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

Author

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

Author_Institution

Meas. & Control Eng. Res. Center (MCERC), Idaho State Univ., Pocatello, ID, USA

fYear

2010

fDate

26-29 Sept. 2010

Firstpage

413

Lastpage

418

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 predetermined 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.

Keywords

dexterous manipulators; electromyography; entropy; fuzzy control; motion control; neurophysiology; prosthetics; ANFIS path planning; EMG-entropy data; adaptive neurofuzzy inference system; finger joint angle; fuzzy Mamdani controller; fuzzy control strategy; fuzzy logic controller; grasping motion; hand-finger force; motion control; multifingered prosthetic hand; Electromyography; Entropy; Fingers; Force; Fuzzy logic; Indexes; Prosthetic hand;

fLanguage

English

Publisher

ieee

Conference_Titel

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

Conference_Location

Tokyo

ISSN

2155-1774

Print_ISBN

978-1-4244-7708-1

Type

conf

DOI

10.1109/BIOROB.2010.5627782

Filename

5627782