EEG analysis relies on using different frequencies to extract meaningful information about brain activity. Here’s a breakdown:
- Brainwaves and Frequency Bands: The electrical activity measured by EEG recordings exhibits variations in frequency. These variations are grouped into different frequency bands, each associated with specific brain states or cognitive functions.
- Common EEG Frequency Bands:
- Delta Waves (1–4 Hz): Associated with deep sleep, unconsciousness, or brain injuries.
- Theta Waves (4–7 Hz): Associated with drowsiness, daydreaming, and emotional processing.
- Alpha Waves (8–13 Hz): Associated with relaxation, calmness, and eyes-closed resting state.
- Beta Waves (13–30 Hz): Associated with alertness, concentration, and information processing.
- Gamma Waves (30–100 Hz): Associated with high cognitive functions, information binding, and sensory processing.
- Feature Extraction and Frequency Domain Analysis: EEG feature extraction techniques often utilize the concept of frequency bands. Here’s how:
- Power Spectrum Density (PSD): This analysis method reveals the distribution of power (amplitude squared) across different frequencies within an EEG signal. By examining the power spectrum, we can identify which frequency bands are dominant and potentially relate them to the subject’s brain state.
- Band-pass filtering: We can isolate specific frequency bands using filters that allow only a certain range of frequencies to pass through. This allows us to focus on the activity within a particular band of interest.
- Choosing the Right Frequencies: The specific frequencies used for EEG feature extraction depend on the research question or application. Here are some examples:
- Sleep stage classification: Researchers might focus on delta and theta wave activity to differentiate between sleep stages.
- Attention detection: Alpha waves can be indicative of a relaxed but focused state, useful for applications like brain-computer interfaces.
- Epilepsy detection: Abnormal spikes or changes in specific frequency bands might be used to identify epileptic activity.
In essence, using different frequencies in EEG analysis allows us to extract information about the underlying brain activity. By focusing on specific frequency bands or analyzing the overall power spectrum, we can gain insights into a person’s brain state, cognitive functions, or even potential neurological conditions.
