eprintid: 10189969 rev_number: 7 eprint_status: archive userid: 699 dir: disk0/10/18/99/69 datestamp: 2024-04-08 15:06:30 lastmod: 2024-04-08 15:06:30 status_changed: 2024-04-08 15:06:30 type: proceedings_section metadata_visibility: show sword_depositor: 699 creators_name: Kelly, Merlin creators_name: Yang, Lingqian creators_name: Thomas, Alexander creators_name: Donnelly, Pete creators_name: Cho, Youngjun title: WheelSkills: Prototyping Manual Wheelchair Training through Immersive Visual Feedback ispublished: inpress divisions: UCL divisions: B04 divisions: C05 divisions: F48 keywords: Wheelchair skills training (WST), Manual wheelchair users (MWUs), Motion capture, Visual feedback, Skeleton visualization, Posture correction note: This version is the author accepted manuscript. For information on re-use, please refer to the publisher's terms and conditions. abstract: Wheelchair skills training is an essential structured process for wheelchair users to learn how to maneuver effectively, avoiding improper wheelchair use and preventing potential mobility impairments from developing. Online video tutorials have often been used for this training in familiar settings. However, video training lacks real-time feedback, affecting training efficacy in contrast with in-person training. In this paper, we propose WheelSkill, a prototype wheelchair training system combining motion capture and a training interface, providing real-time visual feedback based on the user’s skeletal motion. Eight wheelchair users and a wheelchair expert trainer were consulted in a pilot focus group and interview. Results highlight themes of human-centred design principles for wheelchair users for the final iteration of WheelSkills to assimilate for a high-fidelity wheelchair training feedback system. Finally, we discuss the benefits and limitations of WheelSkills and the adaptions planned for future works. date: 2024-05-01 date_type: published publisher: ACM official_url: https://dl.acm.org/conference/chi oa_status: green full_text_type: other language: eng primo: open primo_central: open_green verified: verified_manual elements_id: 2263330 lyricists_name: Cho, Youngjun lyricists_id: YCHOX41 actors_name: Cho, Youngjun actors_id: YCHOX41 actors_role: owner full_text_status: public pres_type: paper publication: CHI EA '24: Extended Abstracts of the CHI Conference on Human Factors in Computing Systems event_title: CHI EA '24: Extended Abstracts of the CHI Conference on Human Factors in Computing Systems book_title: CHI EA '24: Extended Abstracts of the CHI Conference on Human Factors in Computing Systems citation: Kelly, Merlin; Yang, Lingqian; Thomas, Alexander; Donnelly, Pete; Cho, Youngjun; (2024) WheelSkills: Prototyping Manual Wheelchair Training through Immersive Visual Feedback. In: CHI EA '24: Extended Abstracts of the CHI Conference on Human Factors in Computing Systems. ACM (In press). Green open access document_url: https://discovery.ucl.ac.uk/id/eprint/10189969/1/chiea24-655.pdf