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dc.contributor.authorToiviainen, Petri
dc.contributor.authorHartmann, Martín
dc.date.accessioned2021-11-18T06:02:33Z
dc.date.available2021-11-18T06:02:33Z
dc.date.issued2022
dc.identifier.citationToiviainen, P., & Hartmann, M. (2022). Analyzing multidimensional movement interaction with generalized cross-wavelet transform. <i>Human Movement Science</i>, <i>81</i>, Article 102894. <a href="https://doi.org/10.1016/j.humov.2021.102894" target="_blank">https://doi.org/10.1016/j.humov.2021.102894</a>
dc.identifier.otherCONVID_101914764
dc.identifier.urihttps://jyx.jyu.fi/handle/123456789/78685
dc.description.abstractHumans are able to synchronize with musical events whilst coordinating their movements with others. Interpersonal entrainment phenomena, such as dance, involve multiple body parts and movement directions. Along with being multidimensional, dance movement interaction is plurifrequential, since it can occur at different frequencies simultaneously. Moreover, it is prone to nonstationarity, due to, for instance, displacements around the dance floor. Various methodological approaches have been adopted for the study of human entrainment, but only spectrogram-based techniques allow for an integral analysis thereof. This article proposes an alternative approach based upon the cross-wavelet transform, a state-of-the-art technique for nonstationary and plurifrequential analysis of univariate interaction. The presented approach generalizes the cross-wavelet transform to multidimensional signals. It allows to identify, for different frequencies of movement, estimates of interaction and leader-follower dynamics across body parts and movement directions. Further, the generalized cross-wavelet transform can be used to quantify the frequency-wise contribution of individual body parts and movement directions to overall movement synchrony. Since both in- and anti-phase relationships are dominant modes of coordination, the proposed implementation ignores whether movements are identical or opposite in phase. The article provides a thorough mathematical description of the method and includes proofs of its invariance under translation, rotation, and reflection. Finally, its properties and performance are illustrated via four examples using simulated data and behavioral data collected through a mirror game task and a free dance movement task.en
dc.format.mimetypeapplication/pdf
dc.language.isoeng
dc.publisherElsevier
dc.relation.ispartofseriesHuman Movement Science
dc.rightsCC BY 4.0
dc.subject.otherEntrainment
dc.subject.otherJoint action
dc.subject.otherDyadic interaction
dc.subject.otherLeader-follower dynamics
dc.subject.otherTime-frequency analysis
dc.titleAnalyzing multidimensional movement interaction with generalized cross-wavelet transform
dc.typearticle
dc.identifier.urnURN:NBN:fi:jyu-202111185696
dc.contributor.laitosMusiikin, taiteen ja kulttuurin tutkimuksen laitosfi
dc.contributor.laitosDepartment of Music, Art and Culture Studiesen
dc.contributor.oppiaineSecure Communications Engineering and Signal Processingfi
dc.contributor.oppiaineMusiikkitiedefi
dc.contributor.oppiaineMusic, Mind and Technologyfi
dc.contributor.oppiaineTekniikkafi
dc.contributor.oppiaineSecure Communications Engineering and Signal Processingen
dc.contributor.oppiaineMusicologyen
dc.contributor.oppiaineMusic, Mind and Technologyen
dc.contributor.oppiaineEngineeringen
dc.type.urihttp://purl.org/eprint/type/JournalArticle
dc.type.coarhttp://purl.org/coar/resource_type/c_2df8fbb1
dc.description.reviewstatuspeerReviewed
dc.relation.issn0167-9457
dc.relation.volume81
dc.type.versionpublishedVersion
dc.rights.copyright© 2021 The Authors. Published by Elsevier B.V.
dc.rights.accesslevelopenAccessfi
dc.relation.grantnumber332331
dc.relation.grantnumber314651
dc.subject.ysomusiikki
dc.subject.ysoliike
dc.subject.ysorytmitaju
dc.subject.ysososiaalinen vuorovaikutus
dc.subject.ysosignaalinkäsittely
dc.subject.ysosynkronointi
dc.subject.ysotanssi
dc.subject.ysoliikeanalyysi
dc.format.contentfulltext
jyx.subject.urihttp://www.yso.fi/onto/yso/p1808
jyx.subject.urihttp://www.yso.fi/onto/yso/p706
jyx.subject.urihttp://www.yso.fi/onto/yso/p25263
jyx.subject.urihttp://www.yso.fi/onto/yso/p10590
jyx.subject.urihttp://www.yso.fi/onto/yso/p12266
jyx.subject.urihttp://www.yso.fi/onto/yso/p23930
jyx.subject.urihttp://www.yso.fi/onto/yso/p1278
jyx.subject.urihttp://www.yso.fi/onto/yso/p24952
dc.rights.urlhttps://creativecommons.org/licenses/by/4.0/
dc.relation.doi10.1016/j.humov.2021.102894
dc.relation.funderResearch Council of Finlanden
dc.relation.funderResearch Council of Finlanden
dc.relation.funderSuomen Akatemiafi
dc.relation.funderSuomen Akatemiafi
jyx.fundingprogramAcademy Project, AoFen
jyx.fundingprogramPostdoctoral Researcher, AoFen
jyx.fundingprogramAkatemiahanke, SAfi
jyx.fundingprogramTutkijatohtori, SAfi
jyx.fundinginformationThis work was supported by funding from the Academy of Finland (project numbers 332331 and 314651).
dc.type.okmA1


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