Reduced-Lead ECG Processing for Faster Heart Failure Risk Scoring
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Solution Overview
Problem
Conventional methods for assessing heart failure risk are time-consuming and result in inaccurate assessments, primarily relying on blood tests and echocardiography data.
Innovation Solution
A method and apparatus for processing electrocardiogram signals to obtain static and dynamic high-frequency QRS waveform features, which are analyzed to determine a risk assessment score for heart failure, utilizing a reduced amplitude zone analysis and a risk assessment function or network model.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional methods use multiple blood tests and echocardiography data to assess heart failure risk, then the assessment comprehensiveness is improved, but the time consumption increases and assessment accuracy deteriorates
Solution Approach 1:
The patent extracts and focuses on the most critical assessment dimensions from the complex conventional methodology. Instead of using all conventional tests simultaneously, it selectively extracts key electrocardiogram waveform features (QRS duration, high-frequency components, morphological characteristics) that provide the essential risk assessment information, thereby reducing time consumption while maintaining or improving accuracy
Solution Approach 2:
The patent replaces the mechanical/invasive blood test system with an electrical signal analysis system. By substituting physical blood sampling and echocardiography with non-invasive electrocardiogram signal processing, it eliminates the time-consuming aspects of conventional methods while providing accurate risk assessment through waveform feature extraction and analysis
2Measurement precision
If conventional methods use multiple detection data to assess heart failure risk, then the assessment coverage is improved, but the assessment accuracy deteriorates due to data integration complexity
Solution Approach 1:
The patent segments the complex assessment task into distinct, analyzable waveform feature components. It divides the electrocardiogram signal into specific features (QRS duration, high-frequency components, morphological characteristics) that can be independently measured and evaluated, then integrates these segmented features systematically to achieve accurate risk assessment without the complexity of integrating multiple different test types
Solution Approach 2:
The patent changes the assessment parameters from multiple different physiological measurements (blood markers, echocardiography measurements) to a unified set of electrocardiogram waveform parameters. This parameter standardization simplifies the assessment methodology while maintaining comprehensive coverage of risk factors through careful selection of discriminative waveform features
Data Source
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AI summary
The present application relates to an electrocardiogram signal processing method and apparatus, and a related device. The method comprises: acquiring electrocardiosignals of a first preset number of leads in a resting state, the leads comprising a second preset number of limb leads, and the second preset number being smaller than the first preset number; performing data processing on each electrocardiosignal in the resting state so as to obtain a static high-frequency QRS waveform feature set, the static high-frequency QRS waveform feature set comprising a QRS time limit, the number of first positive indexes, the number of first target leads and the number of target limb leads; and performing assessment and analysis on a risk assessment feature set so as to obtain a heart failure risk assessment score, the heart failure risk assessment score being used for judging the risk level of developing heart failure, and the risk assessment feature set comprising said static high-frequency QRS waveform feature set.