期刊論文
| 學年 | 108 |
|---|---|
| 學期 | 2 |
| 出版（發表）日期 | 2020-06-05 |
| 作品名稱 | BIA: Behavior Identification Algorithm Using Unsupervised Learning Based on Sensor Data for Home Elderly |
| 作品名稱（其他語言） | |
| 著者 | Cuijuan Shang; Chih-Yung Chang; Guilin Chen; Shenghui Zhao; Haibao Chen |
| 單位 | |
| 出版者 | |
| 著錄名稱、卷期、頁數 | IEEE Journal of Biomedical and Health Informatics 24(6), p.1589-1600 |
| 摘要 | Behavior identification plays an important role in supporting homecare for the elderly living alone. In literature, plenty of algorithms have been designed to identify behaviors of the elderly by learning features or extracting patterns from sensor data. However, most of them adopted probabilistic models or supervised learning to identify behaviors based on labeled sensor data. This paper proposes a behavior identification algorithm ( BIA ) using unsupervised learning based on unlabeled sensor data for the elderly living alone in smart home. This paper presents the observation of elder behaviors with three features: Event Order , Time Length Similarity and Time Interval Similarity features. Based on these features of behavior observations, two properties of behaviors, including the Event Shift and Histogram Shape Similarity properties, are presented. According to these properties, the proposed BIA is developed. Finally, performance results show that the proposed BIA outperforms the existing unsupervised machine learning mechanisms in terms of the behavior identification precision and recall. |
| 關鍵字 | Senior citizens;Hidden Markov models;Smart homes;Histograms;Clustering algorithms;Unsupervised learning;Probabilistic logic |
| 語言 | en_US |
| ISSN | |
| 期刊性質 | 國外 |
| 收錄於 | SCI |
| 產學合作 | |
| 通訊作者 | Chih-Yung Chang |
| 審稿制度 | 否 |
| 國別 | USA |
| 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/987654321/118871 ) |