MICROCONTROLLER-BASED HUMAN STRESS DETECTION SYSTEM USING FUZZY LOGIC
AWAIS GUL AIRIJ
A project report submitted in partial fulfilment of the requirements for the award of the degree of
Master of Engineering (Electronics & Telecommunication)
Faculty of Electrical Engineering Universiti Teknologi Malaysia
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DEDICATION
Gratefully dedicated to my family, my mentor and friends. I couldn’t have completed this without you all. Thank you for your love, support and guidance.
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ACKNOWLEDGEMENT
I am indeed grateful to Almighty ALLAH for providing me the opportunity and strength to commence and conclude my Master of Engineering at Universiti Teknologi Malaysia.
It is a great pleasure to express my heart-felt gratitude to my supervisor Dr Shaikh Nasir Bin Shaikh Husin for his inspirational guidance, kind supervision and comprehensive advice throughout the duration of my work.
I wish to express my deepest appreciation to my previous supervisor Dr Rabia Bakhteri. The present work would not have been possible without her encouragement and support. I thank Dr Rabia Bakhteri for her detailed and insightful feedback, which helped me shape this research. It was a great honour to work under her supervision for nine months. However, she had to move to Canada for some reason and she could not help me complete this research under her supervision.
Finally, I would like to thank my father Muhammad Yaqoob Memon, my brother Naeem Aziz Memon along with my other family members and friends for their encouragement throughout my work. I would not have been able to complete this without them. I also would like to appreciate all those who have helped me directly or indirectly towards the completion of this project.
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ABSTRACT
This research presents a working prototype of human stress detection device capable of measuring human stress level perhaps also for autistic children. The device records human physiological signals in order to determine the mental stress level. High stress levels may be dangerous especially for certain individuals such as autistic children who are unable to express mounting levels of stress. The autistic children can have frequent tantrums and seizure activities without any visible signs or symptoms, making this device a useful tool for parents and doctors to anticipate any harmful behaviours of autism. This research focuses on the hardware and software development of a low cost microcontroller-based stress detection system prototype. The prototype was designed using Arduino Mega platform and tested with 35 clinical patients. The data from two sensors is fed to the microcontroller using its two analog input pins and the sensor data is sent to the fuzzy logic module which is pre-programmed into the microcontroller for further processing. The output of the prototype is displayed on the LCD module connected to five digital pins of the microcontroller. In addition, three LEDs are connected to three digital pins of the microcontroller which light up in accordance with the stress levels. In order to test the developed system, an experiment was designed which requires subjects to perform mental calculations to solve arithmetic problems. The experiment involves three phases: low stress phase (P-1), medium stress phase (P-2) and high stress phase (P-3). The results showed that the prototype measures the stress levels with high degree of accuracy and efficiency. Apart from that, the results also highlighted that the stress neither depends on age nor gender.
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ABSTRAK
Kajian ini membentangkan prototaip alat pengesan tekanan minda manusia yang digunakan untuk mengukur tahap tekanan manusia dan juga untuk kanak-kanak autistik. Peranti berfungsi untuk merakam isyarat fisiologi manusia bagi menentukan kadar tekanan. Tahap tekanan yang tinggi mungkin berbahaya terutamanya untuk individu tertentu seperti kanak-kanak autistik dimana mereka tidak mampu untuk menyatakan dengan jelas perasaan atau tekanan yang dihadapi. Kanak-kanak autistik boleh mempunyai tantrum yang kerap dan bersikap agresif secara drastik tanpa sebarang tanda yang boleh dikesan dengan awal, menjadikan peranti ini alat yang berguna untuk ibu bapa dan doktor untuk menjangka tingkah laku yang berbahaya dari penghidap autisme. Kajian ini memberi tumpuan kepada pembangunan perkakasan dan perisian mikropengawal kos rendah berasaskan prototaip sistem pengesan tekanan. Prototaip ini telah direka menggunakan platform ‘Arduino Mega’ dan kemudian diuji dengan 35 orang pesakit klinikal. Data daripada dua sensor disalurkan ke mikropengawal dengan menggunakan dua pin input analog dan data tersebut dihantar ke modul logik kabur (Fuzzy Logic) yang telah diprogramkan dalam mikropengawal untuk proses seterusnya. Output prototaip ini dipaparkan pada modul paparan kristal cecair (LCD) yang disambungkan dengan lima pin digital mikropengawal. Di samping itu, tiga diod pemancar cahaya (LED) disambungkan kepada tiga pin digital mikropengawal yang menyala mengikut tahap tekanan. Bagi menguji prototaip yang dibangunkan, pesakit dikehendaki menyelesaikan masalah aritmetik dengan melakukan teknik pengiraan secara mental atau congak. Eksperimen ini melibatkan tiga fasa iaitu fasa tekanan rendah (P-1), fasa tekanan sederhana (P-2) dan fasa tekanan tinggi (P-3). Keputusan menunjukkan bahawa tahap tekanan dapat diukur dengan tepat dan cekap. Selain itu, kajian ini merumuskan bahawa tekanan tidak bergantung kepada umur atau jantina.
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TABLE OF CONTENTS
CHAPTER TITLE PAGE
DECLARATION ii
DEDICATION iii
ACKNOWLEDGEMENT iv
ABSTRACT v
ABSTRAK vi
TABLE OF CONTENTS vii
LIST OF TABLES x
LIST OF FIGURES xi
LIST OF ABBREVIATIONS xiii
LIST OF APPENDICES xiv
1 INTRODUCTION 1 1.1 Project Background 1 1.2 Problem Statement 2 1.3 Research Objectives 3 1.4 Research Scope 3 1.5 Research Contributions 3 1.6 Thesis Organization 3 2 LITERATURE REVIEW 5 2.1 Introduction 5 2.2 Project Background 5
2.2.1 Case Studies on Autism Spectrum Disorder 6
2.3 Types of Stress 7
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2.3.2 Episodic Acute Stress 7
2.3.3 Chronic Stress 8
2.4 Sensors/Devices 8
2.4.1 Galvanic Skin Response Sensor 8
2.4.2 Pulse Sensor/Blood Volume Pulse 9
2.4.3 Temperature Sensor 9
2.4.4 ASL 504 Eye Gaze Tracker 10
2.4.5 Peizoelectric Film Sensor 10
2.4.6 Accelerometer 11
2.4.7 EEG Sensor 11
2.4.8 Force Sensor 12
2.5 Artificial Intelligence 12
2.5.1 Fuzzy Logic 12
2.5.2 Bayes Net Classifier 13
2.5.3 Support Vector Machine 13
2.5.4 Decision Tree 14
2.6 Related Literature 14
3 RESEARCH METHODOLOGY 17
3.1 Introduction 17
3.2 Sensors 18
3.2.1 Working Principle of Heartbeat / Pulse Sensor 19 3.2.2 Working Principle of Galvanic Skin Response Sensor 19
3.3 LCD Module 20
3.4 Arduino Mega Board 20
3.5 Indicator 21
3.6 Moving Average 21
3.7 Decision-Making Module 22
3.8 Data Collection 23
4 HARDWARE DESIGN 24
4.1 Interfacing Pulse Sensor with Arduino 24 4.2 Interfacing GSR Sensor with Arduino 25 4.3 Interfacing LCD Module with Arduino 27
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4.4 Arduino Pinouts 28
4.5 Fuzzy Logic Module with Arduino 29
4.5.1 Fuzzy Logic Rules 29
4.5.2 Membership Function 29
4.6 Final Prototype 31
5 RESULTS AND DISCUSSION 32
5.1 Results 33
5.2 Discussion 34
6 CONCLUSION AND FUTURE RECOMMENDATIONS 36
6.1 Conclusion 36
6.2 Future Recommendations 36
REFERENCES 37
x
LIST OF TABLES
TABLE NO. TITLE PAGE
2.1 Summary of literature review 16
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LIST OF FIGURES
FIGURE NO. TITLE PAGE
1.1 2.1 2.2 2.3 2.4 2.5 2.6 2.7 2.8 2.9 3.1 3.2 3.3 3.4 3.5 3.6 4.1 4.2 4.3 4.4 4.5
Stress Response to a Stressor (stimuli)
The reaction of stress factors is governed by ANS GSR sensor
Pulse sensor
Temperature sensor ASL eye gaze tracker
Piezo-electric film sensor
Accelerometer
Device to record brain waves Force-sensing resistor
System architecture Project flowchart
Working principle of photoplethysmography Arduino Mega board
LEDs as indicators Fuzzy decision-making
Heart rate (pulse) sensor by pulsesensor.com Testing heart rate sensor with Arduino Grove GSR sensor
Testing grove GSR sensor with Arduino 48x84 graphic LCD module 1 6 8 9 9 10 10 11 11 12 17 18 19 21 21 22 24 25 26 26 27
xii 4.6 4.7 4.8 4.9 4.10 5.1 5.2 5.3 5.4
Pin connections between Arduino & LCD module Membership function curve (trapezoidal) for low stress Membership function curve (trapezoidal) for med stress Membership function curve (trapezoidal) for high stress Final prototype of stress detection system
Working of human SDS prototype Stress levels in males for all three phases Stress levels in females for all three phases
Testing of LM35 temperature sensor with Arduino
28 30 30 30 31 32 33 34 35
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LIST OF ABBREVIATIONS
ANS - Autonomic Nervous System ASD - Autism Spectrum Disorder BVP - Blood Volume Pulse ECG - Electrocardiography EEG - Electroencephalography
eFLL - Embedded Fuzzy Logic Library FLM - Fuzzy Logic Module
GSR - Galvanic Skin Response LCD - Liquid Crystal Display MRI - Magnetic Resonance Imaging
PPG - Photoplethysmography
REI - Rhythmic Entertainment Intervention
SC - Skin Conductance
SDS - Stress Detection System SVM - Support Vector Machine
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LIST OF APPENDIX
APPENDIX TITLE PAGE
A Arduino Code for Stress Detection System 63
CHAPTER 1
INTRODUCTION
The present research aims at developing a working prototype in order to detect stress by using Arduino Mega. The device makes use of human physiological signals measured with the help of various electronic sensors, along with a fuzzy logic decision-making system to calculate the stress levels accurately.
1.1 Project Background
The term “stress” basically refers to the physical reaction of a person in response to an unpleasant/dangerous environmental condition or stimuli [1] as shown in figure 1.1. Over-stress has proven to be one of the major factors contributing to several serious health problems such as high blood pressure, hypertension, cardiovascular diseases and panic attacks [2].
Figure 1.1: Stress response to a stressor (stimuli)
According to a research, stress is categorized into three types namely; acute stress, episodic acute stress and chronic stress [3]. Acute stress and episodic acute stress do not cause much damage as they are for a short period making people anxious and frightened but are easily treatable [3]. However, on the other hand, the
2 chronic stress lasts longer and causes serious complications depending upon the type of patients [4, 5]. As a result of stress, stress-response hormones such as epinephrine, norepinephrine and cortisol are secreted which can be a contributing factor in cardiac abnormalities[5] along with some other serious complications. Moreover, high levels of stress can cause commonly known mental disorders namely; depression and anxiety[4].
The system proposed in this project can non-invasively detect stress levels in humans through some physiological signals such as skin conductance, temperature, heart rate and blood pressure measured with the help of various electronic sensors.
1.2 Problem Statement
Nowadays, everybody is stressed, however, the type of stress dealt within the very research and complications caused by it are limited to a specific group of people. The children suffering from Autism Spectrum Disorder (ASD) are the focus of study. According to a research, every 1 in 166 births suffers from ASD [6]. Autistic children can have seizures, panic attacks, suicide thoughts, commit homicide and can also be harmful to their surroundings when they are under stress. But there are no visible signs or warnings when under high stress.
Currently, low cost commercial device for detecting stress is not available. Nonetheless, devices to monitor temperature, heart rate and variations in respiration exist. Furthermore, even such high-end devices are devoid of detecting stress on their own. For instance heart rate variation alone is incapable of detecting stress. There is a dire need for a stand-alone device that can detect stress by using a couple of physiological signals and process them further in order to decide whether the person is under stress or not. Such device will possibly help the parents and doctors to anticipate harmful behaviours of autism.
3 1.3 Research Objective
The objectives of this research are:
1) To study the fuzzy logic and familiarize with embedded fuzzy logic library (eFLL) for Arduino.
2) To interface electronic sensors with Arduino Mega board.
3) To measure physiological signals accurately using electronic sensors. 4) To develop a prototype of human stress detection system.
5) To test the prototype functionality on intended subjects.
1.4 Research Scope
The scope of this research covers development of a human stress detection system prototype consisting of Arduino Mega 2560 microcontroller board, LCD display, pulse sensor, grove GSR sensor and LEDs as indicators. AtMega2560 microcontroller is the main processing unit for the entire system and is programmed using Arduino IDE.
1.5 Research Contributions
Prior research has shown various approaches of stress detection but unfortunately, there is no device available till today which is accurate and low cost. This research aims to develop a prototype of human stress detection system which is capable of accurate measurement of human stress levels at a very low cost.
1.6 Thesis Organization
This thesis consists of six chapters. The first chapter discusses the background, problem statement, intended objectives and the scope of this research.
4 Chapter 2 includes the literature review focused on techniques, experimental setup, results and drawbacks found in previously built devices for stress detection purpose. In chapter 3, the working principles of the sensors and other components are discussed. Later in chapter 4 the design of the system is discussed in terms of interfacing the sensors, designing output display along with an indicator and designing of the fuzzy logic system. The next chapter presents the results obtained from the developed stress detection prototype and discussion on the results. The problems and challenges faced during this research are also included in chapter 5. Finally, a conclusion of the entire research and some recommendations for future improvements are given in chapter 6.
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REFERENCES
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