Control Mechanisms and Strategies of Upper-Limb Exoskeleton Rehabilitation Robots

Abstract

Diseases such as stroke are a leading cause of long-term chronic disability around the world and affect people in their most productive years, frequently posing disabling motor impairments that limit dependency and a person’s quality of life. Traditional rehabilitation processes have made significant advances, yet continue to be limited due to physical intensity, consistency and scalability. Exoskeleton rehabilitation robots have emerged as a possible solution to address these issues by providing repetitive, controlled, and adaptive treatment. This dissertation reviewed some of the recent advances made in the control mechanisms to develop upper-limb exoskeleton rehabilitation robots. The focus was on passive and active control methods. Passive control methods provide safety and mechanical consistency, particularly beneficial to patients in the early phase of recovery, while active control methods, such as those using electromyography (EMG) and electroencephalography (EEG), allow patient participation in the rehabilitation process by decoding the patient’s motor intent. Those findings demonstrated that neither passive nor active approaches are mutually exclusive, but rather exist on a spectrum of control methods, and a combination of both may offer the best opportunities for rehabilitation care.