Hands-Free Control Of An Assistive Robotic Arm For High-Level Paralysis

Abstract

Recent advancements in assistive robotic arms have enabled tetraplegics to perform activities of daily living more independently. Because these systems typically require hand use, they are not a ready option for many high-level tetraplegics. Alternative means that might be used by such individuals could involve signals that arise from the head and neck. Therefore, the goal of the study was to evaluate the utility of several non-invasive methods to control a robotic arm during reaching to multiple targets in 3D space. We tested ten able-bodied human subjects using five hands-free modalities (head position, head velocity, facial electromyography, tongue and voice) to control the robot arm. For comparison, subjects also used joystick position and joystick velocity to control reaching movements of the robotic arm. A one-way repeated measures ANOVA was carried out on key performance indicators such as movement time, path efficiency, throughput, and perceived workload. The hands-free control modalities of head position, facial EMG, and tongue had movement times that were not significantly different than that of the benchmark method of hand control of a joystick. Furthermore, no significant differences were revealed in perceived workload across control modalities. These results indicate, therefore, that various non-invasive, hands free methods could used effectively by high-level tetraplegics to operate assistive robotic arms