ABOSA

ABOSA analyzes blood oxygen saturation (SpO₂) signals to detect desaturation and recovery events and compute event-specific metrics for sleep apnea research.

Key Features:

• Automatic Detection: Automatically identifies desaturation and recovery events within SpO₂ signals.
• Comprehensive Metrics: Calculates event-specific metrics including Oxygen Desaturation Index (ODI) and Desaturation Severity (DesSev).
• Batch Analysis: Supports batch processing of large SpO₂ datasets for high-throughput analysis.
• EDF Input Support: Processes EDF (European Data Format) files commonly used for polysomnography.
• MATLAB Implementation: Implemented in MATLAB as the software development environment.
• Sophisticated Parameters: Computes additional signal-based and novel parameters for detailed characterization of desaturation events.

Scientific Applications:

• Sleep Apnea Severity Assessment: Enables quantification of sleep apnea severity using ODI, DesSev, and other desaturation-derived metrics.
• Epidemiological Studies: Applicable to large-scale analyses of population-level oxygen desaturation patterns.
• Clinical Trials: Supports analysis of SpO₂-derived endpoints in clinical studies of respiratory disorders.
• Validation and Method-Comparison Studies: Validated against manual scorings in Kuopio (n = 1981) and Loewenstein (n = 930) datasets using second-by-second Matthew's Correlation Coefficients (MCC) and median parameter differences, and shown comparable desaturation detection to Noxturnal and Profusion.

Methodology:

Implemented in MATLAB; processes EDF files; algorithm automatically detects desaturation and recovery phases in the SpO₂ signal and calculates multiple event-specific parameters.