Exploring Digital Embodiment in Wheelchair Dance with Generative AI

Abstract

In the era of blurring boundaries between technology and humans, the idea of posthumanism in the arts offers opportunities to overcome human natural limitations through the integration of artificial agents that can enhance performance and creativity. Within the field of dance, a variety of technologies have been utilized to amplify aspects such as training, artistic creation, live performance, and dance archives. Nonetheless, a largely unexplored territory exists—the application of emerging technology in the context of disability dance. This paper presents an ongoing project focused on gesture-controlled AI generation for wheelchair dance as a way to explore the complex relationship between dancers and their assistive devices. The system uniquely captures the dancer and wheelchair through body segmentation, then recombines them into a unified body. Subsequently, it extracts movement features based on the previously established framework for visualizing movement quality in wheelchair dance, generating images that enable a deeper understanding of the dance’s expressive qualities. This innovative approach enhances the creative potential of wheelchair dance, empowering dancers to craft personalized visual narratives.

Cite this work

No public copy is stored for this record, so only the metadata is cited.

Stored only when both papers are in the corpus — 6 citations exist upstream.

Papers that cite the same references — the relational fallback while embeddings are still backfilling.