High-Frequency QRS Waveform Analysis for Non-Invasive Ischemia Detection
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Solution Overview
Problem
Existing methods for identifying heart health status based on electrocardiogram (ECG) changes in the ST-T segment are inaccurate, necessitating invasive procedures like coronary angiography for precise assessment.
Innovation Solution
An analysis method and apparatus for high-frequency QRS waveform curves are developed, involving the acquisition and analysis of exercise electrocardiogram data to identify reference points and determine amplitude and duration values, allowing for non-invasive assessment of heart health through the evaluation of high-frequency QRS waveform curves.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If invasive methods such as coronary angiography are used to accurately identify heart health status, then measurement precision is improved, but device complexity and patient risk increase
Solution Approach 1:
The patent replaces invasive mechanical procedures (coronary angiography) with non-invasive electronic signal processing methods. By analyzing high-frequency QRS waveform curves through computational algorithms, the system achieves accurate heart health assessment without physical intrusion into the patient's body, thereby eliminating procedural complexity and associated risks while maintaining diagnostic precision
2Ease of operation
If traditional ST-T segment analysis is used to identify heart health status, then ease of operation is improved, but measurement precision deteriorates
Solution Approach 1:
The patent changes the analysis parameter from traditional ST-T segment to high-frequency QRS waveform characteristics. By focusing on specific waveform features (amplitude falling relative value, amplitude rising relative value, amplitude rising duration) within the QRS complex, the method maintains operational simplicity while significantly improving measurement precision for detecting myocardial ischemia and collateral circulation
Data Source
AI summary
A high-frequency QRS waveform curve analysis method comprises: acquiring a high-frequency QRS waveform curve; selecting the high-frequency QRS waveform curve in a preset time period as a reference waveform curve; selecting a point with the minimum root-mean-square voltage on the reference waveform curve as a first reference point; selecting a second reference point meeting a first selection condition and a third reference point meeting a second selection condition, wherein the time of the first reference point is later than that of the second reference point and earlier than the third reference point; based on the first reference point and the second reference point, determining an amplitude falling relative value; based on the first reference point and the third reference point, determining an amplitude rising relative value. If the amplitude falling rising relative values meet a preset condition, determining reference information according to the high-frequency QRS waveform curve.