HRV Pulse-Frequency Monitoring for Atrial Fibrillation Detection
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Solution Overview
Problem
Existing monitoring systems fail to accurately detect irregular heart rhythms and their underlying patterns, particularly atrial fibrillation and glucose regulation ability, due to reliance on time-based heart rate variability calculations and lack of consideration for irregularity in heart rate patterns.
Innovation Solution
A method for calculating heart rate variability based on the frequency of heartbeat occurrence, using an irregularity index to identify regular patterns, and a sliding window approach to process ECG data for real-time monitoring and alerting.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If time-based heart rate variability calculations are used, then the measurement method is simple and well-established, but the detection accuracy of irregular heart rhythms and atrial fibrillation is insufficient
Solution Approach 1:
The patent changes the fundamental parameter of HRV calculation from time-based intervals between heartbeats to frequency-based occurrence of instantaneous pulses. This parameter transformation enables the system to detect irregular heart rhythms and atrial fibrillation with higher accuracy by analyzing the frequency distribution of pulse occurrences rather than temporal intervals, thereby resolving the contradiction between measurement precision and method simplicity.
2Reliability
If traditional HRV methods eliminate irregularities and artifacts, then the calculation is more stable, but the detection of actual irregular heart rhythms like atrial fibrillation is compromised
Solution Approach 1:
Instead of eliminating irregularities and artifacts as traditional methods do, this patent inverts the approach by specifically targeting and analyzing irregular patterns as the primary measurement objective. The frequency-based analysis of instantaneous pulses allows the system to distinguish between benign variations and pathological irregularities like atrial fibrillation, achieving both reliability and precision by reversing the conventional filtering philosophy.
3Reliability
If continuous real-time monitoring is implemented, then the ability to detect health issues promptly is improved, but the energy consumption and system complexity increase
Solution Approach 1:
The patent replaces complex mechanical and computational systems with a streamlined frequency-based analysis approach. By computing the frequency of instantaneous pulse occurrences rather than performing complex time-series analysis of inter-beat intervals, the system achieves continuous real-time monitoring with reduced computational burden and lower energy consumption, thereby resolving the contradiction between real-time detection capability and energy usage.
Data Source
AI summary
This invention discloses a method to calculate a HRV profile, including variability and irregularity indexes, and detect the psychophysical condition, atrial fibrillation or ability to control glucose. This method receives data from a QRS detector and wearable non-invasive ECG sensor and starts with the calculation of instantaneous pulses and HRV based on pulses instead of heartbeat intervals, and then calculates the variability and irregularity indexes to detect the psychophysical condition, atrial fibrillation and ability to control the glucose level. The results can be sent to the patient, caregiver and doctor as intelligent message customized to avoid emotional stress and provide a gentle advice for current psychophysical and health condition.