Abstract
Quantification of time series that relate to physiological data is challenging for empirical music research. Up to now, most studies have focused on time-dependent responses of individual subjects in controlled environments. However, little is known about time-dependent responses of between-subject interactions in an ecological context. This paper provides new findings on the statistical analysis of group synchronicity in response to musical stimuli. Different statistical techniques were applied to time-dependent data obtained from an experiment on embodied listening in individual and group settings. Analysis of inter group synchronicity are described. Dynamic Time Warping (DTW) and Cross Correlation Function (CCF) were found to be valid methods to estimate group coherence of the resulting movements. It was found that synchronicity of movements between individuals (human–human interactions) increases significantly in the social context. Moreover, Analysis of Variance (ANOVA) revealed that the type of music is the predominant factor in both the individual and the social context.
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Acknowledgements
This research has been conducted in the framework of the MEFEMCO (Methodological foundations of embodied music cognition) project (2008–2011) with support of the Fund for Scientific Research of Flanders (FWO), and the Emcomettecca (Embodied music cognition and mediation technology for creative and cultural applications) project, Methusalem-BOF Ghent University.
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Desmet, F., Leman, M., Lesaffre, M., De Bruyn, L. (2009). Statistical Analysis of Human Body Movement and Group Interactions in Response to Music. In: Fink, A., Lausen, B., Seidel, W., Ultsch, A. (eds) Advances in Data Analysis, Data Handling and Business Intelligence. Studies in Classification, Data Analysis, and Knowledge Organization. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-01044-6_36
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DOI: https://doi.org/10.1007/978-3-642-01044-6_36
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