SmartHypnos: Developing a Toolbox for Polysomnographic Data Visualization and Analysis^.

Area of Science:

• Biomedical Engineering
• Sleep Medicine
• Software Development

Background:

• Polysomnography (PSG) is crucial for diagnosing sleep disorders.
• Manual analysis of PSG data is time-consuming and prone to errors.
• A user-friendly interface for PSG data visualization and event detection is needed.

Purpose of the Study:

• To introduce SmartHypnos, a novel graphical user interface (GUI).
• To enable easy visualization of polysomnography (PSG) signals.
• To facilitate the detection and classification of sleep-related events.

Main Methods:

• Development of a user-friendly GUI for PSG data.
• Integration of various physiological signals: EEG, ECG, EOG, EMG, and respiratory data.
• Implementation of automatic sleep staging and apnea event detection algorithms.

Main Results:

• SmartHypnos supports visualization of EEG, ECG, EOG, EMG, and respiratory signals.
• The software provides automatic sleep staging.
• Apnea event detection accuracy exceeds 80%.

Conclusions:

• SmartHypnos offers a user-friendly platform for PSG data analysis.
• The software demonstrates high accuracy in sleep staging and apnea detection.
• SmartHypnos is expected to reduce sleep data analysis time and human error.