Rapid eye movements analysis¶

Introductory notes:¶

This notebook presents REMs detection functionality.

Import module¶

from sleepeegpy.pipeline import RapidEyeMovementsPipe
from os import makedirs,path

REMs detection¶

If you wish to change the path for output_dir ot input dir, change it below. If no such folders, they will be created automatically.

output_dir  = "output_folder" # Output path and name can be changed here
input_dir = "input_files" # input files dir can be changed here
makedirs(input_dir, exist_ok=True)
makedirs(output_dir, exist_ok=True)

Add required files and data¶

Put all your files in the input folder.
Modify your eeg file name below. The file can be any format supported by the mne.read_raw() function.
Modify your hypnogram file name below
Make sure the hypno_freq is the right frequency.
For more information about the supported formats, see mne documentation

eeg_file_name= "resampled_raw.fif" #None # add your eeg_path here
hypnogram_filename = "staging.txt" # Hypnogram filename can be changed here (file must be in the input dir)
hypno_freq = 1

path_to_eeg = path.join(input_dir,eeg_file_name)
hypnogram_path = path.join(input_dir,hypnogram_filename)

assert path.isfile(path_to_eeg) and path.isfile(hypnogram_path), f"{path_to_eeg} or {hypnogram_path} not exist"
rems_pipe = RapidEyeMovementsPipe(
    path_to_eeg=path_to_eeg,
    output_dir=output_dir,
    path_to_hypno=hypnogram_path,
    hypno_freq=hypno_freq,
)

Please refer to the YASA’s documentation for details about the arguments.

rems_pipe.detect(
    reference="average",
    loc_chname="E46",
    roc_chname="E238",
    include=4,
    freq_rem=(0.5, 5),
    duration=(0.3, 1.2),
    amplitude=(50, 325),
    remove_outliers=False,
    save=True,
)

Please refer to the YASA’s documentation for details about the arguments.

rems_pipe.results.summary(
    grp_stage=False, 
    mask=None, 
    aggfunc='mean', 
    sort=True
)

	Start	Peak	End	Duration	LOCAbsValPeak	ROCAbsValPeak	LOCAbsRiseSlope	ROCAbsRiseSlope	LOCAbsFallSlope	ROCAbsFallSlope	Stage
0	11050.544	11050.904	11051.096	0.552	95.514371	30.423478	130.506125	69.111908	567.494181	147.051950	4
1	11094.860	11095.436	11095.712	0.852	112.146842	40.051066	200.957633	50.196786	420.903964	135.024205	4
2	11095.964	11096.508	11097.108	1.144	83.861166	33.723120	64.100500	46.741223	186.273207	46.131956	4
3	11482.476	11482.772	11483.136	0.660	59.031067	45.284152	75.523086	237.193022	142.850213	153.438315	4
4	15971.100	15971.276	15971.560	0.460	61.745377	60.780729	572.829439	183.557890	102.135926	308.358956	4
...	...	...	...	...	...	...	...	...	...	...	...
80	23049.292	23049.600	23049.904	0.612	104.243540	28.876271	330.751289	95.426070	314.121445	92.583937	4
81	23056.604	23057.204	23057.520	0.916	77.727534	32.451615	58.396074	63.557268	256.425427	99.318708	4
82	23075.852	23076.452	23076.592	0.740	116.082740	33.233345	120.322005	19.386448	859.366479	219.808008	4
83	23076.672	23077.272	23077.544	0.872	129.179400	56.446968	116.311652	61.487780	395.069480	239.110792	4
84	23077.856	23078.224	23078.712	0.856	112.166788	44.556604	274.326404	129.250414	220.010889	106.752248	4

85 rows × 11 columns

rems_pipe.plot_average( 
    save=True, 
    center="Peak",
    time_before=0.5,
    time_after=0.5,
    filt=(None,None),
    mask=None,
    )

../_images/84d90cb08800d5d910fb00287c418e8647fe17036a56fd5e842731ff16650a45.png