Video-Based Activity Recognition for Automated Motor Assessment of Parkinson's Disease-Reference-Cited by-同舟云学术

Video-Based Activity Recognition for Automated Motor Assessment of Parkinson's Disease

Published:2023-10 Issue:10 Volume:27 Page:5032-5041
ISSN:2168-2194
Container-title:IEEE Journal of Biomedical and Health Informatics
language:
Short-container-title:IEEE J. Biomed. Health Inform.

Author:

Sarapata Grzegorz¹^ORCID,Dushin Yuriy¹^ORCID,Morinan Gareth¹^ORCID,Ong Joshua¹^ORCID,Budhdeo Sanjay²^ORCID,Kainz Bernhard³^ORCID,O'Keeffe Jonathan¹^ORCID

Affiliation:

1. Machine Medicine Technologies, London, U.K.

2. Department of Clinical and Movement Neurosciences, Institute of Neurology, University College London, Queen Square, London, U.K.

3. Department of Computing, Imperial College London, London, U.K.

Funder

Machine Medicine Technologies

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Health Information Management,Electrical and Electronic Engineering,Computer Science Applications,Health Informatics

Link

http://xplorestaging.ieee.org/ielx7/6221020/10272722/10193771.pdf?arnumber=10193771

Reference33 articles.

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2. Computer vision quantification of whole-body Parkinsonian bradykinesia using a large multi-site population

3. Shallow Graph Convolutional Network for Skeleton-Based Action Recognition

4. Spatial Temporal Graph Convolutional Networks for Skeleton-Based Action Recognition

5. Human action recognition using a temporal hierarchy of covariance descriptors on 3D joint locations;hussein;Proc 23rd Int Joint Conf Artif Intell,0

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