Effective Multi-Mode Grasping Assistance Control of a Soft Hand Exoskeleton Using Force Myography - Islam, Muhammad Raza Ul; Bai, Shaoping (Frontiers in Robotics and AI, 2020)
Human intention detection is fundamental to control robotic devices in order to assist humans according to their needs. This paper presents a novel approach to detect hand motion intention, i.e. rest, open, close and grasp, and grasping force estimation using forcemyography (FMG). The output is further used to control a soft hand exoskeleton called SEM Glove. In this method, two sensor bands constructed using force sensing resistor (FSR) sensors are utilized to detect hand motion states and muscle activities. Upon placing both bands on an arm, the sensors are able to measure normal forces caused by muscle contraction/relaxation. Afterwards, the sensor data is processed and hand motions are identified through threshold based classification method. The developed method has been tested on human subjects for object grasping tasks. The results show that the developed method is able to detect hand motions accurately and to provide assistance w.r.t to the task requirement.