CN103720462A - Pulse wave signal analyzing method and device - Google Patents
Pulse wave signal analyzing method and device Download PDFInfo
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- CN103720462A CN103720462A CN201310545727.3A CN201310545727A CN103720462A CN 103720462 A CN103720462 A CN 103720462A CN 201310545727 A CN201310545727 A CN 201310545727A CN 103720462 A CN103720462 A CN 103720462A
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Abstract
The invention relates to a pulse wave signal analyzing method and device. The pulse wave signal analyzing method comprises the following steps of (a) receiving pulse wave signals; (b) carrying out optimization processing on the pulse wave signals to obtain improved signals; (c) carrying out analog-digital conversion on the optimized pulse wave signals; (d) identifying an accompany state when the pulse wave signals are collected, executing a step (f) when the accompany state is a static state, and executing a step (e) when the accompany state is a dynamic state; (e) carrying out Fourier transformation on the pulse wave signals processed through the analog-digital conversion; (f) carrying out pulse wave data analysis by combining a characteristic point method and an area graph method to obtain the characteristic quantity of the pulse wave signals. By means of the pulse wave signal analyzing method and device, the characteristic quantity related to cardiovascular indexes can be obtained in a processor executable mode.
Description
Technical field
The present invention relates to signal processing method, more particularly, relate to a kind of pulse wave signal analytical method and device.
Background technology
In stepping into the crowd of high standard of living, the important diseases that cardiovascular disease mortality rate holds pride of place.World Health Organization (WHO) has been classified as the No.1 killer of 2l century harm humans health.The same with most of diseases, early stage detection finds there is obvious help for disease treatment.
The cardiovascular function High altitude method of generally using at present has ultrasoundcardiogram, electrocardio machine drawing, impedance cardiogram and impedance differential ripple figure etc.But these equipment are all expensive special medical instruments, detection technique is complicated, need to have special environmental condition.These equipment all can only provide the quantitative target of parameter in addition, also must make concrete judgement by specialist.These deficiencies have limited these equipment being widely used domestic consumer.
Due to detect without wound, simple to operate, stable performance, the advantage such as cost is low, its practicality has been verified in clinical treatment instrument, pulse wave technology is just becoming the cheap monitoring technology of the domestic consumers such as subhealth state patient in applicable individual patient, person in middle and old age and even young colony.
The analysis that has been found that pulse wave is a kind of effective means for detecting cardiovascular system diseases.In each cardiac cycle, the blood activity of penetrating of heart makes the pressure in arterial produce periodically fluctuation, thereby causes beating of tube wall generating period, is called pulse.Pulse can be propagated along arterial system, claims pulse wave.Each index point (also referred to as flex point) in arteries and veins figure and curve all have clear and definite hemodynamic rheology connotation.The relation of Fig. 8 example arteriosclerosis degree and pulse wave eigenvalue.
A large amount of clinical measured results have confirmed the following fact: the shape of pulse wave, intensity, the R&R reflection much physiology of cardiovascular system of human body and pathological characters; In pulse wave, containing a large amount of hemodynamics information; Hemodynamic parameter variation abnormality or depart from normal value prior to clinical manifestation.
But, how pulse wave signal is carried out to unartificial automatic analysis to obtain the feature of physiological significance, be still the problem that needs solution.
Summary of the invention
Technical problem to be solved by this invention is to provide a kind of pulse wave signal analytical method and device, can carry out pulse wave signal analysis to obtain the characteristic quantity relevant with cardiovascular indicators in the executable mode of processor.
The present invention is that to solve the problems of the technologies described above the technical scheme adopting be to propose a kind of pulse wave signal analytical method, comprises the following steps:
A. receive pulse wave signal;
B. pulse wave signal is optimized to the signal of processing to be improved;
C. the pulse wave signal through optimization process is carried out to analog digital conversion;
D. identify pulse wave signal and follow state when collected, when this follows state to be static state, enter step f, when this is when to follow state be dynamic, enter step e;
E. to carrying out Fourier transformation through analog-to-digital pulse wave signal;
F. pulse wave data analysis is carried out in the combination of use characteristic point method and area graph method, to obtain the characteristic quantity of pulse wave signal.
In one embodiment of this invention, the step that pulse wave signal is optimized to processing comprise amplification, filtering, denoising and shaping partly or entirely.
In one embodiment of this invention, said method also comprise provide reflection this follow the acceleration signal of state.
In one embodiment of this invention, said method comprises: obtain each flex point of this pulse wave signal as characteristic point.
In one embodiment of this invention, this area graph method comprises the characteristic quantity K that calculates pulse wave signal with following formula:
Wherein,
p (t) pulse wave signal, T is interval;
P
gfor the maximum of pulse wave signal P (t) in interval T, P
dfor the minima of pulse wave signal P (t) in interval T.
The present invention also proposes a kind of pulse wave signal analytical equipment, comprises pulse wave optimization unit and microprocessor.This pulse wave is optimized unit and is received pulse wave signal, and pulse wave signal is optimized to the signal of processing to be improved.This microprocessor comprises analog to digital conversion circuit, signal recognition circuit, Fourier-transform circuitry and data analysis circuit.Analog to digital conversion circuit carries out analog digital conversion to the pulse wave signal through optimization process, and exports Fourier-transform circuitry and signal recognition circuit to.Signal recognition circuit connects this analog to digital conversion circuit, identification pulse wave signal is followed state when collected, when this is when to follow state be dynamic, indication Fourier-transform circuitry is carried out Fourier transformation, when this follows state to be static state, provide through analog-to-digital pulse wave signal to data analysis circuit.Fourier-transform circuitry connects this analog to digital conversion circuit and this signal recognition circuit, to carrying out Fourier transformation through analog-to-digital pulse wave signal.Data analysis circuit connects this Fourier-transform circuitry and this signal recognition circuit, and pulse wave data analysis is carried out in the combination of use characteristic point method and area graph method, to obtain the characteristic quantity of pulse wave signal.
In one embodiment of this invention, said apparatus also comprises acceleration transducer, detects the acceleration signal of following state reflecting when this pulse wave signal is collected.
In one embodiment of this invention, said apparatus also comprises signal amplification circuit, is connected between this analog to digital conversion circuit and this signal recognition circuit.
In one embodiment of this invention, said apparatus also comprises data storing circuit, connects this data analysis circuit.
The present invention, owing to adopting above technical scheme, makes it compared with prior art, by pulse wave signal is carried out to a series of processing, and finally in the executable mode of processor, obtains the characteristic quantity relevant with cardiovascular indicators.The present invention can be applied in cheapness, operate in easy electronic equipment, is applicable to non-medical skill personnel for family healthcare monitoring.
Accompanying drawing explanation
For above-mentioned purpose of the present invention, feature and advantage can be become apparent, below in conjunction with accompanying drawing, the specific embodiment of the present invention is elaborated, wherein:
Fig. 1 illustrates for implementing the example structure of pulse wave analysis device of the present invention.
Fig. 2 illustrates the example composition that pulse wave signal shown in Fig. 1 is optimized unit.
The example that Fig. 3 illustrates microprocessor shown in Fig. 1 forms.
Fig. 4 illustrates the pulse wave analysis method flow diagram of one embodiment of the invention.
Fig. 5 illustrates typical pulse wave.
Fig. 6 illustrates the extraction schematic diagram of pulse waveform characteristic quantity K value.
Fig. 7 illustrates the data analysis flow chart of pulse wave.
The relation of Fig. 8 example arteriosclerosis degree and pulse wave eigenvalue.
the specific embodiment
Fig. 1 illustrates for implementing the example structure of pulse wave analysis device of the present invention.Shown in Fig. 1, analytical equipment 100 can comprise pulse wave signal optimization unit 110, acceleration transducer 120, microprocessor 130 and output unit 140.Pulse wave signal is optimized the input of unit 110 can introduce pulse wave signal.For example, pulse wave signal optimization unit 110 can be connected to a pulse wave sensor to obtain pulse wave signal.Pulse wave signal is optimized the first input end IN1 of the outfan connection microprocessor 130 of unit 110.Acceleration transducer 120 connects the second input IN2 of microprocessor 130.Microprocessor 130 has three outfans, and the first outfan OUT1 connects pulse wave signal and optimizes unit 110, the second outfan OUT2 connection acceleration transducer 120, the three outfans connection output units 140.
Pulse wave signal is optimized unit 110 for realizing the optimization process to pulse wave signal.Through the pulse wave signal of optimizing, there is better quality, contribute to improve the accuracy of subsequent analysis.The exemplary circuit of pulse wave signal optimization unit 110 as shown in Figure 2, comprises the pre-amplification circuit 201, baseline correction circuit 202, wave filter 203, wave trap 204 and the shaping circuit 205 that connect successively.These circuit respectively to signal amplify, filtering, denoising, shaping, to obtain the signal that quality is higher.Wherein, baseline correction circuit 202 is mainly used in eliminating the baseline drift causing due to muscle twitches, human body is nervous, breathing is trembled etc.Baseline correction circuit 202 can comprise voltage follower and in-phase adder.
In one embodiment of this invention, the model of acceleration transducer can be ADXL345.
In an embodiment of the present invention, microprocessor 130 can adopt on-chip system chip, or adopts the independently combination of microprocessor chip and peripheral circuit.
The example that Fig. 3 illustrates microprocessor shown in Fig. 1 forms.Shown in Fig. 3, microprocessor 130 has input IN1, IN2, outfan OUT1, OUT2 and OUT3.IN1 is pulse wave signal input, and IN2 is acceleration signal input.OUT1 and OUT2 are respectively the optimal control outfan for pulse signal and acceleration signal.OUT3 is data output end.
Fourier-transform circuitry 303 connects analog to digital conversion circuit 301, pulse wave signal can be transformed from the time domain to frequency domain.Preferably, the conversion that Fourier-transform circuitry 303 is carried out is real time fourier processing (hereinafter to be referred as RFT).
Signal recognition circuit 304, provides the kinestate about carrier for the data analysis circuit 305 to rear class.
Data analysis circuit 305 connects Fourier-transform circuitry 303 and signal recognition circuit 304, can with reference to the signal of the two, carry out the data analysis of pulse wave, obtains the characteristic quantity of required reflection cardiovascular physiology index.The intermediate data that data analysis circuit 305 produces and final data can be stored in data storage circuitry 306.Data analysis circuit 305 connection data outfan OUT3, to provide pulse wave signal and analysis result to outside.
Data analysis circuit 305 also connects optimal control circuit 307.Optimal control circuit 307 connects optimal control outfan OUT1 and the OUT2 of pulse signal and acceleration signal.
In one embodiment, the pulse wave analysis device shown in Fig. 1 is as an integral module, embeds in the products such as wearable product (as wrist strap, wrist-watch), mobile phone, panel computer, notebook computer, appliance for personal care, and pulse wave analysis function is provided.When embedded product is the such small sized product of wrist strap, wrist-watch, the output unit 140 of pulse wave analysis device is for being configured to wireless transport module, to export based on short-range communication protocols such as WIFI, 2.4GZigBee, bluetooths the data of being analyzed.When embedded product is the such product of panel computer, notebook computer, output unit 140 can be the interface of panel computer, notebook computer to access pulse wave analysis device.
In another embodiment, the pulse wave analysis device shown in Fig. 1 can be split as two parts on entity.First is the combination that pulse wave signal is optimized unit 110 and acceleration transducer 120.Second portion is microprocessor 130 and output unit 140.Pulse wave signal is optimized unit 110 and acceleration transducer 120 can embed in wearable product.For example, pulse wave signal is optimized unit 110 and acceleration transducer 120 can be installed with pulse transducer integral type.And the annexation that pulse wave signal is optimized between unit 110 and acceleration transducer 120 and microprocessor 130 is wireless connections.
When reality is implemented, the example model of microprocessor 130 is CC2530.CC2530 is a kind of on-chip system chip, the module one such as collection analog-digital converter, operational amplifier, microprocessor, memorizer, radio frequency transmission.
The pulse wave analysis method of one embodiment of the invention can be implemented in the pulse wave analysis device 100 shown in Fig. 1, but is not construed as limiting.The pulse wave analysis method of the present embodiment can be implemented on any suitable device.Fig. 4 illustrates the pulse wave analysis method flow diagram of one embodiment of the invention.Shown in Fig. 4, method flow is as follows:
In step 401, will receive pulse wave signal.
For example, pulse wave signal is optimized unit 110 by the pulse wave sensor acquisition pulse wave signal from being attached thereto.
In step 402, pulse wave signal is optimized to processing.
Such as optimize the amplification of carrying out signal in unit 110, filtering, denoising, shaping etc. at pulse wave signal, with the signal being improved.
In step 403, the pulse wave signal through optimization process is carried out to analog digital conversion.
For example, the 301 pairs of pulse wave signals of analog to digital conversion circuit in microprocessor 130 carry out analog digital conversion, obtain the pulse wave signal of digital form.
In step 404, identification pulse wave signal is followed state when collected.For example, acquisition target is static or dynamic in the collected moment of signal.For portable set, the action of carrier may impact the gatherer process of pulse wave, so the present embodiment is by detecting pulse wave signal following state to alleviate or eliminating this impact when collected.
For example, the action that acceleration transducer 120 can sensing user also provides acceleration signal to the signal recognition circuit 304 in microprocessor 130.Signal recognition circuit 304 can obtain pulse wave signal from signal amplification circuit 302, and to identify each pulse wave signal position user be dynamic or static.If user is static, can directly the pulse wave signal of obtaining be carried out to arteries and veins map analysis, flow process directly enters step 406.On the contrary, if user is dynamic, pulse wave signal can be submerged in interfering signal, need in interfering signal, extract correct pulse wave signal.In the present embodiment, use Fourier transform to carry out the conversion of time/frequency-region signal and realize the extraction of pulse wave signal.Flow process enters step 405.
In step 405, to carrying out Fourier transformation through analog-to-digital pulse wave signal.
For example, the 303 pairs of pulse wave signals of Fourier-transform circuitry in microprocessor 130 carry out Fourier transformation, and signal is transformed from the time domain to frequency domain.
In step 406, carry out pulse wave data analysis.In the present embodiment, this analysis is that combination by method of characteristic point and area graph method realizes.This will launch to describe later.
For instance, can the data analysis circuit 305 in microprocessor 130 carry out pulse wave data analysis.
Method of characteristic point will be identified the characteristic point of pulse wave.The characteristic point of pulse wave is exactly in fact pulse wave pressure curve
flex point.Characteristic point is that cardiac cycle changes the transition point of another mechanical process into from a mechanical process, thereby these flex points have clear and definite physiological significance.Fig. 5 illustrates typical pulse wave.As shown in the typical pulse waveform of Fig. 5, its A, B, C, tetra-characteristic points of D have reflected the different physiology of human body and pathological change in the height fluctuations of arteries and veins figure.
Area graph method is to take the extracting method of pulse wave area change as pulse waveform characteristic quantity K value.Fig. 6 illustrates the extraction schematic diagram of pulse waveform characteristic quantity K value.Shown in Fig. 6, aforesaid
with straight line, be labeled in the waveform that is spaced apart T of pulse wave signal P (t).According to following formula:
Can obtain characteristic quantity K value.P wherein
gfor the maximum of pulse wave signal P (t) in interval T, P
dfor the minima of pulse wave signal P (t) in interval T.
Cardiovascular physiology and pathological change will cause the respective change of arteries and veins figure waveform and area, and it can be reflected in the variation of K value, not only regular, and quite responsive, are important physical signs of cardiovascular clinical examination.
Conclude, the pulse wave data analysing method of the present embodiment as shown in Figure 7, can comprise the steps:
In step 701, read in pulse wave data P (t).
In step 702, search the characteristic point in pulse wave data P (t).For example the characteristic point A in Fig. 5, B, C, D.This can obtain by calculating the flex point of P (t).
In step 703, the value that keeps current P (t) characteristic point is P (t) ', the i.e. value of regeneration characteristics point.
In step 704, calculated characteristics amount K value.
In step 705, keeping current K value is K ', i.e. regeneration characteristics amount.
In step 706, relatively K value, P (t) characteristic point obtain variation value.
In step 707, according to the comparative result of step 706, determine whether early warning.
Because method of characteristic point physiological significance is clear and definite, the pulse wave data analysis of the present embodiment is by each characteristic point of identification pulse wave, extract features relevant amount, differentiate the variation tendency of characteristic quantity, can utilize area graph method to supplement simultaneously and revise the analysis to the shape of pulse wave, area, intensity, R&R variation.
Result based on above-mentioned analysis, when finding the variation abnormality of pulse wave, according to its corresponding pathological characters development trend seriousness, can produce early warning signal.
Therefore the pulse wave analysis method and apparatus of the embodiment of the present invention, makes the detection operation based on pulse wave very simple and relatively inexpensive, is more suitable for non-medical skill personnel and guards for family healthcare.
Although the present invention describes with reference to current specific embodiment, but those of ordinary skill in the art will be appreciated that, above embodiment is only for the present invention is described, in the situation that not departing from spirit of the present invention, also can make variation or the replacement of various equivalences, therefore, as long as the variation of above-described embodiment, modification all will be dropped in the application's the scope of claims within the scope of connotation of the present invention.
Claims (9)
1. a pulse wave signal analytical method, comprises the following steps:
A. receive pulse wave signal;
B. pulse wave signal is optimized to the signal of processing to be improved;
C. the pulse wave signal through optimization process is carried out to analog digital conversion;
D. identify pulse wave signal and follow state when collected, when this follows state to be static state, enter step f, when this is when to follow state be dynamic, enter step e;
E. to carrying out Fourier transformation through analog-to-digital pulse wave signal;
F. pulse wave data analysis is carried out in the combination of use characteristic point method and area graph method, to obtain the characteristic quantity of pulse wave signal.
2. pulse wave signal analytical method as claimed in claim 1, is characterized in that, the step that pulse wave signal is optimized to processing comprises the part or all of of amplification, filtering, denoising and shaping.
3. pulse wave signal analytical method as claimed in claim 1, is characterized in that, also comprise provide reflection this follow the acceleration signal of state.
4. pulse wave signal analytical method as claimed in claim 1, is characterized in that, this method of characteristic point comprises: obtain each flex point of this pulse wave signal as characteristic point.
5. pulse wave signal analytical method as claimed in claim 1, is characterized in that, this area graph method comprises the characteristic quantity K that calculates pulse wave signal with following formula:
Wherein,
p (t) pulse wave signal, T is interval;
P
gfor the maximum of pulse wave signal P (t) in interval T, P
dfor the minima of pulse wave signal P (t) in interval T.
6. a pulse wave signal analytical equipment, comprising:
Pulse wave is optimized unit, receives pulse wave signal, and pulse wave signal is optimized to the signal of processing to be improved;
Microprocessor, comprising:
Analog to digital conversion circuit, carries out analog digital conversion to the pulse wave signal through optimization process, and exports Fourier-transform circuitry and signal recognition circuit to;
Signal recognition circuit, connect this analog to digital conversion circuit, identification pulse wave signal is followed state when collected, when this is when to follow state be dynamic, indication Fourier-transform circuitry is carried out Fourier transformation, when this follows state to be static state, provide through analog-to-digital pulse wave signal to data analysis circuit;
Fourier-transform circuitry, connects this analog to digital conversion circuit and this signal recognition circuit, to carrying out Fourier transformation through analog-to-digital pulse wave signal;
Data analysis circuit, connects this Fourier-transform circuitry and this signal recognition circuit, and pulse wave data analysis is carried out in the combination of use characteristic point method and area graph method, to obtain the characteristic quantity of pulse wave signal.
7. pulse wave signal analytical equipment as claimed in claim 6, is characterized in that, also comprises:
Acceleration transducer, detects the acceleration signal of following state reflecting when this pulse wave signal is collected.
8. pulse wave signal analytical equipment as claimed in claim 6, is characterized in that, also comprises:
Signal amplification circuit, is connected between this analog to digital conversion circuit and this signal recognition circuit.
9. pulse wave signal analytical equipment as claimed in claim 6, is characterized in that, also comprises:
Data storing circuit, connects this data analysis circuit.
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Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN104082920A (en) * | 2014-06-24 | 2014-10-08 | 吕志雪 | Smart bracelet |
| CN108720821A (en) * | 2018-05-28 | 2018-11-02 | 京东方科技集团股份有限公司 | A kind of blood pressure estimation device and blood pressure estimating system |
Citations (9)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| EP0645117A1 (en) * | 1993-09-28 | 1995-03-29 | Seiko Epson Corporation | Blood pulse wave detecting apparatus and motion intensity measuring apparatus |
| US20040086060A1 (en) * | 2002-10-04 | 2004-05-06 | Keisuke Tsubata | Pulse wave detecting apparatus and fourier transform process apparatus |
| CN101785667A (en) * | 2010-01-15 | 2010-07-28 | 北京工业大学 | Waveform characteristic point based method for analyzing volume pulse wave pattern and detection device |
| CN201668380U (en) * | 2010-06-13 | 2010-12-15 | 南京信息工程大学 | Pulse signal collecting and processing system |
| CN201912069U (en) * | 2010-05-06 | 2011-08-03 | 桂林电子科技大学 | Portable pulse wave detector |
| US20110282224A1 (en) * | 2009-02-03 | 2011-11-17 | Omron Healthcare Co., Ltd. | Pulse wave analyzer and pulse wave analyzing method |
| CN102499669A (en) * | 2011-10-26 | 2012-06-20 | 中国科学院深圳先进技术研究院 | Heart parameter measuring method and device |
| CN103054562A (en) * | 2012-12-25 | 2013-04-24 | 中国科学院合肥物质科学研究院 | Cardiovascular function detection method based on multi-channel pulse wave form analysis and device thereof |
| JP2013085702A (en) * | 2011-10-18 | 2013-05-13 | Toyota Central R&D Labs Inc | Device and program for estimation of biosignals |
-
2013
- 2013-11-06 CN CN201310545727.3A patent/CN103720462A/en active Pending
Patent Citations (9)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| EP0645117A1 (en) * | 1993-09-28 | 1995-03-29 | Seiko Epson Corporation | Blood pulse wave detecting apparatus and motion intensity measuring apparatus |
| US20040086060A1 (en) * | 2002-10-04 | 2004-05-06 | Keisuke Tsubata | Pulse wave detecting apparatus and fourier transform process apparatus |
| US20110282224A1 (en) * | 2009-02-03 | 2011-11-17 | Omron Healthcare Co., Ltd. | Pulse wave analyzer and pulse wave analyzing method |
| CN101785667A (en) * | 2010-01-15 | 2010-07-28 | 北京工业大学 | Waveform characteristic point based method for analyzing volume pulse wave pattern and detection device |
| CN201912069U (en) * | 2010-05-06 | 2011-08-03 | 桂林电子科技大学 | Portable pulse wave detector |
| CN201668380U (en) * | 2010-06-13 | 2010-12-15 | 南京信息工程大学 | Pulse signal collecting and processing system |
| JP2013085702A (en) * | 2011-10-18 | 2013-05-13 | Toyota Central R&D Labs Inc | Device and program for estimation of biosignals |
| CN102499669A (en) * | 2011-10-26 | 2012-06-20 | 中国科学院深圳先进技术研究院 | Heart parameter measuring method and device |
| CN103054562A (en) * | 2012-12-25 | 2013-04-24 | 中国科学院合肥物质科学研究院 | Cardiovascular function detection method based on multi-channel pulse wave form analysis and device thereof |
Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN104082920A (en) * | 2014-06-24 | 2014-10-08 | 吕志雪 | Smart bracelet |
| CN108720821A (en) * | 2018-05-28 | 2018-11-02 | 京东方科技集团股份有限公司 | A kind of blood pressure estimation device and blood pressure estimating system |
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Application publication date: 20140416 |