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Development of an automated exercise Detection and Evaluation system using the Kinect depth camera.

Muijzer, Frodo (2014) Development of an automated exercise Detection and Evaluation system using the Kinect depth camera.

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Abstract:This report described the development and implementation of a proof-of-principle exercise detection and evaluation framework. The objective was to find out whether the affordable Microsoft Kinect depth camera can be used for such an exercise evaluation system. In order to detect and evaluate an exercise, the exercise has to be taught to the computer system via explicitly defining the parameters. The concepts of a method used to notate dances, Labanotation, were used to develop a new parameterization method. Chapter 5 described how to convert joint positions, measured by the Kinect, into the translations used in the parameterization. Next a method was given to compare a single measured translation to an arbitrary element from the exercise playlist. Finally, the difficult issue of when to advance to subsequent items in the playlist was described. Chapter 7 discussed the protocol and results of experiments carried out to test the performance of the system. Unfortunately, the results of these experiments were not positive. Solely based on this, it can be stated that the Kinect depth camera cannot be used for automated rehabilitation exercise evaluation without alteration of the exercises, or exercise specific workarounds.
Item Type:Essay (Master)
Faculty:EEMCS: Electrical Engineering, Mathematics and Computer Science
Subject:44 medicine, 50 technical science in general
Programme:Biomedical Engineering MSc (66226)
Link to this item:https://purl.utwente.nl/essays/64507
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