Heart Sound Frequency Normalization for Sensor Attenuation
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Solution Overview
Problem
Healthcare systems capturing heart sounds often experience attenuation due to improper placement of sound sensors, leading to inconsistent and inaccurate representations of heart sounds, particularly affecting different frequencies of heart sounds differently.
Innovation Solution
A system and method for processing heart sounds with frequency-dependent normalization, which involves comparing a captured heart sound with a control to determine attenuation and modifying the sound accordingly to normalize it, using spectral analysis and inverse spectral analysis to produce accurate time-domain representations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If sound sensors are placed on the subject to capture heart sounds, then heart sounds can be captured electronically, but attenuation occurs due to improper placement leading to inconsistent and inaccurate representations
Solution Approach 1:
The patent applies parameter changes by modifying the captured heart sound signal through frequency-dependent normalization. The system determines attenuation characteristics across different frequency bands and applies compensatory gain adjustments to restore the original spectral balance. This transforms the degraded signal parameters back to their expected values, resolving the accuracy and consistency issues caused by sensor placement attenuation.
Solution Approach 2:
The patent replaces the mechanical solution of perfect sensor placement with a signal processing solution. Instead of relying on precise physical positioning of the sound sensor, the system uses spectral analysis and frequency-dependent normalization algorithms to compensate for attenuation effects. This substitution of mechanical precision with computational correction resolves the reliability and accuracy contradictions.
2Measurement precision
If frequency-dependent normalization is applied to compensate for attenuation, then accurate representation is achieved, but processing complexity increases
Solution Approach 1:
The patent segments the heart sound signal into different frequency bands for independent analysis and normalization. By dividing the spectral content into manageable segments (frequency bins), the system can apply targeted attenuation compensation to each segment. This segmentation approach manages processing complexity by breaking down the complex normalization task into simpler, frequency-specific operations.
Solution Approach 2:
The system performs self-service by automatically determining its own attenuation characteristics through spectral analysis of the captured signal. The algorithm identifies the attenuation profile from the signal itself and applies appropriate normalization without requiring external calibration or manual intervention. This self-service approach reduces operational complexity while maintaining high accuracy.
Data Source
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AI summary
There is disclosed herein examples of systems and methods of processing captured heart sounds with frequency-dependent normalization. Based on an amount of attenuation of a first heart sound, a second heart sound can be normalized by modifying portions of the second heart sound by amounts determined based on frequencies of the portions. Accordingly, the systems and methods disclosed herein can result in different amounts of modification of different portions of the second heart sound based on the different frequencies of the portions.