Automated Second Heart Sound Component Detection
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Solution Overview
Problem
Current methods for non-invasive detection of the aortic and pulmonary components of the second heart sound are hindered by noise interference, requiring specialized training and are not fully automated, limiting their clinical application.
Innovation Solution
A method involving the production of electronic representations of heart sounds, frequency-weighted energy calculation, peak identification, and normalization to estimate the location of aortic and pulmonary components, using multiple transducers and sub-channel analysis to enhance detection accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional auscultation methods are used, then clinical practitioners can detect heart sounds, but the detection requires specialized training and manual interpretation which reduces productivity and increases time consumption
Solution Approach 1:
The system performs automated detection and analysis of heart sound components without requiring manual interpretation by clinicians. The computer automatically identifies S1, S2, A2, and P2 components, calculates timing intervals, and generates diagnostic information, enabling the system to serve itself rather than relying on human expertise for each measurement.
Solution Approach 2:
The patent replaces the mechanical/manual process of auscultation and manual measurement with an automated computer-based system that uses signal processing algorithms to detect and analyze heart sounds electronically, substituting human sensory and manual measurement functions with automated electronic detection.
2Productivity
If automated detection methods are implemented, then productivity increases, but measurement precision deteriorates due to noise interference and inability to distinguish components reliably
Solution Approach 1:
The patent divides the heart sound signal into distinct segments and components (S1, S2, A2, P2) using signal processing techniques. By segmenting the continuous audio signal into discrete identifiable components, the system can automatically detect and measure each component's timing and characteristics separately, improving automated detection precision.
Solution Approach 2:
The system uses dynamic signal processing approaches that adapt to varying heart sound characteristics. The detection algorithm dynamically identifies component locations based on signal features rather than fixed thresholds, allowing it to maintain precision across different physiological conditions and noise levels.
3Ease of operation
If non-invasive phonocardiography is used, then ease of operation improves, but reliability is reduced due to noise masking and difficulty in distinguishing A2 and P2 components
Solution Approach 1:
The patent introduces intermediate processing steps including signal filtering, component identification algorithms, and timing calculation procedures that act as mediators between the raw heart sound signal and the final diagnostic output. These intermediary processes enhance the reliability of component detection by systematically processing the signal to distinguish A2 and P2 even in noisy conditions.
Solution Approach 2:
The system incorporates feedback mechanisms where the detected signal characteristics inform subsequent detection and analysis steps. The automated system uses the identified signal features to adjust and refine component detection, improving reliability through iterative verification and confirmation of detected components.
Data Source
AI summary
A method and apparatus for estimating a location of pulmonary and aortic components of second heart sounds of a patient over an interval. The method comprises the steps of producing an electronic representation of heart sounds of the patient over the interval, identifying at least one second heart sound in the interval using the electronic representation, for each identified second heart sound generating an estimated value for a location of the aortic component and the pulmonary component. There is also included a method for using the estimated location of the aortic component and the pulmonary component for estimation of the blood pressure in the pulmonary artery of a patient.