A Hands-Free Interface for Controlling Virtual Electric-Powered Wheelchairs

Electric-powered wheelchair (EPW) users with different impairment types must learn to operate the wheelchair with their residual body motions. The EPW interfaces are often customized to fit the needs of the users. In this study, we present a hands-free interface (HFI) that can be customized to the varying needs of the EPW users. The HFI utilizes the signals generated by the user’s voluntary shoulder and elbow movements and translates them into EPW control scheme. To test the performance of the HFI, the output of upper-limb movements (shoulder and elbows) was tested on 6 participants, and is compared with an output of precision position tracking (PPT) optical system for validation. Correlations between the HFI signal counts and PPT optical system during different upper-limb movement tasks ranged from r = 0.86 to 0.94. We also tested the HFI performance in driving the EPW in a virtual reality environment on a spinal-cord injured (SCI) patient. The results show that HFI is able to adapt and translate the residual mobility of SCI patient into efficient control commands within a week’s training. The results are encouraging and are discussed towards the development of efficient HFIs.