Electronic Stethoscope FFT Analysis for Coronary Artery Stenosis Detection
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Solution Overview
Problem
Current diagnostic techniques for coronary artery disease are costly, invasive, and have varying sensitivity and specificity, often failing to detect stenosis until blood flow is severely restricted, leading to potential health deterioration in asymptomatic patients.
Innovation Solution
An electronic stethoscope system that records acoustic data from the chest, applies filters, and performs a Fast Fourier Transform (FFT) to identify a bell curve within a specific frequency range, indicating 50-99% coronary artery blockage, allowing for early detection and potentially reducing the need for invasive tests.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If invasive diagnostic techniques (coronary angiogram) are used to detect coronary artery stenosis, then measurement precision is improved, but device complexity and patient risk increase
Solution Approach 1:
The patent replaces the mechanical/invasive coronary angiogram procedure with an acoustic detection system using electronic stethoscope and FFT analysis. The system substitutes direct visual imaging with non-invasive acoustic signal processing to detect stenosis, eliminating the need for catheter insertion and contrast dye administration while maintaining diagnostic capability through spectral analysis of heart sounds
Solution Approach 2:
The patent introduces acoustic signals as an intermediary to detect coronary artery stenosis. Instead of directly visualizing the artery, the system uses sound waves captured by the electronic stethoscope as a mediator to indirectly detect the presence and severity of stenosis through characteristic acoustic patterns in the frequency spectrum
2Productivity
If stress testing is used to detect coronary artery disease, then productivity is improved, but measurement precision deteriorates due to varying sensitivity and specificity
Solution Approach 1:
The patent transforms the diagnostic approach by changing from functional assessment (stress testing) to spectral frequency analysis. Instead of measuring physiological responses during exercise, the system analyzes the frequency spectrum of heart sounds, specifically looking for bell curves in the 50-80 Hz range that indicate stenosis, providing more consistent and objective diagnostic criteria
3Ease of operation
If traditional stethoscope is used for physical examination, then ease of operation is improved, but measurement precision deteriorates due to inability to detect subtle acoustic patterns
Solution Approach 1:
The patent replaces the purely mechanical traditional stethoscope with an electronic system that incorporates digital signal processing. The electronic stethoscope converts acoustic signals to digital data, applies FFT transformation, and automatically identifies pathological bell curves, enhancing the detection precision while maintaining the simplicity of auscultation
Solution Approach 2:
The patent creates a digital copy of the acoustic signal for analysis. The electronic stethoscope captures heart sounds, converts them to digital form, and generates a spectral representation through FFT. This digital copy allows for precise measurement and automatic identification of stenosis-indicating patterns without affecting the simplicity of the examination process
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 system effectively identifies coronary artery disease with high specificity and sensitivity, reducing unnecessary invasive procedures and enabling early intervention, while also saving healthcare resources by minimizing false positives and negatives.
Implementation Method 1
an acoustic sensing device is employed to transmit the raw sound data from the patient
Implementation Method 2
applying one or more filters to the acoustic data and calculating a Fast Fourier Transform (FFT) of the data to produce FFT data
Data Source
AI summary
The disclosure describes an electronic stethoscope system that automatically detects coronary artery disease in patients. The system uses an electronic stethoscope to record acoustic data from the fourth left intercostal space of a patient. A processing technique is then applied in order to filter the data and produce Fast Fourier Transform (FFT) data of magnitude versus frequency. If a bell curve is identified in the data between a predefined frequency range (e.g., 50 and 80 Hz) with a peak magnitude of greater than a predefined threshold (e.g., 2.5 units), the system automatically provides an output indicating that the patient is likely to have 50 to 99 percent stenosis of the coronary artery. If no bell curve is present, the patient may have artery stenosis of less than 50 percent. An interface module may be used to transfer diagnosis information to the stethoscope and data to a general purpose computer. This inexpensive and quick system may improve the chances for early detection and patient survival of coronary artery disease.