AI WALKUP: A Computer-Vision Approach to Quantifying MDS-UPDRS in Parkinson's Disease

• URL: http://arxiv.org/abs/2404.01654v1
• Date: Tue, 2 Apr 2024 05:53:34 GMT
• Title: AI WALKUP: A Computer-Vision Approach to Quantifying MDS-UPDRS in Parkinson's Disease
• Authors: Xiang Xiang, Zihan Zhang, Jing Ma, Yao Deng,
• Abstract summary: Parkinson's Disease (PD) is the second most common neurodegenerative disorder. The existing assessment method for PD is usually the Movement Disorder Society - Unified Parkinson's Disease Rating Scale (MDS-UPDRS) to assess the severity of various types of motor symptoms and disease progression. We want to use a computer vision based solution to capture human pose images based on a camera, reconstruct and perform motion analysis using algorithms, and extract the features of the amount of motion through feature engineering.
• Score: 26.404367811027996
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: Parkinson's Disease (PD) is the second most common neurodegenerative disorder. The existing assessment method for PD is usually the Movement Disorder Society - Unified Parkinson's Disease Rating Scale (MDS-UPDRS) to assess the severity of various types of motor symptoms and disease progression. However, manual assessment suffers from high subjectivity, lack of consistency, and high cost and low efficiency of manual communication. We want to use a computer vision based solution to capture human pose images based on a camera, reconstruct and perform motion analysis using algorithms, and extract the features of the amount of motion through feature engineering. The proposed approach can be deployed on different smartphones, and the video recording and artificial intelligence analysis can be done quickly and easily through our APP.

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