Theme D: Sensors,wearable devices,intelligent networks and smart homecare for health

This paper presents the activities of the research group in sensors, wearable devices, intelligent networks and smart homecare for health inside the GdR STIC-Santé. Four research fields are covered: sensors, clothing, housing and networks, to allow better monitoring of health parameters and quality of life. Several events were organized or co-organized during the period 2011–2102. They were devoted to the issue of the autonomy of people with a particular focus on the needs and expectations and also the embedded technologies developed to enable monitoring of health parameters and activities in their living environment. Future projects will try to complete the knowledge of the current work on frailty and the risks incurred, in particular falls, and identify opportunities to share the achievements of the research teams to respond to National or European projects calls.     

Centrale de mesure ambulatoire biomédicale sur PSoC

Improvement in quality and efficiency of health and medicine, at home and in hospital, has become of paramount importance. The solution to this problem would require the continuous monitoring of several key patient parameters, including the assessment of autonomic nervous system (ANS) activity using non-invasive sensors, providing information for emotional, sensorial, cognitive and physiological analysis of the patient. Recent advances in embedded systems, microelectronics, sensors and wireless networking enable the design of wearable systems capable of such advanced health monitoring. The subject of this article is an ambulatory system comprising of a small wrist device connected to several sensors for the detection of the autonomic nervous system activity. It affords monitoring of skin resistance, skin temperature and heart activity. It is also capable of recording the data on a removable media or sending it to computer via a wireless communication. The wrist device is based on a programmable system-on-chip (PSoC) from Cypress.     

Evaluating and preventing illness associated with indoor air pollution.

Homicides have been on the rise in California in recent years, almost entirely as a result of increased firearm activity, resulting in one of the highest homicide rates in the country. With increasing morbidity and mortality from guns, health care professionals have called the situation an epidemic. In the past decade, attention from the health care profession has resulted in a new focus on the public health issues surrounding firearms. There is considerable confusion among policy makers regarding what should be done to stem firearm violence. I discuss morbidity and mortality trends, academic research, and legal issues surrounding firearm violence, affording insight into the seriousness and complexity of this rapidly growing problem and providing policy ideas for addressing the role of firearms. Such policy ideas include removal of the California Legislature''s preemptive authority on firearms licensing and registration; the formation of an information and advisory body within the California Department of Health; increased liability for manufacturers, distributors, dealers, and owners; and a statewide registration system.     

Feasibility Study on a Microwave-Based Sensor for Measuring Hydration Level Using Human Skin Models

Tissue dehydration results in three major types of exsiccosis—hyper-, hypo-, or isonatraemia. All three types entail alterations of salt concentrations leading to impaired biochemical processes, and can finally cause severe morbidity. The aim of our study was to demonstrate the feasibility of a microwave-based sensor technology for the non-invasive measurement of the hydration status. Electromagnetic waves at high frequencies interact with molecules, especially water. Hence, if a sample contains free water molecules, this can be detected in a reflected microwave signal. To develop the sensor system, human three-dimensional skin equivalents were instituted as a standardized test platform mimicking reproducible exsiccosis scenarios. Therefore, skin equivalents with a specific hydration and density of matrix components were generated and microwave measurements were performed. Hydration-specific spectra allowed deriving the hydration state of the skin models. A further advantage of the skin equivalents was the characterization of the impact of distinct skin components on the measured signals to investigate mechanisms of signal generation. The results demonstrate the feasibility of a non-invasive microwave-based hydration sensor technology. The sensor bears potential to be integrated in a wearable medical device for personal health monitoring.     

Smart textile for respiratory monitoring and thoraco‐abdominal motion pattern evaluation

The use of wearable systems for monitoring vital parameters has gained wide popularity in several medical fields. The focus of the present study is the experimental assessment of a smart textile based on 12 fiber Bragg grating sensors for breathing monitoring and thoraco‐abdominal motion pattern analysis. The feasibility of the smart textile for monitoring several temporal respiratory parameters (ie, breath‐by‐breath respiratory period, breathing frequency, duration of inspiratory and expiratory phases), volume variations of the whole chest wall and of its compartments is performed on 8 healthy male volunteers. Values gathered by the textile are compared to the data obtained by a motion analysis system, used as the reference instrument. Good agreement between the 2 systems on both respiratory period (bias of 0.01 seconds), breathing frequency (bias of ?0.02 breaths/min) and tidal volume (bias of 0.09 L) values is demonstrated. Smart textile shows good performance in the monitoring of thoraco‐abdominal pattern and its variation, as well.      

Ostracoda (Crustacea) as indicators for surface water quality: a case study from the Ledra River basin (NE Italy)

Wastewater discharges associated with urbanisations, farming activities and industry may dramatically reduce the ecological health of river ecosystems. During the reconstruction of the Friuli Venezia Giulia region following the 1976 earthquake, a lot of resources were used to build large numbers of wastewater treatment plants to minimize the impact of human activities on lotic ecosystems. Their efficiency is usually assessed through monitoring of the physical and chemical environment near the discharge point. However, discontinuous monitoring of the abiotic environment may fail to detect periodic malfunctioning and do not recognize indirect effects on the ecosystem. We assessed the potential of an alternative approach to assess the impact of wastewater discharges, based on the monitoring of ostracod density, richness and community composition. We repeatedly measured physical, chemical and microbial parameters and collected ostracod samples at stations up- and downstream from wastewater discharge points scattered over a 21-km stretch of the Ledra River (NE Italy). The results indicate that monitoring ostracods is a potentially valuable approach, for two reasons. Communities appeared to be well differentiated even in the small spatial area of this study, indicating that they can provide sufficient resolution to pick up even minor impacts. Secondly, despite the seasonal succession in species composition, spatial differentiation was consistent over time, suggesting that ostracods provide a time-integrated picture of the water quality. The traditional approach failed to detect any consistent impact of wastewater discharges, apart from an ambiguous increase in nutrient levels. The density and/or richness of the ostracod communities was altered by some wastewater discharges, but not by others. We identified a general trend for wastewater discharges to systematically replace regionally rare ostracod species with common species. In particular, the species Ilyocypris inermis was very sensitive to discharges, and may be used as an indicator species for good ecosystem health.     

Novel approach to ambulatory assessment of human segmental orientation on a wearable sensor system

A new method using a double-sensor difference based algorithm for analyzing human segment rotational angles in two directions for segmental orientation analysis in the three-dimensional (3D) space was presented. A wearable sensor system based only on triaxial accelerometers was developed to obtain the pitch and yaw angles of thigh segment with an accelerometer approximating translational acceleration of the hip joint and two accelerometers measuring the actual accelerations on the thigh. To evaluate the method, the system was first tested on a 2° of freedom mechanical arm assembled out of rigid segments and encoders. Then, to estimate the human segmental orientation, the wearable sensor system was tested on the thighs of eight volunteer subjects, who walked in a straight forward line in the work space of an optical motion analysis system at three self-selected speeds: slow, normal and fast. In the experiment, the subject was assumed to walk in a straight forward way with very little trunk sway, skin artifacts and no significant internal/external rotation of the leg. The root mean square (RMS) errors of the thigh segment orientation measurement were between 2.4° and 4.9° during normal gait that had a 45° flexion/extension range of motion. Measurement error was observed to increase with increasing walking speed probably because of the result of increased trunk sway, axial rotation and skin artifacts. The results show that, without integration and switching between different sensors, using only one kind of sensor, the wearable sensor system is suitable for ambulatory analysis of normal gait orientation of thigh and shank in two directions of the segment-fixed local coordinate system in 3D space. It can then be applied to assess spatio-temporal gait parameters and monitoring the gait function of patients in clinical settings.     

Feasibility of an Ingestible Sensor-Based System for Monitoring Adherence to Tuberculosis Therapy

Poor adherence to tuberculosis (TB) treatment hinders the individual’s recovery and threatens public health. Currently, directly observed therapy (DOT) is the standard of care; however, high sustaining costs limit its availability, creating a need for more practical adherence confirmation methods. Techniques such as video monitoring and devices to time-register the opening of pill bottles are unable to confirm actual medication ingestions. A novel approach developed by Proteus Digital Health, Inc. consists of an ingestible sensor and an on-body wearable sensor; together, they electronically confirm unique ingestions and record the date/time of the ingestion. A feasibility study using an early prototype was conducted in active TB patients to determine the system’s accuracy and safety in confirming co-ingestion of TB medications with sensors. Thirty patients completed 10 DOT visits and 1,080 co-ingestion events; the system showed 95^.0% (95% CI 93^.5–96^.2%) positive detection accuracy, defined as the number of detected sensors divided by the number of transmission capable sensors administered. The specificity was 99^.7% [95% CI 99^.2–99^.9%] based on three false signals recorded by receivers. The system’s identification accuracy, defined as the number of correctly identified ingestible sensors divided by the number of sensors detected, was 100%. Of 11 adverse events, four were deemed related or possibly related to the device; three mild skin rashes and one complaint of nausea. The system’s positive detection accuracy was not affected by the subjects’ Body Mass Index (p = 0^.7309). Study results suggest the system is capable of correctly identifying ingestible sensors with high accuracy, poses a low risk to users, and may have high patient acceptance. The system has the potential to confirm medication specific treatment compliance on a dose-by-dose basis. When coupled with mobile technology, the system could allow wirelessly observed therapy (WOT) for monitoring TB treatment as a replacement for DOT.     

Glutamine Flux Imaging Using Genetically Encoded Sensors

Genetically encoded sensors allow real-time monitoring of biological molecules at a subcellular resolution. A tremendous variety of such sensors for biological molecules became available in the past 15 years, some of which became indispensable tools that are used routinely in many laboratories.One of the exciting applications of genetically encoded sensors is the use of these sensors in investigating cellular transport processes. Properties of transporters such as kinetics and substrate specificities can be investigated at a cellular level, providing possibilities for cell-type specific analyses of transport activities. In this article, we will demonstrate how transporter dynamics can be observed using genetically encoded glutamine sensor as an example. Experimental design, technical details of the experimental settings, and considerations for post-experimental analyses will be discussed.     

Wearable technology for spine movement assessment: A systematic review

Continuous monitoring of spine movement function could enhance our understanding of low back pain development. Wearable technologies have gained popularity as promising alternative to laboratory systems in allowing ambulatory movement analysis. This paper aims to review the state of art of current use of wearable technology to assess spine kinematics and kinetics.Four electronic databases and reference lists of relevant articles were searched to find studies employing wearable technologies to assess the spine in adults performing dynamic movements. Two reviewers independently identified relevant papers. Customised data extraction and quality appraisal form were developed to extrapolate key details and identify risk of biases of each study. Twenty-two articles were retrieved that met the inclusion criteria: 12 were deemed of medium quality (score 33.4–66.7%), and 10 of high quality (score >66.8%). The majority of articles (19/22) reported validation type studies. Only 6 reported data collection in real-life environments. Multiple sensors type were used: electrogoniometers (3/22), strain gauges based sensors (3/22), textile piezoresistive sensor (1/22) and accelerometers often used with gyroscopes and magnetometers (15/22). Two sensors units were mainly used and placing was commonly reported on the spine lumbar and sacral regions. The sensors were often wired to data transmitter/logger resulting in cumbersome systems. Outcomes were mostly reported relative to the lumbar segment and in the sagittal plane, including angles, range of motion, angular velocity, joint moments and forces.This review demonstrates the applicability of wearable technology to assess the spine, although this technique is still at an early stage of development.     

Long-term <Emphasis Type="Italic">ex vivo</Emphasis> monitoring of <Emphasis Type="Italic">in vivo</Emphasis> microRNA activity in liver using a secreted luciferase sensor

Technology for monitoring in vivo microRNA (miRNA) activity is extremely important for elucidating miRNA biology. However, in vivo studies of miRNA have been hampered by the lack of a convenient approach to reliably reflect real-time functional changes in miRNAs. Sensors for miRNA were developed by adding miRNA target sequences to the 3′-untranslated region of Gaussia princeps luciferase (Gluc) mRNA. These sensors were then evaluated in vitro and in vivo by measuring Gluc activity in cell supernatants and in peripheral blood. Sensors driven by the CMV promoter were effective for monitoring miR-122 in living cells, but not for the long-term monitoring of miR-122 or miR-142 in mouse liver because of CMV-promoter silencing. Replacing the CMV promoter with a CAG promoter rendered these sensors effective for the long-term monitoring of relevant liver miRNA activities. We subsequently used the CAG-promoter-based sensor for the long-term monitoring of endogenous liver miR-122, miR142 and miR-34a activities, as well as for exogenous miR-34a activity. Our study demonstrates that real-time in vivo activities of miRNAs can be continuously and conveniently detected in mouse liver using the sensors that we have developed.     

Machine learning in human movement biomechanics: Best practices,common pitfalls,and new opportunities

Traditional laboratory experiments, rehabilitation clinics, and wearable sensors offer biomechanists a wealth of data on healthy and pathological movement. To harness the power of these data and make research more efficient, modern machine learning techniques are starting to complement traditional statistical tools. This survey summarizes the current usage of machine learning methods in human movement biomechanics and highlights best practices that will enable critical evaluation of the literature. We carried out a PubMed/Medline database search for original research articles that used machine learning to study movement biomechanics in patients with musculoskeletal and neuromuscular diseases. Most studies that met our inclusion criteria focused on classifying pathological movement, predicting risk of developing a disease, estimating the effect of an intervention, or automatically recognizing activities to facilitate out-of-clinic patient monitoring. We found that research studies build and evaluate models inconsistently, which motivated our discussion of best practices. We provide recommendations for training and evaluating machine learning models and discuss the potential of several underutilized approaches, such as deep learning, to generate new knowledge about human movement. We believe that cross-training biomechanists in data science and a cultural shift toward sharing of data and tools are essential to maximize the impact of biomechanics research.     

A community mobilisation intervention to prevent violence against women and reduce HIV/AIDS risk in Kampala, Uganda (the SASA! Study): study protocol for a cluster randomised controlled trial

ABSTRACT: BACKGROUND: Gender based violence, including violence by an intimate partner, is a major global human rights and public health problem, with important connections with HIV risk. Indeed, the elimination of sexual and gender based violence is a core pillar of HIV prevention for UNAIDS. Integrated strategies to address the gender norms, relations and inequities that underlie both violence against women and HIV/AIDS are needed. However there is limited evidence about the potential impact of different intervention models. This protocol describes the SASA! Study: an evaluation of a community mobilisation intervention to prevent violence against women and reduce HIV/AIDS risk in Kampala, Uganda. METHODS: The SASA! Study is a pair-matched cluster randomised controlled trial being conducted in eight communities in Kampala. It is designed to assess the community-level impact of the SASA! intervention on the following six primary outcomes: attitudes towards the acceptability of violence against women and the acceptability of a woman refusing sex (among male and female community members); past year experience of physical intimate partner violence and sexual intimate partner violence (among females); community responses to women experiencing violence (among women reporting past year physical/sexual partner violence); and past year concurrency of sexual partners (among males). 1583 women and men (aged 18-49 years) were surveyed in intervention and control communities prior to intervention implementation in 2007/8. A follow-up cross-sectional survey of community members will take place in 2012. The primary analysis will be an adjusted cluster-level intention to treat analysis, comparing outcomes in intervention and control communities at follow-up. Complementary monitoring and evaluation and qualitative research will be used to explore and describe the process of intervention implementation and the pathways through which change is achieved. DISCUSSION: This is one of few cluster randomised trials globally to assess the impact of a gender-focused community mobilisation intervention. The multi-disciplinary research approach will enable us to address questions of intervention impact and mechanisms of action, as well as its feasibility, acceptability and transferability to other contexts. The results will be of importance to researchers, policy makers and those working on the front line to prevent violence against women and HIV.     

Fiber optic evanescent wave immunosensors for medical diagnostics.

Immunodiagnostic sensors permit sensitive measurement of a wide variety of both high and low molecular mass analytes--serum analytes may be detected at picomolar concentrations. Due to the sensor monitoring antigen--antibody reactions directly, quantitative results are available within seconds to minutes of sample introduction. In recent years, the trend has been for immunodiagnostics to be used at sites away from centralized medical laboratories. Specific requirements associated with such use are being achieved by the development of optical devices incorporating evanescent wave sensors.     

Sleeping posture recognition using fuzzy c-means algorithm

Background

Pressure sensors have been used for sleeping posture detection, which meet privacy requirements. Most of the existing techniques for sleeping posture recognition used force-sensitive resistor (FSR) sensors. However, lower limbs cannot be recognized accurately unless thousands of sensors are deployed on the bedsheet.

Method

We designed a sleeping posture recognition scheme in which FSR sensors were deployed on the upper part of the bedsheet to record the pressure distribution of the upper body. In addition, an infrared array sensor was deployed to collect data for the lower body. Posture recognition was performed using a fuzzy c-means clustering algorithm. Six types of sleeping body posture were recognized from the combination of the upper and lower body postures.

Results

The experimental results showed that the proposed method achieved an accuracy of above 88%. Moreover, the proposed scheme is cost-efficient and easy to deploy.

Conclusions

The proposed sleeping posture recognition system can be used for pressure ulcer prevention and sleep quality assessment. Compared to wearable sensors and cameras, FSR sensors and infrared array sensors are unobstructed and meet privacy requirements. Moreover, the proposed method provides a cost-effective solution for the recognition of sleeping posture.

     

A Spark-based genetic algorithm for sensor placement in large scale drinking water distribution systems

Water pollution incidents have occurred frequently in recent years, causing severe damages, economic loss and long-lasting society impact. A viable solution is to install water quality monitoring sensors in water supply networks (WSNs) for real-time pollution detection, thereby mitigating the risk of catastrophic contamination incidents. Given the significant cost of placing sensors at all locations in a network, a critical issue is where to deploy sensors within WSNs, while achieving rapid detection of contaminant events. Existing studies have mainly focused on sensor placement in water distribution systems (WDSs). However, the problem is still not adequately addressed, especially for large scale WSNs. In this paper, we investigate the sensor placement problem in large scale WDSs with the objective of minimizing the impact of contamination events. Specifically, we propose a two-phase Spark-based genetic algorithm (SGA). Experimental results show that SGA outperforms other traditional algorithms in both accuracy and efficiency, which validates the feasibility and effectiveness of our proposed approach.     

Development of hyperthermia measurable fiber radiometric thermometer for thermotherapy

Temperature monitoring is extremely important during thermotherapy. Fiber‐optic temperature sensors are preferred because of their flexibility and immunity to electromagnetic interference. Although many types of fiber‐optic sensors have been developed, clinically adopting them remains challenging. Here, we report a silica fiber‐based radiometric thermometer using a low‐cost extended InGaAs detector to detect black body radiation between 1.7 and 2.4 μm. For the first time, this silica fiber‐based thermometer is capable of measuring temperatures down to 35°C, making it suitable for monitoring hyperthermia during surgery. In particular, the thermometer has potential for seamless integration with current silica fiber catheters, which are widely used in laser interstitial thermotherapy. The feasibility, capability and sensitivity of tracking tissue temperature variation were proved through ex vivo tissue studies. After further improvement, the technology has the potential to be translated into clinics for monitoring tissue temperature.     

Nanogap Dielectric Spectroscopy for Aptamer-Based Protein Detection

Among the various label-free methods for monitoring biomolecular interactions, capacitive sensors stand out due to their simple instrumentation and compatibility with multiplex formats. However, electrode polarization due to ion gradient formation and noise from solution conductance limited early dielectric spectroscopic measurements to high frequencies only, which in turn limited their sensitivity to biomolecular interactions, as the applied excitation signals were too fast for the charged macromolecules to respond. To minimize electrode polarization effects, capacitive sensors with 20 nm electrode separation were fabricated using silicon dioxide sacrificial layer techniques. The nanoscale separation of the capacitive electrodes in the sensor results in an enhanced overlapping of electrical double layers, and apparently a more ordered “ice-like” water structure. Such effects in turn reduce low frequency contributions from bulk sample resistance and from electrode polarization, and thus markedly enhance sensitivity toward biomolecular interactions. Using these nanogap capacitive sensors, highly sensitive, label-free aptamer-based detection of protein molecules is achieved.     

Versatile Core–Sheath Yarn for Sustainable Biomechanical Energy Harvesting and Real‐Time Human‐Interactive Sensing

The emergence of stretchable textile‐based mechanical energy harvester and self‐powered active sensor brings a new life for wearable functional electronics. However, single energy conversion mode and weak sensing capabilities have largely hindered their development. Here, in virtue of silver‐coated nylon yarn and silicone rubber elastomer, a highly stretchable yarn‐based triboelectric nanogenerator (TENG) with coaxial core–sheath and built‐in spring‐like spiral winding structures is designed for biomechanical energy harvesting and real‐time human‐interactive sensing. Based on the two advanced structural designs, the yarn‐based TENG can effectively harvest or respond rapidly to omnifarious external mechanical stimuli, such as compressing, stretching, bending, and twisting. With these excellent performances, the yarn‐based TENG can be used in a self‐counting skipping rope, a self‐powered gesture‐recognizing glove, and a real‐time golf scoring system. Furthermore, the yarn‐based TENG can also be woven into a large‐area energy‐harvesting fabric, which is capable of lighting up light emitting diodes (LEDs), charging a commercial capacitor, powering a smart watch, and integrating the four operational modes of TENGs together. This work provides a new direction for textile‐based multimode mechanical energy harvesters and highly sensitive self‐powered motion sensors with potential applications in sustainable power supplies, self‐powered wearable electronics, personalized motion/health monitoring, and real‐time human‐machine interactions.     

Triboelectric Nanogenerator Enabled Wearable Sensors and Electronics for Sustainable Internet of Things Integrated Green Earth

The advancement of the Internet of Things/5G infrastructure requires a low-cost ubiquitous sensory network to realize an autonomous system for information collection and processing, aiming at diversified applications ranging from healthcare, smart home, industry 4.0 to environmental monitoring. The triboelectric nanogenerator (TENG) is considered the most promising technology due to its self-powered, cost-effective, and highly customizable advantages. Through the use of wearable electronic devices, advanced TENG technology is developed as a core technology enabling self-powered sensors, power supplies, and data communications for the aforementioned applications. In this review, the advancements of TENG-based electronics regarding materials, material/device hybridization, systems integration, technology convergence, and applications in healthcare, environment monitoring, transportation, and smart homes toward the future green earth are reported.