A proof of concept that stroke patients can steer a robotic system at paretic side with myo-electric signals

Abstract

An exoskeleton can be a possible aid for faster recovery for stroke survivors. Controlling such a device safe and accurately is mandatory for applying this rehabilitation aid outside a highly controlled lab environment. MYO electric signals have the potential to provide such steering, as they could command the exoskeleton with the same underlying muscle movement. As stroke survivors have severe motor impairments, the question arises whether the electric signals that steer their muscles at paretic side, can be picked up and classified with sensitive electrodes and machine learning techniques. Six paretic stroke survivors were evaluated in this first pilot study. An of-the shelf wearable myo electric device (MYO armband, Thalmic labs) and matching machine learning and control system was used. Patients were assessed for muscular control and manual motor functions via a modified Lovett test, in a five point Likert scale. Hands and forearms at unaffected and paretic side were used as baseline and inter-subject comparison. Calibration was successful in all subjects at unaffected forearm and in most subjects at paretic forearm. These subjects had moderate to good motor performance. The subjects that were unable to calibrate the device at paretic forearm exhibit inferior motor performance. One subject was able to perform full gesture control at paretic forearm. Most striking is the observation that in one patient, the functionality offered by the MYO armband, outperformed the subject’s muscular control, notably without prior practice.