Apr 10, 2024
Sleep scoring using Neuroscore
- daniel.dautan daniel1,2,
- Per Svenningsson1,2
- 1Department of Clinical Neuroscience, Karolinska Institutet, 171 76 Stockholm, Sweden;
- 2Aligning Science Across Parkinson’s (ASAP) Collaborative Research Network, Chevy Chase, MD 20815, USA
Protocol Citation: daniel.dautan daniel, Per Svenningsson 2024. Sleep scoring using Neuroscore. protocols.io https://dx.doi.org/10.17504/protocols.io.81wgbxjdolpk/v1
License: This is an open access protocol distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited
Protocol status: Working
We use this protocol and it's working
Created: February 22, 2024
Last Modified: September 23, 2024
Protocol Integer ID: 95633
Keywords: ASAPCRN, behavior, sleep, neuroscore
Funders Acknowledgements:
Aligning Science Across Parkinson's
Grant ID: 020608
Abstract
Analysis of sleep data using Neuroscore v.30
Open the file using File – Open Recording – Browse – Open
Remove unused signals using the right side tools “signal & data” and unselect all markers:
Identify the EEG and EMG signals by adjusting the time windows:
If the signal is unusable, just move to another recording. Here the top signal is EMG and bottom is EEG. You can see clear changes in EMG corresponding to movement and nice oscillation in EEG, the signal is as expected.
You can adjust the vertical scale for each signal using the right+click on the axis and scale to fit.
Once the signal is identified, you can proceed to sleep scoring. The built-in sleep scoring allows perfect scoring of frontal cortex EEG/EMG.
In inputs signal, select EEG channel for both Cortical EEG and theta EEG, EMG for EMG and activity for activity. Adjust the vertical scale to confirm the selection of correct signals.
In scoring rules, select “score active wake as awake.”
In artifact detection, select the threshold based on the signal of the recordings. Move the time windows to avoid cutting off signals.
Select the stage transition as below:
In advanced, select delta oscillation starting at 0.5Hz.
Press score study.
You should have sleep scoring for all your recordings on top of the signals.
Extract the data.
Select the data that need to be analyzed:
- time stamps normally 20s
-sleep scoring S is NREM, P is REM, W is awake and X is artifact
- select add column – select EMG channel – select statistical Root Mean Square
Copy this to excel:
a) Using the time you can extract the total number of sleep events, number of Awake, REM and NREM and thus express it onto %
b) You can extract the % of time in dark/light phase based on the timestamps
c) You can average/stdev EMG signal and thus express is as a z score
Using the z-score of the EMG, you can detect significant increase (SD >2SD) during REM events. This will be the rem sleep behavior disorders events.