Multifractal Detrended Analysis
Multifractal Detrended Analysis for time series signals, particularly applied to ECG and EEG signals with implementation of detrending algorithms and scaling exponent calculations
Feature Extraction of EEG Slow Wave P300 Signals Using Multi-Resolution Wavelet Transform
Feature extraction of EEG slow-wave P300 signals using multi-resolution wavelet transform, including algorithm implementation and code-oriented signal processing techniques.
Filtering, Fast Fourier Transform (FFT), Autocorrelation, and Cross-Correlation Analysis of EEG Signals
Implementation of EEG signal filtering, Fast Fourier Transform (FFT), autocorrelation, and cross-correlation computations to analyze inter-channel correlations in brain activity
EEG (Electroencephalogram) as a Bioelectrical Signal Reflecting Brain Activity
EEG (Electroencephalogram) is a bioelectrical signal that reflects brain activity. Due to its high time-varying sensitivity, EEG signals are highly susceptible to external interference during acquisition. Physiological activities such as eye movements, blinking, electrocardiogram (ECG), and electromyogram (EMG) can introduce noise (artifacts) into genuine EEG signals. This noise significantly complicates the analysis and processing of EEG data. Researchers have proposed numerous methods ranging from artifact removal techniques in EEG to noise elimination effect evaluation. This paper presents a MATLAB-based implementation for subtracting various EEG signal artifacts using algorithmic approaches.
MATLAB Algorithm for EEG Feature Extraction
MATLAB Implementation for Electroencephalogram (EEG) Feature Extraction and Signal Processing
Computing Second-Order Moment Energy for EEG Signals from C3 and C4 Channels
Calculating the second-order moment energy of EEG signals from C3 and C4 channels, which can be used to distinguish imagined left and right hand movements. This involves signal processing techniques and feature extraction for brain-computer interface applications.