{"title":"Artificial neural network integrated heart rate variability with detection system","authors":"Chen-Shen Huang, K. Huang, G. Jong","doi":"10.1109/ICAWST.2013.6765447","DOIUrl":null,"url":null,"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.","PeriodicalId":68697,"journal":{"name":"炎黄地理","volume":"21 1","pages":"275-280"},"PeriodicalIF":0.0000,"publicationDate":"2013-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"5","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"炎黄地理","FirstCategoryId":"1089","ListUrlMain":"https://doi.org/10.1109/ICAWST.2013.6765447","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 5
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.