Wearable ECG Monitor With Adaptive Compression for P-Wave Sensing
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Solution Overview
Problem
Current ECG monitoring systems are inadequate for long-term, ambulatory monitoring of cardiac rhythm disorders due to challenges in sensing low-amplitude P-waves, electrode adhesion issues, and the need for invasive surgical implantation, leading to discomfort, cost, and limited usability.
Innovation Solution
A lightweight, wearable electrocardiography monitor with a flexible extended wear electrode patch and a reusable recorder that optimizes P-wave sensing through axial placement on the sternal midline, featuring a self-optimizing compression algorithm for efficient data storage and transmission, allowing patients to easily replace electrodes and extend monitoring periods.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Duration of action of moving object
If conventional ECG monitoring systems are used for long-term ambulatory monitoring, then monitoring duration can be extended, but P-wave sensing quality deteriorates due to low-amplitude signal detection challenges
Solution Approach 1:
The patent applies local quality by optimizing electrode placement specifically for P-wave detection. The electrodes are positioned at the sternal midline in an axial orientation that maximizes capture of atrial electrical activity, rather than using standard ECG lead positions. This localized optimization of electrode placement quality enables sustained P-wave detection capability throughout extended monitoring periods.
Solution Approach 2:
The patent employs parameter changes by implementing a self-optimizing compression algorithm that dynamically adjusts compression parameters based on the detected ECG signal characteristics. The algorithm monitors signal quality metrics and adapts compression settings to preserve P-wave morphology while maintaining efficient data reduction, thereby sustaining measurement precision throughout long-term monitoring.
2Measurement precision
If invasive surgical implantation is used to improve P-wave sensing, then measurement precision improves, but device complexity and patient discomfort increase
Solution Approach 1:
The patent applies self-service through the self-optimizing compression algorithm that automatically adjusts compression parameters without requiring manual intervention or complex external programming. The device autonomously monitors signal characteristics and adapts its compression settings to maintain P-wave quality, eliminating the need for invasive procedures or complex external control systems.
Solution Approach 2:
The patent replaces the mechanical/invasive approach of surgical implantation with an electronic/software-based solution. Instead of physically implanting electrodes to improve signal quality, the system uses advanced signal processing and adaptive compression algorithms to enhance P-wave detection from non-invasive surface electrodes, substituting mechanical invasion with electronic optimization.
3Loss of substance
If higher compression algorithms are applied to reduce data storage requirements, then loss of substance decreases, but measurement precision deteriorates due to potential loss of diagnostic information
Solution Approach 1:
The patent applies dynamics by implementing a dynamic, self-adjusting compression algorithm that continuously adapts its compression ratio and parameter settings based on real-time analysis of ECG signal characteristics. The algorithm increases compression during periods of normal sinus rhythm while maintaining lower compression during periods with abnormal P-wave morphology or arrhythmias, thereby optimizing both data reduction and diagnostic information preservation throughout the monitoring period.
Solution Approach 2:
The patent employs feedback through the self-optimizing compression algorithm that continuously monitors ECG signal quality metrics and uses this feedback to adjust compression parameters. The system analyzes detected P-wave characteristics and feedback from signal quality assessments to dynamically modify compression settings, ensuring that diagnostic information is preserved while achieving efficient data storage.
Data Source
AI summary
An electrocardiography monitor configured for self-optimizing ECG data compression is provided. ECG waveform characteristics are rarely identical in patients with cardiac disease making this innovation crucial for the long-term data storage and analysis of complex cardiac rhythm disorders. The monitor includes a memory and a micro-controller operable to execute under a micro-programmable control and configured to: obtain a series of electrode voltage values; select one or more of a plurality of compression algorithms for compressing the electrode voltage series; apply one or more of the selected compression algorithms to the electrode voltage series; evaluate a degree of compression of the electrode voltage series achieved using the application of the selected algorithms; apply one or more of the compression algorithms to the compressed electrode voltage series upon the degree of compression not meeting a predefined threshold; and store the compressed electrode voltage series within the memory.