کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
4966866 1449296 2017 12 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Monitoring stress with a wrist device using context
ترجمه فارسی عنوان
استرس را با یک دستگاه مچ دست با استفاده از زمینه کنترل کنید
کلمات کلیدی
تشخیص استرس، زندگی واقعی، دستگاه مچ دست، فراگیری ماشین، متن نوشته، مراقبت های بهداشتی،
موضوعات مرتبط
مهندسی و علوم پایه مهندسی کامپیوتر نرم افزارهای علوم کامپیوتر
چکیده انگلیسی


- A method that unobtrusively monitors psychological stress in real life is presented.
- It is a context-based stress detector, which uses physical activity as a context.
- The context information significantly improved the performance of the method.
- The method detects (recalls) 70% of the stress events with a precision of 95%.

Being able to detect stress as it occurs can greatly contribute to dealing with its negative health and economic consequences. However, detecting stress in real life with an unobtrusive wrist device is a challenging task. The objective of this study is to develop a method for stress detection that can accurately, continuously and unobtrusively monitor psychological stress in real life. First, we explore the problem of stress detection using machine learning and signal processing techniques in laboratory conditions, and then we apply the extracted laboratory knowledge to real-life data. We propose a novel context-based stress-detection method. The method consists of three machine-learning components: a laboratory stress detector that is trained on laboratory data and detects short-term stress every 2 min; an activity recognizer that continuously recognizes the user's activity and thus provides context information; and a context-based stress detector that uses the outputs of the laboratory stress detector, activity recognizer and other contexts, in order to provide the final decision on 20-min intervals. Experiments on 55 days of real-life data showed that the method detects (recalls) 70% of the stress events with a precision of 95%.

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ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Journal of Biomedical Informatics - Volume 73, September 2017, Pages 159-170
نویسندگان
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