Body ares networks for human motor assessment

Healthcare, Human Computer Interfaces (HCI), Security and Biometry are the most promising application scenario directly involved in the Body Area Networks (BANs) evolution. Both wearable devices and sensors directly integrated in garments envision a word in which each of us is supervised by an invisible assistant monitoring our health and daily-life activities. New opportunities are enabled because improvements in sensors miniaturization and transmission efficiency of the wireless protocols, that achieved the integration of high computational power aboard independent, energy-autonomous, small form factor devices. Application’s purposes are various: (I) data collection to achieve off-line knowledge discovery; (II) user notification of his/her activities or in case a danger occurs; (III) biofeedback rehabilitation; (IV) remote alarm activation in case the subject need assistance; (V) introduction of a more natural interaction with the surrounding computerized environment; (VI) users identification by physiological or behavioral characteristics. Telemedicine and mHealth [1] are two of the leading concepts directly related to healthcare. The capability to borne unobtrusiveness objects supports users’ autonomy. A new sense of freedom is shown to the user, not only supported by a psychological help but a real safety improvement. Furthermore, medical community aims the introduction of new devices to innovate patient treatments. In particular, the extension of the ambulatory analysis in the real life scenario by proving continuous acquisition. The wide diffusion of emerging wellness portable equipment extended the usability of wearable devices also for fitness and training by monitoring user performance on the working task. The learning of the right execution techniques related to work, sport, music can be supported by an electronic trainer furnishing the adequate aid. HCIs made real the concept of Ubiquitous, Pervasive Computing and Calm Technology introduced in the 1988 by Marc Weiser and John Seeley Brown. They promotes the creation of pervasive environments, enhancing the human experience. Context aware, adaptive and proactive environments serve and help people by becoming sensitive and reactive to their presence, since electronics is ubiquitous and deployed everywhere. In this thesis we pay attention to the integration of all the aspects involved in a BAN development. Starting from the choice of sensors we design the node, configure the radio network, implement real-time data analysis and provide a feedback to the user. We present algorithms to be implemented in wearable assistant for posture and gait analysis and to provide assistance on different walking conditions, preventing falls. Our aim, expressed by the idea to contribute at the development of a non proprietary solutions, driven us to integrate commercial and standard solutions in our devices. We use sensors available on the market and avoided to design specialized sensors in ASIC technologies. We employ standard radio protocol and open source projects when it was achieved. The specific contributions of the PhD research activities are presented and discussed in the following. • We have designed and build several wireless sensor node providing both sensing and actuator capability making the focus on the flexibility, small form factor and low power consumption. The key idea was to develop a simple and general purpose architecture for rapid analysis, prototyping and deployment of BAN solutions. Two different sensing units are integrated: kinematic (3D accelerometer and 3D gyroscopes) and kinetic (foot-floor contact pressure forces). Two kind of feedbacks were implemented: audio and vibrotactile. • Since the system built is a suitable platform for testing and measuring the features and the constraints of a sensor network (radio communication, network protocols, power consumption and autonomy), we made a comparison between Bluetooth and ZigBee performance in terms of throughput and energy efficiency. Test in the field evaluate the usability in the fall detection scenario. • To prove the flexibility of the architecture designed, we have implemented a wearable system for human posture rehabilitation. The application was developed in conjunction with biomedical engineers who provided the audio-algorithms to furnish a biofeedback to the user about his/her stability. • We explored off-line gait analysis of collected data, developing an algorithm to detect foot inclination in the sagittal plane, during walk. • In collaboration with the Wearable Lab – ETH, Zurich, we developed an algorithm to monitor the user during several walking condition where the user carry a load. The remainder of the thesis is organized as follows. Chapter I gives an overview about Body Area Networks (BANs), illustrating the relevant features of this technology and the key challenges still open. It concludes with a short list of the real solutions and prototypes proposed by academic research and manufacturers. The domain of the posture and gait analysis, the methodologies, and the technologies used to provide real-time feedback on detected events, are illustrated in Chapter II. The Chapter III and IV, respectively, shown BANs developed with the purpose to detect fall and monitor the gait taking advantage by two inertial measurement unit and baropodometric insoles. Chapter V reports an audio-biofeedback system to improve balance on the information provided by the use centre of mass. A walking assistant based on the KNN classifier to detect walking alteration on load carriage, is described in Chapter VI.

From fall-risk assessment to fall detection: inertial sensors in the clinical routine and daily life

Falls are caused by complex interaction between multiple risk factors which may be modified by age, disease and environment. A variety of methods and tools for fall risk assessment have been proposed, but none of which is universally accepted. Existing tools are generally not capable of providing a quantitative predictive assessment of fall risk. The need for objective, cost-effective and clinically applicable methods would enable quantitative assessment of fall risk on a subject-specific basis. Tracking objectively falls risk could provide timely feedback about the effectiveness of administered interventions enabling intervention strategies to be modified or changed if found to be ineffective. Moreover, some of the fundamental factors leading to falls and what actually happens during a fall remain unclear. Objectively documented and measured falls are needed to improve knowledge of fall in order to develop more effective prevention strategies and prolong independent living. In the last decade, several research groups have developed sensor-based automatic or semi-automatic fall risk assessment tools using wearable inertial sensors. This approach may also serve to detect falls. At the moment, i) several fall-risk assessment studies based on inertial sensors, even if promising, lack of a biomechanical model-based approach which could provide accurate and more detailed measurements of interests (e.g., joint moments, forces) and ii) the number of published real-world fall data of older people in a real-world environment is minimal since most authors have used simulations with healthy volunteers as a surrogate for real-world falls. With these limitations in mind, this thesis aims i) to suggest a novel method for the kinematics and dynamics evaluation of functional motor tasks, often used in clinics for the fall-risk evaluation, through a body sensor network and a biomechanical approach and ii) to define the guidelines for a fall detection algorithm based on a real-world fall database availability.

Gait analysis using a single wearable inertial measurement unit

Procedures for quantitative walking analysis include the assessment of body segment movements within defined gait cycles. Recently, methods to track human body motion using inertial measurement units have been suggested. It is not known if these techniques can be readily transferred to clinical measurement situations. This work investigates the aspects necessary for one inertial measurement unit mounted on the lower back to track orientation, and determine spatio-temporal features of gait outside the confines of a conventional gait laboratory. Apparent limitations of different inertial sensors can be overcome by fusing data using methods such as a Kalman filter. The benefits of optimizing such a filter for the type of motion are unknown. 3D accelerations and 3D angular velocities were collected for 18 healthy subjects while treadmill walking. Optimization of Kalman filter parameters improved pitch and roll angle estimates when compared to angles derived using stereophotogrammetry. A Weighted Fourier Linear Combiner method for estimating 3D orientation angles by constructing an analytical representation of angular velocities and allowing drift free integration is also presented. When tested this method provided accurate estimates of 3D orientation when compared to stereophotogrammetry. Methods to determine spatio-temporal features from lower trunk accelerations generally require knowledge of sensor alignment. A method was developed to estimate the instants of initial and final ground contact from accelerations measured by a waist mounted inertial device without rigorous alignment. A continuous wavelet transform method was used to filter and differentiate the signal and derive estimates of initial and final contact times. The technique was tested with data recorded for both healthy and pathologic (hemiplegia and Parkinson’s disease) subjects and validated using an instrumented mat. The results show that a single inertial measurement unit can assist whole body gait assessment however further investigation is required to understand altered gait timing in some pathological subjects.

Movement Analysis by means of inertial sensors: from bench to bedside

in the everyday clinical practice. Having this in mind, the choice of a simple setup would not be enough because, even if the setup is quick and simple, the instrumental assessment would still be in addition to the daily routine. The will to overcome this limit has led to the idea of instrumenting already existing and widely used functional tests. In this way the sensor based assessment becomes an integral part of the clinical assessment. Reliable and validated signal processing methods have been successfully implemented in Personal Health Systems based on smartphone technology. At the end of this research project there is evidence that such solution can really and easily used in clinical practice in both supervised and unsupervised settings. Smartphone based solution, together or in place of dedicated wearable sensing units, can truly become a pervasive and low-cost means for providing suitable testing solutions for quantitative movement analysis with a clear clinical value, ultimately providing enhanced balance and mobility support to an aging population.

Three-dimensional joint kinematics of swimming using body-worn inertial and magnetic sensors

Wearable inertial and magnetic measurements units (IMMU) are an important tool for underwater motion analysis because they are swimmer-centric, they require only simple measurement set-up and they provide the performance results very quickly. In order to estimate 3D joint kinematics during motion, protocols were developed to transpose the IMMU orientation estimation to a biomechanical model. The aim of the thesis was to validate a protocol originally propositioned to estimate the joint angles of the upper limbs during one-degree-of-freedom movements in dry settings and herein modified to perform 3D kinematics analysis of shoulders, elbows and wrists during swimming. Eight high-level swimmers were assessed in the laboratory by means of an IMMU while simulating the front crawl and breaststroke movements. A stereo-photogrammetric system (SPS) was used as reference. The joint angles (in degrees) of the shoulders (flexion-extension, abduction-adduction and internal-external rotation), the elbows (flexion-extension and pronation-supination), and the wrists (flexion-extension and radial-ulnar deviation) were estimated with the two systems and compared by means of root mean square errors (RMSE), relative RMSE, Pearson’s product-moment coefficient correlation (R) and coefficient of multiple correlation (CMC). Subsequently, the athletes were assessed during pool swimming trials through the IMMU. Considering both swim styles and all joint degrees of freedom modeled, the comparison between the IMMU and the SPS showed median values of RMSE lower than 8°, representing 10% of overall joint range of motion, high median values of CMC (0.97) and R (0.96). These findings suggest that the protocol accurately estimated the 3D orientation of the shoulders, elbows and wrists joint during swimming with accuracy adequate for the purposes of research. In conclusion, the proposed method to evaluate the 3D joint kinematics through IMMU was revealed to be a useful tool for both sport and clinical contexts.

Progettazione e sviluppo di un prototipo di dispositivo wearable per il monitoraggio dell'attivita elettro-meccanica del cuore

Il presente lavoro di tesi è finalizzato allo sviluppo di un dispositivo indossabile, e minimamente invasivo, in grado di registrare in maniera continua segnali legati all’attività elettromeccanica del muscolo cardiaco, al fine di rilevare eventuali anomalie cardiache. In tal senso il sistema non si limita alla sola acquisizione di un segnale ECG, ma è in grado di rilevare anche i toni cardiaci, ovvero le vibrazioni generate dalla chiusura delle valvole cardiache, la cui ampiezza è espressione della forza contrattile (funzione meccanica) del cuore. Il presente lavoro di tesi ha riguardato sia la progettazione che la realizzazione di un prototipo di tale dispositivo ed è stato svolto presso il laboratorio di Bioingegneria del Dipartimento di Medicina Specialistica Diagnostica e Sperimentale dell’Università di Bologna, sito presso l’Azienda Ospedaliero-Universitaria Policlinico Sant’Orsola-Malpighi. Il sistema finale consiste in un dispositivo applicabile al torace che, attraverso una serie di sensori, è in grado di rilevare dati legati alla meccanica del cuore (toni cardiaci), dati elettrici cardiaci (ECG) e dati accelerometrici di attività fisica. Nello specifico, il sensing dei toni cardiaci avviene attraverso un accelerometro in grado di misurare le vibrazioni trasmesse al torace. I tracciati, raccolti con l’ausilio di una piattaforma Arduino, vengono inviati, tramite tecnologia Bluetooth, ad un PC che, attraverso un applicativo software sviluppato in LabVIEW™, ne effettua l’analisi, il salvataggio e l’elaborazione in real-time, permettendo un monitoraggio wireless ed in tempo reale dello stato del paziente.

Wearable computing e body area network: Android e wristox2 come caso di studio

In questa tesi verranno affrontati due argomenti principali. Il primo sono le tecnologie wearable, comprendendo anche la notazione più generica di tecnologie bearable, che si stanno sempre più diffondendo negli ultimi anni; il secondo sono le BAN (Body Area Network), reti di sensori e dispositivi posti sul corpo umano, utilizzate per rendere possibile la comunicazione e l'interazione fra i device wearable. Si partirà da una trattazione di tipo generico degli argomenti, descrivendo l'architettura fisica delle tecnologie, con focalizzazione sull'aspetto informatico prevalentemente che su quello elettronico e telecomunicazionistico. Si parlerà degli attuali impieghi dei dispositivi e delle reti, e delle loro probabili evoluzioni future. Si introdurranno poi i protocolli di comunicazione principali e se ne analizzeranno le differenze, decretando se sia o meno conveniente puntare su uno o sull'altro rispetto alle esigenze di progetto. Verrà introdotto il sistema operativo Android, descrivendo la sua architettura e fornendo le informazioni basilari per comprendere al meglio il rapporto esistente con la tecnologia Bluetooth.

Un sistema di controllo accessi basato su tecnologie wearable

Negli ultimi anni il mondo ha assistito ad un'espansione esponenziale del mercato mobile, un settore che ha rivoluzionato le nostre vite e le nostre abitudini. Parallelamente, sono entrati in commercio i primi dispositivi commerciali dell'era dell'Internet delle Cose (Internet-of-Things), un paradigma secondo il quale oggetti utilizzati quotidianamente possono dialogare tra loro mediante Internet al fine di migliorare la vita personale e i processi produttivi aziendali. Un'applicazione pratica di Internet-of-Things è costituita dai dispositivi indossabili (wearable) capaci per mezzo di sensori di raccogliere dati sanitari, ambientali e fisici attorno a noi. I dispositivi indossabili attualmente in commercio permettono di collegarsi tramite protocolli e standard come WiFi e Bluetooth ad altri dispositivi, siano essi indossabili, smartphone o computer. Da questo concetto nasce l’idea di far comunicare un indossabile con altri dispositivi utilizzati in un contesto aziendale. In questo documento verrà preso in considerazione un tassello fondamentale nella gestione delle risorse umane e della sicurezza: il controllo degli accessi in un edificio e lo sblocco di un varco, sia esso un tornello, una porta o una serranda. Verrà quindi analizzato e progettato un sistema che possa effettuare le operazioni di timbratura e di apertura di varchi dall'orologio Apple Watch e da iPhone collegandosi ad un terminale dedicato.

Heart Failure Monitoring System Based on Wearable and Information Technologies

In Europe, Cardiovascular Diseases (CVD) are the leading source of death, causing 45% of all deceases. Besides, Heart Failure, the paradigm of CVD, mainly affects people older than 65. In the current aging society, the European MyHeart Project was created, whose mission is to empower citizens to fight CVD by leading a preventive lifestyle and being able to be diagnosed at an early stage. This paper presents the development of a Heart Failure Management System, based on daily monitoring of Vital Body Signals, with wearable and mobile technologies, for the continuous assessment of this chronic disease. The System makes use of the latest technologies for monitoring heart condition, both with wearable garments (e.g. for measuring ECG and Respiration); and portable devices (such as Weight Scale and Blood Pressure Cuff) both with Bluetooth capabilities

A novel context ontology to facilitate interoperation of semantic services in environments with wearable devices

The LifeWear-Mobilized Lifestyle with Wearables (Lifewear) project attempts to create Ambient Intelligence (AmI) ecosystems by composing personalized services based on the user information, environmental conditions and reasoning outputs. Two of the most important benefits over traditional environments are 1) take advantage of wearable devices to get user information in a nonintrusive way and 2) integrate this information with other intelligent services and environmental sensors. This paper proposes a new ontology composed by the integration of users and services information, for semantically representing this information. Using an Enterprise Service Bus, this ontology is integrated in a semantic middleware to provide context-aware personalized and semantically annotated services, with discovery, composition and orchestration tasks. We show how these services support a real scenario proposed in the Lifewear project.

A wearable device for recording of biopotentials and body movements

Long term recording of biomedical signals such as ECG, EMG, respiration and other information (e.g. body motion) can improve diagnosis and potentially monitor the evolution of many widespread diseases. However, long term monitoring requires specific solutions, portable and wearable equipment that should be particularly comfortable for patients. The key-issues of portable biomedical instrumentation are: power consumption, long-term sensor stability, comfortable wearing and wireless connectivity. In this scenario, it would be valuable to realize prototypes using available technologies to assess long-term personal monitoring and foster new ways to provide healthcare services. The aim of this work is to discuss the advantages and the drawbacks in long term monitoring of biopotentials and body movements using textile electrodes embedded in clothes. The textile electrodes were embedded into garments; tiny shirt and short were used to acquire electrocardiographic and electromyographic signals. The garment was equipped with low power electronics for signal acquisition and data wireless transmission via Bluetooth. A small, battery powered, biopotential amplifier and three-axes acceleration body monitor was realized. Patient monitor incorporates a microcontroller, analog-to-digital signal conversion at programmable sampling frequencies. The system was able to acquire and to transmit real-time signals, within 10 m range, to any Bluetooth device (including PDA or cellular phone). The electronics were embedded in the shirt resulting comfortable to wear for patients. Small size MEMS 3-axes accelerometers were also integrated. © 2011 IEEE.

Flexible Sensor for Wearable Vital Sign Monitoring System

In modern society, the body health is a very important issue to everyone. With the development of the science and technology, the new and developed body health monitoring device and technology will play the key role in the daily medical activities. This paper focus on making progress in the design of the wearable vital sign system. A vital sign monitoring system has been proposed and designed. The whole detection system is composed of signal collecting subsystem, signal processing subsystem, short-range wireless communication subsystem and user interface subsystem. The signal collecting subsystem is composed of light source and photo diode, after emiting light of two different wavelength, the photo diode collects the light signal reflected by human body tissue. The signal processing subsystem is based on the analog front end AFE4490 and peripheral circuits, the collected analog signal would be filtered and converted into digital signal in this stage. After a series of processing, the signal would be transmitted to the short-range wireless communication subsystem through SPI, this subsystem is mainly based on Bluetooth 4.0 protocol and ultra-low power System on Chip(SoC) nRF51822. Finally, the signal would be transmitted to the user end. After proposing and building the system, this paper focus on the research of the key component in the system, that is, the photo detector. Based on the study of the perovskite materials, a low temperature processed photo detector has been proposed, designed and researched. The device is made up of light absorbing layer, electron transporting and hole blocking layer, hole transporting and electron blocking layer, conductive substrate layer and metal electrode layer. The light absorbing layer is the important part of whole device, and it is fabricated by perovskite materials. After accepting the light, the electron-hole pair would be produced in this layer, and due to the energy level difference, the electron and hole produced would be transmitted to metal electrode and conductive substrate electrode through electron transporting layer and hole transporting layer respectively. In this way the response current would be produced. Based on this structure, the specific fabrication procedure including substrate cleaning; PEDOT:PSS layer preparation; pervoskite layer preparation; PCBM layer preparation; C60, BCP, and Ag electrode layer preparation. After the device fabrication, a series of morphological characterization and performance testing has been done. The testing procedure including film-forming quality inspection, response current and light wavelength analysis, linearity and response time and other optical and electrical properties testing. The testing result shows that the membrane has been fabricated uniformly; the device can produce obvious response current to the incident light with the wavelength from 350nm to 800nm, and the response current could be changed along with the light wavelength. When the light wavelength keeps constant, there exists a good linear relationship between the intensity of the response current and the power of the incident light, based on which the device could be used as the photo detector to collect the light information. During the changing period of the light signal, the response time of the device is several microseconds, which is acceptable working as a photo detector in our system. The testing results show that the device has good electronic and optical properties, and the fabrication procedure is also repeatable, the properties of the devices has good uniformity, which illustrates the fabrication method and procedure could be used to build the photo detector in our wearable system. Based on a series of testing results, the paper has drawn the conclusion that the photo detector fabricated could be integrated on the flexible substrate and is also suitable for the monitoring system proposed, thus made some progress on the research of the wearable monitoring system and device. Finally, some future prospect in system design aspect and device design and fabrication aspect are proposed.

Wearable cameras can reduce dietary under-reporting: doubly labelled water validation of a camera-assisted 24 h recall

Preliminary research has suggested that wearable cameras may reduce under-reporting of energy intake (EI) in self-reported dietary assessment. The aim of the present study was to test the validity of a wearable camera-assisted 24 h dietary recall against the doubly labelled water (DLW) technique. Total energy expenditure (TEE) was assessed over 15 d using the DLW protocol among forty adults (n 20 males, age 35 (sd 17) years, BMI 27 (sd 4) kg/m2 and n 20 females, age 28 (sd 7) years, BMI 22 (sd 2) kg/m2). EI was assessed using three multiple-pass 24 h dietary recalls (MP24) on days 2-4, 8-10 and 13-15. On the days before each nutrition assessment, participants wore an automated wearable camera (SenseCam (SC)) in free-living conditions. The wearable camera images were viewed by the participants following the completion of the dietary recall, and their changes in self-reported intakes were recorded (MP24+SC). TEE and EI assessed by the MP24 and MP24+SC methods were compared. Among men, the MP24 and MP24+SC measures underestimated TEE by 17 and 9%, respectively (P< 0.001 and P= 0.02). Among women, these measures underestimated TEE by 13 and 7%, respectively (P< 0.001 and P= 0.004). The assistance of the wearable camera (MP24+SC) reduced the magnitude of under-reporting by 8% for men and 6% for women compared with the MP24 alone (P< 0.001 and P< 0.001). The increase in EI was predominantly from the addition of 265 unreported foods (often snacks) as revealed by the participants during the image review. Wearable cameras enhance the accuracy of self-report by providing passive and objective information regarding dietary intake. High-definition image sensors and increased imaging frequency may improve the accuracy further.

Strain sensors with adjustable sensitivity by tailoring the microstructure of graphene aerogel/PDMS nanocomposites

Strain sensors with high elastic limit and high sensitivity are required to meet the rising demand for wearable electronics. Here, we present the fabrication of highly sensitive strain sensors based on nanocomposites consisting of graphene aerogel (GA) and polydimethylsiloxane (PDMS), with the primary focus being to tune the sensitivity of the sensors by tailoring the cellular microstructure through controlling the manufacturing processes. The resultant nanocomposite sensors exhibit a high sensitivity with a gauge factor of up to approximately 61.3. Of significant importance is that the sensitivity of the strain sensors can be readily altered by changing the concentration of the precursor (i.e., an aqueous dispersion of graphene oxide) and the freezing temperature used to process the GA. The results reveal that these two parameters control the cell size and cell-wall thickness of the resultant GA, which may be correlated to the observed variations in the sensitivities of the strain sensors. The higher is the concentration of graphene oxide, then the lower is the sensitivity of the resultant nanocomposite strain sensor. Upon increasing the freezing temperature from −196 to −20 °C, the sensitivity increases and reaches a maximum value of 61.3 at −50 °C and then decreases with a further increase in freezing temperature to −20 °C. Furthermore, the strain sensors offer excellent durability and stability, with their piezoresistivities remaining virtually unchanged even after 10 000 cycles of high-strain loading−unloading. These novel findings pave the way to custom design strain sensors with a desirable piezoresistive behavior.

Data processing of physiological sensor data and alarm determination utilising activity recognition

Current physiological sensors are passive and transmit sensed data to Monitoring centre (MC) through wireless body area network (WBAN) without processing data intelligently. We propose a solution to discern data requestors for prioritising and inferring data to reduce transactions and conserve battery power, which is important requirements of mobile health (mHealth). However, there is a problem for alarm determination without knowing the activity of the user. For example, 170 beats per minute of heart rate can be normal during exercising, however an alarm should be raised if this figure has been sensed during sleep. To solve this problem, we suggest utilising the existing activity recognition (AR) applications. Most of health related wearable devices include accelerometers along with physiological sensors. This paper presents a novel approach and solution to utilise physiological data with AR so that they can provide not only improved and efficient services such as alarm determination but also provide richer health information which may provide content for new markets as well as additional application services such as converged mobile health with aged care services. This has been verified by experimented tests using vital signs such as heart pulse rate, respiration rate and body temperature with a demonstrated outcome of AR accelerometer sensors integrated with an Android app.