Cookies on this website

We use cookies to ensure that we give you the best experience on our website. If you click 'Accept all cookies' we'll assume that you are happy to receive all cookies and you won't see this message again. If you click 'Reject all non-essential cookies' only necessary cookies providing core functionality such as security, network management, and accessibility will be enabled. Click 'Find out more' for information on how to change your cookie settings.

The use of a fixed electroencephalogram (EEG) amplitude threshold of 75 µV for labelling slow waves is a subject of ongoing discussion given EEG amplitude is known to vary with age and sex. This paper investigates the impact of this amplitude threshold on age- and sex-related trends in visually-annotated SWS. Automated methods for labelling SWS using data-driven thresholds and amplitude- or frequency-based inputs are developed. Age- and sex-related trends in SWS derived from visual annotation and automated labelling are then compared across a cohort of 2,913 participants from the Sleep Heart Health Study. In the selected cohort, males exhibit an age-related decrease in visually-annotated SWS, which is preserved when using automated labelling. In contrast, females exhibit a mild age-related increase in visually-annotated and amplitude-labelled SWS, but an age-related decrease in frequency-labelled SWS. Further, using frequency-labelled SWS results in a reduction in SWS in females to a level comparable to that of males. Overall, the consistency of age-related trends in SWS in males between visual annotation and automated labelling, as well as the lack of consistency in these trends in females, is striking. Given that the 75 µV amplitude threshold was established using data acquired primarily from young males, these results suggest that observed sex-based differences in visually-annotated SWS may be artefactual rather than physiological, and a result of the 75 µV amplitude criterion. This sex-related disparity highlights the need for the AASM guidelines for scoring SWS to be reviewed and updated to provide equivalent performance for males and females.

Original publication

DOI

10.1093/sleep/zsaf063

Type

Journal article

Journal

Sleep

Publication Date

13/03/2025

Keywords

EEG analysis, Gender, Mathematical Modelling, Sleep and the Brain, Slow Wave Sleep