Electronic Stethoscope CAD Risk Detection via Frequency Band Power Analysis
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Solution Overview
Problem
Current methods for detecting coronary artery disease (CAD) using electronic stethoscopes are prone to noise interference, making it difficult to accurately differentiate between CAD and non-CAD heart sounds, as the differences between the two are subtle and often masked by ambient or physiological noise.
Innovation Solution
A system and method that utilize an electronic stethoscope to record acoustic data, identify diastolic or systolic periods, apply filters to generate low and high frequency band signals, estimate power in these bands, and calculate a combined power ratio to indicate the risk of CAD, with a focus on low frequency signals which are less sensitive to noise and provide a more robust diagnosis when combined with high frequency signals.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If spectral analysis of heart sounds is used to detect CAD, then diagnostic capability is improved, but noise interference increases making differentiation difficult
Solution Approach 1:
The patent segments the heart sound signal into distinct frequency bands (low frequency 20-150 Hz and high frequency 150-500 Hz) and time periods (systolic and diastolic). This segmentation allows selective analysis of frequency bands that are less sensitive to noise, thereby improving CAD detection accuracy while mitigating noise interference.
Solution Approach 2:
The patent applies different analysis methods to different frequency bands and time periods. Low frequency bands during diastolic periods are given greater weight as they are less sensitive to noise. This local quality approach optimizes the signal-to-noise ratio by focusing analysis on the most reliable segments of the heart sound signal.
2Reliability
If traditional heart sound analysis is used, then diagnostic simplicity is maintained, but detection reliability decreases due to subtle differences being masked
Solution Approach 1:
The patent changes the analysis parameters by computing power spectral density across multiple frequency bands and time periods, then combining these with weighted coefficients. This parameter transformation converts subtle, difficult-to-detect differences into more pronounced and reliable diagnostic indicators while maintaining systematic complexity at an acceptable level.
Solution Approach 2:
The patent adds temporal and spectral dimensions to the analysis by dividing heart sounds into systolic/diastolic periods and low/high frequency bands. This multi-dimensional approach transforms the analysis from a single-dimensional time-domain examination to a comprehensive time-frequency analysis, significantly improving detection reliability.
3Measurement precision
If high frequency signals are analyzed for CAD detection, then sensitivity to CAD markers is improved, but noise sensitivity increases
Solution Approach 1:
The patent changes the frequency domain parameters by analyzing multiple frequency bands (20-150 Hz and 150-500 Hz) and combining their power spectral densities with weighted coefficients. This allows the system to capture CAD-related high frequency markers while compensating for noise sensitivity through the combined analysis framework.
Solution Approach 2:
The patent creates a composite diagnostic indicator by combining power spectral density values from multiple frequency bands and time periods with different weighting coefficients. This composite approach integrates information from both low frequency (noise-resistant) and high frequency (CAD-sensitive) bands, achieving a balance between sensitivity and noise immunity.
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
The approach significantly improves the accuracy of CAD diagnosis by reducing noise interference and enhancing the detection of CAD-related markers, providing a more secure and accurate assessment of coronary artery disease risk.
Implementation Method 1
an acoustic sensor adapted to be placed on the chest of a patient, and to generate acoustic signals SA
Data Source
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AI summary
The present invention relates to a system for detection of frequency power for diagnosing of coronary artery disease (CAD), comprising: an acoustic sensor adapted to be placed on the chest of a patient, and to generate acoustic signals SA; at least one memory adapted to store acoustic signals SA from the acoustic sensor; a control unit adapted to receive said acoustic signals SA; the control unit further comprises: an identification unit adapted to identify diastolic or systolic periods in a predetermined time period of the stored acoustic signals SA, and to generate a period signal SP indicating said identified periods; a filtering unit adapted to apply at least one filter to said identified periods and to generate a low frequency band signal SLFB indicating low frequency bands of said identified periods; a calculation unit adapted to estimate the power in said low frequency band of said identified periods, to calculate a low frequency power measure based upon said estimated power and to generate a low frequency power measure signal SLFP indicating said low frequency power measure. The invention also relates to a stethoscope and a method for detection of low frequency power.