步态
痴呆
路易氏体型失智症
物理医学与康复
计算机科学
路易体
步态分析
疾病
人工智能
医学
病理
作者
D. Wang,Chaima Zouaoui,Jongsoo Jang,Hassen Drira,Hyewon Seo
标识
DOI:10.1007/978-3-031-47076-9_8
摘要
Dementia with Lewy Bodies (DLB) and Alzheimer’s Disease (AD) are two common neurodegenerative diseases among elderly people. Gait analysis plays a significant role in clinical assessments to discriminate these neurological disorders from healthy controls, to grade disease severity, and to further differentiate dementia subtypes. In this paper, we propose a deep-learning based model specifically designed to evaluate gait impairment score for assessing the dementia severity using monocular gait videos. Named MAX-GR, our model estimates the sequence of 3D body skeletons, applies corrections based on spatio-temporal gait features extracted from the input video, and performs classification on the corrected 3D pose sequence to determine the MDS-UPDRS gait scores. Experimental results show that our technique outperforms alternative state-of-the-art methods. The code, demo videos, as well as 3D skeleton dataset is available at https://github.com/lisqzqng/Video-based-gait-analysis-for-dementia .
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