In this study, the EEG recordings were acquired from patients by 62 channels (BrainAmp 64 MRplus, BrainProducts) with positions of the international 10-20 system. The equipment used sintered Ag/AgCl-pin electrodes. We set a band-pass filtered at DC to 1000Hz in the recorder. The EEG signals were digitized at a sampling rate of 2.5 kHz. During the recording, the skin/electrode impedance was maintained below 5kΩ. We monitored patients for possible EEG signs of drowsiness and sleep onset (an increase of tonic theta rhythms, sleep spindles). An arousal procedure of CRS-R would be performed in the patients who showed above EEG signs.
An off-line analysis was performed with the EEGLAB 12.0.2.5b, running in a MATLAB environment (Version 2013b, MathWorks Inc., Natick, USA). An independent component analysis (ICA) function was used to identify and remove the artefact’s relevant components such as eye movement and muscle activities [27 (link)]. The EEG data from two patients were excluded because of serious artefacts (over one of three ICA components were identified as artefacts). The EEG data were down-sampled to 500Hz, bandpass filtered (1-45Hz) and average referenced. Then, the EEG data were divided into epochs of 10 seconds. Artefact-free epochs were preserved and recorded for EEG analysis.
An off-line analysis was performed with the EEGLAB 12.0.2.5b, running in a MATLAB environment (Version 2013b, MathWorks Inc., Natick, USA). An independent component analysis (ICA) function was used to identify and remove the artefact’s relevant components such as eye movement and muscle activities [27 (link)]. The EEG data from two patients were excluded because of serious artefacts (over one of three ICA components were identified as artefacts). The EEG data were down-sampled to 500Hz, bandpass filtered (1-45Hz) and average referenced. Then, the EEG data were divided into epochs of 10 seconds. Artefact-free epochs were preserved and recorded for EEG analysis.