Abstract
This paper introduces a decision support system architecture for continuous activity recognition and actigraphy, which are important for mental health evaluation; the architecture is based on triaxial accelerometer data. Recent developments in acceleration sensor device technologies have made it possible to precisely measure the acceleration of motor activity with a triaxial accelerometer for a lengthy period of time. We propose an AMD (Actigraphy based Mental health Decision support system) architecture for objectively measuring daily activity, recognizing continuous activities, and analyzing the behavior pattern of people with mental disorders, as well as the correlation between change in mood symptoms and mental disorders.
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Acknowledgments
This research was supported by grant no. 10037283 from the Industrial Strategic Technology Development Program funded by the Ministry of Knowledge Economy.
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Song, MH., Noh, JS., Yoo, SM., Lee, YH. (2013). Design of an Actigraphy Based Architecture for Mental Health Evaluation. In: Kim, K., Chung, KY. (eds) IT Convergence and Security 2012. Lecture Notes in Electrical Engineering, vol 215. Springer, Dordrecht. https://doi.org/10.1007/978-94-007-5860-5_118
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DOI: https://doi.org/10.1007/978-94-007-5860-5_118
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