Implicit Irregularity Detection using Unsupervised Learning on Daily Behaviors
學年 107
學期 2
出版（發表）日期 2019-02-01
作品名稱 Implicit Irregularity Detection using Unsupervised Learning on Daily Behaviors
作品名稱（其他語言）
著者 C. J. Shang; C. Y. Chang; G. L. Chen; S. H. Zhao; J. Z. Lin
單位
出版者
著錄名稱、卷期、頁數 IEEE Journal of Biomedical and Health Informatics, p.1-12
摘要 The irregularity detection of daily behaviors for the elderly is an important issue in homecare. Plenty of mechanisms have been developed to detect the health condition of the elderly based on the explicit irregularity of several biomedical parameters or some specific behaviors. However, few researches focus on detecting the implicit irregularity involving the combination of diverse behaviors, which can assess the cognitive and physical wellbeing of elders but cannot be directly identified based on sensor data. This paper proposes an Implicit IRregularity Detection (IIRD) mechanism, which aims to detect the implicit irregularity by developing the unsupervised learning algorithm based on daily behaviors. The proposed IIRD mechanism identifies the distance and similarity between daily behaviors, which are important features to distinguish the regular and irregular daily behaviors and detect the implicit irregularity of elderly health condition. Performance results show that the proposed IIRD outperforms the existing unsupervised machine learning mechanisms in terms of the detection accuracy and irregularity recall.
關鍵字 Senior citizens;Feature extraction;Biomedical monitoring;Unsupervised learning;Monitoring;Analytical models;Hardware
語言 zh_TW
ISSN 2168-2194
期刊性質 國內
收錄於 SCI
產學合作
通訊作者
審稿制度 否
國別 TWN
公開徵稿
出版型式 ,電子版
相關連結

機構典藏連結 ( http://tkuir.lib.tku.edu.tw:8080/dspace/handle/987654321/116996 )