Linking Audience Physiology to Choreography

Han, Jiawen; Chernyshov, George; Sugawa, Moe; Zheng, Dingding; Hynds, Danny; Furukawa, Taichi; Padovani, Marcelo; Minamizawa, Kouta; Marky, Karola; Ward, Jamie A and Kunze, Kai. 2022. Linking Audience Physiology to Choreography. ACM Transactions on Computer-Human Interaction, ISSN 1073-0516 [Article] (In Press)

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Abstract or Description

The use of wearable sensor technology opens up exciting avenues for both art and HCI research, providing new ways to explore the invisible link between audience and performer. To be effective, such work requires close collaboration between performers and researchers. In this paper, we report on the co-design process and research insights from our work integrating physiological sensing and live performance. We explore the connection between the audience’s physiological data and their experience during the performance, analyzing a multi-modal dataset collected from 98 audience members. We identify notable moments based on HRV and EDA, and show how the audience's physiological responses can be linked to the choreography. The longitudinal changes in HRV features suggest a strong connection to the choreographer’s intended narrative arc, while EDA features appear to correspond with short-term audience responses to dramatic moments. We discuss the physiological phenomena and implications for designing feedback systems and interdisciplinary collaborations.

Item Type:

Article

Identification Number (DOI):

https://doi.org/10.1145/3557887

Additional Information:

"© 2022 Association for Computing Machinery . This is the author's version of the work. It is posted here for your personal use. Not for redistribution. The definitive Version of Record is available at, https://doi.org/10.1145/3557887."

This work is conducted under the Cybernetic Being project supported by JST Moonshot R&D Program Grant Number JPMJMS2013.

JW is funded by a Leverhulme supported grant from The British Academy, Royal Academy of Engineering and Royal Society (APX R1 201093), and a European Research Council (ERC) grant (Neurolive 864420).

Keywords:

datasets, dance performance, electrodermal activity, heart activity

Departments, Centres and Research Units:

Computing

Dates:

DateEvent
6 May 2022Accepted
17 August 2022Published Online

Item ID:

31949

Date Deposited:

22 Aug 2022 11:00

Last Modified:

23 Aug 2022 16:12

Peer Reviewed:

Yes, this version has been peer-reviewed.

URI:

https://research.gold.ac.uk/id/eprint/31949

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