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Distance Physical Rehabilitation System Framework with Multi-Kinect Motion Captured Data

Mohammad Rafiuzzaman, Cemil Öz Published in Applied Sciences

Communications on Applied Electronics
Year of Publication: 2015
© 2015 by CAE Journal
10.5120/cae-1558

Mohammad Rafiuzzaman and Cemil Oz. Article: Distance Physical Rehabilitation System Framework with Multi-Kinect Motion Captured Data. Communications on Applied Electronics 1(5):29-39, April 2015. Published by Foundation of Computer Science, New York, USA. BibTeX

@article{key:article,
	author = {Mohammad Rafiuzzaman and Cemil Oz},
	title = {Article: Distance Physical Rehabilitation System Framework with Multi-Kinect Motion Captured Data},
	journal = {Communications on Applied Electronics},
	year = {2015},
	volume = {1},
	number = {5},
	pages = {29-39},
	month = {April},
	note = {Published by Foundation of Computer Science, New York, USA}
}

Abstract

Visiting physical therapists to the clinics for physical rehabilitation in regular basis is a very long and time-consuming trip where the final result for success is truly hard to see in daily training. That's why technological development in traditional physical rehabilitation system is both important, interesting and its effects on patients' time-management process is huge. In this paper we have proposed a framework for distance physical rehabilitation system using motion captured data from multiple Kinects which can interact directly with the patients, even grasp and track their movements so as to send those data back to the doctors in clinics using Windows Azure. Its goal is to coach patients through their physical therapy exercises and make those exercises a more enjoyable experience and bring physical therapy alive for them at their homes, the same way doctors interact with them in clinics.

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Keywords

Distance rehabilitation, Multiple Kinects, posture recognition, posture database, PCA, skeleton tracking, Windows Azure