Cardiac Malfunction Detection via ECG and Motion Signal Correlation
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Solution Overview
Problem
Current methods for diagnosing cardiac malfunctions and abnormalities, such as atrial fibrillation, face challenges in accurately distinguishing between normal and abnormal cardiovascular functions, particularly due to the complexity of visual analysis of waveforms indicative of cardiovascular motion.
Innovation Solution
A method and apparatus that receive and process signals indicative of electromagnetic phenomena and cardiovascular motion, extracting specific wave patterns to form timing data and determine correlation with pacing data, using correlation coefficients to indicate cardiac malfunctions and abnormalities, with optional low-pass and band-pass filtering to enhance peak detection.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If visual analysis of waveforms is used to diagnose cardiac malfunctions, then diagnostic capability is provided, but accuracy in distinguishing normal from abnormal cardiovascular functions deteriorates due to complexity
Solution Approach 1:
The patent replaces manual visual analysis with automated computational processing. A processing device automatically extracts wave patterns from ECG and cardiovascular motion signals, computes timing data, calculates correlation coefficients, and generates diagnostic indicators, eliminating the need for complex visual interpretation by diagnosticians
Solution Approach 2:
The patent transforms complex waveform analysis into simplified quantitative parameters. By extracting specific wave patterns (P-wave, QRS complex, T-wave from ECG; aortic valve opening, mitral valve closure from motion signals) and computing timing intervals and correlation coefficients, the system converts complex visual patterns into manageable numerical indicators for automated diagnosis
2Loss of information
If comprehensive cardiac assessment is performed using multiple signals, then diagnostic information completeness is improved, but processing complexity increases
Solution Approach 1:
The patent divides the comprehensive cardiac assessment into distinct processing streams. The system separately processes ECG signals to extract electrical wave patterns and processes cardiovascular motion signals to extract mechanical wave patterns, then integrates them through timing data and correlation analysis, making the complex processing manageable through modular segmentation
Solution Approach 2:
The processing device performs multiple functions within a unified system: it extracts wave patterns from different signal types, computes timing intervals, calculates correlation coefficients, and generates diagnostic indicators. This multi-functional approach consolidates complex processing tasks into a single integrated system rather than requiring separate specialized devices
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
This approach enables more accurate and reliable detection of cardiac malfunctions and abnormalities by quantifying correlations and variations in timing data, improving the identification of conditions like atrial fibrillation through statistical analysis and signal processing techniques.
Implementation Method 1
a first signal indicative of electromagnetic phenomena related to cardiac activity
Implementation Method 2
a second signal indicative of cardiovascular motion, measured with an accelerometer
Data Source
Figure 1a~1b
Figure 2a
Figure 2b
AI summary
An apparatus for determining information indicative of cardiac malfunctions and abnormalities comprises a processing device (402) configured to extract, from a signal indicative of electromagnetic phenomena related to cardiac activity, a first wave pattern repeating on a heart-beat rate and, from a signal indicative of cardiovascular motion, a second wave pattern repeating on the heart-beat rate. The processing device is configured to form timing data such that each timing value of the timing data is indicative of a time period from a reference point of the first wave pattern belonging to one heart-beat period to a reference point of the second wave pattern belonging to the same heart-beat period. The processing device is configured to determine, at least partly on the basis of the timing data, an indicator of cardiac malfunction and abnormality. The figure proposed to be presented with the abstract: