산업경영시스템학회지 (Journal of Korean Society of Industrial and Systems Engineering)

  • 제46권3호
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  • Pages.161-169
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  • 2023
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  • 2005-0461(pISSN)
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  • 2287-7975(eISSN)
한국산업경영시스템학회 (Society of Korea Industrial and System Engineering)
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3차원 보행 영상 기반 퇴행성 관절염 환자 분류 알고리즘 개발

Developing Degenerative Arthritis Patient Classification Algorithm based on 3D Walking Video

  • 강태호 (인하대학교 산업경영공학과) ;
  • 성시열 (인하대학교 산업경영공학과) ;
  • 한상혁 (인하대학교 산업경영공학과) ;
  • 박동현 (인하대학교 산업경영공학과) ;
  • 강성우 (인하대학교 산업경영공학과)
  • Tea-Ho Kang (Department of Industrial Engineering, Inha University) ;
  • Si-Yul Sung (Department of Industrial Engineering, Inha University) ;
  • Sang-Hyeok Han (Department of Industrial Engineering, Inha University) ;
  • Dong-Hyun Park (Department of Industrial Engineering, Inha University) ;
  • Sungwoo Kang (Department of Industrial Engineering, Inha University)
  • 투고 : 2023.08.17
  • 심사 : 2023.09.14
  • 발행 : 2023.09.30
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초록

Degenerative arthritis is a common joint disease that affects many elderly people and is typically diagnosed through radiography. However, the need for remote diagnosis is increasing because knee pain and walking disorders caused by degenerative arthritis make face-to-face treatment difficult. This study collects three-dimensional joint coordinates in real time using Azure Kinect DK and calculates 6 gait features through visualization and one-way ANOVA verification. The random forest classifier, trained with these characteristics, classified degenerative arthritis with an accuracy of 97.52%, and the model's basis for classification was identified through classification algorithm by features. Overall, this study not only compensated for the shortcomings of existing diagnostic methods, but also constructed a high-accuracy prediction model using statistically verified gait features and provided detailed prediction results.

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과제정보

This work was supported by the National Research Foundation of Korea(NRF) grant funded by the Korea government (MSIT) (No. 2022H1D8A3037396).

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