Computer vision devices for tracking gross upper limb movements in post-stroke rehabilitation

Authors

DOI:

https://doi.org/10.33448/rsd-v10i6.16143

Keywords:

Stroke; Rehabilitation; Upper limb; Computer vision; Gross Motor function.

Abstract

Games and virtual reality are new concepts applied to upper limb rehabilitation after stroke. To perform upper limb physiotherapy rehabilitation and restore motor skills through virtual reality resources it is necessary to use an arm tracker, which would be the input of the video game. However, one of the main issues when starting a post-stroke rehabilitation game project is choosing the most suitable gross upper limb motion tracking device. Thus, this article aims to explore the gross upper limb motion tracking devices most commonly used in the scientific literature. To carry out this research, literature searches in English were conducted up to December 2020 in the ACM, PubMed and IEEE Xplore databases. We have selected a total of ninety-five (95) articles. In these studies, we identified the most used gross upper limb motion devices and we classified them into 5 different categories: RGB-D skeletal tracking, RGB object tracking, IR marker tracking, LeapMotion and RGB markerless body tracking. We found that most studies (52%) used RGB-D skeletal tracking. In addition, we found fifteen (15) different commercial systems or tracking devices and the most used was Kinect® (47% of all studies). However, it was not possible to generalize whether one device is better than the other. Although the amount of research in this area has increased significantly in recent years, additional studies are still needed to quantify the potential of the use of gross upper limb motion tracking devices in rehabilitation with games in post-stroke treatment.

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10/06/2021

How to Cite

SOUZA, J. T. de; NAVES, E. L. M.; SÁ, A. A. R. de. Computer vision devices for tracking gross upper limb movements in post-stroke rehabilitation. Research, Society and Development, [S. l.], v. 10, n. 6, p. e57910616143, 2021. DOI: 10.33448/rsd-v10i6.16143. Disponível em: https://rsdjournal.org/index.php/rsd/article/view/16143. Acesso em: 18 jun. 2021.

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Review Article