Enhanced sleep staging with artificial intelligence: a validation study of new software for sleep scoring

Front Artif Intell. 2023 Dec 5:6:1278593. doi: 10.3389/frai.2023.1278593. eCollection 2023.

Abstract

Manual sleep staging (MSS) using polysomnography is a time-consuming task, requires significant training, and can lead to significant variability among scorers. STAGER is a software program based on machine learning algorithms that has been developed by Medibio Limited (Savage, MN, USA) to perform automatic sleep staging using only EEG signals from polysomnography. This study aimed to extensively investigate its agreement with MSS performed during clinical practice and by three additional expert sleep technicians. Forty consecutive polysomnographic recordings of patients referred to three US sleep clinics for sleep evaluation were retrospectively collected and analyzed. Three experienced technicians independently staged the recording using the electroencephalography, electromyography, and electrooculography signals according to the American Academy of Sleep Medicine guidelines. The staging initially performed during clinical practice was also considered. Several agreement statistics between the automatic sleep staging (ASS) and MSS, among the different MSSs, and their differences were calculated. Bootstrap resampling was used to calculate 95% confidence intervals and the statistical significance of the differences. STAGER's ASS was most comparable with, or statistically significantly better than the MSS, except for a partial reduction in the positive percent agreement in the wake stage. These promising results indicate that STAGER software can perform ASS of inpatient polysomnographic recordings accurately in comparison with MSS.

Keywords: artificial intelligence; deep learning; machine learning; medical software; sleep staging.

Grants and funding

The author(s) declare financial support was received for the research, authorship, and/or publication of this article. Medibio Limited sponsored the costs associated with the acquisition of the 40 sleep studies used in this work and the sleep staging performed by the three independent sleep technicians.