Motion Sensor-Based Detection of Outlier Days Supporting Continuous Health Assessment for Single Older Adults

被引:2
|
作者
Mertens, Marc [1 ,2 ]
Debard, Glen [1 ]
Davis, Jesse [2 ]
Devriendt, Els [3 ,4 ]
Milisen, Koen [3 ,4 ]
Tournoy, Jos [4 ,5 ]
Croonenborghs, Tom [2 ]
Vanrumste, Bart [6 ,7 ]
机构
[1] Thomas More Univ Appl Sci Kempen, Mobilab & Care, Kleinhoefstr 4, B-2440 Geel, Belgium
[2] Katholieke Univ Leuven, Dept Comp Sci, B-3001 Heverlee, Belgium
[3] Katholieke Univ Leuven, Dept Publ Hlth & Primary Care, Acad Ctr Nursing & Midwifery, B-3001 Leuven, Belgium
[4] Univ Hosp Leuven, Dept Geriatr Med, B-3000 Leuven, Belgium
[5] Univ Leuven, Dept Publ Hlth & Primary Care, Gerontol & Geriatr, B-3000 Leuven, Belgium
[6] Katholieke Univ Leuven, eMedia Res Lab, Dept Elect Engn ESAT, B-3001 Heverlee, Belgium
[7] Katholieke Univ Leuven, STADIUS, Dept Elect Engn ESAT, B-3001 Heverlee, Belgium
关键词
monitoring of elderly people; PIR motion sensors; sensor network; assisted living; behavior analysis; assisted care; synthetic data; INDEX;
D O I
10.3390/s21186080
中图分类号
O65 [分析化学];
学科分类号
070302 ; 081704 ;
摘要
The aging population has resulted in interest in remote monitoring of elderly individuals' health and well being. This paper describes a simple unsupervised monitoring system that can automatically detect if an elderly individual's pattern of presence deviates substantially from the recent past. The proposed system uses a small set of low-cost motion sensors and analyzes the produced data to establish an individual's typical presence pattern. Then, the algorithm uses a distance function to determine whether the individual's observed presence for each day significantly deviates from their typical pattern. Empirically, the algorithm is validated on both synthetic data and data collected by installing our system in the residences of three older individuals. In the real-world setting, the system detected, respectively, five, four, and one deviating days in the three locations. The deviating days detected by the system could result from a health issue that requires attention. The information from the system can aid caregivers in assessing the subject's health status and allows for a targeted intervention. Although the system can be refined, we show that otherwise hidden but relevant events (e.g., fall incident and irregular sleep patterns) are detected and reported to the caregiver.
引用
收藏
页数:22
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