sEMG based fuzzy control strategy with ANFIS path planning for prosthetic hand

Chandrasekhar Potluri, Parmod Kumar, Madhavi Anugolu, Steve Chiu, Alex Urfer, Marco P. Schoen, D. Subbaram Naidu

Research output: Chapter in Book/Report/Conference proceedingConference contribution

8 Scopus citations

Abstract

This paper presents an intelligent adaptive neurofuzzy inference system (ANFIS) based fuzzy Mamdani controller for a multifingered prosthetic hand. The objective of the controller is to move the finger joint angles along pre-determined paths representing a grasping motion. The initiation of the grasping task is evaluated via EMG-entropy data, measured at the forearm of the prosthetic user. In addition to the motion control, the finger force is regulated with a Fuzzy logic controller. Simulation results indicate good performance of the proposed controller. Results show that the outputs follow the hand/finger force and given reference trajectory closely.

Original languageEnglish (US)
Title of host publication2010 3rd IEEE RAS and EMBS International Conference on Biomedical Robotics and Biomechatronics, BioRob 2010
Pages413-418
Number of pages6
DOIs
StatePublished - 2010
Event2010 3rd IEEE RAS and EMBS International Conference on Biomedical Robotics and Biomechatronics, BioRob 2010 - Tokyo, Japan
Duration: Sep 26 2010Sep 29 2010

Publication series

Name2010 3rd IEEE RAS and EMBS International Conference on Biomedical Robotics and Biomechatronics, BioRob 2010

Other

Other2010 3rd IEEE RAS and EMBS International Conference on Biomedical Robotics and Biomechatronics, BioRob 2010
CountryJapan
CityTokyo
Period9/26/109/29/10

Fingerprint Dive into the research topics of 'sEMG based fuzzy control strategy with ANFIS path planning for prosthetic hand'. Together they form a unique fingerprint.

Cite this