Definition
Electroencephalography (EEG) is a method of studying the brain’s electrical activity by placing electrodes in certain areas on the surface of the head. The brain consists of nerve cells – neurons that can transmit electrical impulses along a chain (Omejc et al., 2019). Different parts of the brain react to various external stimuli – within these areas, neurons transmit a single impulse.
In addition, the impulses can weaken or strengthen each other under certain conditions. Electrodes attached to the patient’s head pick up the pulses and transmit them to a computer for interpretation and display. Waves differ in characteristics – frequency and amplitude, and are divided into alpha, beta, delta, theta, and mu waves (Malik & Amin, 2017). An electroencephalogram allows a specialist to see signs of various brain disorders and assess their nature.
Technical Description
Biological Signal and Transducers
The brain’s biological signal of reading waves is obtained using electrodes, which are classified according to their purposes, advantages, and disadvantages, including a cup or needle. They require correct placement, and only electrodes of the same type should be used within the same study to avoid polarization between them (Ivanov, 2022). Due to electrical contact with the scalp, this method allows reading the biological signals of neurons, impulses emanating from different parts of the brain. As a result of such an interaction, waves appear as output data, the characteristics of which are studied further at the interpretation stage.
Impedance and Energy Conversion
In this method, the impedance, or electrical resistance, should ideally be minimal – for this, the skin is pre-treated, in some cases even with an abrasive paste. As a rule, EEG electrodes have a built-in function for measuring this indicator, and values not exceeding 25 kΩ are considered the norm (Ivanov, 2022). Such a check is carried out before and after the actual research process to assess the quality.
However, this control measure should be carried out periodically for lengthy procedures to eliminate potential error risks. The impedance is determined using the probed current applied to the electrodes, and in modern models, it is carried out online. Hardware reference electrodes, which record the received data, transfer it to software reference electrodes, which already average the value or localize it for further processing by the system (Ivanov, 2022). Here, the location of hardware and software electrodes, regulated by accepted standards, is significant.
Amplification, Filtering, and Digitisation
Through wires, usually copper and braided to reduce artifacts, the signal from the reference electrodes is fed to the amplifier. The signals received from the brain have an extremely low amplitude; therefore, for further processing, they must be increased tenfold (Ivanov, 2022). It uses the highest quality amplifiers with minimal self-interference to carry the desired signal through cascaded amplification. Using a ground electrode in this procedure is essential to reduce common-mode noise. After that, the signal is sent to the ADC, where it is converted from analog to digital. Additional filtering processes between gain and conversion include low-pass and high-pass filters and a standard mode filter. An essential aspect of the ADC elements in the EEG is using an extremely high signal sampling frequency, which exceeds the original one by tens of times.
Data Processing and Storage
Data is transmitted to the computer via USB, LAN, Bluetooth, Wi-Fi, or Optical connections, where, in the future, they can undergo additional filtering of the already digital signal with the same filters as indicated above, either at the stage of receiving or before direct visualization of the waves on the screen. However, additional filtering can do more harm than good in some cases, as it introduces distortions in the original data. The received information is stored and reproduced in pixel images, where anti-aliasing technologies can already be applied or remain in the original stepped form.
References
Ivanov, A. A. (2023). The structure of modern EEG recorder. Epilepsy and Paroxysmal Conditions, 14(4), 362-378. Web.
Malik, A. S., & Amin, H. U. (2017). Designing EEG experiments for studying the brain: Design code and example datasets. Academic Press.
Omejc, N., Rojc, B., Battaglini, P. P., & Marusic, U. (2019). Review of the therapeutic neurofeedback method using electroencephalography: EEG Neurofeedback. Bosnian Journal of Basic Medical Sciences, 19(3), 213. Web.