Abstract
Everyday, people experience stress, and it has been suggested for a long time that stress will eventually develop into anxiety as well as other physical issues. The emerging technology, such as wearable sensors and smartphone, have enabled the opportunity of using the technology to help solve the issue. In this paper, we proposed a system using Internet of Things architecture where we adopted an activity tracker as our sensing device to reduce cumbersome for daily use. Among the total of 17 features extracted from activity tracker, five features from sleep data and six features from heart rate data were proposed to develop the stress recognition model. In the evaluation of our system, we achieved the accuracy as high as 81.70% on the cross validation and 78.95% when tested on the test set. Despite that this is a preliminary result, it has shown that it is possible to use the IoT architecture along with the activity tracker to accurately recognize stress and help improve one’s wellbeing.
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This work was supported by JSPS KAKENHI Grant number 15K00929.
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Lawanont, W., Mongkolnam, P., Nukoolkit, C., Inoue, M. (2019). Daily Stress Recognition System Using Activity Tracker and Smartphone Based on Physical Activity and Heart Rate Data. In: Czarnowski, I., Howlett, R., Jain, L., Vlacic, L. (eds) Intelligent Decision Technologies 2018. KES-IDT 2018 2018. Smart Innovation, Systems and Technologies, vol 97. Springer, Cham. https://doi.org/10.1007/978-3-319-92028-3_2
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DOI: https://doi.org/10.1007/978-3-319-92028-3_2
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