Quantifying Electric-Powered Wheelchair (EPW) Driving Performance Using Jerk Metrics: A Pilot Study
Serena S. W. Ng, Chung Hang Tang, Stephen C. H. Tse, Alfred C. H. Yip, Winnie W. T. LamBackground
Current assessments of electric-powered wheelchair (EPW) driving, such as the Wheelchair Skills Test (WST), rely on observational scoring and lack validation in outdoor environments. Occupational Therapists require standardized, quantitative measures to evaluate driving performance and monitor training progress.
Objective
This pilot study examined: (1) the influence of cognitive, physical, and sensory components on EPW driving, (2) the validity of sensor-derived jerk metrics relative to WST scores, and (3) the feasibility of these metrics as outcome measures in an EPW training program.
Methods
Seven adults with mobility impairments (six novice wheelchair drivers; mean age 59.4 years) completed baseline assessments. Sensors mounted on the EPW and joystick captured jerk during seven WST tasks with Apps displayed. Three metrics—median jerk, time above threshold, and the Jerk Index—were computed and correlated with WST scores. Pre/post comparisons were conducted following four training sessions.
Results
Sensor-derived metrics demonstrated strong inverse correlations with WST scores (ρ = −0.750 to −0.857,
Conclusions
Jerk-based metrics, particularly the Jerk Index, show promise as objective measures of EPW driving performance. They demonstrated concurrent validity with WST scores and applicability in outdoor contexts. Larger studies are warranted to confirm reliability, establish clinical thresholds, and support integration into rehabilitation practice.