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Published on: April 10, 2011
Impact of a mobile application and assistive chopsticks on traditional chopstick manipulation: an exploratory
Yuki Choji1, Nanami Hirokawa2, Norihito China1
1Occupational Therapy Course, Department of Rehabilitation, Faculty of Allied Health Science, Niigata University of Rehabilitation, Murakami City, Niigata Prefecture, Japan.
Objective:
This study examined (1) the feasibility and utility of a vision-based mobile application for assessing chopstick manipulation ability and (2) the preliminary effectiveness of newly developed assistive chopsticks designed to promote the traditional holding form among children.
Methods:
An exploratory consecutive controlled case series was conducted with 15 children aged 6-12 years from two elementary schools in Japan. Each participant completed a baseline phase using standard chopsticks, followed by an intervention phase using co-developed assistive chopsticks. Daily performance was recorded through the Kuchibashi App, which used MediaPipe for hand posture estimation and YOLOv8 for chopstick detection. App-based scores were analysed using the Visual Aid Implying an Objective Rule (VAIOR). Qualitative data included questionnaires from children and parents and visual assessments of grip by two trained raters.
Results:
Fourteen participants completed the study. VAIOR analysis showed that six children (42.86%) had higher app-based scores during the intervention phase, whereas qualitative assessments indicated that 13 of 14 children (92.86%) improved. Eight children (57.14%) achieved complete correction to the "Four Finger" grip, five (35.71%) showed partial improvement, and one (7.14%) showed no change. Most children (85.71%) wished to continue using the assistive chopsticks, and parents reported high satisfaction with usability and motivation.
Conclusions:
Integrating a vision-based app with ergonomically designed assistive chopsticks proved feasible, usable, and culturally meaningful. Although qualitative improvements were seen in nearly all participants, quantitative metrics detected fewer changes, indicating the need to refine analytic sensitivity. This combined approach shows promise for technology-assisted rehabilitation.
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