HRV Measurement Using Poincaré Plot Geometry
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Solution Overview
Problem
Current methods for measuring heart rate variability (HRV) are complex and unreliable, leading to inadequate risk stratification for post-acute myocardial infarction (AMI) patients, resulting in inappropriate implantation of implantable cardioverter defibrillators (ICDs) and drug therapies, and failing to provide timely and effective treatment for ventricular tachycardia (VT)/ventricular fibrillation (VF) episodes.
Innovation Solution
A method and system for measuring HRV by recording electrocardiograph measurements, determining peak intervals, generating data points, and calculating an HRV relative density parameter (RD) to provide real-time monitoring and treatment, including the use of a data collector, analyzer, and output device to alert for potential VT/VF episodes.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If complicated mathematical algorithms are applied to HRV data, then measurement precision may be improved, but device complexity increases and reliability decreases
Solution Approach 1:
The patent extracts only the essential features needed for HRV measurement by using simple geometric calculations on Poincaré plot data points. Instead of applying complicated mathematical algorithms to the entire waveform, the method extracts RR intervals and plots them as simple (x,y) coordinates, then calculates HRV using basic geometric formulas for area and perimeter of the resulting plot.
Solution Approach 2:
The patent replaces complex, computationally intensive algorithms with simple, easily calculable geometric formulas. The HRV is derived from basic measurements of the Poincaré plot geometry (area, perimeter, aspect ratio) rather than sophisticated signal processing, making the measurement simpler and more reliable.
2Device complexity
If simple HRV measurement methods are used, then device complexity is reduced, but measurement precision and reliability deteriorate
Solution Approach 1:
The patent transforms the one-dimensional RR interval time series into a two-dimensional Poincaré plot, where each RR interval is plotted against the next RR interval. This dimensional transformation allows simple geometric calculations to capture the complexity of heart rate variability, improving reliability without increasing algorithmic complexity.
Solution Approach 2:
The patent changes the measurement parameters from complex time-domain or frequency-domain analyses to simple geometric parameters of the Poincaré plot (area, perimeter, aspect ratio). These geometric parameters provide reliable HRV measurement while keeping the calculation method simple and straightforward.
3Reliability
If ICD is implanted for VT/VF prevention, then patient safety may be improved, but device complexity, surgical risk, and cost increase
Solution Approach 1:
The patent enables preliminary detection of VT/VF risk by analyzing HRV patterns before arrhythmia occurs. By measuring geometric parameters of the Poincaré plot and comparing them to established thresholds, the system can identify patients at high risk and initiate preventive treatments before life-threatening arrhythmias develop, reducing or eliminating the need for ICD implantation.
Solution Approach 2:
The patent introduces HRV geometric parameter analysis as an intermediary between simple ECG monitoring and complex ICD therapy. This intermediate measurement layer provides sufficient information for risk stratification and treatment decision-making, avoiding the need to proceed directly to complex implanted devices for all patients.
4Measurement precision
If extensive HRV analysis is performed, then measurement precision is improved, but loss of time in processing increases
Solution Approach 1:
The patent segments the HRV analysis into distinct geometric calculations (area, perimeter, aspect ratio) that can be performed independently and efficiently. Each geometric parameter provides specific information about HRV, allowing the system to calculate multiple precision metrics without proportionally increasing processing time, as the calculations are based on simple coordinate geometry rather than intensive algorithmic analysis.
Data Source
AI summary
A system for measuring heart rate variability (HRV) comprising 3 sub-systems: a data collection sub-system, a data analysis sub-system, and an output sub-system. A patient is connected to a heart monitoring device such as an ECG and the data collection sub-system records the patients heart beats, and an ECG chart is produced from which the patient's HRV value is derived by the data analysis sub-system. The present invention obtains the HRV value through calculation of a new parameter called relative density (RD). In accordance with the inventive method, data points are generated from the peak interval data of measured heart beats and the HRV relative density parameter (RD) is calculated by correlation between two subsets of data points.