Personal Sensing: Understanding Mental Health Using Ubiquitous Sensors and Machine Learning.
Personal Sensing: Understanding Mental Health Using Ubiquitous Sensors and Machine Learning.
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DOI:
10.1146/annurev-clinpsy-032816-044949
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发表时间:
2017-05-08
影响因子:
18.4
通讯作者:
Schueller SM
中科院分区:
文献类型:
--
作者:
Mohr DC;Zhang M;Schueller SM
Sensors in everyday devices, such as our phones, wearables, and computers, leave a stream of digital traces. Personal sensing refers to collecting and analyzing data from sensors embedded in the context of daily life with the aim of identifying human behaviors, thoughts, feelings, and traits. This article provides a critical review of personal sensing research related to mental health, focused principally on smartphones, but also including studies of wearables, social media, and computers. We provide a layered, hierarchical model for translating raw sensor data into markers of behaviors and states related to mental health. Also discussed are research methods as well as challenges, including privacy and problems of dimensionality. Although personal sensing is still in its infancy, it holds great promise as a method for conducting mental health research and as a clinical tool for monitoring at-risk populations and providing the foundation for the next generation of mobile health (or mHealth) interventions.
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影响因子:
3.7
作者:
Andrews S;Ellis DA;Shaw H;Piwek L
通讯作者:
Piwek L
影响因子:
7.4
作者:
Burns MN;Begale M;Duffecy J;Gergle D;Karr CJ;Giangrande E;Mohr DC
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Mohr DC
影响因子:
7.4
作者:
Asselbergs J;Ruwaard J;Ejdys M;Schrader N;Sijbrandij M;Riper H
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Riper H
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作者:
Berke, Ethan M.;Choudhury, Tanzeem;Rabbi, Mashfiqui
通讯作者:
Rabbi, Mashfiqui
DOI:
10.1109/jproc.2013.2262913
发表时间:
2013-12-01
期刊:
Proceedings of the IEEE. Institute of Electrical and Electronics Engineers
影响因子:
--
作者:
Acampora G;Cook DJ;Rashidi P;Vasilakos AV
通讯作者:
Vasilakos AV