Passive and In-situ Assessment of Mental and Physical Well-being using Mobile Sensors

被引:0
|
作者
Rabbi, Mashfiqui [1 ,3 ]
Ali, Shahid [2 ]
Choudhury, Tanzeem [1 ,3 ]
Berke, Ethan [2 ]
机构
[1] Cornell Univ, Dept Informat Sci, Ithaca, NY 14853 USA
[2] Dartmouth Med Sch, Community & Family Med, Hanover, NH USA
[3] Dartmouth Coll, Dept Comp Sci, Hanover, NH 03755 USA
来源
UBICOMP'11: PROCEEDINGS OF THE 2011 ACM INTERNATIONAL CONFERENCE ON UBIQUITOUS COMPUTING | 2011年
关键词
mental health; physical health; activity inference; mobile sensing; machine learning; MOMENTARY ASSESSMENT; OLDER-ADULTS; DEPRESSION; HEALTH; RECOGNITION; VARIABILITY; DISABILITY; DISORDERS; INTENSITY; VALIDITY;
D O I
暂无
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
The idea of continuously monitoring well-being using mobile sensing systems is gaining popularity. In -situ measurement of human behavior has the potential to overcome the short comings of gold -standard surveys that have been used for decades by the medical community. However, current sensing systems have mainly focused on tracking physical health; some have approximated aspects of mental health based on proximity measurements but have not been compared against medically accepted screening instruments. In this paper, we show the feasibility of a multi -modal mobile sensing system to simultaneously assess mental and physical health. By continuously capturing line -grained motion and privacy sensitive audio data, we are able to derive different metrics that reflect the results of commonly used surveys for assessing well-being by the medical community. In addition, we present a case study that highlights how errors in assessment due to the subjective nature of the responses could potentially be avoided by continuous mobile sensing.
引用
收藏
页码:385 / 394
页数:10
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