A bionic soft robotic glove mimicking finger actions based on sEMG recognition

Abstract

Abstract Compared with rigid robots, soft robotics is more suitable to develop anthropomorphic digits that mimics the biological structures and dexterous motions of human finger. This study proposed a surface electromyogram (sEMG) sensors-based soft robotic glove system which was able to recognize the finger activities and execute the same operation via the bionic glove. Finger activities can be recognized by using electrodes sensors to monitor the electric potential variations on specific surface of the forearm muscle regions. A hybrid robotic digit was designed that utilizes pneumatic bellow actuators to satisfy the anatomical range of the finger motion in order to mimic finger action according to sEMG information. The moving trajectory of digit tip and the range motion of each joint of the robotic digit were measured in experiments under the pressure from 0kPa to 70kPa. The bionic soft robotic glove successfully demonstrated the finger action recognition and robotic digits controlling for a variety of manipulation tasks. The feasible results provided a novel technique for controlling the soft robotic glove through sEMG signals holistically and practically, and also give inspiration and guidance for multiple fingers remote operational applications.