cancels out noise from the MA-corrupted PPG signals. We aim to open and pave the path to find an appropriate MA reference selection for MA cancelation in PPG.Methods: We investigated how the acceleration and gyroscope reference signals correlate with the MAs of the distorted PPG signals and derived both mathematically and experimentally an adaptive MA reference selection approach. We applied our algorithm to five state-of-the-art (SOTA) methods for the performance evaluation. In addition, we compared the four MA reference selection approaches, i.e. with acceleration signal only, with gyroscope signal only, with both signals, and using our proposed adaptive selection.Results: When applied to 47 PPG recordings acquired during intensive physical exercise from two differ-ent datasets, our proposed adaptive MA reference selection method provided higher accuracy than the other MA selection approaches for all five SOTA methods.Conclusion: Our proposed adaptive MA reference selection approach can be used in other MA cancelation methods and reduces the HR estimation error.Significance: We believe that this study helps researchers to address acceleration and gyroscope signals as accurate MA references, which eventually improves the overall performance for estimating HRs through the various algorithms developed by research groups.

In recent years, new efficient power devices have been implemented. Silicon Carbide has replaced silicon as regards the production and the utilization of many devices, such as MOSFETs, diodes, IGBTs and many others. SiC devices are characterized by a low reverse recovery charge, high carrier saturation velocity, by which it is possible to work at high frequency, and high breakdown voltage. Thanks to the great thermal conductivity and the wide bandgap, these devices can operate at high temperature and reach high voltages and currents. What is important to stress is the fact that power losses in SiC devices are lower than the silicon ones. These are the reasons why these devices are utilized in a wide range of technological applications, including power electronics. In this paper, power losses in Si and SiC devices are evaluated in simulation and compared to each other. In order to demonstrate the remarkable advantages of the SiC devices over the silicon ones, a study which makes use of an isolated DC-DC converter has been conducted. As regards the proposed full-bridge converter, SiC and silicon MOSFETs and diodes, of whom some static and dynamic parameters are defined, are used in order to transfer power from a DC voltage supply to a load.

In this work, we report on a comparison among graphene field-effect transistors (GFETs) employing different dielectrics as gate layers to evaluate their microwave response. In particular, aluminum oxide (Al$_{2}$O$_{3}$), titanium oxide (TiO$_{2}$), and hafnium oxide (HfO$_{2}$) have been tested. GFETs have been fabricated on a single chip and a statistical analysis has been performed on a set of 24 devices for each type of oxide. Direct current and microwave measurements have been carried out on such GFETs and short circuit current gain and maximum available gain have been chosen as quality factors to evaluate their microwave performance. Our results show that all of the devices belonging to a specific group (i.e., with the same oxide) have a well-defined performance curve and that the choice of hafnium oxide represents the best trade-off in terms of dielectric properties. Graphene transistors employing HfO$_{2}$ as the dielectric layer, in fact, exhibit the best performance in terms of both the cutoff frequency and the maximum frequency of oscillation.

In this work, we report on the design, fabrication and characterization of Metal-Oxide Graphene Field-effect Transistors (MOGFETs) exploiting novel clamped gate geometries aimed at enhancing the device transconductance. The fabricated devices employ clamped metal contacts also for source and drain, as well as an optimized graphene meandered pattern for source contacting, in order to reduce parasitic resistance. Our experimental results demonstrate that MOGFETs with the proposed structure show improved high frequency performance, in terms of maximum available gain and transition frequency values, as a consequence of the higher equivalent transconductance obtained.

In this work, we extend to the multivariate case the classical correlation analysis used in the field of network physiology to probe dynamic interactions between organ systems in the human body. To this end, we define different correlation-based measures of the multivariate interaction (MI) within and between the brain and body subnetworks of the human physiological network, represented, respectively, by the time series of delta, theta, alpha, and beta electroencephalographic (EEG) wave amplitudes, and of heart rate, respiration amplitude, and pulse arrival time (PAT) variability. MI is computed: (i) considering all variables in the two subnetworks to evaluate overall brain–body interactions; (ii) focusing on a single target variable and dissecting its global interaction with all other variables into contributions arising from the same subnetwork and from the other subnetwork; and (iii) considering two variables conditioned to all the others to infer the network topology. The framework is applied to the time series measured from the EEG, electrocardiographic (ECG), respiration, and blood volume pulse (BVP) signals recorded synchronously via wearable sensors in a group of healthy subjects monitored at rest and during mental arithmetic and sustained attention tasks. We find that the human physiological network is highly connected, with predominance of the links internal of each subnetwork (mainly heart rate-respiration and delta-theta, theta-alpha, alpha-beta), but also statistically significant interactions between the two subnetworks (mainly heart rate-beta and heart rate-delta). MI values are often spatially heterogeneous across the scalp and are modulated by the physiological state, as indicated by the decrease of cardiorespiratory interactions during sustained attention and by the increase of brain–heart interactions and of brain–brain interactions at the frontal scalp regions during mental arithmetic. These findings illustrate the complex and multi-faceted structure of interactions manifested within and between different physiological systems and subsystems across different levels of mental stress.

The objective of this study is to present a new method to assess in the frequency domain the directed interactions between the spontaneous variability of systolic arterial pressure (SAP) and heart period (HP) from their linear model representation, and to apply it for studying the baroreflex control of arterial pressure in healthy physiological states and after acute myocardial infarction (AMI). The method is based on pole decomposition of the model transfer function and on the following evaluation of causal measures of coupling and gain from the poles associated to low frequency (0.04−0.15 Hz) oscillatory components. It is compared with traditional non-causal approaches for the spectral analysis of the baroreflex gain, and with causal approaches based on the directed coherence, in a group of AMI patients and in Young and Old healthy controls studied at rest and during head-up tilt. Analysis of feedforward interactions from RR to SAP is also performed. Our results support the importance of using local causal approaches to quantify separately baroreflex and feedforward interactions between RR and SAP, allowing both to confirm known physiological behaviors (e.g., weaker baroreflex effectiveness and lower sensitivity after AMI) and to suggest novel findings (e.g., preserved low frequency baroreflex response to postural stress after AMI). We also find that the postural stress alters feedforward interactions selectively across groups, being related to decreased coupling only in Young and to increased gain mostly in AMI. These results have a significance for the clinical assessment of the baroreflex and the physiological evaluation of cardiovascular interactions.

We present an innovative implementation of the solid-state-biased coherent detection (SSBCD) technique, which we have recently introduced for the reconstruction of both amplitude and phase of ultra-broadband terahertz pulses. In our previous works, the SSBCD method has been operated via a heterodyne scheme, which involves demanding square-wave voltage amplifiers, phase-locked to the THz pulse train, as well as an electronic circuit for the demodulation of the readout signal. Here, we demonstrate that the SSBCD technique can be operated via a very simple homodyne scheme, exploiting plain static bias voltages. We show that the homodyne SSBCD signal turns into a bipolar transient when the static field overcomes the THz field strength, without the requirement of an additional demodulating circuit. Moreover, we introduce a differential configuration, which extends the applicability of the homodyne scheme to higher THz field strengths, also leading a two-fold improvement of the dynamic range compared to the heterodyne counterpart. Finally, we demonstrate that, by reversing the sign of the static voltage, it is possible to directly retrieve the absolute THz pulse polarity. The homodyne configuration makes the SSBCD technique of much easier access, leading to a vast range of field-resolved applications.

Il monitoraggio di pazienti tramite segnali fotopletismografici (PhotoPlethysmoGram, PPG) acquisiti sul polso, arteria radiale, piuttosto che sulla punta dell’indice, permette di ottenere un segnale più stabile e con maggiori informazioni, come la gittata cardiaca, la durata della contrazione ventricolare e la chiusura dell’aorta. In questo lavoro è presentata un’attività preliminare per rilevare condizioni come l’ostruzione polmonare e le apnee notturne. Si è indagato l’andamento dell’aritmia respiratoria in relazione ad eventuali difficoltà respiratorie. Per il momento ci si è limitati ad osservare soggetti sani e l’ostruzione è stata simulata facendo respirare i soggetti attraverso una cannuccia.

In this work, we have designed and realised a portable and compact electronic system for the synchronous acquisition of multiple physiological signals. The system employs a Texas Instruments ADS1298 front-end with 24-bit resolution for data acquisition and supports up to 8 channels and 4 kHz sampling rate. The front-end communicates via SPI with a STM32 microcontroller which pre-processes the data and sends them through USB or Bluetooth to a suitable PC application. The system has been realized for the simultaneous acquisition of electrocardiographic (ECG) and photoplethysmographic (PPG) signals, but it can also be employed for acquiring other typologies of signals, e.g. breathing or electro-dermal activity, for a potential use in the automotive field to assess the driver’s health status in real-time or, in perspective, the stress level. PPG probes have also been realised, each one including dual wavelength LED (emitting at 735 and 850 nm), and a Silicon Photomultiplier (SiPM) detector (provided by STMicroelectronics) having high responsivity and gain [1]. The system integrates an I2C interface, 8-channel, 16-levels current LED driver for PPG probes and includes a Graphical User Interface (GUI) able, in real time, to (i) plot the signals, (ii) save the data, (iii) calculate and display main cardiovascular parameters (i.e., heart rate, breath rate, pulse arrival time, pulse transit time, pulse wave velocity). Both instantaneous or averaged values of heart rate are shown, also to display the time variation of the considered parameters and thus assess the so-called Heart Rate Variability [2]. Current version of the system is able to acquire up to 5 PPG waveforms and 3 ECG leads. Figure 1 shows a photo of the system, alongside with the PPG probes (on the right) and the standard ECG electrodes (on the left) which are used for signals acquisition. Figure 2 illustrates some screenshots of the developed GUI showing 2 ECG leads and 2 PPG waveforms. In detail, Fig. 2(a) depicts the windows displaying the waveforms, while, Fig. 2(b) exhibits the window dedicated to show in real-time the instantaneous and averaged values of the above-mentioned physiological parameters. Several measurement campaigns have been carried out on healthy volunteers of different ages to both test the correct functioning of the system, and also to compare the Pulse Arrival Time values computed between different body locations. In the future, by performing measurements on other typologies of subjects (e.g., hypertensive or diabetic patients), a statistical analysis of the collected data will be carried out, in order to evaluate the capability of using our system for distinguishing between different pathologies or for early disease detection, or even for assessing various stress levels. This activity was supported by Advancing Smart Optical Imaging and Sensing for Health (ASTONISH) Project (Grant no. 692470), funded by H2020-EU.2.1.1.7.-ECSEL programme.

Network physiology is a recent approach describing the human body as an integrated network composed of several organ systems which continuously interact to produce healthy and diseased states. In this work, we apply the network physiology paradigm to study dynamical interactions between EEG activity and heart rate variability in children suffering from focal epilepsy. We aim to study the characteristics of brainheart coupling between, before, and after seizures to better understand the physiological mechanisms underlying seizure onset in the pre-ictal phase and the recovery of normal autonomic function in the post-ictal phase. In perspective, linking the dynamic information of brain-heart can provide useful information for a better seizure prediction. EEG and ECG data were recorded in 10 patients with focal epilepsy. After removal of baseline drift and muscle artifacts, the variability of heart rate and brain activity were measured extracting R-R intervals from the ECG and computing the spectral power of the EEG. 143 synchronous time series of 300 points were obtained in 4 different time windows (10 min and 10 sec before and after the seizure) and analyzed computing the cross-correlation coefficient (CC) and the mutual information (MI). A statistically significant increase of MI was observed just after seizure episodes (pvalue equal to 0.04, 10s before vs 10s after distributions, electrode O2), while a recovery of the baseline value was obtained 10 minutes after the episodes. This trend was found for several other EEG electrodes (Fp2, F3, F8, T3, C4, T4). On the contrary, CC did not change significantly across time windows. These results suggest that focal seizures are associated with an increased brain-heart coupling which is noticeable after seizure termination only in terms of mutual information. We conclude that focal epilepsy in childhood is associated with nonlinear brain-heart interaction mechanisms.

In this work, partial information decomposition (PID) was applied to the time series of heart rate and EEG amplitude variability to investigate the dynamical interactions in brain-heart coupling before and after epileptic seizures. From ECG and EEG signals collected on 23 children suffering from focal epilepsy, the RR intervals and the EEG variance at ipsilateral and contralateral temporal electrodes were computed in four different time windows before and after the seizures. Static PID was used to obtain redundant, unique and synergistic components of the total information shared between the series of RR and EEG variance. Results highlight, in the progression from preictal to postictal states, a statistically significant change of mutual information at the ipsilateral electrode and of the synergy between brain locations.

The human body can be seen as a functional network depicting the dynamical interactions between different organ systems. This exchange of information is often evaluated with information-theoretic approaches which comprise the use of vector autoregressive (VAR) and state space (SS) models, normally identified with the Ordinary Least Squares (OLS). However, the number of time series to be included in the model is strictly related to the length of data recorded thus limiting the use of the classical approach. In this work, a new method based on penalized regressions, the so-called LASSO, was compared with OLS on physiological time-series extracted from 18 subjects during different stress conditions. Results show similarities between the brain-body interactions estimated by both methodologies, highlighting a greater intepretability of patterns estimated with LASSO especially in the subnetwork of brain-brain interactions.

The recent advances in multiparametric monitoring of biosignals and management of big data prompt for the development of devices and techniques for the extraction of indicators with physiological relevance. In this context, we have designed and realized a portable electronic system, equipped with simple biomedical sensors, able to synchronously record multiple electrocardiographic (ECG), photoplethysmographic (PPG) and breathing signals, for carrying out a non-invasive monitoring of several cardiovascular parameters. In this work, we show the results of preliminary measurements performed following a specific physiological protocol (i.e., deep breathing with 10 s per cycle). The system allows to monitor specific physiological behaviors, such as the decrease of the R-R interval (increase of the heart rate) during inhalation and the increase of the stroke volume increases during exhalation. The high quality of the ECG/PPG/breath waveforms acquired by our probes, sensors and system allows an improvement in the accuracy of the extraction of noteworthy cardiovascular parameters.

Baroreflex response consists of cardiac chronotropic (effect on heart rate), cardiac inotropic (on contractility), venous (on venous return) and vascular (on vascular resistance) arms. Because of its measurement simplicity, cardiac chronotropic arm is most often analysed. The aim was to introduce a method to assess vascular baroreflex arm, and to characterize its changes during stress. We evaluated the effect of orthostasis and mental arithmetics (MA) in 39 (22 female, median age: 18.7 yrs.) and 36 (21 female, 19.2 yrs.) healthy volunteers, respectively. We recorded systolic and mean blood pressure (SBP and MBP) by volume-clamp method and R-R interval (RR) by ECG. Cardiac output (CO) was recorded using impedance cardiography. From MBP and CO, peripheral vascular resistance (PVR) was calculated. The directional spectral coupling and gain of cardiac chronotropic (SBP to RR) and vascular arms (SBP to PVR) were quantified. The strength of the causal coupling from SBP to PVR was significantly higher than SBP to RR coupling during whole protocol (P < 0.001). Along both arms, the coupling was higher during orthostasis compared to supine (P < 0.001 and P = 0.006), no MA effect was observed. No significant changes in the spectral gain (ratio of RR or PVR change to a unit SBP change) across all phases were found (0.111 ≤ P ≤ 0.907). We conclude that changes in PVR are tightly coupled with SBP oscillations via the baroreflex providing an approach for the baroreflex vascular arm analysis with a potential to reveal new aspects of blood pressure dysregulation.

We present the solid-state-biased coherent detection technique for ultra-broadband THz pulses operated via a homodyne configuration. This makes our detection method of easy implementation, suitable for cost-effective and portable THz systems.

In this work, we investigate the possibility of employing graphene field effect transistors, specifically designed for microwave applications, as infrared detectors for telecom applications. Our devices have been fabricated on a sapphire substrate employing CVD-grown transferred graphene. The roles of both the gate dielectric and the DC bias conditions have been evaluated in order to maximize the infrared generated signal through an experimental investigation of the signal-to-noise ratio dependence on the transistor operating point.

In this paper, we present a low cost prototype of a Time-Of-Flight (TOF) LiDAR system, employing a SiPM as photo detector and MEMS mirrors in order to steer the nanosecond pulsed optical beam with a scanning angle of +/-6°. Preliminary TOF measurements have been performed both indoor and outdoor to test the limits of the system.

This work presents a preliminary study on the electrical characterization of high efficiency bifacial solar cells. An opening discussion on the state-of-the-art of such advanced technology is initially proposed and the experimental characterization of some prototypes is described. From this analysis, it can be stated that the bifacial silicon solar cells can be a very promising technology with high electrical performances and efficiency.