Upper extremity pain among manual wheelchair users induces functional decline and reduces quality of life. Research has identified chronic overuse due to wheelchair propulsion as one of the factors associated with upper limb injuries. Lack of a feasible tool to track wheelchair propulsion in the community precludes testing validity of wheelchair propulsion performed in the laboratory. Recent studies have shown that wheelchair propulsion can be tracked through machine learning methods and wearable accelerometers. Better results were found in subject-specific machine learning method. To further develop this technique, we conducted a pilot study examining the feasibility of measuring wheelchair propulsion patterns.