Heart and Respiratory Sound Rate Estimation Under Noise
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
The accuracy of heart and respiratory sound segmentation is affected by noise and interference in recordings, leading to inconsistent rate estimates which impact subsequent processing and analysis.
Innovation Solution
A method and apparatus that utilize a weighted combination of individual rate estimates from multiple sound recordings, each determined by analyzing their autocorrelation functions and quality measures, to calculate an aggregate rate estimate, improving robustness and accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If a single sound recording is used to determine rate estimate, then the processing is simple, but the accuracy is reduced due to noise and interference
Solution Approach 1:
The patent combines multiple sound recordings from different locations on the body to determine a consolidated rate estimate. By merging the information from multiple recordings and applying a weighted combination based on quality measures, the system achieves higher accuracy in rate estimation while compensating for noise and interference present in individual recordings.
2Measurement precision
If multiple sound recordings are processed, then the accuracy of rate estimate improves, but the processing time and computational load increase
Solution Approach 1:
The patent performs preliminary processing of each sound recording by determining quality measures before the final rate estimation. This preliminary assessment allows the system to weight or prioritize recordings based on their quality, enabling more accurate rate estimation while reducing unnecessary computational effort on low-quality recordings.
3Measurement precision
If quality measures are applied to weight individual rate estimates, then the aggregate rate estimate accuracy improves, but the processing complexity increases
Solution Approach 1:
The patent introduces quality measures as additional parameters to characterize each sound recording. These quality parameters are used to weight the contribution of individual rate estimates in the aggregate calculation. By changing the parameter set to include quality metrics, the system achieves more accurate aggregate rate estimation while managing algorithmic complexity through systematic parameter integration.
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 aggregate rate estimate provides a more reliable basis for subsequent sound processing, enhancing the accuracy of segmentation and analysis by mitigating the effects of noise and interference.
Implementation Method 1
determining a respective individual rate estimate for the sound recording by analysing a respective autocorrelation function of the sound recording
Data Source
AI summary
A method, apparatus and computer software for determining rate estimates from sounds emanating from a heart or respiratory system of a human or animal body. A plurality of sound recordings of a heart or respiratory system of a human or animal body are received, wherein each sound recording is or has been captured by a microphone positioned at a respective location on the exterior of the human or animal body. For each of the sound recordings, a respective individual rate is determined (51) by analysing a respective autocorrelation function of the sound recording and determining a respective quality measure. An aggregate rate estimate for the heart or respiratory system is determined (53) by evaluating a weighted combination of two or more of the plurality of individual rate estimates, wherein each of the individual rate estimates included in the weighted combination is weighted at least in part by the respective quality measure for the respective sound recording.