3차원 보행 영상 기반 퇴행성 관절염 환자 분류 알고리즘 개발

• 영문명: Developing Degenerative Arthritis Patient Classification Algorithm based on 3D Walking Video
• 발행기관: 한국산업경영시스템학회
• 저자명: 강태호 성시열 한상혁 박동현 강성우
• 간행물 정보: 『산업경영시스템학회지』제46권 제3호, 161~169쪽, 전체 9쪽
• 주제분류: 공학 > 산업공학
• 파일형태: PDF
• 발행일자: 2023.09.30

영문 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.

목차

1. 서 론

2. 이론적 배경

3. 연구 방법

4. 연구 결과

5. 결 론

References

키워드

Degenerative arthritis Azure Kinect DK ANOVA Random Forest Classification