Hypopnea Detection Using Respiratory Flow Variance Ratios

The patent applies parameter changes by systematically varying detection thresholds (e.g., 30%, 50%, 70% reductions in respiratory flow) and time window parameters (e.g., 10-second, 30-second windows) to establish a standardized detection framework. This resolves the contradiction by providing multiple calibrated parameter sets that maintain detection sensitivity while ensuring consistent scoring across different clinical scenarios through predefined criteria.

The patent implements dynamics by using adaptive detection algorithms that adjust detection parameters based on individual patient baseline respiratory patterns. The system dynamically modifies detection thresholds and time windows according to each patient's specific breathing characteristics, thereby maintaining high detection accuracy while achieving scoring consistency through personalized adaptive criteria rather than fixed universal thresholds.

The patent applies segmentation by dividing the detection process into distinct stages: initial event detection using sensitive thresholds, followed by verification stages that apply additional criteria (duration confirmation, flow pattern analysis, arousal detection). This multi-stage segmented approach ensures complete detection of hypopnea events while filtering out false positives through progressive validation at each segment.

The patent implements feedback mechanisms where detection results are continuously evaluated and used to adjust subsequent detection parameters. The system incorporates feedback loops that verify detected events against multiple criteria (duration, flow reduction percentage, associated arousals, oxygen desaturation) and provide corrective feedback to refine detection accuracy, thereby maintaining high detection completeness while minimizing false positives through iterative validation.