J Mov Disord.  2022 May;15(2):140-145. 10.14802/jmd.21129.

Automatic Measurement of Postural Abnormalities With a Pose Estimation Algorithm in Parkinson’s Disease

• Shin JH
• Woo KA
• Lee CY
• Jeon SH
• Kim HJ
• Jeon B

• KMID: 2530219
• DOI: http://doi.org/10.14802/jmd.21129

Abstract

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.

Keyword

Parkinson’s disease; Camptocormia; Pose estimation