Movement Quality Visualization for Wheelchair Dance

Author:

Xie Yurui1ORCID,Barbareschi Giulia1ORCID,Nabila Ayesha1ORCID,Kunze Kai1ORCID,Inakage Masa1ORCID

Affiliation:

1. Keio University Graduate School of Media Design, Keio University, Hiyoshi Kohoku-ku, Yokohama-city Kanagawa, Japan, Yokohama, Japan

Abstract

Wheelchair dance is an important form of disability art that is still subject to significant levels of ableism and art exclusion. Wheelchair dancers face challenges finding teachers and choreographers who can accommodate their needs, documenting and sharing choreographies that suit their body shapes and their assistive technologies. In turn, this hinders their ability to share creative expressions. Accessible resources and communication tools could help address these challenges. The goal of this research is the development of a visualization system grounded on Laban Movement Analysis (LMA) that notates movement quality while opening new horizons on perceptions of disabled bodies and the artistic legitimacy of wheelchair dance. The system uses video to identify the body landmarks of the dancer and wheelchair and extracts key features to create visualizations of expressive qualities from LMA basic effort. The current evaluation includes a pilot study with the general public and an online questionnaire targeting professionals to gain feedback supporting practical implementation and real-world deployment. Results from the general public evaluation showed that the visualization was effective in conveying basic effort movement qualities even to a novice audience. Expert consulted via questionnaire stated that the tool could be employed for reflective evaluation, as well as performance augmentation. The LMA visualization tool can support the artistic legitimization of wheelchair dancing through education, communication, performance, and documentation.

Publisher

Association for Computing Machinery (ACM)

Subject

Computer Graphics and Computer-Aided Design,Computer Science Applications

Reference25 articles.

1. Sarah Fdili Alaoui , Jules Franoise , Thecla Schiphorst , Karen Studd , and Frederic Bevilacqua . 2017 . Seeing, Sensing and Recognizing Laban Movement Qualities . In Proceedings of the 2017 CHI Conference on Human Factors in Computing Systems. ACM, Denver Colorado USA, 4009--4020 . https://doi.org/10.1145/3025453.3025530 10.1145/3025453.3025530 Sarah Fdili Alaoui, Jules Franoise, Thecla Schiphorst, Karen Studd, and Frederic Bevilacqua. 2017. Seeing, Sensing and Recognizing Laban Movement Qualities. In Proceedings of the 2017 CHI Conference on Human Factors in Computing Systems. ACM, Denver Colorado USA, 4009--4020. https://doi.org/10.1145/3025453.3025530

2. Three-Dimensional Visualization of Movement Qualities in Contemporary Dance

3. Folk Dance Evaluation Using Laban Movement Analysis

4. “When They See a Wheelchair, They’ve Not Even Seen Me”—Factors Shaping the Experience of Disability Stigma and Discrimination in Kenya

5. Giulia Barbareschi and Masa Inakage. 2022. Assistive or Artistic Technologies? Exploring the Connections between Art Disability and Wheelchair Use Assistive or Artistic Technologies? Athens. Giulia Barbareschi and Masa Inakage. 2022. Assistive or Artistic Technologies? Exploring the Connections between Art Disability and Wheelchair Use Assistive or Artistic Technologies? Athens.

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