See How It Feels to Move : Relationships Between Movement Characteristics and Perception of Emotions in Dance
Burger, B., & Toiviainen, P. (2020). See How It Feels to Move : Relationships Between Movement Characteristics and Perception of Emotions in Dance. Human Technology, 16(3), 233-256. https://doi.org/10.17011/ht/urn.202011256764
Julkaistu sarjassa
Human TechnologyPäivämäärä
2020Tekijänoikeudet
©2020 Birgitta Burger & Petri Toiviainen, and the Open Science Centre, University
of Jyväskylä
Music makes humans move in ways found to relate to, for instance, musical characteristics, personality, or emotional content of the music. In this study, we investigated associations between embodiments of musical emotions and the perception thereof. After collecting motion capture data of dancers moving to emotionally distinct musical stimuli, silent stick-figure animations were rated by a set of observers regarding perceived discrete emotions, while 10 movement features were computationally extracted from the motion capture data. Results indicate kinematic profiles—emotion-specific sets of movement characteristics—that furthermore conform with dimensional models of valence and arousal, suggesting that observers rated the emotions consistently according to distinct movement features prevalent in the animations. Outcomes show commonalities and differences to a previous study that linked these movement features to auditory perception of musical emotion, providing insights into how emotional expression of music-induced movement could be conveyed and understood through auditory and visual channels, respectively.
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Julkaisija
Jyväskylän YliopistoISSN Hae Julkaisufoorumista
1795-6889Asiasanat
Versioita muualla
https://doi.org/10.17011/ht/urn.202011256764Julkaisu tutkimustietojärjestelmässä
https://converis.jyu.fi/converis/portal/detail/Publication/47228164
Metadata
Näytä kaikki kuvailutiedotKokoelmat
Rahoittaja(t)
Suomen AkatemiaRahoitusohjelmat(t)
Akatemiaprofessorin tehtävä, SA; Tutkijatohtori, SALisätietoja rahoituksesta
This research was supported by Academy of Finland grants (Project Numbers 272250, 274037, and 299067).Lisenssi
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