CN102715915A - Portable heart sound automatic sorting assistant diagnostic apparatus - Google Patents
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- CN102715915A CN102715915A CN2012102459412A CN201210245941A CN102715915A CN 102715915 A CN102715915 A CN 102715915A CN 2012102459412 A CN2012102459412 A CN 2012102459412A CN 201210245941 A CN201210245941 A CN 201210245941A CN 102715915 A CN102715915 A CN 102715915A
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Abstract
The invention discloses a portable heart sound automatic sorting assistant diagnostic apparatus which consists of a front-end heart sound/electrocardio signal acquiring, conditioning and transmitting part and an OMAP3530 core signal processing part. According to the invention, a favorable human-computer interaction interface is provided so that the heart sounds and electrocardio data of human bodies can be acquired conveniently and correctly and be displayed in real time; the storage and playback of the heart sounds and electrocardio data are supported; and through a heart sound subsection algorithm and a heart sound sorting algorithm, 17 types of common heart sound signals can be comprehensively analyzed and the results are correct and effective, so that the diagnosis can be preferably assisted. The ARM (Advanced RISC machine) and DSP (Digital Signal Processor) dual-core processing ability of the OMAP3530 is fully utilized, the DSP is capable of accelerating the heart sound sorting algorithm and the ARM is convenient for expanding peripherals and integrating new applications, so that respective load is effectively balanced; and because of being developed on an embedded platform, the portable heart sound automatic sorting assistant diagnostic apparatus has the advantages of low cost, low power consumption, portability and the like when being compared with the traditional similar equipment operating on PC (Personnel Computer).
Description
Technical field
The present invention relates to a kind of portable hear sounds auxiliary diagnosis appearance of classifying automatically, belong to the cardiechema signals processing technology field.
Background technology
In the last few years, the cardiovascular disease incidence rate was high always, and all kinds of cardiovascular disease can both reflect from the unusual performance of heart greatly.One of physiological signal that cardiechema signals is wanted as body weight for humans has comprised and can reflect the normal perhaps abundant information of pathology of heart, has very high superiority in detection the type disease field, is a kind of important non-intrusion type detection technique.Whether unusual cardiophony be one of current diagnosis heart the most frequently used, fundamental method.But traditional cardiophony has a lot of shortcomings: at first it is to use the auditory analysis cardiechema signals with doctor's experience; The subjective judgment that depends on the doctor to a great extent; Need the doctor to have rich experience in advance; Special when external environment complicated, as in the in disorder scene of the accident, busy ambulance is first-class, just more is difficult to accurate judgement; Secondly cardiechema signals is a bass, and frequency mainly is distributed in 50-600Hz, though people's earshot at 20-20000Hz, only to the acoustic phase of 300-3000Hz to sensitivity, so auscultation has very big limitation; In addition, traditional auscultation also can't be preserved a large amount of patient datas.
Along with the development of electronic information technology and processing of biomedical signals technology, more and more both at home and abroad research worker are put into the cardiechema signals process field, have occurred some hear sounds auxiliary diagnosis products abroad.But at present, mostly the product on the market is to utilize computer acquisition, demonstration, playback hear sounds; Can not analyze classification intelligently to cardiechema signals; Even associated class is arranged like emulator, also because of the complexity of cardiechema signals, only can be to several types of cardiechema signals classification.And most the application concentrate on the PC, and cost is higher, and is portable poor.In the field of study; The research of sorting out for analysis of PCG Signal at present mainly is to utilize signal processing technology such as time-frequency domain analysis; The analysis of PCG Signal that has normal or pathologic information to common is sorted out; Still many places are in theoretical research stage, and rare in the market a can collection in real time shows the human body cardiechema signals, and can analyze the portable instrument of classification, auxiliary diagnosis to hear sounds automatically comprehensively.If this type of portable auxiliary diagnosis equipment of exploitation with the deficiency that remedies traditional cardiophony greatly, alleviates doctor's workload simultaneously; Because its portability also can conveniently be applied to various occasions such as family, the scene of the accident.
Summary of the invention
In view of the necessity and the huge prospect of this kind equipment of exploitation, not enough to prior art, the present invention has designed a kind of portable hear sounds auxiliary diagnosis appearance of classifying automatically.This equipment is core with American TI (Texas Instrument) company based on the technological OMAP3530 flush bonding processor of DaVinci, and the good man-machine interaction interface is provided, and can make things convenient for, gather accurately human body hear sounds, electrocardiogram (ECG) data and demonstration in real time; Support hear sounds, electrocardiogram (ECG) data storage and playback; Through hear sounds segmentation algorithm, hear sounds sorting algorithm, can be to 17 types of common hear sounds (normal cardiac sound, third heart sound, fourth heart sounds; Ejection sound, clicking sound, two cents split; Opening snap, gallop rhythm, noise continuously; Presystole, mid-term, later stage, full phase noise, protodiastole, mid-term, later stage, full phase noise) make comprehensive analysis classification, assist diagnosis.Compare with common hear sounds collection demonstration playback reproducer and other simple hear sounds classification emulators, this invention has following advantage:
1. this invention is developed on embedded platform, operates on the PC with traditional similar devices and compares, and cost is low, and is low in energy consumption, has certain portability;
2. hear sounds segmentation, sorting algorithm of should invention adopting are simply effective, can conveniently operate on the embedded system, can analyze classification to 17 types of common hear sounds, more comprehensively and accuracy rate up to more than 90%;
3. this invention also can be gathered demonstration playback electrocardiosignal when hear sounds being gathered demonstration playback, rounded analysis diagnosis, and collection hear sounds, electrocardio are applied to all over the body, and function is more powerful, the flexible equipment purchase cost that reduces simultaneously;
4. this invention has made full use of the double-core disposal ability of ARM+DSP, and DSP good data operational capability has been quickened the hear sounds sorting algorithm, and ARM better controlling ability can make things convenient for expanding peripherals, integrated new function.
This invention can be used as the auxiliary diagnosis of auxiliary diagnosis instrument when participating in the cintest, has good market prospect and social benefit.
The portable hear sounds of the present invention auxiliary diagnosis appearance of classifying has automatically adopted following technical scheme:
A kind of portable hear sounds auxiliary diagnosis appearance of classifying automatically; Comprise front end hear sounds, ecg signal acquiring conditioning hop and signal processing; Front end hear sounds, ecg signal acquiring conditioning hop is gathered in real time, conditioning human body-centered sound, electrocardiogram (ECG) data; And upload hear sounds, electrocardiogram (ECG) data to signal processing through USB interface; Signal processing is at first controlled front end hear sounds, the real-time collection modulation transmission of ecg signal acquiring conditioning hop hear sounds, electrocardiogram (ECG) data, and shows human body hear sounds, electrocardiogram in real time; Then cardiechema signals is carried out analyzing and processing; It is characterized in that: when signal processing is carried out analyzing and processing to cardiechema signals; Utilize electrocardiosignal to the cardiechema signals periodic segment, utilize and cardiechema signals is done comprehensive judgment analysis based on the hear sounds sorting algorithm of decision tree and time-domain analysis in short-term.
The present invention with American TI Company based on the OMAP3530 flush bonding processor of DaVinci technology core as signal processing; ARM analyzes mastery routine as general processor operation linux system and hear sounds auxiliary diagnosis, and DSP is responsible for the big data quantity computings such as hear sounds sorting algorithm based on decision tree and time-domain analysis in short-term as coprocessor.
In the OMAP3530 core signal of the present invention processing section, the hear sounds auxiliary diagnosis is analyzed mastery routine and is divided into hear sounds, electrocardiogram acquisition control module on the ARM microprocessor, hear sounds periodic segment module, hear sounds classification judgment analysis module, UI interface display control module.
Hear sounds of the present invention, electrocardiogram acquisition control module and front end hear sounds, ecg signal acquiring conditioning hop are connected through USB interface; According to the two communication protocol regulation; The former can be to latter's transmitting control commands; Comprise startup collection transmission, stop to gather transmission, sample frequency being set that the latter then after receiving startup collection transmission command, gathers human body hear sounds, electrocardiogram (ECG) data in real time and is uploaded to the former.
Hear sounds periodic segment module of the present invention is through electrocardiosignal and cardiechema signals relation in time; Cardiechema signals was divided according to the cycle; Find the position of hear sounds first heart sound, second heart sound and next first heart sound in the cycle, and give hear sounds classification judgment analysis module these parameter informations.
Hear sounds classification judgment analysis module of the present invention is obtained the heart sound data of sectional one-period; Call the DSP end group in the decision tree and the hear sounds sorting algorithm of time frequency analysis in short-term; Time-frequency characteristic parameter when the extraction cardiechema signals is short-and-medium; Cardiechema signals is done the rounded analysis judgement, and give UI interface display control module analysis result.
UI interface display control module of the present invention shows human body hear sounds, electrocardiogram in real time; The user can be through pushbutton enable on the interface, stop to gather and show, amplifies, dwindles present image, starts the hear sounds diagnostic analysis, and diagnostic analysis finishes the back and shows the hear sounds analysis result; Can store current hear sounds, electrocardiogram.
Classify the automatically method of work of auxiliary diagnosis appearance of portable hear sounds of the present invention is:
The user at first is placed on the appropriate auscultation monitoring location of human chest with the heart sound transducer auscultation head and the disposable electrocardioelectrode subsides of EGC sensor of front end hear sounds, ecg signal acquiring conditioning hop;
Behind system's electrifying startup; OMAP3530 core signal processing section at first starts (SuSE) Linux OS and the hear sounds auxiliary diagnosis mastery routine of classifying automatically; Accomplish the initialization of each several part and module, operational factor is set, show the UI interface; UI interface display control module begins to accept the user and clicks various functional keyss on the interface as the control core of system;
The user clicks " start and gather " button; Hear sounds, the response of electrocardiogram acquisition control module; Forward end hear sounds, ecg signal acquiring conditioning hop send " start and gather " control command, and after front end hear sounds, ecg signal acquiring conditioning hop received this order, beginning was gathered human body hear sounds, electrocardiosignal in real time and is uploaded to OMAP3530 core signal processing section; UI interface display control module receives these data, dynamically shows hear sounds, electrocardiogram;
The user clicks " suspend and gather " button; Hear sounds, the response of electrocardiogram acquisition control module; Forward end hear sounds, ecg signal acquiring conditioning hop send " stopping to gather transmission " control command; After front end hear sounds, ecg signal acquiring conditioning hop receives this order, stop hear sounds, electrocardiogram (ECG) data is uploaded, hear sounds, the electrocardiogram of UI interface display are static temporarily.
The user clicks " selection " button; Hear sounds periodic segment module responds; Carry out the hear sounds segmentation algorithm,, hear sounds, the electrocardiogram of current demonstration is divided into some heart beat cycles according to hear sounds, electrocardiosignal time co-relation; And writing down each heart beat cycle first heart sound, second heart sound position, the user can select any heart beat cycle further to adjudicate diagnostic analysis;
The user clicks " analysis " button, and hear sounds classification judgment analysis module responds is called DSP end hear sounds sorting algorithm, extracts the cardiechema signals characteristic parameter, the analysis-by-synthesis cardiechema signals, and send analysis result back to the UI interface display.
The user clicks " amplifying/dwindle " button, can the current hear sounds of convergent-divergent, electrocardiogram;
The user clicks " preservation " button, can store current hear sounds, electrocardiogram;
The user clicks open button, hear sounds, the electrocardiogram of storage before can checking again.
The invention has the beneficial effects as follows:
The portable hear sounds of the present invention design auxiliary diagnosis appearance of classifying automatically is that first item can be gathered simultaneously and shows playback hear sounds, electrocardio on the market, and can carry out that rounded analysis is sorted out, the portable set of auxiliary diagnosis to 17 types of common hear sounds.This invention provides the good man-machine interaction interface, can make things convenient for, gather accurately human body hear sounds, electrocardiogram (ECG) data and demonstration in real time; Support hear sounds, electrocardiogram (ECG) data storage and playback; Through hear sounds segmentation algorithm, hear sounds sorting algorithm, can carry out rounded analysis to 17 types of cardiechema signals, court verdict accurate and effective, auxiliary diagnosis preferably.This invention has made full use of the ARM+DSP double-core disposal ability of OMAP3530, and DSP quickens the hear sounds sorting algorithm, and ARM makes things convenient for the integrated new application of expanding peripherals, active balance load separately; This invention operates on the PC with traditional similar devices and compares owing to be on embedded platform, to develop, and has advantages such as low cost, low-power consumption, portability; The integrated cardiac electrical collection of this invention shows playback etc., and function is more powerful, convenient, flexible reduction equipment purchase cost.This invention has realized the classification of hear sounds rounded analysis preferably; Can be applicable to various occasions such as hospital, family, the scene of the accident; Greatly facilitate doctor and patient, find in time that for auxiliary diagnosis, patient pathological information etc. has valuable help, has good market prospect and social benefit.
Description of drawings
Fig. 1 is the portable hear sounds of the present invention auxiliary diagnosis instrument system block diagram of classifying automatically.
Fig. 2 is the portable hear sounds of the present invention auxiliary diagnosis appearance hear sounds categorised decision tree structure diagram of classifying automatically.
Fig. 3 is classify the automatically segmentation of auxiliary diagnosis appearance hear sounds, a sorting algorithm flow chart of the portable hear sounds of the present invention.
The specific embodiment
In order to make technical scheme of the present invention clearer, the present invention is further elaborated below in conjunction with accompanying drawing.
Shown in Figure 1ly be the portable hear sounds of the present invention auxiliary diagnosis instrument system block diagram of classifying automatically, this system mainly is made up of two parts: front end hear sounds, ecg signal acquiring are nursed one's health hop and OMAP3530 core signal processing section.Front end hear sounds, ecg signal acquiring conditioning hop is gathered in real time, conditioning human body-centered sound, electrocardiosignal, and uploads hear sounds, electrocardiogram (ECG) data to OMAP3530 core place signal reason part through USB interface.Front end hear sounds, the real-time collection modulation transmission of ecg signal acquiring conditioning hop hear sounds, electrocardiogram (ECG) data are at first controlled in OMP3530 core signal processing section, and show human body hear sounds, electrocardiogram in real time; Utilize electrocardiosignal to the cardiechema signals periodic segment then, utilize and cardiechema signals is done comprehensive judgment analysis based on the hear sounds sorting algorithm of decision tree and time-domain analysis in short-term.
1, front end hear sounds, ecg signal acquiring conditioning hop
Front end hear sounds, ecg signal acquiring conditioning hop adopt " Hefei Huake Electron Technique Research Academy " hear sounds collection modulation transport module HKY-06C and electrocardiogram acquisition conditioning transport module HKD-10C.Though the physical interface that hear sounds collection modulation transport module, electrocardiogram acquisition conditioning transport module are connected with host computer is a USB interface; But because inside modules uses serial ports to change USB chip CP2102; Therefore after the host computer linux system is correctly installed the CP2102 driver, be similar to common serial ports for the control programming of two modules.
Worked out simple communication protocols between hear sounds collection modulation transport module, electrocardiogram acquisition conditioning transport module and host computer; Stipulate according to communication protocol; Two modules can effectively be controlled through serial port programming in OMAP3530 core signal processing section, gather transmission as starting, stop to gather transmission, sample frequency etc. being set.
Hear sounds collection modulation transport module parameter is: hear sounds sample frequency 1K-8KHz; Data bits 8bits, low-pass cut-off frequencies 1500Hz, full duplex serial communication interface; 1 start bit, 8 data bit, 1 position of rest, no parity position, baud rate 115200bps; The control command of supporting has: read device number, start sampling, close sampling, the amplification rank is set, baseline is set, sample frequency etc. is set.
Electrocardiogram acquisition conditioning parameter module parameter is: electrocardio sample frequency 200Hz, data bits 8bits, full duplex serial communication interface, 1 start bit, 8 data bit, 1 position of rest, no parity position, baud rate 57600bps; The control command of supporting has: read device number, start sampling, close sampling etc.
2, OMAP3530 core signal processing section
In OMAP3530 core signal processing section, the hear sounds auxiliary diagnosis mastery routine of classifying automatically can be divided into hear sounds, electrocardiogram acquisition control module on the ARM microprocessor, hear sounds periodic segment module, hear sounds classification judgment analysis module, UI interface display control module; Operation hear sounds sorting algorithm on the DSP Digital Signal Processing.
(1) hear sounds electrocardiogram acquisition control module
This module is controlled the hear sounds collection modulation transport module and the electrocardiogram acquisition conditioning transport module of above-mentioned front end hear sounds, ecg signal acquiring conditioning hop effectively through serial port programming.
(2) hear sounds periodic segment module
This module is carried out hear sounds segmentation algorithm, and one section cardiechema signals in a plurality of cycles is divided into some heart beat cycles.Because the quasi periodic of cardiechema signals; So can extract the one-period of cardiechema signals analyzes; Just can obtain the characteristic of whole hear sounds, extract preceding necessary original position and the end position of confirming a heart beat cycle of cardiechema signals, and then find the position of first heart sound, second heart sound.According to hear sounds, electrocardiosignal relation in time, utilize electrocardio among the present invention to the hear sounds split fix.Periodic segment and the method for locating first second heart sound are:
(a) with ecg-r wave as the hear sounds one-period to begin be the first heart sound position; The location algorithm of R ripple is: calculate one section average maximum of electrocardiogram (ECG) data earlier; Be made as 1 greater than this value of peaked 80%, otherwise be made as 0, electrocardiosignal is shaped as similar square wave like this; All 1 correspondence positions search electrocardiogram (ECG) data maximums from square wave then, i.e. the R ripple in cycle for this reason; Be a heart beat cycle between two adjacent R ripples.
(b) with electrocardio T ripple terminal as the second heart sound position, through repeatedly the test, according to adult's meansigma methods, this position is at 0.35 place of a heart beat cycle.
(3) hear sounds classification judgment analysis module
This module is mainly called and is carried out the DSP end group in the decision tree and the hear sounds sorting algorithm of time frequency analysis in short-term, rounded analysis cardiechema signals.In a cardiac cycle, contain a lot of hear sounds,, can roughly be divided into two kinds of noise and non-noises according to the time limit branch.The longer duration of the non-noise of noise ratio.Noise roughly comprises systolic murmur (SM), diastolic murmur (DM) and continuous murmur (CM).Systolic murmur can be divided into presystole, mid-term, later stage and full phase noise again, and diastolic murmur can be divided into protodiastole, mid-term, later stage and full phase noise again.Non-noise comprises that mainly first heart sound (S1), second heart sound (S2), third heart sound (S3), fourth heart sound (S4), ejection sound (ES), clicking sound (MSC), two cents split (A2P2), opening snap (OS) and gallop rhythm (SS).Wherein except first and second hear sounds, all contain the pathologic meaning.
Fig. 2 is the portable hear sounds of the present invention auxiliary diagnosis appearance hear sounds categorised decision tree structure diagram of classifying automatically.As shown in Figure 2:
Grader one: hear sounds is divided into two types of noise and non-noises.The frequency of noise is higher, and the persistent period is shorter; The frequency of non-noise is lower, and the persistent period is longer.Noise grader one utilizes short-time zero-crossing rate and two parameters of rate that transfinite in short-term come cardiechema signals is classified.Confirm short-time zero-crossing rate and the persistent period of the rate that transfinites in short-term and thresholding of amplitude.When a given cardiechema signals,, just think and contain noise in this cardiechema signals if calculate its short-time zero-crossing rate or time that the rate that transfinites in short-term surpasses the amplitude thresholding has surpassed time threshold.Do not contain noise otherwise be judged to.
Grader two: noise is the branch systolic murmur, diastolic murmur and continuous noise.The main distinction of these three kinds of noises is that short-time zero-crossing rate is different with the beginning and ending time of the rate that transfinites in short-term.Judge process is: if the starting and ending position of noise thinks then that all at systole this noise is a systolic murmur.If the starting and ending position of noise thinks then that all at relaxing period this noise is a diastolic murmur.If the original position of noise is at systole, end position judges then at relaxing period whether the persistent period of this noise has surpassed 60% of the whole hear sounds cycle, is judged to continuous murmur if surpass 60%; Otherwise judge according to the ratio of noise in systole and relaxing period; If the ratio in systole is bigger; Then be judged to systolic murmur,, then be judged to diastolic murmur if the ratio in relaxing period is bigger; If all bigger in the ratio of systole and relaxing period, then being judged to systole and relaxing period all has noise.
Grader three: systolic murmur is divided into presystolic murmur, mid systolic murmur, late systolic murmur and the full phase noise of contraction.This grader has utilized time average and average two characteristic parameters of reversed time.These two parameters can be told the distributing position of noise more accurately.Differentiation process: at first calculate the time average of systolic murmur,, otherwise see that time average is whether less than the thresholding of noise in mid-term if time average then is judged to presystolic murmur less than the threshold value of noise in early stage.If time average then is judged to mid systolic murmur less than the thresholding of noise in mid-term, otherwise the reversed time of calculating cardiechema signals is average.If reversed time on average less than the threshold value of noise in late period, then is judged to late systolic murmur, shrink full phase noise otherwise be judged to.
Grader four: diastolic murmur is divided into the protodiastole noise, mid diastolic murmur, the full phase noise of diastasis period noise and diastole.This grader and grader three are accomplished similar function.
Grader five: the non-noise that is used for searching for cardiechema signals.The main hear sounds type of distinguishing comprises: ejection sound, clicking sound, two cent classes, opening snap, third heart sound, fourth heart sound and plyability gallop rhythm.The differentiation process: this grader has at first calculated the short-time energy of cardiechema signals; Pass through The disposal of gentle filter then; The rule of the ad-hoc location that in cardiechema signals, occurs according to all kinds of non-noises at last removes to seek peak value to the relevant position, comprise this noise if exist peak value then to think.
According to above-mentioned hear sounds periodic segment, hear sounds classification analysis scheme, design hear sounds segmentation, sorting algorithm flow chart are as shown in Figure 3.Above-mentioned employing based on the decision tree and the hear sounds sorting algorithm accurate and effective of time frequency analysis in short-term; " the modern cardiac auscultation " published to the Chinese medical audio & video press attaches the cardiechema signals of giving among the CD; The judgment analysis rate of accuracy reached is more than 90%; For further clinical experiment,, also can obtain good result through key parameter in the adjustment algorithm.
UI interface display control module provides the good man-machine interaction interface as the control core of system.This interface can show human body hear sounds, electrocardiogram in real time; The user can be through pushbutton enable on the interface, stop to gather and show, amplifies, dwindles present image, starts the hear sounds diagnostic analysis, and diagnostic analysis finishes the back and shows the hear sounds analysis result; The user can store current hear sounds, electrocardiogram, hear sounds, the electrocardiogram of storage before also can checking again.
Claims (7)
1. portable hear sounds auxiliary diagnosis appearance of classifying automatically; Comprise front end hear sounds, ecg signal acquiring conditioning hop and signal processing; Front end hear sounds, ecg signal acquiring conditioning hop is gathered in real time, conditioning human body-centered sound, electrocardiogram (ECG) data; And upload hear sounds, electrocardiogram (ECG) data to signal processing through USB interface; Signal processing is at first controlled front end hear sounds, the real-time collection modulation transmission of ecg signal acquiring conditioning hop hear sounds, electrocardiogram (ECG) data, and shows human body hear sounds, electrocardiogram in real time; Then cardiechema signals is carried out analyzing and processing; It is characterized in that: when signal processing is carried out analyzing and processing to cardiechema signals; Utilize electrocardiosignal to the cardiechema signals periodic segment, utilize and cardiechema signals is done comprehensive judgment analysis based on the hear sounds sorting algorithm of decision tree and time-domain analysis in short-term.
2. the portable hear sounds as claimed in claim 1 auxiliary diagnosis appearance of classifying automatically; It is characterized in that: with American TI Company based on the OMAP3530 flush bonding processor of DaVinci technology core as signal processing; ARM analyzes mastery routine as general processor operation linux system and hear sounds auxiliary diagnosis, and DSP is responsible for the big data quantity computings such as hear sounds sorting algorithm based on decision tree and time-domain analysis in short-term as coprocessor.
3. according to claim 1 or claim 2 the portable hear sounds auxiliary diagnosis appearance of classifying automatically; It is characterized in that: in OMAP3530 core signal processing section; The hear sounds auxiliary diagnosis is analyzed mastery routine and is divided into hear sounds, electrocardiogram acquisition control module on the ARM microprocessor; Hear sounds periodic segment module, hear sounds classification judgment analysis module, UI interface display control module.
4. the portable hear sounds as claimed in claim 3 auxiliary diagnosis appearance of classifying automatically; It is characterized in that: hear sounds, electrocardiogram acquisition control module and front end hear sounds, ecg signal acquiring conditioning hop are connected through USB interface; According to the two communication protocol regulation; The former can be to latter's transmitting control commands; Comprise startup collection transmission, stop to gather transmission, sample frequency being set that the latter then after receiving startup collection transmission command, gathers human body hear sounds, electrocardiogram (ECG) data in real time and is uploaded to the former.
5. the portable hear sounds as claimed in claim 3 auxiliary diagnosis appearance of classifying automatically; It is characterized in that: hear sounds periodic segment module is through electrocardiosignal and cardiechema signals relation in time; Cardiechema signals was divided according to the cycle; Find the position of hear sounds first heart sound, second heart sound and next first heart sound in the cycle, and give hear sounds classification judgment analysis module these parameter informations.
6. the portable hear sounds as claimed in claim 3 auxiliary diagnosis appearance of classifying automatically; It is characterized in that: hear sounds classification judgment analysis module is obtained the heart sound data of sectional one-period; Call the DSP end group in the decision tree and the hear sounds sorting algorithm of time frequency analysis in short-term; Time-frequency characteristic parameter when the extraction cardiechema signals is short-and-medium is done the rounded analysis judgement to cardiechema signals, and gives UI interface display control module with analysis result.
7. like the right 3 described portable hear sounds auxiliary diagnosis appearance of classifying automatically, it is characterized in that: UI interface display control module shows human body hear sounds, electrocardiogram in real time; The user can be through pushbutton enable on the interface, stop to gather and show, amplifies, dwindles present image, starts the hear sounds diagnostic analysis, and diagnostic analysis finishes the back and shows the hear sounds analysis result; Can store current hear sounds, electrocardiogram.
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