CN101449971A - Portable cardiac diagnosis monitoring device based on rhythm mode - Google Patents

Abstract

A portable electrocardiographic diagnosis and monitoring device based on a rhythm pattern, comprising an ECG signal acquisition module, a signal front-end processing module, an A/D conversion module, a main processor, a data storage unit and a display module. The ECG signal collected by the ECG signal acquisition module is connected to the signal front-end processing module, and then passed to the main processor after the A/D conversion module, and the main processor is respectively connected with the data storage unit and the display module; The signal extracts the R wave peak position to obtain the rhythm interval signal; the main processor completes the feature extraction and classification diagnosis: extracts the rhythm variation pattern, counts its distribution law, and quantitatively describes its distribution law through indicators; and then establishes a spatial model according to the variation pattern distribution , to classify unknown data. The device solves the problems existing in the prior art, adopts the heart rhythm signal as the object, and is not easily affected by noise and measurement accuracy; it can produce stable results by using short-term data, and is suitable for clinical use.

Description

Portable cardiac diagnosis monitoring device based on rhythm mode

Technical field

The invention belongs to medical instruments field, relate to a kind of novel based on portable cardiac diagnosis monitoring device based on rhythm mode.

Technical background

From Einthoven (W.Einthoven) electrocardiogram (ECG) century more than one so far of noting for the first time human body in 1903, electrocardiogram is used widely owing to it is convenient and swift, low-cost as the basic means of cardiac function evaluation and cardiovascular disease diagnosis.Electrocardiosignal Treatment Analysis means have also obtained rapid progress.By to common Electrocardiographic automatic analysis, develop into body surface and lead Electrocardiographic tracing more, and by before its Converse solved myocardial action potential excitation wave, and the analysis of little electromotive force in the electrocardiogram, as late current potential, high frequency current potential etc.(HRV) signal of heart beat rhythm variation in recent decades becomes another forward position research focus in the ECG signal processing.

Yet in actual applications, have following problem: the ECG wave-shape amplitude is subject to disturb; The initial cut-off point of specific waveforms detects and has error.Simultaneously, analytical parameters numerous and lack the unified standard and scope.Main or basic parameter that same category of device that retrieves at present and doctor are used such as heart rate and range estimation typical waveform form come auxiliary diagnosis unusually.Electrocardiogram quantitative analysis parameter is used for the function of clinical diagnosis and the function of automated diagnostic can not access performance fully.Therefore excavation and physiology, the closely-related specificity parameter of pathological state, and be applied to have important practice significance in clinical cardiac function evaluation and the disease auxiliary diagnosis equipment.

Summary of the invention

The objective of the invention is in order to solve the above-mentioned problems in the prior art, technical scheme of the present invention is as follows:

A kind of portable cardiac diagnosis monitoring device based on rhythm mode comprises ECG signal acquisition module, signal front-end processing module, A/D modular converter, primary processor, data storage cell and display module; The signal that the ECG signal acquisition module is gathered imports primary processor into again behind the A/D modular converter after the signal front-end processing resume module; Primary processor is connected with data storage cell, display module respectively; Primary processor is finished feature extraction and classification diagnosis.

Described signal front-end processing module comprises one-level amplifying circuit, secondary amplification filtering circuit, power frequency trap circuit; Electrocardiosignal obtains the ECG signal of 1 ± 0.1V again through the power frequency trap after one-level amplification, secondary amplify; Described one-level amplifying circuit is the instrument amplifier of 10 times of amplifications; Secondary amplification filtering circuit is 100 times of amplification filtering circuit that the amplifier chip constitutes; The power frequency trap circuit is the 50Hz wave trap.

The ECG signal acquisition module adopts simulation V5 to lead, and promptly anodal at left breast the 4th intercostal midaxillary line place, negative pole places the mode of leading of breastbone upper limb.Primary processor is finished data acquisition by the PIO mouth.Described one-level amplifying circuit also is connected with right lower limb common mode negative-feedback circuit (being driven-right-leg circuit) and carries out further common mode disturbances inhibition.

Described display module is a LCD MODULE.This device also comprises radio receiving transmitting module; Described LCD MODULE is by PIO mouth and host interface; Pass through the SPI interface communication between described radio receiving transmitting module and the primary processor; Radio transmitting and receiving chip is carried out parameter configuration to primary processor and data transmit; The work of wireless transmission is divided into: user side registration process and data transmission procedure.

This equipment also is provided with data storage function: described data storage cell and primary processor are by the SPI interface communication; Data storage cell adopts general fast-flash memory storage card, as the SD card.

The SPI interface is a serial peripheral interface; PIO is the parallel transmission interface.

Primary processor is finished feature extraction and classification diagnosis according to the heart beat rhythm variation mode.Step is that the electrocardiogram ECG signal extraction R crest location from gathering obtains rhythm and pace of moving things interval signal; Extract rhythm and pace of moving things variation mode again, add up its regularity of distribution, and describe its regularity of distribution by index quantification; According to variation mode distribution, set up the hyperspace model then, unknown data is classified.

The invention has the beneficial effects as follows:

The present invention is based on the cardioscribe detection system of embedded technology, and volume is little, and is low in energy consumption, is convenient to carry the long record ECG signal.Adopt general fast-flash memory storage card storage ECG data, volume is little, in light weight, capacity is big, cost is low.In addition, system also possesses wireless data transmission function.Adopt heart rhythm signal as object, be not subject to the influence of noise and certainty of measurement.Based on the mode profile of characteristic parameter cardiac rhythm variation and physiological status, pathological state closely related, have clear physical meaning, and simple description form, particular state is had distribution of specific, use short time data just can produce stable result, be fit to clinical use.Algorithm is simple, is convenient to realize based on micro controller systems such as single-chip microcomputer, ARM.

Description of drawings

Fig. 1 is an equipment operation principle structured flowchart;

Fig. 2 is the structured flowchart of device hardware;

Fig. 3 is front end simulation amplification module block diagram

Fig. 4 is the categorizing system schematic diagram

Fig. 5 is the program flow diagram in the primary processor

Specific embodiments

The invention will be further described below in conjunction with accompanying drawing and the specific embodiment.

This equipment operation principle structured flowchart as shown in Figure 1.Comprising: electrocardiogram acquisition module (mainly finishing the electrocardiogram collection), storage and demonstration, wireless transmission; Heart beat rhythm signal, the feature extraction of rhythm and pace of moving things variation mode distribution; The definition index is with quantitative description mode profile feature; Make up the hyperspace model and classify, export the result.

Its specific embodiments is as follows:

1. the structural framing of hardware system is seen Fig. 2.Obtain electrocardiosignal from human body with crosslinking electrode, detect front end it is amplified and Filtering Processing, obtain the signal of certain frequency scope and amplitude, handle through analog-digital converter, the digital signal after the conversion is delivered to primary processor by special interface.Adopt the arm processor of embedded technology in this example, finish ecg wave form demonstration, data preservation, wireless transmission and data analysis and warning.Because general arm processor may be used to this equipment, primary processor just has not been further limited at this.

Adopt simulation V5 to lead (promptly anodal at left breast the 4th intercostal midaxillary line place, negative pole places the mode of leading of breastbone upper limb) 2.ECG signal obtains, drive inhibition 50Hz power frequency with right lower limb simultaneously and disturb.One-level is amplified (10 times) and is adopted high accuracy, low-power consumption instrument amplifier, and common amplifier chip constitutes secondary and amplifies (100 times), power frequency trap (50Hz), and the amplitude of obtaining is the ECG signal about 1V, as Fig. 3.Owing to describedly lead, amplifying circuit, power frequency notch filter and right lower limb common mode negative-feedback circuit (being driven-right-leg circuit) and their connected mode be all very common in the prior art, just be not further limited at this.

3. radio receiving transmitting module adopts the transceiver chip as master chip, selects PTR8000 in this example for use.The function of this chip has, and the multifrequency point multiband can be used for multiple-point wireless transmission; Low voltage power supply, GFSK modulation, but frequency hopping, and have carrier wave detection, matching addresses, data ready output.Built-in communication protocol and CRC check.Primary processor can carry out parameter configuration and data transmission to radio transmitting and receiving chip by special interface (as the SPI interface).In order to realize the transfer of data of point-to-multipoint, promptly service end is to the working method of several user sides, and satisfies the response and the space requirement of embedded system, and the work of wireless transmission is divided into: user side registration process and data transmission procedure.A general purpose control passage is used for service end and sends order and request-reply to user side, and user side sends request to service end; A plurality of data channel, the data channel that each user is corresponding different is used for transmitting data to service end.

4. data storage adopts general fast-flash memory storage card (as the SD card).Size is little, and is in light weight, and memory capacity is big, and data transmission bauds is fast, possesses the defencive function of data information, supports hot plug, has great mobile motility and well safety.

5. primary processor is gathered, is shown by special interface (as the PIO mouth), carries out rhythm and pace of moving things extraction to obtaining electrocardiogram ECG.The interval of detecting the electrocardiogram adjacent R ripple of continuous acquisition obtains heart beat rhythm signal RR (i), represent the i time and the i+1 time heart beating between interval.Its process is as follows:

1. get the search window width about about 1.5 cycles in cycle, the electrocardiogram (ECG) data of sampling is found out the slope maximum; 2. this slope maximum is designated as MaxSlopeGate; Position with MaxSlopeGate is a starting point, seeks the interior amplitude maximum of certain window scope (about an about QRS ripple is wide) backward, and its corresponding position is the preliminary position of R ripple; 3. calculate this R ripple position and time value between the RR of R ripple position last time, if this interval,, think then that the R ripple of seeking exists many inspections or omission, rejects this position less than RR interval threshold minimum MinRRInternal or greater than RR interval thresholding maximum MaxRRInternal, adjust the search window width, if the search window width is then dwindled in omission, if many inspections, then increase the search window width, search meets the requirements up to the interval of the R ripple position of finding, or does not find that 4. reposition changes over to once more; 4. with the current R ripple position that searches out as benchmark pass backward half QRS ripple wide about, get next window width (about about 1.5 cycles) data, return step 1., seek next R ripple position.

(described threshold value is to decide according to the scope of the interval between normal person the i time and the i+1 time heart beating, for example, and for the desirable threshold value of normal person: MinRRInternal=300ms, MaxRRInternal=2000ms)

6. extract rhythm and pace of moving things variation mode.The present invention proposes to use the directional information of three kinds of symbology heart rate variabilities, and the building method of concrete symbol sebolic addressing is as follows: as RR (i)〉RR (i+1), x (i) is designated as 0; As RR (i)=RR (i+1), x (i) is designated as 1; As RR (i)＜RR (i+1), x (i) is designated as 2; I=1,2,3 .., N-1.Setting the word length width is m, structure sequence vector: X (i)=[x (i), x (i+1) .., x (i+ (m-1))], i=1,2 .., N-m.Definition index quantification description scheme distribution characteristics, the Probability p of add up every kind of pattern appearance, to might combining form the distribution probability ask comentropy:

$\mathrm{SSE}\left(m\right)=-\underset{j=1}{\overset{M}{\mathrm{\Σ}}}{p}_j{\log }_2{p}_j.$

As follows with two-dimensional spatial model explanation classificating thought, as Fig. 4:

At two-dimensional space two known vectorial OA (a of classification are arranged ₁, a ₂) and vectorial OB (b ₁, b ₂), and the vectorial OC (c that waits to declare classification ₁, c ₂).Angle between OC and OA, the OB is respectively α and β.If α＜β, then think OC more near OA, just in that OC and OA are close in nature.If wherein, vectorial OA, OB have represented the position of centre of gravity of A, B two class vectors respectively, can conclude that then the C point belongs to category-A; Otherwise, then belong to category-B.

$\cos \mathrm{\α}=\frac{a_1{c}_1+a_2{c}_2}{\sqrt{a_1^2+a_2^2}\·\sqrt{c_1^2+c_2^2}}$ $\cos \mathrm{\β}=\frac{b_1{c}_1+b_2{c}_2}{\sqrt{b_1^2+b_2^2}\·\sqrt{c_1^2+c_2^2}}$

A wherein _i, b _i, c _i(i=1,2) are respectively the plane coordinates value of A, B, C each point.

It is as follows that the C point is differentiated: when α＜β, and cos α-cos β〉0, the C point belongs to category-A; As α〉during β, cos α-cos β〉0, the C point belongs to category-B.

Primary processor can also be with age factor as feature input separately; The detected object age is chosen different category sets as standard.

The work process of primary processor for example shown in Figure 5: electrocardiogram obtains, and the R crest extracts to obtain the heart beat rhythm signal, extracts rhythm and pace of moving things variation mode, makes up the hyperspace model.Read age information, the right side of fifty, calculate and young healthy group (for example OA represents) and disease group (for example OB represents) between included angle cosine COS, fall into the group of COS maximum; More than 50 years old, calculate with old healthy organize and disease group between included angle cosine COS, fall into the group of COS maximum.

This equipment shows the classification diagnosis result at last on screen.Normally then show normal; Tachycardia, bradycardia, premature beat, the leakage slight state of an illness such as fight is reminded the patient to have a rest or is taken medicine or seek advice from Xiang the doctor; Quiver, stop fighting in heart failure, dangerous arrhythmia, chamber, warning surpasses the still then electrocardio of the transmission storage at once request first aid of no change of 30s electrocardio.Patient can press the warning key and send the request that helps according to self state of feeling during this.

Claims (10)

1. A portable ECG diagnostic monitoring device based on a rhythm pattern, comprising an ECG signal acquisition module, a signal front-end processing module, an A/D conversion module, a main processor, a data storage unit and a display module, characterized by an ECG signal acquisition module The collected ECG signal is connected to the signal front-end processing module, and then transmitted to the main processor after the A/D conversion module, and the main processor is respectively connected to the data storage unit and the display module; the main processor extracts the R peak from the collected ECG signal position, to obtain the interrhythm signal; the main processor completes feature extraction and classification diagnosis: extract the rhythm variation pattern, count its distribution law, and describe its distribution law quantitatively through indicators; then according to the variation pattern distribution, establish a spatial model, and analyze sort. 2. The portable ECG diagnosis and monitoring device based on rhythm mode according to claim 1, characterized in that the signal front-end processing module includes a primary amplifier circuit, a secondary amplifier filter circuit, and a power frequency notch circuit; the ECG The signal collected by the signal acquisition module passes through a primary amplifier circuit and a secondary amplifier filter circuit, and then passes through a power frequency notch circuit to obtain an ECG signal of 1 ± 0.1V; the primary amplifier circuit is a 10-fold instrumentation amplifier; The secondary amplification filter circuit is a 100-fold amplification filter circuit composed of an operational amplifier chip; the power frequency notch circuit is a 50Hz notch filter; Further common-mode interference suppression. 3. The portable ECG diagnosis and monitoring device based on rhythm pattern according to claim 1 is characterized in that it also includes a wireless transceiver module; through the SPI interface communication between the wireless transceiver module and the main processor, the main processor is connected to the wireless The transceiver chip performs parameter configuration and data transmission, and the work of wireless transmission is divided into: client registration process and data transmission process. 4. The rhythm mode-based portable ECG diagnostic monitoring device according to claim 1, wherein the display module is a liquid crystal display module, and the liquid crystal display module communicates with the main processor interface through the PIO port. 5. The rhythm mode-based portable ECG diagnostic monitoring device according to claim 2, characterized in that the ECG signal acquisition adopts an analog V5 lead, that is, the positive pole is at the midaxillary line of the fourth intercostal space of the left chest, and the negative pole is placed The lead mode of the upper edge of the sternum; the main processor is connected to the A/D conversion module through the PIO port, that is, the main processor completes data acquisition through the PIO port. 6. The portable ECG diagnosis and monitoring device based on rhythm mode according to claim 1, characterized in that the data storage unit communicates with the main processor through the SPI interface, and the data storage unit adopts a general-purpose flash memory memory card to realize data storage capabilities. 7. The portable ECG diagnostic monitoring device based on rhythm pattern according to claim 1, characterized in that the main processor extracts the R wave peak position from the collected electrocardiogram ECG signal to obtain the rhythm interval signal: ① Take the search window width and find the maximum value of the slope for the sampled ECG data; ②The maximum value of the slope is recorded as MaxSlopeGate; starting from the position of MaxSlopeGate, search backward for the maximum value of the amplitude within a certain window range, and its corresponding position is the initial position of the R wave; ③ Calculate the RR interval value of the R wave position and the previous R wave position. If the interval is less than the minimum value of the RR interval threshold MinRRInternal or greater than the maximum value of the RR interval threshold MaxRRInternal, it is considered that the R wave you are looking for has multiple detection or For missed detection, remove the position and adjust the search window width. If it is a missed detection, then narrow the search window width. If it is a multi-detection, increase the search window width, and search again until the interval of the found R wave position meets the requirements. Or no new location is found and transferred to ④; ④ Use the found current R wave position as a reference to move back about half the QRS wave width, take the data of the next window width, and return to step ① to find the next R wave position. 8. The portable ECG diagnosis and monitoring device based on rhythm pattern according to claim 1, characterized in that said main processor extracts rhythm variation pattern, counts its distribution law, and quantitatively describes its distribution law by index, and the steps include: Symbol sequence construction: When RR(i)>RR(i+1), x(i) is recorded as 0; when RR(i)=RR(i+1), x(i) is recorded as 1; when RR(i)<RR( i+1), x(i) is recorded as 2;; i=1, 2, 3, . . ., N-1; the word length and width are set as m, and the vector sequence is constructed: X(i)=[x(i), x(i+1), .., x(i+(m-1))], i=1, 2, .., N-m; Define indicators to quantitatively describe the pattern distribution characteristics: Count the probability p of each mode, and find the information entropy for the distribution probability of all possible combinations: $\mathrm{SSE}\left(m\right)=-\underset{j=1}{\overset{m}{\mathrm{\&Sigma;}}}{p}_j{\log }_2{p}_j.$ 9. The rhythm pattern-based portable ECG diagnostic monitoring device according to claim 1, characterized in that the main processor establishes a multi-dimensional space model according to the variation pattern distribution, and classifies unknown data, the method is as follows: Suppose there are two vectors OA(a ₁ , a ₂ ) and vector OB(b ₁ , b ₂ ) with known categories in two-dimensional space and OC(c ₁ , c ₂ ) with categories to be judged; OC and OA, The angles between OB are α and β respectively; the vectors OA and OB represent the center of gravity positions of the two types of vectors A and B respectively; if α<β, OC is considered to be closer to OA, that is, OC is similar to OA in nature, Then it can be concluded that point C belongs to category A; otherwise, point C belongs to category B. 10. The rhythm pattern-based portable ECG diagnostic monitoring device according to claim 1, characterized in that the main processor also inputs the age factor as a separate feature, and uses the age of the subject as a standard to select different classification sets.

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