Poincaré Plot HRV Analysis for Real-Time Coherence Detection
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Solution Overview
Problem
Existing methods for determining a person's physiological condition using heart rate variability (HRV) rely on frequency analysis, which is slow to provide reliable coherence measurements and fails to promptly detect outliers, making them unreliable for short changes in coherence.
Innovation Solution
A time-based analysis of HRV using a Poincaré model, where R-R intervals are plotted to form an ellipse, with the centroid and average radius determined to assess coherence, allowing for real-time detection of changes and individual analysis of each entry, transforming the representation into a circle for efficient processing.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If frequency-based analysis of heart rate variability is used, then coherence measurement is obtained, but the measurement time is long and reliability for short changes is poor
Solution Approach 1:
The patent replaces the frequency-based analysis method (which requires averaging over 60 seconds) with a time-based analysis method using Poincaré plots. This substitution enables beat-to-beat analysis, reducing the measurement time from minutes to seconds while maintaining or improving coherence measurement reliability through geometric analysis of R-R interval patterns.
Solution Approach 2:
The patent changes the analysis parameter from frequency domain metrics (requiring long averaging periods) to time domain geometric metrics (Poincaré plot coordinates SD1 and SD2). This parameter transformation allows immediate detection of coherence changes on a beat-to-beat basis, eliminating the 60-second learning period required by frequency methods.
2Reliability
If frequency-based analysis averaging 60 seconds of heart beats is used, then coherence value is reliable, but detection of outliers and short changes is delayed
Solution Approach 1:
The patent substitutes frequency domain averaging (which smooths out short-term variations) with time domain Poincaré plot analysis. This allows immediate detection of outliers and short changes in coherence because each heartbeat is analyzed individually rather than being averaged over 60 seconds, while maintaining reliability through the geometric relationship between SD1 and SD2 metrics.
Solution Approach 2:
The patent performs preliminary geometric characterization of the Poincaré plot (calculating SD1, SD2, and their ratio) that can be updated with each new heartbeat. This preliminary analysis structure enables rapid detection of coherence changes without waiting for a full 60-second averaging window, improving detection speed while preserving reliability through consistent geometric metrics.
Data Source
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AI summary
The present invention relates to a method for determining a physiological condition of a person, comprising sampling a plurality of heart beats of the person, extracting a series of cardiac R-R intervals from the heart beat samples, and providing a two- dimensional representation of subsequent R-R intervals, wherein two subsequent R-R interval forms an entry in the two-dimensional representation, wherein the method further comprises the steps of determining a centroid, an average radius and an average rotation frequency for the plurality of entries in the two-dimensional representation, determining a plurality of distances between the radius and each of the entries in the two-dimensional representation, and determining the physiological condition of the person using the radius in combination with the plurality of distances. An advantage with the present invention following from this solution is that the time it take for determining the coherent state of the person is minimized at the same time as it is possible to quickly detect a change in state as each of the entries are directly related to the radius of the ellipse. The present invention also relates to a corresponding system making use of such a determination method.