A Longitudinal Analysis of the Effects of Power Wheelchair Usage and User Maintenance on Power Wheelchair Failures

Abstract

Introduction/Background Around 80 million people globally use wheelchairs for mobility. Within 6 months of usage, 45- 88% of wheelchairs will break down. Powerchair users experience adverse consequences when their powerchairs fail. To prevent this, data-based tools need to be developed to predict when preventative maintenance should occur to avoid powerchair failures. Objectives The study objective is as follows: 1. Determine the correlation between power wheelchair usage with power wheelchair failures. Methods A 3-month longitudinal study with 2 study visits, one at the beginning and end. Recruited a convenience sample of 12 participants whose primary mobility method was a power wheelchair and were over the age of 18. Study visits took place at the Ohio State University’s Center for Automotive Research. At the first study visit, a sensor was installed on the participant’s power wheelchair to collect usage data between the first and second visit. Surveys were taken at both study visits to collect demographic, maintenance, failure, and wheelchair condition data. At the second study visit, usage data collected by the sensor was collected and downloaded to laboratory computers. Descriptive statistics and correlation were used in data analysis to evaluate the association between road shocks and failure frequency. Results/Current Status Initial demographic information was collected at the first study visit between October-December 2024. Seven males and Four females participated in the study. The average age of the participants was 35.36±16.29years. Second study visits were completed through January-March 2025. Strong and moderate positive correlations were found between shocks and failures as well as between these two measures, maintenance training and self-reported distance traveled per day (p<.05). Discussion and Conclusions Powerchair users’ demographics and usage data can be used to predict whether they are at high or low risk for powerchair failures. Clinicians can use this data to schedule follow-up, preventative maintenance and prevent future failures. Future studies must investigate demographics and usage more in-depth to conclude exact predictors.Rehabilitation Engineering Design LaboratoryA one-year embargo was granted for this item.Academic Major: Health Sciences Progra