International Archives of Medicine published the Retrospective cross-validation of automated sleep staging using electroocular recordings in patients with and without sleep disordered breathing. The study included 87 subjects, of which 48% had moderate or severe sleep disordered breathing (SDB). The accuracy in detection of slow-wave-sleep and rapid-eye-movement sleep was comparable to variability across manual scorers, with both auto- and manual-scoring accuracies inversely proportional to SDB severity. Total sleep time and sleep efficiency was slightly under-estimated as compared to manual scoring however, the automated detection of sleep onset was within 10-minutes it 75% of the cases. The results suggest that the Sleep Profiler algorithms may prove useful in evaluating sleep architecture patterns in patients with chronic diseases.