Abstract
AbstractAssist-as-needed control with a soft robotic hand glove for active rehabilitation is studied in this work. There are two resources of the grasping force, the robotic glove and the subject. Compared with traditional passive rehabilitation where the grasping force is merely provided by a robotic hand rehabilitation device (such as hand exoskeleton, robotic glove), assist-as-needed control accounts for the user contribute to performing grasping tasks collaboratively. In this control method, the human muscle strength for grasping is estimated through the myoelectrical signals of the human forearm collected by the MYO armband. A neural network is used for the recognition of human-object contact estimation. The assist-as-needed control is finally implemented to assist humans in grasping tasks. Experiment results on a soft robotic glove show the effectiveness of the proposed assistive control method.
Funder
Hong Kong Polytechnic University
Publisher
Springer Science and Business Media LLC
Subject
Computational Mathematics,Engineering (miscellaneous),Information Systems,Artificial Intelligence
Reference42 articles.
1. Akira F, Shintaro E, Kosuke N et al (2019) A myoelectric prosthetic hand with muscle synergy-based motion determination and impedance model-based biomimetic control. Sci Robot. https://doi.org/10.1126/scirobotics.aaw6339
2. Andrei N, Strahinja D, Silvia M et al (2014) Closed-loop control of grasping with a myoelectric hand prosthesis: which are the relevant feedback variables for force control? IEEE Trans Neural Syst Rehabil Eng 22(5):1041–1052
3. Anirban C, Sunder NS, Kumar MY et al (2018) Hand-exoskeleton assisted progressive neurorehabilitation using impedance adaptation based challenge level adjustment method. IEEE Trans Haptics 12(2):128–140
4. Asl H J, Narikiyo T, Kawanishi M (2017) An assist-as-needed control scheme for robot-assisted rehabilitation. In: American control conference (ACC), pp 198–203
5. Asl HJ, Yamashita M, Narikiyo T et al (2020) Field-based assist-as-needed control schemes for rehabilitation robots. IEEE/ASME Trans Mechatron 25(4):2100–2111