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