Dokumentdetails
ID
oai:arXiv.org:2404.01654
Thema
Computer Science - Computer Vision... Computer Science - Artificial Inte... Electrical Engineering and Systems... Electrical Engineering and Systems...Autor
Xiang, Xiang Zhang, Zihan Ma, Jing Deng, YaoKategorie
Computer Science
Jahr
2024
Auflistungsdatum
10.04.2024
Schlüsselwörter
parkinson engineering ai disease scienceZusammenfassung
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.
;Comment: Technical report for AI WALKUP, an APP winning 3rd Prize of 2022 HUST GS AI Innovation and Design Competition
Xiang, Xiang,Zhang, Zihan,Ma, Jing,Deng, Yao, 2024, AI WALKUP: A Computer-Vision Approach to Quantifying MDS-UPDRS in Parkinson's Disease
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