# Development of a Wheelchair Maintenance Alert Application for Elderly Wheelchair Users

> **NIH NIH R03** · UNIVERSITY OF PITTSBURGH AT PITTSBURGH · 2020 · $75,877

## Abstract

Project Summary
Elderly wheelchair users experience wheelchair breakdowns every 2-3 months in low- and middle-income
countries (LMICs) and rural areas of high-income countries. One in three breakdowns leads to adverse physical,
social, psychosocial and economic consequences to wheelchair users which increases the public health and
personal burden. Preventative wheelchair maintenance has been found to reduce the frequency of wheelchair
breakdowns by ten-fold, but compliance with maintenance recommendations is extremely low because they are
generic and not reflective of how and where the wheelchair is being used. To address this issue, we are
developing a low-cost, scalable maintenance application that leverages artificial intelligence tools to provide
maintenance recommendations tailored to how a wheelchair is used. The availability of low-cost technology and
widespread use of smartphones by the elderly and people with disabilities in LMICs has led us to develop a
smartphone application called WheelTrak that measures wheelchair wear as a function of usage in community.
Based on the wear factors, the application produces a Wheelchair Wear Index (WWI) that is representative of
wear of critical wheelchair parts that are prone to breakdown. Once a WWI threshold is reached, maintenance
is required, and the application notifies the user and/or caregiver who can conduct maintenance to avoid
breakdowns and related health consequences. We will conduct a data collection study in collaboration with our
wheelchair industry partner – UCP Wheels in El Salvador – and characterize the WWI for the elderly by tracking
wear factors which include user’s travel distance, ground shocks and surface vibrations using WheelTrak and a
wheel sensor. Based on the trained WWI algorithm, a preventative maintenance schedule will be developed for
older adults that can be employed through WheelTrak for maintenance reminders. Semi-structured interviews
will be conducted to evaluate the usability of the application and gather barriers to maintenance. User feedback
will assist us in improving WheelTrak for greater user satisfaction and compliance with maintenance, and
addressing any personal or logistical challenges that elderly users and their caregivers or family members may
face with conducting maintenance activities in LMICs. Findings from the proposed studies in this application will
assist us in planning future studies to investigate the WWI-enabled WheelTrak tool as an intervention to prevent
or reduce breakdowns and health consequences with the elderly in LMICs.

## Key facts

- **NIH application ID:** 10095020
- **Project number:** 1R03AG069836-01
- **Recipient organization:** UNIVERSITY OF PITTSBURGH AT PITTSBURGH
- **Principal Investigator:** Anand Mhatre
- **Activity code:** R03 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2020
- **Award amount:** $75,877
- **Award type:** 1
- **Project period:** 2020-09-30 → 2022-08-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10095020

## Citation

> US National Institutes of Health, RePORTER application 10095020, Development of a Wheelchair Maintenance Alert Application for Elderly Wheelchair Users (1R03AG069836-01). Retrieved via AI Analytics 2026-05-23 from https://api.ai-analytics.org/grant/nih/10095020. Licensed CC0.

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