Vision skeleton trajectory based motion assessment system for healthcare rehabilitation-Reference-Cited by-同舟云学术

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Vision skeleton trajectory based motion assessment system for healthcare rehabilitation

Published:2020-08-28 Issue:9 Volume:2020 Page:805-808
ISSN:2051-3305
Container-title:The Journal of Engineering
language:en
Short-container-title:J. eng.

Author:

Shi Qinghongya¹²,Zhang Hong‐Bo¹²³,Dong Li‐Jia¹³,Lei Qing¹,Hsiao Tsung‐Chih¹²

Affiliation:

1. Department of Computer Science and TechnologyHuaqiao UniversityXiamenFujianPeople's Republic of China

2. Fujian Key Laboratory of Big Data Intelligence and SecurityHuaqiao UniversityXiamenFujianPeople's Republic of China

3. Xiamen Key Laboratory of Computer Vision and Pattern RecognitionHuaqiao UniversityXiamenFujianPeople's Republic of China

Funder

National Natural Science Foundation of China

Publisher

Institution of Engineering and Technology (IET)

Subject

General Engineering,Energy Engineering and Power Technology,Software

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1049/joe.2019.1316

Reference21 articles.

1. Recognition of table tennis strokes based on acceleration sensor;Huang L.S.;Transducer Microsyst. Technol.,2016

2. A comprehensive survey of vision‐based human action recognition methods;Zhang H.B.;Sensors,2019

3. Validation of enhanced kinect sensor based motion capturing for gait assessment;Müller B.;PLoS ONE,2017

4. Video and accelerometer‐based motion analysis for automated surgical skills assessment;Zia A.;Int. J. Comput. Assist. Radiol. Surg.,2018

5. GülerR.A. NeverovaN. KokkinosI.: ‘Densepose: dense human pose estimation In the wild’.Proc. IEEE Int. Conf. on Computer Vision and Pattern Recognition Salt Lake City UT USA 2018 pp.7297–9206

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