of tbe

ELECTROMYOGRAPHY (EMG) SIGNAL ACQUISITION AND CLASSIFICATION

By

SARFRAZ HUSSAIN 10524

Final Report submitted in partial fulfillment of tbe requirements for tbe

Bachelor of Engineering (Hons) (Electrical

&

Electronic Engineering)

JANUARY 2011

Universiti Teknologi PETRONAS Bandar Seri Iskandar

31750Tronoh Perak Darul Ridzuan.

© Copyright 20 I 0 by Sarfraz Hussain

CERTIFICATION OF APPROVAL

ELECTROMYOGRAPHY SIGNAL ACUISITION AND CLASSIFICATION

by

Sarfraz Hussain

A project dissertation submitted to the Electrical & Electronics Engineering Programme

Universiti Teknologi PETRONAS in partial fulfilment of the requirement for the

Bachelor of Engineering (Hons) (Electrical & Electronics Engineering)

Dr. Irraivan Elamvazuthi Project supervisor

UNIVERSITI TEKNOLOGI PETRONAS TRONOH, PERAK

JANUARY 2011

II

CERTIFICATION OF ORIGINALITY

This project is to certify that I am responsible for the work submitted in this project, that the original work is my own except as specified in the reference and acknowledgments, and that the original work contained herein have not been undertaken or done by un- specified sources or persons.

Ill

ABSTRACT

Electromyography (EMG) is obtained by measuring the electrical signal associated with the activation of the muscle. EMG can be used for a lot of studies (e.g., clinical, biomedical, basic physiological and biomechanical studies); consequently, in this project the EMG is used as a diagnostic tool for the rehabilitation purpose. The methodology and instrumentation of Electromyography are presented and the main objectives of this project are to acquire signals and perform classification. In this research, Many signals need to be acquired from EMG system or any Data base source which are experimented on subjects having different age and gender, in order to carry out detailed analysis for the purpose of performing classification therefore, the signals are analyzed using MA TLAB and thereatler, feature recognition method is applied by implementing fuzzy logic technique to classify the signals in terms of age groups. The final form of the project consists of a successful finding of signal acquisition to perform classification of EMG signals in tenns of age groups using Fuzzy logic.

IV

ABSTRACT.

LISTOFFIGURES.

LIST OFT ABLES .

TABLE OF CONTENTS

CHAPTER I: INTRODUCTION

I.

I

Background of Study •

1.2

Surface Electromyography 1.3 Surface Electrodes

1.4

Problem Statement

1.5

Objectives

1.6

Scope of Study

CHAPTER2: LITERATURE REVIEW ANDTHEORY.

2.1

Basic concept of Electromyography 2.1.1 Motor units and force

.

2. 1.2 Motor unit Action Potential 2.1.3 Motor unit Action Potential train

2.2

Description ofEMG signal

2.3

Basic EMG circuit 2.3.1 The EMG Signal

2.4

Concept of frequency spectrum

2.5

Basic Concept of filtering

2.6

Recent research and development ofEMG 2.6.1 Analysis on the SEMG signal

2.6.2 Existing product using SEMG

2.6.3 Similar technique used prosthesis control.

2.7

Current methods for rehabilitation

v

.IV

.VII .VIII

. I . I

. 3

.4 .4 . 6 . 6

. 7

• 7 . 7 . 8 . I 0 . 12 . 12 . 15 . 17

.17

. 18 . 18 . 19

• 20

.21

CHAPTER3:

CHAPTER4:

CHAPTERS:

REFERENCES APPENDIX A

METHODOLOGY

.

3.1 Project Flow Chart 3.2 Topic Selection

3.3 Literature Review on sEMG Signal Acquisition 3.4 Analysis on the Project Requirement .

3.4.1 Tools required 3.5 Project Design

3.5.1 Surface EMG signal measurement 3.5.2 Processing Unit .

3.5.3 Software for analysis 3.6 Project Development .

3.7 Selection of Classification tool

RESULTS AND DISCUSSION 4.1

4.2

Result Discussion

CONCLUSION AND RECOMMENDATION 5.1

5.2

Conclusion Recommendation

VI

. 23 .24 .24 .24 .24

• 24 . 25 .26

.27 .27

.27 .28

. 31 . 31 . 36

. 38 . 38 . 39

. 40 . 43