{"title":"Activity recognition and its applications for elder care based on mono-type sensor network","authors":"Y. Zeng, Yu-Shian Chiu, Wen-Tsung Chang","doi":"10.1109/GCCE.2015.7398518","DOIUrl":null,"url":null,"abstract":"Total fertility rate of the world comes down every year. Low fertility rate implies the coming of aging societies, it raises high pressure to younger for the elder care. The objective of activity recognition is helpful for smart space technology in efficient allocation of manpower for elder care. We propose the activity recognition scheme performed on mono-type sensor network in space. Probability-based classification is available by analyzing sensor signal in order to train parameters of activity recognizers. The experiment results demonstrate that our scheme is capable of recognizing activities, generating activity of daily living, and detecting anomaly.","PeriodicalId":363743,"journal":{"name":"2015 IEEE 4th Global Conference on Consumer Electronics (GCCE)","volume":"41 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2015-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"5","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2015 IEEE 4th Global Conference on Consumer Electronics (GCCE)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/GCCE.2015.7398518","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
Total fertility rate of the world comes down every year. Low fertility rate implies the coming of aging societies, it raises high pressure to younger for the elder care. The objective of activity recognition is helpful for smart space technology in efficient allocation of manpower for elder care. We propose the activity recognition scheme performed on mono-type sensor network in space. Probability-based classification is available by analyzing sensor signal in order to train parameters of activity recognizers. The experiment results demonstrate that our scheme is capable of recognizing activities, generating activity of daily living, and detecting anomaly.