Jorge L Candiotti1, Deepan C Kamaraj1, Brandon Daveler1, Cheng-Shiu Chung1, Garrett G Grindle1, Rosemarie Cooper1, Rory A Cooper2. 1. Center of Excellence in Wheelchairs and Associated Rehabilitation Engineering, Veterans Affairs Pittsburgh Healthcare System and Human Engineering Research Laboratories, Pittsburgh, PA; Department of Rehabilitation Sciences and Technology, School of Health and Rehabilitation Sciences, University of Pittsburgh, Pittsburgh, PA. 2. Center of Excellence in Wheelchairs and Associated Rehabilitation Engineering, Veterans Affairs Pittsburgh Healthcare System and Human Engineering Research Laboratories, Pittsburgh, PA; Department of Rehabilitation Sciences and Technology, School of Health and Rehabilitation Sciences, University of Pittsburgh, Pittsburgh, PA. Electronic address: rcooper@pitt.edu.
Abstract
OBJECTIVE: To compare the Mobility Enhancement roBotic (MEBot) wheelchair's capabilities with commercial electric-powered wheelchairs (EPWs) by performing a systematic usability evaluation. DESIGN: Usability in effectiveness, efficacy, and satisfaction was evaluated using quantitative measures. A semistructured interview was employed to gather feedback about the users' interaction with MEBot. SETTING: Laboratory testing of EPW driving performance with 2 devices in a controlled setting simulating common EPW driving tasks. PARTICIPANTS: A convenience sample of expert EPW users (N=12; 9 men, 3 women) with an average age of 54.7±10.9 years and 16.3± 8.1 years of EPW driving experience. INTERVENTIONS: Not applicable. MAIN OUTCOME MEASURES: Powered mobility clinical driving assessment (PMCDA), Satisfaction Questionnaire, National Aeronautics and Space Administration's Task Load Index. RESULTS: Participants were able to perform significantly higher number of tasks (P=.004), with significantly higher scores in both the adequacy-efficacy (P=.005) and the safety (P=.005) domains of the PMCDA while using MEBot over curbs and cross-slopes. However, participants reported significantly higher mental demand (P=.005) while using MEBot to navigate curbs and cross-slopes due to MEBot's complexity to perform its mobility applications which increased user's cognitive demands. CONCLUSIONS: Overall, this usability evaluation demonstrated that MEBot is a promising EPW device to use indoors and outdoors with architectural barriers such as curbs and cross-slopes. Current design limitations were highlighted with recommendations for further improvement.
OBJECTIVE: To compare the Mobility Enhancement roBotic (MEBot) wheelchair's capabilities with commercial electric-powered wheelchairs (EPWs) by performing a systematic usability evaluation. DESIGN: Usability in effectiveness, efficacy, and satisfaction was evaluated using quantitative measures. A semistructured interview was employed to gather feedback about the users' interaction with MEBot. SETTING: Laboratory testing of EPW driving performance with 2 devices in a controlled setting simulating common EPW driving tasks. PARTICIPANTS: A convenience sample of expert EPW users (N=12; 9 men, 3 women) with an average age of 54.7±10.9 years and 16.3± 8.1 years of EPW driving experience. INTERVENTIONS: Not applicable. MAIN OUTCOME MEASURES: Powered mobility clinical driving assessment (PMCDA), Satisfaction Questionnaire, National Aeronautics and Space Administration's Task Load Index. RESULTS: Participants were able to perform significantly higher number of tasks (P=.004), with significantly higher scores in both the adequacy-efficacy (P=.005) and the safety (P=.005) domains of the PMCDA while using MEBot over curbs and cross-slopes. However, participants reported significantly higher mental demand (P=.005) while using MEBot to navigate curbs and cross-slopes due to MEBot's complexity to perform its mobility applications which increased user's cognitive demands. CONCLUSIONS: Overall, this usability evaluation demonstrated that MEBot is a promising EPW device to use indoors and outdoors with architectural barriers such as curbs and cross-slopes. Current design limitations were highlighted with recommendations for further improvement.
Authors: Sivashankar Sivakanthan; Jorge L Candiotti; Andrea S Sundaram; Jonathan A Duvall; James Joseph Gunnery Sergeant; Rosemarie Cooper; Shantanu Satpute; Rose L Turner; Rory A Cooper Journal: Neurosci Lett Date: 2022-01-29 Impact factor: 3.046
Authors: Sivashankar Sivakanthan; Jeremy Castagno; Jorge L Candiotti; Jie Zhou; Satish Andrea Sundaram; Ella M Atkins; Rory A Cooper Journal: Sensors (Basel) Date: 2021-11-24 Impact factor: 3.576