Analysis and processing EMG signals using Simulink
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Abstract
Many applications, such as brain-computer interfaces, sleep monitors and intelligent
alarms, mood monitors, and other similar ones, use real-time analysis and processing of
electroencephalography (EEG) data. This study was carried out using MATLAB Simulink to
perform real-time analysis and processing of single and multi-channel EEG data by real-time
classifying them into brain wave components: alpha, beta, delta, and theta, and real-time
calculating the energy ratio of each brain wave component in real-time. We used basic blocks
from the Simulink basic library and signal processing blocks from the DSP System Toolbox to
construct our model. Our model has four main functions: plotting and pre-processing data,
classification of brain wave components, calculation of energy ratios, and visualization of
results. After connecting and configuring the settings of the blocks, we were able to finish our
model. We then used single-channel EEG data to simulate the model and categorized the data in
real-time into four different brain wave components: alpha, beta, delta, and theta. Through this
research, we have developed a whole system for real-time analysis and processing of EEG
signals, which may be utilized in various applications such as brain-computer interfaces, sleep
monitors and intelligent alarms, emotion monitors, and so on.
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