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Littérature scientifique sur le sujet « Wearable wireless sensor »

Auteur : Grafiati

Publié le 4 juin 2021

Mis à jour le 7 février 2022

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Articles de revues sur le sujet "Wearable wireless sensor"

Park, Young-Geun, Sangil Lee et Jang-Ung Park. « Recent Progress in Wireless Sensors for Wearable Electronics ». Sensors 19, n^o 20 (9 octobre 2019) : 4353. http://dx.doi.org/10.3390/s19204353.

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The development of wearable electronics has emphasized user-comfort, convenience, security, and improved medical functionality. Several previous research studies transformed various types of sensors into a wearable form to more closely monitor body signals and enable real-time, continuous sensing. In order to realize these wearable sensing platforms, it is essential to integrate wireless power supplies and data communication systems with the wearable sensors. This review article discusses recent progress in wireless technologies and various types of wearable sensors. Also, state-of-the-art research related to the application of wearable sensor systems with wireless functionality is discussed, including electronic skin, smart contact lenses, neural interfaces, and retinal prostheses. Current challenges and prospects of wireless sensor systems are discussed.

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Song, Yu, Jihong Min, You Yu, Haobin Wang, Yiran Yang, Haixia Zhang et Wei Gao. « Wireless battery-free wearable sweat sensor powered by human motion ». Science Advances 6, n^o 40 (septembre 2020) : eaay9842. http://dx.doi.org/10.1126/sciadv.aay9842.

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Wireless wearable sweat biosensors have gained huge traction due to their potential for noninvasive health monitoring. As high energy consumption is a crucial challenge in this field, efficient energy harvesting from human motion represents an attractive approach to sustainably power future wearables. Despite intensive research activities, most wearable energy harvesters suffer from complex fabrication procedures, poor robustness, and low power density, making them unsuitable for continuous biosensing. Here, we propose a highly robust, mass-producible, and battery-free wearable platform that efficiently extracts power from body motion through a flexible printed circuit board (FPCB)–based freestanding triboelectric nanogenerator (FTENG). The judiciously engineered FTENG displays a high power output of ~416 mW m−2. Through seamless system integration and efficient power management, we demonstrate a battery-free triboelectrically driven system that is able to power multiplexed sweat biosensors and wirelessly transmit data to the user interfaces through Bluetooth during on-body human trials.

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Aqueeb, Ahsan, Sayan Roy, Yichun Ding, Obiora Onyilagha et Zhengtao Zhu. « On the Report of Performance Analysis of Electrospun Carbon Nanofibers based Strain Sensor for Applications in Human Motion Monitoring ». Applied Computational Electromagnetics Society 35, n^o 11 (4 février 2021) : 1324–25. http://dx.doi.org/10.47037/2020.aces.j.351131.

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Flexible and wearable sensors are currently being extensively used in versatile applications including wireless body area network. Specifically, such sensors are mostly incorporated to yield a linear response within their range of operations. A recently developed flexible and wearable resistive strain sensor made of electrospun carbon nanofibers has been reported with a gauge factor up to 72. In this paper, the performance of the strain sensor embedded in a polyurethane matrix was studied at first. A linear region of operation of such sensor was defined from direct measurements for wireless body area network applications. The equivalent analytical expressions were established and reported.

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Quwaider, Muhannad, et Subir Biswas. « Physical Context Detection using Wearable Wireless Sensor Networks ». Journal of Communications Software and Systems 4, n^o 3 (22 septembre 2008) : 191. http://dx.doi.org/10.24138/jcomss.v4i3.219.

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This paper presents the architecture of a wearable sensor network and a Hidden Markov Model (HMM) processingframework for stochastic identification of body postures andphysical contexts. The key idea is to collect multi-modal sensor data from strategically placed wireless sensors over a human subject’s body segments, and to process that using HMM in order to identify the subject’s instantaneous physical context. The key contribution of the proposed multi-modal approach is a significant extension of traditional uni-modal accelerometry in which only the individual body segment movements, without their relative proximities and orientation modalities, is used for physical context identification. Through real-life experiments with body mounted sensors it is demonstrated that while the unimodal accelerometry can be used for differentiating activityintensive postures such as walking and running, they are not effective for identification and differentiation between lowactivity postures such as sitting, standing, lying down, etc. In the proposed system, three sensor modalities namely acceleration, relative proximity and orientation are used for context identification through Hidden Markov Model (HMM) based stochastic processing. Controlled experiments using human subjects are carried out for evaluating the accuracy of the HMMidentified postures compared to a naïve threshold based mechanism over different human subjects.

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Mehmood, Amir, Adnan Nadeem, Kashif Rizwan, Nadeem Mahmood et Ahmad Waqas. « A Study of Wearable Bio-Sensor Technologies and Applications in Healthcare ». Sukkur IBA Journal of Computing and Mathematical Sciences 1, n^o 1 (30 juin 2017) : 67. http://dx.doi.org/10.30537/sjcms.v1i1.9.

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In today’s world the rapid advancements in Micro-Electromechanical Systems (MEMS) and Nano technology have improved almost all the aspects of daily life routine with the help of different smart devices such as smart phones, compact electronic devices etc. The prime example of these emerging developments is the development of wireless sensors for healthcare procedures. One kind of these sensors is wearable bio-sensors. In this paper, the technologies of two types of bio-sensors (ECG, EMG) are investigated and also compared with traditional ECG, EMG equipment. We have taken SHIMMERTM wireless sensor platform as an example of wearable biosensors technology. We have investigated the systems developed for analysis techniques with SHIMMERTM ECG and EMG wearable bio-sensors and these biosensors are used in continuous remote monitoring. For example, applications in continuous health monitoring of elderly people, critical chronic patients and Fitness & Fatigue observations. Nevertheless, early fall detection in older adults and weak patients, treatment efficacy assessment. This study not only provides the basic concepts of wearable wireless bio-sensors networks (WBSN), but also provides basic knowledge of different sensor platforms available for patient’s remote monitoring. Also various healthcare applications by using bio-sensors are discussed and in last comparison with traditional ECG and EMG is presented.

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Yun, Inyeol, Jinpyeo Jeung, Mijung Kim, Young-Seok Kim et Yoonyoung Chung. « Ultra-Low Power Wearable Infant Sleep Position Sensor ». Sensors 20, n^o 1 (20 décembre 2019) : 61. http://dx.doi.org/10.3390/s20010061.

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Numerous wearable sensors have been developed for a variety of needs in medical/healthcare/wellness/sports applications, but there are still doubts about their usefulness due to uncomfortable fit or frequent battery charging. Because the size or capacity of battery is the major factor affecting the convenience of wearable sensors, power consumption must be reduced. We developed a method that can significantly reduce the power consumption by introducing a signal repeater and a special switch that provides power only when needed. Antenna radiation characteristics are an important factor in wireless wearable sensors, but soft material encapsulation for comfortable fit results in poor wireless performance. We improved the antenna radiation characteristics by a local encapsulation patterning. In particular, ultra-low power operation enables the use of paper battery to achieve a very thin and flexible form factor. Also, we verified the human body safety through specific absorption rate simulations. With these methods, we demonstrated a wearable infant sleep position sensor. Infants are unable to call for help in unsafe situations, and it is not easy for caregivers to observe them all the time. Our wearable sensor detects infants’ sleep positions in real time and automatically alerts the caregivers when needed.

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Kovalska, Evgeniya, Anna Baldycheva et Andrey Somov. « Wireless graphene-enabled wearable temperature sensor ». Journal of Physics : Conference Series 1571 (juillet 2020) : 012001. http://dx.doi.org/10.1088/1742-6596/1571/1/012001.

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Lim, Hyo-Ryoung, Yun-Soung Kim, Shinjae Kwon, Musa Mahmood, Young-Tae Kwon, Yongkuk Lee, Soon Min Lee et Woon-Hong Yeo. « Wireless, Flexible, Ion-Selective Electrode System for Selective and Repeatable Detection of Sodium ». Sensors 20, n^o 11 (10 juin 2020) : 3297. http://dx.doi.org/10.3390/s20113297.

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Wireless, flexible, ion-selective electrodes (ISEs) are of great interest in the development of wearable health monitors and clinical systems. Existing film-based electrochemical sensors, however, still have practical limitations due to poor electrical contact and material–interfacial leakage. Here, we introduce a wireless, flexible film-based system with a highly selective, stable, and reliable sodium sensor. A flexible and hydrophobic composite with carbon black and soft elastomer serves as an ion-to-electron transducer offering cost efficiency, design simplicity, and long-term stability. The sensor package demonstrates repeatable analysis of selective sodium detection in saliva with good sensitivity (56.1 mV/decade), stability (0.53 mV/h), and selectivity coefficient of sodium against potassium (−3.0). The film ISEs have an additional membrane coating that provides reinforced stability for the sensor upon mechanical bending. Collectively, the comprehensive study of materials, surface chemistry, and sensor design in this work shows the potential of the wireless flexible sensor system for low-profile wearable applications.

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Andersson, L. Mattias, Hironao Okada, Ryotaro Miura, Yi Zhang, Koji Yoshioka, Hiroshi Aso et Toshihiro Itoh. « Wearable wireless estrus detection sensor for cows ». Computers and Electronics in Agriculture 127 (septembre 2016) : 101–8. http://dx.doi.org/10.1016/j.compag.2016.06.007.

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Jiang, Jie, Yun Liu, Fuxing Song, Ronghao Du et Mengsen Huang. « The Routing Algorithm Based on Fuzzy Logic Applied to the Individual Physiological Monitoring Wearable Wireless Sensor Network ». Journal of Electrical and Computer Engineering 2015 (2015) : 1–7. http://dx.doi.org/10.1155/2015/546425.

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In recent years, the research of individual wearable physiological monitoring wireless sensor network is in the primary stage. The monitor of physiology and geographical position used in wearable wireless sensor network requires performances such as real time, reliability, and energy balance. According to these requirements, this paper introduces a design of individual wearable wireless sensor network monitoring system; what is more important, based on this background, this paper improves the classical Collection Tree Protocol and puts forward the improved routing protocol F-CTP based on the fuzzy logic routing algorithm. Simulation results illustrate that, with the F-CTP protocol, the sensor node can transmit data to the sink node in real time with higher reliability and the energy of the nodes consumes balance. The sensor node can make full use of network resources reasonably and prolong the network life.

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Thèses sur le sujet "Wearable wireless sensor"

Lapinski, Michael Tomasz. « A wearable, wireless sensor system for sports medicine ». Thesis, Massachusetts Institute of Technology, 2008. http://hdl.handle.net/1721.1/46581.

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Thesis (S.M.)--Massachusetts Institute of Technology, School of Architecture and Planning, Program in Media Arts and Sciences, 2008.
Includes bibliographical references (p. 135-139).
This thesis describes a compact, wireless, wearable system that measures, for purposes of biomechanical analysis, signals indicative of forces, torques and other descriptive and evaluative features that the human body undergoes during bursts of extreme physical activity (such as during athletic performance). Standard approaches leverage high speed camera systems, which need significant infrastructure and provide limited update rates and dynamic accuracy, to make these measurements. This project uses 6 degree-of-freedom inertial measurement units worn on various segments of an athlete's body to directly make these dynamic measurements. A combination of low and high G sensors enables sensitivity for slow and fast motion, and the addition of a compass helps in tracking joint angles. Data from the battery-powered nodes is acquired using a custom wireless protocol over an RF link. This data, along with rigorous calibration data, is processed on a PC, with an end product being precise angular velocities and accelerations that can be employed during biomechanical analysis to gain a better understanding of what occurs during activity. The focus of experimentation was baseball pitching and batting at the professional level. Several pitchers and batters were instrumented with the system and data was gathered during several pitches or swings. The data was analyzed, and the results of this analysis are presented in this thesis. The dynamic results are more precise than from other camera based systems and also offer the measurement of metrics that are not available from any other system, providing the opportunity for furthering sports medicine research. System performance and results are evaluated, and ideas for future work and system improvements are presented.
by Michael Tomasz Lapinski.
S.M.

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Liu, Congrui. « Wearable Fall Detection using Barometric Pressure Sensor ». Thesis, Mittuniversitetet, Avdelningen för elektronikkonstruktion, 2017. http://urn.kb.se/resolve?urn=urn:nbn:se:miun:diva-29968.

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Wearable wireless sensor devices, which are implemented by deploying sensor nodes on objects, are widely utilized in a broad field of applica-tions, especially in the healthcare system for improving the quality of life or monitoring different types of physical data from the observed objects. The aim of this study is to design an in-home, small-size and long-term wearable fall detection system in wireless network by using barometric pressure sensing for elderly or patient who needs healthcare monitoring. This threshold-based fall detection system is to measure the altitude of different positions on the human body, and detect the fall event from that altitude information. As a surveillance system, it would trigger an alert when the fall event occurs so that to protect people from the potential life risk by immediate rescue and treatment. After all the performances evaluation, the measurement result shows that standing, sitting and fall state was detected with 100% accuracy and lying on bed state was detected with 93.3% accuracy by using this wireless fall detection system. Furthermore, this system with low power consumption on battery-node can operate continuously up to 150 days.

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Strauss, Marc D. « HandWave : design and manufacture of a wearable wireless skin conductance sensor and housing ». Thesis, Massachusetts Institute of Technology, 2005. http://hdl.handle.net/1721.1/32944.

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Thesis (S.B.)--Massachusetts Institute of Technology, Dept. of Mechanical Engineering, 2005.
Includes bibliographical references (p. 48-49).
This thesis report details the design and manufacture of HandWave, a wearable wireless Bluetooth skin conductance sensor, and dedicated housing. The HandWave collects Electrodermal Activity (EDA) data by measuring skin conductance over a pair of electrodes. The EDA data signal is used to infer the excitement level of the subject. The injection-molded housing is affixed to the wrist of the subject, and the electrodes are positioned on the fingers and/or palm. The HandWave amplification board utilizes a PIC to sample the EDA signal level with an analog-to-digital converter (ADC), control the gain of the amplification circuitry, and pass the data to a Bluetooth module. The Bluetooth module manages the wireless connection to a remote base-station and streams the EDA data over this link. Driver software on the base-station recomposes the EDA signal into standard units of conductance for display or further analysis.
by Marc D. Strauss.
S.B.

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Celik, Numan. « Wireless graphene-based electrocardiogram (ECG) sensor including multiple physiological measurement system ». Thesis, Brunel University, 2017. http://bura.brunel.ac.uk/handle/2438/15698.

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In this thesis, a novel graphene (GN) based electrocardiogram (ECG) sensor is designed, constructed and tested to validate the concept of coating GN, which is a highly electrically conductive material, on Ag substrates of conventional electrodes. The background theory, design, experiments and results for the proposed GN-based ECG sensor are also presented. Due to the attractive electrical and physical characteristics of graphene, a new ECG sensor was investigated by coating GN onto itself. The main focus of this project was to examine the effect of GN on ECG monitoring and to compare its performance with conventional methods. A thorough investigation into GN synthesis on Ag substrate was conducted, which was accompanied by extensive simulation and experimentation. A GN-enabled ECG electrode was characterised by Raman spectroscopy, scanning electron microscopy along with electrical resistivity and conductivity measurements. The results obtained from the GN characteristic experimentation on Raman spectroscopy, detected a 2D peak in the GN-coated electrode, which was not observed with the conventional Ag/AgCl electrode. SEM characterisation also revealed that a GN coating smooths the surface of the electrode and hence, improves the skin-to-electrode contact. Furthermore, a comparison regarding the electrical conductivity calculation was made between the proposed GN-coated electrodes and conventional Ag/AgCl ones. The resistance values obtained were 212.4 Ω and 28.3 Ω for bare and GN-coated electrodes, respectively. That indicates that the electrical conductivity of GN-based electrodes is superior and hence, it is concluded that skin-electrode contact impedance can be lowered by their usage. Additional COMSOL simulation was carried out to observe the effect of an electrical field and surface charge density using GN-coated and conventional Ag/AgCl electrodes on a simplified human skin model. The results demonstrated the effectiveness of the addition of electrical field and surface charge capabilities and hence, coating GN on Ag substrates was validated through this simulation. This novel ECG electrode was tested with various types of electrodes on ten different subjects in order to analyse the obtained ECG signals. The experimental results clearly showed that the proposed GN-based electrode exhibits the best performance in terms of ECG signal quality, detection of critical waves of ECG morphology (P-wave, QRS complex and T-wave), signal-to-noise ratio (SNR) with 27.0 dB and skin-electrode contact impedance (65.82 kΩ at 20 Hz) when compared to those obtained by conventional a Ag/AgCl electrode. Moreover, this proposed GN-based ECG sensor was integrated with core body temperature (CBT) sensor in an ear-based device, which was designed and printed using 3D technology. Subsequently, a finger clipped photoplethysmography (PPG) sensor was integrated with the two-sensors in an Arduino based data acquisition system, which was placed on the subject's arm to enable a wearable multiple physiological measurement system. The physiological information of ECG and CBT was obtained from the ear of the subject, whilst the PPG signal was acquired from the finger. Furthermore, this multiple physiological signal was wirelessly transmitted to the smartphone to achieve continuous and real-time monitoring of physiological signals (ECG, CBT and PPG) on a dedicated app developed using the Java programming language. The proposed system has plenty of room for performance improvement and future development will make it adaptabadaptable, hence being more convenient for the users to implement other applications than at present.

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Shaban, Heba Ahmed. « A Novel Highly Accurate Wireless Wearable Human Locomotion Tracking and Gait Analysis System via UWB Radios ». Diss., Virginia Tech, 2010. http://hdl.handle.net/10919/27562.

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Gait analysis is the systematic study of human walking. Clinical gait analysis is the process by which quantitative information is collected for the assessment and decision-making of any gait disorder. Although observational gait analysis is the therapistâ s primary clinical tool for describing the quality of a patientâ s walking pattern, it can be very unreliable. Modern gait analysis is facilitated through the use of specialized equipment. Currently, accurate gait analysis requires dedicated laboratories with complex settings and highly skilled operators. Wearable locomotion tracking systems are available, but they are not sufficiently accurate for clinical gait analysis. At the same time, wireless healthcare is evolving. Particularly, ultra wideband (UWB) is a promising technology that has the potential for accurate ranging and positioning in dense multi-path environments. Moreover, impulse-radio UWB (IR-UWB) is suitable for low-power and low-cost implementation, which makes it an attractive candidate for wearable, low-cost, and battery-powered health monitoring systems. The goal of this research is to propose and investigate a full-body wireless wearable human locomotion tracking system using UWB radios. Ultimately, the proposed system should be capable of distinguishing between normal and abnormal gait, making it suitable for accurate clinical gait analysis.
Ph. D.

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Gaszczyk, Dariusz. « Wearable Assistant For Monitoring Solitary People ». Thesis, Blekinge Tekniska Högskola, Institutionen för tillämpad signalbehandling, 2016. http://urn.kb.se/resolve?urn=urn:nbn:se:bth-14592.

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Master Thesis presents the system consisting of software and components of Arduinoplatform along with modules compatible with it, intended for use indoor. The device fulfils thefollowing requirements which are: to ensure privacy preservation, low energy consumptionand the wireless nature. This thesis reports the development of a prototype that would ensure step detection,posture detection, indoor localization, tumble detection and heart rate detection using themicrocontroller, AltIMU-10 v4 module, heart rate monitor, WiFi module and battery. Veryimportant part of the thesis is algorithm, which uses comparison function. Thanks to thewireless nature of a prototype, the system collects data regardless of an environment and sendthem directly to every device supported by Microsoft Windows platform, Linux platform orOS X platform, which are monitored by the supervisor, who takes care of the solitary person. The main contributions of the prototype are: indoor localization, identification andclassification of occurring situations and monitoring vital signs of the solitary person. To ensure indoor localization the prototype must collect data from accelerometer. Ofcourse data from AltIMU-10 v4 module in basic form are useless for the supervisor, so thealgorithm, using by the prototype, is programmed to processing and filtering it. Algorithm is also used to identification and classification occurring situations. Datafrom accelerometer are processed by it and compared with the created pattern. Monitoring vital signs of the solitary person are more complicated function, because itrequires not only data from accelerometer, but also from heart rate monitor. This sensor isusing to the analyzing condition of the patient when dangerous situation occurs.

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Moravec, Luboš. « Nositelná elektronika ». Master's thesis, Vysoké učení technické v Brně. Fakulta elektrotechniky a komunikačních technologií, 2016. http://www.nusl.cz/ntk/nusl-241150.

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This master’s thesis deals with the explanation of the concept of smart wearables and the different application possibilities. This work also includes examples of finished demonstration devices in this category. Part of this work is devoted to guide the selection of appropriate components for the design of new equipment in the category of smart wearable. The result of this thesis is designed wearable and charging station. This device is able to read user input and display that information on a smart device running under Android system connected via Bluetooth technology.

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Palacios, Sebastian R. « A smart wireless integrated module (SWIM) on organic substrates using inkjet printing technology ». Thesis, Georgia Institute of Technology, 2014. http://hdl.handle.net/1853/51906.

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This thesis investigates inkjet printing of fully-integrated modules fabricated on organic substrates as a system-level solution for ultra-low-cost and eco-friendly mass production of wireless sensor modules. Prototypes are designed and implemented in both traditional FR-4 substrate and organic substrate. The prototype on organic substrate is referred to as a Smart Wireless Integrated Module (SWIM). Parallels are drawn between FR-4 manufacturing and inkjet printing technology, and recommendations are discussed to enable the potential of inkjet printing technology. Finally, this thesis presents novel applications of SWIM technology in the area of wearable and implantable electronics. Chapter 1 serves as an introduction to inkjet printing technology on organic substrates, wireless sensor networks (WSNs), and the requirements for low-power consumption, low-cost, and eco-friendly technology. Chapter 2 discusses the design of SWIM and its implementation using traditional manufacturing techniques on FR-4 substrate. Chapter 3 presents a benchmark prototype of SWIM on paper substrate. Challenges in the manufacturing process are addressed, and solutions are proposed which suggest future areas of research in inkjet printing technology. Chapter 4 presents novel applications of SWIM technology in the areas of implantable and wearable electronics. Chapter 5 concludes the thesis by discussing the importance of this work in creating a bridge between current inkjet printing technology and its future.

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Ferreira, Gonzalez Javier. « Textile-enabled Bioimpedance Instrumentation for Personalised Health Monitoring Applications ». Licentiate thesis, KTH, Medicinska sensorer, signaler och system (MSSS), 2013. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-120373.

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A growing number of factors, including the costs, technological advancements, an ageing population, and medical errors are leading industrialised countries to invest in research on alternative solutions to improving their health care systems and increasing patients’ life quality. Personal Health System (PHS) solutions envision the use of information and communication technologies that enable a paradigm shift from the traditional hospital-centred healthcare delivery model toward a preventive and person-centred approach. PHS offers the means to follow patient health using wearable, portable or implantable systems that offer ubiquitous, unobtrusive bio-data acquisition, allowing remote access to patient status and treatment monitoring. Electrical Bioimpedance (EBI) technology is a non-invasive, quick and relatively affordable technique that can be used for assessing and monitoring different health conditions, e.g., body composition assessments for nutrition. EBI technology combined with state-of-the-art advances in sensor and textile technology are fostering the implementation of wearable bioimpedance monitors that use functional garments for the implementation of personalised healthcare applications. This research studies the development of a portable EBI spectrometer that can use dry textile electrodes for the assessment of body composition for the purposes of clinical uses. The portable bioimpedance monitor has been developed using the latest advances in system-on-chip technology for bioimpedance spectroscopy instrumentation. The obtained portable spectrometer has been validated against commercial spectrometer that performs total body composition assessment using functional textrode garments. The development of a portable Bioimpedance spectrometer using functional garments and dry textile electrodes for body composition assessment has been shown to be a feasible option. The availability of such measurement systems bring closer the real implementation of personalised healthcare systems.

QC 20130405

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Lapinski, Michael Tomasz. « A platform for high-speed biomechanical analysis using wearable wireless sensors ». Thesis, Massachusetts Institute of Technology, 2013. http://hdl.handle.net/1721.1/91852.

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Thesis: Ph. D., Massachusetts Institute of Technology, School of Architecture and Planning, Program in Media Arts and Sciences, 2013.
116
Page 276 blank. Cataloged from PDF version of thesis.
Includes bibliographical references (pages 263-275).
Humanity's desire to capture and understand motion started in 1878 and has continually evolved. Today, the best-of- breed technology for capturing motion are marker based optical systems that leverage high speed cameras. While these systems are excellent at providing positional information, they suffer from an innate inability to accurately provide fundamental parameters such as velocity and acceleration. The problem is further compounded when the target of capture is high-speed human motion. When applied to biomechanical study, this inaccuracy is magnified when higher order parameters, such as torque and force, are calculated using optical information. This dissertation presents a a first-of-its-kind wearable dual-range inertial sensor platform that allows end-to-end investigation of high level biomechanical parameters. The platform takes a novel approach by providing these parameters more accurately and at a higher fidelity than the current state of the art.The dual-range sensing approach allows accurate capture of both slow-moving motion and rapid movement which pushes the limits of human ability. The platform addresses inherent problems with scaling clinical biomechanical analysis to tens-of-thousands of trials using the sensor platform's data. This end-to-end approach provides mechanisms for rapid player instrumentation, en masse data translation and calculation of clinically relevant joint forces and torques. I present design details for this platform along with kinematic testing and some early biomechanical insight gleamed from system measurements.
by Michael T. Lapinski.
Ph. D.

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Livres sur le sujet "Wearable wireless sensor"

Danilo, De Rossi, et SpringerLink (Online service), dir. Wearable Monitoring Systems. Boston, MA : Springer Science+Business Media, LLC, 2011.

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International Conference on "Smart Materials, Structures, and Systems" (4th 2012 Terme, Italy). Wearable/wireless body sensor networks for healthcare applications : Selected, peer reviewed papers from the Symposium I "Progress in wearable/wireless and implantable body sensor networks for healthcare applications" of CIMTEC 2012 - 4th International Conference "Smart Materials, Structures and Systems" held in Montecatini Terme, Italy, June 10-14, 2012. Durnten-Zurich : Trans Tech, 2013.

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Fortino, Giancarlo, Raffaele Gravina et Stefano Galzarano. Wearable Computing : From Modeling to Implementation of Wearable Systems Based on Body Sensor Networks. Wiley & Sons, Incorporated, John, 2018.

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Fortino, Giancarlo, Raffaele Gravina et Stefano Galzarano. Wearable Computing : From Modeling to Implementation of Wearable Systems based on Body Sensor Networks. Wiley-Interscience, 2018.

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Velez, Fernando José, et Fardin Derogarian Miyandoab, dir. Wearable Technologies and Wireless Body Sensor Networks for Healthcare. Institution of Engineering and Technology, 2019. http://dx.doi.org/10.1049/pbhe011e.

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Bonfiglio, Annalisa, et Danilo De Rossi. Wearable Monitoring Systems. Springer, 2014.

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Wearable Sensors : Fundamentals, Implementation and Applications. Elsevier Science & Technology Books, 2014.

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Sazonov, Edward. Wearable Sensors : Fundamentals, Implementation and Applications. Elsevier Science & Technology Books, 2014.

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Sazonov, Edward. Wearable Sensors : Fundamentals, Implementation and Applications. Elsevier Science & Technology Books, 2020.

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Chapitres de livres sur le sujet "Wearable wireless sensor"

Gomha, Siddig, et Khalid M. Ibrahim. « Generic Design and Advances in Wearable Sensor Technology ». Dans Emerging Wireless Communication and Network Technologies, 155–71. Singapore : Springer Singapore, 2018. http://dx.doi.org/10.1007/978-981-13-0396-8_9.

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Kumar, Vaishna S., Kavan Gangadhar Acharya, B. Sandeep, T. Jayavignesh et Ashvini Chaturvedi. « Wearable Sensor-Based Human Fall Detection Wireless System ». Dans Wireless Communication Networks and Internet of Things, 217–34. Singapore : Springer Singapore, 2018. http://dx.doi.org/10.1007/978-981-10-8663-2_23.

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Murao, Kazuya, Tsutomu Terada et Shojiro Nishio. « Toward Construction of Wearable Sensing Environments ». Dans Wireless Sensor Network Technologies for the Information Explosion Era, 207–30. Berlin, Heidelberg : Springer Berlin Heidelberg, 2010. http://dx.doi.org/10.1007/978-3-642-13965-9_7.

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Rathee, Anu, T. Poongodi, Monika Yadav et Balamurugan Balusamy. « Internet of Things in Healthcare Wearable and Implantable Body Sensor Network (WIBSNs) ». Dans Soft Computing in Wireless Sensor Networks, 193–224. Boca Raton : Taylor & Francis, a CRC title, part of the Taylor & Francis imprint, a member of the Taylor & Francis Group, the academic division of T&F Informa, plc, 2018. : Chapman and Hall/CRC, 2018. http://dx.doi.org/10.1201/9780429438639-9.

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Wong, A. C. W. « Ultra Low Power Wireless SoC Design for Wearable BAN ». Dans Efficient Sensor Interfaces, Advanced Amplifiers and Low Power RF Systems, 239–54. Cham : Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-21185-5_14.

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Kouris, Ioannis, et Dimitris Koutsouris. « Activity Recognition Using Smartphones and Wearable Wireless Body Sensor Networks ». Dans Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, 32–37. Berlin, Heidelberg : Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-29734-2_5.

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Valchinov, E. S., et N. E. Pallikarakis. « A wearable wireless ECG sensor : a design with a minimal number of parts ». Dans XII Mediterranean Conference on Medical and Biological Engineering and Computing 2010, 288–91. Berlin, Heidelberg : Springer Berlin Heidelberg, 2010. http://dx.doi.org/10.1007/978-3-642-13039-7_72.

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Poongodi, T., Anu Rathee, R. Indrakumari et P. Suresh. « IoT Sensing Capabilities : Sensor Deployment and Node Discovery, Wearable Sensors, Wireless Body Area Network (WBAN), Data Acquisition ». Dans Intelligent Systems Reference Library, 127–51. Cham : Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-33596-0_5.

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Sun, Ying. « Design of Low Cost Human ADL Signal Acquire System Based on Wireless Wearable MEMS Sensor ». Dans Advances in Computer Science, Intelligent System and Environment, 703–7. Berlin, Heidelberg : Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-23777-5_113.

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Yuan, Jian, et Kok Kiong Tan. « Inexpensive and Power-Efficient Wireless Health Monitoring System for the Aging Population ». Dans Wearable Electronics Sensors, 107–33. Cham : Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-18191-2_5.

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Actes de conférences sur le sujet "Wearable wireless sensor"

Pleskachev, V. V. « Wearable wireless ECG sensor ». Dans 2017 Progress In Electromagnetics Research Symposium - Spring (PIERS). IEEE, 2017. http://dx.doi.org/10.1109/piers.2017.8262028.

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Zhang, Zehao, Lin Peng, He Wang, Jin Sun, Tao Chang et Ling Zhuo. « A wearable computer wireless sensor network ». Dans 2017 IEEE Conference on Energy Internet and Energy System Integration (EI2). IEEE, 2017. http://dx.doi.org/10.1109/ei2.2017.8245389.

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Ahola, Tom, Pekka Korpinen, Juha Rakkola, Teemu Ramo, Jukka Salminen et Jari Savolainen. « Wearable FPGA Based Wireless Sensor Platform ». Dans 2007 29th Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE, 2007. http://dx.doi.org/10.1109/iembs.2007.4352782.

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Rault, Tifenn, Abdelmadjid Bouabdallah, Yacine Challal et Frederic Marin. « Energy-efficient architecture for wearable sensor networks ». Dans 2014 Wireless Days (WD). IEEE, 2014. http://dx.doi.org/10.1109/wd.2014.7020803.

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Ma, Zheren, Brandon C. Li et Zeyu Yan. « Wearable driver drowsiness detection using electrooculography signal ». Dans 2016 IEEE Topical Conference on Wireless Sensors and Sensor Networks (WiSNet). IEEE, 2016. http://dx.doi.org/10.1109/wisnet.2016.7444317.

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Kumar, Neelesh, Sasan Haghani et Devdas Shetty. « Wearable Wireless Inertial Sensors for Estimation of Gait Parameters and its Integration With Portable Harness Ambulatory System for Rehabilitation ». Dans ASME 2014 International Mechanical Engineering Congress and Exposition. American Society of Mechanical Engineers, 2014. http://dx.doi.org/10.1115/imece2014-38028.

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There is a growing demand for quantifying the performance and efficacy of rehabilitation programs. Researchers are advocating home based rehabilitation devices and continuous monitoring of patients status in real time through wearable sensors. This paper investigates the use of inertial measurement sensors for recording the dynamic gait status. In order to facilitate long term recording and minimal interface of recording devices, these MEMS sensors are advantageous in many ways over the conventional laboratory methods. Portable Harness Ambulatory System (PHAS) can be effectively used in home environments with minimal assistance for gait rehabilitation. This paper addresses the stages of mechatronic integration of a prototype of PHAS with an aim for early gait rehabilitation of elderly and stroke survivors without fear of falling. Sensors modules comprised of accelerometer and gyroscope were developed. X-bee wireless communication protocol is used for transmitting the gait data for computer storage. Gait experiments with wireless sensor modules attached to shoulder, wrist, thigh and ankle joints of normal human subjects were conducted for slow and fast walking speed. The inertial measurement sensors provide information on the range of motion, gait speed, and orientation. Experimental results prove that sensor modules were successfully able to acquire and record the gait information wirelessly. These sensor modules can also be integrated in the PHAS prototype. The paper outlines the results of initial research and discusses possible alternatives.

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Saranraj, A. « Wearable-sensor based wireless braille natural keypad ». Dans 2nd International Conference on Computer and Automation Engineering (ICCAE 2010). IEEE, 2010. http://dx.doi.org/10.1109/iccae.2010.5452026.

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Pierleoni, Paola, Alberto Belli, Lorenzo Palma, Michele Paoletti, Sara Raggiunto et Federica Pinti. « Postural stability evaluation using wearable wireless sensor ». Dans 2019 IEEE 23rd International Symposium on Consumer Technologies (ISCT). IEEE, 2019. http://dx.doi.org/10.1109/isce.2019.8901040.

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Khan, Jamal Ahmad, Haroon Ali Akbar, Usama Pervaiz et Osman Hassan. « A wearable wireless sensor for cardiac monitoring ». Dans 2016 IEEE 13th International Conference on Wearable and Implantable Body Sensor Networks (BSN). IEEE, 2016. http://dx.doi.org/10.1109/bsn.2016.7516233.

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Morris, Karcher, Minghui Zhao, Jenny Lam, Garth Jacobsen, Santiago Horgan et Frank E. Talke. « A Wearable Neck Measurement Device and Monitoring System to Improve Ergonomic Performance of Surgeons ». Dans ASME 2019 28th Conference on Information Storage and Processing Systems. American Society of Mechanical Engineers, 2019. http://dx.doi.org/10.1115/isps2019-7513.

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Abstract The long-term health of a surgeon is significantly affected by repetitive tasks and positions assumed during surgery. In order to evaluate neck positions throughout surgery, a novel wireless neck measurement system has been designed and developed. Extension, protraction, and rotation data of the neck are captured with accelerometers and flex sensors. Data is transmitted wirelessly and processed utilizing MATLAB. Sensor results are evaluated and compared with the goal to improve the ergonomic behavior of surgeons.

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Rapports d'organisations sur le sujet "Wearable wireless sensor"

Chon, Ki, et Yitzhak Mendelson. Wearable Wireless Sensor for Multi-Scale Physiological Monitoring. Fort Belvoir, VA : Defense Technical Information Center, octobre 2013. http://dx.doi.org/10.21236/ada590832.

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