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Assessment of joint parameters in a Kinect sensor based rehabilitation game.

Manna, S.K. and Dubey, V. N., 2019. Assessment of joint parameters in a Kinect sensor based rehabilitation game. In: ASME 2019 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference, 18-21 August 2019, Anaheim, CA, USA.

Full text available as:

IDETC 2019-97519.pdf - Accepted Version
Available under License Creative Commons Attribution Non-commercial.


DOI: 10.1115/DETC2019-97519


Copyright © 2019 ASME. A Kinect sensor based basketball game is developed for delivering post-stroke exercises in association with a newly developed elbow exoskeleton. Few interesting features such as audio-visual feedback and scoring have been added to the game platform to enhance patient’s engagement during exercises. After playing the game, the performance score has been calculated based on their reachable points and reaching time to measure their current health conditions. During exercises, joint parameters are measured using the motion capture technique of Kinect sensor. The measurement accuracy of Kinect sensor is validated by two comparative studies where two healthy subjects were asked to move elbow joint in front of Kinect sensor wearing the developed elbow exoskeleton. In the first study, the joint information collected from Kinect sensor was compared with the exoskeleton based sensor. In the next study, the length of upperarm and forearm measured by Kinect were compared with the standard anthropometric data. The measurement errors between Kinect and exoskeleton are turned out to be in the acceptable range; 1% for subject 1 and 0.44% for subject 2 in case of joint angle; 5.55% and 3.58% for subject 1 and subject 2 respectively in case of joint torque. The average errors of Kinect measurement as compared to the anthropometric data of the two subjects are 16.52% for upperarm length and 9.87% for forearm length. It shows that Kinect sensor can measure the activity of joint movement with a minimum margin of error.

Item Type:Conference or Workshop Item (Paper)
Group:Bournemouth University Business School
ID Code:33344
Deposited By: Symplectic RT2
Deposited On:01 Jul 2020 08:56
Last Modified:14 Mar 2022 14:19


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