CN111543947B - Traditional Chinese medicine sound diagnosis method and system - Google Patents
Traditional Chinese medicine sound diagnosis method and system Download PDFInfo
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Abstract
The invention relates to a traditional Chinese medicine sound diagnosis method and system, and mainly relates to the field of sound diagnosis methods. The method comprises the steps of obtaining a voice signal of a pre-diagnosis case, extracting characteristic information in the voice signal, comparing and matching the characteristic information of the pre-diagnosis case with the characteristic information of a pre-storage case base, namely respectively matching the amplitude information, the frequency spectrum information and the power information of the pre-diagnosis case with the amplitude information, the frequency spectrum information and the power information of the pre-storage case base in a database, and outputting a diagnosis report of the pre-diagnosis case according to the matching degree of the amplitude information, the frequency spectrum information and the power information.
Description
Technical Field
The invention relates to the field of sound diagnosis methods, in particular to a traditional Chinese medicine sound diagnosis method and system.
Background
The sound diagnosis is one of the four diagnostic methods of the Chinese medicine, i.e., the diagnosis of diseases by examining the sound produced by the patient by means of the sense of hearing. Clinically, the auscultation and auscultation are combined with the inspection, inquiry and palpation to comprehensively and systematically understand the condition of an illness and make a correct judgment on the disease, and the auscultation and auscultation of traditional Chinese medicine accumulate deep experience and further enrich the theory, so the auscultation and auscultation has a very high value for the clinical diagnosis of modern medicine.
In the prior art, doctors generally make a diagnosis for patients according to experience and knowledge by examining the size, height and clarity of the voice of the patients and distinguishing cold, heat, deficiency and excess.
However, the above-mentioned method of diagnosing by voice is too dependent on the inherent experience of the doctor, which is not favorable for the wide popularization and application of the theory of traditional Chinese medicine, and the diagnosis is performed by only depending on the experience and knowledge of the doctor, so the subjective consciousness is too strong, and misdiagnosis is easy to occur.
Disclosure of Invention
The invention aims to provide a method and a system for the sound diagnosis of traditional Chinese medicine, aiming at overcoming the defects in the prior art, and solving the problems that the sound diagnosis method in the prior art depends too much on the inherent experience of doctors, is not beneficial to the wide popularization and application of the traditional Chinese medicine theory, and the diagnosis is carried out by only depending on the experience and knowledge of doctors, so that the subjective consciousness is too strong, and the misdiagnosis is easy to generate.
In order to achieve the above purpose, the embodiment of the present invention adopts the following technical solutions:
in a first aspect, the present application provides a method for acoustic diagnosis in traditional Chinese medicine, the method comprising:
acquiring a voice signal of a pre-diagnosis case;
extracting characteristic information in the voice signal, wherein the characteristic information comprises amplitude information, frequency spectrum information and power information;
comparing and matching the characteristic information of the pre-diagnosis case with the characteristic information of each case in the pre-stored case library;
and obtaining a diagnosis report of the pre-diagnosis case according to the comparison and matching result.
Optionally, the step of obtaining the voice signal of the pre-diagnosis case further comprises:
and converting the collected voice signals of the pre-diagnosis cases into digital signals.
Optionally, the step of extracting feature information in the speech signal includes:
amplitude information, frequency information, spectrum information and power information in the digital signal converted from the voice signal are extracted by using a time domain analysis method or a frequency domain analysis method.
Optionally, the step of comparing and matching the feature information of the pre-diagnosis case with the feature information of the pre-stored case library includes:
and comparing the amplitude information, the frequency spectrum information and the power information of the pre-diagnosis cases with the amplitude information, the frequency spectrum information and the power information of each case in the pre-storage case library to respectively obtain the matching degree of the amplitude information, the frequency spectrum information and the power information of each case and the pre-diagnosis cases.
Optionally, the step of obtaining a diagnosis report of the pre-diagnosis case according to the comparison and matching result includes:
calculating the matching degree of the amplitude information, the frequency spectrum information and the power information of each case in the pre-diagnosis case and the pre-storage case library, and arranging the calculated matching degree according to a certain sequence;
and outputting the disease types of the cases in the pre-stored case library corresponding to the matching degree of the rearranged pre-diagnosis cases and the pre-stored case library as diagnosis reports.
Optionally, the step of obtaining a diagnosis report according to the comparison and matching result further includes:
and storing the pre-diagnosis cases and amplitude information, frequency spectrum information and power information corresponding to the pre-diagnosis cases.
In a second aspect, the present application provides a system for acoustic diagnosis in traditional chinese medicine, the system comprising: the system comprises an acquisition module, an extraction module, a matching module and a diagnosis module;
the acquisition module is used for acquiring the voice signal of the pre-diagnosis case;
the extraction module is used for extracting characteristic information in the voice signal, wherein the characteristic information comprises frequency spectrum information and power information;
the matching module is used for comparing and matching the characteristic information of the pre-diagnosed case with the characteristic information of each case in the pre-stored case library;
and the diagnosis module is used for obtaining a diagnosis report of the pre-diagnosis case according to the comparison and matching result.
Optionally, the system further includes a conversion module, and the conversion module is configured to convert the collected voice signal of the pre-diagnosis case into a digital signal.
Optionally, the extracting module is specifically configured to extract amplitude information, frequency information, spectrum information, and power information in the digital signal converted from the speech signal by using a time domain analysis method or a frequency domain analysis method.
Optionally, the matching module is specifically configured to compare the amplitude information, the frequency information, the spectrum information, and the power information of the pre-diagnosis case with the amplitude information, the frequency information, the spectrum information, and the power information of each case in the pre-storage case library, and obtain the matching degree of the amplitude information, the frequency information, the spectrum information, and the power information of each case and the pre-diagnosis case, respectively.
Optionally, the output module is specifically configured to calculate matching degrees of the amplitude information, the frequency information, the spectrum information, and the power information of each pre-diagnosis case and each case in the pre-storage case library, and arrange the calculated matching degrees in a certain order;
and outputting the disease types of the cases in the pre-stored case library corresponding to the matching degree of the rearranged pre-diagnosis cases and the pre-stored case library as diagnosis reports.
Optionally, the system further includes a storage module, and the storage module is configured to store the pre-diagnosis cases and amplitude, frequency spectrum, and power information corresponding to the pre-diagnosis cases.
The invention has the beneficial effects that:
the method comprises the steps of obtaining a voice signal of a pre-diagnosis case, extracting characteristic information in the voice signal, comparing and matching the characteristic information of the pre-diagnosis case with the characteristic information of a pre-storage case base, namely respectively matching the amplitude information, the frequency spectrum information and the power information of the pre-diagnosis case with the amplitude information, the frequency spectrum information and the power information of the pre-storage case base in a database, and outputting a diagnosis report of the pre-diagnosis case according to the matching degree of the amplitude information, the frequency spectrum information and the power information.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings needed to be used in the embodiments will be briefly described below, it should be understood that the following drawings only illustrate some embodiments of the present invention and therefore should not be considered as limiting the scope, and for those skilled in the art, other related drawings can be obtained according to the drawings without inventive efforts.
Fig. 1 is a schematic structural diagram of a traditional Chinese medicine acoustic diagnosis system provided in an embodiment of the present invention;
FIG. 2 is a schematic flow chart of a method for acoustic diagnosis in traditional Chinese medicine according to an embodiment of the present invention;
FIG. 3 is a schematic flow chart of another method for acoustic diagnosis in traditional Chinese medicine according to an embodiment of the present invention;
fig. 4 is a schematic block diagram of a system for acoustic diagnosis in traditional Chinese medicine according to an embodiment of the present invention;
fig. 5 is a schematic block diagram of a system for acoustic diagnosis in traditional Chinese medicine according to an embodiment of the present invention;
fig. 6 is a schematic block diagram of a system for acoustic diagnosis in traditional Chinese medicine according to an embodiment of the present invention.
Detailed Description
In order to make the purpose, technical solutions and advantages of the embodiments of the present application clearer, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application, and it should be understood that the drawings in the present application are for illustrative and descriptive purposes only and are not used to limit the scope of protection of the present application. Additionally, it should be understood that the schematic drawings are not necessarily drawn to scale. The flowcharts used in this application illustrate operations implemented according to some embodiments of the present application. It should be understood that the operations of the flow diagrams may be performed out of order, and steps without logical context may be performed in reverse order or simultaneously. One skilled in the art, under the guidance of this application, may add one or more other operations to, or remove one or more operations from, the flowchart.
In addition, the described embodiments are only a part of the embodiments of the present application, and not all of the embodiments. The components of the embodiments of the present application, as generally described and illustrated in the figures herein, could be arranged and designed in a wide variety of different configurations. Thus, the following description of the embodiments of the present application, provided in the accompanying drawings, is not intended to limit the scope of the claimed application, but is merely representative of selected embodiments of the application. All other embodiments, which can be derived by a person skilled in the art from the embodiments of the present application without making any creative effort, shall fall within the protection scope of the present application.
It should also be noted that the term "comprising" will be used in the embodiments of the present application to indicate the presence of the features stated hereinafter, but does not exclude the addition of further features.
Fig. 1 is a schematic structural diagram of a traditional Chinese medicine acoustic diagnosis system according to an embodiment of the present invention. As shown in fig. 1, the system includes: the system comprises a main server 10, a computer 20, a collection device 30 and an output device 40, wherein the collection device 30, the output device 40 and the main server 10 are respectively in communication connection with the computer 20, the collection device 30 can be a sound sensor or a microphone in general, a sound card is arranged in the computer 20 and used for converting a voice signal into a digital signal, and software for processing the digital signal is arranged in the computer 20 and used for processing the digital signal converted from the voice signal.
In some embodiments, the host server 10 may be a processor. In some embodiments, a processor may include one or more processing cores (e.g., a single-core processor (S) or a multi-core processor (S)). Merely by way of example, a Processor may include a Central Processing Unit (CPU), an Application Specific Integrated Circuit (ASIC), an Application Specific Instruction Set Processor (ASIP), a Graphics Processing Unit (GPU), a Physical Processing Unit (PPU), a Digital Signal Processor (DSP), a Field Programmable Gate Array (FPGA), a Programmable Logic Device (PLD), a controller, a microcontroller Unit, a Reduced Instruction Set computer 20 (Reduced Instruction Set Computing, RISC), a microprocessor, or the like, or any combination thereof.
The above system further comprises: the network, the database, the collecting device 30, the output device 40 and the main server 10 are respectively connected with the computer 20 through the network, and the main server 10 is provided with a corresponding first database. The network may be used for the exchange of information and/or data. In some embodiments, one or more components in the user behavior analysis system (e.g., host server 10 may be connected to multiple computers 20 for processing requests of multiple computers 20). In some embodiments, the network may be any type of wired or wireless network, or combination thereof. Merely by way of example, the Network may include a wired Network, a Wireless Network, a fiber optic Network, a telecommunications Network, an intranet, the internet, a Local Area Network (LAN), a Wide Area Network (WAN), a Wireless Local Area Network (WLAN), a Metropolitan Area Network (MAN), a Wide Area Network (WAN), a Public Switched Telephone Network (PSTN), a bluetooth Network, a ZigBee Network, a Near Field Communication (NFC) Network, or the like, or any combination thereof. In some embodiments, the network may include one or more network access points. For example, the network may include wired or wireless network access points, such as base stations and/or network switching nodes, through which one or more components of the service data prediction system may connect to the network to exchange data and/or information.
The first database is used to store data and/or instructions for the main server 10. In some embodiments, the first database may store the obtained information and/or data. In some embodiments, the first database may store data and/or instructions of the exemplary methods described herein. In some embodiments, the first database may include mass storage, removable storage, volatile Read-write Memory, read-Only Memory (ROM), or the like, or any combination thereof. By way of example, mass storage may include magnetic disks, optical disks, solid state drives, and the like; removable memory may include flash drives, floppy disks, optical disks, memory cards, zip disks, tapes, and the like; volatile read-write Memory may include Random Access Memory (RAM); the RAM may include Dynamic RAM (DRAM), double data Rate synchronous Dynamic RAM (DDR SDRAM); static RAM (SRAM), thyristor-Based Random Access Memory (T-RAM), zero-capacitor RAM (Zero-RAM), and the like. By way of example, ROMs may include Mask Read-Only memories (MROMs), programmable ROMs (PROMs), erasable Programmable ROMs (PERROMs), electrically Erasable Programmable ROMs (EEPROMs), compact disk ROMs (CD-ROMs), digital versatile disks (ROMs), and the like. In some embodiments, the first database may be implemented on a cloud platform. By way of example only, the cloud platform may include a private cloud, a public cloud, a hybrid cloud, a community cloud, a distributed cloud, across clouds, multiple clouds, or the like, or any combination thereof.
In some embodiments, the first database may be connected to a network to communicate with one or more components in the user behavior analysis system. One or more components in the user behavior analysis system may access data or instructions stored in the first database via a network. In some embodiments, the first database may be directly connected to one or more components in the user behavior analysis system; alternatively, in some embodiments, the first database may also be part of the host server 10.
FIG. 2 is a schematic flow chart of a method for acoustic diagnosis in traditional Chinese medicine according to an embodiment of the present invention; the embodiment of the present application provides a method for acoustic diagnosis in traditional Chinese medicine, as shown in fig. 2, the method includes:
s101, voice signals of the pre-diagnosis case are obtained.
In the actual operation process, in order to avoid the influence of external noise and improve the diagnosis accuracy, the pre-diagnosis case can be in a quiet space and is at the same distance from the microphone or other sound acquisition devices, the sound wave amplitude is prevented from being weakened by the distance, the pre-diagnosis case reads the language on the specified template by the common Chinese language, the specified template can be a sentence consisting of ' palace, quotient, horn, vowel, feather and pinyin ' vowel ', the reading time can be generally set to three minutes in order to obtain more accurate diagnosis results, and in addition, the content of the specified template is beneficial to quantifying the extracted characteristic value and is convenient to classify.
And S102, extracting characteristic information in the voice signal.
The method comprises the steps of extracting characteristic information such as amplitude information, frequency spectrum information and power information of a voice signal of a pre-diagnosis case, wherein the characteristic information in sentences is extracted, a section of sentences with stable tone can be selected for extraction, influence of external factors is avoided, and the power information is power spectrum information.
S103, comparing and matching the characteristic information of the pre-diagnosed case with the characteristic information of each case in the pre-stored case library.
And comparing the characteristic information of the pre-diagnosed case with the characteristic information of each case in the pre-stored case library by using a characteristic comparison method, and then matching according to a comparison result.
And S104, obtaining a diagnosis report of the pre-diagnosis case according to the comparison and matching result.
According to the comparison result of the characteristic information of the pre-diagnosis case, a diagnosis report of the characteristic information is obtained, and it should be noted that the diagnosis report may include a confirmed disease type and a suspected disease type.
Optionally, the step of acquiring the voice signal of the pre-diagnosis case further includes:
and converting the collected voice signals of the pre-diagnosis cases into digital signals.
After the voice signal of the pre-diagnosis case is obtained, the voice signal of the pre-diagnosis case is converted into a digital signal, and characteristic information such as amplitude information, frequency spectrum information and power information of the digital signal corresponding to the voice signal is extracted and compared with the characteristic information of the pre-stored case library.
Optionally, the step of extracting feature information from the speech signal includes: amplitude information, frequency information, spectrum information and power information in the digital signal converted from the voice signal are extracted by using a time domain analysis method or a frequency domain analysis method.
Extracting and analyzing amplitude information, frequency information and the like in a digital signal corresponding to a voice signal by using a time domain analysis method, wherein the frequency domain analysis method is used for analyzing frequency domain characteristics of the voice signal and comprises frequency spectrum information, power information and the like, generally, a stable section in the digital signal corresponding to the voice signal of a pre-diagnosis case can be intercepted, and characteristic extraction is carried out in the stable section; and/or comparing the cepstrum and wavelet analysis characteristics with the characteristic information of the pre-stored case library.
Optionally, the step of comparing and matching the feature information of the pre-diagnosed case with the feature information of each case in the pre-stored case library includes:
and comparing the amplitude information, the frequency spectrum information and the power information of the pre-diagnosis cases with the amplitude information, the frequency spectrum information and the power information of each case in the pre-storage case library to respectively obtain the matching degree of the amplitude information, the frequency spectrum information and the power information of each case and the pre-diagnosis cases.
Because the amplitude information, the frequency spectrum information and the power information can be digitalized, the matching degree of the characteristic information of the pre-diagnosis case and the characteristic information of the pre-storage case library can be obtained; comparing the obtained amplitude information with amplitude information of a pre-stored case library to obtain the matching degree of the amplitude information; comparing the obtained frequency information with frequency information of a pre-stored case library to obtain the matching degree of the frequency information; comparing the acquired frequency spectrum information with frequency spectrum information of a pre-stored case library to acquire the matching degree of the frequency spectrum information; the obtained power information is compared with the power information of the pre-stored case library to obtain the matching degree of the power information, and as the data of each characteristic information of the pre-diagnosed case is certain and the data of the characteristic information of different cases in the pre-stored case library are different, the pre-diagnosed case is matched with each case in the pre-stored case library to obtain a plurality of groups of matching results.
Fig. 3 is a schematic flow chart of another method for acoustic diagnosis in traditional Chinese medicine according to an embodiment of the present invention. Optionally, as shown in fig. 3, the step of obtaining a diagnosis report of the pre-diagnosis case according to the comparison and matching result includes:
s201, calculating the matching degree of the amplitude information, the frequency spectrum information and the power information of each case in the pre-diagnosis case and the pre-storage case library, and arranging the calculated matching degree according to a certain sequence.
When the matching degree is calculated, the matching degree between the pre-diagnosis case and each case in the pre-stored case library respectively can be obtained by using the matching degree of each feature in the feature information to carry out a weighted average method, and since the matching degree is a numerical value finally obtained, if the matching degree between the pre-diagnosis case finally obtained and a plurality of cases in the pre-stored case library is larger than a preset threshold value, the matching degrees between the plurality of cases and the pre-diagnosis case are arranged in a sequence from large to small or from small to large, it needs to be noted that the size of the threshold value is determined according to actual needs, and no specific limitation is made here.
S202, outputting the disease types of the cases in the pre-stored case library corresponding to the matching degree of the rearranged pre-diagnosis cases and the pre-stored case library as diagnosis reports.
After the matching degrees of the multiple cases and the pre-diagnosis case are arranged in the sequence from large to small or from small to large, the disease names corresponding to the multiple matching degrees are also arranged in the pre-storage case base in the sequence of the matching degrees and output, it needs to be noted that if the matching degrees of several disease types are arranged in the sequence from large to small, the pre-diagnosis case has the highest possibility of being the disease type corresponding to the first matching degree, and generally, the disease information corresponding to the pre-storage case with higher matching degree is selected in the pre-storage case base as output.
Optionally, the step of obtaining a diagnosis report according to the comparison and matching result further includes: and storing the pre-diagnosis cases and amplitude information, frequency spectrum information and power information corresponding to the pre-diagnosis cases.
Storing the amplitude information, the frequency spectrum information and the power information corresponding to the pre-diagnosis cases so as to improve the accuracy of diagnosing the pre-diagnosis cases next time, and expanding the case types in the pre-storage case library.
In practical application, for convenience of description, the viral influenza is taken as an example for explanation, a pre-diagnosis case reads contents of a specified template for three minutes by using mandarin, a microphone collects the contents read by the pre-diagnosis case, converts the contents read by the pre-diagnosis case into a digital signal, extracts amplitude information, frequency information, spectrum information and power information of the digital signal corresponding to the voice signal, finds that the amplitude information of the digital signal is 40, the frequency information is 50, the spectrum information is 60 and the power information is 70, and finds that the amplitude information, the frequency information, the spectrum information and the power information of allergic rhinitis in a pre-storage case library are 40, the frequency information is 50, the spectrum information is 60 and the power information is 40 by comparing with the amplitude information, the frequency information, the spectrum information and the power information of the pre-storage case library; if the amplitude information, the frequency information, the spectrum information and the power information of the viral influenza are respectively 75, 50, 60 and 68, the matching degree of the pre-diagnosis case and the viral influenza is calculated to be 0.95, the matching degree of the pre-diagnosis case and the allergic rhinitis is 0.89, if the threshold value is 0.8, and both 0.89 and 0.95 are greater than 0.8, the allergic rhinitis corresponding to 0.89 and the viral influenza corresponding to 0.95 are output as diagnosis reports, and if the matching degrees are output in the order from large to small, the diagnosis reports are 1 and the viral influenza, and the matching degree: 0.95; 2. allergic rhinitis, degree of matching: 0.89.
the method comprises the steps of obtaining voice signals of a pre-diagnosis case, extracting characteristic information in the voice signals, comparing and matching the characteristic information of the pre-diagnosis case with characteristic information of a pre-storage case library, namely respectively matching amplitude information, frequency information, spectrum information and power information of the pre-diagnosis case with the amplitude information, the frequency information, the spectrum information and the power information of the pre-storage case library in a database, and outputting a diagnosis report of the pre-diagnosis case according to the matching degree of the amplitude information, the frequency information, the spectrum information and the power information. The system is based on the traditional Chinese medicine acoustic diagnosis theory, combines the digital signal processing technology, can objectively record and detect the sound signal of a detected person, analyzes the detected sound signal and extracts the characteristics, inputs the extracted characteristics into the built neural network through the artificial intelligence and deep learning technology, obtains the corresponding relation between the sound of the patient and the traditional Chinese medicine symptoms, and improves the diagnosis efficiency and accuracy.
Fig. 4 is a schematic block diagram of a system for acoustic diagnosis in traditional Chinese medicine according to an embodiment of the present invention; as shown in fig. 4, an embodiment of the present application further provides a system for diagnosing a chinese medical sound, which includes: an acquisition module 50, an extraction module 60, a matching module 70 and a diagnostic module 80;
an obtaining module 50, configured to obtain a voice signal of a pre-diagnosis case;
an extracting module 60, configured to extract feature information in the voice signal, where the feature information includes frequency spectrum information and power information;
the matching module 70 is used for comparing and matching the characteristic information of the pre-diagnosed case with the characteristic information of each case in the pre-stored case library;
and the diagnosis module 80 is used for obtaining a diagnosis report of the pre-diagnosis case according to the comparison and matching result.
Fig. 5 is a schematic block diagram of a system for acoustic diagnosis in traditional Chinese medicine according to an embodiment of the present invention; as shown in fig. 5, the system optionally further includes a conversion module 90, which is configured to convert the collected voice signals of the pre-diagnosis cases into digital signals.
Optionally, the extracting module 60 is specifically configured to extract amplitude information, frequency information, spectrum information, and power information in the digital signal converted from the speech signal by using a time domain analysis method or a frequency domain analysis method.
Optionally, the matching module 70 is specifically configured to compare the amplitude information, the frequency information, the spectrum information, and the power information of the pre-diagnosis case with the amplitude information, the frequency information, the spectrum information, and the power information of each case in the pre-storage case library, and obtain the matching degree of the amplitude information, the frequency information, the spectrum information, and the power information of each case and the pre-diagnosis case respectively.
Optionally, the diagnosis module 80 is specifically configured to calculate matching degrees of the pre-diagnosed case and amplitude information, frequency information, spectrum information, and power information of each case in the pre-stored case library, and arrange the calculated matching degrees in a certain order;
and outputting the disease types of the cases in the pre-stored case library corresponding to the matching degree of the rearranged pre-diagnosis cases and the pre-stored case library as diagnosis reports.
Fig. 6 is a schematic block diagram of a system for acoustic diagnosis in traditional Chinese medicine according to an embodiment of the present invention, as shown in fig. 6, optionally, the system further includes a storage module 91 for storing the amplitude, frequency spectrum and power information corresponding to the pre-diagnosis cases.
The above is only a preferred embodiment of the present invention, and is not intended to limit the present invention, and various modifications and changes will occur to those skilled in the art. Any modification, equivalent replacement, or improvement made within the spirit and principle of the present invention should be included in the protection scope of the present invention.
Claims (1)
1. A system for acoustic diagnosis in traditional chinese medicine, the system comprising: the device comprises an acquisition module, an extraction module, a matching module and a diagnosis module;
the acquisition module is used for acquiring a voice signal of the pre-diagnosis case;
the extraction module is configured to extract feature information in the speech signal, where the feature information includes spectrum information and power information;
the matching module is used for comparing and matching the characteristic information of the pre-diagnosed case with the characteristic information of each case in a pre-stored case library;
the diagnosis module is used for obtaining a diagnosis report of the pre-diagnosis case according to the comparison and matching result;
the system also comprises a conversion module, wherein the conversion module is used for converting the collected voice signals of the pre-diagnosis cases into digital signals;
the extraction module is specifically used for extracting amplitude information, frequency spectrum information and power information in the digital signal converted from the voice signal by using a time domain analysis method or a frequency domain analysis method; the matching module is specifically used for comparing the amplitude information, the frequency information, the spectrum information and the power information of the pre-diagnosis cases with the amplitude information, the frequency information, the spectrum information and the power information of each case in the pre-storage case library to respectively obtain the matching degree of the amplitude information, the frequency information, the spectrum information and the power information of each case and the pre-diagnosis cases;
the diagnosis module is specifically used for calculating the matching degree of the amplitude information, the frequency spectrum information and the power information of each pre-diagnosis case and each pre-storage case, and arranging the calculated matching degree according to a certain sequence; outputting the disease types of the cases in the pre-storage case base corresponding to the matching degree of the rearranged pre-diagnosis cases and the pre-storage case base as diagnosis reports;
the system further comprises a storage module, and the storage module is used for storing the pre-diagnosis cases and amplitude, frequency spectrum and power information corresponding to the pre-diagnosis cases.
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| Publication number | Priority date | Publication date | Assignee | Title |
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| CN103251386A (en) * | 2011-12-20 | 2013-08-21 | 台达电子工业股份有限公司 | Apparatus and method for voice assisted medical diagnosis |
| CN106709254A (en) * | 2016-12-29 | 2017-05-24 | 天津中科智能识别产业技术研究院有限公司 | Medical diagnostic robot system |
| JP2018048887A (en) * | 2016-09-21 | 2018-03-29 | 富士ゼロックス株式会社 | Diagnostic device, diagnostic system, and program |
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| Publication number | Priority date | Publication date | Assignee | Title |
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| CN103251386A (en) * | 2011-12-20 | 2013-08-21 | 台达电子工业股份有限公司 | Apparatus and method for voice assisted medical diagnosis |
| JP2018048887A (en) * | 2016-09-21 | 2018-03-29 | 富士ゼロックス株式会社 | Diagnostic device, diagnostic system, and program |
| CN106709254A (en) * | 2016-12-29 | 2017-05-24 | 天津中科智能识别产业技术研究院有限公司 | Medical diagnostic robot system |
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