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

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

Affiliations

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

Laurie Thiesse et al. Sleep Adv. .

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" (ICCAAAvg95% ≥ 0.75) or "good" (ICCAAAvg95% ≥ 0.60) for all sleep parameters assessed, except non-REM (NREM) and N3 sleep in healthy participants (ICCAAAvg95% = 0.43, ICCAAAvg95% = 0.56) and N3 sleep in OSA patients (ICCAAAvg95% = 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.

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Figures

Figure 1.
Figure 1.
Bland-Altman plots for sleep efficiency, sleep latency, wake after sleep onset, N1 + N2, N3, and REM sleep. Bias and lower and upper LoA between PSG and Somno-Art Software of the overall group are represented (n = 458). Black dots represent the healthy group (n = 79), green diamond OSA patients (n = 33), pink upward triangle insomniac patients (n = 135), and blue downward triangle MDD patients (n = 211).
Figure 2.
Figure 2.
Example of hypnograms obtained with PSG (in black) and Somno-Art Software (in blue) for a healthy subject, an obstructive sleep apnea (OSA), an insomniac and a MDD patient. W, wake.

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