Ijraset Journal For Research in Applied Science and Engineering Technology
Authors: Shreya Dave, Dr. Bhavna Ambudkar, Neelum Dave
DOI Link: https://doi.org/10.22214/ijraset.2022.43448
Certificate: View Certificate
People in today’s world thrive on perfection and performance, which leads to an increase in stress. The damage caused by stress is often underrated. An increase in stress affects our mental health and can lead to various long-term physical implications. These include diabetes, high blood pressure, headache, weak immune system, and many others It is a social phenomenon that needs to be monitored closely. Thus, it is necessary to detect stress in early-stage and take measures to reduce it. In our study, we aim to detect stress using brainwaves.
I. INTRODUCTION
Whenever the body responds to any kind of excessive demand, it experiences stress[4]. It can be caused by both good and bad experiences. It is the feeling of emotional or physical tension. Any event that makes you feel angry, nervous or frustrated can lead to stress. When stress is for short durations, it can be positive, such as when helps you meet deadlines or avoid danger. Stress when present for a longer duration can be harmful to your health.
There are two main types of stress:
When you have chronic stress, your body stays alert, even though there is no danger. Over time, this puts you at risk for health problems, including:
High blood pressure, Heart disease, Diabetes, Obesity, Depression or anxiety, Skin problems, such as acne or eczema, Menstrual problems
II. MOTIVATION
According to researchers, a feeling of strain, and pressure in the human body is stress. While acute stress can be helpful as it may motivate us to complete our work in a given period of time but chronic stress may lead to serious health disorders. If this condition is not noticed it may have serious effects on the body[5]. When any person is under stress, the human body releases stress hormones called adrenaline and cortisol. This makes our heartbeats run at a faster rate. Other changes in humans are body tightening up and blood pressure rising also there can be trouble in breathing. Many Cardiovascular diseases are caused by a prolonged effect of stress on our body[9].
III. DETECTION OF STRESS
There are various ways to detect stress in our bodies.An electrocardiogram is one of the ways to measure stress. In this method, Heart Rate Variability is measured. The features Extracted from it help us identify the stress of a person.[9] Another great way to detect stress is using facial expressions. The human face is very expressive. Using Image Processing, Emotions can be detected, indicating whether a person is angry, sad, happy or depressed. These features can further be extracted to predict the stress level.[11]
Apart from this galvanic skin response is also an efficient way to measure Stress.[18]
The human brain is a complex circuit of neurons. All neurons communicate with each other using electrical signals. These Signals can be measured using an electroencephalograph. These signals received from EEG are known as brainwaves. Stress can be detected by the measurement of the frequency of brainwaves. Brain wave is a generic term used to refer to the electrical impulses generated by the neurons or during the interaction between them.[3] These impulses are observed by a measuring technique called an Electroencephalogram (EEG).
The EEG (electroencephalograph) measures brainwaves of different frequencies within the brain. Electrodes are placed on specific sites on the scalp to detect and record the electrical impulses within the brain. A frequency is the number of times a wave repeats itself within a second.
The raw EEG has usually been described in terms of frequency bands
IV. METHODOLOGY
EEG Click is a board that allows monitoring of Brainwaves. It is equipped with high sensitivity circuit that amplifies even the faintest electrical signals from the brain, allowing them to be sampled by the host MCU. In our project, we have taken Arduino as our Host MCU.
INA114 on the chip provides gain up to 10000. It provides low noise, LASER trimmed offset voltage, and a very good common rejection ratio. The gain on EEG Click is set about 12 times. Further, MCP6909 offers more amplification and filtering.
EEG click board provides an easy and cheaper solution to measure brainwaves compared to other solutions present in the market. The board is compact and compatible with multiple host MCUs such as ARM processors, PIC processors, Arduino, and Raspberry Pi.
Steps to collect the Data:
Step 1: Connect Click Board to Arduino using the Arduino shield.
Step 2: Attach the USB cable to the machine and turn on MATLAB.
Step 3: Run the code to start plotting the brain waves in real-time.
Step 4: Find the Power Spectral Density of the EEG Data Collected to find the frequency of the signal.
Step 5: Based on the frequency calculated, identify whether the Subject is stressed or not.
Step 6: Store the data file for future reference as a text file or CSV file using MATLAB.
Calculation of Power Spectral Density to determine the Frequency of Signal is done as follows:
V. EXPERIMENTAL RESULT
For our experiment, we collected the brainwave of 30 people: Staff Members and Students from Dr. D. Y. Patil Institute of Technology. The Brainwaves were measured before the viva exam began and after the exam ended. They were recorded for an average time of 120 seconds.
Sr.No. |
Profession |
Age |
Frequency Before Viva |
Frequency After Viva |
1 |
Professor |
39 |
16.13Hz |
12.26Hz |
2 |
Student |
20 |
13.86Hz |
9.44Hz |
3 |
Student |
21 |
10.82Hz |
11.38Hz |
4 |
Student |
21 |
10.73Hz |
11.61Hz |
5 |
Student |
21 |
11.053Hz |
8.23Hz |
6 |
Professor |
43 |
15.59Hz |
12.69Hz |
7 |
Professor |
39 |
12.97Hz |
11.86Hz |
8 |
Student |
21 |
10.81Hz |
8.43Hz |
9 |
Student |
21 |
11.54Hz |
11.29Hz |
10 |
Student |
20 |
10.97Hz |
11.16Hz |
11 |
Student |
20 |
11.33Hz |
10.30Hz |
12 |
Student |
21 |
12.73Hz |
12.08Hz |
13 |
Student |
21 |
17.62Hz |
11.95Hz |
14 |
Student |
19 |
18.66Hz |
15.24Hz |
16 |
Student |
19 |
12.73Hz |
13.24Hz |
17 |
Student |
21 |
10.49Hz |
10.4737 |
18 |
Student |
20 |
13.45Hz |
12.69Hz |
19 |
Professor |
47 |
10.45Hz |
11.03Hz |
20 |
Student |
21 |
18.23Hz |
12.55Hz |
21 |
Student |
22 |
17.68Hz |
14Hz |
22 |
Student |
21 |
15.24Hz |
12.53Hz |
23 |
Student |
20 |
14.652Hz |
13.34Hz |
24 |
Student |
20 |
11.42Hz |
12.83Hz |
25 |
Student |
20 |
13.28Hz |
12.58Hz |
26 |
Student |
21 |
12.72Hz |
12.05Hz |
27 |
Professor |
44 |
10.49Hz |
10.25Hz |
28 |
Student |
21 |
15.463Hz |
13.25Hz |
29 |
Student |
21 |
12.263Hz |
11.57Hz |
30 |
Student |
20 |
9.335Hz |
10.386Hz |
Table: Data Collected
It was noticed that for most of the subjects the brainwave frequency was reduced after the viva indicating that they were more relaxed after the exam thus the stress levels were reduced.
This paper proposes an automated system for stress detection using EEG signals. The frequency of Brainwave is detected using Power Spectral Density which a simple and robust. It has been noticed that once the stressful situation, in this case, an exam, is overcome the stress level automatically reduces. Stress can be relieved in various ways such as through Music Therapy, Yoga, Meditation, Exercise, Art, Reading, and so on. In the future Stress reduction using music can also be implemented using machine learning and deep learning technique-based recommender systems.
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Copyright © 2022 Shreya Dave, Dr. Bhavna Ambudkar, Neelum Dave. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Paper Id : IJRASET43448
Publish Date : 2022-05-27
ISSN : 2321-9653
Publisher Name : IJRASET
DOI Link : Click Here