An internet-based wearable watch-over system for elderly and disabled utilizing EMG and accelerometer

  • Authors:

  • M. Kishimoto;T. Yoshida;T. Hayasaka;D. Mori;Y. Imai;N. Matsuki;T. Ishikawa;T. Yamaguchi

  • Affiliations:

  • Department of Bioengineering and Robotics, Tohoku University, Sendai, Japan;Department of Bioengineering and Robotics, Tohoku University, Sendai, Japan;Department of Bioengineering and Robotics, Tohoku University, Sendai, Japan;Department of Bioengineering and Robotics, Tohoku University, Sendai, Japan;Department of Bioengineering and Robotics, Tohoku University, Sendai, Japan;Department of Bioengineering and Robotics, Tohoku University, Sendai, Japan;(Correspd. Tel.: +81 22 795 4009/ Fax: +81 22 795 6959/ E-mail: ishikawa@pfsl.mech.tohoku.ac.jp) Department of Bioengineering and Robotics, Tohoku University, Sendai, Japan;Department of Bioengineering and Robotics, Tohoku University, Sendai, Japan

  • Venue:
  • Technology and Health Care
  • Year:
  • 2009

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Abstract

An effective way for preventing injuries and diseases among the elderly is to monitor their daily lives. In this regard, we propose the use of a "Hyper Hospital Network", which is an information support system for elderly people and patients. In the current study, we developed a wearable system for monitoring electromyography (EMG) and acceleration using the Hyper Hospital Network plan. The current system is an upgraded version of our previous system for gait analysis (Yoshida et al. [13], Telemedicine and e-Health 13 703-714), and lets us monitor decreases in exercise and the presence of a hemiplegic gait more accurately. To clarify the capabilities and reliability of the system, we performed three experimental evaluations: one to verify the performance of the wearable system, a second to detect a hemiplegic gait, and a third to monitor EMG and accelerations simultaneously. Our system successfully detected a lack of exercise by monitoring the iEMG in healthy volunteers. Moreover, by using EMG and acceleration signals simultaneously, the reliability of the Hampering Index (HI) for detecting hemiplegia walking was improved significantly. The present study provides useful knowledge for the development of a wearable computer designed to monitor the physical conditions of older persons and patients.