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Time-Varying Motion Pattern Detection with Application in Coaching and Rehabilitation
Blekinge Institute of Technology, Faculty of Computing, Department of Computer Science and Engineering.
2014 (English)Independent thesis Advanced level (degree of Master (Two Years))Student thesisAlternative title
Time-Varying Motion Pattern Detection with Application in Coaching and Rehabilitation (Swedish)
Abstract [en]

MS Kinect premiere has introduced new possibilities in the field of motion capture and has inspired many researchers to use it in coaching or rehabilitation support systems. Nonetheless, the majority of researches have been focused on game development and do not emphasize on motion analysis. In this thesis a set of tools are provided to detect certain motion pattern for rehabilitation, coaching or other similar area. A novel set of tracking signals, originated from joints data of body movement, along with their selection algorithm is proposed. The signals are utilized by a novel time-varying motion pattern detection algorithm which operates in the time domain and only needs one sample of a training pattern. The performance of the algorithm is evaluated on a group of five people performing seven types of exercises 10 times each, giving 350 samples. The performance evaluation shows significant success of the proposed algorithm. Also in spite of low recall factors, the results promise the high potential of future use of the algorithm. Finally, an interactive software application was created to record movement, create the reference pattern and perform coaching of individual movements.

Place, publisher, year, edition, pages
2014. , 59 p.
Keyword [en]
time-varying, motion detection, pattern recognition, spotting, coaching, rehabilitation, gesture
Keyword [sv]
Master of Science Programme in Electrical Engineering with emphasis on Signal Processing /Masterprogram i Elektroteknik med inriktning mot signalbehandling
National Category
Signal Processing
URN: urn:nbn:se:bth-2248Local ID: diva2:829515
Available from: 2015-04-22 Created: 2014-06-17 Last updated: 2015-06-30Bibliographically approved

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Department of Computer Science and Engineering
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