You are off the beat! Is accelerometer data enough for measuring dance rhythm?

Augusto Dias Pereira Dos Santos, Lie Ming Tang, Lian Loke, Roberto Martinez-Maldonado

Research output: Chapter in Book/Report/Conference proceedingConference PaperResearch

2 Citations (Scopus)

Abstract

Rhythm is the most basic skill for people learning to dance. Beginners need practice but also close coaching and constant feedback. However, in most dance classes teachers often find challenging to provide attention to each student. A possible solution to this problem would be to automate the provision of feedback to students by objectively assessing rhythm from their movement data. But how effective would a fully automated approach be compared to dance experts in evaluating dance performance? We conducted a study aimed at exploring this by ?easuring' dance rhythm from accelerometer data streams and contrasting the algorithm results with expert human judgement.We developed RiMoDe, an algorithm that tracks bodily rhythmic skills, and gathered a dataset that includes 282 independent evaluations made by expert dance teachers on 94 dance exercises performed by 7 dance students. Our findings revealed major gaps between a purely algorithmic approach and how experts evaluate dance rhythm.We identified 6 themes that are important when assessing rhythm. We discuss how these themes should be considered and incorporated into future systems aimed at supporting people learning to dance.

Original languageEnglish
Title of host publicationProceedings of the 5th International Conference on Movement and Computing (MOCO’18)
EditorsMaurizio Mancini
Place of PublicationNew York NY USA
PublisherAssociation for Computing Machinery (ACM)
Number of pages8
ISBN (Electronic)9781450365048
DOIs
Publication statusPublished - 2018
Externally publishedYes
EventInternational Conference on Movement and Computing 2018 - Genoa, Italy
Duration: 28 Jun 201830 Jun 2018
Conference number: 5th
http://moco18.movementcomputing.org/

Conference

ConferenceInternational Conference on Movement and Computing 2018
Abbreviated titleMOCO 2018
CountryItaly
CityGenoa
Period28/06/1830/06/18
Internet address

Keywords

  • Accelerometer
  • Dance education
  • Dance rhythm detection

Cite this

Dias Pereira Dos Santos, A., Tang, L. M., Loke, L., & Martinez-Maldonado, R. (2018). You are off the beat! Is accelerometer data enough for measuring dance rhythm? In M. Mancini (Ed.), Proceedings of the 5th International Conference on Movement and Computing (MOCO’18) [12] Association for Computing Machinery (ACM). https://doi.org/10.1145/3212721.3212724