NEW SENSOR DEVELOPMENT FOR BIONIC HAND
By
Billy Susantio 11601020
BACHELOR’S DEGREE in
MECHANICAL ENGINEERING – MECHATRONICS CONCENTRATION
ENGINEERING AND INFORMATION TECHNOLOGY
SWISS GERMAN UNIVERSITY The Prominence Tower
Jalan Jalur Sutera Barat No. 15, Alam Sutera Tangerang, Banten 15143 - Indonesia
July 2020
Revision after Thesis Defense on 14 July 2020
Billy Susantio STATEMENT BY THE AUTHOR
I hereby declare that this submission is my own work and to the best of my knowledge, it contains no material previously published or written by another person, nor material which to a substantial extent has been accepted for the award of any other degree or diploma at any educational institution, except where due acknowledgement is made in the thesis.
Billy Susantio
Student Date
Approved by:
Dr. Eka Budiarto, S.T., M.Sc.
Thesis Advisor Date
Erikson F. Sinaga, S.T., M.Kom.
Thesis Co-Advisor Date
Maulahikmah Galinium, S.Kom, M.Sc, PhD
Dean Date
ABSTRACT
NEW SENSOR DEVELOPMENT FOR BIONIC HAND
By
Billy Susantio
Dr. Eka Budiarto, S.T., M.Sc.
Erikson F. Sinaga, S.T., M.Kom. SWISS GERMAN UNIVERSITY
In Indonesia it is uncommon for Bionic Hand to be used for amputees. The biggest hurdle to be faced is the relatively expensive price that starts from USD 3000 made by Open Bionics. Not to mention, that does not include the retail price and the shipment, which means it will be a lot more expensive when it arrives in Indonesia. And so, one of the objectives of this project is to overcome that hurdle by creating a bionic arm that’s affordable for Indonesia’s market. Though it’s cheap, it’s important to maintain the quality standards. Another goal is to make the bionic hand lighter, more compact, and more reliable than the previous generation while keeping the price affordable. The main focus of this paper is to make a new sensor for the bionic hand that’s reliable, compact, and cost-effective. The signal of the muscle movement is sensed by electromyography (EMG) sensor, which is then conditioned through a module, and finally into the Arduino. In the Arduino, there will be further signal and data processing by using algorithm.
This data is to be interpreted as different hand gestures, which is then initiates the servo motor to move the bionic arm.
Billy Susantio
© Copyright 2020 by Billy Susantio All rights reserved
DEDICATION
I dedicate this work for God, my family, my girlfriend, and my best friends who believe in me, the future of amputees and the sake of the future of my country, Indonesia.
Billy Susantio ACKNOWLEDGEMENTS
First and foremost, I want to express my gratitude to the one and only God Himself, as he never fails to give me His blessings and guidance in each and every day.
I want to thank my family for all the endless support. I want to thank lecturers who have guided me, Mr. Eka Budiarto, Mr. Erikson Sinaga, Mr. Rusman Rusyadi, Mr. Boris, Mr. Benny Widjaja, Ms. Yunita Umniyati, Mr. Leonard Rusli, and other lecturers.
I want to thank Elizabeth Vanessa for supporting me through ups and downs. And to all of my friends who believed in me. To Group WA Keluarga, Daniel Alvin, Audrey Satriajaya,
Agustinus Pratama, Andrian Marcello, Heverett Louiscious, Einser Nahiman, Radya, Ivan Goldy, Alvin Tri Hartono, Deo Marcellino who travelled this journey with me.
TABLE OF CONTENTS
Page
STATEMENT BY THE AUTHOR ... 2
ABSTRACT ... 3
DEDICATION ... 5
ACKNOWLEDGEMENTS ... 6
TABLE OF CONTENTS ... 7
LIST OF FIGURES ... 9
CHAPTER 1 - INTRODUCTION ... 11
1.1 Background ... 11
1.2 Research Problems ... 12
1.3 Research Objectives ... 12
1.4 Significance of Study ... 12
1.5 Research Questions ... 12
1.6 Hypothesis... 13
CHAPTER 2 – LITERATURE REVIEW ... 14
2.1 CNT-coated Thread for Mechamnomyography... 14
2.2 Prototyping of EMG-Controlled Prosthetic Hand with Sensory System... 14
2.3 Myoelectric Bionic Hand ... 14
2.4 Bionic Hand Mechanics ... 15
2.5 EMG Sensor ... 16
2.6 Extensor and Flexor Muscle for EMG ... 17
CHAPTER 3 – RESEARCH METHODS ... 18
3.1 Design Justification ... 18
3.1.1 General Overview ... 18
3.1.2 Comparison and Considerations ... 19
3.1.2.1 Mechanomyography (MMG) ... 19
3.1.2.2 Electromyography (EMG) ... 21
3.1.2.3 Arduino ... 22
Billy Susantio
3.1.2.5 Sleeve ... 23
3.1.2.6 The Final Verdict ... 23
3.2. Components of Design ... 24
3.2.1 Electrical Components ... 24
3.2.2 Software and Algorithm ... 29
3.2.3 Price of the Electrical Components... 31
CHAPTER 4 – RESULTS AND DISCUSSIONS... 32
4.1. Sleeve and Components Improvement ... 32
4.1.1 Outer Sleeve ... 32
4.1.2 Inner Sleeve ... 33
4.1.3 Battery ... 34
4.2. Performance Test ... 35
4.2.1 Simple Bicep Flexing Test ... 35
4.2.2 4 Gestures Test ... 37
4.2.2.1. Gesture Test for Young, Male, Pre-workout... 37
4.2.2.2. Gesture Test for Young, Female, Pre-workout ... 37
4.2.2.3. Gesture Test for Young, Old, Male, Female, Post-workout... 41
4.2.2.4. Gesture Test for moving Young, Male, Pre-workout ... 42
4.3. Algorithm ... 42
4.3.1 Constructing an Algorithm Based on the Data Above... 42
4.3.2 Testing the Algorithm ... 45
4.4. Synchronization ... 47
4.4.1 Synchronization Algorithm ... 48
CHAPTER 5 - CONCLUSION AND RECOMMENDATION 5.1. Conclusion ... 49
5.2. Recommendation ... 49
REFERENCES ... 51
LIST OF FIGURES
Figures Page
2.1. Myoelectric Hand... 15
2.2. Screw and Ball Nut Mechanism ... 16
2.3. Extensor and Flexor Muscle for EMG ... 18
3.1. General connections of the bionic hand sensor ... 19
3.2. Mechanomyography ... 20
3.3. Mechanomyography simple muscle contraction data from James Alan ... 20
3.4. Electromyography ... 21
3.5. Arduino ... 22
3.6. Raspberry Pi ... 23
3.7. Conductive fabric ... 23
3.8. Surface EMG electrode pad ... 23
3.9. EMG muscle sensor module v3.0 with cable... 24
3.10. Graph of muscle activities signal conditioning ... 25
3.11. Detailed connections of the bionic hand sensor ... 25
3.12. AD8226 ... 27
3.13. TL084 ... 28
3.14. Arduino Nano... 28
3.15. Electrical Diagram ... 29
3.16. Logic Flowchart ... 30
4.1. Bionic Hand of the Previous Generation ... 32
4.2. The New Half-Shell Design ... 33
4.3. Kuangmi Rubber Sleeve ... 33
4.4. Inner Sleeve with Velcro/Strap Mechanism ... 34
4.5. Using Half-Shell and Velcro Sleeve ... 34
4.6. 11.1 V, 2200 mAh Lithium Polymer Battery ... 35
4.7. 14.8 V, 2200 mAh Lithium Polymer Battery ... 35
4.8. Analog input data of simple muscle contraction ... 36
4.9. Graph of a simple muscle contraction ... 37
Billy Susantio
4.10. Gesture Test for Young, Male, Pre-workout ... 38
4.11. Cronbach’s Alpha Test for Young, Male, Pre-Workout Gesture Test ... 39
4.12. The Pattern for 4 Gestures ... 40
4.13. Gestures Test for Young, Female, Pre-workout ... 40
4.14. Gestures Test for Young, Old, Male, Female, Post-workout... 41
4.15. Gestures Test for moving Young, Male, Pre-workout ... 42
4.16. Algorithm Snippet of Using Percentage Difference for Gesture Recognition ... 44
4.17. Algorithm Snippet of Taking the Origin EMG Value ... 44
4.18. Algorithm Snippet of Percentage Difference Calculation ... 44
4.19. Normal Gesture ... 45
4.20. Fist Gesture ... 46
4.21. Up Gesture ... 46
4.22. Down Gesture ... 47
4.23. Synchronization of Bionic Hand and Bionic Sleeve... 47
4.24. Synchronization of Bionic Hand and Bionic Sleeve... 48
