Detection of coronary artery disease using an electronic stethoscope
First Claim
1. A method for detecting coronary artery disease using an electronic stethoscope, the method comprising:
- recording acoustic data with an electronic stethoscope having an acoustic sensor placed over a fourth left intercostal space of a patient'"'"'s chest;
applying one or more filters to the acoustic data and calculating a Fast Fourier Transform (FFT) of the data to produce FFT data;
analyzing the FFT data to detect a bell curve within a predefined frequency range of 50 and 80 Hz indicative of coronary artery disease; and
generating an output on a display when the bell curve is detected to indicate that the patient is likely to have coronary artery disease.
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Abstract
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.
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Citations
24 Claims
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1. A method for detecting coronary artery disease using an electronic stethoscope, the method comprising:
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recording acoustic data with an electronic stethoscope having an acoustic sensor placed over a fourth left intercostal space of a patient'"'"'s chest; applying one or more filters to the acoustic data and calculating a Fast Fourier Transform (FFT) of the data to produce FFT data; analyzing the FFT data to detect a bell curve within a predefined frequency range of 50 and 80 Hz indicative of coronary artery disease; and generating an output on a display when the bell curve is detected to indicate that the patient is likely to have coronary artery disease. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18)
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19. An electronic stethoscope comprising:
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a display; an acoustic sensor; one or more memories that stores acoustic data from the acoustic sensor placed over a fourth left intercostal space of a patient'"'"'s chest and instructions for processing the acoustic data; and a processor that applies one or more filters to the acoustic data and calculates a Fast Fourier Transform (FFT) of the data to produce FFT data, wherein the processor analyzes the FFT data to detect a bell curve having an onset on or after 50 Hz and a downslope at or before 80 Hz, and generates an output on the display when the bell curve is detected to indicate that the patient is likely to have coronary artery disease. - View Dependent Claims (20, 21, 22)
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23. A computer-readable medium comprising instructions to cause an electronic stethoscope having a processor to:
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record acoustic data with an electronic stethoscope having an acoustic sensor placed over a fourth left intercostal space of a patient'"'"'s chest; apply one or more filters to the acoustic data and calculates a Fast Fourier Transform (FFT) of the data to produce FFT data; analyze the FFT data to detect a bell curve between 50 and 80 Hz; and generate an output on a display when the bell curve is detected to indicate that the patient is likely to have coronary artery disease.
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24. A method for detecting coronary artery disease using an electronic stethoscope, the method comprising:
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recording acoustic data with an electronic stethoscope having an acoustic sensor placed over a fourth left intercostal space of a patient'"'"'s chest; applying one or more filters to the acoustic data and calculating a Fast Fourier Transform (FET) of the data to produce FFT data; displaying a graph of the FFT data for manual diagnosis including plotting harmonic magnitudes on the y-axis and plotting harmonic frequencies on the x-axis; analyzing the FFT data to detect a bell curve within a predefined frequency range indicative of coronary artery disease; and generating an output on a display when the bell curve is detected to indicate that the patient is likely to have coronary artery disease.
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Specification