SOMAS - an open-source software for the analysis of muscle activity during sleep

Area of Science:

• Sleep Medicine
• Neurophysiology
• Biomedical Engineering

Background:

• Existing algorithms for sleep muscle activity analysis lack open-source options for both muscle tone and movement.
• This limitation hinders reproducibility and collaborative research in sleep-related movement disorders.

Purpose of the Study:

• To develop SOMAS (Sleep Open-source Muscle activity Analysis System), an open-source software addressing the gap in analyzing sleep muscle tone and movements.
• To validate SOMAS's performance against established methods and its ability to differentiate specific sleep disorders.

Main Methods:

• SOMAS processes European Data Format+ (EDF+) files, calculating the atonia index, distribution of normalized electromyography (DNE), and leg movement indices.
• Recordings from patients with isolated REM sleep behavior disorder (iRBD), restless legs syndrome (RLS), sleep breathing disorders, and controls were analyzed.
• SOMAS-derived indices were compared with Hypnolab (non-open-source software) and used for diagnostic differentiation.

Main Results:

• SOMAS-derived atonia index and leg movement indices showed strong correlation (Spearman >0.97) with Hypnolab results.
• The DNE and atonia index effectively differentiated iRBD patients from others (AUC 0.89-1.00).
• Periodic leg movement and periodicity indices differentiated RLS patients from controls (AUC 0.71-0.75).

Conclusions:

• SOMAS provides a reliable, open-source solution for quantifying sleep muscle tone and movements from EDF+ files.
• The software demonstrates potential for improving research reproducibility and collaboration in sleep-related movement disorders.
• SOMAS aids in differentiating key sleep-related movement disorders, offering clinical and research utility.