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KMID : 1197720220150020140
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대한파킨슨병 및 이상운동질환 학회지
2022 Volume.15 No. 2 p.140 ~ p.145
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Automatic Measurement of Postural Abnormalities With a Pose Estimation Algorithm in Parkinson’s Disease
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Shin Jung-Hwan
Woo Kyung-Ah
Lee Chan-Young
Jeon Seung-Ho
Kim Han-Joon
Jeon Beom-Seok
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Abstract
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Objective: This study aims to develop an automated and objective tool to evaluate postural abnormalities in Parkinson’s disease (PD) patients.
Methods: We applied a deep learning-based pose-estimation algorithm to lateral photos of prospectively enrolled PD patients (n = 28). We automatically measured the anterior flexion angle (AFA) and dropped head angle (DHA), which were validated with conventional manual labeling methods.
Results: The automatically measured DHA and AFA were in excellent agreement with manual labeling methods (intraclass correlation coefficient > 0.95) with mean bias equal to or less than 3 degrees.
Conclusion: The deep learning-based pose-estimation algorithm objectively measured postural abnormalities in PD patients.
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KEYWORD
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Parkinson’s disease, Camptocormia, Pose estimation
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