Characterizing movement fluency in musical performance: Toward a generic measure for technology enhanced learning

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  • Víctor Evaristo González Sánchez
  • Sofia Dahl
  • Johannes Hatfield
  • Rolf Inge Godøy

Abstract

Virtuosity in music performance is often associated with fast, precise, and efficient sound-producing movements. The generation of such highly skilled movements involves complex joint and muscle control by the central nervous system, and depends on the ability to anticipate, segment, and coarticulate motor elements, all within the biomechanical constraints of the human body. When successful, such motor skill should lead to what we characterize as fluency in musical performance. Detecting typical features of fluency could be very useful for technology-enhanced learning systems, assisting and supporting students during their individual practice sessions by giving feedback and helping them to adopt sustainable movement patterns.
In this study, we propose to assess fluency in musical performance as the ability to smoothly and efficiently coordinate while accurately performing slow, transitionary, and rapid movements. To this end, the movements of three cello players and three drummers at different levels of skill were recorded with an optical motion capture system, while a wireless electromyography (EMG) system recorded the corresponding muscle activity from relevant landmarks. We analyzed the kinematic and coarticulation characteristics of these recordings separately and then propose a combined model of fluency in musical performance predicting music sophistication. Results suggest that expert performers' movements are characterized by consistently smooth strokes and scaling of muscle phasic coactivation. The explored model of fluency as a function of movement smoothness and coarticulation patterns was shown to be limited by the sample size, but it serves as a proof of concept. Results from this study show the potential of a technology-enhanced objective measure of fluency in musical performance, which could lead to improved practices for aspiring musicians, instructors, and researchers.
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Virtuosity in music performance is often associated with fast, precise, and efficient sound-producing movements. The generation of such highly skilled movements involves complex joint and muscle control by the central nervous system, and depends on the ability to anticipate, segment, and coarticulate motor elements, all within the biomechanical constraints of the human body. When successful, such motor skill should lead to what we characterize as fluency in musical performance. Detecting typical features of fluency could be very useful for technology-enhanced learning systems, assisting and supporting students during their individual practice sessions by giving feedback and helping them to adopt sustainable movement patterns.
In this study, we propose to assess fluency in musical performance as the ability to smoothly and efficiently coordinate while accurately performing slow, transitionary, and rapid movements. To this end, the movements of three cello players and three drummers at different levels of skill were recorded with an optical motion capture system, while a wireless electromyography (EMG) system recorded the corresponding muscle activity from relevant landmarks. We analyzed the kinematic and coarticulation characteristics of these recordings separately and then propose a combined model of fluency in musical performance predicting music sophistication. Results suggest that expert performers' movements are characterized by consistently smooth strokes and scaling of muscle phasic coactivation. The explored model of fluency as a function of movement smoothness and coarticulation patterns was shown to be limited by the sample size, but it serves as a proof of concept. Results from this study show the potential of a technology-enhanced objective measure of fluency in musical performance, which could lead to improved practices for aspiring musicians, instructors, and researchers.
Original languageEnglish
JournalFrontiers in Psychology
Volume10
ISSN1664-1078
DOI
Publication statusPublished - 2019
Publication categoryResearch
Peer-reviewedYes

    Research areas

  • performance, Motion capture, Phase transition, Smoothness, motor control, EMG, skill acquisition
ID: 291965528