Fyp Thomas Tie Tong Heng 44453 Hardbound Printing.pdf

Faculty of Engineering

EMG ANALYSIS OF UPPER LIMB WITH REHABILITATION ROBOT

Thomas Tie Tong Heng

Bachelor of Engineering with Honours (Mechanical and Manufacturing Engineering) 2017

UNIVERSITI MALAYSIA SARAWAK

Grade:_____________ Please tick () Final Year Project Report



Masters PhD

DECLARATION OF ORIGINAL WORK

This declaration is made on the 24th day of May 2017.

Student’s Declaration: I THOMAS TIE TONG HENG 44453 FACULTY OF ENGINEERING hereby declare that the work entitled EMG ANALYSIS OF UPPER LIMB WITH REHABILITATION ROBOT is my original work. I have not copied from any other students’ work or from any other sources except where due reference or acknowledgement is made explicitly in the text, nor has any part been written for me by another person.

____________________ Date submitted

________________________ THOMAS TIE TONG HENG (44453)

Supervisor’s Declaration: I SHAHROL MOHAMADDAN hereby certifies that the work entitled EMG ANALYSIS OF UPPER LIMB WITH REHABILITATION ROBOT was prepared by the above named student, and was submitted to the FACULTY OF ENGINEERING as a partial fulfillment for the conferment of BACHELOR OF ENGINEERING (HONS) IN MECHANICAL AND MANUFACTURING ENGINEERING, and the aforementioned work, to the best of my knowledge, is the said student’s work.

Received for examination by:

_____________________

(SHAHROL MOHAMADDAN)

Date:____________________

I declare that Project/Thesis is classified as (Please tick (√)): CONFIDENTIAL (Contains confidential information under the Official Secret Act 1972)* RESTRICTED (Contains restricted information as specified by the organisation where research was done)*  OPEN ACCESS

Validation of Project/Thesis I therefore duly affirm with free consent and willingly declare that this said Project/Thesis shall be placed officially in the Centre for Academic Information Services with the abiding interest and rights as follows:    

 

This Project/Thesis is the sole legal property of Universiti Malaysia Sarawak (UNIMAS). The Centre for Academic Information Services has the lawful right to make copies for the purpose of academic and research only and not for other purpose. The Centre for Academic Information Services has the lawful right to digitalise the content for the Local Content Database. The Centre for Academic Information Services has the lawful right to make copies of the Project/Thesis for academic exchange between Higher Learning Institute. No dispute or any claim shall arise from the student itself neither third party on this Project/Thesis once it becomes the sole property of UNIMAS. This Project/Thesis or any material, data and information related to it shall not be distributed, published or disclosed to any party by the student except with UNIMAS permission.

Student signature _____________________ (Date)

Supervisor signature _____________________ (Date)

Current Address: N0. 48, WAYANG STREET, 98700 LIMBANG, SARAWAK

Notes: * If the Project/Thesis is CONFIDENTIAL or RESTRICTED, please attach together as annexure a letter from the organisation with the period and reasons of confidentiality and restriction.

[The instrument is duly prepared by The Centre for Academic Information Services]

APPROVAL SHEET

This project report which entitled “EMG Analysis of Upper Limb with Rehabilitation Robot” was prepared by Thomas Tie Tong Heng (44453) is hereby read and approved by:

___________________________

___________________

Dr. Shahrol Mohamaddan

Date

(Supervisor)

EMG ANALYSIS OF UPPER LIMB WITH REHABILITATION ROBOT

THOMAS TIE TONG HENG

A dissertation submitted in partial fulfilment Of the requirement for the degree of Bachelor of Engineering with Honours (Mechanical and Manufacturing Engineering)

Faculty of Engineering Universiti Malaysia Sarawak

2017

To my beloved family and friends.

ACKNOWLEDGEMENT

First of all, I would like to thank my supervisor, Dr. Shahrol Mohamaddan of Universiti Malaysia Sarawak from Mechanical and Manufacturing Engineering department for his unlimited guidance and support throughout the thesis. This thesis could not have been completed without his supervision and inspirations. I would like to thank the Lord for keeping me in good health and safe from any harm throughout my four years study in Universiti Malaysia Sarawak. Thank God for giving me strength and wisdom in completing my final year project and the whole degree course. Next, I would want to extend my thanks to my family members, especially my parents who have supported, raised and disciplined me throughout my four years of undergraduate studies. No words or actions can express how grateful I am to be surrounded by supportive family members that motivate me to achieve success. Special thanks to my coursemates and my friends who give me great encouragement and love during my degree course. May all your future endeavours succeed.

i

ABSTRACT

Stroke is one of the cardiovascular diseases (CVD). It occurs as a result of an obstruction within a blood vessel supplying blood to the brain. Stroke can happen to anyone. It affects the quality of human life. Victims of stroke may experience varying level of disability. Thus, the victims cannot perform activities of daily (ADL) as usual as before. They require people’s help to assist them to perform ADL. Normally the stroke victims undergo post-stroke rehabilitation exercise to regain their motor function. The conventional and widely used rehabilitation process involves a physiotherapist who provides physiotherapy to the stroke patients to regain their motor function. The rehabilitation exercise has some limitations. They are time consuming, costly and lacking of experienced physiotherapist. Thus, nowadays there is more interest in developing the robotic assistive device to help in the victims’ motor function recovery. The field of robotic has expanded from manufacturing to healthcare due to the advancement in technology. Robot-assisted therapy is widely used for rehabilitation for post-stroke patients nowadays. Robots are more reliable, consistent, and accurate. Besides, robots are able to repeat the same task without getting bored. Many robots have been developed in the application of post-stroke rehabilitation. However, the effect of the newly developed rehab robot onto human muscle is not known. Ethical issue will arise when the newly developed rehab robot is tested directly to the post-stroke patient. Therefore, there is a need to study the effect of the robotic rehabilitation device (RRD) towards the user. Nowadays, electromyography (EMG) analysis is widely used in studying the human muscle activity. Electromyogram studies help to facilitate the effectiveness of the rehabilitation device. Biceps and triceps of the subjects were selected to analyse their muscle activity and found out that the types of movements affect the muscles differently. All four movements Z-Y, Y-Z, X-Y, and X-X axis have been performed by the subjects in this research and the muscles activities of the subjects were obtained. The effect of the upper limb rehab robot towards human muscles was analysed.

ii

ABSTRAK

Strok ialah salah satu penyakit kardiovaskular (CVD). Ia berlaku akibat daripada sumbatan dalam salur darah yang membekalkan darah ke otak. Strok boleh berlaku kepada sesiapa sahaja. Ia menjejaskan kualiti hidup manusia. Mangsa strok mungkin mengalami tahap kemerosotan otot yang berlainan. Oleh itu, mangsa tidak dapat melakukan aktiviti-aktiviti harian (ADL) seperti biasa seperti sebelum ini. Mereka memerlukan bantuan rakyat untuk membantu mereka untuk melaksanakan aktiviti seharian. Biasanya mangsa strok menjalani latihan pemulihan selepas strok untuk memulihkan fungsi otot mereka. Proses pemulihan melibatkan ahli fisioterapi yang menawarkan khidmat fisioterapi kepada pesakit strok untuk menyembuhkan fungsi otot mereka. Cara pemulihan ini mempunyai beberapa kelemahan. Ia mengambil masa panjang, mahal dan kekurangan ahli fisioterapi yang berpengalaman lama. Oleh itu, pada masa kini, ahli-ahli sains lebih berminat dalam menghasilkan alat bantuan robot untuk membantu dalam pemulihan fungsi otot mangsa. Bidang robotik telah berkembang daripada bidang pembuatan kepada bidang kesihatan disebabkan oleh kemajuan dalam teknologi. Alat robot terapi digunakan secara meluas untuk pemulihan untuk pesakit pasca strok. Robot adalah lebih dipercayai, konsisten, dan tepat. Selain itu, robot yang dapat mengulangi tugas yang sama tanpa bosan. Banyak robot telah dibangunkan dalam permohonan pemulihan selepas strok. Walau bagaimanapun, kesan robot pemulihan yang baru dibangunkan terhadap otot manusia tidak diketahui lagi. isu etika akan timbul apabila robot pemulihan yang baru dibangunkan diuji secara langsung kepada pesakit pasca strok. Oleh itu, terdapat keperluan untuk mengkaji kesan peranti robotik pemulihan terhadap penggunanya. Pada masa kini, Electromyography (EMG) analisis digunakan secara meluas dalam mengkaji aktiviti otot manusia. kajian Electromyogram membantu untuk memudahkan keberkesanan peranti pemulihan. Bisep dan triceps subjek telah dipilih untuk menganalisis aktiviti otot mereka dan mendapati bahawa jenis pergerakan membawa kesan yang berbeza terhadap otot. Semua empat pergerakan Z-Y, Y-Z, X-Y dan X-X paksi telah dilakukan oleh subjek dalam kajian ini dan aktiviti-aktiviti otot-otot subjek eksperimen telah diperolehi. Kesan robot bantuan terhadap otot manusia telah dianalisis. iii

TABLE OF CONTENTS

Page Acknowledgement

i

Abstract

ii

Abstrak

iii

Table of Contents

iv

List of Tables

vi

List Figures

vii

List of Abbreviations

ix

Chapter 1

Chapter 2

INTRODUCTION 1.1 General Background

1

1.2 Problem Statement

3

1.3 Objective of Research

6

1.4 Scope of Research

7

1.5 Chapter Outline

7

LITERATURE REVIEW 2.1 Upper Limb

8

2.2 Effect of Stroke

14

2.3 Stroke Rehabilitation

15

2.4 Electromyography (EMG) Analysis

17

2.5 Previous Upper Limb Rehabilitation

21

Robotic Device (RRD) 2.6 Robotic Rehabilitation Device (RRD) 2.6.1 EMG-Driven Upper Limb Rehabilitation

25 25

Robotic Device (RRD) 2.6.2 Exoskeleton Hand Robotic Training Device iv

25

Chapter 3

Chapter 4

METHODOLOGY 3.1 Introduction

27

3.2 Literature Review

29

3.3 Experiment Conduct

30

3.4 Experimental Setup

31

3.4.1 Electromyography (EMG) Sensor

36

3.4.2 Skin Preparation and Electrode Placement

37

3.4.3 Hands on Arduino Software (IDE)

38

RESULTS AND DISCUSSION 4.1 Introduction

39

4.1.1 Muscle Activity 4.2 Limitations Chapter 5

40 49

CONCLUSION AND RECOMMENDATION 5.1 Introduction

50

5.2 Conclusion

50

5.3 Recommendation

51

REFERENCES

52

APPENDIX A

58

APPENDIX B

63

v

LIST OF TABLES

Table

Page

1.1

Activated muscles for motions

4

2.1

Movements of upper limb (2012)

10

2.2

Advantages and disadvantages of surface electrodes

20

(Rash & Quesada, 2003) 2.3

Advantages and disadvantages of fine wire electrodes

20

(Rash & Quesada, 2003) 3.1

Movements with respect of axis

32

4.1

Muscle activity of biceps and triceps of Subject A and Subject B

41

vi

LIST OF FIGURES

Figure

2.1

Page

Examples of EMG recordings: (A) multiple, overlapping action

19

potentials due to the concurrent activation of many motor units; (B) a train of action potentials for muscle fibers belonging to one motor unit (Figure from Rudroff et al. 2007c). 2.2

Previous upper limb rehabilitation robotic device (Tan, 2015).

22

2.3

Position of Patient and Prototype for Movements along X-X and

23

X-Z Axis (Tan, 2015). 2.4

Position of Patient and Prototype for Movements along Y-Y and

23

Y-Z Axis (Tan, 2015). 2.5

Testing of assembled prototype (Tan, 2015).

24

2.6

Scissors Lift Mechanism (Tan, 2015).

24

2.7

Armrest Mechanism.

25

2.8

Exoskeleton hand robotic training device: A) robotic hand module

27

with 5 linear actuators at the back, B) hand is secured with the robotic hand module using Velcro straps and C) holding an object with robotic hand (Ho et al., 2011). 3.1

Flow Chart.

29

3.2

Human upper limb to be examined.

31

3.3

Initial position of the upper limb (Movement 1).

33

vii

3.4

Final position of the upper limb (Movement 1).

33

3.5

Initial position of the upper limb (Movement 2).

34

3.6

Final position of the upper limb (Movement 2).

34

3.7

Initial position of the upper limb (Movement 3).

35

3.8

Final position of the upper limb (Movement 3).

35

3.9

Initial position of the upper limb (Movement 4).

36

3.10

Final position of the upper limb (Movement 4).

36

3.11

Electromygraphy (EMG) sensor.

37

3.12

User interface of Arduino Programming Software.

39

4.1

Muscle activity of biceps for movement 1 (Subject A).

41

4.2

Muscle activity of biceps for movement 1 (Subject B).

41

4.3

Muscle activity of biceps for movement 2 (Subject A).

42

4.4

Muscle activity of biceps for movement 2 (Subject B).

42

4.5

Muscle activity of biceps for movement 3 (Subject A).

43

4.6

Muscle activity of biceps for movement 3 (Subject B).

43

4.7

Muscle activity of biceps for movement 4 (Subject A).

44

4.8

Muscle activity of biceps for movement 4 (Subject B).

44

4.9

Muscle activity of triceps for movement 1 (Subject A).

45

4.10

Muscle activity of triceps for movement 1 (Subject B).

45

4.11

Muscle activity of triceps for movement 2 (Subject A).

46

4.12

Muscle activity of triceps for movement 2 (Subject B).

46

4.13

Muscle activity of triceps for movement 3 (Subject A).

47

4.14

Muscle activity of triceps for movement 3 (Subject B).

47

4.15

Muscle activity of triceps for movement 4 (Subject A).

48

4.16

Muscle activity of triceps for movement 4 (Subject B).

48

viii

LIST OF ABBREVIATION

ADL

=

Activities of daily living

CVS

=

Cardiovascular disease

DIP

=

Distal interphalangeal

DOF

=

Degree of freedom

EE

=

Elbow extension

EF

=

Elbow flexion

EMG

=

Electromyography

FP

=

Forearm pronation

FS

=

Forearm supination

IP

=

interphalangeal

LL

=

Lower limb

MP

=

Metacarpophalangeal

NCS

=

Nerve conduction studies

PIP

=

Proximal interphalangeal

RRD

=

Rehabilitation robotic device

SAB

=

Shoulder abduction

SAD

=

Shoulder adduction

SER

=

Shoulder external rotation

SHE

=

Shoulder horizontal extension

SHF

=

Shoulder horizontal flexion

SIR

=

Shoulder internal rotation

SVE

=

Shoulder vertical extension

SVF

=

Shoulder vertical flexion

UE

=

Upper extremity

UL

=

Upper limb

WE

=

Wrist extension

WF

=

Wrist flexion

WRD

=

Wrist radial deviation

ix

CHAPTER 1

INTRODUCTION

1.1 General Background

Stroke is one of the critical illnesses in this world. According to Gurr and Dendle (2015), an interruption of the blood supply to part of the brain causes stroke. Stroke can happen very suddenly and strike a person without giving any sign of warning. It happens to anyone. Stroke is one of the main leading causes of adult disability in Western countries and it is one of the most common causes of death in the world (Archambault, Fung & Nahid, 2012). In Malaysia, an estimated of 40,000 people suffer from stroke annually (National Stroke Association of Malaysia, n.d.-a). Strong, Mathers and Bonita (2007) stated that the worldwide burden of stroke is increasing and expected to rise to 23 million first-ever strokes by 2030. Archambault et al. (2012) claimed that people who are able to survive after hitting by stroke suffer of the partial loss of neurological functions as a result of brain cell damage. The blockage of blood vessels in the human brain causes blood cannot be supplied to certain brain tissues. Thus, the brain cells die as a result of no nutrients and oxygen supply. According to Truelsen and Bonita (2009), there are an estimated 64.5 million stroke survivors who live with varying levels of disability and require assistance for activities of daily living (ADL) among those who have experienced a stroke. Post-stroke patients should undergo post-stroke rehabilitation program to regain the motor function of their upper limb (UL). 1

Rehabilitation is the combination and coordination application of medical, social, educational, and vocational measures for retraining patient to the highest possible level of functional ability (Dombovy, Sandol, & Basford, 1986). This process is time consuming and costly. The rehabilitation period varies from weeks to months. Many hours are spent on post-stroke rehabilitation to improve motor function, reduce impairment and enable stroke survivors to live more independently. A great part of stroke rehabilitation involves improving motor function. Langhome, Coupar and Pollock (2009) stated that out of 10 stroke survivors, 8 of them have motor deficits which in the end cause serious disability. According to Adams (2007), brain artery that plays important role to transport blood to areas which control human upper limb (UL) always involve in a stroke thus it causes human UL experience severe impairments more frequently. Loureiro, Amirabdollahian, Topping, Driessen, and Harwin (2003) stated that human upper limb (UL) is more difficult to recover if compared to human lower limb (LL). This is because human UL is complex and it performs most of the basic ADL such as locating a target, reach (transport of arm and hand) and also grasp an object.

Many secondary

complications due to immobilization may also occur, including joint contracture, muscle atrophy and shoulder-hand syndrome. Hence, it is essential for the UL to be supported and rehabilitated.

2

1.2 Problem Statement The upper limb (UL) motions play very essential role in the daily life of human beings. Human beings use their upper limb to conduct the activities of daily life (ADL) such as eating, drinking, bathing, brushing teeth, washing face and so on. It is sometimes difficult for the weak elderly, disabled and injured individuals to perform daily UL activities.

Nowadays, the number of physically weak population is

increasing but the number of young population which is in another way round. This situation causes the weak individuals to take care of themselves in present society. Human UL consists of several degrees of freedom (DOF). Generally, shoulder joint consists of 3DOF, elbow joint consists of 2DOF and wrist joint consists of 2DOF. Rosen, Perry, Manning, Burns, and Hannaford (2005) mentioned that there are eight basic individual motions of human UL. They are shoulder vertical flexion/extension, shoulder

horizontal

flexion/extension,

shoulder

adduction/abduction,

shoulder

internal/external rotation, elbow flexion/extension, forearm supination/pronation, wrist flexion/extension, and wrist ulnar/radial deviation. In daily life, human upper limb perform the combination of these basic motions. There are many muscles that activate human UL. Some of them are bi-articular muscles and the others are uni-articular. In the UL agonist-antagonist muscles activate shoulder, elbow and wrist. The upper-limb motions and the related muscles for the motions (Martini, Timmons & Tallitsch, 1997) are shown in Table 1. The rehabilitation process takes place conventionally in which it involves a physiotherapist who provides physiotherapy to those disabled, weak or stroke patients. The rehabilitation activities involve a several exercises which help to improve the UL motor function recovery. The patients are required to attend the physiotherapy session consistently so that the recovery process goes on smoothly. Maciejasz, Eschweiler, Gerlach-Hahn, Jansen-Troy, and Leonhardt (2014) highlighted that when patients have neurologically based disorders, it depends a lot on several factors as stated, rehabilitation duration, intensity of activities, training’s task orientation, patient’s health condition, patient’s attention and patient’s effort too, in order to get positive outcome of physical rehabilitation.

3

Table 1.1 below shows the muscles involved in the motions of upper limb. Table 1.1 Activated muscles for motions Motion

Activated Muscles

Shoulder vertical flexion (SVF)

Coracobrachialis,

Deltoid

(anterior),

Pectoralis

major Shoulder

vertical

extension Deltoid (posterior), Teres major, Latissimus dorsi

(SVE) Shoulder

horizontal

flexion Pectoralis major (calvicular part)

(SHF) Shoulder horizontal extension Deltoid (posterior) (SHE) Shoulder adduction (SAD)

Coracobrachialis, Latissimus dorsi, Teres major, Pectoralis major

Shoulder abduction (SAB)

Deltoid, Supraspinatus

Shoulder internal rotation (SIR)

Deltoid (anterior), Subscapularis, Latissimus dorsi, Teres major

Shoulder external rotation (SER)

Deltoid (posterior), Infraspinatus, Teres minor

Elbow flexion (EF)

Biceps brachii, Brachioradialis, Brachialis

Elbow extension (EE)

Anconeus, Triceps brachii

Forearm supination (FS)

Supinator, Biceps brachii (long head)

Forearm pronation (FP)

Pronator quadratus, Pronator teres

Wrist flexion (WF)

Flexor carpi radialis, Flexor carpi ulnaris, Palmaris longus

Wrist extension (WE)

Extensor carpi radialis longus, Extensor carpi radialis brevis, Extensor carpi ulnaris

Wrist ulnar deviation (WUD)

Flexor carpi ulnaris, Extensor carpi ulnaris

Wrist radial deviation (WRD)

Extensor carpi radialis longus, Extensor carpi radialis brevis, Flexorcarpi radialis

4

According to Cheng et al. (2012), there are some limitations of one-to-one manually assisted upper limb rehabilitation therapy. Firstly, it is lacking of occupational therapists. Wong (2014) mentioned that the ratio of occupational therapist to patients is 1:20,000. It is running out of manpower in upper limb rehabilitation therapy. Besides, rehabilitation therapy is time consuming. There are a lot of activities needed to be done by the patients repeatedly, consistently and precisely for certain duration until the patients regain motor function. Thirdly, Amiradollahian et al. (2003) added, physiotherapy is inconsistent varying from one therapist to another and from hospital to hospital. Amiradollahian et al. (2003) even mentioned that physiotherapy is not totally depending on theories or literature research but on the type of approach that the therapist was trained on and the experience gained over the years by working with patients and experts in field. Therefore, traditional rehabilitation approach is lacking of high motivational content, and objective standardized analytical methods for evaluating patient’s performance and assessment of therapy effectiveness (Amiradollahian et al., 2003). As a result, interest in the use of robotic therapy for rehabilitation is increasing. Lately, assistive robotic system have been developed to assist daily life motions and/or rehabilitation of physically weak persons (Gopura and Kiguchi, 2008; Gupta et al., 2006; Kawamoto and Sankai, 2005; Kiguchi, 2007; Sasaki et al., 2014). The assistive robotic system that were developed are human robot interacting. In a human robot interaction scenario, the prediction of human motion intention is important in order to avoid inconvenient delays and for a smooth reactivity of the robotic system. Nowadays, rehabilitation programs are using rehabilitation devices in their tasks. The functionality of devices depends on muscle contraction. Electromyogram studies help to facilitate the effectiveness of the rehabilitation device. The technique of measuring electrical activity that produced by muscles during rest or contractions known as electromyography (EMG). The electrical signal generates from the brain and sends to the muscles via motor neuron. The EMG could detect the dysfunctional of the muscles or failure in signals transmission from nerves to muscles. The failure of sending the electrical signal from the brain to the conducting nerves requires electrical stimulation from the external source to muscles. Electrodes are used for signal detection of electrical activity in muscles.

5

The study of this electrical activity is important for combination of electromyogram into the rehabilitation device. EMG signal reflects the muscles activity of the users directly. It provides important information for power-assist robotic systems to understand the motion intention of the user. Therefore, it is necessary and important to analyze the relationships between the UL motions and related muscle activities to perform the power-assist of the UL motion. There were some researchers had done several studies regarding EMG signals. According to Coury, Kumar, and Narayan (1998), an EMG study has been carried out for adduction force with varying shoulder and elbow postures. Besides, Kronberg et al. (1990) have studied about the muscle activity and coordination in the normal shoulder. A small-sized training set of EMG signals data have been used to identify UL movements (Micera et al., 2000). The rehabilitation device is a tool that used to help the movements for daily life activities of the patients who suffer from UL motor malfunction, due to the failure of the muscles contractions the movements is limited. The ability of the patients to do the tasks in the rehabilitation programs need to be measured. Ada, Dorsch and Canning (2006) mentioned that the rehabilitation programs have to assure whether the tasks will cause effective or bring harm to the patients.

Summary of problem statement: I. II. III.

Difficulty in studying the muscles activity of human upper limb. Difficulty in control the upper limb movement during rehabilitation. Poor interaction between power-assist robotic system and users.

1.3 Objective of Research I.

To analyze the muscle activity of human’s upper limb using EMG signals.

II.

To study the effect of the rehabilitation robotic device (RRD) towards human upper limb muscle.

6

1.4 Scope of Research This chapter will focus on the electromyography analysis of the upper limb with rehabilitation robot. This research will determine the effect of the upper limb rehabilitation robot towards human upper limb muscle. The selected device is the upper limb rehabilitation robotic device produced by Tan, 2015.

1.5 Chapter Outline Chapter 1: Introduction Mainly introduce definition of stroke. Discuss the facts regarding stroke. Discuss the importance of power-assisted robotic devices in rehabilitation. The problem statement is also being listed and the objectives of the project are being mentioned too. Chapter 2: Literature Review The extensive reading and study were done and in this section, the type of the upper limb robotic device that had been developed was being reviewed here. Chapter 3: Methodology This section elaborates the methods that were used to complete this project. Those methods include the extensive study, software hands on, and wiring were being learnt and were being described in this section. Chapter 4: Results and Discussions In this section, the result will be reported based on the objectives that were being set earlier. There will be description and discussion on the product or the system that were being developed. Chapter 5: Conclusions and Recommendations This section concludes the project whether have it achieved the objectives or not. The main advantages of the product or system developed are being emphasized again this session. It also includes the part of the recommendation which mention about the future work for this project.

7

CHAPTER 2

LITERATURE REVIEW

2.1 Upper Limb

Basically, human upper limb (UL) consists of shoulder, arm, forearm and hand. The learning modules Movements of the Upper Limb (2002) stated that upper limb (UL) is highly mobile since UL is the human primary tool to manipulate the environment. Upper limb consists of a lot of joints so it is highly (Movements of the Upper Limb, 2002). UL and hands have slowly evolved into organs having great manipulative skill. Whole UL works as a jointed lever. Besides, human hand grasp tool. It is able to perform various complex functions. UL has been highly modified to enable the superior reach and grasp. Hand is the most evolved organ in UL. Human hand’s functions reflect their ability to do work. Besides, our shoulder, arm and forearm are responsible to put our hand where we want it to be, doing what we want it to do. They put the hand into desirable positions. They lift and rotate to reach something.

8

Table 2.1: Movements of upper limb (2012) Movement

Description

Scapular

Scapular protraction is also known

Protraction

as scapula abduction. The scapula moves laterally and anteriorly along the chest wall.

Scapular

Also known as scapula adduction.

Retraction

The scapula moves posteriorly and medially along the chest wall.

Scapular Upward The scapula can pivot on its Rotation

attachment to the clavicle, and rotate upward. This is also called upward rotation of the glenoid fossa, and it is an essential motion for completing abduction of the arm.

Scapular

When the arm is fully abducted,

Downward

downward rotation of the scapula

Rotation

(or glenoid fossa) occurs first in adduction of the arm.

9

Picture

Arm Abduction

Also

known

as

shoulder

abduction. This motion actually can be divided into two motions: true abduction of the arm at the shoulder and upward rotation of the scapula.

Arm Adduction

Also

known

as

shoulder

adduction. This motion can be divided

into

two

motions:

downward rotation of the scapula and true adduction of the arm at the shoulder.

Arm Flexion

Also known as shoulder flexion. It is typically thought of as an anterior excursion of the arm, but remember that any motion away from full extension is flexion.

Arm Extension

Also

known

as

shoulder

extension. It is typically thought of as movement of the arm posteriorly, but remember that any motion away from full flexion is extension Forearm Flexion

Sometimes it is called elbow flexion.

10

Forearm

Extension of the forearm is also

Extension

called elbow extension.

Hand Supination

Supination of the hand brings the palm to face forward in the anatomical position. It is the position you would place your hand in order to hold "soup".

Hand Pronation

Pronation of the hand brings the palm to face posteriorly in the anatomical position, or face down when lying down.

Wrist Flexion

Sometimes it is called hand flexion.

Wrist Extension

Sometimes it is called hand extension.

11

Wrist Abduction

Also

known

as

hand

radial

deviation, because the hand moves toward the radius, or laterally.

Wrist Adduction

Also

known

as

hand

ulnar

deviation, because the hand moves medially toward the ulna.

Finger Flexion

The four fingers have 3 different joints at which they can flex or extend - the metacarpophalangeal (MP)

joint,

the

proximal

interphalangeal (PIP) joint, and the distal interphalangeal (DIP) joint. Finger Extension

Extension of the fingers occurs at the same 3 joints, but there is no muscle that extends only the DIP joint.

Thumb Flexion

In contrast to the fingers, the thumb can flex at only two joints the metacarpophalangeal joint and an interphalangeal (IP) joint, since it has only two phalanges. Flexion of the thumb takes place in a plane at an angle to the other digits. 12

When flexed, the thumb points generally toward the 5th MP joint. Thumb Extension

Extension of the thumb also occurs in a plane offset from that of the fingers, but the motion has the same effect of taking the thumb

posteriorly

anatomical position.

13

in

the

2.2 Effect of Stroke The quality of life of a person is greatly affected when he or she cannot perform the activities of daily due to stroke. Stroke causes motor impairment. Murray and Lopez (1997) mentioned that stroke is the second most common cause death after ischaemic heart disease. Archambault, Fung and Nahid (2012) pointed out that stroke is one of the main leading causes of adult disability in Western countries. 9 % of all deaths around the world is due to stroke. Bonita (1992) found that in western countries, there are approximately 12 % of deaths are as a result of stroke and among these group of people, 12 % of them are below 65 years old. Stroke is a cerebral vascular disease (CVD) which occurs when human brain loses oxygenated blood supply due to blood vessel blockage (Archambault et al., 2012). Human brain is the nerve centre of a human body. It is responsible for coordinating sensation, intellectual, and nervous activity (National Stroke Association of Malaysia, n.d.-a). Continuous supply of oxygenated blood is essential for the brain to work well. The blockage of blood vessels in the human brain causes blood cannot be supplied to certain brain tissues. Thus, the brain cells die and result in permanent brain damage. Trueslen and Bonita (2009) stated that different patients face different levels of disability. Some patients may experience light problems such as momentary weakness of limbs whereas some patients would be permanently paralyzed on one side of the body or lose the ability to speak. According to a study, there is 33 % of the stroke patient will recover completely while the other 67 % will face some types of disability (National Stroke Association of Malaysia, n.d.-b).

14

2.3 Stroke Rehabilitation Conventional stroke rehabilitation such as exercise therapy aims to help stroke patients’ recovery by doing several exercises consistently, precisely and repeatedly. Loureiro et al., (2003) mentioned that the recovery of the impaired UL can be done by means of physiotherapy which this therapy has been accepted worldwide as a routine for patient following a stroke. The stroke patients need to make appointment with hospital authority and then attend to the hospital in order to undergo the physiotherapy with the physiotherapist’s aid and guidance. However, people care about how far can the exercise therapy be improved so that it is able to help the stroke patients in speed recovery. Conventional rehabilitation involves one-on-one treatment between the therapist and stroke patient. This is labor-intensive and experience-dependent. Some therapists are experienced but some are not. The experienced therapist knows how to help the patients to regain motor function using the best way but the inexperienced one may not know. This causes the rehabilitation process to be ineffective and. Therefore, it is necessary to develop better ways to augment exercise training in a functional way. The conventional exercise therapy consists of several types. The interaction between the therapist and patient are categorised into three categories which are passive, active-assisted, and active-resisted movement (Lum, Reinkensmeyer, Mahoney, Rymer, & Burgar, 2002). Firstly, the patient doesn’t need to have any effort in passive movement. The therapist moves the patient’s joint. Range of motion at joint and flexibility in muscle and connective tissue is maintained. Passive movements can also momentarily reduce hypertonia or resistance to passive movement. Secondly, in active-assisted movement, the therapist will only help the patients to complete the movement that they are unable to do by their own. In active-assisted movement, patients who are unable to complete movement of their joints independently is aided by external forces from therapist or patient’s contralateral limb, or from constraints which guides and assists the movements. Active-resisted movement is where patients are capable to complete movements, resisting gravity, extra weights, elastic bands, or therapist.

15

In recent decades, more scientist, research and development engineer are getting more interested in the use of robotic therapy for rehabilitation. With the advancement of technology, the field of robotics play important role in medical and health care. This improves human’s healthcare. Among many fields of robotics, the current research community around the world has been attracted to the assistive robotic technologies. Assistive robotic technology gives hope to those disabled person and stroke victims that they will one day regain their motor function. This has improved the function and ability of rehabilitation based on the various types of robots that have been developed for the upper extremity (UE) on the paralyzed sides of the body (Miyasaka et al., 2015). Robotic rehabilitation therapies are able to provide high-frequency and high-intensity training, thus making it beneficial for patients with motor disabilities caused by stroke or spinal cord disease (Chang & Kim, 2013). Krebs, Hogan, Aisen, and Volpe (1998) claimed that robotics is a new promising development that can be used as therapeutic adjuncts to facilitate clinical practice. People who have UL disability can have their own home-based rehabilitation robotic device and have the rehabilitation process at home. They are able to train themselves independently. Furthermore, by using computer-assisted devices for regaining UL function, the robot can easily apply new constraints, to optimize the required movement pattern. Thus, the complexity of a motor task to be learned can be controlled far more precisely with robotics than in conventional treatment approaches. Owing to the assistive robots have interactions with users, it is needed to be controlled using sophisticated technologies. They are required to control according to the motion intention of the user. Electromyography (EMG) is identified as one of the potential signals for these control methods in order to monitor the motion intention of the assistive robots users. There are still problems in control methods of UL assistive robots to be coped although many studies have been carried out previously by the researchers. They need to put more effort in their studies to cope all these problems. Hence, this thesis is prepared to address issues related to the control of UL assistive robots using EMG signals.

16

2.4 Electromyography (EMG) Analysis According to Whittaker (2012), patients who have neuromuscular disease needs to do electromyography (EMG) assessment to provide help in their motor function recovery. Basmajian and De Luca (1985) claimed that electromyography (EMG) is an experimental technique concerned with the development, recording and analysis of myoelectirc signals which are formed by physiological variations in the electrical behavior of muscles fiber membranes. EMG has several functions. According to Basmajian and De Luca (1985), it has been used in the muscle function assessment during exercise or therapeutic procedures. EMG is able to provide biofeedback to the patients. It can evaluate the muscular control of the patients by assessing muscle onset time duration or to establish motor unit discharge rates, assess gait, determine the requirements of job-related tasks and assess fatigue. EMG translates the signals transmitted by motor neurons to cause muscles to contract into data and display through the electromyogram. Soderberg and Cook (1984) stated that EMG has evolved to be a great technique to study muscle function and dysfunction due to the advancement of technology in instrumentation and sophisticated electronics during recent decades. Electromyogram is used to measure the muscle electrical activity whivh is either stationary or contract. Nerve conduction studies (NCS) measure health of people’s nerves. Nerves send impulses in the form of electrical signals to muscles in order to make them react as human desires. Electromyography analysis is encouraged to be carried out by the people who have neurological disorder or motor unit malfunction. EMG analysis will determine the healthiness and function of the human muscle. Rash and Quesada (2003) claimed that there are two types of electromyography (EMG). They are clinical (diagnostic) EMG and kinesiological EMG. Normally, physiatrists and neurologists run diagnostic EMG to study the characteristics of the motor unit action potential for duration and amplitude in order to help diagnostic neuromuscular pathology. Besides, it also evaluates the spontaneous discharges of relaxed muscles and is able to isolate single motor unit activity. Kinesiological EMG is an established subfield of modern locomotion biomechanics (Rash & Quesada, 2003). It analyzes the muscle movement activity. It also studies the relationship of muscular

17

function to movement of the body segments and evaluates timing of muscle activity with regard to the movements. EMG recording is known as bipolar recording too. It requires two electrodes. The resulting signal represents the potential difference between the two electrodes. For recording an EMG signal, the electrodes can be placed on the skin over a muscle (surface EMG), under the skin but over the muscle (subcutaneous EMG), or in the muscle between the fibers (intramuscular EMG). The size and location of the electrode determine the composition of the recording, which can range from single action potentials to global muscle activity (Fig 2.1). Surface EMG recordings with many overlapping action potentials are known as interference EMG (Adrian, 1925; Fuglesang-Frederiksen, 2000; Sanders et al., 1996). Electrodes placed on the skin provide a global measure of action potential activity in the underlying muscle, whereas fine wire electrodes placed in the muscle are able to record both interference EMG and single action potentials from adjacent muscle fibres.

A

B

Figure 2.1 Examples of EMG recordings: (A) multiple, overlapping action potentials due to the concurrent activation of many motor units; (B) a train of action potentials for muscle fibers belonging to one motor unit (Figure from Rudroff et al. 2007c).

Soderber and Cook (1984) stated that there are two types of electrode techniques used in kinesiological EMG. They are surface electrodes and fine wire electrodes. Surface electrode is a small device that is attached to the skin to measure or cause 18

electrical activity in the tissue under it. It is able to detect the problems happened in muscles and nerves. Surface electrode is taped to the skin to measure the speed and strength of signals travelling two or more points. There are two groups in surface electrodes. The first is active electrode whereby there is a built-in amplifier at the electrode site to improve the impedance. Second is passive electrode. It detects EMG signal without a built-in amplifier, making it important to reduce all possible skin resistance as much as possible. With passive electrodes, signal to noise ratio decreases and many movement artifacts are amplifies along with the actual signal once amplification occurs. Table 2.2 Advantages and disadvantages of surface electrodes (Rash & Quesada, 2003) Advantages 

Less pain caused;



Move reproducible;



Easy to apply;



Good for movement applications.

Disadvantages 

More potential for cross talk from adjacent muscles;



Large pick-up area;



Can only be used for surface muscles.

The second electrode technique is fine wire electrodes. This technique requires a needle for insertion into the belly of the muscle. Table 2.3 Advantages and disadvantages of fine wire electrodes (Rash & Quesada, 2003) Advantages

Disadvantages



Extremely sensitive;



Invasive;



Record single muscle activity;



Repositioning nearly impossible;



Access to deep musculature;



Small detection area;



Low concern of cross-talk.



Minor discomfort.

19

It is difficult to obtain EMG recordings from thin and deep muscles due to crosstalk from adjacent muscle layers. Therefore, surface electrode is not suitable for recording muscle activity in these muscles. Although fine wire electrodes can be manipulated while monitoring EMG activity and are suitable for clinical investigations, accurate placement of fine wire electrodes is more difficult than with surface EMG. They must hook into the desired muscle layer and cannot be repositioned once inserted. Once inserted fine wire electrodes are superior for prolonged and non-clinical investigations of muscle function because they are hooked in the muscle fibres and therefore move with the fibres ensuring that the recording area is the same.

20

2.5 Previous Upper Limb Rehabilitation Robotic Device (RRD)

Figure 2.2 Previous upper limb rehabilitation robotic device (Tan, 2015). Figure 2.3 above shows the fabrication of upper limb rehabilitation robot developed by Tan (2015). Tan claimed that the problems of the previous rehabilitation robotic device are big, heavy and bulky. This makes it not convenient to the disabled person to use it. Therefore this problem should be encountered. Through several studies he had made, he developed this rehab robot which is lightweight, portable and also home-setting in the end. The upper limb rehabilitation robotic device which had been developed by Tan has several advantages. This RRD is lightweight and portable. The robot consists of two sections. They are upper and lower platform. Tan (2015) stated that the upper platform enables movement along x-axis and y-axis while the lower platform enables vertical movement along z-axis. The length, width and height of the rehab robot are 770mm, 135mm and 220 mm respectively. Besides, this rehab robot weighs 7.0 kg. The rehab robot must be placed on a flat surface so that it is able to function. The robot is equipped with motors, motor driver, microcontroller and some material used to develop the device such as, aluminium, wood, bolt and nuts.

21

Figure 2.3 Position of Patient and Prototype for Movements along X-X and X-Z Axis (Tan, 2015). When the rehab robot is placed horizontally from the patient, the rehab robot moves along X-X axis and X-Z axis as shown in Figure 2.3 (Tan, 2015)

Figure 2.4 Position of Patient and Prototype for Movements along Y-Y and Y-Z Axis (Tan, 2015). However, when the rehab is placed vertically from the patient, the device moves in Y-Y axis and Y-Z axis as shown in Figure 2.4 above (Tan, 2015).

22

Figure 2.5 Testing of assembled prototype (Tan, 2015). Figure 2.5 shows a male student who acts as a subject for the rehabilitation robotic device. The device is being control by the motor controller which the controller is connected to the microcontroller called Arduino. The movement along X-X, X-Z, YY and Y-Z axis is being done on the device by using the programming of the Arduino. This rehab robot applies two mechanisms which are scissors lift and armrest mechanism. These mechanisms are important in order to move the patient’s shoulder and elbow. The scissors lift mechanism travels along z-axis. The pushing force pushes the link towards the dead joint, resulting in an upward motion. The scissors lift mechanism moves linearly in two directions as the rehab robot can be placed either horizontally or vertically from the patient.

Figure 2.6 Scissors Lift Mechanism (Tan, 2015) Figure 2.6 shows the scissors lift mechanism used in the rehab robot.

23

Figure 2.7 Armrest Mechanism. Patients can place their forearm at the armrest when using the rehab robot. The armrest mechanism is produced by the four small nylon rollers attached at the bottom of the wooden block. It moves linearly along the x- or y-axis, depending on the position of the rehab robot from the patient. Figure 2.7 shows the arm rest mechanism used in the rehab robot.

24

2.6 Robotic Rehabilitation Device (RRD) Frumento, Messier, and Montero (2010) mentioned that the field of the Robotics Rehabilitation Engineering started officially with the research into Powered Human Exoskeleton Devices in the 1960s. Besides, according to Tan (2015), the Department of Veterans Affairs (VA) Palo Alto Health Care System and the School of Engineering at Stanford University had initiated the collaborative research and development efforts in the area of Robotics Rehabilitation Devices. The purpose to have a research on Robotics Rehabilitation Devices at that time was to replace the lost or impaired anatomy (Burgar, Lum, Shor, & Van der Loos, 2000). According to Prange (2009), nowadays the advancement of the technology has reached the level providing the chance to design therapeutic interventions that take many key aspects for stimulation learning into account.

2.6.1 EMG-Driven Upper Limb Rehabilitation RoBotic Device (RRD) Colombo et al. (2005), Tong and Hu (2008) claimed that robots have proved to be effective in assisting the therapist to provide safe and intensive rehabilitation training for the stroke subjects. According to Tong and Hu (2008), rehabilitation robot for elbow and wrist has already been proven effective in clinical trials. In the market nowadays, there are only a few RRD found.

2.6.2 Exoskeleton Hand Robotic Training Device One of the RRD is an exoskeleton hand robotic training device. An exoskeleton hand robotic training device is specially designed for stroke survivors to actively train their impaired hand functions. By measuring his/her surface electromyography (EMG) signals from the impaired hand muscles, this robotic device detects the stroke person’s intention and assists in hand opening or hand closing.

25

A

B

C

Figure 2.8 Exoskeleton hand robotic training device: A) robotic hand module with 5 linear actuators at the back, B) hand is secured with the robotic hand module using Velcro straps and C) holding an object with robotic hand (Ho et al., 2011).

Figure 2.8 above shows the exoskeleton hand robotic training device developed by Ho et al. (2011). This system consists of a robotic hand module and an embedded controller. The fingers and the palm of the stroke subject hand are mounted comfortably on to the robotic hand module using finger rings and Velcro straps. The palm area of the hand and distal interphalangeal (DIP) joint on figure are left open to allow user to grip and feel the objects with their own fingers.

26

CHAPTER 3

METHODOLOGY

3.1 Introduction

This chapter discusses the steps and methods of conducting this research. The mechanism of the newly developed upper limb rehabilitation robot by the previous final year project student was studied. This chapter summarizes the way to analyze the human upper limb muscle activity using EMG with the upper limb rehabilitation robotic device. The result obtained was analysed and comparison was made between the experimental result and the result obtained using simulation.

27

Figure 3.1 below shows the flow chart of this final year project. \ Start

Extended literature review writing

Study the mechanism of upper limb rehabilitation robot

Study EMG and Arduino sensor

Conduct Experiment

No Successful Successful Successful Yes Result analysis

End End

Figure 3.1Flow chart. 28

Figure 3.1 shows the process flow in analysing the upper limb muscle activity using EMG sensor. Many journals, articles and websites regarding storke, post-stroke upper limb rehabilitation, robotic rehabilitation and EMG sensor have been studied. This is to give idea on how to conduct the experiment to analyse upper limb muscle activity using EMG sensor. Lastly, the effect of the upper limb rehab robot towards human muscles was analysed.

3.2 Literature Review The objective of this research acts as a guideline to complete the final year project to study on human muscle activity through EMG. The literature research was started by using Google Scholar, IEEE, Springer and Mendeley. The research content of the literature review began by using terms such as “stroke”, “activities of daily”, “upper limb”,

“upper limb rehabilitation”, “robotics”, “electromyography”, and “arduino

sensor”. Then it narrowed down to “robot-assisted therapy”. After reviewing many journals, articles, and websites, application of robotics in post-stroke rehabilitation program was proven to have a higher chance of motor recovery in post-stroke patient. However, a newly developed rehabilitation robot cannot be used directly on a poststroke patient without knowing how the rehabilitation robot affects the patient’s muscle.

29

3.3 Experiment Conduct Two subjects were chosen to conduct the experiment. The subjects need to fulfill the following requirement: a. Cooperative; b. Muscular; c. Less hair on upper limb; d. Aged between 20 to 25; and e. One male one female. There are three parts of human upper limb area were chosen to place the surface EMG sensor in order to obtain the electrical signal of human muscles when several movement is made. They are deltoid, biceps and triceps.

Figure 3.2 Human upper limb to be examined.

30

3.4 Experimental Setup The experiment was set in the control lab of Mechanical and Manufacturing department. The experimental was set up with the subject(s) sit on the chair while the hand is on the table. The subject was briefed through the steps of the experiment. All the experimental procedures were discussed with the subject before the experiment started. The area of the subject’s upper limb to be placed using EMG sensor was cleaned wet tissue before the taping of the surfac electrodes. The EMG sensor was taped at that particular area of the upper limb that had been cleaned. Four movements were made by the subject. The EMG analysis result is obtained and visualised in the form of graphs and tables. The experiment was repeated by inserting the electrodes at different area of upper limb.

Table 3.1 Movements with respect of axis.

Movement

Axis

1

Z-Y

2

Z-Z

3

X-Y

4

X-X

31

Figure 3.3 Initial position of the upper limb (Movement 1).

Figure 3.4 Final position of the upper limb (Movement 1).

32

Figure 3.5 Initial position of the upper limb (Movement 2).

Figure 3.6 Final position of the upper limb (Movement 2).

33

Figure 3.7 Initial position of the upper limb (Movement 3).

Figure 3.8 Final position of the upper limb (Movement 3).

34

Figure 3.9 Initial position of the upper limb (Movement 4).

Figure 3.10 Final position of the upper limb (Movement 4).

35

3.4.1 Electromyography(EMG) Sensor

Figure 3.11 Electromygraphy (EMG) sensor. Electromygraphy(EMG) sensor is used in this experiment to obtain the subject’s upper limb muscle activity. It measures the electrical activity of the muscles at rest and during contraction. EMG signlas are used in many clinical and biomedical applications. EMG is used as a diagnostics tool for identifying neuromuscular diseases, assessing low-back pain, kinesiology and disorders motor control. EMG signals are also used as a control signal for prostehtic devices such as prosthetic hans, arms and lower limbs. This sensor will measure the filtered and rectified electrical activity of a muscle, depends on the amount of activity in the selected muscle. Features: 

Adjustable gain



Small Form Factor



Full integrated

36

3.4.2 Skin Preparation and Electrode Placements Skin preparation preceeds EMG sensor placements. The skin of the subject was cleaned by using wet tissue. This is to make sure the noise can be minimized and ensure a good contact with the electrodes of the skin.

3.4.3 Hands on Arduino Software (IDE) The microcontroller that is used in the device is Arduino board. Arduino is an open-source electronics platform or board and the software used to program it. Arduino is designed to make electronics more accessible to artists, designers, hobbyists and anyone interested in creating interactive objects or environments. Arduino boards are able to read inputs such as lights on a sensor, a finger on a button and turn it into an output – activating a motor, turning on an LED, publishing something. A set of instructions can be sent to the microcontroller on the board in order to tell the board what to do. To do so, Arduino programming language and the Arduino Software (IDE) are being used. It is important to explore and master the skill of programming by using Arduino Software (IDE) because all the algorithm will be related to this software. Arduino Software (IDE) user interface is being shown in Figure 3.12.

37

Figure 3.12 Arduino Software (IDE) user interface.

38

CHAPTER 4

RESULTS AND DISCUSSION

4.1 Introduction

This chapter presents the results in the form of graphs and tables obtained from the experiment using EMG sensor. The subjects of the experiment were asked to perform four movements in order to examine and study their muscle activities at their biceps and triceps. The upper limb rehabilitation robot which was fabricated by the previous senior was used in this experiment conduction. The effect of the upper limb rehab robot towards human muscles had been discussed further in this chapter.

4.1.1 Muscle Activity Biceps and triceps of the subjects were studied. The biomedical surface electrodes were taped to the biceps and triceps of the subject to obtain the reading of muscle activity. Figure 4.1, 4.2, 4.3, 4.4, 4.5, 4.6, 4.7, 4.8 shows the biceps’ muscle activity obtained from both Subjects A and B throughout the experiment. Meanwhile, figure 4.9, 4.10, 4.11, 4.12, 4.13, 4.14, 4.15 and 4.16 shows the triceps’ muscle activity of the two subjects. Each subject practises four movements throughout the experiment using the rehab robot.

39

Table 4.1: Muscle activity of biceps and triceps of Subject A and Subject B Subject A Candy Tie Shi En First Movement (Biceps)

Muscle Activity

Muscle Activity Vs Time 500.00 450.00 400.00 350.00 300.00 250.00 200.00 150.00 100.00 50.00 0.00 15:05:46

Muscle Activity

15:06:29

15:07:12

15:07:55

Time

Figure 4.1 Muscle activity of biceps for movement 1 (Subject A).

Subject B Faiz Othman First Movement (Biceps)

Muscle Activity

Muscle Activity Vs Time 500.00 450.00 400.00 350.00 300.00 250.00 200.00 150.00 100.00 50.00 0.00 13:55:55

Muscle activity

13:56:38

13:57:22

13:58:05

Time

Figure 4.2 Muscle activity of biceps for movement 1 (Subject B).

40

Subject A Candy Tie Shi En Second Movement (Biceps)

Muscle Activity Vs Time 450.00 400.00 Muscle Activity

350.00 300.00 250.00 200.00

Muscle Activity

150.00 100.00 50.00 0.00 15:10:48

15:11:31

15:12:14

15:12:58

Time

Figure 4.3 Muscle activity of biceps for movement 2 (Subject A).

Subject B Faiz Othman Second Movement (Biceps)

Muscle Activity

Muscle Activity Vs Time 450.00 400.00 350.00 300.00 250.00 200.00 150.00 100.00 50.00 0.00 14:07:26 14:08:10 14:08:53 14:09:36 14:10:19

Muscle Activity

Time

Figure 4.4 Muscle activity of biceps for movement 2 (Subject B).

41

Subject A Candy Tie Shi En Third Movement (Biceps)

Muscle Activity Vs Time 600.00 Muscle Activity

500.00 400.00 300.00 Muscle Activity

200.00 100.00 0.00 15:15:50

15:16:34

15:17:17

15:18:00

Time

Figure 4.5 Muscle activity of biceps for movement 3 (Subject A).

Subject B Faiz Othman Third Movement (Biceps)

Muscle Activity Vs Time 600.00

Muscle Activity

500.00 400.00 300.00 Muscle Activity

200.00 100.00 0.00 14:12:29 14:13:12 14:13:55 14:14:38 14:15:22 Time

Figure 4.6 Muscle activity of biceps for movement 3 (Subject B).

42

Subject A Candy Tie Shi En Forth Movement (Biceps)

Muscle Activity Vs Time 700.00 Muscle Activity

600.00 500.00 400.00 300.00

Muscle Activity

200.00 100.00 0.00 15:20:53

15:21:36

15:22:19

15:23:02

Time

Figure 4.7 Muscle activity of biceps for movement 4 (Subject A).

Subject B Faiz Othman Forth Movement (Biceps)

Muscle Activity

Muscle Activity Vs Time 500.00 450.00 400.00 350.00 300.00 250.00 200.00 150.00 100.00 50.00 0.00 14:15:22 14:16:05 14:16:48 14:17:31 14:18:14

Muscle Activity

Time

Figure 4.8 Muscle activity of biceps for movement 4 (Subject B).

43

Subject A Candy Tie Shi En First Movement (Triceps)

Muscle Activity Vs Time 500.00 Muscle Activity

400.00 300.00 200.00

Muscle Activity

100.00 0.00 15:25:55

15:26:38

15:27:22

15:28:05

Time

Figure 4.9 Muscle activity of triceps for movement 1 (Subject A).

Subject B Faiz Othman First Movement (Triceps)

Muscle Activity

Muscle Activity Vs Time 500.00 450.00 400.00 350.00 300.00 250.00 200.00 150.00 100.00 50.00 0.00 14:19:41

Muscle Activity

14:20:24

14:21:07

14:21:50

Time

Figure 4.10 Muscle activity of triceps for movement 1 (Subject B).

44

Subject A Candy Tie Shi En Second Movement (Triceps)

Muscle Activity

Muscle Activity Vs Time 500.00 450.00 400.00 350.00 300.00 250.00 200.00 150.00 100.00 50.00 0.00 15:30:14 15:30:58 15:31:41 15:32:24 15:33:07

Muscle Activity

Time

Figure 4.11 Muscle activity of triceps for movement 2 (Subject A).

Subject B Faiz Othman Second Movement (Triceps)

Muscle Activity Vs Time 450.00 400.00 Musle Activity

350.00 300.00 250.00 200.00

Muscle Activity

150.00 100.00 50.00 0.00 14:24:43

14:25:26

14:26:10

14:26:53

Time

Figure 4.12 Muscle activity of triceps for movement 2 (Subject B).

45

Subject A Candy Tie Shi En Third Movement (Triceps)

Muscle Activity Vs Time 300.00 Muscle Activity

250.00 200.00 150.00 Muscle Activity

100.00 50.00 0.00 15:35:17 15:36:00 15:36:43 15:37:26 15:38:10 Time

Figure 4.13 Muscle activity of triceps for movement 3 (Subject A).

Subject B Faiz Othman Third Movement (Triceps)

Muscle Activity Vs Time 600.00

Muscle Activity

500.00 400.00 300.00 Muscle Activity

200.00 100.00 0.00 14:29:46

14:30:29

14:31:12

14:31:55

Time

Figure 4.14 Muscle activity of triceps for movement 3 (Subject B).

46

Subject A Candy Tie Shi En Forth Movement (Triceps)

Muscle Activity Vs Time 600.00 Muscle Activity

500.00 400.00 300.00 Muscle Activity

200.00 100.00 0.00 15:40:19 15:41:02 15:41:46 15:42:29 15:43:12 Time

Figure 4.15 Muscle activity of triceps for movement 4 (Subject A).

Subject B Faiz Othman Forth Movement (Triceps)

Muscle Activity Vs Time 700.00

Muscle Activity

600.00 500.00 400.00 300.00

Muscle Activity

200.00 100.00 0.00 14:34:48

14:35:31

14:36:14

14:36:58

Time

Figure 4.16 Muscle activity of triceps for movement 4 (Subject B).

47

Based on the figures 4.1, 4.2, 4.3, 4.4, 4.5, 4.6, 4.7, 4.8, 4.9, 4.10, 4.11, 4.12, 4.13, 4.14, 4.15 and 4.16, it shows the relationship of the muscle activity versus time. For each of the movement, it took 15 seconds from the initial position to the final position and vice versa. Each movement is repeated 3 times. It was found that the biceps and triceps of the subjects relaxed while their upper limbs were at initial position. When the rehab robot moved from initial position to the final position, the biceps and triceps started to contract. Therefore, the graph was low at the initial as the muscles were relaxed. There was less muscle activity. The muscle activity increased gradually as the muscles contracted slowly. When the rehab robot moved from the final position to the initial position, the biceps and triceps started to relax and thus the muscle activity decreased. When the muscle activity decreased, the graph decreased as well. However, graphs didn’t show constant changes. The muscle activity fluctuated. It is because the muscle activities vary from time to time. Generally, when muscle relaxed, the muscle activity is low. The muscle activity is high when the muscle contracted. The maximum muscle activity recorded is 629 while the minimum is 32.

48

4.2 Limitations In this experiment, surface electrodes were used. Surface electrodes are able to provide only a limited assessment of the muscle activity. Surface EMG can be recorded by a pair of electrodes or by a more complex array of multiple electrodes. More than one electrode is needed because EMG recordings display the potential difference (voltage difference) between two separate electrodes. Limitations of this approach are the fact that surface electrode recordings are restricted to superficial muscles, are influenced by the depth of the subcutaneous tissue at the site of the recording which can be highly variable depending of the weight of a patient, and cannot reliably discriminate between the discharges of adjacent muscles. In order to get more accurate result, fine wire EMG sensor may be used. Surface electrodes places on shoulder muscles picked-up cross talks signals from neighbouring superficial muscles. The surface electrodes cannot accurately represent the activation patterns of deep shoulder muscles. The significance of the results obtained was difficult to be understood as it requires a consultation with a specialist regarding human muscles.

49

CHAPTER 5

CONCLUSION AND RECOMMENDATION

5.1 Introduction

This chapter concludes this research. The findings of this research were also been concluded. Recommendations were specified for future works.

5.2 Conclusion This research has been a success. All four movements; Z-Y, Z-Z, X-Y, X-X axis, of the human upper limb rehab robot had been performed by the subjects of the experiment. The experimental data which is the muscle activities of the subjects were obtained by the muscle sensor and displayed in the form of graph in Microsoft Excel file. The effect of the upper limb rehabilitation robotic device towards human upper limb muscles was analysed and determined. The muscle activities of the human upper limb vary when different movements are made. The value of muscle activity is low when the muscles relax and the value muscle activity increases when muscles contract.

50

5.3 Recommendation Based on the research that has been carried out, the results need to be improved using better electromyography (EMG) sensor which has higher sensitivity towards the muscle activity variation. The current muscle sensor used is the product from Advancer Technology. It rectifies the raw data obtained from the experiment conducted. It is recommended to use the muscle sensor which is not rectified one so that when obtaining the data, the data is raw and it will be better. Besides, while conducting the experiment, it is recommended to have advice from the doctor, who is the professional from medical field. A medical practitioner may understand more regarding the usage of the EMG sensor compared to researchers from engineering field. Fine wire electrodes are recommended to be used in obtaining the muscle activity. This is because fine wire electrodes can be manipulated while monitoring EMG activity and are suitable for clinical investigations. However, accurate placement of fine wire electrodes is more difficult than with surface EMG. They must hook into the desired muscle layer and cannot be repositioned once inserted. Once inserted fine wire electrodes are superior for prolonged and non-clinical investigations of muscle function because they are hooked in the muscle fibres and therefore move with the fibres ensuring that the recording area is the same. A deeper understanding of human anatomy is also important in conducting this research. The position and function of the muscles must be studied beforehand to easily analyse the results obtained. The anatomical terms of motion must be understood so that it would be easier to identify the movements involved by the upper limb rehab robot. Last but not least, it is important to know which muscles are going to be analyzed during the experiment. In this case, it is determined that biceps and triceps are suitable to be studied.

51

References Ada, L., Dorsch, S., & Canning, C. G. (2006). Strengthening interventions increase strength and improve activity after stroke: A systematic review. Australian Journal of Physiotherapy, 52(4), 241-248. Adams, H. P. J., (2007). Principles of cerebrovascular disease. New York: McGrawHill. Amirabdollahian, F., Driessen, B, Harwin, W., Loureiro, R., and Topping, M., (2003). Upper limb robot mediated stroke therapy—GENTLE/s approach. Autonomous Robots 15, 35–51. Archambault, P. S., Fung, J. & Nahid, N., (2012). Effects of robot-assisted therapy on stroke rehabilitation in upper limbs: Systematic review and meta-analysis of the literature. Journal of Rehabilitation Research and Development, 49(4), 479-496. Basmajian, J. V., & De Luca, C. J. (1985). Muscles alive. Muscles alive: their functions revealed by electromyography, 278, 126. Burgar, C. G., Lum, P. S., Shor, P. C., & Van der Loos, H. F. (2000). Development of robots for rehabilitation therapy: The Palo Alto VA/Stanford experience. Journal of Rehabilitation Research and Development, 663-673. Chang, W. H., & Kim, Y.-H. (2013). Robot-assisted therapy in stroke rehabilitation. Journal of Stroke, 15(3), 174. Cheng, X., Zhou, Y., Zuo, C., & Fan, X. (2012). Mechanical design and kinematic simulation of upper limb rehabilitation robot. Advances in Biomedical Engineering, 9, 37.

52

Colombo, R., Pisano, F., Micera, S., Mazzone, A., Delconte, C., Carrozza, M. C., ... & Minuco, G. (2005). Robotic techniques for upper limb evaluation and rehabilitation of stroke patients. IEEE transactions on neural systems and rehabilitation engineering, 13(3), 311-324. Coury, H. G., Kumar, S., & Narayan, Y. (1998). An electromyographic study of upper limb adduction force with varying shoulder and elbow postures. Journal of Electromyography and Kinesiology, 8(3), 157-168. Dombovy, M. L., Sandok, B. A., & Basford, J. R. (1986). Rehabilitation for stroke: A review. Stroke, 17(3), 363–369. Frumento, C., Messier, E., & Montero, V., (2010). History and future of rehabilitation robotics. Faculty of Worcester Polytechnic Institute. Fuglsang‐Frederiksen, A. (2000). The utility of interference pattern analysis.Muscle & nerve, 23(1), 18-36. Rash, G. S. (2002). Electromyography Fundamentals. Gait and Clinical Movement Analysis Society. Gopura, R. A. R. C., & Kiguchi, K. (2008). An exoskeleton robot for human forearm and wrist motion assist. Journal of Advanced Mechanical Design, Systems, and Manufacturing, 2(6), 1067-1083. Gupta, A., & O'Malley, M. K. (2006). Design of a haptic arm exoskeleton for training and rehabilitation. IEEE/ASME Transactions on mechatronics, 11(3), 280-289. Gurr, B. & Dendle, J. (2015). Assessment of stroke survivors on an inpatient rehabilitation unit. British Journal of Neuroscience Nursing, 11(4).

53

Ho, N. S. K., Tong, K. Y., Hu, X. L., Fung, K. L., Wei, X. J., Rong, W., & Susanto, E. A. (2011, June). An EMG-driven exoskeleton hand robotic training device on chronic stroke subjects: task training system for stroke rehabilitation. In 2011 IEEE international conference on rehabilitation robotics(pp. 1-5). IEEE. Kawamoto, H., & Sankai, Y. (2005). Power assist method based on phase sequence and muscle force condition for HAL. Advanced Robotics, 19(7), 717-734. Kiguchi, K. (2007). Active exoskeletons for upper-limb motion assist.International Journal of Humanoid Robotics, 4(03), 607-624. Krebs, H. I., Hogan, N., Aisen, M. L., & Volpe, B. T. (1998). Robot-aided neurorehabilitation. IEEE Transactions on Rehabilitation Engineering, 6(1), 7587. Kronberg, M., NÉMETH, G., & BROSTRÖM, L. A. (1990). Muscle activity and coordination in the normal shoulder: An electromyographic study. Clinical Orthopaedics and Related Research, 257, 76-85. Langhorne, P., Coupar, F., & Pollock, A. (2009). Motor recovery after stroke: A systematic review. The Lancet Neurology, 8(8), 741-754. Loureiro, R., Amirabdollahian, F., Topping, M., Driessen, B., & Harwin, W. (2003). Upper limb robot mediated stroke therapy—GENTLE/s approach. Autonomous Robots, 15(1), 35–51. Lum, P., Reinkensmeyer, D., Mahoney, R., Rymer, W. Z., & Burgar, C. (2002). Robotic devices for movement therapy after stroke: current status and challenges to clinical

acceptance.

Topics

in

Stroke

Rehabilitation,

http://doi.org/10.1310/9KFM-KF81-P9A4-5WW0 54

8(4),

40–53.

Maciejasz, P., Eschweiler, J., Gerlach-Hahn, K., Jansen-Troy, A., & Leonhardt, S. (2014). A survey on robotic devices for upper limb rehabilitation. Journal of neuroengineering and rehabilitation, 11(1), 1. Martini, F., Timmons, M. J. & Tallitsch, R. B. (1997). Human anatomy. New Jersey: Pearson Education, Inc. Micera, S., Sabatini, A. M., & Dario, P. (2000). On automatic identification of upperlimb movements using small-sized training sets of EMG signals. Medical Engineering & Physics, 22(8), 527-533. Miyasaka, H., Tomita, Y., Orand, A., Tanino, G., Takeda, K., Okamoto, S., & Sonoda, S. (2015). Robot-aided training for upper limbs of sub-acute stroke patients. Japanese Journal of Comprehensive Rehabilitation Science, 6(0), 27-32. Movements of the upper limb. (2002). Retrieved 19 October, 2016 from http://www.med.umich.edu/lrc/coursepages/m1/anatomy2010/html/modules/uppe r_limb_module/Module-UpperLimb.pdf. Murray, C. J., & Lopez, A. D. (1997). Mortality by cause for eight regions of the world: Global Burden of Disease Study. The lancet, 349(9061), 1269-1276. National Stroke Association of Malaysia. (n.d.-a). How Stroke Is Diagnosed? Retrieved December

10,

2015,

from

http://www.nasam.org/english/prevention

what_is_a_stroke.php National Stroke Association of Malaysia. (n.d.-b). What is stroke? Retrieved December 10, 2015, from http://www.stroke.org/understand-stroke/what-stroke

55

Prange, G. B. (2009). Stimulating restoration of arm function after stroke. Rehabiliation Robotics. Rash, G. S., & Quesada, P. M. (2003). Electromyography fundamentals.Retrieved February, 4. Rosen, J., Perry, J. C., Manning, N., Burns, S., & Hannaford, B. (2005, July). The human arm kinematics and dynamics during daily activities-toward a 7 DOF upper limb powered exoskeleton. In ICAR'05. Proceedings., 12th International Conference on Advanced Robotics, 2005. (pp. 532-539). IEEE. Rudroff, T., Enoka, J. A., Jordan, K., & Enoka, R. M. (2007c). Motor unit discharge rate declines when supporting an inertial load with the forearm supinated. Society for Neuroscience, 38th Annual Meeting. Sanders, D. B., Stålberg, E. V., & Nandedkar, S. D. (1996). Analysis of the electromyographic interference pattern. Journal of clinical neurophysiology,13(5), 385-400. Sasaki, D., Noritsugu, T., & Takaiwa, M. (2005). Development of active support splint driven by pneumatic soft actuator (ASSIST). In Proceedings of the 2005 IEEE International Conference on Robotics and Automation (pp. 520-525). IEEE. Soderberg, G. L., & Cook, T. M. (1984). Electromyography in biomechanics.Physical Therapy, 64(12), 1813-1820. Strong, K., Mathers, C., & Bonita, R. (2007). Preventing stroke: Saving lives around the world. The Lancet Neurology, 6(2), 182-187.

56

Tan, F. H., (2015). Design and fabrication of upper limb rehabilitation robotic device. Unpublished degree’s thesis, University of Malaysia Sarawak, Sarawak, Malaysia. Tong, R. K. Y., & Hu, X. (2008). Service robotics: Robot-assisted training for stroke rehabilitation. INTECH Open Access Publisher. Truelsen, T., & Bonita, R. (2008). The worldwide burden of stroke: Current status and future projections. Handbook of clinical neurology, 92, 327-336. Whittaker,

R.

G.

(2012).

The

fundamentals

of

electromyography. Practical

neurology, 12(3), 187-194. Wong, L. Z. (2014). Not enough occupational therapists in Malaysia. Retrieved from http://www.thestar.com.my/Lifestyle/Health/2014/10/16/Not-enoughoccupational-therapists-in-Malaysia/

57

APPENDIX

APPENDIX A CODING FOR ARDUINO

58

APPENDIX B MOVEMENTS OF SUBJECT A

Movement 1 (initial position)

Movement 1 (final position)

59

Movement 2 (initial position)

Movement 2 (final position)

60

Movement 3 (initial position)

Movement 3 (final position)

61

Movement 4 (initial position)

Movement 4 (final position)

62

MOVEMENTS OF SUBJECT B

Movement 1 (initial position)

Movement 1 (final position)

63

Movement 2 (initial position)

Movement 2 (final position)

64

Movement 3 (initial position)

Movement 3 (final position)

65

Movement 4 (initial position)

Movement 4 (final position)

66