Science of Emotion and Sensibility (감성과학)

Korean Society for Emotion and Sensibility (한국감성과학회)
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Gait Feature Vectors for Post-stroke Prediction using Wearable Sensor

  • Hong, Seunghee (Center for Medical Convergence Metrology, KRISS) ;
  • Kim, Damee (Center for Medical Convergence Metrology, KRISS) ;
  • Park, Hongkyu (Department of KSB Convergence Research, ETRI) ;
  • Seo, Young (Center for Medical Convergence Metrology, KRISS) ;
  • Hussain, Iqram (Center for Medical Convergence Metrology, KRISS) ;
  • Park, Se Jin (Center for Medical Convergence Metrology, KRISS)
  • Received : 2019.06.19
  • Accepted : 2019.08.21
  • Published : 2019.09.30
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Abstract

Stroke is a health problem experienced by many elderly people around the world. Stroke has a devastating effect on quality of life, causing death or disability. Hemiplegia is clearly an early sign of a stroke and can be detected through patterns of body balance and gait. The goal of this study was to determine various feature vectors of foot pressure and gait parameters of patients with stroke through the use of a wearable sensor and to compare the gait parameters with those of healthy elderly people. To monitor the participants at all times, we used a simple measuring device rather than a medical device. We measured gait data of 220 healthy people older than 65 years of age and of 63 elderly patients who had experienced stroke less than 6 months earlier. The center of pressure and the acceleration during standing and gait-related tasks were recorded by a wearable insole sensor worn by the participants. Both the average acceleration and the maximum acceleration were significantly higher in the healthy participants (p < .01) than in the patients with stroke. Thus gait parameters are helpful for determining whether they are patients with stroke or normal elderly people.

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References

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