Detection abnormal pattern in activities of daily living using sequence alignment method
Detection abnormal pattern in activities of daily living using sequence alignment method
复制标题
使用序列比对方法检测日常生活活动的异常模式
DOI：
10.1109/iembs.2008.4649915
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发表时间：
2008
期刊：
影响因子：
--
通讯作者：
Soo Joon Park
中科院分区：
文献类型：
--
作者：
Ho;Seon;Soo Joon Park
随着老龄化的快速到来，照顾老年人的必要性增加。随着对需要他人帮助的患者的护理服务请求的增加，已经开发了用于护理服务的各种系统。对于护理服务，最近开发了跟踪和监视个人日常活动的技术，并通过分析跟踪的数据来识别个人的日常活动。特别是，已经开发了用于照顾其状态应被定期检查的人的系统，例如病人或老年人。普通护理系统很好地跟踪个人执行的活动，但仅限于检测个人的状态，如正常或异常状态。因此，有必要开发一种新的计算方法，通过一系列日常生活活动的变化来检测生命模式中的异常迹象。
As the aging is rapidly coming, the necessity of cares for old people increases. As requests for care services for patients requiring help of others increases, various systems for care services have been developed. For care services, recently, there have been developed technologies of tracking and monitoring daily activities of a person and recognizing the daily activities of the person by analyzing tracked data. Particularly, there have been developed systems for taking care of a person whose state should be periodically checked, such as patients or old persons. General care systems are good for tracking what activity the person executes, but limited to detecting what a person's state is, such as a normal or an abnormal state. So it is necessary to develop a new computational method to detect abnormal signs in a life pattern via changes of a sequence of activities of daily living.