ECG Evaluation Universal Scoring System
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Solution Overview
Problem
Current methods for diagnosing cardiovascular system (CVS) pathology are limited by their inability to comprehensively evaluate cardiovascular regulation, myocardial state, and emotional state, and lack advanced diagnostic indicators, leading to reduced accuracy and diagnostic potential, especially in asymptomatic forms.
Innovation Solution
A hierarchical diagnostic algorithm that calculates quantitative ECG and HRV parameters, divides them into specific groups, and uses a 4-value decision rule to assess CVS functional state, emotional state, and myocardial reserves, incorporating advanced diagnostic codes for comprehensive and prognostic evaluations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If traditional ECG analysis methods are used, then the diagnostic process is simple, but the comprehensive evaluation of cardiovascular regulation, myocardial state, and emotional state is insufficient
Solution Approach 1:
The evaluation system is divided into multiple independent modules: ECG signal processing module, HRV analysis module, spectral analysis module, and integrated diagnosis module. Each module processes specific parameters (amplitude-time parameters, frequency-domain parameters, time-domain parameters) and contributes to the overall diagnostic accuracy without requiring the entire system to be complex
Solution Approach 2:
The patent transitions from traditional single-dimensional ECG analysis to multi-dimensional analysis by incorporating time-domain parameters, frequency-domain spectral parameters, and their interactions. This dimensional expansion enables comprehensive evaluation of cardiovascular regulation, myocardial state, and emotional state simultaneously, improving diagnostic accuracy without overwhelming complexity
2Reliability
If multiple ECG parameters are analyzed simultaneously, then diagnostic potential increases, but calculation complexity increases
Solution Approach 1:
The system performs preliminary calculations of individual parameters (PQ, QT, QR, RS, T wave amplitude, HRV parameters) and their spectral characteristics before the final integrated diagnosis. By pre-computing these components and storing them in a structured format, the final diagnostic process becomes more efficient and less computationally intensive, maintaining high diagnostic accuracy while improving productivity
3Measurement precision
If normalization of parameters onto heart rate is implemented, then parameter comparability improves, but diagnostic specificity decreases
Solution Approach 1:
The patent applies different normalization approaches to different parameter groups based on their specific characteristics. Time-domain parameters (PQ, QT, QR intervals) are normalized differently from frequency-domain spectral parameters and HRV parameters. Each parameter group receives the normalization method most suitable for its physiological meaning, preserving diagnostic specificity while achieving comparability within each group
Data Source
AI summary
The invention is designed to diagnose cardiovascular system (CVS) based on at least 148 quantitative ECG parameters including Heart Rate Variability (HRV) ones. Parameters are rated to 100 points, divided into 7 groups with close physiological nature, 4 diagnostic criteria (evaluation of CVS regulation, myocardium state, emotion state, HR disorders) and complex index of functional state (CIFS) are calculated. Aggregated diagnostic and prognostic decision are made about the functional CVS state and psycho-emotional state by combining CIFS, Hannover (or other similar algorithm), Minnesota code, myocardial abnormalities codes, and prediction codes of serious cardiovascular events. The method increases the accuracy and reliability of diagnostics.