NeuroAnalyzer tutorials: Remove power line noise

Power line noise (at 50 or 60 Hz, depending on the country) may be automatically attenuated using remove_powerline(). Currently it supports:

IIR notch filtering + automated detection and removal of power line peaks; for best results the notch filter bandwidth is calculated separately for each peak for each channel (this may take approx. 2 minutes per object)

To use IIR notch filtering method:

eeg = import_edf("NEURO-testing-data/EDF/eeg-test-edf.edf")
p1 = plot_psd(eeg, ch=1)
remove_powerline!(eeg, method=:iir, pl_frq=50)
p2 = plot_psd(eeg, ch=1)
p = Plots.plot(p1, p2, layout=(2, 1))
plot_save(p, file_name="images/remove_pl1.png")

Output:

[ Info: Removing power line noise at 50 Hz and its peaks.
Progress: 100%|████████████████████| Time: 0:01:46         
24×6 DataFrame
 Row │ channel  power line bandwidth  peak 1 frequency  peak 2 frequency  peak 1 bandwidth  peak 2 bandwidth 
     │ Int64    Float64               Float64           Float64           Float64           Float64          
─────┼───────────────────────────────────────────────────────────────────────────────────────────────────────
   1 │       1                   1.6             100.0             106.0               0.2               0.2
   2 │       2                   1.3             100.0             106.0               0.2               0.2
   3 │       3                   3.4             100.0             106.0               0.3               0.3
   4 │       4                   2.2             100.0             106.0               0.2               0.2
   5 │       5                   3.1             100.0             106.0               0.3               0.3
   6 │       6                   3.5             100.0             106.0               0.3               0.3
   7 │       7                   1.9             100.0             106.0               0.2               0.3
   8 │       8                   1.6             100.0             106.0               0.2               0.2
   9 │       9                   0.1             100.0             106.0               0.3               5.0
  10 │      10                   1.9             100.0             106.0               0.2               0.2
  11 │      11                   5.0             100.0             106.0               0.2               0.2
  12 │      12                   0.7             100.0             106.0               0.1               0.1
  13 │      13                   1.8             100.0             106.0               0.2               5.0
  14 │      14                   0.9             100.0             106.0               0.2               0.1
  15 │      15                   2.2             100.0             106.0               0.2               0.2
  16 │      16                   1.2             100.0             106.0               0.2               0.2
  17 │      17                   3.1             100.0             106.0               0.3               0.3
  18 │      18                   1.6             100.0             106.0               0.1               0.2
  19 │      19                   2.7             100.0             106.0               0.3               0.3
  20 │      20                   4.2             100.0             106.0               0.2               0.1
  21 │      21                   3.6             100.0             106.0               0.2               0.2
  22 │      22                   5.0             100.0             106.0               0.1               0.1
  23 │      23                   5.0             100.0             106.0               0.2               0.2
  24 │      24                   5.0             100.0             106.0               0.3               0.2

The output data frame may be used to remove peaks manually:

NeuroAnalyzer.filter!(eeg, ch=1, fprototype=:iirnotch, cutoff=50, bw=1.6))
NeuroAnalyzer.filter!(eeg, ch=1, fprototype=:iirnotch, cutoff=100, bw=0.2))
NeuroAnalyzer.filter!(eeg, ch=1, fprototype=:iirnotch, cutoff=106, bw=0.2))

eeg = import_edf("NEURO-testing-data/EDF/eeg-test-edf.edf")
e10 = epoch(eeg, ep_len=10)
p1 = plot_spectrogram(e10, ch=1, ep=2)
remove_powerline!(eeg, method=:iir, pl_frq=50)
e10 = epoch(eeg, ep_len=10)
p2 = plot_spectrogram(e10, ch=1, ep=2)
p = Plots.plot(p1, p2, layout=(2, 1))
plot_save(p, file_name="images/remove_pl2.png")