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MusicJacket: the efficacy of real-time vibrotactile feedback for learning to play the violin

Published: 10 April 2010 Publication History

Abstract

This research investigates the potential for vibrotactile feedback to enhance motor learning in the context of playing the violin. A prototype has been built which delivers vibrotactile feedback to the arms to indicate to a novice player how to correctly hold the violin and how to bow in a straight manner. This prototype was tested in a pilot user study with four complete beginners. Observations showed improvements in three of the four players whilst receiving the feedback. We also discuss the pros and cons of using negative feedback to enhance learning.

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A. Bloomfield and N.I. Badler, "Virtual Training via Vibrotactile Arrays," Presence: Teleoperators & Virtual Environments, vol. 17, Apr. 2008, pp. 103--120.
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J. Konczak, H. vander Velden, and L. Jaeger, Learning to play the violin: motor control by freezing, not freeing degrees of freedom," Journal of Motor Behavior, vol. 41, 2009, pp. 243--252.
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J. Lieberman and C. Breazeal, "TIKL: Development of a Wearable Vibrotactile Feedback Suit for Improved Human Motor Learning," Robotics, IEEE Transactions on, vol. 23, 2007, pp. 919--926.
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D. Spelmezan, M. Jacobs, A. Hilgers, and J. Borchers, "Tactile motion instructions for physical activities," Proc. CHI 2009.
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van der Linden, J., Schoonderwaldt E., Bird J.,Johnson, R., MusicJacket - A Case Study in Combining Motion Capture and Vibrotactile Feedback to Teach Violin Bowing. IEEE Transactions on Instrumentation and Measurements, Special issue on Haptic, Audio and Visual Environments for Games. 2009, (Under review.)
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cover image ACM Conferences
CHI EA '10: CHI '10 Extended Abstracts on Human Factors in Computing Systems
April 2010
2219 pages
ISBN:9781605589305
DOI:10.1145/1753846

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 10 April 2010

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Author Tags

  1. haptics
  2. motion capture
  3. vibrotactile feedback
  4. violin teaching
  5. wearable computing

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CHI '10
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CHI EA '10 Paper Acceptance Rate 350 of 1,346 submissions, 26%;
Overall Acceptance Rate 6,164 of 23,696 submissions, 26%

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