The Experts below are selected from a list of 3906 Experts worldwide ranked by ideXlab platform
Hsueh Chun Lin - One of the best experts on this subject based on the ideXlab platform.
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Developing a ubiquitous Health Management System with Healthy diet control for metabolic syndrome Healthcare in Taiwan
Computer Methods and Programs in Biomedicine, 2017Co-Authors: Yao Chiang Kan, Kai Hong Chen, Hsueh Chun LinAbstract:Background and Objective Self-Management in Healthcare can allow patients managing their Health data anytime and everywhere for prevention of chronic diseases. This study established a prototype of ubiquitous Health Management System (UHMS) with Healthy diet control (HDC) for people who need services of metabolic syndrome Healthcare in Taiwan. Methods System infrastructure comprises of three portals and a database tier with mutually supportive components to achieve functionality of diet diaries, nutrition guides, and Health risk assessments for self-Health Management. With the diet, nutrition, and personal Health database, the design enables the analytical diagrams on the interactive interface to support a mobile application for diet diary, a Web-based platform for Health Management, and the modules of research and development for medical care. For database integrity, dietary data can be stored at offline mode prior to transformation between mobile device and server site at online mode. Results The UHMS-HDC was developed by open source technology for ubiquitous Health Management with personalized dietary criteria. The System integrates mobile, internet, and electronic Healthcare services with the diet diary functions to manage Healthy diet behaviors of users. The virtual patients were involved to simulate the self-Health Management procedure. The assessment functions were approved by capturing the screen snapshots in the procedure. The proposed System development was capable for practical intervention. Conclusion This approach details the expandable framework with collaborative components regarding the self-developed UHMS-HDC. The multi-disciplinary applications for self-Health Management can support the Healthcare professionals to reduce medical resources and improve Healthcare effects for the patient who requires monitoring personal Health condition with diet control. The proposed System can be practiced for intervention in the hospital.
Yao Chiang Kan - One of the best experts on this subject based on the ideXlab platform.
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Developing a ubiquitous Health Management System with Healthy diet control for metabolic syndrome Healthcare in Taiwan
Computer Methods and Programs in Biomedicine, 2017Co-Authors: Yao Chiang Kan, Kai Hong Chen, Hsueh Chun LinAbstract:Background and Objective Self-Management in Healthcare can allow patients managing their Health data anytime and everywhere for prevention of chronic diseases. This study established a prototype of ubiquitous Health Management System (UHMS) with Healthy diet control (HDC) for people who need services of metabolic syndrome Healthcare in Taiwan. Methods System infrastructure comprises of three portals and a database tier with mutually supportive components to achieve functionality of diet diaries, nutrition guides, and Health risk assessments for self-Health Management. With the diet, nutrition, and personal Health database, the design enables the analytical diagrams on the interactive interface to support a mobile application for diet diary, a Web-based platform for Health Management, and the modules of research and development for medical care. For database integrity, dietary data can be stored at offline mode prior to transformation between mobile device and server site at online mode. Results The UHMS-HDC was developed by open source technology for ubiquitous Health Management with personalized dietary criteria. The System integrates mobile, internet, and electronic Healthcare services with the diet diary functions to manage Healthy diet behaviors of users. The virtual patients were involved to simulate the self-Health Management procedure. The assessment functions were approved by capturing the screen snapshots in the procedure. The proposed System development was capable for practical intervention. Conclusion This approach details the expandable framework with collaborative components regarding the self-developed UHMS-HDC. The multi-disciplinary applications for self-Health Management can support the Healthcare professionals to reduce medical resources and improve Healthcare effects for the patient who requires monitoring personal Health condition with diet control. The proposed System can be practiced for intervention in the hospital.
Kai Goebel - One of the best experts on this subject based on the ideXlab platform.
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prognostic Health Management System development for electromechanical actuators
Journal of Aerospace Information Systems, 2015Co-Authors: Edward Balaban, Indranil Roychoudhury, Sriram Narasimhan, Abhinav Saxena, Marion Koopmans, Kai GoebelAbstract:Systemthatdiagnoseselectromechanicalactuatorfaultsandemploysprognosticalgorithmstotrackfaultprogression and predict the actuator’s remaining useful life. The diagnostic algorithm is implemented using a combined modelbased and data-driven reasoner. The prognostic algorithm, implemented using Gaussian process regression, estimates the remaining life of the faulted component. The paperalso covers the selection of fault modes for coverage and methods developed for fault injection. Validation experiments were conducted in both laboratory and flight conditions using a flyable electromechanical actuator test stand. The stand allows test actuators to be subjected to realistic environmental and operating conditions while providing the capability to safely inject and monitor propagation of various fault modes. The paper covers both diagnostic and prognostic run-to-failure experiments, conducted in laboratory and flight conditions for several types of faults. The experiments demonstrated robust fault diagnosis on the selected set of component and sensor faults and high-accuracy predictions of failure time in prognostic scenarios.
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Prognostic Health-Management System Development for Electromechanical Actuators
Journal of Aerospace Information Systems, 2015Co-Authors: Edward Balaban, Carl Ott, Indranil Roychoudhury, Sriram Narasimhan, Abhinav Saxena, Marion Koopmans, Kai GoebelAbstract:Electromechanical actuators have been gaining increased acceptance as safety-critical actuation devicesinthe next generation of aircraft and spacecraft. The aerospace manufacturers are not ready, however, to completely embrace electromechanical actuators for all applications due to apprehension with regard to some of the more critical fault modes. This work aims to help address these concerns by developing and testing a prognostic Health-Management System that diagnoses electromechanical actuator faults and employs prognostic algorithmstotrack fault progression and predict the actuator's remaining useful life. The diagnostic algorithm is implemented using a combined modelbased and data-driven reasoner. The prognostic algorithm, implemented using Gaussian process regression, estimates the remaining life of the faulted component. The paper also covers the selection of fault modes for coverage and methods developed for fault injection. Validation experiments were conducted in both laboratory and flight conditions using a flyable electromechanical actuator test stand. The stand allows test actuators to be subjected to realistic environmental and operating conditions while providing the capability to safely inject and monitor propagation of various fault modes. The paper covers both diagnostic and prognostic run-to-failure experiments, conducted in laboratory and flight conditions for several types of faults. The experiments demonstrated robust fault diagnosis on the selected set of component and sensor faults and high-accuracy predictions of failure time in prognostic scenarios.
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Battery Health Management System for electric UAVs
IEEE Aerospace Conference Proceedings, 2011Co-Authors: Bhaskar Saha, Edward F. Hogge, Thomas H. Strom, Boyd L. Hill, Sixto L. Vazquez, Cuong C. Quach, Edwin Koshimoto, Kai GoebelAbstract:This paper presents a novel battery Health Management System for electric UAVs (unmanned aerial vehicles) based on a Bayesian inference driven prognostic framework. The aim is to be able to predict the end-of-discharge (EOD) event that indicates that the battery pack has run out of charge for any given flight of an electric UAV platform. The amount of usable charge of a battery for a given discharge profile is not only dependent on the starting state-of-charge (SOC), but also other factors like battery Health and the discharge or load profile imposed. This problem is more pronounced in battery powered electric UAVs since different flight regimes like takeoff/landing and cruise have different power requirements and a dead stick condition (battery shut off in flight) can have catastrophic consequences. Since UAVs deployments are relatively new, there is a lack of statistically significant flight data to motivate data-driven approaches. Consequently, we have developed a detailed discharge model for the batteries used and used it in a Bayesian inference based filtering (Particle Filtering) technique to generate remaining useful life (RUL) distributions for a given discharge. The results section presents the validation of this approach in hardware-in-the-loop tests.12
Xingkuan Yang - One of the best experts on this subject based on the ideXlab platform.
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Construction and Application of Failure Prediction and Health Management System for Bearing of Running Gear of Rolling Stock
2019 IEEE International Conference on Prognostics and Health Management (ICPHM), 2019Co-Authors: Hongzhi Song, Li Li, Xingkuan YangAbstract:According to the special working conditions of Chinese railway System, the failure prediction and Health Management System for the bearing of running gear of rolling stock is established, which includes data collection, storage and analysis. The overall structure of the System and the functions of each part in the System are introduced in detail, and the development of failure prediction and Health Management System for Chinese railway is prospected. After the initial trial of the System, on the basis of ensuring the safe operation of the rolling stock, the downtime caused by bearing failure or overhaul can be effectively reduced, the service efficiency of the rolling stock is improved, and data and technical support are provided for optimizing the design, manufacturing and assembly technology improvement of the bearing.
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ICPHM - Construction and Application of Failure Prediction and Health Management System for Bearing of Running Gear of Rolling Stock
2019 IEEE International Conference on Prognostics and Health Management (ICPHM), 2019Co-Authors: Hongzhi Song, Li Li, Xingkuan YangAbstract:According to the special working conditions of Chinese railway System, the failure prediction and Health Management System for the bearing of running gear of rolling stock is established, which includes data collection, storage and analysis. The overall structure of the System and the functions of each part in the System are introduced in detail, and the development of failure prediction and Health Management System for Chinese railway is prospected. After the initial trial of the System, on the basis of ensuring the safe operation of the rolling stock, the downtime caused by bearing failure or overhaul can be effectively reduced, the service efficiency of the rolling stock is improved, and data and technical support are provided for optimizing the design, manufacturing and assembly technology improvement of the bearing.
Ren-yi Tsai - One of the best experts on this subject based on the ideXlab platform.
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ICCE - Design of blood pressure measurement with a Health Management System for the aged
IEEE Transactions on Consumer Electronics, 2012Co-Authors: Chi-huang Hung, Ren-yi TsaiAbstract:In this paper we propose a design using a guiding System, Radio Frequency Identification (RFID), IEEE 802.15.1 short-range wireless transmission technology and the Internet to fabricate a blood pressure measurement (BPM) which works in cooperation with a Health Management System. Our design has many advantages, including being easy to use by the aged, low cost and wireless connectivity. It allows the early detection of high blood pressure and provides a doctor with a means for observing a patient's Health over a long period. The guiding System provides video guide features for the measuring steps, reminds the patient of the measurement results and makes suggestions. We propose here a new design to determine the BPM posture in order to increase the BPM reliability.
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Design of blood pressure measurement with a Health Management System for the aged
2012 IEEE International Conference on Consumer Electronics (ICCE), 2012Co-Authors: Chi-huang Hung, Ren-yi TsaiAbstract:In this paper we propose a design using a touchpad, Radio Frequency Identification (RFID), Bluetooth technology and the Internet to construct a blood pressure measurement which works in cooperation with a Health Management System.
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Design of blood pressure measurement with a Health Management System for the aged
IEEE Transactions on Consumer Electronics, 2012Co-Authors: Chi-huang Hung, Ren-yi TsaiAbstract:In this paper we propose a design using a guiding System, Radio Frequency Identification (RFID), IEEE 802.15.1 short-range wireless transmission technology and the Internet to fabricate a blood pressure measurement (BPM) which works in cooperation with a Health Management System. Our design has many advantages, including being easy to use by the aged, low cost and wireless connectivity. It allows the early detection of high blood pressure and provides a doctor with a means for observing a patient's Health over a long period. The guiding System provides video guide features for the measuring steps, reminds the patient of the measurement results and makes suggestions. We propose here a new design to determine the BPM posture in order to increase the BPM reliability.
