CN109431493A - Wearable body surface potential acquisition device and method based on range segment separating weighting algorithm - Google Patents
Wearable body surface potential acquisition device and method based on range segment separating weighting algorithm Download PDFInfo
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- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B5/00—Measuring for diagnostic purposes; Identification of persons
- A61B5/24—Detecting, measuring or recording bioelectric or biomagnetic signals of the body or parts thereof
- A61B5/316—Modalities, i.e. specific diagnostic methods
- A61B5/318—Heart-related electrical modalities, e.g. electrocardiography [ECG]
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- A—HUMAN NECESSITIES
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- A61B5/25—Bioelectric electrodes therefor
- A61B5/279—Bioelectric electrodes therefor specially adapted for particular uses
- A61B5/28—Bioelectric electrodes therefor specially adapted for particular uses for electrocardiography [ECG]
- A61B5/282—Holders for multiple electrodes
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- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B5/00—Measuring for diagnostic purposes; Identification of persons
- A61B5/24—Detecting, measuring or recording bioelectric or biomagnetic signals of the body or parts thereof
- A61B5/316—Modalities, i.e. specific diagnostic methods
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- A61B5/00—Measuring for diagnostic purposes; Identification of persons
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- A61B5/6801—Arrangements of detecting, measuring or recording means, e.g. sensors, in relation to patient specially adapted to be attached to or worn on the body surface
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Abstract
The invention discloses wearable body surface potential acquisition devices and method based on range segment separating weighting algorithm, after user puts on device, the body surface potential that the dry electrode being distributed on vest collects user is sent into data collection system after accessing AFE(analog front end), and data collection system and the end PC connect.The signal that part of dry electrode receives is as electrocardiosignal, for synthesizing electrocardiogram.If corresponding lead signals are good, directly adopt；If corresponding lead signals are bad, corresponding electrocardiogram is obtained using four kinds of different multi-lead algorithms.It is used according to similarity and selects the algorithm that can most represent user's electrocardiogram from four kinds of algorithms based on range segment separating weighting algorithm.According to the physical condition of the ecg analysis user obtained and lesion distributing position can be determined to instruct successive treatment according to Body Surface Potential Map (body surface potential mapping, BSPM) simultaneously.
Description
Technical field
The present invention relates to a kind of body surface potential acquisition techniques, more particularly to the wearable body based on range segment separating weighting algorithm
Table potential acquisition device and method.
Background technique
With the improvement of people ' s living standards and living-pattern preservation, the disease incidence of cardiovascular disease also rise year by year
Height, high disability rate, high admission rate and high case fatality rate cause great burden to patients ' life quality and social development again.At present
National cardiovascular patient estimated 2.9 hundred million, case fatality rate are 40% that the China 2.5%~3.0%, Yi Zhan death is constituted
More than.The features such as high mortality of cardiovascular and cerebrovascular disease, high disability rate, high medical-risk, high medical burden, becomes great
Social concern.The items sign monitoring such as electrocardio is the effective means of early detection cardiovascular and cerebrovascular disease.If can be to heart and brain blood
Pipe Disease, inferior health or even healthy population implement large-scale every body sign dynamic monitoring, in time unusual condition
Doctor is fed back to, and early intervention is carried out to the cause of disease that may cause serious consequence, cardiovascular and cerebrovascular disease can be significantly reduced
It dies of illness, disability rate, greatly reduction Socie-economic loss.
Although application No. is the electrocardios that the invention of CN201710262618.9 can accomplish real-time monitoring patient, to the heart
The monitoring of electricity is still inaccurate, is affected by user's movement.Further analysis can not be carried out to patient and is examined
It is disconnected, it can not heart lesion positioning analysis to user.
Application No. is the invention of CN201711309089.X by the borborygmus of human body, heartbeat, breathing, body temperature, blood oxygen etc. come
The health of human body is monitored, has only carried out most basic monitoring, excessively generally.And for more prevalent cardiovascular and cerebrovascular
Disease is not achieved finds preventive effect in advance.
Summary of the invention
The invention discloses wearable body surface potential acquisition devices and method based on range segment separating weighting algorithm.Purpose is
The body surface potential of cardiovascular and cerebrovascular disease group of people at high risk is monitored in order to prevent to give treatment to cardiovascular and cerebrovascular burst in time and facilitate subsequent
Treatment.Wherein, described device includes vest, dry electrode, AFE(analog front end), data collection system and the end PC；
Dry electrode directly contacts human body, and human body electricity physiological signal is transferred to the defeated of AFE(analog front end) by conducting wire by dry electrode
Inbound port, AFE(analog front end) is by filtering with after enhanced processing, and output signal is connected to the input port of data collection system, and data are adopted
Collecting system analog signal after A D conversion is changed into digital signal, and stores and arrive computer, the number as Body Surface Potential Map
According to support.
The dry distribution of electrodes is on vest；
The AFE(analog front end) sews the right side loins in vest, and AFE(analog front end) is connected with dry electrode with conducting wire；
The AFE(analog front end) (analog front-end AFE) handles the hardware device that signal source issues analog signal,
The function of needing to realize is differential amplifier circuit, high-pass filtering circuit, main amplifying circuit, low-pass filter circuit.Peripheral circuit master
It to be in series or in parallel to form by multi-group resistance-capacitance, connect the big resistance of appropriate resistance value in two input ports of differential amplifier circuit,
The level of impedance match of electrode and AFE(analog front end) can be increased；By the resistance (amplification for placing different numerical value around amplifier
Device is the included amplifier of the chip of AFE(analog front end), strictly speaking chip is exactly an amplifier), capacitor, may be constructed difference
The filter circuit of passband；
The AFE(analog front end) handles the signal for the body-sensing potential that dry electrode acquires, including signal is amplified and
Filtering；
The data collection system is that analog electrocardiogram signal is converted to the circuit system of digital signal.Entire acquisition system
System be segmented into A D conversion portion, synchronous triggering part, TCP data segment.A D conversion portion be cascade 8 block number according to adopting
Truck, every piece of data collecting card can 16 road signal synchronized samplings, every piece of data collecting card is 16 sampling precisions, and sample frequency reaches
To 250kS/s (it is on sale that this data collecting card has matured product).Between 8 pieces of data collecting cards by same group of clock signal into
The synchronous triggering of row, allows 8 pieces of data collecting cards to open sampling simultaneously.Obtained data are sampled to be transferred to by PCI-E interface
Host computer, host computer receive data by Visual Studio and save in real time；
The signal of the collected body-sensing potential of dry electrode is after the amplification of the peripheral circuit of AFE(analog front end) and filtering
The chip for accessing AFE(analog front end) converts the signal into digital signal by data collection system, is sent into the end PC；
The end PC determines the signal of acquisition, if signal-to-noise ratio (Signal-to-noise ratio) reach 90dB and
More than, then electrocardiogram is synthesized, otherwise obtains corresponding electrocardiogram using two or more multi-lead electrocardio algorithms, and filter out most
Meet the electrocardiogram of user.
In the present invention, corresponding twelve-lead electrocardiogram is obtained using four kinds of multi-lead electrocardio algorithms, and filter out and most accord with
Close the electrocardiogram of user.Four kinds of multi-lead electrocardio algorithms are as follows:
Three leads rebuild 12 lead algorithm: electrocardial vector is the vector in linear space, when three axis of leads
When SYSTEM OF LINEAR VECTOR is unrelated, they just constitute a base of linear space, original lead so as to find out each lead at these three
Projection coefficient on connection and as reconstructed coefficients, finds out the ECG data of 12 lead.
Artificial neural network (ANN) method: by training the connection relationship continuously adjusted between node, until network is instructed
Experienced error reaches minimum value, establishes contacting between input layer and output layer.Using lead signals used for reconstruction as nerve
The input neuron of network, 12 lead ECG remaining signal of standard to be reconstructed are trained as output neuron.Training terminates
Afterwards, the relationship between lead used for reconstruction and lead to be reconstructed is just by training the neural network completed to get up.When answering
When for actual conditions, it is only necessary to know that lead signals used for reconstruction are input in the network, so that it may obtain to be reconstructed its
Remaining lead signals.
Support vector machines (SVM) method: input data is mapped to a higher-dimension sky by a specific kernel function first
Between in, the largest interval hyperplane for then feature space being given to create a separation to carry out classification differentiation, and returns and finds this
The hyperplane of a largest interval.
Linear lead method for reconstructing: a certain number of leads are chosen as initial lead used for reconstruction, are resettled just
Linear model between beginning lead and standard 12 lead, to realize the reconstruction of lead.
Specifically comprise the following steps:
Step 1, four kinds of corresponding electrocardiograms are obtained using four kinds of different multi-lead electrocardio algorithms, four kinds of electrocardiograms are same
The one period electrocardiographic wave of corresponding a cycle is denoted as A respectively1, A2, A3, A4:
A=(A1, A2, A3, A4)
N is the number of data point in an ecg wave form,Indicate the nth strong point in i-th kind of electrocardiographic wave, A
Indicate that the set of the electrocardiogram of four kinds of electrocardiogram same period corresponding a cycles, i value are 1,2,3,4；
It step 2, include P wave, QRS wave, T wave and U wave by four kinds of electrocardiographic waves according to medically complete ecg wave form
Four sections are all respectively divided into, first segment a1~ax, second segment ax~ay, third section is ay~az, the 4th section is az~an, wherein
a1For first point, that is, P wave wave crest of a complete cycle, axFor the wave crest of QRS wave, ayFor the wave crest of T wave, azFor U wave
Wave crest, anThe last one point for complete cycle is also the wave crest of P wave.Calculate separately four sections of hearts that every kind of electrocardiographic wave is divided into
The Hausdorff distance of electrograph waveform, Hausdorff distance are generally used for the similarity measurement of bianry image, and similarity is higher,
Hausdorff is apart from smaller, and when two figures are the same, Hausdorff distance is 0；
Step 3, four Duan Xin electricity are obtained by BP neural network (Back Propagation Neural Network) training
The weight of figure waveform is respectively P1, P2, P3, P4；
Step 4, respectively with A1, A2, A3, A4For template, and its excess-three waveshape similarity:
H(ai, as)=max (h (As, Ai), h (Ai, As)),
Wherein, AsFor template waveforms, AiFor another waveform of the similarity compared with template waveforms, asFor waveform AsOne
Point, aiFor waveform AiA point, h (As, Ai)、h(Ai, As) it is the median calculated, H (ai, as) it is one section of waveform in electrocardiogram
Hausdorff distance, D (ai, as) be two waveforms in each corresponding points distance, t be a complete cycle waveform sampling point,
For t-th point in template waveforms,It is t-th point of the waveform compared with template waveforms, H (Ai, As) it is with AsFor the A of templatei
And AsHausdorff distance, HyFor the Hausdorff distance of y sections of waveforms, PyFor the weight of y sections of waveforms, four groups are obtained
Hausdorff distance: with A1For template: H (A2, A1)、H(A3, A1)、H(A4, A1)；With A2For template: H (A1, A2)、H(A3, A2)、
H(A4, A2)；With A3For template: H (A1, A3)、H(A2, A3)、H(A4, A3)；With A4For template: H (A1, A4)、H(A2, A4)、H(A3,
A4)；
Step 5, compare after every group of Hausdorff distance being added, select and be worth the template of that minimum group as most
It is excellent as a result, the corresponding electrocardiographic wave of optimal result is to be best suitable for the electrocardiogram of user.
The dry electrode is button shape, shares N number of (generally 120).
The data collection system synchronizing acquires the signal for the body-sensing potential that N number of dry electrode obtains,
The dry electrode has 120, is roughly divided into eight rows 18 column, wherein seven arrange dry electrodes close to left thoracic portion, vest
The back side six arranges dry electrode and is uniformly distributed, and respectively has the dry electrode of a column at left clavicle 1/3 and 2/3 respectively, and vest left side has two column dry
Electrode.
The AFE(analog front end) is integrated in a box, and setting is provided with the charged lithium cells of power supply in box, outside box
Surface is provided with switch and electricity is shown.
The vest is by having the cloth of elasticity and gas permeability to be made.
The present invention also provides the wearable body surface potential acquisition method based on range segment separating weighting algorithm, feature exists
In including the following steps:
Step a1, after wearable body surface potential acquisition device is fully charged, user puts on vest, by lower switch；
Step a2, the dry electrode on vest acquire the body surface potential of user simultaneously, are sent to AFE(analog front end), adopt by data
Collecting system synchronous acquisition is transmitted to the end PC；
The step end a3, PC determines the signal of acquisition, if appropriate, then synthesizes electrocardiogram, if improper,
Corresponding electrocardiogram is obtained using two or more multi-lead electrocardio algorithms, and filters out the electrocardiogram for being best suitable for user；
Step a3 determines the distribution of lesion according to Body Surface Potential Map if electrocardiographic abnormality.
Step a3 includes the following steps:
Step a3-1 is arranged a normal myocardium model, obtains corresponding body surface potential energy diagram, and carries out the integral during QRS,
The integrogram for marking resulting body surface potential is SO；
Step a3-2, heart are divided into 53 subregions according to anatomical position, as basic unit body surface electricity in operation
Gesture；
The model of n-th subregion ectopic pacemaker is set, corresponding body surface map is measured by dry electrode, carries out the QRS phase
Between integral, the integrogram of body surface potential obtained by label is Sn, and n value is 0~53；
Step a3-3 subtracts SO from Sn and obtains the difference of body surface potential integrogram, is denoted as Dn；
Step a3-4 finds out maximum maxn from Dn, and records the position of its appearance；
Step a3-5 finds out minimum minn from Dn, and records the position of its appearance；
Step a3-6 is calculated from minimum and is directed toward maximum direction An；
Step a3-7 analyzes all An, determines the position of ectopic pacemaker.
The beneficiary of this product is with the people for suffering from cardiovascular and cerebrovascular disease possibility, first is that some heart diseases are shown
In the case where special, the monitoring of prolonged body surface potential can find the exception of electrocardiogram in time, prevent some bursts in advance
Situation；Second is that can sound an alarm under the situation of heart attack, patient is allowed timely to be given treatment to, to reduce patient's
The death rate and disability rate；Third is that lesion distributing position can be determined according to the Body Surface Potential Map that surveyed body surface potential obtains,
For instructing successive treatment.For this purpose, a kind of wearable body surface of the sectionally weighting algorithm based on Hausdorff distance of the present invention
Potential acquisition system.
Present apparatus shape is similar to common jerkin, the right-handed based on most people, in the right waist of vest
Between have the etui of EGC analog front end, have switch on box and electricity shown.It turns on the switch, body surface potential monitoring device
Start to work, be sent to data collection system and the end PC after the 120 acquired processing of road body surface potential, at the end PC synchronous acquisition, deposit
Storage, analysis, display.
The invention has the benefit that
Using the cloth with fine air permeability and elasticity, contact of the electrode with skin can be promoted, reduce electrode and skin
Frictional resistance caused by skin rubs also contributes to the wearing experience of people, is suitble to dress for a long time, is used for prolonged body surface
Potential monitoring.Body surface potential is acquired using 120 leads in the case where corresponding lead signals are bad, then passes through four kinds of different calculations
Method obtains corresponding electrocardiogram, finally closest to select using a kind of sectionally weighting algorithm based on Hausdorff distance
In the electrocardiogram of the practical electrocardio situation of user, greatly reduce because interference caused by frictional resistance etc., improves and moving
When measured electrocardiogram accuracy.Complete heart electromotive force distribution map can be established, helps to pinpoint lesion when diagnosis,
Instruct subsequent treatment.Patient is assisted in a large amount of data acquisition of user and establishes complete electrocardiogram (ECG) data model,
Convenient for the analyzing and diagnosing in the future to user's state of an illness.
Detailed description of the invention
The present invention is done with reference to the accompanying drawings and detailed description and is further illustrated, it is of the invention above-mentioned or
Otherwise advantage will become apparent.
Fig. 1 is the arrangement location drawing of 120 dry electrodes on vest.
Fig. 2 is the primary structure figure of apparatus of the present invention.
Specific embodiment
The present invention will be further described with reference to the accompanying drawings and embodiments.
As shown in Figure 2, apparatus of the present invention include vest body, 120 dry electrodes, box-like EGC analog front end,
Data collection system and the end PC.
Button shape is made in 120 dry electrodes, and position is sewed on vest as shown in Figure 1.It is roughly divided into eight rows 18 column.Its
In the seven dry electrodes of column it is more close, close to left thoracic portion.Dry electrode is connected with AFE(analog front end) by conducting wire.
The EGC analog front end of the box-like is made of peripheral circuit and chip.The dry collected body surface potential of electrode
The chip of AFE(analog front end) is accessed after the amplification of peripheral circuit and filtering.PC is sent into after being acquired by data collection system synchronizing
End.
Chip model is AD8232.
Data collection system uses Shanghai abridged armilla sci-tech product, is able to achieve 128 road synchronous acquisitions, sampling rate is reachable
250kS/s。
Data collection system is connect for PCIE mouthfuls with PC end main frame cabinet, realizes that data are same using C# in visual studio
Step acquisition, stores, display.
Peripheral circuit is transmitted to using the signal that 120 dry electrodes collect 120 tunnel body-sensing potentials respectively.By peripheral circuit
Amplification and filtering after access AFE(analog front end).Data collection system realizes 120 road synchronous acquisitions, and collected signal is sent into PC
End obtains corresponding electrocardiogram using four kinds of different multi-lead electrocardio algorithms.With a kind of segmentation based on Hausdorff distance
Weighting algorithm selects the electrocardiogram for being best suitable for user.The last information according to obtained QRS wave is drawn a conclusion, and is made corresponding
Processing method.
The detailed step of algorithm is as follows:
Step 1: the electrocardiographic wave of four kinds of electrocardiogram same period corresponding a cycles is denoted as A respectively1, A2, A3,
A4:
A=(A1, A2, A3, A4)
N is the number of data point in an ecg wave form.
Electrocardio is divided into four sections according to standard P wave, QRS wave, T wave, calculates separately Hausdorff distance.First segment is a1
~ax, second segment ax~ay, third section is ay~az, the 4th section is az~an。
Step 2: the size of each section of weight is determined by nerve training network, passes through obtaining for BP nerve training network
Each section of weight is respectively P={ P1, P2, P3, P4}。
Step 3: respectively with A1, A2, A3, A4For template, and its excess-three waveshape similarity:
H(ai, as)=max (h (As, Ai), h (Ai, As))
Wherein, D (ai, as) be two waveforms in each point distance.
Obtain four groups of Hausdorff distances: with A1For template: H (A2, A1)、H(A3, A1)、H(A4, A1)；With A2For template: H
(A1, A2)、H(A3, A2)、H(A4, A2)；With A3For template: H (A1, A3)、H(A2, A3)、H(A4, A3)；With A4For template: H (A1,
A4)、H(A2, A4)、H(A3, A4)。
Step 4: comparing after every group of Hausdorff distance is added, and selects and is worth the template of that minimum group as most
Excellent result.
If electrocardiogram has exception, heart lesion is determined using following methods:
One normal myocardium model is set, corresponding body surface potential energy diagram is obtained, and carries out the integral during QRS, obtained by label
Body surface potential integrogram be SO；
Heart is divided into 53 subregions according to anatomical position, and basic unit body surface potential is used as in operation.
The model of n-th (0~53) subregion ectopic pacemaker is set, corresponding body surface map is measured by dry electrode, into
The integrogram of integral during row QRS, label gained body surface potential is Sn；
SO is subtracted from Sn and obtains the difference of body surface potential integrogram, is denoted as Dn；
Maximum maxn is found out from Dn, and records the position of its appearance；
Minimum minn is found out from Dn, and records the position of its appearance；
It calculates from minimum and is directed toward maximum direction An；
All An are analyzed, determine the position of ectopic pacemaker.Determine that method is as follows:
Individual difference matching is first carried out, so that Different Individual is carried out disease to Body Surface Isopotential Mapping under the same standard and sentences
Not.To the patient of a large amount of practical dystopy pace-making, its body surface potential data is first acquired, then passes through clinical doctor by insertion type means
Imaging technique is learned, finds the position of current patient ectopic pacemaker, a kind of ectopic pacemaker position necessarily corresponds to a variety of body surfaces electricity
Gesture figure matches body surface potential data with ectopic pacemaker position, the parameter (full value 1) of a matching degree is arranged, with this
An ectocardia pacemaker position and body surface potential energy diagram corresponding relation database are established based on data.It will collect patient's
Body surface potential energy diagram is matched with ectopic pacemaker position in database, when matching degree parameter reaches 0.8 i.e. it is believed that this patient
Ectopic pacemaker position and the ectopic pacemaker position consistency that measures in advance.
Embodiment
Button shape is made in 120 dry electrodes, and position is sewed on vest as shown in Figure 1.It is roughly divided into eight rows 18 column.Its
In the seven dry electrodes of column it is more close, close to left thoracic portion.Dry electrode is connected with AFE(analog front end) by conducting wire.
The EGC analog front end of box-like is made of peripheral circuit and chip.The dry collected body surface potential difference of electrode is defeated
Enter, signal accesses the chip of AFE(analog front end) after the amplification of peripheral circuit and filtering.After being acquired by data collection system synchronizing
It is sent into the end PC.
Chip model is AD8232, and the chip power-consumption is small, small in size, is suitable for prolonged carrying and measurement.
Data collection system uses Shanghai abridged armilla sci-tech product, is able to achieve 128 road synchronous acquisitions, sampling rate is reachable
250kS/s。
Data collection system is connect for PCIE mouthfuls with PC end main frame cabinet, realizes that data are same using C# in visual studio
Step acquisition, stores, display.
Sample rate is set as 360Hz.It is said from the angle of medicine, selects 180 points at least to represent a complete electrocardio
Figure, i.e. n=180.
Electrocardio is divided into four sections according to standard P wave, QRS wave, T wave, first segment a1~a60, second segment a61~a80, the
Three sections are a81~a130, the 4th section is a131~a180。
The weight that each section is obtained by training neural network is respectively P={ P1, P2, P3, P4}={ 0.2,0.05,0.4,
0.35)。
Respectively with A1, A2, A3, A4For template, and its excess-three waveshape similarity:
Obtain four groups of Hausdorff distances: H (A2, A1)、H(A3, A1)、H(A4, A1)；H(A1, A2)、H(A3, A2)、H
(A4, A2)；H(A1, A3)、H(A2, A3)、H(A4, A3)；H(A1, A4)、H(A2, A4)、H(A3, A4).Every group of Hausdorff away from
From comparing after addition, selects and be worth the mould of that minimum group as optimal result.
If electrocardiogram have it is different, according to Body Surface Potential Map analyze determine heart lesion position distribution.
It is specific real the present invention provides wearable body surface potential acquisition device and method based on range segment separating weighting algorithm
Now there are many method of the technical solution and approach, the above is only a preferred embodiment of the present invention, it is noted that for this
For the those of ordinary skill of technical field, without departing from the principle of the present invention, several improvement and profit can also be made
Decorations, these modifications and embellishments should also be considered as the scope of protection of the present invention.Each component part being not known in the present embodiment is available
The prior art is realized.
Claims (9)
1. the wearable body surface potential acquisition device based on range segment separating weighting algorithm, which is characterized in that including vest, dry electricity
Pole, AFE(analog front end), data collection system and the end PC；
The dry distribution of electrodes is on vest；
The AFE(analog front end) sews the right side loins in vest, and AFE(analog front end) is connected with dry electrode with conducting wire；
The AFE(analog front end) handles the signal for the body-sensing potential that dry electrode acquires, including signal is amplified and filtered
Wave；
The signal of the collected body-sensing potential of dry electrode is after the amplification of AFE(analog front end) and filtering, by data collection system
Digital signal is converted the signal into, the end PC is sent into；
The end PC determines the signal of acquisition, if signal-to-noise ratio reaches 90dB or more, synthesizes electrocardiogram, otherwise uses
Two or more multi-lead electrocardio algorithms obtain corresponding electrocardiogram, and filter out the electrocardiogram for being best suitable for user.
2. the apparatus according to claim 1, which is characterized in that described to obtain phase using two or more multi-lead electrocardio algorithms
The electrocardiogram answered, and the electrocardiogram for being best suitable for user is filtered out, specifically comprise the following steps:
Step 1, four kinds of corresponding electrocardiograms are obtained using four kinds of different multi-lead electrocardio algorithms, four kinds of electrocardiograms with for the moment
The electrocardiographic wave of the corresponding a cycle of section is denoted as A respectively1, A2, A3, A4:
A=(A1, A2, A3, A4)
N is the number of data point in an ecg wave form,Indicate the nth strong point in i-th kind of electrocardiographic wave, A is indicated
The set of the electrocardiogram of four kinds of electrocardiogram same period corresponding a cycles, i value are 1,2,3,4；
Step 2, four kinds of electrocardiographic waves are all respectively divided into four sections according to standard P wave, QRS wave, T wave and U wave, first segment a1
~ax, second segment ax~ay, third section is ay~az, the 4th section is az~an；Wherein a1For first point of a complete cycle
That is the wave crest of P wave, axFor the wave crest of QRS wave, ayFor the wave crest of T wave, azFor the wave crest of U wave, anFor the last one of complete cycle
Point is also the wave crest of P wave；The Hausdorff distance for four sections of electrocardiographic waves that every kind of electrocardiographic wave is divided into is calculated separately,
Step 3, obtaining the weight of four sections of electrocardiographic waves by BP neural network training is respectively P1, P2, P3, P4；
Step 4, respectively with A1, A2, A3, A4For template, and its excess-three waveshape similarity:
H(ai, as)=max (h (As, Ai), h (Ai, As)),
Wherein, AsFor template waveforms, AiFor another waveform of the similarity compared with template waveforms, asFor waveform AsA point, ai
For waveform AiA point, h (As, Ai)、h(Ai, As) it is the median calculated, H (ai, as) it is one section of waveform in electrocardiogram
Hausdorff distance, D (ai, as) be two waveforms in each corresponding points distance, t be a complete cycle waveform sampling point,For
T-th point in template waveforms,It is t-th point of the waveform compared with template waveforms, H (Ai, As) it is with AsFor the A of templateiWith
AsHausdorff distance, HyFor the Hausdorff distance of y sections of waveforms, PyFor the weight of y sections of waveforms, four groups are obtained
Hausdorff distance: with A1For template: H (A2, A1)、H(A3, A1)、H(A4, A1)；With A2For template: H (A1, A2)、H(A3, A2)、
H(A4, A2)；With A3For template: H (A1, A3)、H(A2, A3)、H(A4, A3)；With A4For template: H (A1, A4)、H(A2, A4)、H(A3,
A4)；
Step 5, compare after every group of Hausdorff distance being added, select and be worth the template of that minimum group as optimal knot
Fruit, the corresponding electrocardiographic wave of optimal result are the electrocardiogram for being best suitable for user.
3. the apparatus of claim 2, which is characterized in that the dry electrode is button shape, is shared N number of.
4. device according to claim 3, which is characterized in that the data collection system synchronizing acquires N number of dry electrode and obtains
The signal of the body-sensing potential taken.
5. device according to claim 4, which is characterized in that the dry electrode has 120, is divided into eight rows 18 column,
In the seven dry electrodes of column close to left thoracic portion, the vest back side six arranges dry electrode and is uniformly distributed, and respectively has respectively at left clavicle 1/3 and 2/3
The one dry electrode of column, there is the dry electrode of two column in vest left side.
6. device according to claim 5, which is characterized in that the AFE(analog front end) is integrated in a box, in box
The charged lithium cells for being provided with power supply are set, and box outer surface is provided with switch and electricity is shown.
7. device according to claim 6, which is characterized in that the vest is by having the cloth system of elasticity and gas permeability
At.
8. the wearable body surface potential acquisition method based on range segment separating weighting algorithm, which comprises the steps of:
Step a1, after wearable body surface potential acquisition device is fully charged, user puts on vest, by lower switch；
Step a2, the dry electrode on vest acquire the body surface potential of user simultaneously, are sent to AFE(analog front end), acquire by data and are
System synchronous acquisition is transmitted to the end PC；
The step end a3, PC determines the signal of acquisition, if appropriate, then synthesizes electrocardiogram, if improper, uses
Two or more multi-lead electrocardio algorithms obtain corresponding electrocardiogram, and filter out the electrocardiogram for being best suitable for user；
Step a3 determines the distribution of lesion according to Body Surface Potential Map if electrocardiographic abnormality.
9. according to the method described in claim 8, it is characterized in that, step a3 includes the following steps:
Step a3-1 is arranged a normal myocardium model, obtains corresponding body surface potential energy diagram, and carries out the integral during QRS, label
The integrogram of resulting body surface potential is SO；
Step a3-2, heart are divided into 53 subregions according to anatomical position, and basic unit body surface potential is used as in operation；
The model of n-th subregion ectopic pacemaker is set, corresponding body surface map is measured by dry electrode, during carrying out QRS
Integral, the integrogram of label gained body surface potential are Sn, and n value is 0~53；
Step a3-3 subtracts SO from Sn and obtains the difference of body surface potential integrogram, is denoted as Dn；
Step a3-4 finds out maximum maxn from Dn, and records the position of its appearance；
Step a3-5 finds out minimum minn from Dn, and records the position of its appearance；
Step a3-6 is calculated from minimum and is directed toward maximum direction An；
Step a3-7 analyzes all An, determines the position of ectopic pacemaker.
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