CN116364117A - Low-frequency electronic auscultation system based on sound vibration microphone - Google Patents
Low-frequency electronic auscultation system based on sound vibration microphone Download PDFInfo
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- 239000011159 matrix material Substances 0.000 claims abstract description 10
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- G—PHYSICS
- G10—MUSICAL INSTRUMENTS; ACOUSTICS
- G10L—SPEECH ANALYSIS OR SYNTHESIS; SPEECH RECOGNITION; SPEECH OR VOICE PROCESSING; SPEECH OR AUDIO CODING OR DECODING
- G10L25/00—Speech or voice analysis techniques not restricted to a single one of groups G10L15/00 - G10L21/00
- G10L25/48—Speech or voice analysis techniques not restricted to a single one of groups G10L15/00 - G10L21/00 specially adapted for particular use
- G10L25/51—Speech or voice analysis techniques not restricted to a single one of groups G10L15/00 - G10L21/00 specially adapted for particular use for comparison or discrimination
- G10L25/66—Speech or voice analysis techniques not restricted to a single one of groups G10L15/00 - G10L21/00 specially adapted for particular use for comparison or discrimination for extracting parameters related to health condition
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- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B5/00—Measuring for diagnostic purposes; Identification of persons
- A61B5/48—Other medical applications
- A61B5/4803—Speech analysis specially adapted for diagnostic purposes
-
- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B7/00—Instruments for auscultation
- A61B7/02—Stethoscopes
- A61B7/04—Electric stethoscopes
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- G—PHYSICS
- G10—MUSICAL INSTRUMENTS; ACOUSTICS
- G10L—SPEECH ANALYSIS OR SYNTHESIS; SPEECH RECOGNITION; SPEECH OR VOICE PROCESSING; SPEECH OR AUDIO CODING OR DECODING
- G10L25/00—Speech or voice analysis techniques not restricted to a single one of groups G10L15/00 - G10L21/00
- G10L25/03—Speech or voice analysis techniques not restricted to a single one of groups G10L15/00 - G10L21/00 characterised by the type of extracted parameters
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- G—PHYSICS
- G10—MUSICAL INSTRUMENTS; ACOUSTICS
- G10L—SPEECH ANALYSIS OR SYNTHESIS; SPEECH RECOGNITION; SPEECH OR VOICE PROCESSING; SPEECH OR AUDIO CODING OR DECODING
- G10L25/00—Speech or voice analysis techniques not restricted to a single one of groups G10L15/00 - G10L21/00
- G10L25/27—Speech or voice analysis techniques not restricted to a single one of groups G10L15/00 - G10L21/00 characterised by the analysis technique
- G10L25/30—Speech or voice analysis techniques not restricted to a single one of groups G10L15/00 - G10L21/00 characterised by the analysis technique using neural networks
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04R—LOUDSPEAKERS, MICROPHONES, GRAMOPHONE PICK-UPS OR LIKE ACOUSTIC ELECTROMECHANICAL TRANSDUCERS; DEAF-AID SETS; PUBLIC ADDRESS SYSTEMS
- H04R1/00—Details of transducers, loudspeakers or microphones
- H04R1/46—Special adaptations for use as contact microphones, e.g. on musical instrument, on stethoscope
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04R—LOUDSPEAKERS, MICROPHONES, GRAMOPHONE PICK-UPS OR LIKE ACOUSTIC ELECTROMECHANICAL TRANSDUCERS; DEAF-AID SETS; PUBLIC ADDRESS SYSTEMS
- H04R19/00—Electrostatic transducers
- H04R19/04—Microphones
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04R—LOUDSPEAKERS, MICROPHONES, GRAMOPHONE PICK-UPS OR LIKE ACOUSTIC ELECTROMECHANICAL TRANSDUCERS; DEAF-AID SETS; PUBLIC ADDRESS SYSTEMS
- H04R2201/00—Details of transducers, loudspeakers or microphones covered by H04R1/00 but not provided for in any of its subgroups
- H04R2201/003—Mems transducers or their use
Abstract
The invention discloses a low-frequency electronic auscultation system based on an acoustic vibration microphone, which comprises: the low-frequency heart sound collecting stethoscope head is provided with a filtering communication display module and a low-frequency sound signal analysis module which are arranged on the upper computer; the low-frequency heart sound collecting stethoscope head is used for collecting heart sound and sound vibration signals in real time based on the sound vibration MEMS microphone; the filtering communication display module is used for obtaining frequency domain signals through filtering processing and Fourier transformation on the heart sound and sound vibration signals acquired in real time and displaying related heart sound waveforms to be analyzed; the low-frequency sound signal analysis module is used for extracting features of heart sounds to be analyzed after Fourier transformation to obtain a low-frequency heart sound feature matrix, and obtaining relevant parameters of the vascular stenosis condition through correlation analysis. The stethoscope head design of the present invention may be used for the detection of wider heart sounds, including infrasound; and (3) carrying out automatic analysis of heart sounds by combining a frequency spectrum analysis method with a neural network, and providing intermediate data for relevant screening and analysis.
Description
Technical Field
The invention belongs to the technical field of medical instruments, and particularly relates to a low-frequency electronic auscultation system based on an acoustic vibration microphone.
Background
The prior art has only been concerned with conventional electronic stethoscopes.
The current electronic stethoscopes have gradually been applied to auscultation and analysis of heart sounds, and as the auscultation principle is still based on the traditional stethoscopes, how to develop a novel stethoscope capable of better detecting heart-related diseases is of great importance. At present, an infrasound auscultation instrument and an analysis method based on a silicon-based MEMS low-frequency sound vibration sensor are not available internationally. Conventional stethoscopes can perform conventional heart sound diagnosis on sound transmission of heart sounds, but because they must be checked by a professional doctor and a patient must go to a hospital to perform the related detection, the patient takes time and effort to perform preliminary screening only. The existing electronic stethoscope has the problems that the signal difference and the signal-to-noise ratio are low in the collection of heart sounds, and the diagnosis of low-frequency heart sound signals with the frequency lower than 20Hz cannot be carried out, and a novel instrument and a novel system for carrying out wider frequency band collection and analysis methods, including the infrasound emitted by the heart, are lacked, so that the heart and cardiovascular health condition of a patient are comprehensively analyzed.
Disclosure of Invention
The invention aims to overcome the defects of the prior art, and provides a low-frequency electronic auscultation system based on an acoustic vibration microphone, which can provide intermediate data for early diagnosis of subsequent coronary heart disease and cardiovascular stenosis.
In order to achieve the above object, the present invention proposes a low-frequency electronic auscultation system based on an acoustic vibration microphone, the system comprising: the low-frequency heart sound collecting stethoscope head is provided with a filtering communication display module and a low-frequency sound signal analysis module which are arranged on the upper computer; wherein, the liquid crystal display device comprises a liquid crystal display device,
the low-frequency heart sound collecting stethoscope head is used for collecting heart sound and sound vibration signals in real time based on the sound vibration MEMS microphone;
the filtering communication display module is used for obtaining frequency domain signals through filtering processing and Fourier transformation on the heart sound and sound vibration signals acquired in real time and displaying related heart sound waveforms to be analyzed;
the low-frequency sound signal analysis module is used for extracting features of heart sounds to be analyzed after Fourier transformation to obtain a low-frequency heart sound feature matrix, and obtaining relevant parameters of the vascular stenosis condition through correlation analysis.
As an improvement of the above system, the low frequency heart sound collection stethoscope head comprises an acoustic vibration sensor and a resonant diaphragm; the sound vibration sensor is arranged inside the stethoscope head and fixed on the resonant diaphragm, a sound pick-up hole is formed in the sound vibration sensor, and a resonant cavity is formed inside the stethoscope head.
As an improvement of the system, the system also comprises a signal conditioning packaging module electrically connected with the low-frequency heart sound collecting stethoscope head, and the signal conditioning packaging module is used for preprocessing the electric signals collected by the stethoscope head in real time through a filtering and amplifying circuit.
As an improvement of the system, the filtering communication display module receives the electric signals preprocessed by the signal conditioning packaging module in a wired or wireless communication mode, and the wireless communication mode comprises Bluetooth and GPRS.
As an improvement of the system, the filtering processing adopted by the filtering communication display module comprises a low-pass filtering algorithm, a band-pass filtering algorithm, a high-pass filtering algorithm, a wavelet transformation algorithm and a chebyshev algorithm.
As an improvement of the above system, the processing procedure of the low-frequency acoustic signal analysis module specifically includes:
the standard low-frequency heart sound signals after Fourier transformation and the heart sounds to be analyzed are input into a pre-established and trained feature extraction model to carry out low-frequency feature heart sound extraction, so that a low-frequency feature heart sound matrix is formed;
based on the low-frequency characteristic heart sound matrix, obtaining a low-frequency heart sound signal curve, heart sound peak and trough position degree, heart sound scale energy and frequency distribution of a frequency spectrum signal, inputting a pre-established and trained correlation model for correlation analysis, and obtaining blood vessel stenosis position degree information and blood vessel stenosis degree correlation parameters.
As an improvement of the above system, the feature extraction model and the correlation model are both neural networks.
Compared with the prior art, the invention has the advantages that:
the auscultation head design based on the sound vibration MEMS microphone can be used for detecting wider heart sounds including infrasound; the heart sound and low-frequency sound signals can be processed and analyzed, and the heart sound is automatically analyzed by a frequency spectrum analysis method and by combining a neural network, deep learning and other methods in artificial intelligence; and providing intermediate data for early screening and analysis of heart diseases, coronary heart diseases and cardiovascular stenosis in the later stage according to the acquired heart sound and infrasound signals.
Drawings
FIG. 1 is a block diagram of a low frequency electronic auscultation system based on a sound vibration microphone in accordance with the present invention;
FIG. 2 is a schematic diagram of a low frequency heart sound acquisition stethoscope head according to the present invention;
FIG. 3 is a schematic diagram of a signal conditioning package module of the present invention;
FIG. 4 is a schematic diagram of waveforms obtained by using the filtered communication display module of the present invention, wherein FIG. 4 (a) is a graph of amplitude versus time and FIG. 4 (b) is a graph of amplitude versus frequency;
fig. 5 is a diagram showing analysis and extraction of heart sound low-frequency signals output and displayed by the low-frequency sound signal analysis module according to the present invention, wherein fig. 5 (a) is an initial signal amplitude-sampling time diagram, fig. 5 (b) is a low-frequency sound signal amplitude-frequency diagram, and fig. 5 (c) is an amplitude-time diagram of a low-frequency sound signal obtained after inverse fourier transformation;
FIG. 6 is a system process flow diagram of the present invention;
fig. 7 is a flow chart of the processing of the low-frequency acoustic signal analysis module of the present invention.
Reference numerals
1. Resonant cavity 2, pickup hole 3 and acoustic vibration sensor
4. Resonant film 5, signal conditioning packaging shell 6 and signal filtering amplifying circuit
7. Electronic component circuit board
Detailed Description
The technical scheme of the invention is described in detail below with reference to the accompanying drawings and examples.
Examples
As shown in fig. 1, an embodiment of the present invention proposes a low-frequency electronic auscultation system based on a sound vibration microphone, the system comprising: the low-frequency heart sound collecting stethoscope head is provided with a filtering communication display module and a low-frequency sound signal analysis module which are arranged on the upper computer; wherein, the liquid crystal display device comprises a liquid crystal display device,
the low-frequency heart sound collecting stethoscope head is used for collecting heart sound and sound vibration signals in real time based on the sound vibration MEMS microphone;
the signal conditioning packaging module is used for preprocessing the electric signals acquired by the stethoscope head in real time through the filtering amplifying circuit;
the filtering communication display module is used for obtaining frequency domain signals through filtering processing and Fourier transformation on the heart sound and sound vibration signals acquired in real time and displaying related heart sound waveforms to be analyzed;
the low-frequency sound signal analysis module is used for extracting the characteristics of heart sounds to be analyzed after Fourier transformation to obtain a low-frequency heart sound characteristic matrix, and obtaining relevant parameters of the vascular stenosis condition through correlation analysis.
Specific analyses were performed as follows:
1) Low frequency signal acquisition stethoscope head: the low-frequency signal of the sound vibration MEMS microphone comprises a infrasound acquisition function, and the structure of a stethoscope and the acquisition position information of heart sound signals are selected to acquire heart sound and low-frequency sound signals in real time
The low frequency heart sound collecting stethoscope head as shown in fig. 2 comprises: a resonant cavity 1, a pickup hole 2, an acoustic vibration sensor 3 and a resonant membrane 4. The signal acquisition module mainly controls auscultation modes by means of the placement positions of the sensors, when heart sounds and vibration signals are acquired, the direct conduction auscultation mode is adopted, the sound vibration sensor 3 is fixedly connected to the resonant film 4 of the auscultation head, when the heart sound signals are driven by the resonant film 4 to be directly conducted to the receiving end of the sensor, and the heart sound signals are transmitted to the pick-up hole 2 of the sensor after echoes are gathered through the resonant cavity 1.
2) The signal conditioning package module, as shown in fig. 3, includes: a signal conditioning package shell 5, a signal filtering and amplifying circuit 6 and an electronic component circuit board 7. For weak electric signals acquired by the low-frequency heart sound stethoscope head, the signals obtained are filtered and amplified through a signal transmission line by a signal filtering and amplifying circuit 6 embedded on an electronic component circuit board 7, and the signals are integrally packaged in a signal conditioning packaging shell 5.
3) And the filtering communication display module is used for: the filtering and amplifying circuit module is used for transmitting data and displaying signals of the upper computer, and performing frequency spectrum analysis according to Fourier transformation, wherein the frequency spectrum analysis comprises conventional heart sound signals and low-frequency sound signals;
as shown in fig. 4, a schematic waveform diagram obtained by using the filtering communication display module of the present invention is shown, wherein fig. 4 (a) is a magnitude-time diagram and fig. 4 (b) is a magnitude-frequency diagram; comprising the following steps: and displaying a time-series curve of the transmitted data on the upper computer, and analyzing and filtering by adopting a filtering algorithm when the curve characteristic is obtained so as to obtain the better curve characteristic, wherein the frequency characteristic of the curve is obtained before filtering by Fourier transformation, and the low-frequency signal in the signal acquisition result is confirmed, and the filtering algorithm comprises: low pass, band pass, and high pass filtering algorithms, wavelet transform algorithms, chebyshev algorithms, and the like.
4) The low-frequency sound signal analysis module: the heart sound signal is automatically analyzed through the spectrum display of heart sound and infrasound signals by an artificial intelligence method, and the analysis model uses different algorithms including neural network, machine learning, deep learning and the like. Early screening and correlation analysis models of heart disease, coronary heart disease and cardiovascular stenosis are performed, including conventional heart sound disease signal analysis and detection of cardiovascular related parameters of low frequency acoustic signals.
As shown in fig. 5, fig. 5 is a diagram showing an analysis and extraction of a heart sound low-frequency signal output and displayed by the low-frequency sound signal analysis module according to the present invention, wherein fig. 5 (a) is an initial signal amplitude-sampling time diagram, fig. 5 (b) is a low-frequency sound signal amplitude-frequency diagram, and fig. 5 (c) is an amplitude-time diagram of a low-frequency sound signal obtained after inverse fourier transformation;
the heart sound signal is automatically analyzed through the spectrum display of heart sound and infrasound signals by an artificial intelligence method, and the analysis model uses different algorithms including neural network, machine learning, deep learning and the like. According to the characteristic extraction of the low-frequency signals in the spectrogram, the time sequence curve reduction of the low-frequency acoustic signals can be performed, and the effective theoretical basis for analyzing heart diseases, coronary heart diseases and cardiovascular stenosis by the low-frequency acoustic signals is provided.
A system process flow diagram of the present invention is shown in fig. 6. The signal sampling and noise elimination are realized through the preprocessing of the heart sound and the low-frequency sound signals, and the low-frequency sound heart sound decomposition can be carried out; the characteristic extraction of heart sound and low-frequency signals, the data in a fixed domain is selected through a window function, an artificial intelligence method is carried out to automatically divide the heart sound signals, and different algorithms including a neural network, machine learning, deep learning and the like are used for an analysis model, so that the low-frequency sound heart sound data extraction is realized; the output data is taken as intermediate data, and if statistical analysis is carried out, a basis can be provided for early screening and relevance analysis models of heart diseases, coronary heart diseases and cardiovascular stenosis in the later stage. Statistical analysis such as low frequency sound noise and normal heart sound difference statistics, cardiovascular disease and normal person low frequency sound heart sound difference analysis, cardiovascular stenosis degree and infrasound heart sound characteristic difference analysis, etc. In addition, the output data can also provide intermediate data for early nondestructive testing and screening of cardiovascular, such as analysis of heart low-frequency infrasound and coronary heart disease characteristic parameters, coronary artery stenosis degree characteristic parameters and the like. The method specifically comprises the following steps:
for example, a neural network is adopted, and a low-frequency characteristic heart sound is extracted by inputting a standard low-frequency heart sound signal after Fourier transformation and a characteristic extraction model which is pre-established and trained for heart sound to be analyzed, so as to form a low-frequency characteristic heart sound matrix;
and 3, performing feature extraction of heart sounds and low-frequency signals, namely selecting data in a fixed domain through a window function, acquiring a low-frequency heart sound signal curve, heart sound peak and trough position degree, heart sound scale energy and frequency spectrum signal frequency distribution based on a low-frequency feature heart sound matrix, inputting a pre-established and trained correlation model for correlation analysis, and obtaining vascular stenosis position degree information and vascular stenosis degree correlation parameters. The correlation model may be implemented by a neural network.
Finally, it should be noted that the above embodiments are only for illustrating the technical solution of the present invention and are not limiting. Although the present invention has been described in detail with reference to the embodiments, it should be understood by those skilled in the art that modifications and equivalents may be made thereto without departing from the spirit and scope of the present invention, which is intended to be covered by the appended claims.
Claims (7)
1. A low frequency electronic auscultation system based on a vibro-acoustic microphone, the system comprising: the low-frequency heart sound collecting stethoscope head is provided with a filtering communication display module and a low-frequency sound signal analysis module which are arranged on the upper computer; wherein, the liquid crystal display device comprises a liquid crystal display device,
the low-frequency heart sound collecting stethoscope head is used for collecting heart sound and sound vibration signals in real time based on the sound vibration MEMS microphone;
the filtering communication display module is used for obtaining frequency domain signals through filtering processing and Fourier transformation on the heart sound and sound vibration signals acquired in real time and displaying related heart sound waveforms to be analyzed;
the low-frequency sound signal analysis module is used for extracting features of heart sounds to be analyzed after Fourier transformation to obtain a low-frequency heart sound feature matrix, and obtaining relevant parameters of the vascular stenosis condition through correlation analysis.
2. The low-frequency electronic auscultation system based on sound vibration microphones according to claim 1, characterized in that the low-frequency heart sound collection stethoscope head comprises a sound vibration sensor (3) and a resonance membrane (4); the sound vibration sensor (3) is arranged inside the stethoscope head and fixed on the resonant diaphragm (4), the sound vibration sensor (3) is provided with a sound pick-up hole (2), and a resonant cavity (1) is formed inside the stethoscope head.
3. The system of claim 1, further comprising a signal conditioning package module electrically connected to the low frequency heart sound collection stethoscope head for preprocessing the real-time collected electrical signals of the stethoscope head through a filtering and amplifying circuit.
4. The system of claim 3, wherein the filtering communication display module receives the electrical signal preprocessed by the signal conditioning and packaging module by wired or wireless communication, and the wireless communication includes bluetooth and GPRS.
5. The system of claim 1, wherein the filtering process performed by the filtering communication display module includes a low pass, a band pass, a high pass filtering algorithm, a wavelet transform algorithm, and a chebyshev algorithm.
6. The system of claim 5, wherein the processing of the low frequency acoustic signal analysis module comprises:
the standard low-frequency heart sound signals after Fourier transformation and the heart sounds to be analyzed are input into a pre-established and trained feature extraction model to carry out low-frequency feature heart sound extraction, so that a low-frequency feature heart sound matrix is formed;
based on the low-frequency characteristic heart sound matrix, obtaining a low-frequency heart sound signal curve, heart sound peak and trough position degree, heart sound scale energy and frequency distribution of a frequency spectrum signal, inputting a pre-established and trained correlation model for correlation analysis, and obtaining blood vessel stenosis position degree information and blood vessel stenosis degree correlation parameters.
7. The acoustic microphone based low frequency electronic auscultation system of claim 6, wherein the feature extraction model and the correlation model are both neural networks.
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| 孔春秀: "基于 MEMS 声振传感器的电子听诊器", 传感技术学报, vol. 34, no. 8, pages 1140 - 1142 * |
| 康宇琪: "MEMS电子听诊器信号采集传输系统", 电子器件, vol. 42, no. 06 * |
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