EEG importance and challenges

1. EEG importance and challenges
Presentation · September 2014 DOI: 10.13140/RG.2.1.2387.4166
https://www.researchgate.net/publication/304216715
Outline
Introduction about EEG.
Importance of EEG.
Challenges of EEG.
Introduction about EEG
EEG (Electro-encephalo-gram) belongs to biopotential signals which become
important field in diagnosing human health since 1929 [1].
EEG is the registration and the interpretation of the electrical waves generated
from the neuron activity of the brain, which is related to the nervous system [2,
3, 4, 5-6, 7].
EEG signal is a low amplitude voltage ranged from 10μV to 100μV and it
occupies low frequency bands from 0.1Hz to 100Hz [8-1, 15]. Table 1 compares
different biopotential signals in their amplitude and frequency ranges [8-1, 9-13,
14, 15-16].
Table 1 The amplitude voltage, the frequency, and the segment of the signal
for some biopotential signals.

2. There are five classifications of the frequency waves of the EEG signal
mentioned in table 2, ordered from lowest to highest frequencies.
Table 2 The amplitude voltage, the frequency band, the location, the
occurrence, and morphology of EEG’s waves [1, 17, 18, 19].
There are five classifications of the frequency waves of the EEG signal
mentioned in table 2, ordered from lowest to highest frequencies.
The brain rhythm is used to diagnose the brain seizures and injuries [8].
EEG device can be connected on the scalp of the patient through electrodes. A
common used system to place electrode is 10-20 system standard [1-20, 18-21].

3. Importance of EEG
•EEG test
EEG test is an indicator to check brain waves normality and to diagnose brain
illness and injury.
It is used in hospitals for medical purposes and in research laboratories for
scientific researches and device developments.
EEG based Brain Control Interface
EEG works as a brain monitoring method employed in BCI.
BCI is a communication/control system which allows interface between human
and computer without the use of muscles or peripheral nerves [22].
The system diagram of BCI is shown in figure 2.

5. Challenges in EEG
The challenges face designing EEG system can be categorized as:
1.EEG characteristics.
2.Application used EEG acquisition system.
3.Building blocks of EEG acquisition system.

6. 1.EEG characteristics.
Measuring EEG signal is difficult due to its characteristics.
The surface voltage which reaches to the scalp passes through different
nonhomogeneous tissues. These tissues are listed in the table 3 with their
corresponding resistivity [1, 15].
Measuring EEG signal is difficult due to its characteristics.
The surface voltage which reaches to the scalp passes through different
nonhomogeneous tissues. These tissues are listed in the table 3 with their
corresponding resistivity.
Its low frequency band is easily affected by interference and noise.

7. 2.Application used EEG acquisition system.
EEG based BCI challenges.
1.Portability and Wearability
Compact/Miniaturized.
Lightweight.
Handheld.
Simple to use.
► Portable EEG system with Laptop/computer/phone

8. 1.Portability and Wearability
Easily worn.
Wireless.
Mobility.
► Wireless EEG system integrated in clothes (handset/headband/helmet/cap)

9. 2. Dry/Noncontact electrodes.
Free-gel media (direct skin contact).
Comfortable and easy to prepare.
Long term monitoring (electrode longevity).
Flexible electrodes to push away hair from scalp (through hair) [31].

10. ► Wearable EEG system with direct skin contact.
₪Suffered from motion artifacts [31].
2. Dry/Noncontact electrodes.
Free-gel media (special case of dry electrodes [31]).
Inserted on insulation layer (clothes [31, 41]).
Long term monitoring.

11. ► Wearable EEG system with through clothes electrodes.
₪Sensitive to motion artifacts [31].
3.Building blocks of EEG acquisition system.
Analog readout EEG circuit.
The analog readout EEG circuit is shown in figure 11.
EEG Readout circuit.
1.1/f noise appears in the band of EEG frequency.
2.AC power line interference (mains interference) can easily interfere with EEG
signal ( can reach amplitude of 1mV) [44].

12. 3.Skin-electrode interface generates differential DC electrode offset voltage (can
reach amplitude 50mV) [45].
► Readout circuit should have HPF characteristics to remove low frequency
noise (1/f noise and DC offset), and LPF to eliminate unwanted high frequency.
₪Readout circuit designed for dry electrode must have high input impedance
(>>1GΩ) [45].
Biopotential Amplifier
1.High CMRR to neglect mains interference.
2.HPF features to filter DC electrodes offset voltage.
3.Low noise to have high quality signal.
4.Low power dissipation to increase supply voltage life [45].
5.Configurable gain and filter features that suit with the needs of different
biopotential signals and different applications.
Table 2 and table 3 show different designs of instrumentation amplifier and
differential amplifier using for biopotential applications, respectively.

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