NeuroAnalyzer tutorials: Plot (1)

Load data:

using NeuroAnalyzer
eeg = load("files/eeg.hdf");

[ Info: Loaded: EEG (24 × 308480 × 1; 1204.996 s)

Plot multi-channel signal:

NeuroAnalyzer.plot(eeg, ch="all")

Plot a time segment 10 to 12.5 second of a single-channel:

NeuroAnalyzer.plot(eeg, ch="Fp1", seg=(10, 12.5))

Plot multi-channel signal, mean ± 95CI of two channels:

NeuroAnalyzer.plot(eeg, ch=["F3", "F4"], type=:mean)

Butterfly plot multi-channel signal:

NeuroAnalyzer.plot(eeg, ch=["F3", "F4"], type=:butterfly)

You may also compare two signals, e.g. before and after filtering:

eeg1 = import_edf("files/eeg.edf");
eeg2 = NeuroAnalyzer.filter(eeg1, ch="all", fprototype=:fir, ftype=:lp, cutoff=30)
NeuroAnalyzer.plot(eeg1, eeg2, ch="eeg")

[ Info: Imported: EEG (24 × 308480 × 1; 1205.0 s)
[ Info: Signal should be tapered prior to filtering to reduce edge artifacts
[ Info: Creating LP filter:
[ Info:  Using default window: hamming(32)
[ Info:  Attenuation: 16 dB
[ Info:  Transition bandwidth: 0.0293 Hz
[ Info:  F_pass: 30.0 Hz
[ Info:  F_stop: 37.5 Hz
[ Info:  Cutoff frequency: 29.9854 Hz
Progress:   8%|█▋                  |  ETA: 0:00:43Progress: 100%|████████████████████| Time: 0:00:04