Respiration Rate Variability Footprint for Disordered Breathing Detection
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Solution Overview
Problem
Disordered breathing, often associated with conditions like heart failure, is frequently undiagnosed and can lead to severe health consequences due to the lack of effective detection and monitoring tools.
Innovation Solution
A system and method for assessing patient conditions using respiration rate variability and generating a footprint from respiration-modulated signals, which allows for the detection, tracking, and prediction of disordered breathing and heart failure, enabling the adjustment of therapy and monitoring of patient status.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional respiration monitoring methods are used, then the monitoring system is simple, but the detection precision and ability to predict disordered breathing is insufficient
Solution Approach 1:
The patent transitions from traditional single-dimensional respiration rate monitoring to multi-dimensional analysis by generating a footprint that plots respiration rate against respiration rate variability. This dimensional expansion enables more precise detection of disordered breathing patterns while maintaining reasonable system complexity by building upon existing respiration monitoring capabilities.
Solution Approach 2:
The patent introduces respiration rate variability as a new parameter alongside traditional respiration rate monitoring. By calculating and analyzing the variability of respiration rate over time, the system achieves higher detection precision for disordered breathing conditions without requiring completely new hardware, thus managing system complexity.
2Reliability
If respiration rate variability footprint analysis is implemented, then the ability to detect and predict disordered breathing improves, but the computational complexity and data processing requirements increase
Solution Approach 1:
The patent performs preliminary calculations of respiration rate variability continuously in the background, building up the footprint data structure over time. This preliminary action ensures that when disordered breathing detection is needed, the analysis can be performed rapidly using pre-computed data, thereby improving detection reliability while managing computational complexity through staged processing.
Solution Approach 2:
The patent creates a simplified graphical representation (footprint) that copies and visualizes the complex respiration rate variability data in an interpretable format. This copying approach maintains high detection reliability by preserving the essential patterns while reducing the complexity of data interpretation for clinicians.
3Measurement precision
If continuous respiration monitoring is performed, then the detection capability improves, but the loss of time for data collection and the burden on patients increases
Solution Approach 1:
The patent implements continuous respiration monitoring but processes and presents only the essential features through the footprint analysis. By focusing on the most diagnostically relevant patterns in the respiration rate variability data, the system maintains high detection capability while reducing the effective data collection time needed for meaningful clinical assessment.
Data Source
AI summary
Systems and methods provide for detecting respiration disturbances and changes in respiration disturbances, preferably by detecting variability in one or more respiration parameters. Respiration rate variability is determined for a variety of diagnostic and therapeutic purposes, including disease/disorder detection, diagnosis, treatment, and therapy titration. Systems and methods provide for generating a footprint, such as a two- or three-dimensional histogram, representative of a patient's respiration parameter variability, and generating one or more indices representative of quantitative measurements of the footprint.