The Experts below are selected from a list of 107877 Experts worldwide ranked by ideXlab platform
Himanshu Thapliyal - One of the best experts on this subject based on the ideXlab platform.
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wearable Health Monitoring System for older adults in a smart home environment
arXiv: Signal Processing, 2021Co-Authors: Rajdeep Kumar Nath, Himanshu ThapliyalAbstract:The advent of IoT has enabled the design of connected and integrated smart Health Monitoring Systems. These smart Health Monitoring Systems could be realized in a smart home context to render long-term care to the elderly population. In this paper, we present the design of a wearable Health Monitoring System suitable for older adults in a smart home context. The proposed System offers solutions to monitor the stress, blood pressure, and location of an individual within a smart home environment. The stress detection model proposed in this work uses Electrodermal Activity (EDA), Photoplethysmogram (PPG), and Skin Temperature (ST) sensors embedded in a smart wristband for detecting physiological stress. The stress detection model is trained and tested using stress labels obtained from salivary cortisol which is a clinically established biomarker for physiological stress. A voice-based prototype is also implemented and the feasibility of the proposed System for integration in a smart home environment is analyzed by simulating a data acquisition and streaming scenario. We have also proposed a blood pressure estimation model using PPG signal and advanced regression techniques for integration with the stress detection model in the wearable Health Monitoring System. Finally, the design of a voice-assisted indoor location System is proposed for integration with the proposed System within a smart home environment. The proposed wearable Health Monitoring System is an important direction to realize a smart home environment with extensive diagnostic capabilities so that such a System could be useful for rendering long-term and personalized care to the aging population in the comfort of their home.
Han Ji - One of the best experts on this subject based on the ideXlab platform.
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a wireless sensor network based structural Health Monitoring System for highway bridges
Computer-aided Civil and Infrastructure Engineering, 2013Co-Authors: Xiaoya Hu, Bingwen Wang, Han JiAbstract:An integrated structural Health Monitoring (SHM) System for highway bridges is presented in this article. The System described is based on a customized wireless sensor network platform with a flexible design that provides a variety of sensors that are typical to SHM. These sensors include accelerometers, strain gauges, and temperature sensors with ultra-low power consumption. A S-Mote node, an acceleration sensor board, and a strain sensor board are developed to satisfy the requirements of bridge structural Monitoring. The article discusses how communication software components are integrated within TinyOS operating System to provide a flexible software platform whereas the data processing software performs analysis of acceleration, dynamic displacement, and dynamic strain data. The prototype System comprises a nearly linear multi-hop topology and is deployed on an in-service highway bridge. Data acquired from the System are used to examine network performance and to help evaluate the state of the bridge. Experimental results presented in the article show that the System enables continuous or regular interval Monitoring for in-service highway bridges.
Liang Zhang - One of the best experts on this subject based on the ideXlab platform.
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Distributed structural Health Monitoring System based on smart wireless sensor and multi-agent technology
Smart Materials and Structures, 2006Co-Authors: Shenfang Yuan, Xiaosong Lai, Xin Xu, Xia Zhao, Liang ZhangAbstract:This paper presents a new parallel distributed structural Health Monitoring technology based on the wireless sensor network and multi-agent System for large scale engineering structures. The basic idea of this new technology is that of adopting the smart wireless sensor with on-board microprocessor to form the Monitoring sensor network and the multi-agent technology to manage the whole Health Monitoring System. Using this technology, the Health Monitoring System becomes a distributing parallel System instead of a serial System with all processing work done by the central computer. The functions, the reliability, the flexibility and the speed of the whole System will be greatly improved. In addition, with wireless communication links instead of wires, the System weight and complexity will be lowered. In this paper, the distributed smart wireless sensor network is designed first based on the Berkeley Mote Mica wireless sensor platform. Two kinds of sensor have been adopted: piezoelectric sensors and electric resistance wires. They are connected to a Mica MPR board though a designed charge amplifier circuit or bridge circuit and MTS101 board. Seven&160;kinds of agents are defined for the structural Health Monitoring System. A distributed Health Monitoring architecture based on the defined agents is proposed. Finally, a composite structural Health Monitoring System based on a Mica wireless platform and multi-agent technology is developed to evaluate the efficacy of the new technology. The developed System can successfully monitor the concentrated load position or a loose bolt position.
Rajdeep Kumar Nath - One of the best experts on this subject based on the ideXlab platform.
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wearable Health Monitoring System for older adults in a smart home environment
arXiv: Signal Processing, 2021Co-Authors: Rajdeep Kumar Nath, Himanshu ThapliyalAbstract:The advent of IoT has enabled the design of connected and integrated smart Health Monitoring Systems. These smart Health Monitoring Systems could be realized in a smart home context to render long-term care to the elderly population. In this paper, we present the design of a wearable Health Monitoring System suitable for older adults in a smart home context. The proposed System offers solutions to monitor the stress, blood pressure, and location of an individual within a smart home environment. The stress detection model proposed in this work uses Electrodermal Activity (EDA), Photoplethysmogram (PPG), and Skin Temperature (ST) sensors embedded in a smart wristband for detecting physiological stress. The stress detection model is trained and tested using stress labels obtained from salivary cortisol which is a clinically established biomarker for physiological stress. A voice-based prototype is also implemented and the feasibility of the proposed System for integration in a smart home environment is analyzed by simulating a data acquisition and streaming scenario. We have also proposed a blood pressure estimation model using PPG signal and advanced regression techniques for integration with the stress detection model in the wearable Health Monitoring System. Finally, the design of a voice-assisted indoor location System is proposed for integration with the proposed System within a smart home environment. The proposed wearable Health Monitoring System is an important direction to realize a smart home environment with extensive diagnostic capabilities so that such a System could be useful for rendering long-term and personalized care to the aging population in the comfort of their home.
Xiaoya Hu - One of the best experts on this subject based on the ideXlab platform.
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a wireless sensor network based structural Health Monitoring System for highway bridges
Computer-aided Civil and Infrastructure Engineering, 2013Co-Authors: Xiaoya Hu, Bingwen Wang, Han JiAbstract:An integrated structural Health Monitoring (SHM) System for highway bridges is presented in this article. The System described is based on a customized wireless sensor network platform with a flexible design that provides a variety of sensors that are typical to SHM. These sensors include accelerometers, strain gauges, and temperature sensors with ultra-low power consumption. A S-Mote node, an acceleration sensor board, and a strain sensor board are developed to satisfy the requirements of bridge structural Monitoring. The article discusses how communication software components are integrated within TinyOS operating System to provide a flexible software platform whereas the data processing software performs analysis of acceleration, dynamic displacement, and dynamic strain data. The prototype System comprises a nearly linear multi-hop topology and is deployed on an in-service highway bridge. Data acquired from the System are used to examine network performance and to help evaluate the state of the bridge. Experimental results presented in the article show that the System enables continuous or regular interval Monitoring for in-service highway bridges.
