SAAH ECG Device Subwaveform Detection for Heart Muscle Analysis
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Solution Overview
Problem
Conventional ECG devices only provide a limited view of heart function through the P, Q, R, S, T, U, and J waveforms, failing to capture the complete operation of all heart muscle tissues, which restricts diagnosis and treatment capabilities for various heart issues.
Innovation Solution
The development of a saah ECG device that employs signal processing to detect subwaveforms within and between the P, Q, R, S, T, and J waveforms, using band pass filters to identify depolarization and repolarization of specific heart muscle tissues, providing more detailed information on heart function.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If conventional ECG devices are used to detect heart electrical signals, then the basic P, Q, R, S, T, U, and J waveforms can be obtained, but the complete operation of all heart muscle tissues cannot be captured
Solution Approach 1:
The patent applies segmentation by dividing the detection of heart electrical signals into multiple frequency bands. Instead of treating the ECG signal as a single entity, the system segments it into different frequency components using band pass filters, allowing separate analysis of depolarization and repolarization processes in different heart muscle tissues. This enables capture of information that would be lost in conventional single-band ECG analysis.
Solution Approach 2:
The patent changes the parameter of frequency analysis by introducing multiple band pass filters with different frequency ranges. This allows the system to detect subwaveforms at different frequency bands within the same ECG signal, transforming the detection approach from a single frequency view to a multi-frequency spectrum analysis, thereby revealing hidden information about heart muscle tissue function.
2Measurement precision
If signal processing with band pass filters is employed to detect subwaveforms, then more detailed information on heart function is provided, but the device complexity increases
Solution Approach 1:
The signal processing is segmented into multiple parallel band pass filter channels, each targeting specific frequency ranges associated with different cardiac events. This segmentation allows precise detection of depolarization and repolarization subwaveforms without requiring complex sequential processing, as each filter independently processes its designated frequency band simultaneously.
Solution Approach 2:
The band pass filter system serves multiple functions: it detects different waveforms (P, QRS, T), identifies various heart muscle tissue activities, and provides frequency-based classification of cardiac events. This multi-functionality reduces the need for separate detection systems for each cardiac parameter, thereby managing complexity while enhancing measurement precision.
3Reliability
If subwaveforms within P, Q, R, S, T, and J waveforms are detected, then diagnostic capabilities for conditions like Wolff-Parkinson-White syndrome are enhanced, but the complexity of waveform analysis increases
Solution Approach 1:
The waveform analysis is segmented by frequency bands, with each band pass filter isolating specific subwaveforms associated with particular cardiac conditions. This segmentation simplifies the analysis of complex waveforms like those in Wolff-Parkinson-White syndrome by separating pathological signals into distinct frequency components that can be independently evaluated.
Solution Approach 2:
The band pass filters act as intermediaries between the raw ECG signal and the diagnostic analysis. They preprocess the signal by isolating relevant frequency components, thereby simplifying the subsequent diagnostic evaluation and reducing the complexity of direct waveform interpretation while maintaining high diagnostic reliability.
Data Source
AI summary
Systems and methods are provided to display discrete conduction timing values of layers of the ventricles. Electrical impulses are detected using two or more electrodes placed proximate to a beating heart and are converted to an ECG waveform for each heartbeat of the beating heart. One or more subwaveforms within Q, R, S, and T waveforms of the ECG waveform for each heartbeat or in an interval between the Q, R, S, and T waveforms are detected that represent the depolarization or repolarization of anatomically distinct layers of the ventricles of the beating heart. A conduction timing value is calculated for each of the one or more subwaveforms for each electrode of the two or more electrodes for each heartbeat of the beating heart. At least one conduction timing value is displayed for at least one subwaveform for each electrode for at least one heartbeat of the beating heart.