Comparison of a single‐channel EEG sleep study to polysomnography

Abstract

Summary An accurate home sleep study to assess electroencephalography (EEG)-based sleep stages and EEG power would be advantageous for both clinical and research purposes, such as for longitudinal studies measuring changes in sleep stages over time. The purpose of this study was to compare sleep scoring of a single-channel EEG recorded simultaneously on the forehead against attended polysomnography. Participants were recruited from both a clinical sleep center and a longitudinal research study investigating cognitively-normal aging and Alzheimer's disease. Analysis for overall epoch-by-epoch agreement found strong and substantial agreement between the single-channel EEG compared to polysomnography (kappa=0.67). Slow wave activity in the frontal regions was also similar when comparing the single-channel EEG device to polysomnography. As expected, stage N1 showed poor agreement (sensitivity 0.2) due to lack of occipital electrodes. Other sleep parameters such as sleep latency and REM onset latency had decreased agreement. Participants with disrupted sleep consolidation, such as from obstructive sleep apnea, also had poor agreement. We suspect that disagreement in sleep parameters between the single-channel EEG and polysomnography is partially due to altered waveform morphology and/or poorer signal quality in the single-channel derivation. Our results show that single-channel EEG provides comparable results to polysomnography in assessing REM, combined stages N2 and N3 sleep, and several other parameters including frontal slow wave activity. The data establish that single-channel EEG can be a useful research tool.

Machine‐learning‐derived sleep–wake staging from around‐the‐ear electroencephalogram outperforms manual scoring and actigraphy

“…These studies all showed promising results, but involved a limited number of participants and also restricted electrode positioning. Other user-mounted systems have been developed specifically for sleep (Levendowski et al, 2017;Younes, Soiferman, Thompson, & Giannouli, 2017Lucey et al, 2016Shambroom et al, 2012;Werth and Borbely, 1995), but these systems all require electrodes to be placed in highly visible locations. Ear-centered EEG solutions come with the benefit of being sufficiently discrete and therefore acceptable to users also for routine applications during the daytime.…”

The Accuracy, Night-to-Night Variability, and Stability of Frontopolar Sleep Electroencephalography Biomarkers

“…18 A second study evaluated the agreement with PSG in a group that included elderly control patients for an Alzheimer disease investigation. 19 The first part of the current study was intended to demonstrate the validity of sleep biomarkers by first evaluating the accuracy based on the agreement in the autostaging from frontopolar sites to simultaneously acquired PSG in a group of patients mainly referred for probable obstructive sleep apnea. In the second part of this study, we evaluated the night-to-night consistency of sleep biomarkers identified by this device in a clinical population of insomnia patients vulnerable to a firstnight effect.…”

“…After rejection of periods when the absolute amplitude is ≥ 500 µV, the signals were notch filtered, and then infinite impulse response band pass-filtered to obtain 16 Hz samples of the power values for delta (1-3.5 Hz), Delta C (delta power corrected for ocular activity), theta (4-6.5 Hz), alpha (8-12 Hz), sigma (12)(13)(14)(15)(16), beta (18)(19)(20)(21)(22)(23)(24)(25)(26)(27)(28), and EMG bands ( > 40 Hz with a 80 Hz, 3 dB rolloff). A second set of power values was obtained after application of a 0.75-Hz highpass filter.…”

Automatic identification of sleep and wakefulness using single‐channel EEG and respiratory polygraphy signals for the diagnosis of obstructive sleep apnea

“…Previous small‐sample‐size studies have evaluated automated scoring software using single‐channel EEG data (Fietze et al., ; Fraiwan, Lweesy, Khasawneh, Wenz, & Dickhaus, ; Garcia‐Molina et al., ; Lucey et al., ; Su, Luo, Hong, Nagurka, & Yen, ; Zhang & Wu, ; Zhu, Li, & Wen, ). In 15 healthy adults.…”

“…Previous small-sample-size studies have evaluated automated scoring software using single-channel EEG data (Fietze et al, 2015;Fraiwan, Lweesy, Khasawneh, Wenz, & Dickhaus, 2012;Garcia-Molina et al, 2015;Lucey et al, 2016;Su, Luo, Hong, Nagurka, & Yen, 2015;Zhang & Wu, 2018;Zhu, Li, & Wen, 2014 patients. However, the agreement was slightly lower for the singlelead EEG by itself than when EOG and EMG data were added to the analysis (Fietze et al, 2015).…”