ANOMALY DETECTION FOR HOME ACTIVITY BASED ON SEQUENCE PATTERN

被引：3
|
作者：
Poh, Soon-Chang [1 ]
Tan, Yi-Fei [1 ]
Cheong, Soon-Nyean [1 ]
Ooi, Chee-Pun [1 ]
Tan, Wooi-Haw [1 ]
机构：
[1] Multimedia Univ, Fac Engn, Selangor 63000, Malaysia
来源：
INTERNATIONAL JOURNAL OF TECHNOLOGY | 2019年 / 10卷 / 07期
关键词：
Anomaly detection; Elderly; Home activities; Sequence pattern; ACCELEROMETER;
D O I：
10.14716/ijtech.v10i7.3230
中图分类号：
T [工业技术];
学科分类号：
08 ;
摘要：
In Malaysia, the elderly population continues to grow. At the same time, young adults are unable to take care of their elderly parents due to work commitments. This results in an increasing number of elderly people living in solitude. Therefore, it is crucial to monitor elderly people's behavior, especially the pattern of their daily home activities. Abnormal behaviors in carrying out home activities may indicate health concerns in elderly people. Past studies have proposed the use of complex machine learning algorithms to detect anomalies in daily sequences of home activities. In this paper, a simple, alternative method for detecting anomalies in daily sequences of home activities is presented. The experiment results demonstrate that the model achieved a test accuracy of 90.79% on a public dataset.
引用
收藏
页码：1276 / 1285
页数：10
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