The document presents the development of a low-cost PC-based single-channel EEG monitoring system. It aims to design an analog circuit to reliably record electrical brain activity using affordable electrodes and provide raw EEG data for research purposes. The proposed system uses a combination of filters, an instrumentation amplifier, and Arduino for ADC to process EEG signals in the range of 10-100μV. The total cost is about 2071.5 Tk compared to commercial devices that cost over 8000 Tk with additional licensing fees, making raw data accessible for research more affordable.

1. Development of a Low-
cost PC-based Single-
channel EEG Monitoring
System
 Presented by
1

2. Outline
 Introduction
Motivation and Objectives
Electro-Encephalography(EEG) Basics
 Proposed System Design
 Hardware Implementation
 Signal Analysis
 Performance Evaluation
 Limitations
 Conclusion
 Future work
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3. Motivatio
n
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Motivation:
• EEG(Emotive) device is available to diagnose
disease which is very expensive (around
$799).
• Available EEG(emotive) devices are not easily
affordable for research purpose.
• Raw data of these commercial devices are not
available for everyone. A license is required to
access the data which costs around $100(1
year subscription).
Objectives:
• Design an analog circuit to reliably record the
electrical activity of our brain using Ag/AgCl
electrodes.
• Detect different types of signal so that it can
be used for further research.
Goal:
To provide a user friendly EEG device
with raw data for research purpose at an
affordable price.

4. 4
Challenges
 Low Amplitude: Brain
signal has very low
amplitude(10uV-100uV).
 Low SNR: The signal is
submerged under the
noise. We have to extract
the signal from the ocean
of noise.
 Need to design a very
robust system because
here we are dealing with
very low amplitude and
our filter should be perfect
to capture noise free data.

5. Electro-Encephalography(EEG)
What is EEG?
• An Electroencephalogram (EEG) is a
noninvasive test that records electrical
patterns in your brain.
• The test is used to help diagnose conditions
such as seizures, epilepsy, head injuries,
dizziness, headaches, brain tumors and
sleeping problems. It can also be used to
confirm brain death.
Signal Properties :
• Amplitude range: 10 µV to 100 µV in
amplitude when measured from the
scalp and 10–20 mV when measured
from subdural electrodes
• Frequency range: 0.1 Hz to more than
100 Hz
• Maximum Usable Energy: 1Hz to 20Hz
5

6. 6
Brain Waves
Band Frequency (Hz)
Delta < 4
Theta ≥ 4 and < 8
Alpha ≥ 8 and < 14
Beta ≥ 14
Gamma 30-100

7. OpenBCI :
US Price (as of
January
2017):
4 channels:
$200
8 channels:
$500
16 channels:
Muse :
US Price
(as of
January
2017):
$200
Emotiv Epoc
:
14 channels
US Price (as
of January
2017): $800
Emotiv Insight:
5 channels
US Price (as of
January 2017):
$300
Neurosky Mindwave :
1 channel
US Price (as of January
2017): $100
Comparison of Existing Devices
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8. Low Pass
Filter
(4th Order)
Clamper
Instrumentation
Amplifier
AD620
High Pass
Filter
(4th Order)
Non-
Inverting
Amplifier
Non-
Inverting
Amplifier
50 Hz
Twin-T Notch
Filter
Arduino
10bit_ADC
Proposed System8

9. Combinations Vin Frequency Vout
Notch_HPF_LPF 100uV 10Hz 4.3mV
100uV 50Hz 1.9mV
HPF_Notch_LPF 100uV 10Hz 4.45mV
100uV 50Hz 0.1mV
LPF_HPF_Notch 100uV 10Hz 4.5mV
100uV 50Hz 2.1mV
HPF_LPF_Notch 100uV 10Hz 4.5mV
100uV 50Hz 0.7mV
LPF_Notch_HPF 100uV 10Hz 4.5mV
100uV 50Hz 0.28mV
Notch_LPF_HPF 100uV 10Hz 2.15mV
100uV 50Hz 0.15mV
Combinations of Filters(With AD620)
Filter combinations
that could be used
for proper noise-free
data. We used
HPF_LPF_NOTCH
filter combination.
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10. Electrodes
 Electrodes made of
Ag/AgCl.
 Permits electron
conduction from the skin
to the wire.
 The connectors of these
electrodes have three
conductor sensor cable
with electrode pad leads.
 Using electrolytic gel
between skin and
electrode can reduce
electrode impedance.
 Multi-useable electrodes,
positive, negative and
ground, to the
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11. Constant 5V DC Supply
• To provide constant 5V
and protect circuit IC
components.
• Two boost modules are
used to boost the 4.7V.
• A switch is used to
on/off the voltage
supply and two charger
module to charge the
battery.
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12. Instrumentation Amplifier
• Low cost, high accuracy with high input
impedance, low DC offset, low noise
and very high open-loop gain.
• High CMRR: >100dB
• Gain = 1+
49.4𝑘𝞨
100
= 501
• Takes the difference between two
electrodes and amplify it by removing
common-mode noise.
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13. • Remove low frequency noise
interference.
• Cutoff Frequency:
1
2π𝑅𝐶
=
.4897Hz
• Order of filter: 4th order
• Gain: Unity
• Output: Non inverted
Active High Pass Filter
(Calculation & Simulation Result)13

14. Frequency
(Hz)
Input(V) Output(V)
0.04 3.12 0.24
0.21 3.12 0.16
0.37 3.12 0.24
0.469 3.12 0.4
0.518 3.12 0.48
0.667 3.12 0.96
0.719 3.12 1.2
0.869 3.12 1.68
0.924 3.12 1.76
0.993 3.12 1.84
0.998 3.12 2.16
3 3.12 2.8
5 3.12 2.96
10 3.12 3.12
15 3.12 3.2
20 3.12 3.2
25 3.12 3.04
30 3.12 3.04
35 3.12 3.12
40 3.12 3.04
45 3.12 2.48
50 3.12 2.48
55 3.12 2.56
Active High Pass
Filter
(Practical Data)
14

15. • Remove high frequency noise
interference.
• Cutoff Frequency:
1
2π𝑅𝐶
=
35.54 Hz
• Order of filter: 4th order
• Gain: Unity
• Output: Non inverted
Active Low Pass Filter
(Calculation & Simulation)15

16. Frequency(Hz) Input(V) Output(V)
1 4.12 4.12
5 4.12 4.04
10 4.12 4.04
15 4.12 3.92
20 4.12 3.84
22 4.12 3.72
25 4.12 3.52
27 4.12 3.36
30 4.12 3.04
33 4.12 2.76
35 4.12 2.4
40 4.12 1.88
45 4.12 1.48
50 4.12 1.24
70 4.12 0.6
100 4.12 0.36
Active Low Pass Filter
(Practical Data)16

17. 50Hz Notch Filter
(Calculation & Simulation)17
• Remove 50 Hz power line noise.
• Gain : Unity.
• Cutoff Frequency:
1
2π𝑹𝒇𝑪
=
50.57 Hz

18. Frequency Input Output
1 1.96 1.6
4 1.96 2.68
8 1.96 2.84
12 1.96 2.84
16 1.96 2.84
20 1.96 2.84
24 1.96 2.84
28 1.96 2.76
32 1.96 2.72
40 1.96 2.36
42 1.96 2.12
45 1.96 1.6
50 1.96 0.56
52 1.96 0.56
55 1.96 1.4
57 1.96 1.6
60 1.96 2.08
64 1.96 2.32
68 1.96 2.48
72 1.96 2.56
76 1.96 2.64
80 1.96 2.72
85 1.96 2.76
90 1.96 2.78
100 1.96 2.8
50Hz Notch Filter
(Practical Data)18

19. Clamper
For shifting the signal
so that we can
capture the signal
properly.
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20. Cascaded Circuit
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21. 21
Hardware

22. PCB
22

23. 23
Front Layer Back Layer
PCB Design

24. 24
This analysis shows that
when the eyes are on
blinking mode we are
getting peak on every
blink.
Signal Analysis in MATLAB
When Eyes are blinking
Blink Blink Blink
24

25. Alpha : 8 -
12 Hz.
If any peak is
found in this
range that
signal is definitely
EEG signal.
Signal Analysis in MATLAB
When Eyes are closed
25
Peak

26. 26
Signal in Time Domain

27. Cost Analysis
Components Quantity Unit
Price
(BDT)
Total
Cost
(BDT)
Remark
s
Arduino Uno 1 600.00 600.00
EEG
Electrodes
2 10.00 20.00
AD620 1 180.00 180.00
5V Battery 1 550.00 550.00
Resistor 30 .25 7.5
Capacitor 10 1.00 10.00
741 11 14.00 154.00
PCB 1 550.00 550.00
Total 2071.5
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• The overall cost of the proposed
system is approx. 2071.5 Tk.
• The available EEG device costs
$100 or 8500 Tk. (minimum).
• And the license cost of raw data is
around $100 per year .

28. Problem Faced/Limitations
 Low SNR
 Signal Generator
 Internal and external noises:
o General background noise(outside the
brain, internal circuitry noise)
o Natural noise(from our brain)
 Availability of affordable electrodes
 Limited usability of electrodes
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29. Conclusion
 Signal recording is done properly by this system .
 Anyone can modify the system because design is simple.
 Signal recording and detection achieved reasonable accuracy.
 With a modification anyone can make it portable and record as
much data as possible. The raw data can be accessed easily.
 This EEG system can be used for medical purposes after
further improvements.
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30. Future Works
 To make the EEG device wireless.
 To make the whole system user-friendly and more accurate by adding
more channel.
 To control a body part or moving mouse cursor by EEG signal.
 This work can be used for a security system like fingerprint, face-id. We
can use the eeg signals to security system. Because every person has a
unique brain signal.
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31. Video
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32. References
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