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

> **NIH VA IK1** · VETERANS HEALTH ADMINISTRATION · 2020 · —

## 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 organization:** VETERANS HEALTH ADMINISTRATION
- **Principal Investigator:** Jorge Candiotti
- **Activity code:** IK1 (R01, R21, SBIR, etc.)
- **Funding institute:** VA
- **Fiscal year:** 2020
- **Award amount:** —
- **Award type:** 1
- **Project period:** 2019-11-01 → 2021-10-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/9833708

## Citation

> US National Institutes of Health, RePORTER application 9833708, OPTIMIZATION AND EVALUATION OF A SELF-LEVELING POWER WHEELCHAIR FOR TIP PREVENTION (1IK1RX003076-01A1). Retrieved via AI Analytics 2026-05-23 from https://api.ai-analytics.org/grant/nih/9833708. Licensed CC0.

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