Validation of Somno-Art Software, a novel approach of sleep staging, compared with polysomnography in disturbed sleep profiles

Laurie Thiesse; Luc Staner; Patrice Bourgin; Thomas Roth; Gil Fuchs; Debora Kirscher; Jean-Yves Schaffhauser; Jay B Saoud; Antoine U Viola

doi:10.1093/sleepadvances/zpab019

Validation of Somno-Art Software, a novel approach of sleep staging, compared with polysomnography in disturbed sleep profiles

Sleep Adv. 2021 Dec 9;3(1):zpab019. doi: 10.1093/sleepadvances/zpab019. eCollection 2022.

Authors

Laurie Thiesse¹, Luc Staner², Patrice Bourgin^{3

4}, Thomas Roth⁵, Gil Fuchs¹, Debora Kirscher¹, Jean-Yves Schaffhauser¹, Jay B Saoud^{6

7}, Antoine U Viola¹

Affiliations

¹ PPRS, Colmar, France.
² Unité d'Exploration des Rythmes Veille-Sommeil, Centre Hospitalier de Rouffach, Rouffach, France.
³ Sleep Disorders Center and CIRCSom (International Research Center for ChronoSomnology), Strasbourg University Hospital, Strasbourg, France.
⁴ CNRS UPR 3212, Institute for Cellular and Integrative Neurosciences, Strasbourg, France.
⁵ Sleep Disorders Center, Henry Ford Hospital, Detroit, MI, USA.
⁶ PPRS Research Inc., Groton, MA, USA.
⁷ PPDA, LLC, Groton, MA, USA.

Abstract

Study objectives: Integrated analysis of heart rate (electrocardiogram [ECG]) and body movements (actimetry) during sleep in healthy subjects have previously been shown to generate similar evaluation of sleep architecture and continuity with Somno-Art Software compared to polysomnography (PSG), the gold standard. However, the performance of this new approach of sleep staging has not yet been evaluated on patients with disturbed sleep.

Methods: Sleep staging from 458 sleep recordings from multiple studies comprising healthy and patient population (obstructive sleep apnea [OSA], insomnia, major depressive disorder [MDD]) was obtained from PSG visual scoring using the American Academy of Sleep Medicine rules and from Somno-Art Software analysis on synchronized ECG and actimetry.

Results: Inter-rater reliability (IRR), evaluated with 95% absolute agreement intra-class correlation coefficient, was rated as "excellent" (ICC_AAAvg95% ≥ 0.75) or "good" (ICC_AAAvg95% ≥ 0.60) for all sleep parameters assessed, except non-REM (NREM) and N3 sleep in healthy participants (ICC_AAAvg95% = 0.43, ICC_AAAvg95% = 0.56) and N3 sleep in OSA patients (ICC_AAAvg95% = 0.59) rated as "fair" IRR. Overall sensitivity, specificity, accuracy, and Cohen's kappa coefficient of agreement (κ) on the entire sample were respectively of 93.3%, 69.5%, 87.8%, and 0.65 for wake/sleep classification and accuracy and κ were of 68.5% and 0.55 for W/N1+N2/N3/rapid eye movement (REM) classification. These performances were similar in healthy and patient population.

Conclusions: The present results suggest that Somno-Art can be a valid sleep-staging tool in both healthy subjects and patients with OSA, insomnia, or MDD. It could complement existing non-attended techniques measuring sleep-related breathing patterns or be a useful alternative to laboratory-based PSG when this latter is not available.

Keywords: actimetry; automatic sleep analysis; heart rate; insomnia; major depressive disorder; obstructive sleep apnea.