Abstract
This paper presents a control method for prosthetic hand's grip force. Firstly, the correlated characters of the SEMG signal are calculated and input into the neural network in order to extract the estimation of muscle strength. Secondly, the estimation of muscle strength and the real-time prosthetic hand’s grip force are input into the designed fuzzy logic controller in order to adjust the motor speed, and indirectly control the grip force. This method could greatly reduce the individual difference of SEMG signal, make it can be used by Non-specific patient, and the experiment demonstrates that the control of prosthetic hand’s grip force is effective.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
