Sleep

Sleep provides visualization, scoring, and analysis of polysomnographic data to detect and quantify sleep features such as spindles, K-complexes, slow waves, and rapid eye movements (REM).

Key Features:

• Dynamic Visualization Capabilities: Displays polysomnographic recordings, spectrograms, hypnograms, and topographic maps for exploration of sleep data.
• Automatic Detection of Sleep Features: Implements automatic detection of spindles, K-complexes, slow waves, and rapid eye movements (REM).
• Signal Processing Tools: Provides re-referencing and filtering for EEG preprocessing.
• Descriptive Statistics and Reporting: Generates descriptive statistics and publication-ready tables and figures.
• File Format Support: Supports European Data Format (EDF) and various commercial polysomnographic file formats.

Scientific Applications:

• Sleep architecture and dynamics analysis: Enables detailed analysis of sleep architecture and temporal dynamics from polysomnography and EEG recordings.
• Sleep disorder research: Facilitates investigation of sleep disorders through automated detection and quantification of spindles, K-complexes, slow waves, and REM.

Methodology:

Implemented in Python; uses the VisPy library for GPU-based visualization; supports EDF and various commercial formats; includes algorithms for automatic detection of spindles, K-complexes, slow waves, and REM; provides re-referencing and filtering for EEG preprocessing; generates descriptive statistics and publication-ready tables and figures.