Wearable sensors system for an improved analysis of freezing of gait in Parkinson's disease using electromyography and inertial signals

We propose a wearable sensor system for automatic, continuous and ubiquitous analysis of Freezing of Gait (FOG), in patients affected by Parkinson's disease. FOG is an unpredictable gait disorder with different clinical manifestations, as the trembling and the shuffling-like phenotypes, whose underlying pathophysiology is not fully understood yet. Typical trembling-like subtype features are lack of postural adaptation and abrupt trunk inclination, which in general can increase the fall probability. The targets of this work are detecting the FOG episodes, distinguishing the phenotype and analyzing the muscle activity during and outside FOG, toward a deeper insight in the disorder pathophysiology and the assessment of the fall risk associated to the FOG subtype. To this aim, gyroscopes and surface electromyography integrated in wearable devices sense simultaneously movements and action potentials of antagonist leg muscles. Dedicated algorithms allow the timely detection of the FOG episode and, for the first time, the automatic distinction of the FOG phenotypes, which can enable associating a fall risk to the subtype. Thanks to the possibility of detecting muscles contractions and stretching exactly during FOG, a deeper insight into the pathophysiological underpinnings of the different phenotypes can be achieved, which is an innovative approach with respect to the state of art

THE VALIDITY OF MEASURING SKIPPING CADENCE WITH A NOVEL WEARABLE SENSOR - SINTEC SMART PATCH

The aim of this study was to test the validity of running cadence assessed with a novel smart patch designed within a SINTEC Horizon 2020 project. Participants performed 3 consecutive 20-seconds skipping with increasing intensity (slow, medium, fast). Cadence was derived from raw data from a “SINTEC” smart patch, Dytran accelerometers, and HBM bilateral force plates. Data from all devices were compared using Bland-Altman analysis and Wilcoxon signed-rank test. The mean bias between cadence measured with Dytran accelerometer and force plates with ‘’SINTEC’’ smart patch was 0.08 and -0.17 steps/min, respectively. In addition, there were no statistically significant difference between the mean cadence determined with different sensors/devices. Therefore, we can conclude that the measurement of cadence using a novel SINTEC smart patch showed good validity

Supercooled Liquid Ga Stretchable Electronics

By controlling the properties of its medium, supercooled liquid Ga (SLGa) based stretchable remains stretchable at -22 degrees C, i.e., 52 degrees C below its thermo-dynamic melting point of Ga. Thus far, our oldest deposited SLGa circuit and film have remained liquids for 2 years at room temperature. The study investi-gates the crystallization of SLGa triggered by the surface energy of nucleation agents, temperature, circuit cross-section, and mechanical impact. Based on these parameters, a method is presented to integrate electronic components with SLGa circuits without compromising its supercooling effect. Further, the large stiffness variation induced by phase transition is demonstrated in dif-ferent applications. For the desired stiffness variation, the crystallization rate can be controlled by varying the temperature and cross-section area. Finally, spray-printing an ink of microscale SLGa microscale particles can confor-mally pattern Ga on a rough surface, e.g., to fabricate a stretchable array of SLGa microelectrodes. A smart patch with stretchable SLGa electrode arrays records human electrocardiogram signals in cold water and does not stain the skin after use. Its low and stable impedance in water will enable novel applications in wearable electronics

Long-Term Polygraphic Monitoring through MEMS and Charge Transfer for Low-Power Wearable Applications

In this work, we propose a wireless wearable system for the acquisition of multiple biopotentials through charge transfer electrostatic sensors realized in MEMS technology. The system is designed for low power consumption and low invasiveness, and thus candidates for long-time monitoring in free-living conditions, with data recording on an SD or wireless transmission to an external elaborator. Thanks to the wide horizon of applications, research is very active in this field, and in the last few years, some devices have been introduced on the market. The main problem with those devices is that their operation is time-limited, so they do not match the growing demand for long monitoring, which is a must-have feature in diagnosing specific diseases. Furthermore, their versatility is hampered by the fact that they have been designed to record just one type of signal. Using ST-Qvar sensors, we acquired an electrocardiogram trace and single-channel scalp electroencephalogram from the frontal lobes, together with an electrooculogram. Excellent results from all three types of acquisition tests were obtained. The power consumption is very low, demonstrating that, thanks to the MEMS technology, a continuous acquisition is feasible for several days

Systolic Blood Pressure Estimation from PPG Signal Using ANN

High blood pressure is one of the most important precursors for Cardiovascular Diseases (CVDs), the most common cause of death in 2020, as reported by the World Health Organization (WHO). Moreover, many patients affected by neurodegenerative diseases (e.g., Parkinson’s Disease) exhibit impaired autonomic control, with inversion of the normal circadian arterial pressure cycle, and consequent augmented cardiovascular and fall risk. For all these reasons, a continuous pressure monitoring of these patients could represent a significant prognostic factor, and help adjusting their therapy. However, the existing cuff-based methods cannot provide continuous blood pressure readings. Our work is inspired by the newest approaches based on the photoplethysmographic (PPG) signal only, which has been used to continuously estimate systolic blood pressure (SP), using artificial neural networks (ANN), in order to create more compact and wearable devices. Our first database was derived from the PhysioNet resource; we extracted PPG and arterial blood pressure (ABP) signals, collected at a sampling frequency of 125 Hz, in a hospital environment. It consists of 249,672 PPG periods and the relative SP values. The second database was collected at STMicroelectronics s.r.l., in Agrate Brianza, using the MORFEA3 wearable device and a digital cuff-based sphygmomanometer, as reference. The pre-processing phase, in order to remove noise and motion artifacts and to segment the signal into periods, was carried out on Matlab R2019b. The noise removal was one of the challenging parts of the study because of the inaccuracy of the PPG signal during everyday-life activity, and this is the reason why the MORFEA3 dataset was acquired in a controlled environment in a static position. Different solutions were implemented to choose the input features that best represent the period morphology. The first database was used to train the multilayer feed-forward neural network with a back-propagation model, whereas the second one was used to test it. The results obtained in this project are promising and match the Association for the Advancement of Medical Instruments (AAMI) and the British Hypertension Society (BHS) standards. They show a Mean Absolute Error of 3.85 mmHg with a Standard Deviation of 4.29 mmHg, under the AAMI standard, and reach the grade A under the BHS standard

A New Wearable System for Home Sleep Apnea Testing, Screening, and Classification

We propose an unobtrusive, wearable, and wireless system for the pre-screening and follow-up in the domestic environment of specific sleep-related breathing disorders. This group of diseases manifests with episodes of apnea and hypopnea of central or obstructive origin, and it can be disabling, with several drawbacks that interfere in the daily patient life. The gold standard for their diagnosis and grading is polysomnography, which is a time-consuming, scarcely available test with many wired electrodes disseminated on the body, requiring hospitalization and long waiting times. It is limited by the night-by-night variability of sleep disorders, while inevitably causing sleep alteration and fragmentation itself. For these reasons, only a small percentage of patients achieve a definitive diagnosis and are followed-up. Our device integrates photoplethysmography, an accelerometer, a microcontroller, and a bluetooth transmission unit. It acquires data during the whole night and transmits to a PC for off-line processing. It is positioned on the nasal septum and detects apnea episodes using the modulation of the photoplethysmography signal during the breath. In those time intervals where the photoplethysmography is detecting an apnea, the accelerometer discriminates obstructive from central type thanks to its excellent sensitivity to thoraco-abdominal movements. Tests were performed on a hospitalized patient wearing our integrated system and the type III home sleep apnea testing recommended by The American Academy of Sleep Medicine. Results are encouraging: sensitivity and precision around 90% were achieved in detecting more than 500 apnea episodes. Least thoraco-abdominal movements and body position were successfully classified in lying down control subjects, paving the way toward apnea type classification

Reliability and validity of running step rate derived from a novel wearable Smart Patch

A novel, wearable, stretchable Smart Patch can monitor various aspects of physical activity, including the dynamics of running. However, like any new device developed for such applications, it must first be tested for validity and reliability. Here, we compare the step rate while running on a treadmill measured by this smart patch with the corresponding values obtained with the ”gold standard” OptoGait, as well as with other devices commonly used to assess running dynamics, i.e., the MEMS accelerometer and commercially available and widely used Garmin Running Dynamic Pod. The 14 healthy, physically active volunteers completed two identical sessions with a 5-minute rest between. Each session involved two one-minute runs at 11 km/h and 14 km/h separated by a one-min rest. The major finding was that the Smart Patch demonstrated fair to good test-retest reliability. The best test-retest reliability for the Running Pod was observed in connection with running at 11 km/h and both velocities combined (good and excellent, respectively) and for the OptoGait when running at 14 km/h (good). The best concurrent validity was achieved with the Smart Patch, as reflected in the highest Pearson correlation coefficient for this device when running at 11 or 14 km/h, as well as for both velocities combined. In conclusion, this study demonstrates that the novel wearable Smart Patch shows promising reliability and excellent concurrent validity in measuring step rate during treadmill running, making it a viable tool for both research and practical applications in sports and exercise science.Full text license: CC BY-NC-ND 4.0;</p

Multisensor Integrated Platform Based on MEMS Charge Variation Sensing Technology for Biopotential Acquisition

We propose a new methodology for long-term biopotential recording based on an MEMS multisensor integrated platform featuring a commercial electrostatic charge-transfer sensor. This family of sensors was originally intended for presence tracking in the automotive industry, so the existing setup was engineered for the acquisition of electrocardiograms, electroencephalograms, electrooculograms, and electromyography, designing a dedicated front-end and writing proper firmware for the specific application. Systematic tests on controls and nocturnal acquisitions from patients in a domestic environment will be discussed in detail. The excellent results indicate that this technology can provide a low-power, unexplored solution to biopotential acquisition. The technological breakthrough is in that it enables adding this type of functionality to existing MEMS boards at near-zero additional power consumption. For these reasons, it opens up additional possibilities for wearable sensors and strengthens the role of MEMS technology in medical wearables for the long-term synchronous acquisition of a wide range of signals

A Comparison of a Novel Stretchable Smart Patch for Measuring Runner's Step Rates with Existing Measuring Technologies

A novel wearable smart patch can monitor various aspects of physical activity, including the dynamics of running, but like any new device developed for such applications, it must first be tested for validity. Here, we compare the step rate while running in place as measured by this smart patch to the corresponding values obtained utilizing ''gold standard'' MEMS accelerometers in combination with bilateral force plates equipped with HBM load cells, as well as the values provided by a three-dimensional motion capture system and the Garmin Dynamics Running Pod. The 15 healthy, physically active volunteers (age = 23 +/- 3 years; body mass = 74 +/- 17 kg, height = 176 +/- 10 cm) completed three consecutive 20-s bouts of running in place, starting at low, followed by medium, and finally at high intensity, all self-chosen. Our major findings are that the rates of running in place provided by all four systems were valid, with the notable exception of the fast step rate as measured by the Garmin Running Pod. The lowest mean bias and LoA for these measurements at all rates were associated consistently with the smart patch

Effectiveness of the cross-compliance Standard 5.2 'buffer strips' on protecting freshwater against diffuse nitrogen pollution

Sette Fasce Tampone, realizzate secondo le indicazioni tecniche contenute nello Standard di condizionalità 5.2, in diversi ambiti e contesti climatici, sono state monitorate per un periodo biennale, al fine di quantificare la loro efficienza nella rimozione di azoto inorganico disciolto. Tale azoto è costituito per lo più da molecole di azoto nitrico che vengono veicolate principalmente tramite deflussi sub-superficiali da zone soggette a diverse pratiche colturali verso i corpi idrici superficiali adiacenti. Ad eccezione di due casi: i siti di Lodi e Metaponto, in tutti i sistemi monitorati è stata confermata la presenza di deflussi trasversali ai sistemi tampone, permanenti o temporanei, in grado di veicolare inquinanti e con portate variabili fra 919 e 8.590 m3/anno per 100 m lineari di FT. Le differenze di portata sono imputabili principalmente alla diversa superficie dei bacini agricoli afferenti ai sistemi tampone, che nei casi analizzati occupano superfici variabili fra il 3,6 ed il 33,3% del bacino agricolo. Sulla base dei bilanci di massa è emerso che dai campi coltivati giungono ai sistemi tampone percentuali variabili fra l’1,6 ed il 29,4% dell’azoto inorganico applicato. Ad eccezione dei sistemi in cui i maggiori deflussi non hanno alcuna interazione con la rizosfera (deflussi profondi) oppure non attraversano la Fascia Tampone, in tutti gli altri siti si registra un effetto di riduzione dell’azoto fra entrata ed uscita, con percentuali variabili fra il 33 ed il 62 %. Percentuali di abbattimento non elevate sono giustificate dallo scarso grado di maturazione dei siti monitorati, in molti casi recentemente convertiti a Fascia Tampone. Ancora una volta si conferma l’estrema eterogeneità delle risposte di questi sistemi ed il ruolo prioritario delle forzanti idrologiche nel determinarne l’efficacia. Seven buffer strips (BS) adjacent to fresh water bodies, realized according to the technical data contained in the Standard 5.2 of Cross-compliance, located in different areas and climate contexts, were monitored for a period of two years. It was done in order to quantify their effectiveness in removing dissolved inorganic nitrogen conveyed through sub- surface flow from field crops with different cultural practices. Except for two case studies (sites: Lodi and Metaponto) in all monitored systems has been confirmed an outflow, permanent or temporary, through the buffer systems, with flow rates ranging from 919 to 8590 m3y-1 every 100 meters of buffer stip. The differences in flow rate were mainly due to different sizes of agricultural basins related to buffer systems, which in the case studies ranging from 3.6 to 33.3%. Based on the mass balance, was found percentages of applied inorganic nitrogen, flowing from cultivated fields to the buffer systems, varied between 1.6 and 29.4%. In most of the sites was estimated nitrogen reduction between inlet and outlet of BS, with percentages ranging from 33 to 61.9%. The exceptions were the systems with groundwater that: or have no interaction with the rhizosphere (deep flow) or not crossing the buffer zone. Low percentages of removal shall be justified by the young stage of the monitored sites, being in many cases recently converted to buffer strip. This study confirms the extreme variability of these systems efficiency and the key role of hydrology drives its effectiveness