Coevolution of Myoelectric Hand Control under the Tactile Interaction among Fingers and Objects

Abstract

The usability of a prosthetic hand differs significantly from that of a real hand. Moreover, the complexity of manipulation increases as the number of degrees of freedom to be controlled increases, making manipulation with biological signals extremely difficult. To overcome this problem, users need to select a grasping posture that is adaptive to the object and a stable grasping method that prevents the object from falling. In previous studies, these have been left to the operating skills of the user, which is extremely difficult to achieve. In this study, we demonstrate how stable and adaptive grasping can be achieved according to the object regardless of the user’s operation technique. The required grasping technique is achieved by determining the correlation between the motor output and each sensor through the interaction between the prosthetic hand and the surrounding stimuli, such as myoelectricity, sense of touch, and grasping objects. The agents of the 16-DOF robot hand were trained with the myoelectric signals of six participants, including one child with a congenital forearm deficiency. Consequently, each agent could open and close the hand in response to the myoelectric stimuli and could accomplish the object pickup task. For the tasks, the agents successfully identified grasping patterns suitable for practical and stable positioning of the objects. In addition, the agents were able to pick up the object in a similar posture regardless of the participant, suggesting that the hand was optimized by evolutionary computation to a posture that prevents the object from being dropped.

Enhanced Motor Imagery Decoding by Calibration Model-Assisted With Tactile ERD

“…Imagined hand movement is always accompanied by tactile sensation imagery [66], and the motor cortex and sensor cortex communicate with each other during motor imagery [67]. It has been proved that real afferent stimulation can enhance excitability in the contralateral sensorimotor cortex [68], [69], [70], [71], [72], [73]. The current results further validate this conclusion.…”

Advanced Technologies and Applications of Robotic Soft Grippers

“…By alloy materials with better actuating effects [186] and more reasonable driving methods, [187] soft grippers are expected to achieve micrometer-scale targeted medical effects. 2) Structural flexibility and stability: In assistive applications, such as soft grippers used in wearable technology, [188,189] the structural flexibility and stability of the grippers are of great importance. However, wearable systems are more practical application oriented system designs.…”

“…In addition, considering the directional operation and micro‐nanoscale properties of targeted therapy, [ 185 ] the application of soft grippers in the micro–nano medical field also requires further breakthroughs in operation accuracy and response speed. By alloy materials with better actuating effects [ 186 ] and more reasonable driving methods, [ 187 ] soft grippers are expected to achieve micrometer‐scale targeted medical effects. 2)Structural flexibility and stability: In assistive applications, such as soft grippers used in wearable technology, [ 188,189 ] the structural flexibility and stability of the grippers are of great importance. However, wearable systems are more practical application oriented system designs.…”

An all-position type control strategy of the haptic interactive virtual training system based on cable-driven

“…As the requirements of deep space operations become more complex and diverse, astronauts need a training system with better tactile sensation. Astronaut's tactile sensation is positively correlated with the force control accuracy and motion control accuracy of the system, 6 so a higher accuracy training system is needed. At present, the research on HIVMTS is in its infancy.…”