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Article Dans Une Revue ACM Computing Surveys Année : 2022

Human Movement Datasets: An Interdisciplinary Scoping Review

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Temitayo Olugbade
  • Fonction : Auteur
Giulia Barbareschi
  • Fonction : Auteur
Vincenzo D’amato
  • Fonction : Auteur
Luca Oneto
  • Fonction : Auteur
Antonio Camurri
  • Fonction : Auteur
Catherine Holloway
  • Fonction : Auteur
Mårten Björkman
  • Fonction : Auteur
Peter Keller
  • Fonction : Auteur
Martin Clayton
  • Fonction : Auteur
Amanda Williams
  • Fonction : Auteur
Nicolas Gold
  • Fonction : Auteur
Cristina Becchio
  • Fonction : Auteur
Benoit G. Bardy
Nadia Bianchi-Berthouze
  • Fonction : Auteur

Résumé

Movement dataset reviews exist but are limited in coverage, both in terms of size and research discipline. While topic-specific reviews clearly have their merit, it is critical to have a comprehensive overview based on a systematic survey across disciplines. This enables higher visibility of datasets available to the research communities and can foster interdisciplinary collaborations. We present a catalogue of 704 open datasets described by 10 variables that can be valuable to researchers searching for secondary data: name and reference, creation purpose, data type, annotations, source, population groups, ordinal size of people captured simultaneously, URL, motion capture sensor, and funders. The catalogue is available in the supplementary materials. We provide an analysis of the datasets and further review them under the themes of human diversity, ecological validity, and data recorded. The resulting 12-dimension framework can guide researchers in planning the creation of open movement datasets. This work has been the interdisciplinary effort of researchers across affective computing, clinical psychology, disability innovation, ethnomusicology, human-computer interaction, machine learning, music cognition, music computing, and movement neuroscience.
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Dates et versions

hal-03769783 , version 1 (05-09-2022)

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Temitayo Olugbade, Marta Bieńkiewicz, Giulia Barbareschi, Vincenzo D’amato, Luca Oneto, et al.. Human Movement Datasets: An Interdisciplinary Scoping Review. ACM Computing Surveys, 2022, ⟨10.1145/3534970⟩. ⟨hal-03769783⟩
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