{"title":"A Classification Application Based on Support Vector Machine for Health IoT","authors":"Su Caiyu, Dong Jie, Mo Yi, Wu Shanyun","doi":"10.1109/PHM2022-London52454.2022.00064","DOIUrl":null,"url":null,"abstract":"The booming socio-economic development has led to great progress in the Internet of Things (IoT) and computer technology, which are gradually applied in all aspects of society. The Internet of Health Things (IoH) has emerged to meet the new era of higher demands placed on medical institutions. Machine learning is beginning to be used in the medical service system and is achieving significant results in driving related services. This paper analyses sensor data from several elderly people to analyse their postural status and text reports on classification metrics. The performance of the support vector machine on this problem is evaluated using information such as accuracy, recall, and F1 value. The study achieves a more accurate judgement of the health status of the elderly and provides some help to medical institutions in developing relevant treatment plans, as well as providing a reference for related academic research. abstract","PeriodicalId":269605,"journal":{"name":"2022 Prognostics and Health Management Conference (PHM-2022 London)","volume":"118 2 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2022 Prognostics and Health Management Conference (PHM-2022 London)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/PHM2022-London52454.2022.00064","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1
Abstract
The booming socio-economic development has led to great progress in the Internet of Things (IoT) and computer technology, which are gradually applied in all aspects of society. The Internet of Health Things (IoH) has emerged to meet the new era of higher demands placed on medical institutions. Machine learning is beginning to be used in the medical service system and is achieving significant results in driving related services. This paper analyses sensor data from several elderly people to analyse their postural status and text reports on classification metrics. The performance of the support vector machine on this problem is evaluated using information such as accuracy, recall, and F1 value. The study achieves a more accurate judgement of the health status of the elderly and provides some help to medical institutions in developing relevant treatment plans, as well as providing a reference for related academic research. abstract