Skeleton-based human action evaluation using graph convolutional network for monitoring Alzheimer’s progression

•We propose a novel two-task graph convolutional network (2T-GCN) to represent skeleton data for human action evaluation (HAE) tasks of abnormality detection and quality evaluation. To the best of our knowledge, this is the first work that applies GCN to skeleton-based HAE.•We validate the effective...

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Bibliographic Details

Published in:	Pattern recognition Vol. 119; p. 108095
Main Authors:	Yu, Bruce X.B., Liu, Yan, Chan, Keith C.C., Yang, Qintai, Wang, Xiaoying
Format:	Journal Article
Language:	English
Published:	Elsevier Ltd 01.11.2021
Subjects:	Abnormality detection Alzheimer’s disease Graph neural network Human action evaluation Abnormality detection Human action evaluation Alzheimer’s disease Graph neural network
ISSN:	0031-3203, 1873-5142
Online Access:	Get full text
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