A Modified K-means Algorithm for Pattern Identification on Monitoring Care Systems

• Main Authors: Ya-Chu Chang, 張雅筑
• Other Authors: Kuang-Yow Lian
• Format: Others
• Language: zh-TW
• Published: 2011
• Online Access: http://ndltd.ncl.edu.tw/handle/6ss867

碩士 === 國立臺北科技大學 === 電機工程系研究所 === 99 === In response to the tendency of aging society, this thesis focuses on assistive technology to improve the monitoring care systems of the elderly. We develop an automatic technology to monitor sleeping posture. The variation of the sleeping posture of human being is closely related to their physiological status. To this end, we propose a modified K-means algorithm for pattern identification on monitoring sleeping posture. Based on the general K-means algorithm, we improve the clustering results through the proposed algorithm. We used the algorithm to find an appropriate number of clusters and produce the suitable initial center of each cluster. We construct a pressure button sensor panel to mimic a bed with dedicated pressure sensors. The monitoring platform is built on National Instruments LabVIEW and its function contains signal acquisition, analysis and processing. Finally, we carry out many monitoring experiments and verify our algorithm with satisfactory results.