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Artificial neural network integrated heart rate variability with detection system
This paper describes an expert system of bio-information, which is combined with the smart devices using wireless sensor network (WSN). The physiological signals can be acquired by some wireless bio-sensor module, such as electrocardiogram (ECG), heart rate (HR), heart rate variability (HRV) and aut...
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creator | Chen-Shen Huang Kong-Sheng Huang Gwo-Jia Jong |
description | This paper describes an expert system of bio-information, which is combined with the smart devices using wireless sensor network (WSN). The physiological signals can be acquired by some wireless bio-sensor module, such as electrocardiogram (ECG), heart rate (HR), heart rate variability (HRV) and autonomic nervous system (ANS) activity, etc. The smart device transmits the bio-information by wireless network, which provides the real-time expert consultation function requirements for the purpose of bio-information analysis, storage and decision. The smart device is also connected the expert system server by the wireless network The HRV detection parameter value is adopted the criteria and basis for the features of diabetes by using artificial neural network (ANN) algorithm. The remote client can be inquired the bio-information at any time on internet information service (IIS) platform. In addition, the system platform is adequate for comparing the data files. The bio-information and diabetes information can be provided for the alert message timely and actively. The system of this paper is achieved a ubiquitous mobile physiological monitor purpose. |
doi_str_mv | 10.1109/ICAwST.2013.6765447 |
format | conference_proceeding |
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The physiological signals can be acquired by some wireless bio-sensor module, such as electrocardiogram (ECG), heart rate (HR), heart rate variability (HRV) and autonomic nervous system (ANS) activity, etc. The smart device transmits the bio-information by wireless network, which provides the real-time expert consultation function requirements for the purpose of bio-information analysis, storage and decision. The smart device is also connected the expert system server by the wireless network The HRV detection parameter value is adopted the criteria and basis for the features of diabetes by using artificial neural network (ANN) algorithm. The remote client can be inquired the bio-information at any time on internet information service (IIS) platform. In addition, the system platform is adequate for comparing the data files. The bio-information and diabetes information can be provided for the alert message timely and actively. The system of this paper is achieved a ubiquitous mobile physiological monitor purpose.</description><identifier>EISBN: 1479923648</identifier><identifier>EISBN: 9781479923649</identifier><identifier>DOI: 10.1109/ICAwST.2013.6765447</identifier><language>eng</language><publisher>IEEE</publisher><subject>Accuracy ; ANN ; Artificial neural networks ; Biomedical monitoring ; Diabetes ; Heart rate variability ; HRV ; Medical diagnostic imaging ; Smart device ; Training ; WSN</subject><ispartof>2013 International Joint Conference on Awareness Science and Technology & Ubi-Media Computing (iCAST 2013 & UMEDIA 2013), 2013, p.275-280</ispartof><woscitedreferencessubscribed>false</woscitedreferencessubscribed></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://ieeexplore.ieee.org/document/6765447$$EHTML$$P50$$Gieee$$H</linktohtml><link.rule.ids>309,310,780,784,789,790,2058,27925,54920</link.rule.ids><linktorsrc>$$Uhttps://ieeexplore.ieee.org/document/6765447$$EView_record_in_IEEE$$FView_record_in_$$GIEEE</linktorsrc></links><search><creatorcontrib>Chen-Shen Huang</creatorcontrib><creatorcontrib>Kong-Sheng Huang</creatorcontrib><creatorcontrib>Gwo-Jia Jong</creatorcontrib><title>Artificial neural network integrated heart rate variability with detection system</title><title>2013 International Joint Conference on Awareness Science and Technology & Ubi-Media Computing (iCAST 2013 & UMEDIA 2013)</title><addtitle>ICAwST</addtitle><description>This paper describes an expert system of bio-information, which is combined with the smart devices using wireless sensor network (WSN). The physiological signals can be acquired by some wireless bio-sensor module, such as electrocardiogram (ECG), heart rate (HR), heart rate variability (HRV) and autonomic nervous system (ANS) activity, etc. The smart device transmits the bio-information by wireless network, which provides the real-time expert consultation function requirements for the purpose of bio-information analysis, storage and decision. The smart device is also connected the expert system server by the wireless network The HRV detection parameter value is adopted the criteria and basis for the features of diabetes by using artificial neural network (ANN) algorithm. The remote client can be inquired the bio-information at any time on internet information service (IIS) platform. In addition, the system platform is adequate for comparing the data files. The bio-information and diabetes information can be provided for the alert message timely and actively. The system of this paper is achieved a ubiquitous mobile physiological monitor purpose.</description><subject>Accuracy</subject><subject>ANN</subject><subject>Artificial neural networks</subject><subject>Biomedical monitoring</subject><subject>Diabetes</subject><subject>Heart rate variability</subject><subject>HRV</subject><subject>Medical diagnostic imaging</subject><subject>Smart device</subject><subject>Training</subject><subject>WSN</subject><isbn>1479923648</isbn><isbn>9781479923649</isbn><fulltext>true</fulltext><rsrctype>conference_proceeding</rsrctype><creationdate>2013</creationdate><recordtype>conference_proceeding</recordtype><sourceid>6IE</sourceid><recordid>eNotj8lOwzAURc0CCSj9gm78Awl-9bysKiapEkJkXznxM32QpsgxVPl7pq7OXR3dw9gCRA0g_M3jenV8aeqlAFkba7RS9oxdgbLeL6VR7oLNx_FNCAHeOGHkJXte5UKJOgo9H_Az_6EcD_md01DwNYeCke8w5MJ_N_8KmUJLPZWJH6nseMSCXaHDwMdpLLi_Zucp9CPOT5yx5u62WT9Um6f7n3-birwolRVaJgAdvU8pASYLMbmuA43gk3Fag3HglbGhjdqh0AYgyai07VrtnJyxxb-WEHH7kWkf8rQ9Rctv8VdPMQ</recordid><startdate>201311</startdate><enddate>201311</enddate><creator>Chen-Shen Huang</creator><creator>Kong-Sheng Huang</creator><creator>Gwo-Jia Jong</creator><general>IEEE</general><scope>6IE</scope><scope>6IL</scope><scope>CBEJK</scope><scope>RIE</scope><scope>RIL</scope></search><sort><creationdate>201311</creationdate><title>Artificial neural network integrated heart rate variability with detection system</title><author>Chen-Shen Huang ; Kong-Sheng Huang ; Gwo-Jia Jong</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-i90t-7053f115d99fff1ef71df8cc15e19f685516819467abd58e05611f3d457cb5883</frbrgroupid><rsrctype>conference_proceedings</rsrctype><prefilter>conference_proceedings</prefilter><language>eng</language><creationdate>2013</creationdate><topic>Accuracy</topic><topic>ANN</topic><topic>Artificial neural networks</topic><topic>Biomedical monitoring</topic><topic>Diabetes</topic><topic>Heart rate variability</topic><topic>HRV</topic><topic>Medical diagnostic imaging</topic><topic>Smart device</topic><topic>Training</topic><topic>WSN</topic><toplevel>online_resources</toplevel><creatorcontrib>Chen-Shen Huang</creatorcontrib><creatorcontrib>Kong-Sheng Huang</creatorcontrib><creatorcontrib>Gwo-Jia Jong</creatorcontrib><collection>IEEE Electronic Library (IEL) Conference Proceedings</collection><collection>IEEE Proceedings Order Plan All Online (POP All Online) 1998-present by volume</collection><collection>IEEE Xplore All Conference Proceedings</collection><collection>IEEE Xplore</collection><collection>IEEE Proceedings Order Plans (POP All) 1998-Present</collection></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>Chen-Shen Huang</au><au>Kong-Sheng Huang</au><au>Gwo-Jia Jong</au><format>book</format><genre>proceeding</genre><ristype>CONF</ristype><atitle>Artificial neural network integrated heart rate variability with detection system</atitle><btitle>2013 International Joint Conference on Awareness Science and Technology & Ubi-Media Computing (iCAST 2013 & UMEDIA 2013)</btitle><stitle>ICAwST</stitle><date>2013-11</date><risdate>2013</risdate><spage>275</spage><epage>280</epage><pages>275-280</pages><eisbn>1479923648</eisbn><eisbn>9781479923649</eisbn><abstract>This paper describes an expert system of bio-information, which is combined with the smart devices using wireless sensor network (WSN). The physiological signals can be acquired by some wireless bio-sensor module, such as electrocardiogram (ECG), heart rate (HR), heart rate variability (HRV) and autonomic nervous system (ANS) activity, etc. The smart device transmits the bio-information by wireless network, which provides the real-time expert consultation function requirements for the purpose of bio-information analysis, storage and decision. The smart device is also connected the expert system server by the wireless network The HRV detection parameter value is adopted the criteria and basis for the features of diabetes by using artificial neural network (ANN) algorithm. The remote client can be inquired the bio-information at any time on internet information service (IIS) platform. In addition, the system platform is adequate for comparing the data files. The bio-information and diabetes information can be provided for the alert message timely and actively. The system of this paper is achieved a ubiquitous mobile physiological monitor purpose.</abstract><pub>IEEE</pub><doi>10.1109/ICAwST.2013.6765447</doi><tpages>6</tpages></addata></record> |
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language | eng |
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source | IEEE Electronic Library (IEL) Conference Proceedings |
subjects | Accuracy ANN Artificial neural networks Biomedical monitoring Diabetes Heart rate variability HRV Medical diagnostic imaging Smart device Training WSN |
title | Artificial neural network integrated heart rate variability with detection system |
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