OPTIMIZATION AND EVALUATION OF A SELF-LEVELING POWER WHEELCHAIR FOR TIP PREVENTION

NIH RePORTER · VA · IK1 · · view on reporter.nih.gov ↗

Abstract

Electric Powered Wheelchairs (EPWs) are key assistive devices for Veterans with Disabilities (VwD), providing mobility and independence. However, existing EPWs are not intended for heavy duty use in outdoor environments and have difficulties navigating steep hills, cross slopes, and other uneven surfaces commonly encountered in outdoor environments. The limitation of the EPW technology in such environments can cause loss of stability and traction, leading to tips and falls. Approximately 100,000 wheelchair-related injuries, mostly associated with falls, are treated in emergency departments every year. Moreover, 65%-80% of these injuries, are caused by tips and falls. Our previous research introduced a Mobility Enhancement Robot (MEBot) EPW to enhance the mobility and safety of VwD when driving in outdoor environments. MEBot provides a self-leveling application that maintains the VwD's center of mass within its footprint to prevent tips and falls in these environments. In preliminary usability studies with active EPW users using MEBot, participants agreed to feel stable with MEBot and stated the importance of the MEBot self-Leveling Application (MEBot-SLA) when driving on steep ramps and curb-ramps. Also, EPW users suggested to (1) self-adjust in real-time, (2) avoid unnecessary seat adjustments, and (3) provide continuous operation of the self-leveling application. Therefore, the objectives of this research were to (Aim 1) perform engineering design upgrades in MEBot-SLA to address EPW user's feedback and (Aim 2) to perform a user evaluation of the optimized MEBot-SLA. Aim 1 of this work proposes to (1) Incorporate electro- hydraulic actuators and force sensors to perform rapid seat adjustment for the user's safety and comfort (2) redesign electronics to operate electro-hydraulic actuators and sensors, (3) implement the MEBot-SLA control algorithm to reduce power consumption and unwanted seat adjustment, and (4) perform static and dynamic stability analyses to evaluate the accuracy and feasibility of the optimized MEBot-SLA. Aim 2 proposes to evaluate MEBot-SLA in comparison with the prior MEBot-SLA and VwD' own EPWs in outdoor driving tasks. We hypothesize that VwD will report (Hypothesis 2a) significantly better driving performance in terms of safety (less change in seat angle) and efficacy (similar or higher number of completed tasks and less seat angle adjustment time), and (Hypothesis 2b) higher satisfaction (higher scores in satisfaction (QUEST) and usability (SUS) assessment tool) when using MEBot-SLA in comparison to the prior MEBot-SLA and their own EPWs on driving tasks that simulate outdoor environments. We will recruit up to 10 active VwD who own EPWs. Participants will be trained in the use of MEBot- SLA to reduce selection bias. After training, each participant will complete five trials using the three devices on three outdoor driving tasks. Quantitative driving metrics will be recorded for each trial and EPW using a data acquisitio...

Key facts

NIH application ID
9833708
Project number
1IK1RX003076-01A1
Recipient
VETERANS HEALTH ADMINISTRATION
Principal Investigator
Jorge Candiotti
Activity code
IK1
Funding institute
VA
Fiscal year
2020
Award amount
Award type
1
Project period
2019-11-01 → 2021-10-31