Respiratory Event Detection via Flow Segmentation
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Solution Overview
Problem
Conventional methods for monitoring respiratory events in patients with sleep breathing disorders, such as obstructive sleep apnea, often lead to erroneous detections or missed events due to limitations in analyzing gas flow patterns, necessitating an enhanced monitoring approach.
Innovation Solution
A method and system that monitor a patient's respiratory events by detecting flow limitations through a flow sensor, identifying event entries and exits based on peak flow changes, and adjusting treatment accordingly, utilizing a processor-controlled gas delivery system with modules for event detection and treatment adjustment.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If conventional methods monitor gas flow signal for shape and/or pattern to detect flow limitation, then respiratory events can be detected, but erroneous detections occur and some events are missed
Solution Approach 1:
The patent segments the respiratory event detection process into distinct phases: event entry detection (identifying when a respiratory event begins) and event exit detection (identifying when a respiratory event ends). This segmentation allows each phase to be optimized independently, improving overall detection accuracy by addressing the specific challenges of detecting event onset and offset separately rather than as a single continuous signal analysis problem.
2Productivity
If conventional methods use absolute measurement or relative changes in flow rate, then respiratory events can be identified, but false positives and negatives increase
Solution Approach 1:
The patent applies preliminary action by detecting event entry points before the full respiratory event pattern develops. The system identifies the onset of flow limitation early in the respiratory cycle, allowing for earlier intervention and more accurate event characterization. This preliminary detection capability reduces false negatives by catching events at their inception rather than waiting for full pattern development.
Solution Approach 2:
The system uses feedback mechanisms where the detected event entry and exit points are used to continuously refine the monitoring algorithm. By analyzing the characteristics of detected events and adjusting detection thresholds and parameters accordingly, the system reduces false positives and negatives over time, improving reliability while maintaining monitoring efficiency.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
This approach improves the accuracy of respiratory event detection and allows for real-time treatment adjustments, enhancing patient care by reducing false positives and negatives in monitoring respiratory events.
Implementation Method 1
a flow sensor that detects a flow of breathable gas generated by respiration of the patient
Data Source
AI summary
A system and method of monitoring a patient, that in one embodiment, comprises determining a flow of gas generated by respiration of the patient, identifying a respiratory event entry and a respiratory event exit based on the flow of gas generated by respiration of the patient, and identifying a respiratory event when the identification of the respiratory event entry is followed by the identification of respiratory event exit.