Acceptability of using a Kinect-based virtual reality intervention to remediate arm motor impairments in subacute stroke

Demers, Marika; Kong, Daniel Chan Chun; Levin, Mindy F.

doi:10.1109/icvr.2017.8007496

Cited by 3 publications

(1 citation statement)

References 4 publications

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“…Progress toward customizable motion training and evaluation has been made using Kinect data and techniques like Dynamic Time Warping (DTW), which scales time-series motion data for comparative analysis [7]. Several other recent studies have validated the Kinect as a rehabilitative device [1,2,3]. Despite many advances in motion tracking in this field, there remains one major component in motivating and engaging players: realtime affective interaction.…”

Section: Introductionmentioning

confidence: 99%

Real-time stealth intervention for motor learning using player flow-state

Tadayon

Amresh

McDaniel

et al. 2018

2018 IEEE 6th International Conference on Serious Games and Applications for Health (SeGAH)

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We present a novel approach to real-time adaptation in serious games for at-home motor learning. Our approach assesses and responds to the "flow-state" of players by tracking and classifying facial emotions in real-time using the Kinect camera. Three different approaches for stealth assessment and adaptation using performance and flow-state data are defined, along with a case-study evaluation of these approaches based on their effectiveness at maintaining positive affective interaction in a subject.

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Section: Introductionmentioning

confidence: 99%

Real-time stealth intervention for motor learning using player flow-state

Tadayon

Amresh

McDaniel

et al. 2018

2018 IEEE 6th International Conference on Serious Games and Applications for Health (SeGAH)

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Using Microsoft Kinect V2 for Custom Upper-Limb Rehabilitation Exercises

Rabbani

Ali

Amin

2021

Advances in Intelligent Systems and Computing

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

Souza

Naves

Sá

2021

RSD

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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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Acceptability of using a Kinect-based virtual reality intervention to remediate arm motor impairments in subacute stroke

Cited by 3 publications

References 4 publications

Real-time stealth intervention for motor learning using player flow-state

Real-time stealth intervention for motor learning using player flow-state

Using Microsoft Kinect V2 for Custom Upper-Limb Rehabilitation Exercises

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

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