대한임베디드공학회논문지 (IEMEK Journal of Embedded Systems and Applications)

대한임베디드공학회 (Institute of Embedded Engineering of Korea)
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뇌성마비 환자의 자세 불균형 탐지를 위한 스마트폰 동영상 기반 보행 분석 시스템

Smartphone-based Gait Analysis System for the Detection of Postural Imbalance in Patients with Cerebral Palsy

  • 투고 : 2023.02.27
  • 심사 : 2023.04.17
  • 발행 : 2023.04.30
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초록

Gait analysis is an important tool in the clinical management of cerebral palsy, allowing for the assessment of condition severity, identification of potential gait abnormalities, planning and evaluation of interventions, and providing a baseline for future comparisons. However, traditional methods of gait analysis are costly and time-consuming, leading to a need for a more convenient and continuous method. This paper proposes a method for analyzing the posture of cerebral palsy patients using only smartphone videos and deep learning models, including a ResNet-based image tilt correction, AlphaPose for human pose estimation, and SmoothNet for temporal smoothing. The indicators employed in medical practice, such as the imbalance angles of shoulder and pelvis and the joint angles of spine-thighs, knees and ankles, were precisely examined. The proposed system surpassed pose estimation alone, reducing the mean absolute error for imbalance angles in frontal videos from 4.196° to 2.971° and for joint angles in sagittal videos from 5.889° to 5.442°.

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과제정보

본 논문은 정부 (교육부)의 재원으로 한국연구재단 기초연구사업의 지원을 받아 수행된 연구임 (No. NRF-2020R1I1A3070636). 본 논문은 교육부 및 한국연구재단의 4단계 BK21 사업 (경북대학교 컴퓨터학부 지능융합 소프트웨어 교육연구단)으로 지원된 연구임 (4199990214394).

참고문헌

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