Journal of the Korea Society of Computer and Information (한국컴퓨터정보학회논문지)

Korean Society of Computer Information (한국컴퓨터정보학회)
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Recognition of Physical Rehabilitation on the Upper Limb Function using 3D Trajectory Information from the Stereo Vision Sensor

스테레오비전 센서의 3D 궤적 정보를 이용한 상지 재활 동작 인식

  • Kwon, Ki-Hyeon (Dept. of Electronics, Information & Communication Engineering, Kangwon National University) ;
  • Lee, Hyung-Bong (Dept. of Computer Science & Engineering, Gangneung-Wonju National University)
  • 권기현 (강원대학교 전자정보통신공학부) ;
  • 이형봉 (강릉원주대학교 컴퓨터공학과)
  • Received : 2013.07.14
  • Accepted : 2013.08.14
  • Published : 2013.08.30
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Abstract

The requirement of rehabilitation is increasing from the stroke, spinal cord injury. One of the most difficult part is the upper limb rehabilitation because of its nervous complexity. A rehabilitation has effectiveness when a professional therapist treats in work at facility, but it has problems of an accessibility, a constant availability, a self-participation and taking lots of cost and time. In this paper, we test and experiment the accuracy and execution time of the pattern recognition algorithms like PCA, ICA, LDA, SVM to show the recognition possibility of it on the upper limb function from the 3D trajectory information which is gathered from stereo vision sensor(Kinect). From the result, PCA, ICA have low accuracy, but LDA, SVM have good accuracy to use for physical rehabilitation on the upper limb function.

뇌졸중 및 척수 신경 손상으로 인해 재활에 대한 요구는 증대되고 있다. 재활 영역 중에서도 상지(上肢) 재활은 신경의 복잡도로 인해 매우 어렵고 시간이 많이 걸린다. 재활은 전문치료사가 시설에서 작업치료를 하는 것이 효과적이기는 하나, 접근성, 상시성, 자발성 등에 대한 문제와 함께 비용과 시간이 많이 소요되는 문제점을 가지고 있다. 이 논문에서는 상지 재활 동작을 인식하기 위해 스테레오 비전 센서를 통해 취득한 3D 궤적정보에 대해 PCA, ICA, LDA, SVM의 패턴인식 알고리즘을 적용하여 인식정확도 및 실행시간을 구하고, 여러 패턴인식 알고리즘 중에서 어떤 알고리즘이 인식정확도 및 실행시간 측면에서 적용이 가능한지 제시한다. 실험결과, PCA, ICA는 인식정확도가 낮아 사용하기에 부적합하며 LDA, SVM은 인식정확도가 우수하여 상지 재활 동작 인식에 사용이 적합함을 보인다.

Keywords

References

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