Embodied Meter Revisited : Entrainment, Musical Content, and Genre in Music-Induced Movement
Toiviainen, P., & Carlson, E. (2022). Embodied Meter Revisited : Entrainment, Musical Content, and Genre in Music-Induced Movement. Music Perception, 39(3), 249-267. https://doi.org/10.1525/mp.2022.39.3.249
Published inMusic Perception
© 2022 the Regents of the University of California
Previous research has shown that humans tend to embody musical meter at multiple beat levels during spontaneous dance. This work that been based on identifying typical periodic movement patterns, or eigenmovements, and has relied on time-domain analyses. The current study: 1) presents a novel method of using time-frequency analysis in conjunction with group-level tensor decomposition; 2) compares its results to time-domain analysis, and 3) investigates how the amplitude of eigenmovements depends on musical content and genre. Data comprised three-dimensional motion capture of 72 participants’ spontaneous dance movements to 16 stimuli including eight different genres. Each trial was subjected to a discrete wavelet transform, concatenated into a trial-space-frequency tensor and decomposed using tensor decomposition. Twelve movement primitives, or eigenmovements, were identified, eleven of which were frequency locked with one of four metrical levels. The results suggest that time-frequency decomposition can more efficiently group movement directions together. Furthermore, the employed group-level decomposition allows for a straightforward analysis of interstimulus and interparticipant differences in music-induced movement. Amplitude of eigenmovements was found to depend on the amount of fluctuation in the music in particularly at one- and two-beat levels. ...
PublisherUniversity of California Press
ISSN Search the Publication Forum0730-7829
Dataset(s) related to the publicationhttp://urn.fi/URN:NBN:fi:jyu-202103262191
Publication in research information system
MetadataShow full item record
Related funder(s)Academy of Finland
Funding program(s)Academy Project, AoF
Additional information about fundingThis work was supported by the Academy of Finland (project number 332331).
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