CN107184204A - The extraction of nociceptive component and expression way in a kind of brain wave - Google Patents
The extraction of nociceptive component and expression way in a kind of brain wave Download PDFInfo
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Abstract
The invention discloses a kind of extraction of nociceptive component in brain wave and expression way, by gathering eeg signal in real time, utilize the mathematical computations algorithm of discrete signal processing, extract in brain wave about pain, analgesia, anxiety, anxiety, look forward or upwards it is absurd, forget, the method for the characteristic component of comfort, and express the expression way as 0 100 dimensionless number evidence.Eeg signal is gathered using the sensing technology of electro physiology, and apply calculating analysis to signal, find and extract features described above index, by normalized, obtain measuring the quantitative value of features above index, form the technological means and application apparatus of real-time pain measurement.The present invention provides strong support means for the scientific research of pain therapy and management method, for analysis curative effect of medication, summarize treatment method, adjust therapeutic scheme, research and analyse Pain mechanisms, collect large sample long-time Clinical Pain relevant information in terms of have important practical value.
Description
Technical field
Can be one the present invention relates to the extracting method and expression way of a kind of brain wave characteristic index of nociceptive component
Machine or framework can be applied to house, the realization of the pain measurement method of hospital's integration in wireless platform of internet of things.
Background technology
Current era brain science is the leading science that people pay close attention to.In brain science, the e measurement technology development of brain state
It is important content therein, is also one of the target of brain science application study.In clinical medicine domain, until current, not
Have it is a kind of can real-time objective quantitative measurement pain, analgesia, anxiety, anxiety, look forward or upwards it is absurd, forget, the measurement of comfortable etc. brain state
Method is applied to practice.Due to the missing of this real-time objective quantitative measurement techniques, in Clinical Pain treatment, people are for pain
The subjective scale that the measurement of pain relies only on pain is completed, and subjective scale is the subjective self judgment of people, with 0-10
Scale, describes the pain degree of oneself.Such method is filled with uncertain and nonrepeatability, causes relevant pain
Therapeutic effect can not be measured accurately, and analgesia degree (pain threshold) can not also be measured, and the use for medicine can not also realize visitor
See and appropriateness.Anxiety that particularly pain is brought, anxiety, delirium, forget and can not more measure and apply corresponding processing.Its
Secondary, Internet technology and mechanics of communication are to lead one of bracing force of scientific and technological progress, with reference to clinical treatment service,
Realize that medical information integration is exchanged on internet platform with wireless telecommunications means, for chronic pain patient, such as pain caused by cancer disease
People, analgesia therapy under home environment is simultaneously insufficient, without the quantitative pain index of real-time objective, often makes doctor can not
Drug therapy is applied according to the objective pain degree of patient, patient is often dead in extreme pain.Suffer from for Acute Pain
The pain therapy of person, such as postoperative patient, more need comprising the brain state quantitative data including pain depth as medical treatment
The objective basis of pain, the development of Internet technology is that doctor understands the pain of patient on houseization or sick bed, town in real time
Bitterly, anxiety, anxiety, look forward or upwards it is absurd, forget, level of comfort provide a kind of technological means that can be employed.
Acute and chronic pain therapy, the foundation of monitoring-information management platform based on internet communication, can be controlled for pain
Treat and the scientific research of management method provides strong support means.Especially for the pain of patient, analgesia, anxiety, tight
Open, look forward or upwards absurd, forgetting, the grasp of the quantitative data of level of comfort, for analysis curative effect of medication, summarize treatment method, adjustment treatment
Scheme, research and analyse Pain mechanisms, collect large sample long-time Clinical Pain relevant information in terms of have important practical valency
Value.
The content of the invention
It is an object of the invention to provide a kind of extraction of nociceptive component in brain wave and expression way, to solve by collection
Eeg signal, extracts pain therein, analgesia, anxiety, anxiety, delirium, forgetting, the side of the characteristic component of level of comfort
Method and expression way, and pain measurement equipment is formed, realize pain management in clinical treatment service and houseization health control
The technical problem of application.
In order to realize foregoing invention purpose, the technology used in the present invention method is as follows：
The extraction of nociceptive component and expression way in a kind of brain wave, are included under various ambient conditions, and human body is due to pain
In brain brain wave caused by pain on pain, analgesia, anxiety, anxiety, look forward or upwards it is absurd, forget, the extraction of comfortable characteristic component
Method and expression way；By the use of brain wave as raw signal processing blocks, discretization is collected in computer, applies mathematics
Calculate analysis, brain wave resolved into low frequency, intermediate frequency, high frequency, hyperfrequency unit, extract its neutralize pain, it is analgesia, anxiety, tight
Open, look forward or upwards absurd, forgetting, comfortable related characteristic component, by normalized, be expressed as 0-100 dimensionless number evidence, in real time
React the pain of people, analgesia, anxiety, anxiety, look forward or upwards it is absurd, forget, comfortable real-time objective quantitative depth；Using eeg sensor,
It is worn on frons and the ear position on head, the electric potential signal at the noninvasive multiple positions of collection brain, signal is via preposition amplification
Device and multistage integrated circuit and analog-digital converter enter computing unit, signal bandwidth include in brain wave more than 30hz with
On hyperfrequency composition, brain wave acquisition lead is set to minimum two leads comprising left and right brain prefrontal lobe or more, via preceding
Put big, analog-to-digital conversion, into microcontroller system, then by data encryption, compression after, directly passed via wired mode
Computer unit is delivered to, or is packed via the ICP/IP protocol of wireless telecommunications control unit and is sent to internet data service
Software systems in device, computer or server handle the EEG signals received calculating, display, storage, forwarding in real time,
Wherein calculating section uses wavelet analysis, waveform recognition algorithm, and that decomposes in brain wave various is relevant to having for frequency and time domain
Composition and artifact composition are imitated, and is combined into new data flow, then via fuzzy diagnosis analysis, multiple regression analysis, correlation
Analysis, multidimensional analysis of spectrum, extract pain, analgesia, anxiety, anxiety, look forward or upwards it is absurd, forget, comfortable characteristic index, by normalizing
Change is handled, and is obtained from 0-100 multiple quantitative datas, the pain of real-time objective quantitative response human body, analgesia, anxiety, anxiety,
Look forward or upwards it is absurd, forget, comfortable degree, obtain pain depth, analgesia depth, anxiety depth, nervous depth, look forward or upwards absurd depth, forget deep
Degree, comfortable depth factor.
Eeg signal acquisition unit possesses wired and wireless communication capability, and integral pain can be combined into computer
Depth-measuring system, can also be combined into the pain depth survey system of cloud computing mode by internet platform and server
System, forms the Telemedicine shared platform to pain measurement data, and the big data for forming pain measurement collects new model,
Using 232 interface standards, 3G, 4G, bluetooth, WIFI communication technology realize nearly long-range, multi-environment, real-time brain electricity
Transmission terminal is gathered, for the brain wave analogue signal of collection amplification, one-chip computer realizes the discretization of analog-to-digital conversion to it
Processing, by multichannel brain wave discrete signal Real Time Compression, encryption, packing, realizes dynamic memory queue management, recognizes connection
Road, automatic switching communication modes, communication control is sent, and real time data bag or is directly sent to calculating by 232 communication interfaces
In machine or via wireless the Internet platform, it is sent directly in cloud computing server, via computer or cloud computing server
Calculating is handled, the pain depth factor of formation, analgesia depth factor, anxiety depth factor, nervous depth factor, delirium depth
Index, forgetting depth factor, comfortable depth factor are shown in terminal or cell phone end.
The adjoint analgesia of pain numerical value, anxiety, anxiety, delirium, forgetting, the quantitative measurment of the comfortable psychological state of mind, from
Synchronously extracted in brain wave analgesia, anxiety, anxiety, look forward or upwards it is absurd, forget, comfortable quantitative expression, in the quantitative table of pain depth
Up to together, the process of pain measurement is completed, the integrality and accuracy of pain measurement is reached.
In small echo processing is calculated, both bioelectrical signals sequences can be decomposited, are believed as signal intensity and interference
Number marker characteristic use；Using small echo formula：
To the electric Vector Groups of brain
Fi (x)=[x1x2x3 ... xm-2xm-1xm]
i：Brain wave lead quantity, m：Vector element quantity, x：Brain wave data
Real-time calculating processing, with multi-scale filtering device group algorithm, decomposites the wavelet basis function under each scaled window
(Wf(2^j,fj(x)))j∈z
(Wf (2^0, fj (x))), (Wf (2^1, f0 (x))),, (Wf (2^N, fN (x)))
j：Wavelet basis quantity
By wavelet basis function and the inverse transformation of each yardstick data, one group of time domain reconstruction function is obtained as follows：
Fi, j (x)=∑ Wf (2^j, x) * X2^j (x)
Fi, 1 (x), fi, 2 (x),, fi, N (x)；Reconstruction of function, X2^1 (x), X2^2 (x),, X2^N (x), each yardstick
Wavelet data point；N：Exponent number；j：Yardstick quantity, i：Lead number；
Each reconstruction of function represents the brain wave under different scale, and eye moves the performance of electric wave and myoelectricity ripple；Yardstick is also right
The frequency content of induction signal, is distributed in the normal rhythmic and higher frequency rhythms of electroencephalogram；For each sequence of the reconstruction of function of decomposition
Column data, the characteristic point of data is extracted using the waveform recognition algorithm in algorithm for pattern recognition：
Tj(x)∈z；
T：Feature value vector, j：Yardstick, x：Discrete data, represents wave characteristics；z：Time domain space；
Characteristic in vector T j (x) includes distinguished point, amplitude, variation, slope, area, auto-correlation, cross-correlation etc.
Result of calculation, calculating comes from rudimentary algorithm：
Data sequence：Y (t, i)=(f (j)-f (j-1))/Δ t
j：Discrete data subscript, i：Yardstick；
Greatest measure in sequences y (t, i) is obtained, one of characteristic index can be obtained, positive-negative reverse-phase point therein is exactly
Distinguished point, the quantity of distinguished point is represented by the size of t values；
Iteration differential algorithm is applied to f (x) sequence datas：
D (j, i)=∑ (f (j+i)-f (j+i-1)/(Δ t+i))
i：Δ t increment, from 1..N, j：Numerical value sequence number；
For each vector in matrix d (j, i), the data point in vector is sorted and is added, choose each vector
In maximum be added and, be used as slope and amplitude；
For each scaling vector fi (x) in reconstruction of function=[x1 x2 x3 ... xm-2 xm-1 xm], it will handle
Result vector y (t, i), d (j, i) generation mode class ω 1, ω 2 ..., the ω c arrived, then the distance between Land use models function
Calculate the distance of each reconstruction of function；Obtain the variation of reconstruction of function, auto-correlation, cross-correlation numerical value；
Calculate the integration of reconstruction of function：
Si (t)=∫ f (j, i) * Δs t
Try to achieve the area figures of each function；
Tj (x) vectors express the wave characteristics and rule of reconstruction of function；Telecommunications is moved for the eye in the brain wave of collection
Number and frontalis electric signal, be distributed in the reconstruction of function of particular dimensions, for these reconstruction of function, first, ask for therein one
Order derivative：
Di (x)=(fi (x)-fi (x+m))/Δ x
x：Abscissa, Δ x：Abscissa increment；
Di (x) is sorted, maximum and minimum is obtained, given threshold a can be asked for
Di (x) positive-negative polarity change point, obtains one group of extreme point vector：
Mi(j)；High point；
mi(j)；Low spot；
j：The quantity of extreme point；
Integral algorithm is used to related reconstruction of function：
E=∫ fi (t) ^2* Δs t
E1=∫ fj (t) ^2* Δs t
Obtain myoelectricity and the dynamic performance number size of eye；For the above results data, by normalizing combinational algorithm：
Sq=exp (a*abs (Mi-mi)+b*E)；
A, b：Weight coefficient, is determined by signal representation scope；
The quantitative expression Sq of the signal intensity of interference can be obtained indicating, one of display result is used as；
Dynamic and myoelectricity the brain wave reconstruct composition of eye is eliminated in reconstruction of function, using power spectra algorithm：
f(x)：Time domain brain wave discrete data, X (w)：Spectrum power size；
Each composition of power spectrum in brain wave can be obtained, includes the numerical value of α β δ θ wave bands, sef, the edge frequency such as mef
Rate, the numerical value such as dominant frequency：
Fj=α, β, δ, θ,, sef, mef }；
With reference to the characteristic vector obtained by waveform recognition, it is combined into one group and covers time domain and frequency domain, and it is non-linear
The data vector group of complexity result：
Gi (x)={ Tj, Fj }；
i：Yardstick quantity；
Data vector Gi (x) groups, as the single treatment result of brain wave, are named as first number of brain wave coagulation
According to group, the regular characteristic component in hundreds of brain waves is contained in metadata group, can be by the base as secondary calculating
Plinth data；
Some of each yardstick reconstruction of function metadata characteristic is extracted, the corresponding data of wherein each yardstick are calculated
Slope, rate of change and the integral area of ratio, each yardstick data：
Y (x, t)={ Gi (x, t)-Gi (x, t-1)/Δ t } ∈ z；
Zi, j (x)={ Gi (x1)/Gj (x1) } ∈ z；
S (x, t)={ ∫ G (x, t) * Δs t } ∈ z；
D (x, t)={ abs (G (x, t1)-G (x, t2)) } ∈ z；
t：Calculate time point, i, j：Scaling sequence, x：Characteristic vector subscript；z：Calculate space size；
For each above-mentioned data sequence, by data weighting, volume of data calculation formula is obtained：
Ei=a, b, c, d,, and n } * { Yi, Zi, Si, Di }；
i：Data target sequence number；
Apply normalization to Ei data to calculate：
Pain index=(esp (E0)) × 100
Analgesia index=(esp (E1)) × 100
Nervous index=(esp (E2)) × 100
Delirium index=(esp (E3)) × 100
Anxiety index=(esp (E4)) × 100
Forget index=(esp (E5)) × 100
Comfort index=(esp (E5)) × 100；
Obtain the pain in brain wave, analgesia, anxiety, anxiety, look forward or upwards it is absurd, forget, comfortable real-time objective quantitative characteristic refers to
Mark.
Advantages of the present invention：
The present invention, using the mathematical computations algorithm of discrete signal processing, extracts brain by gathering eeg signal in real time
In electric wave about pain, analgesia, anxiety, anxiety, look forward or upwards it is absurd, forget, the method for the characteristic component of comfort, and express and turn into
The expression way of 0-100 dimensionless number evidence.Eeg signal is gathered using the sensing technology of electro physiology, and to signal
Apply a variety of mathematical computations algorithms, find and extract pain therein, analgesia, anxiety, anxiety, look forward or upwards it is absurd, forget, comfortable composition
Characteristic index, by normalized, obtain measuring the quantitative value of features above index, form real-time pain measurement
Technological means and application apparatus.The present invention provides strong support hand for the scientific research of pain therapy and management method
Section, for analysis curative effect of medication, summarize treatment method, adjust therapeutic scheme, research and analyse Pain mechanisms, collect large sample it is long
There is important practical value in terms of time Clinical Pain relevant information.
Brief description of the drawings
Fig. 1 is eeg signal acquisition circuit of the invention.
Fig. 2 is the annexation between the mobile message collection transmission equipment each several part of the present invention.
Embodiment
The principle and structure of the present invention is referring to shown in Fig. 1,2.The extraction of nociceptive component and expression way in a kind of brain wave,
Be included under various ambient conditions, human body due in brain brain wave caused by pain on pain, analgesia, anxiety, anxiety,
Look forward or upwards absurd, forgetting, the extracting method and expression way of comfortable characteristic component；By the use of brain wave as raw signal processing blocks,
Discretization is collected in computer, applies a variety of mathematical computations algorithms, brain wave is resolved into low frequency, intermediate frequency, high frequency, superelevation
Frequency unit, extract its neutralize pain, analgesia, anxiety, anxiety, look forward or upwards it is absurd, forget, comfortable related characteristic component, by normalization
Processing, is expressed as 0-100 dimensionless number evidence, the pain of real time reaction people, analgesia, anxiety, anxiety, look forward or upwards it is absurd, forget, it is comfortable
Real-time objective quantitative depth；
Using eeg sensor, frons and the ear position on head, the electricity at the noninvasive multiple positions of collection brain are worn on
Position signal, signal enters computing unit, signal bandwidth via preamplifier and multistage integrated circuit and analog-digital converter
Comprising the hyperfrequency composition (the brain wave composition more than more than 30hz) in brain wave, brain wave acquisition lead is set to minimum bag
Two leads of the prefrontal lobe of brain containing left and right or more, via preposition amplification, analog-to-digital conversion, into microcontroller system, then lead to
Cross after data encryption, compression, computer unit is conveyed directly to via wired mode, or via wireless telecommunications control unit
ICP/IP protocol is packed and is sent to internet data service device, and the specical software system in computer or server is to receiving
To EEG signals handle in real time calculating, display, storage, forwarding, wherein calculating section using wavelet analysis, waveform recognition calculate
Method, decompose in brain wave it is various be relevant to the active ingredient and artifact composition of frequency and time domain, and be combined into new data
Stream, then via many algorithms such as fuzzy diagnosis analysis, multiple regression analysis, correlation analysis, multidimensional analysis of spectrums, extract pain
Bitterly, analgesia, anxiety, anxiety, look forward or upwards it is absurd, forget, comfortable characteristic index, by normalized, obtain from the multiple of 0-100
Quantitative data, the pain of real-time objective quantitative response human body, analgesia, anxiety, anxiety, look forward or upwards it is absurd, forget, comfortable degree, obtain
Pain depth, analgesia depth, anxiety depth, nervous depth, look forward or upwards absurd depth, forget depth, comfortable depth factor.
Eeg signal acquisition unit possesses wired and wireless communication capability, and integral pain can be combined into computer
Depth-measuring system, can also be combined into the pain depth survey system of cloud computing mode by internet platform and server
System, forms the Telemedicine shared platform to pain measurement data, and the big data for forming pain measurement collects new model,
Using 232 interface standards, 3G, 4G, bluetooth, WIFI communication technology realize nearly long-range, multi-environment, real-time brain wave acquisition transmission
Terminal, for the brain wave analogue signal of collection amplification, one-chip computer realizes the sliding-model control of analog-to-digital conversion to it, will
Multichannel brain wave discrete signal Real Time Compression, encryption, packing, realize dynamic memory queue management, recognize communication line, automatically
Switch communication mode, communication control is sent, real time data bag or be transferred directly in computer (utilize 232 communication interfaces)
Or via wireless the Internet platform, be sent directly in cloud computing server, via the calculating of computer or cloud computing server
Processing, the pain depth factor of formation, analgesia depth factor, anxiety depth factor, nervous depth factor, delirium depth factor,
Forget depth factor, comfortable depth factor and be shown in terminal or cell phone end.
The adjoint analgesia of pain numerical value, anxiety, anxiety, delirium, forgetting, the quantitative measurment of the comfortable psychological state of mind, from
Synchronously extracted in brain wave analgesia, anxiety, anxiety, look forward or upwards it is absurd, forget, comfortable quantitative expression, in the quantitative table of pain depth
Up to together, the process of pain measurement is completed, the integrality and accuracy of pain measurement is reached；Pain is a kind of table of brain state
It is existing, analgesia, anxiety, anxiety, delirium, forgetting, be also comfortably brain state performance, pain can cause the anxiety of people, anxiety
With delirium, forgetting；Anxiety, the nervous effect again with reinforcement pain degree, particularly in nervous and anxiety state, Ren Mencheng
It will be declined therewith by the threshold value (analgesia) of pain；Anxiety, anxiety, delirium, forgetting, comfortable degree can be with pain
Occur, can also occur in the state of no pain.
The present invention relates to one module of manufacture or an equipment, mobile message collection transmission terminal and related mobile communication
Terminal, fixed terminal, calculating and data management software etc., comprising the acquisition process part and noninvasive electrode for leading brain wave more,
Communication control module and computer, the pain of server, analgesia, anxiety, anxiety, look forward or upwards it is absurd, forget, the brain electricity of level of comfort
Wave characteristic component extracting method and normalization expression way.
Mobile message collection transmission equipment contains pre-amplification circuit, single chip machine controlling circuit, dynamic data link and delayed
Deposit the parts such as circuit, combined wireless communication Access Control circuit, power circuit.
By the brain wave receptor electrode (bioelectrical signals sensor) with patient, by patient lead brain wave letter more
Number collection is sent to the filtering of pre-amplification circuit, noise control, amplification importation, and terminal is respectively fed to through respective channel
One-chip computer control section mould, number change-over circuit in.One-chip computer control section obtains digitized brain wave
(including after high frequency brain wave more than more than 30hz) data, by the data handling procedure of encryption, compression, are obtained after processing
Data flow, feeding dynamic data link buffer queue in.Dynamic data link buffer queue is the data storage and defeated of change
Go out structure.According to the difference of network state, structure of the data in storage region is different.Obtained by single chip machine controlling circuit
After the interrupt event triggering of network state change, the different permutation and combination of data collected are controlled.Under write command control,
Write storage queue data.Data in queue are output to indigo plant in the case where monolithic controls the reading instruction control of circuit through FPDP
Tooth, wifi and 3G, 4G internet communication module.Internet communication module completes auto dialing to network, network state
Identification, the modulation of TCP mode signals, subpackage, the function of output.The eeg datas of leading of collection can be directly with wired, wireless parties more
Formula is sent in computer, and is transmitted automatically into cloud computing server by internet platform simultaneously.
Data center server manages the data that all mobile message collection transmission terminals are sent, and each terminal profile is only
One geocoding, the fixed ip address for adding server by machine number, server number is constituted：
The fixation IP of unique address number+server number+networking services device in the range of terminal machine address=server number
Address
Maximum machine quantity=65535 in networking
Mobile message gathers transmission terminal to be implemented plus densification process and compression for being converted into the data of data signal.Integrate
Data flow enter in incoming link storage queue.Data window is 7-15 bety
L flows window=m+addr+asyn+data
M is the encrypted indicia that module is transmitted, and addr is machine address, and asyn is synchronous, and data is encryption data, including number
Value type data and Wave data
Terminal data is sent and state receives, order receives to be the practical basic assurance of system.It is also that system can pacify
One of key link used entirely.When by the use of computer closely as processing platform, terminal data is directly by calculating
The wifi configured on machine or bluetooth communication port receive data, and operating system and pain measurement application software by computer
Complete all working that data are calculated, show, stored.Original brain wave data is sent to internet platform by terminal simultaneously, if
In fixed cloud processing server chain, data are controlled the corresponding clothes of management software equipped with special webserver application data streams
Business device receives, calculated, storing, display, and is sent result data to internet platform with identical encryption format, for correlation
Personnel share in diverse geographic location, different terminals.Because GPRS or 3G, 4G mechanics of communication are not one on the move
The wireless communication platform of individual complete stability.All too many levels can influence the effect that data are transmitted.For the biography of numeric type data
Send, UDP bags can be used.By the way of repeatedly sending, it is ensured that server can receive a valid data entity.It is right
In the transmission of waveform image, it is desirable to continuity and exclusiveness.The transmission of waveform image must use TCP bags.Calculated using monolithic
The flow-control capability of machine, state and inner buffer size that real-time processing data is sent.Automatic identification and self-recision network are logical
The real-time process of news, and then the direction of control data stream and calling network dialing.There is provided the data link of up to six minutes is moved
State queue region.Ensure the raising of the complete and fault-tolerant ability of data.
Data wait networking in link storage queue.One network state event of network state trigger circuit triggers, meter
The event handling flow of control unit is calculated according to event property, different threaded processing elements are respectively enterd.In normal condition
Under, link data is obtained, with Transmission Control Protocol subpackage, the network address set by wireless network into network and port send agreement
Bag.
Transmission Control Protocol bag +=(save_point++) * real_data → save_point++
Save_point is data address pointer, and real_data is real time data.
Dynamic data link management contains internal storage data queue management, data encryption management, data compression management.Cover
The mutually coordinated function of dynamic that current data is sent.
The data transfer of system, using public network and wireless mode, the encryption of data is dynamic with data content using data structure
The method that state changes, changes regular one：It is the dynamic size according to each lead numerical value, each lead of auto arrangement is in data flow
In position.Second, using 16 binary code weighting algorithms, to the real-time weighted calculation of data flow, generating the data flow of encryption
Send to internet platform.Third, data flow does not include the personally identifiable information of user, corresponding informance is in central station
Use login system in bind.
For Mobile solution, the real time data of each mobile message collection transmission terminal is initially transmitted to terminal address and specified
Cloud computing server chain in a certain server in, server runs special cloud computing processing real-time software bag, data
Forward management software packages, user identity management by synchronization software kit.The calculating of server completion data, identities match, original and knot
Fruit data storage, forwarding, order generation etc. Intelligentized Information monitoring software.Server cloud computing extract real-time pain,
Analgesia, anxiety, anxiety, the quantitative expression for looking forward or upwards absurd, forgetting, comfortable etc. brain state, are distributed in computer, the hand of different location
Machine, mobile flat board etc. intelligent terminal are responsible for the real-time display and alarm of data.Server needs to connect public internet mutual
Networking, it is desirable to configure fixed ip address on the router.Server can realize interconnection with hospital's Intranet, set up intranet and extranet
VPN passages, make result of calculation information enter the Intranet of hospital, the computer of connection hospital Intranet under multiple firewalls protection
(including desktop computer, mobile phone, tablet personal computer etc.) can serve as video data terminal and use, by the power of user of service
Limit control enters the software service of the system.A user identity management server is configured in cloud computing server link, as
The identity registration work station of user (including doctor, follower, patient) is used, and this usual server is arranged at the interior of hospital
In net.Authority is distributed in data acquisition transmission terminal address and user's identity binding by software thereon.It is all to use
Pain, analgesia, anxiety, anxiety, time, the identity for looking forward or upwards absurd, forgetting, the measurement result data of comfortable depth and user of journey
Etc. all information unifications be stored in its corresponding database preserve.
For the non-moving application scenario of medical real-time monitoring, in order to meet the demand that the data display of promptness is expressed,
Upload to the above-mentioned data processing mode of internet platform in real time using data, meanwhile, terminal by the wifi that configures thereon or
Wifi, the bluetooth communication interface of bluetooth communication module and computer (including desktop computer, flat board etc.) closely are realized
Data exchange.Data on computer calculate city edition software logarithm and factually played tricks calculation processing, and the result of acquisition is shown in calculating
On machine screen, the application of the traditional function pattern of medical patient monitor is completed.Meanwhile, cloud computing result it is synchronous be sent to doctor
On the mobile phone of business personnel, the application model of carry-on mobile phone monitor is realized.
PC, the mobile phone of medical worker can directly obtain different by internet internets under corresponding authority
Special-purpose software bag to be installed, mobile phone needs to download special APP application software on the pain medical information of patient, PC.
Rights management will be included in hospital and integrally manage extent of competence.Meanwhile, all operation notes will beam back cloud computing server, as
Follow the trail of, excavate, the initial data of analysis is preserved.Real-time online interaction between doctors and patients between a line two wires doctor is by connecting
Realized between the computer or personal mobile communication terminal of server end, exchange of information is reached by the two-way converting of server
To the purpose of real-time dual-way communication.Real-time interactive function is realized by system software function.
The wireless telecommunications control AM access module that data acquisition transmission terminal is used, can be replaced, mobile phone leads to using mobile phone
The Bluetooth function configured thereon is crossed, under the support of pain measurement application APP softwares, the encrypting traffic that receiving terminal is sent.
And by the process of display, calling, forwarding, real time data synchronization is sent to internet platform.Set between mobile phone and terminal
Socket threads are used in bluetooth communication, pairing, mobile phone A PP, Bluetooth channels are initialized, into flow is received, for receiving
Data-signal, decoding and is shown on mobile phone screen in real time.Simultaneously for the data of decoding, cloud computing therein is extracted
Server address and port address, any processing is not added with by the initial data of receiving, is sent to corresponding cloud computing server,
APP receives the order data and result data of respective server transmission using another Socket thread, and the decryption of data is calculated
Form is same as the data computation scheme of terminal transmission.For result data, data are included the fixation in mobile phone by APP in real time
Screen position, for the change of the condition such as user or doctor's Real Time Observation pain depth.Under pain measurement application software
Load needs user to set corresponding true identity information, by the use of identification card number as unique user identification code, in the same of download
When, the Profile of user is set up in subscriber management server, wherein the letter of the identity comprising patient and the doctor used
Cease, if data confidentiality and ownership requirement, server architecture can be arranged on the interior online of hospital, then anti-by VPN encryptions
Shield passage enters internet platform.Once generating after user profile, mobile phone A PP softwares can just turn into data forwarding and
As a result display terminal.The mobile phone quantity for downloading pain application software is not limited.
For the processing of brain wave, by 1400/s of sample frequency, sampling time window be 1.25s, sampling precision be 10
Position bite sliding-model control, using waveform recognition, Algorithms of Wavelet Analysis, calculates the heterogeneity sequence and each sequence of brain
The temporal signatures of row, multiple dimensioned complexity characteristics.And power spectra algorithm is used, extract rhythm and pace of moving things composition in brain wave and each
The watt level of rhythm and pace of moving things wave band, obtains the result of calculation sequence of coagulation calculating, this sequence pair is answered hundreds of in brain wave
Independent or weak related law characteristic.In the brain wave gathered for forehead bilateral, include the dynamic electric composition of eye and frontalis electricity into
Point.In small echo processing is calculated, both bioelectrical signals sequences can be decomposited, signal intensity and interference signal is used as
Marker characteristic is used.Using small echo formula：
To the electric Vector Groups of brain
Fi (x)=[x1 x2 x3 ... xm-2 xm-1 xm]
i：Brain wave lead quantity, m：Vector element quantity, x：Brain wave data
Real-time calculating processing, with multi-scale filtering device group algorithm, decomposites the wavelet basis function under each scaled window
(Wf(2^j,fj(x)))j∈z
(Wf (2^0, fj (x))), (Wf (2^1, f0 (x))),, (Wf (2^N, fN (x)))
j：Wavelet basis quantity
By wavelet basis function and the inverse transformation of each yardstick data, one group of time domain reconstruction function is obtained as follows：
Fi, j (x)=∑ Wf (2^j, x) * X2^j (x)
Fi, 1 (x), fi, 2 (x),, fi, N (x)；Reconstruction of function, X2^1 (x), X2^2 (x),, X2^N (x), each yardstick
Wavelet data point.N：Exponent number；j：Yardstick quantity, i：Lead number.
Each reconstruction of function represents the brain wave under different scale, and eye moves the performance of electric wave and myoelectricity ripple.Yardstick is also right
The frequency content of induction signal, is distributed in the normal rhythmic and higher frequency rhythms of electroencephalogram.For each sequence of the reconstruction of function of decomposition
Column data, the characteristic point of data is extracted using the waveform recognition algorithm in algorithm for pattern recognition：
Tj(x)∈z；
T：Feature value vector, j：Yardstick, x：Discrete data, represents wave characteristics.z：Time domain space.
Characteristic in vector T j (x) includes distinguished point, amplitude, variation, slope, area, auto-correlation, cross-correlation etc.
Result of calculation, calculating comes from rudimentary algorithm：
Data sequence：Y (t, i)=(f (j)-f (j-1))/Δ t
j：Discrete data subscript, i：Yardstick.
Greatest measure in sequences y (t, i) is obtained, one of characteristic index can be obtained, positive-negative reverse-phase point therein is exactly
Distinguished point, the quantity of distinguished point is represented by the size of t values.
Iteration differential algorithm is applied to f (x) sequence datas：
D (j, i)=∑ (f (j+i)-f (j+i-1)/(Δ t+i))
i：Δ t increment, from 1..N, j：Numerical value sequence number.
For each vector in matrix d (j, i), the data point in vector is sorted and is added, choose each vector
In maximum be added and, be used as slope and amplitude.
For each scaling vector fi (x) in reconstruction of function=[x1 x2 x3 ... xm-2 xm-1 xm], it will handle
Result vector y (t, i), d (j, i) generation mode class ω 1, ω 2 ..., the ω c arrived, then the distance between Land use models function
Calculate the distance of each reconstruction of function.Obtain the variation of reconstruction of function, auto-correlation, cross-correlation numerical value.
Calculate the integration of reconstruction of function：
Si (t)=∫ f (j, i) * Δs t
Try to achieve the area figures of each function.
Tj (x) vectors express the wave characteristics and rule of reconstruction of function.Telecommunications is moved for the eye in the brain wave of collection
Number and frontalis electric signal, be distributed in the reconstruction of function of particular dimensions, for these reconstruction of function, first, ask for therein one
Order derivative：
Di (x)=(fi (x)-fi (x+m))/Δ x
x：Abscissa, Δ x：Abscissa increment.
Di (x) is sorted, maximum and minimum is obtained, given threshold a can be asked for
Di (x) positive-negative polarity change point, obtains one group of extreme point vector：
Mi(j)；High point.
mi(j)；Low spot.
j：The quantity of extreme point.
Integral algorithm is used to related reconstruction of function：
E=∫ fi (t) ^2* Δs t
E1=∫ fj (t) ^2* Δs t
Obtain myoelectricity and the dynamic performance number size of eye.For the above results data, by normalizing combinational algorithm：
Sq=exp (a*abs (Mi-mi)+b*E)；
A, b：Weight coefficient, is determined by signal representation scope.
The quantitative expression Sq of the signal intensity of interference can be obtained indicating, one of display result is used as.
Dynamic and myoelectricity the brain wave reconstruct composition of eye is eliminated in reconstruction of function, using power spectra algorithm：
f(x)：Time domain brain wave discrete data, X (w)：Spectrum power size.
Each composition of power spectrum in brain wave can be obtained, includes the numerical value of α β δ θ wave bands, sef, the edge frequency such as mef
Rate, the numerical value such as dominant frequency：
Fj=α, β, δ, θ,, sef, mef }；
With reference to the characteristic vector obtained by waveform recognition, it is combined into one group and covers time domain and frequency domain, and it is non-linear
The data vector group of complexity result：
Gi (x)={ Tj, Fj }；
i：Yardstick quantity.
Data vector Gi (x) groups, as the single treatment result of brain wave, are named as first number of brain wave coagulation
According to group, the regular characteristic component in hundreds of brain waves is contained in metadata group, can be by the base as secondary calculating
Plinth data.
Some of each yardstick reconstruction of function metadata characteristic is extracted, the corresponding data of wherein each yardstick are calculated
Slope, rate of change and the integral area of ratio, each yardstick data：
Y (x, t)={ Gi (x, t)-Gi (x, t-1)/Δ t } ∈ z；
Zi, j (x)={ Gi (x1)/Gj (x1) } ∈ z；
S (x, t)={ ∫ G (x, t) * Δs t } ∈ z；
D (x, t)={ abs (G (x, t1)-G (x, t2)) } ∈ z；
t：Calculate time point, i, j：Scaling sequence, x：Characteristic vector subscript.z：Calculate space size.
For each above-mentioned data sequence, by data weighting, volume of data calculation formula is obtained：
Ei=a, b, c, d,, and n } * { Yi, Zi, Si, Di }；
i：Data target sequence number.
Apply normalization to Ei data to calculate：
Pain index=(esp (E0)) × 100
Analgesia index=(esp (E1)) × 100
Nervous index=(esp (E2)) × 100
Delirium index=(esp (E3)) × 100
Anxiety index=(esp (E4)) × 100
Forget index=(esp (E5)) × 100
Comfort index=(esp (E5)) × 100；
Obtain the pain in brain wave, analgesia, anxiety, anxiety, look forward or upwards it is absurd, forget, comfortable real-time objective quantitative characteristic refers to
Mark.
Claims (4)
1. the extraction of nociceptive component and expression way in a kind of brain wave, are included under various ambient conditions, human body is due to pain
In caused brain brain wave on pain, analgesia, anxiety, anxiety, look forward or upwards it is absurd, forget, the extracting method of comfortable characteristic component
And expression way；It is characterized in that：By the use of brain wave as raw signal processing blocks, discretization is collected in computer, is applied
Plus mathematical computations analysis, brain wave is resolved into low frequency, intermediate frequency, high frequency, hyperfrequency unit, it is extracted and neutralizes pain, analgesia, Jiao
Consider, it is nervous, look forward or upwards it is absurd, forget, comfortable related characteristic component, by normalized, be expressed as 0-100 dimensionless number evidence,
The pain of real time reaction people, analgesia, anxiety, anxiety, look forward or upwards it is absurd, forget, comfortable real-time objective quantitative depth；Utilize brain fax sense
Device, is worn on frons and the ear position on head, and the electric potential signal at the noninvasive multiple positions of collection brain, signal is put via preceding
Big device and multistage integrated circuit and analog-digital converter enter computing unit, signal bandwidth include in brain wave more than 30hz
Hyperfrequency composition above, brain wave acquisition lead is set to minimum two leads comprising left and right brain prefrontal lobe or more, via
Preposition amplification, analog-to-digital conversion, into microcontroller system, then by data encryption, compression after, directly passed via wired mode
Computer unit is delivered to, or is packed via the ICP/IP protocol of wireless telecommunications control unit and is sent to internet data service
Software systems in device, computer or server handle the EEG signals received calculating, display, storage, forwarding in real time, its
Middle calculating section uses wavelet analysis, waveform recognition algorithm, and that decomposes in brain wave various is relevant to the effective of frequency and time domain
Composition and artifact composition, and new data flow is combined into, then via fuzzy diagnosis analysis, multiple regression analysis, correlation point
Analysis, multidimensional analysis of spectrum, extract pain, analgesia, anxiety, anxiety, look forward or upwards it is absurd, forget, comfortable characteristic index, at normalization
Reason, is obtained from 0-100 multiple quantitative datas, the pain of real-time objective quantitative response human body, analgesia, anxiety, anxiety, look forward or upwards it is absurd,
Forget, comfortable degree, obtain pain depth, analgesia depth, anxiety depth, nervous depth, look forward or upwards absurd depth, forget depth, relax
Suitable depth factor.
2. the extraction of nociceptive component and expression way, eeg signal acquisition unit in a kind of brain wave as claimed in claim 1
Possess wired and wireless communication capability, integral pain depth-measuring system can be combined into computer, can also be passed through
Internet platform and server are combined into the pain depth-measuring system of cloud computing mode, are formed to the remote of pain measurement data
Journey medical services shared platform, the big data for forming pain measurement collects new model, it is characterised in that：Using 232 interface standards,
3G, 4G, bluetooth, WIFI communication technology, realize nearly long-range, multi-environment, real-time brain wave acquisition transmission terminal, amplify for collection
Brain wave analogue signal, one-chip computer realizes the sliding-model control of analog-to-digital conversion to it, by multichannel brain wave discrete signal
Real Time Compression, encryption, packing, realize dynamic memory queue management, recognize communication line, and automatic switching communication modes, control is logical
News are sent, and real time data bag or are directly sent to by 232 communication interfaces in computer or via wireless the Internet platform, directly
Sending and receiving are sent in cloud computing server, are handled via the calculating of computer or cloud computing server, the pain depth factor of formation,
Ease pain depth factor, anxiety depth factor, nervous depth factor, delirium depth factor, forgetting depth factor, comfortable depth factor
It is shown in terminal or cell phone end.
3. the extraction of nociceptive component and expression way in a kind of brain wave as claimed in claim 1, the adjoint analgesia of pain numerical value,
Anxiety, anxiety, delirium, forgetting, the quantitative measurment of the comfortable psychological state of mind, it is characterised in that：Synchronously carried from brain wave
Take out analgesia, anxiety, anxiety, look forward or upwards it is absurd, forget, comfortable quantitative expression, in pain depth quantitative expression together, completion pain
The process of measurement, reaches the integrality and accuracy of pain measurement.
4. the extraction of nociceptive component and expression way in a kind of brain wave as claimed in claim 1, in small echo processing is calculated,
Both bioelectrical signals sequences can be decomposited, are used as the marker characteristic of signal intensity and interference signal；Using small echo
Formula：
To the electric Vector Groups of brain
Fi (x)=[x1 x2 x3 ... xm-2 xm-1 xm]
i：Brain wave lead quantity, m：Vector element quantity, x：Brain wave data
Real-time calculating processing, with multi-scale filtering device group algorithm, decomposites the wavelet basis function under each scaled window
(Wf(2^j,fj(x)))j∈z
(Wf (2^0, fj (x))), (Wf (2^1, f0 (x))),, (Wf (2^N, fN (x)))
j：Wavelet basis quantity
By wavelet basis function and the inverse transformation of each yardstick data, one group of time domain reconstruction function is obtained as follows：
Fi, j (x)=∑ Wf (2^j, x) * X2^j (x)
Fi, 1 (x), fi, 2 (x),, fi, N (x)；Reconstruction of function, X2^1 (x), X2^2 (x),, X2^N (x), each multi-scale wavelet number
Strong point；N：Exponent number；j：Yardstick quantity, i：Lead number；
Each reconstruction of function represents the brain wave under different scale, and eye moves the performance of electric wave and myoelectricity ripple；Yardstick also corresponds to letter
Number frequency content, be distributed in the normal rhythmic and higher frequency rhythms of electroencephalogram；For each sequence number of the reconstruction of function of decomposition
According to extracting the characteristic point of data using the waveform recognition algorithm in algorithm for pattern recognition：
Tj(x)∈z；
T：Feature value vector, j：Yardstick, x：Discrete data, represents wave characteristics；z：Time domain space；
Characteristic in vector T j (x) calculates knot comprising distinguished point, amplitude, variation, slope, area, auto-correlation, cross-correlation etc.
Really, calculate and come from rudimentary algorithm：
Data sequence：Y (t, i)=(f (j)-f (j-1))/Δ t
j：Discrete data subscript, i：Yardstick；
Greatest measure in sequences y (t, i) is obtained, one of characteristic index can be obtained, positive-negative reverse-phase point therein, is exactly specifically
Point, the quantity of distinguished point is represented by the size of t values；
Iteration differential algorithm is applied to f (x) sequence datas：
D (j, i)=∑ (f (j+i)-f (j+i-1)/(Δ t+i))
i：Δ t increment, from 1..N, j：Numerical value sequence number；
For each vector in matrix d (j, i), the data point in vector is sorted and is added, chosen in each vector
Maximum be added and, be used as slope and amplitude；
For each scaling vector fi (x) in reconstruction of function=[x1 x2 x3 ... xm-2 xm-1 xm], processing is obtained
Result vector y (t, i), d (j, i) generation mode class ω 1, ω 2 ..., ω c, then the distance between Land use models function meter
Calculate the distance of each reconstruction of function；Obtain the variation of reconstruction of function, auto-correlation, cross-correlation numerical value；
Calculate the integration of reconstruction of function：
Si (t)=∫ f (j, i) * Δs t
Try to achieve the area figures of each function；
Tj (x) vectors express the wave characteristics and rule of reconstruction of function；For in the brain wave of collection eye move electric signal and
Frontalis electric signal, is distributed in the reconstruction of function of particular dimensions, for these reconstruction of function, first, asks for single order therein and leads
Number：
Di (x)=(fi (x)-fi (x+m))/Δ x
x：Abscissa, Δ x：Abscissa increment；
Di (x) is sorted, maximum and minimum is obtained, given threshold a can be asked for
Di (x) positive-negative polarity change point, obtains one group of extreme point vector：
Mi(j)；High point；
mi(j)；Low spot；
j：The quantity of extreme point；
Integral algorithm is used to related reconstruction of function：
E=∫ fi (t) ^2* Δs t
E1=∫ fj (t) ^2* Δs t
Obtain myoelectricity and the dynamic performance number size of eye；For the above results data, by normalizing combinational algorithm：
Sq=exp (a*abs (Mi-mi)+b*E)；
A, b：Weight coefficient, is determined by signal representation scope；
The quantitative expression Sq of the signal intensity of interference can be obtained indicating, one of display result is used as；
Dynamic and myoelectricity the brain wave reconstruct composition of eye is eliminated in reconstruction of function, using power spectra algorithm：
f(x)：Time domain brain wave discrete data, X (w)：Spectrum power size；
Each composition of power spectrum in brain wave can be obtained, includes the numerical value of α β δ θ wave bands, sef, the marginal frequency such as mef is excellent
The numerical value such as gesture frequency：
Fj=α, β, δ, θ,, sef, mef }；
With reference to the characteristic vector obtained by waveform recognition, it is combined into one group and covers time domain and frequency domain, and non-linear complexity
Spend the data vector group of result：
Gi (x)={ Tj, Fj }；
i：Yardstick quantity；
Data vector Gi (x) groups, as the single treatment result of brain wave, are named as the metadata of brain wave coagulation
The regular characteristic component in hundreds of brain waves is contained in group, metadata group, can be by the basis as secondary calculating
Data；
Some of each yardstick reconstruction of function metadata characteristic is extracted, the ratio of the corresponding data of wherein each yardstick is calculated
Slope, rate of change and the integral area of rate, each yardstick data：
Y (x, t)={ Gi (x, t)-Gi (x, t-1)/Δ t } ∈ z；
Zi, j (x)={ Gi (x1)/Gj (x1) } ∈ z；
S (x, t)={ ∫ G (x, t) * Δs t } ∈ z；
D (x, t)={ abs (G (x, t1)-G (x, t2)) } ∈ z；
t：Calculate time point, i, j：Scaling sequence, x：Characteristic vector subscript；z：Calculate space size；
For each above-mentioned data sequence, by data weighting, volume of data calculation formula is obtained：
Ei=a, b, c, d,, and n } * { Yi, Zi, Si, Di }；
i：Data target sequence number；
Apply normalization to Ei data to calculate：
Pain index=(esp (E0)) × 100
Analgesia index=(esp (E1)) × 100
Nervous index=(esp (E2)) × 100
Delirium index=(esp (E3)) × 100
Anxiety index=(esp (E4)) × 100
Forget index=(esp (E5)) × 100
Comfort index=(esp (E5)) × 100；
Obtain the pain in brain wave, analgesia, anxiety, anxiety, look forward or upwards it is absurd, forget, comfortable real-time objective quantitative characteristic index.
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Cited By (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN109222906A (en) * | 2018-09-13 | 2019-01-18 | 复旦大学 | A method of pain status prediction model is constructed based on brain electrical signals |
| CN109222906B (en) * | 2018-09-13 | 2021-06-04 | 复旦大学 | Method for constructing pain state prediction model based on brain electrical signals |
| CN110393526A (en) * | 2019-08-16 | 2019-11-01 | 北京师范大学 | A kind of high frequency feeble computer signals amplification acquisition system |
| CN112957014A (en) * | 2021-02-07 | 2021-06-15 | 广州大学 | Pain detection and positioning method and system based on brain waves and neural network |
| CN116831595A (en) * | 2023-06-21 | 2023-10-03 | 中国人民解放军西部战区总医院 | Pain grade assessment method |
| CN116831595B (en) * | 2023-06-21 | 2024-04-12 | 中国人民解放军西部战区总医院 | Pain grade assessment method |
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