Sensor Fusion Used in Applications for Hand Rehabilitation: A Systematic Review

Abstract

Medical conditions and accidents might cause immobility in certain parts of the body. In order to assist people in the rehabilitation process, sensors obtaining bio-signals from the body have been merged to create assistive technology. This systematic review is focused on presenting the state-of-the-art regarding sensor fusion used in the applications for hand rehabilitation. Articles were searched in four databases: IEEE Xplore, Web of Science, ACM Digital Library, and PubMed. Moreover, PRISMA and QualSyst protocols were employed to filter the articles and assess their qualities. As a result, of the 102 articles initially retrieved, only 29 articles performed sensor fusion for hand rehabilitation. Specifically, three application areas were found: sensor fusion for detecting hand movements, sensor fusion for exoskeleton control applications, and sensor fusion on serious games for hand rehabilitation. The studies included in this review measured two key aspects for rehabilitation purposes: user’s limb strength and user’s limb position. Regarding the sensors employed in the fusion, the most widely used sensor was electromyography sensor followed by the inertial sensors. Furthermore, the studies included in this review have focused on the following hand movements used for rehabilitation: flexion, extension, pronation, supination, power grasp, radial/urnal, open hand, single-finger contractions, multi-finger contractions, pinch grip, hand at rest, and hand grip.