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Pantelopoulos, Alexandros A. "¿¿¿¿¿¿¿¿¿¿¿¿PROGNOSIS: A WEARABLE SYSTEM FOR HEALTH MONITORING OF PEOPLE AT RISK." Wright State University / OhioLINK, 2010. http://rave.ohiolink.edu/etdc/view?acc_num=wright1284754643.
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Hellström, Per Anders Rickard. "Wireless Wearable Measurement System Based on Pedobarography for Monitoring of Health." Licentiate thesis, Mälardalens högskola, Inbyggda system, 2016. http://urn.kb.se/resolve?urn=urn:nbn:se:mdh:diva-32101.
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Health care costs have increased over the last decades due to an ageing population. Therefore, research in personal health monitoring (PHM) has increased in response to this. PHM has advantages such as mobility (monitoring of health at work or at home), early detection of health problems enabling preventive health measures and a reduction of health care cost. Human motion analysis, using for example inertial measurement units and pedobarography, is an important subcategory of PHM. Pedobarography (PBG) is the study of pressure fields acting between the plantar surface of the foot and a supporting surface. Gait and posture analysis, prosthetics evaluation and monitoring of recovery from injury or disease are examples of PBG applications. Portable PBG can be performed using force sensing resistors built into the insole inside the shoe. In accordance with this, the research goal for this licentiate thesis is to design, build and evaluate a wireless wearable measurement system based on pedobarography for monitoring of health. In order to fulfil the objectives of the research, literature studies were done and problems with existing in-shoe system solutions were identified. Thus, it was found that further opportunities existed for new designs of PBG systems which take these problems into account. Cross-sectional test case studies were used for validation. The research area is multidisciplinary and encompasses biomedical measurements, electronics and computer science. The main research contributions include design and implementation of a PBG measurement system consisting of commercial off the shelf components, a novel method for selecting measurement samples for weight estimation of carried load during walk, and a novel method for analysing walking intensity using force-time integrals at the toe-off phase of the step. The research results suggest that the new PBG system, in combination with the two novel analysing methods, are suitable for use in wearable systems for monitoring of health. Personal health measurements are done to help decision making related to health. Thus, the future work will strive towards designing different decision support systems.Kostnaderna för vår hälsovård har ökat de senaste årtiondena på grund av att vi lever allt längre. Till följd av detta har forskning inom personlig hälsomonitorering (PHM) ökat. PHM medför fördelar såsom rörlighet (hälsoövervakning på jobbet och i hemmet), tidig upptäckt av hälsoproblem medför möjlighet till åtgärd i ett tidigt skede samt en minskning av kostnaderna för hälsovård. Analys av människors rörelser, med hjälp av till exempel tröghetsmätare och pedobarografi, är en viktig underkategori inom PHM. Pedobarografi (PBG) är studien av tryckfält som uppstår på grund av krafter som verkar mellan fotens undersida och en uppbärande yta. Analys av gångstil och kroppshållning, utvärdering av proteser samt monitorering av återhämtning från skada eller sjukdom är exempel på tillämpningar av PBG. Portabel PBG kan exempelvis utföras med hjälp av resistiva kraftsensorer implementerade i skors inläggssulor. I överrensstämmelse med detta är målet för forskningen i den här licentiatavhandlingen att designa, bygga och utvärdera ett trådlöst bärbart mätsystem baserat på pedobarografi för övervakning av hälsa. För att uppfylla forskningsmålet utfördes litteraturstudier och problem med existerande skobaserade system identifierades. Tvärsnittsstudier användes vid valideringen. Forskningsområdet är tvärvetenskapligt och omfattar biomedicinska mätningar, elektronik och datavetenskap. De främsta vetenskapliga bidragen inkluderar design och implementering av ett pedobarografiskt mätsystem bestående av öppet tillgängliga komponenter, en ny metod för att välja ut uppmätta värden för uppskattning av vikt av buren last under gång, samt en ny analysmetod för gångintensitet med hjälp av kraft-tidsintegraler i stegets avstampsfas. Forskningsresultaten implicerar att det nya pedobarografisystemet, i kombination med de två nya analysmetoderna, är lämpliga att användas i bärbara system för övervakning av hälsa. Mätningar vid personlig hälsomonitorering utförs för att hjälpa till vid beslutsfattande som rör hälsa. Följaktligen strävar framtida forskning mot design av olika beslutsstödsystem.
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Abbasi, Saddedine. "Critical evaluation and novel design of a non-invasive and wearable health monitoring system." Thesis, Brunel University, 2008. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.553648.
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This study is about developing a non-invasive wearable health-monitoring system. The project aims to achieve miniaturisation as much as possible, using nanotechnology. The achieved results of the project are nothing but conceptual images of a convertible watch. The system is a non-invasive health measurement system. An important part of the study is researching the automation of blood pressure measurement by means of experiments which test the effect of exterior factors on blood pressure level. These experiments have been held to improve the automation and simplicity of BP measurements to establish a 24hr BP monitoring system. This study proposed a medical sensor that is part of the watch system, and that is most compatible with the elderly people product preferences in the UK. The “sensor strip” is in cm range, integrating a number of MEMS sensors, for the non-invasive detection of certain health aspects. The health aspects are chosen according to how close they are from the “health vital signs”, which are the first measurements executed by the doctor, if a patient is to visit him. An applied QFD study showed that the most suitable measurement technology to be used in the proposed sensor strip is the infrared technology. In addition to the sensor strip, EEG health detection is added, which is the reason why the watch is convertible. MEMS sensors, MEMS memory and an embedded processor are selected, since that this project also includes minimising the size of a device where the utilization of nanotechnology is vital. The final result of the study is only a conceptual design of a product with a carefully selected subsystems. The software design of the product will not be further developed to become a physical prototype of a consumer product.
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Sung, Michael 1975. "Non-invasive wearable sensing systems for continuous health monitoring and long-term behavior modeling." Thesis, Massachusetts Institute of Technology, 2005. http://hdl.handle.net/1721.1/36181.
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Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, February 2006.Includes bibliographical references (p. 212-228).
Deploying new healthcare technologies for proactive health and elder care will become a major priority over the next decade, as medical care systems worldwide become strained by the aging populations. This thesis presents LiveNet, a distributed mobile system based on low-cost commodity hardware that can be deployed for a variety of healthcare applications. LiveNet embodies a flexible infrastructure platform intended for long-term ambulatory health monitoring with real-time data streaming and context classification capabilities. Using LiveNet, we are able to continuously monitor a wide range of physiological signals together with the user's activity and context, to develop a personalized, data-rich health profile of a user over time. Most clinical sensing technologies that exist have focused on accuracy and reliability, at the expense of cost-effectiveness, burden on the patient, and portability. Future proactive health technologies, on the other hand, must be affordable, unobtrusive, and non-invasive if the general population is going to adopt them.
(cont.) In this thesis, we focus on the potential of using features derived from minimally invasive physiological and contextual sensors such as motion, speech, heart rate, skin conductance, and temperature/heat flux that can be used in combination with mobile technology to create powerful context-aware systems that are transparent to the user. In many cases, these non-invasive sensing technologies can completely replace more invasive diagnostic sensing for applications in long-term monitoring, behavior and physiology trending, and real-time proactive feedback and alert systems. Non-invasive sensing technologies are particularly important in ambulatory and continuous monitoring applications, where more cumbersome sensing equipment that is typically found in medical and clinical research settings is not usable. The research in this thesis demonstrates that it is possible to use simple non-invasive physiological and contextual sensing using the LiveNet system to accurately classify a variety of physiological conditions. We demonstrate that non-invasive sensing can be correlated to a variety of important physiological and behavioral phenomenon, and thus can serve as substitutes to more invasive and unwieldy forms of medical monitoring devices while still providing a high level of diagnostic power.
(cont.) From this foundation, the LiveNet system is deployed in a number of studies to quantify physiological and contextual state. First, a number of classifiers for important health and general contextual cues such as activity state and stress level are developed from basic non-invasive physiological sensing. We then demonstrate that the LiveNet system can be used to develop systems that can classify clinically significant physiological and pathological conditions and that are robust in the presence of noise, motion artifacts, and other adverse conditions found in real-world situations. This is highlighted in a cold exposure and core body temperature study in collaboration with the U.S. Army Research Institute of Environmental Medicine. In this study, we show that it is possible to develop real-time implementations of these classifiers for proactive health monitors that can provide instantaneous feedback relevant in soldier monitoring applications. This thesis also demonstrates that the LiveNet platform can be used for long-term continuous monitoring applications to study physiological trends that vary slowly with time.
(cont.) In a clinical study with the Psychiatry Department at the Massachusetts General Hospital, the LiveNet platform is used to continuously monitor clinically depressed patients during their stays on an in-patient ward for treatment. We show that we can accurately correlate physiology and behavior to depression state, as well as to track changes in depression state over time through the course of treatment. This study demonstrates how long-term physiology and behavioral changes can be captured to objectively measure medical treatment and medication efficacy. In another long-term monitoring study, the LiveNet platform is used to collect data on people's everyday behavior as they go through daily life. By collecting long-term behavioral data, we demonstrate the possibility of modeling and predicting high-level behavior using simple physiologic and contextual information derived solely from ambulatory mobile sensing technology.
by Michael Sung.
Ph.D.
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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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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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Hauke, Adam J. "An Integrated System for Sweat Stimulation, Sampling and Sensing." University of Cincinnati / OhioLINK, 2018. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1535371796736114.
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Chowdhury, Nusrat Jahan, Joseph Blevins, Phoenix Ragsdale, Tahsin Rezwana, and Ferdaus Ahmed Dr Kawsar. "Design and Development of a Comprehensive and Interactive Diabetic Parameter Monitoring System." Digital Commons @ East Tennessee State University, 2019. https://dc.etsu.edu/asrf/2019/schedule/51.
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Regular physical activity, timely medication, controlled diet, and blood glucose monitoring is crucial for any diabetic patient. Laxity on following these treatment regimens can cause severe health complexity. Moreover, A physician’s surveillance on a patient, based on the patient’s real-time progress is difficult with the existing health care system. This research aims to provide a more accurate objective data in real-time to the physicians to help both patients and providers. The data being generated is mined later to investigate interesting questions regarding diabetic care. The resultant system is a mobile healthcare monitoring system for type – 2 diabetic patients that traces patients daily progress. Although many mobile apps provide self-monitoring tools for the patient, an interactive platform for monitoring all relevant parameters of diabetes where patients and physicians both are end users is unique. The Android app is designed with 3 major modules and two submodules: 1. Carb Intake Tracker (CIT), 2. Blood Glucose Tracker (BGT), 3. Physical Activity Tracker (PAT), 4. Medicine and 5. Blood Glucose (BG) reading reminder. Since Carb is an important factor for a diabetic patient’s meals, the CIT provides a platform to record daily meals from which the patient can see the total carb intake. Through BGT, patients can record their fasting or non-fasting blood glucose reading. The PAT collects a patient’s movement data via Bluetooth from a pair of wearable insole devices, and processing the data identifies and records the current activity. The PAT can detect if the patient is active in sedentary, as well as the type of exercise done by the patient. Using BG reminder and medicine reminder, the patient can set reminders which supports the apps self-monitoring aspect. All the data collected by CIT, BGT, and PAT are stored in Microsoft Azure cloud database, an authorized physician can access the database and see graphical statistics of a patient’s diet, physical activity, and glycemic index level. The app portrays statistics of carbs taken over a period, calories burned, and Glucose level trends through graphical representation. This has two advantages: 1. Patients can improve lifestyle observing records and following reminders, 2. Physicians can prescribe actions perceiving a patient’s trends over time. This research presents unique collaborative interaction between diabetic patients and physicians to create a real time patient portal based on android APIs and wearable devices.
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Chowdhury, Nusrat. "Design and Development of a Comprehensive and Interactive Diabetic Parameter Monitoring System - BeticTrack." Digital Commons @ East Tennessee State University, 2019. https://dc.etsu.edu/etd/3646.
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A novel, interactive Android app has been developed that monitors the health of type 2 diabetic patients in real-time, providing patients and their physicians with real-time feedback on all relevant parameters of diabetes. The app includes modules for recording carbohydrate intake and blood glucose; for reminding patients about the need to take medications on schedule; and for tracking physical activity, using movement data via Bluetooth from a pair of wearable insole devices. Two machine learning models were developed to detect seven physical activities: sitting, standing, walking, running, stair ascent, stair descent and use of elliptical trainers. The SVM and decision tree models produced an average accuracy of 85% for these seven activities. The decision tree model is implemented in an app that classifies human activity in real-time.
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Veta, Jacob E. "Analysis and Development of a Lower Extremity Osteological Monitoring Tool Based on Vibration Data." Miami University / OhioLINK, 2020. http://rave.ohiolink.edu/etdc/view?acc_num=miami1595879294258019.
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Hache, Gaetanne. "Development of a wearable mobility monitoring system." Thesis, University of Ottawa (Canada), 2010. http://hdl.handle.net/10393/28511.
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Monitoring mobility at home and in the community, and understanding the environment and context in which mobility occurred, is essential for rehabilitation medicine.
This thesis introduces a Wearable Mobility Monitoring System (WMMS) for objective measurement of community mobility. This prototype WMMS was created using a smartphone-based approach that allowed for an all-in-one WMMS. The wearable system is worn freely on a person's belt, like a normal phone.
The WMMS was designed to monitor a user's mobility state and to take a photograph when a change-of-state was detected. These photographs are used to identify the context of mobility events (i.e., using an elevator, walking up/down stairs, type of walking surface).
Mobility evaluation using the proposed WMMS was performed on five able-bodied subjects. System performance for detecting changes-of-state and the ability to identify context from the photographs was analyzed. The WMMS demonstrated good potential for community mobility monitoring.
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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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Chen, Guangwei. "Towards a truly wearable, non-invasive respiration monitoring system." Thesis, Imperial College London, 2015. http://hdl.handle.net/10044/1/59965.
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Non-intrusive medical-grade accuracy respiratory monitoring is one of the two unresolved challenges in design of wearable vital signs monitoring system, besides blood pressure monitoring. The challenge of respiratory monitoring includes automatic breath detection, respiratory phase classification, and extraction of other respiratory related parameters. The main problem is that the sensed respiratory physiological signals could be heavily corrupted by artefacts and interference from non-relevant sources such as movement and other unwanted physiological signals collected at the same time. This thesis proposes a novel system which can detect respiratory activity from tracheal sounds recorded by a miniature wearable sensor with limited power budget, and can be tailored for variety of clinical scenarios by combining novel state-of-the-art techniques at both hardware and software level. The respiratory monitoring system presented in this thesis consists of two parts: one is a hardware platform for sensing breath sounds and the other is an algorithm for respiratory activity analysis. The low power sensor platform has been optimised for breath sound data acquisition by a combination of: a custom engineered acoustic chamber and a MEMS microphone; and optional power efficient data compression techniques which include the use of novel fixed length adaptive sample size (FLASS) frames optimised for Bluetooth® Smart wireless transmission protocol. The respiratory activity algorithm is based on 3-stage backward adaptive approach, using previous detected respiration’s parameters to fine tune the system and then balancing the system’s sensitivity and specificity in various ways to suit the need of different applications. These include sleep apnoea diagnosis, sudden unexpected death prevention in both epilepsy and babies, early warning scoring in hospitals and management of chronic conditions such as chronic obstructive pulmonary disease and asthma. A clinical trial focused on sleep apnoea detection was conducted in the National Hospital for Neurology and Neurosurgery, London, UK, in order to verify the respiratory monitoring system. Questionnaire results show that all participants scored the novel wearable respiratory sensor in the range 4 to 5, where 5 represents the best possible scoring in a number of attributes related to wearability. Experimental results show the proposed automatic apnoea and hypopnoea detection algorithm has 88.6% sensitivity and 99.6% specificity when comparing its performance with a specialist clinician considered as a gold standard. In comparison a state-of-the-art automatic ambulatory sleep diagnosis system has 14.3% sensitivity and 99.3% specificity.
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Cao, Huiyi. "Remote Gait Monitoring Mobile System Enabled by Wearable Sensor Technology." Case Western Reserve University School of Graduate Studies / OhioLINK, 2020. http://rave.ohiolink.edu/etdc/view?acc_num=case1587042096284549.
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Wu, Hui Hsien. "Development and Evaluation of a BlackBerry-based Wearable Mobility Monitoring System." Thèse, Université d'Ottawa / University of Ottawa, 2012. http://hdl.handle.net/10393/20500.
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A Wearable Mobility Monitoring System (WMMS) can be an advantageous device for rehabilitation decision-making. This thesis presents the design and evaluation of a proof-of-concept WMMS that uses the BlackBerry Smartphone platform. A Java program was developed for the BlackBerry 9550, using the integrated tri-axial accelerometer, Global Positioning System sensor (GPS), CMOS digital video camera, and timer to identify change-of-state (CoS) among static states, dynamic states, small activity of daily living (ADL) movements, and car riding. Static states included sitting, lying, standing, and taking an elevator. Dynamic states included walking on level ground, walking on stairs, and walking on a ramp. Small activity of daily living movements included bathroom activities, working in the kitchen, and meal preparation. Following feature extraction from the sensor data, two decision trees were used to distinguish CoS and mobility activities. CoS identification subsequently triggered video recording for improved mobility context analysis during post-processing.
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Salman, Safa. "A Wearable Real-Time and Non-Invasive Thoracic Cavity Monitoring System." The Ohio State University, 2015. http://rave.ohiolink.edu/etdc/view?acc_num=osu1440345566.
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Sun, Ye. "NON-CONTACT WEARABLE BODY AREA NETWORK FOR DRIVER HEALTH AND FATIGUE MONITORING." Case Western Reserve University School of Graduate Studies / OhioLINK, 2014. http://rave.ohiolink.edu/etdc/view?acc_num=case1405119991.
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Perumal, Shyam Vignesh. "Gait and Tremor Monitoring System for Patients with Parkinson’s Disease Using Wearable Sensors." Scholar Commons, 2016. http://scholarcommons.usf.edu/etd/6353.
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Typically, a Parkinson’s disease (PD) patient would display instances of tremor and bradykinesia (slowness of movement) at an early stage of the disease and later develop gait disturbances and postural instability. So, it is important to measure the tremor occurrences in subjects to detect the onset of PD. Also, it is equally essential to monitor the gait impairments that the patient displays, as the order at which the PD symptoms appear in subjects vary from one to another.
The primary goal of this thesis is to develop a monitoring system for PD patients using wearable sensors. To achieve that objective, our work focused first on identifying the most significant features that would best distinguish between PD and normal healthy subjects. Here, the various gait and tremor features were extracted from the raw data collected from the wearable sensors and further analyzed using statistical analysis and pattern classification techniques to pick the most significant features. In statistical analysis, the analysis of variance (ANOVA) test was conducted to differentiate the subjects based on the values of the mean. Further, pattern classification was carried out using the Linear Discriminant Analysis (LDA) algorithm. The analysis of our results shows that the features of heel force, step distance, stance and swing phases contributed more significantly to achieving a better classification between a PD and a normal subject, in comparison with other features. Moreover, the tremor analysis based on the frequency-domain characteristics of the signal including amplitude, power distribution, frequency dispersion, and median frequency was carried out to identify PD tremor from different types of artifacts.
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Capela, Nicole Alexandra. "Improving a Smartphone Wearable Mobility Monitoring System with Feature Selection and Transition Recognition." Thesis, Université d'Ottawa / University of Ottawa, 2015. http://hdl.handle.net/10393/32793.
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Modern smartphones contain multiple sensors and long lasting batteries, making them ideal platforms for mobility monitoring. Mobility monitoring can provide rehabilitation professionals with an objective portrait of a patient’s daily mobility habits outside of a clinical setting.
The objective of this thesis was to improve the performance of the human activity recognition within a custom Wearable Mobility Measurement System (WMMS). Performance of a current WMMS was evaluated on able-bodied and stroke participants to identify areas in need of improvement and differences between populations. Signal features for the waist-worn smartphone WMMS were selected using classifier-independent methods to identify features that were useful across populations. The newly selected features and a transition state recognition method were then implemented before evaluating the improved WMMS system’s activity recognition performance.
This thesis demonstrated: 1) diverse population data is important for WMMS system design; 2) certain signal features are useful for human activity recognition across diverse populations; 3) the use of carefully selected features and transition state identification can provide accurate human activity recognition results without computationally complex methods.
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Giovanetti, Matthew T. "Physiological Health Assessment and Hazard Monitoring Patch for Firefighters." University of Cincinnati / OhioLINK, 2018. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1535467307291205.
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Asaeikheybari, Golnoush. "WORKPLACE ENVIRONMENTAL AND BEHAVIORAL RISK FACTOR IDENTIFICATION AND MONITORING SYSTEM USING WEARABLE SENSOR TECHNOLOGY." Case Western Reserve University School of Graduate Studies / OhioLINK, 2020. http://rave.ohiolink.edu/etdc/view?acc_num=case1596820612674035.
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Ashwin, Belle. "WIRELESS INTELLIGENT STRUCTURAL HEALTH MONITORING SYSTEM." VCU Scholars Compass, 2008. http://scholarscompass.vcu.edu/etd/1626.
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Metal structures are susceptible to various types of damages, including corrosion, stress damage, pillowing deformation, cracks etc. These kinds of damages in the metal structures occur mainly due to operational conditions and exposure to the environment. Our research involves a portable integrated wireless sensor system with video camera and ultrasound capabilities which is being developed to investigate corrosion damage on real structures in real time. This system uses images of the metal surfaces, which are captured from an integrated wireless sensor and then quantified and analyzed using computational intelligence. The quantification of the obtained images is done with specialized component analysis software which enhances and performs wavelet transforms on the received images. Through this quantized analysis of the images we can detect and isolate regions of degradation on the metal surface. We believe that the final developed system will allow us to detect damage in metallic structures in its early stages, thereby ensuring proper safety and maintenance of its structural health. This system will further be targeted towards medical applications with capabilities of remote health monitoring. The initial target areas being bone structure and cancer detection and analysis. Applying such a wireless data capture system in these areas will reveal a broad spectrum of the usage of such an application system.
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Jasti, Madhu Narasimha Rao. "IoT based remote patient health monitoring system." Kansas State University, 2017. http://hdl.handle.net/2097/38268.
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Master of ScienceDepartment of Computer Science
Daniel A. Andresen
With an improvement in technology and miniaturization of sensors, there have been attempts to utilize the new technology in various areas to improve the quality of human life. One main area of research that has seen an adoption of the technology is the healthcare sector. The people in need of healthcare services find it very expensive this is particularly true in developing countries. As a result, this project is an attempt to solve a healthcare problem currently society is facing. The main objective of the project was to design a remote healthcare system. It’s comprised of three main parts. The first part being, detection of patient’s vitals using sensors, second for sending data to cloud storage and the last part was providing the detected data for remote viewing. Remote viewing of the data enables a doctor or guardian to monitor a patient’s health progress away from hospital premises. The Internet of Things (IoT) concepts have been widely used to interconnect the available medical resources and offer smart, reliable, and effective healthcare service to the patients. Health monitoring for active and assisted living is one of the paradigms that can use the IoT advantages to improve the patient’s lifestyle. In this project, I have presented an IoT architecture customized for healthcare applications. The aim of the project was to come up with a Remote Health Monitoring System that can be made with locally available sensors with a view to making it affordable if it were to be mass produced. Hence the proposed architecture collects the sensor data through Arduino microcontroller and relays it to the cloud where it is processed and analyzed for remote viewing. Feedback actions based on the analyzed data can be sent back to the doctor or guardian through Email and/or SMS alerts in case of any emergencies.
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Zambrano, Ericsson Ocas, Kemeli Reyes Munoz, Jimmy Armas-Aguirre, and Paola A. Gonzalez. "Technological Architecture with Low Cost Sensors to Improve Physical Therapy Monitoring." IEEE Computer Society, 2020. http://hdl.handle.net/10757/656576.
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El texto completo de este trabajo no está disponible en el Repositorio Académico UPC por restricciones de la casa editorial donde ha sido publicado.In this article, we propose a wireless monitoring solution for gait parameters using low-cost sensors in the physical rehabilitation of patients with gait disorders. This solution consists of infrared speed sensors (IRSS), force-sensing Resistor (FSR) and microcontrollers placed in a walker. These sensors collect the pressure distribution on the walker's handle and the speed of the steps during therapy session. The proposal allows to improve the traditional physiotherapy session times through a mobile application to perform the monitoring controlled by a health specialist in real time. The proposed solution consists of 4 stages: 1. Obtaining gear parameters, 2. Data transmission, 3. Information Storage and 4. Data collection and processing. Solution was tested with 10 patients from a physical rehabilitation center in Lima, Peru. Preliminary results revealed a significant reduction in the rehabilitation session from 25 to 5.2 minutes.
Revisión por pares
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Veselá, Barbora. "Gnu Health Monitoring module." Master's thesis, Vysoké učení technické v Brně. Fakulta elektrotechniky a komunikačních technologií, 2019. http://www.nusl.cz/ntk/nusl-399271.
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This thesis focuses on the development of a GNU Health Module for electrocardiogram monitoring and the development of an application providing a fundamental electrocardiogram analysis. The theoretical part contains a brief introduction to hospital information systems including electronic patient record and healthcare data standards information, followed by a description of the GNU Health application and the implementation of the electrocardiogram analysis, written in the Python programming language. The practical part deals with the development of the GNU Health Monitoring module and the external application for signal analysis. The results, disscussion and the conclusion follow.
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Lanatà, Antonio. "Innovative monitoring techniques for new wearable heart monitoring systems innovative and noninvasive techniques in vital signs monitoring for long period of time are applied ; analysis and suggestion of problems and solutions." Saarbrücken VDM Verlag Dr. Müller, 2006. http://d-nb.info/989322106/04.
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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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Wade, Eric R. (Eric Randolph) 1978. "A body area network for wearable health monitoring : conductive fabric garment utilizing DC-power-line carrier communication." Thesis, Massachusetts Institute of Technology, 2007. http://hdl.handle.net/1721.1/38542.
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Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Mechanical Engineering, 2007.This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections.
Includes bibliographical references (p. 112-116).
Wearable computing applications are becoming increasingly present in our lives. Of the many wearable computing applications, wearable health monitoring may have the most potential to make a lasting positive impact. The ability to remotely monitor physiological signals such as respiration, motion, and temperature has benefits for populations such as elderly citizens, fitness professionals, and soldiers in the battlefield. To fully integrate wearable networks into a user's daily life, these systems must be minimally invasive and minimally intrusive. At the same time, such wearable networks require multiple sensors and electronic components to be mounted on the body. Unfortunately, typical off-the-shelf components of this nature are heavy, bulky, and don't integrate well with the human form. Thus, it is critical to figure out how best to minimize the physical and mental burden that these systems place on the user. To address these problems, we propose a new method of designing wearable health monitoring networks by combining electrically conductive fabrics and power-line communication technology. Electrically conductive fabrics are useful in that they feel and behave like normally worn clothing but also have the ability to transmit data and power.
(cont.) To fully exploit the conductive fabric as a transmission medium, we also use power-line communication technology. Power-line communication allows for simultaneous power and data transmission over a shared medium. The use of these two technologies will allow us to significantly reduce the amount of metal cabling on the body and to reduce overall system bulk and weight. With this project, we design the DC-PLC system that will act as the physical layer of the architecture. Next, we construct a prototype body area network, and derive analytical models for predicting garment electrostatic and electro-dynamic properties using Maxwell's equations, and verify using empirical data and finite-element analysis. Finally, we will determine relevant rules and guidelines for the design and construction of such garments.
by Eric R. Wade.
Ph.D.
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Dani, Mohamed Cherif. "Unsupervised anomaly detection for aircraft health monitoring system." Thesis, Sorbonne Paris Cité, 2017. http://www.theses.fr/2017USPCB258.
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La limite des connaissances techniques ou fondamentale, est une réalité dont l’industrie fait face. Le besoin de mettre à jour cette connaissance acquise est essentiel pour une compétitivité économique, mais aussi pour une meilleure maniabilité des systèmes et machines. Aujourd’hui grâce à ces systèmes et machine, l’expansion de données en quantité, en fréquence de génération est un véritable phénomène. À présent par exemple, les avions Airbus génèrent des centaines de mégas de données par jour, et intègrent des centaines voire des milliers de capteurs dans les nouvelles générations d’avions. Ces données générées par ces capteurs, sont exploitées au sol ou pendant le vol, pour surveiller l’état et la santé de l’avion, et pour détecter des pannes, des incidents ou des changements. En théorie, ces pannes, ces incidents ou ces changements sont connus sous le terme d’anomalie. Une anomalie connue comme un comportement qui ne correspond pas au comportement normal des données. Certains la définissent comme une déviation d’un modèle normal, d’autres la définissent comme un changement. Quelques soit la définition, le besoin de détecter cette anomalie est important pour le bon fonctionnement de l'avion. Actuellement, la détection des anomalies à bord des avions est assuré par plusieurs équipements de surveillance aéronautiques, l’un de ces équipements est le « Aircraft condition monitoring System –ACMS », enregistre les données générées par les capteurs en continu, il surveille aussi l’avion en temps réel grâce à des triggers et des seuils programmés par des Airlines ou autres mais à partir d’une connaissance a priori du système. Cependant, plusieurs contraintes limitent le bon fonctionnement de cet équipement, on peut citer par exemple, la limitation des connaissances humaines un problème classique que nous rencontrons dans plusieurs domaines. Cela veut dire qu’un trigger ne détecte que les anomalies et les incidents dont il est désigné, et si une nouvelle condition surgit suite à une maintenance, changement de pièce, etc. Le trigger est incapable s’adapter à cette nouvelle condition, et il va labéliser toute cette nouvelle condition comme étant une anomalie. D’autres problèmes et contraintes seront cités progressivement dans les chapitres qui suivent. L’objectif principal de notre travail est de détecter les anomalies et les changements dans les données de capteurs, afin d’améliorer le system de surveillance de santé d’avion connu sous le nom Aircraft Health Monitoring(AHM). Ce travail est basé principalement sur une analyse à deux étapes, Une analyse unie varie dans un contexte non supervisé, qui nous permettra de se focaliser sur le comportement de chaque capteur indépendamment, et de détecter les différentes anomalies et changements pour chaque capteur. Puis une analyse multi-variée qui nous permettra de filtrer certaines anomalies détectées (fausses alarmes) dans la première analyse et de détecter des groupes de comportement suspects. La méthode est testée sur des données réelles et synthétiques, où les résultats, l’identification et la validation des anomalies sont discutées dans cette thèseThe limitation of the knowledge, technical, fundamental is a daily challenge for industries. The need to updates these knowledge are important for a competitive industry and also for an efficient reliability and maintainability of the systems. Actually, thanks to these machines and systems, the expansion of the data on quantity and frequency of generation is a real phenomenon. Within Airbus for example, and thanks to thousands of sensors, the aircrafts generate hundreds of megabytes of data per flight. These data are today exploited on the ground to improve safety and health monitoring system as a failure, incident and change detection. In theory, these changes, incident and failure are known as anomalies. An anomaly is known as deviation form a normal behavior of the data. Others define it as a behavior that do not conform the normal behavior. Whatever the definition, the anomaly detection process is very important for good functioning of the aircraft. Currently, the anomaly detection process is provided by several health monitoring equipments, one of these equipment is the Aircraft Health Monitoring System (ACMS), it records continuously the date of each sensor, and also monitor these sensors to detect anomalies and incident using triggers and predefined condition (exeedance approach). These predefined conditions are programmed by airlines and system designed according to a prior knowledge (physical, mechanical, etc.). However, several constraints limit the ACMS anomaly detection potential. We can mention, for example, the limitation the expert knowledge which is a classic problem in many domains, since the triggers are designed only to the targeted anomalies. Otherwise, the triggers do not cover all the system conditions. In other words, if a new behavior appears (new condition) in the sensor, after a maintenance action, parts changing, etc. the predefined conditions won't detect any thing and may be in many cases generated false alarms. Another constraint is that the triggers (predefined conditions) are static, they are unable to adapt their proprieties to each new condition. Another limitation is discussed gradually in the future chapters. The principle of objective of this thesis is to detect anomalies and changes in the ACMS data. In order to improve the health monitoring function of the ACMS. The work is based principally on two stages, the univariate anomaly detection stage, where we use the unsupervised learning to process the univariate sensors, since we don’t have any a prior knowledge of the system, and no documentation or labeled classes are available. The univariate analysis focuses on each sensor independently. The second stage of the analysis is the multivariate anomaly detection, which is based on density clustering, where the objective is to filter the anomalies detected in the first stage (false alarms) and to detect suspected behaviours (group of anomalies). The anomalies detected in both univariate and multivariate can be potential triggers or can be used to update the existing triggers. Otherwise, we propose also a generic concept of anomaly detection based on univariate and multivariate anomaly detection. And finally a new concept of validation anomalies within airbus
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Das, Piyali. "Smart Shoe for Remote Monitoring of Parkinson’s Patients." University of Cincinnati / OhioLINK, 2015. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1445342741.
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Gaddam, Sathvik Reddy. "Structural health monitoring system| Filtering techniques, damage localization, and system design." Thesis, California State University, Long Beach, 2016. http://pqdtopen.proquest.com/#viewpdf?dispub=10144825.
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Material testing is a major concern in many manufacturing and aeronautical industries, where structures require periodic inspection using equipment and manpower. Environmental Noise (EN) is the major concern when localizing the damage in real time. Inspecting underlying components involves destructive approaches. These factors can be alleviated using Non Destructive Testing (NDT) and a cost effective embedded sensor system.
This project involves NDT implementation of Structural Health Monitoring (SHM) with filtering techniques in real time. A spectrogram and a scalogram are used to analyze lamb response from an embedded array of Piezo Transducers (PZT). This project gives insights on implementing a real time SHM system with a sensor placement strategy and addresses two main problems, namely filtering and damage localization. An Adaptive Correlated Noise Filter (ACNF) removes EN from the lamb response of a structure. A damage map is developed using Short Time Fourier Transform (STFT), and Continuous Wavelet Analysis (CWA).
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Ren, Xiaoran. "A Wearable Fitness Device System for Multiple Biological Information Data Acquisition for Physically Active Persons." University of Cincinnati / OhioLINK, 2017. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1505209479365329.
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Wang, Xudong. "Vehicle health monitoring system using multiple-model adaptive estimation." Thesis, University of Hawaii at Manoa, 2003. http://hdl.handle.net/10125/7051.
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In this thesis, we propose two failure detection and identification (FDI) approaches based on the multiple-model estimation algorithm to monitor the health of vehicles, specifically aircraft applications. They detect and identify failing components of the vehicle, and the system variations. The dynamics of the vehicle are modeled as a stochastic hybrid system with uncertainty-unknown model structure or parameters. FDI performance is evaluated for each approach. We demonstrate the reliability, validity of these approaches by applying them to simulate aircraft machinery experiencing component failures or structural variations. The approaches that we surveyed are: (i) Multiple-Hypothesis Kalman Filter, and (ii) Interacting Multiple-Model (IMM) Estimator. By coupling the fault detection and identification (FDI) scheme with the reconfigurable controller design scheme, a fault-tolerant control system based on the multiple-model estimation algorithm is defined.vii, 59 leaves
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Chambers, Jeffrey Thomas. "Durability testing of an aircraft structural health monitoring system." Thesis, Massachusetts Institute of Technology, 2006. http://hdl.handle.net/1721.1/37849.
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Thesis (S.M.)--Massachusetts Institute of Technology, Dept. of Aeronautics and Astronautics, 2006.This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections.
Includes bibliographical references (leaves 103-105).
Structural health monitoring (SHM) is an emerging technology leading to systems capable of continuously monitoring structures for damage. Aerospace structures have one of the highest payoffs for SHM systems because damage can lead to catastrophic and expensive failures. Prior work in SHM has focused on damage detection methods and sensor optimization, however, the topics of durability, reliability, and longevity of these systems has not been addressed. A framework for developing SHM durability test standards for aerospace vehicles is offered. Existing standards for the durability of commercial and military aircraft avionics are identified, and the relation to SHM systems is described. Using these existing standards, a test matrix and testing specifics are developed to assess the durability of SHM systems. Careful consideration is necessary in defining the 'system' under testing. Criteria are defined to establish whether a sensor/structural system has been affected by the various environments. Extensive experimental results from durability testing of a surface-mounted piezoelectric Lamb-wave SHM system are presented. Environments tested include temperature extremes, humidity, fluid susceptibility, altitude, and mechanical strain.
(cont.) A voltage change criteria, which measures pre- vs. post-test sensed wave amplitude, proved useful in assessing the SHM system's performance. All sensors survived the tested environments, with an average voltage degradation of -16%. The high-temperature, humidity, and water-based fluids susceptibility tests had the greatest influence on the sensors, with an average voltage degradation of -38%. In several of the tests, the sensors had significant voltage degradation during environmental exposure, which recovered somewhat in most cases after ambient conditions were reestablished. A clear need exists for a supplemental standard geared specifically towards smart structure technologies that would address SHM and other embedded or surface mounted smart structure components and systems. Additional testing of the Lamb-wave sensors, including consideration of ultrasonic fatigue, is recommended.
by Jeffrey Thomas Chambers.
S.M.
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Kerley, Ross Andrew. "Automotive Lead-Acid Battery State-of-Health Monitoring System." Thesis, Virginia Tech, 2014. http://hdl.handle.net/10919/64870.
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This thesis describes the development of a system to continuously monitor the battery in a car and warn the user of an upcoming battery failure. An automotive battery endures enormous strain when it starts the engine, and when it supplies loads without the engine running. Note that the current during a cranking event often exceeds 500 Amperes. Despite the strains, a car battery still typically lasts 4-6 years before requiring replacement. There is often no warning of when a battery should be replaced and there is never a good time for a battery failure.
All currently available lead-acid battery monitoring systems use voltage and current sensing to monitor battery impedance and estimate battery health. However, such a system is costly due to the current sensor and typically requires an expert to operate the system. This thesis describes a prototype system to monitor battery state of health and provide advance warning of an upcoming battery failure using only voltage sensing. The prototype measures the voltage during a cranking event and determines if the battery is healthy or not. The voltage of an unhealthy battery will drop lower than a healthy one, and it will not recover as quickly.
The major contributions of the proposed research to the field are an algorithm to predict automotive battery state-of-health that is temperature-dependent and a prototype implementation of the algorithm on an ARM processor development board.Master of Science
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Wang, Hong. "MACHINE HEALTH MONITORING OF ROTOR-BEARING-GEAR TRANSMISSION SYSTEM." University of Akron / OhioLINK, 2005. http://rave.ohiolink.edu/etdc/view?acc_num=akron1133281063.
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Kirikera, Goutham Raghavendra. "A Structural Neural System for Health Monitoring of Structures." University of Cincinnati / OhioLINK, 2006. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1155149869.
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Sakki, Kranthi Kumar. "A Radio Frequency Identification Multi-Sensor Health Monitoring System." Thesis, California State University, Long Beach, 2017. http://pqdtopen.proquest.com/#viewpdf?dispub=10262351.
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Health Monitoring Systems (HMS) are used to monitor physiological signals such as the blood pressure, heart rate, and temperature of patients. The use of a HMS for continuous monitoring of the Vital Signs of patients requiring constant medical supervision, is particularly important. The current project presents the development and implementation of a multi-sensor HMS to track and record multiple parameters of a patient (Electrocardiogram, pulse, temperature, and body position). The project development uses biomedical sensor technology for monitoring the physiological signals, Radio Frequency Identification (RFID) technology for patient identification, and the Internet of Things (IoT) for information transmission. Sensors attached to a patient’s body collect data that alert users to abnormal values via smart devices, such as mobile phones or laptops. Experimental testing of the multi-sensor HMS developed and implemented for this project, demonstrates the system’s effectiveness in sensing, collecting, and transmitting accurate patient information for remote monitoring.
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Bukhari, Syed Asif Abbas, and Sajid Hussain. "Intelligent Support System for Health Monitoring of elderly people." Thesis, Blekinge Tekniska Högskola, Sektionen för datavetenskap och kommunikation, 2012. http://urn.kb.se/resolve?urn=urn:nbn:se:bth-5132.
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The use of information and communications technology (ICT) to provide medical information, interaction between patients and health-service providers, institution-to-institution transmission of data, in known as eHealth. ICT have become an inseparable part of our life, it can integrate health care more seamlessly to our everyday life. ICT enables the delivery of accurate medical information anytime anywhere in an efficient manner. Cardiovascular disease (CVD) is the single leading cause of death, especially in elderly people. The condition of heart is monitor by electrocardiogram (ECG). The Electrocardiogram (ECG) is widely used clinical tool to diagnose complex heart diseases. In clinical settings, resting ECG is used to monitor patients. Holter-based portable monitoring solutions capable of 24 to 48-hour ECG recording, they lack the capability of providing any real-time feedback in case of alarming situation. The recorded ECG data analyzed offline by doctor. To address this issue, authors propose a functionality of intelligence decision support system, in heart monitoring system. The proposed system has capability of generate an alarm in case of serious abnormality in heart, during monitoring of heart activity.
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Yang, Cheng-Chen. "Cyber-physical system : real-time Internet-based wireless structural health monitoring system /." Available to subscribers only, 2009. http://proquest.umi.com/pqdweb?did=1967890341&sid=3&Fmt=2&clientId=1509&RQT=309&VName=PQD.
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Yang, Chengchen. "CYBER-PHYSICAL SYSTEM: REAL-TIME INTERNET-BASED WIRELESS STRUCTURAL HEALTH MONITORING SYSTEM." OpenSIUC, 2009. https://opensiuc.lib.siu.edu/dissertations/111.
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As the demands to monitor the health status of structures increase, researchers around the world have proposed several concepts to solve this issue. This research first examines the existing technologies and then works toward a novel structural health monitoring solution. A comprehensive discussion includes major topics from sensor selection and installation to sensing data display. A cyber-physical system combining embedded system, wireless communication, and the Java platform was developed for structural health monitoring. The focus of this system is to continuously monitor structural response and broadcast the information to users worldwide via the Internet. A wireless sensor node is designed to connect up to eight sensor channels. Various sensors have been tested on the sensor node. A data acquisition and repository system was also developed. The use of the Java language makes this system capable of running in virtually any existing computer platform. Distributed design concept expands its functionalities and capabilities. Its graphical user interface offers users a friendly and ease-of-use environment to monitor real-time and historical data in both graphical and numerical ways. Every component of the system has been validated to verify its functionality. Additionally, the whole system has been implemented on a steel pedestrian bridge to observe its performance.
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Huang, Kevin. "Exploring In-Home Monitoring of Rehabilitation and Creating an Authoring Tool for Physical Therapists." Research Showcase @ CMU, 2015. http://repository.cmu.edu/dissertations/668.
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Physiotherapy is a key part of treatment for neurological and musculoskeletal disorders, which affect millions in the U.S. each year. Physical therapy treatments typically consist of an initial diagnostic session during which patients’ impairments are assessed and exercises are prescribed to improve the impaired functions. As part of the treatment program, exercises are often assigned to be performed at home daily. Patients return to the clinic weekly or biweekly for check-up visits during which the physical therapist reassesses their condition and makes further treatment decisions, including readjusting the exercise prescriptions. Most physical therapists work in clinics or hospitals. When patients perform their exercises at home, physical therapists cannot supervise them and lack quantitative exercise data reflecting the patients’ exercise compliance and performance. Without this information, it is difficult for physical therapists to make informed decisions or treatment adjustments. To make informed decisions, physical therapists need to know how often patients exercise, the duration and/or repetitions of each session, exercise metrics such as the average velocities and ranges of motion for each exercise, patients’ symptom levels (e.g. pain or dizziness) before and after exercise, and what mistakes patients make. In this thesis, I evaluate and work towards a solution to this problem. The growing ubiquity of mobile and wearable technology makes possible the development of “virtual rehabilitation assistants.” Using motion sensors such as accelerometers and gyroscopes that are embedded in a wearable device, the “assistant” can mediate between patients at home and physical therapists in the clinic. Its functions are to: use motion sensors to record home exercise metrics for compliance and performance and report these metrics to physical therapists in real-time or periodically; allow physical therapists and patients to quantify and see progress on a fine-grain level; record symptom levels to further help physical therapists gauge the effectiveness of exercise prescriptions; offer real-time mistake recognition and feedback to the patients during exercises; One contribution of this thesis is an evaluation of the feasibility of this idea in real home settings. Because there has been little research on wearable virtual assistants in patient homes, there are many unanswered questions regarding their use and usefulness: Q1. What patient in-home data could wearable virtual assistants gather to support physical therapy treatments? Q2. Can patient data gathered by virtual assistants be useful to physical therapists? 3 Q3. How is this wearable in-home technology received by patients? I sought to answer these questions by implementing and deploying a prototype called “SenseCap.” SenseCap is a small mobile device worn on a ball cap that monitors patients’ exercise movements and queries them about their symptoms. A technology probe study showed that the virtual assistant could gather important compliance, performance, and symptom data to assist physical therapists’ decision-making, and that this technology would be feasible and acceptable for in-home use by patients. Another contribution of this thesis is the development of a tool to allow physical therapists to create and customize virtual assistants. With current technology, virtual assistants require engineering and programming efforts to design, implement, configure and deploy them. Because most physical therapists do not have access to an engineering team they and their patients would be unable to benefit from this technology. With the goal of making virtual assistants accessible to any physical therapist, I explored the following research questions: Q4. Would a user-friendly rule-specification interface make it easy for physical therapists to specify correct and incorrect exercise movements directly to a computer? What are the limitations of this method of specifying exercise rules? Q5. Is it possible to create a CAD-type authoring tool, based on a usable interface, that physical therapists could use to create their own customized virtual assistant for monitoring and coaching patients? What are the implementation details of such a system and the resulting virtual assistant? Q6. What preferences do PTs have regarding the delivery of coaching feedback for patients? Q7. What is the recognition accuracy of a virtual rehabilitation assistant created by this tool? This dissertation research aims to improve our understanding of the barriers to rehabilitation that occur because of the invisibility of home exercise behavior, to lower these barriers by making it possible for patients to use a widely-available and easily-used wearable device that coaches and monitors them while they perform their exercises, and improve the ability of physical therapists to create an exercise regime for their patients and to learn what patients have done to perform these exercises. In doing so, treatment should be better suited to each patient and more successful.
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Rhen, Mats. "Studies of condition monitoring methods for system health assessment : health diagnostics and prognostics." Licentiate thesis, Luleå tekniska universitet, 2002. http://urn.kb.se/resolve?urn=urn:nbn:se:ltu:diva-26751.
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Increasing interest in productivity, safety and environmental issues have highlighted the area of maintenance and reliability. The increasing cost of maintenance covers both preservation and sustainable exploitation of resources and awareness in maintaining equipment in a way to ensure return on investment both in the short and long run. The information obtained from condition monitoring of existing turbine, plant, rails and pumps can provide an important basis for dimensioning of future systems and components. The main objective of this research work is to develop and apply methods for efficient condition monitoring, and hence reduce maintenance costs and provide a framework for development and implementation of computer based decision tools. Furthermore, methods enabling existing process data and cost effective transducers to be used together with modern data analysis and diagnostic tools for condition monitoring of complex mechanical systems have been examined and prototypes developed. The areas of investigation covered in this work are hydropower turbines, rails and the main cooling pumps in a nuclear power-plant. The interest in diagnostics for hydropower turbines was driven by the obvious risk of contamination of water by oil leaks and expensive refurbishments caused by wear of the Kaplan turbine vane bearings. The intrest in risk analysis was motivated by Vattenfall's intrest in gaining knowledge about the state of all turbines in the company. The aim of this project was to develop a generic model of hydropower turbine behavior using physics-based models based on material properties, load tolerances, etc.. An important question was whether it was possible to predict the wear rate and plan predictive replacement or maintenance. A systematic approach to find failure modes, their effects, their causes and consequences in combination with Fault Tree Analysis was needed. The objective of this project was to examine a systematic approach to map failure modes and their causes in an hydropower turbine. We have restricted the study to turbine units of the Kaplan, Francis and tube types. The objective of the study concerning rail track was to develop methods and equipment for detection of surface damage in rail track rail in addition to the present system of practice of visual examination. The equipment developed has to be used to obtain objective statistical data for evaluating maintenance methods and efforts. We have restricted the study to spalling and headchecks on the rail head surface and running edge. The method developed enables measurements of different types of surface damage such as spalling and shelling to be made with inductive transducers sensitive to the distance to the measured object. The assumption here is that the damage being detected is characterized by the absence of material from rail surface. The main object of condition monitoring of the cooling pumps was to be able to detect bearing wear in order to be able to plan and carry out restoration well ahead of breakdown or bearing seizure. The study was restricted to the main cooling pump motor and its main bearings. Condition monitoring of the pumps was done using a method based on current measurements. Analysis of the currents on the main cooling pump of the power plant proved that it is possible to monitor the condition of the pump in spite of the presence of electronic frequency converters which distorts the signal.Godkänd; 2002; 20070222 (ysko)
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Hunt, Victor J. "Nondestructive Evaluation and Health Monitoring of Highway Bridges." University of Cincinnati / OhioLINK, 2000. http://rave.ohiolink.edu/etdc/view?acc_num=ucin974836791.
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Haugros, Håkon Unander, and Signe Bø Overå. "A home based health monitoring system: An implementation and evaluation." Thesis, Norwegian University of Science and Technology, Department of Computer and Information Science, 2008. http://urn.kb.se/resolve?urn=urn:nbn:no:ntnu:diva-8873.
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The advances in technology over recent years have opened up a lot of opportunities in the field of wearable health monitoring. Technology equipment that was once reserved for hospital use may now be used in the home of a consumer; this could ease the life of many long term patients and their next of kin. We have been in contact with the case of a child, who suffers from a number of rare conditions and complications. She has to be monitored almost all the time in her home by her parents. She has been in and out of the hospital a number of times, without ever figuring out what causes her problems. Her parents have to use a lot of time and effort to monitor her. Our goal in this thesis was two-fold, automate and ease the monitoring of her as well as logging all the data of vital signs so that it may later be used for diagnosing. We made a prototype system using the hardware of a wearable monitoring shirt called the LifeShirt. Our main focus was to create a system that would allow for discussion around potential usage areas of the LifeShirt. We did live testing on the patient and evaluated the solution with the family and the patients physician. We found that our prototype concept fulfills a need that is currently unmet. Their monitoring can be simplified, and the physician can get more data to use for diagnosing purposes. Based on our result we see a great potential for using wearable health monitoring technology in the home. We envisage many areas that could benefit from automated monitoring with the LifeShirt, both in home as well as in hospital settings.
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Bhesania, Alpaben. "Wireless data acquisition system for health monitoring of civil infrastructure /." Available to subscribers only, 2005. http://proquest.umi.com/pqdweb?did=1079666551&sid=17&Fmt=2&clientId=1509&RQT=309&VName=PQD.
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Machado, Rafael Carvalho. "A Wearable System for Heart Failure Monitoring." Master's thesis, 2020. http://hdl.handle.net/10316/93992.
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Trabalho de Projeto do Mestrado Integrado em Engenharia Biomédica apresentado à Faculdade de Ciências e TecnologiaA insuficiência cardíaca é o problema de saúde mais letal e dispendioso no nos países desenvolvidos. Neste projecto é proposto um sistema vestível para monitorização de biossinais relacionados com a insuficiência cardíaca, baseado em componentes baratose acessíveis e em software de código aberto. Recorrendo a um microcontrolador AVR comum com comunicação Bluetooth e circuitos integrados de processamento de sinais analógicos conseguiu-se adquirir, gravar e transmitir sinais de electrocardiograma e fotopletismograma. Através do desenvolvimento de uma aplicação Android, estes sinais podem ser processados e apresentados em tempo real e é possível executar posprocessamento demasiado pesado para o microcontrolador de forma a calcular parâmetros secundários como a tensão arterial e o ritmo cardíaco. Para isso foi implementado um algoritmo de detecção de picos nas formas de onda dos sinais adquiridos assim como funcionalidade de encriptação de forma a garantir aconfidencialidade dos dados em transmissão. O principal objectivo deste trabalho é tentar evidenciar o potencial para a utilização de sistemas embebidos em redes sem fios de sensores de forma a expandir a recolha de dados médicos, melhorar abordagens terapêuticas baseadas no auto cuidado e dar aos profissionais de saúde uma perspetiva mais abrangente acerca do estado dos seus pacientes.Com isto em mente, os objectivos deste projecto de Mestrado são 1) determinar o estado da arte dos sistemas de dispositivos vestíveis e potenciais equivalentes de baixo custo e open source, 2) estudo e familiarização com estes systemas, 3) desenvolvimento de um protótipo, 4) estudo comparativo entre diferentes configurações, 5) desenvolvimento com uma abordagem full-stack.
Heart failure is the most lethal and costly health problem in the developed world. In this project a wearable device for monitoring heart failure related biosignals based on cheap readily available components and open source software is proposed. Employing a common, Bluetooth enabled, AVRmicrocontroller and simple analog signal processing integrated circuits, live, high sample rate photoplethysmogram and electrocardiogram data recording and streaming was achieved. Through the development of an Android application, the data can be processed and presented real-time and computationally expensive postprocessing can be done to infer relevant secondary parameters, bloodpressure and heart rate. To enable this, a waveform peak detection algorithm was implemented aswell as storage and encryption functionality to ensure data confidentiality. The main purpose ofthis work is to attempt to highlight the potential for the employment of embedded devices in wireless sensor networks to expand medical data collection, improve self-care therapeutical approaches and give practitioners more insight into the condition of their patients.With the above in mind, the objectives of this Master’s project are 1) to assess the state ofthe art of wearable heart disease related monitoring systems and potential low-cost and open source counterparts, 2) the study and familiarization with such system’s components and architecture from an engineering perspective, 3) the development of a proof-of-concept industrial level prototype aiming for low-cost but also quality and feature viability, 4) the comparative study between different possible configurations regarding signal quality and usability and 5) develop along a full-stack approach on circuit design, firmware, device interfacing, signal processing and UI/UX levels.
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Chi, Yun-Chin, and 紀運錦. "A Study And Implementation of Wireless Transmission For A Wearable Health Monitoring System." Thesis, 2004. http://ndltd.ncl.edu.tw/handle/82383850046880139901.
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碩士逢甲大學
通訊工程所
92
The study is to investigate basic network structure and scheduling of several simultaneous single-hop transmission using ISM band transceiver limited to the class of carrier-sense multiple access with collision avoidance (CSMA/CA) protocols. The motivation for this study is two fold, wirelessly connecting smart suits to monitor patient’s physical conditions in the ward of hospital, and reducing power consumption to increase battery life. Main contribution in this work is to provide a design of sequential scheduling algorithm under star network structure in one-master-several-slaves sense. An implementation of the design using five specific ISM band transceivers, one of them for master connected to PC, four for slaves connected to users (smart suits), is realized to obtain test results. Further analysis can then be performed by using these test results for obtaining relationship between sampling frequencies and numbers of users, associated with their sleeping time and numbers of sensors included versus remote display.
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Bhatnagar, Shalabh. "Integration of V2V-AEB system with wearable cardiac monitoring system and reduction of V2V-AEB system time constraints." Thesis, 2017. https://doi.org/10.7912/C2VH3H.
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Indiana University-Purdue University Indianapolis (IUPUI)Autonomous Emergency Braking (AEB) system uses vehicle’s on-board sensors such as radar, LIDAR, camera, infrared, etc. to detect the potential collisions, alert the driver and make safety braking decision to avoid a potential collision. Its limitation is that it requires clear line-of-sight to detect what is in front of the vehicle. Whereas, in current V2V (vehicle-to-vehicle communication) systems, vehicles communicate with each other over a wireless network and share information about their states. Thus the safety of a V2V system is limited to the vehicles with communication capabilities. Our idea is to integrate the complementary capabilities of V2V and AEB systems together to overcome the limitations of V2V and AEB systems. In a V2V-AEB system, vehicles exchange data about the objects information detected by their onboard sensors along with their locations, speeds, and movements. The object information detected by a vehicle and the information received through the V2V network is processed by the AEB system of the subject vehicle. If there is an imminent crash, the AEB system alerts the driver or applies the brake automatically in critical conditions to prevent the collision. To make V2V-AEB system advance, we have developed an intelligent heart Monitoring system and integrated it with the V2V-AEB system of the vehicle. The advancement of wearable and implantable sensors enables them to communicate driver’s health conditions with PC’s and handheld devices. Part of this thesis work concentrates on monitoring the driver’s heart status in real time by using fitness tracker. In the case of a critical health condition such as the cardiac arrest of a driver, the system informs the vehicle to take an appropriate operation decision and broadcast emergency messages over the V2V network. Thus making other vehicles and emergency services aware of the emergency condition, which can help a driver to get immediate medical attention and prevent accident casualties. To ensure that the effectiveness of the V2V-AEB system is not reduced by a time delay, it is necessary to study the effect of delay thoroughly and to handle them properly. One common practice to control the delayed vehicle trajectory information is to extrapolate trajectory to the current time. We have put forward a dynamic system that can help to reduce the effect of delay in different environments without extrapolating trajectory of the pedestrian. This method dynamically controls the AEB start braking time according to the estimated delay time in the scenario. This thesis also addresses the problem of communication overload caused by V2V-AEB system. If there are n vehicles in a V2V network and each vehicle detects m objects, the message density in the V2V network will be n*m. Processing these many messages by the receiving vehicle will take considerable computation power and cause a delay in making the braking decision. To prevent flooding of messages in V2V-AEB system, some approaches are suggested to reduce the number of messages in the V2V network that include not sending information of objects that do not cause a potential collision and grouping the object information in messages.
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You, He-Zhong, and 游賀中. "Design of a Wearable Heart Rate Monitoring System Based on the PSoC." Thesis, 2011. http://ndltd.ncl.edu.tw/handle/uyr7wq.
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碩士國立臺灣科技大學
醫學工程研究所
99
In this paper, we developed a wearable heart rate monitoring system. The sensor can be worn comfortably on the earlobe without affecting human’s action, which can be used for real-time heart rate monitoring in daily life or jogging. The sensing circuit and system was developed by a Programmable System on Chip (PSoC). Clipping the sensing module to the user's earlobe can measure the Photoplethysmogram (PPG) signal. Via bluetooth, the PPG signal can be immediately sent to the smartphone. The smartphone receives the signal, and performs signal processing. When there is a abnormal physiological signal occurs, the smartphone can warn the user by its vibration and sound function. Therefore, user can make the appropriate response. In the same time, the user's GPS coordinates and PPG data can be sent to the remote monitoring center. It is expected to reduce the incidence of accidents happening due to physical illness. In this thesis, the device is worn while chewing, walking, and running. It is verified that the device is effective in eliminating the interference of heart rate detection. As a result, the accuracy of the device is 99.95% to 91.16% on walk speed, 1.8km/hr to 9.0km/hr and is 99.34% on chewing.