Design of an Actigraphy Based Architecture for Mental Health Evaluation

  • Mi-Hwa Song
  • Jae-Sung Noh
  • Seung-Min Yoo
  • Young-Ho Lee
Conference paper
Part of the Lecture Notes in Electrical Engineering book series (LNEE, volume 215)


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.


Actigraphy Tri-axial accelerometer Activities of daily living Activity recognition 



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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Copyright information

© Springer Science+Business Media Dordrecht 2013

Authors and Affiliations

  • Mi-Hwa Song
    • 1
  • Jae-Sung Noh
    • 2
  • Seung-Min Yoo
    • 2
  • Young-Ho Lee
    • 3
  1. 1.U-Healthcare InstituteGachon UniversityYeonsu-GuSouth Korea
  2. 2.Department of Psychiatry & Behavioral Sciences, School of MedicineAjou UniversityYeoungtong-guSouth Korea
  3. 3.IT DepartmentGachon UniversityYeonsu-GuSouth Korea

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