Electroencephalogram (EEG)¶

Electroencephalogram (EEG) signals measure electrical brain activity using scalp electrodes and enable time-domain and frequency-domain analysis of neural dynamics. EEG processing is commonly used for cognitive state assessment, sleep staging, and event-related studies.

API quick links: biosppy.signals.eeg | biosppy.signals.eeg.eeg()

Example EEG signal plot with eyes closed.

Example EEG signal plot with eyes open.

Quick Usage with `biosppy.signals.eeg.eeg()`¶

import numpy as np
from biosppy.signals import eeg

# EEG processing expects channels in columns for multichannel data.
signal = np.loadtxt("examples/eeg_ec.txt")

out = eeg.eeg(signal=signal, sampling_rate=1000.0, show=False)
print(out.keys())

Inputs

signal: EEG samples (N x channels).
sampling_rate: acquisition frequency in Hz.
labels: optional channel labels for readable plots/results.

Outputs

A ReturnTuple with EEG processing results such as filtered signals and derived channel-wise descriptors.
Use out.keys() to inspect all outputs.