Graphical simulation of artificial hand motion with fuzzy EMG pattern recognition

Author

Zahedi, E. ; Farahani, H.

Author_Institution

Dept. of Electr. Eng., Sharif Univ. of Technol., Tehran, Iran

fYear

1995

fDate

15-18 Feb 1995

Firstpage

15766

Lastpage

16132

Abstract

A graphical simulator in which a prosthesis is controlled by means of electromyogram (EMG) processing is described. The integral of the absolute value (IAV) of the biceps and triceps EMGs are used as features. A fuzzy k-means scheme is used to classify the motion before actuating a 3-degrees-of-freedom arm graphically on a computer monitor. The main advantages of such an approach over a classical training are: (i) the possibility of training amputees before using a real prosthesis, (ii) its cost-effectiveness by manpower time-saving, (iii) greater availability of the training set, and (iv) self-paced learning

Keywords

artificial limbs; biocontrol; computer graphics; control system analysis computing; digital simulation; electromyography; fuzzy set theory; medical signal processing; pattern classification; training; 3-DOF arm actuation; amputee training; artificial hand motion; biceps; computer graphics; cost-effectiveness; electromyogram processing; fuzzy EMG pattern recognition; fuzzy k-means scheme; graphical simulator; integral of absolute value; manpower time-saving; motion classification; prosthetic control; self-paced learning; training set availability; triceps; Automatic control; Computer graphics; Electromyography; Fuzzy logic; Heuristic algorithms; Microcomputers; Muscles; Pattern recognition; Prosthetics; USA Councils;

fLanguage

English

Publisher

ieee

Conference_Titel

Engineering in Medicine and Biology Society, 1995 and 14th Conference of the Biomedical Engineering Society of India. An International Meeting, Proceedings of the First Regional Conference., IEEE

Conference_Location

New Delhi

Print_ISBN

0-7803-2711-X

Type

conf

DOI

10.1109/RCEMBS.1995.532968

Filename

532968