CN106419884A - Heart rate calculating method and system based on wavelet analysis - Google Patents
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- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
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- A61B5/00—Measuring for diagnostic purposes; Identification of persons
- A61B5/02—Detecting, measuring or recording pulse, heart rate, blood pressure or blood flow; Combined pulse/heart-rate/blood pressure determination; Evaluating a cardiovascular condition not otherwise provided for, e.g. using combinations of techniques provided for in this group with electrocardiography or electroauscultation; Heart catheters for measuring blood pressure
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Abstract
The invention provides a heart rate calculating method based on wavelet analysis. The heart rate calculating method comprises the following steps: classifying the motion state according to the statistical characteristic value and wave crest characteristic value of acceleration signals; and carrying out n-order wavelet decomposition on photoelectric signals, carrying out de-noising processing on the photoelectric signals after wavelet decomposition by combining with the motion state, and carrying out wavelet reconstruction, wherein the heart rate result obtained after calculation is high in accuracy and good in stability. Meanwhile, when a user is under different motion state environments, with the system for the heart rate calculating method provided by the invention, the current motion state of the user can be judged, further, the heart rate value is calculated, and the heart rate result obtained through calculation is good in reliability.
Description
Technical field
The present invention relates to the technical field of information processing, especially relate to a kind of rate calculation method based on wavelet analysis
With system.
Background technology
In recent years, with the continuous improvement of living standards of the people, national health receives more and more attention, Neng Gousui
The Intelligent worn device that body measures physiological parameter will be following research direction.
Heart rate refers to the number of times of heartbeat in the unit interval.In human parameters detection, heart rate is an important life
Reason index, provides reference for medical diagnosis.Meanwhile, heart rate also can be used as the objective evaluation index of human motion physiological stress.
Occur in that on the market at present and much utilize photoelectric sensor to calculate the bracelet of heart rate.But this bracelet is transported in user
The signal that when dynamic, sensor receives has interference, and rate calculation result has relatively large deviation.When especially body part moves, such as brush
Tooth, shake the hand, the heart rate end value that bracelet records is generally higher than actual value.Patent CN103767696A is passed through to analyze extreme point
To calculate heart rate, but this rate calculation method is easily disturbed by local motion.Patent CN101176662A calculates pole
After value point, the method for the most ballot of application exports a gained vote highest heart rate value, and method needs the sampling of long period
Exact value could be obtained.
Content of the invention
The technical problem to be solved is, provides and a kind of can accurately calculate heart rate under different motion states
Method and system, the signal being received with solving photoelectric sensor present in prior art is interfered the heart rate leading to record
The false problem of result.
For achieving the above object, the invention provides following technical scheme：
A kind of rate calculation method based on wavelet analysis, comprises the following steps：
S1. acceleration signal and the photosignal of acquisition units time are distinguished；
S2. the analysis statistical characteristics of acceleration signal and crest characteristic value, carries out static, locally to the motion state of user
Motion and the classification of motions of mass motion, obtain the first motion state；
S3. N rank wavelet decomposition is carried out to photosignal, obtain N rank coefficient of wavelet decomposition deccoeff；The first fortune in conjunction with S2
Dynamic state carries out denoising to N rank coefficient of wavelet decomposition deccoeff, carries out wavelet reconstruction, the signal after being processed afterwards
reccoeff；This, N=6.
S4. the extreme point of the signal reccoeff after processing is positioned, be calculated the first heart rate value.
During due to only distinguishing local motion and mass motion with acceleration signal, some local motions can be divided into whole
In body motion.In order to reduce the erroneous judgement of motion state, further, described rate calculation method, also includes whole to being mistaken for
The correction of first heart rate value of local motion state of body motion：
If the first motion state obtained by S2 is mass motion state, the first heart rate obtaining after execution step S3 and S4
Value is less than the heart rate threshold that sets, then the first motion state is modified to local motion state, and again execution step S3 and
The operation of S4, and the first heart rate value is modified, obtain the second heart rate value.Second heart rate value obtains after being by revising,
By wavelet decomposition twice and wavelet reconstruction, improve the accuracy in computation of heart rate value.
Further describing as technical scheme, the classification of motions of described step S2, specifically include following
Step：
（1）Calculate the statistical characteristics of acceleration signal：Average and variance；Positioning is entered to the crest of acceleration signal, calculates
To crest characteristic value：The distance between crest number, the height of each crest, adjacent peaks, and it is calculated average crest height
With average peak away from；
（2）Statistical characteristics according to acceleration signal and crest characteristic value, carry out static, local fortune to the motion state of user
The dynamic classification of motions with mass motion, obtains the first motion state：
If a. average is less than average threshold value, variance is less than variance threshold values, and crest number is less than crest number first threshold, then
First motion state is set to inactive state；
If b. crest number is more than crest number Second Threshold, average crest height is more than the threshold value of average crest height, puts down
All peak away from less than average peak away from threshold value, then the first motion state be set to local motion state；By comparing crest number, putting down
All crest height and average peak away from corresponding threshold value, can by shaking hand, the high-frequency action such as brush teeth correctly be divided into local
In the middle of motion.
C., in addition to a and b, remaining first motion state is set to mass motion state.
Further describing as technical scheme, the denoising of described step S3, specifically include following step
Suddenly：
（1）Calculate the mean μ of i-th layer of coefficient of wavelet decompositioniAnd variances sigmai,
（2）According to the first motion state obtained by S2, determine the λ value of denoising function；
A. when the first motion state is inactive state, λ=σi；
B. when the first motion state is local motion state, λ=μi；
C. when the first motion state is mass motion state, λ=μi-pσi, described p value is 0.1 or 0.2 or 0.3；
（3）Select denoising function soft-threshold function or hard threshold function, and the λ value according to the denoising function determining, to small echo
Decomposition coefficient carries out denoising,
Soft-threshold function is：；
Hard threshold function is：.
Present invention also offers a kind of rate calculation system, this system is using the heart rate based on wavelet analysis as above
Computational methods, specifically include：
（1）Signal acquisition module：Acceleration signal by acceleration transducer and photoelectric sensor difference acquisition units time
And photosignal.
（2）Acceleration signal analysis module：Statistical analysis is carried out to the acceleration signal collecting, obtains average and variance
Statistical characteristics；Positioning is entered to the crest of acceleration signal, is calculated crest characteristic value：Crest number, the height of each crest
Degree, the distance between adjacent peaks, and be calculated average crest height peace all peaks away from.
（3）Photosignal wavelet decomposition module：By wavelet-decomposing method, multilayer is decomposed into the photosignal collecting,
After low frequency resolution filter is to original signal data filtering process, then carry out down-sampled obtaining approximation coefficient；In high-frequency decomposition
After wave filter is to original signal data filtering process, then carry out down-sampled obtaining detail coefficients.
Denoising module：The λ value of the denoising function determining, selects denoising function, coefficient of wavelet decomposition is carried out at denoising
Reason.
（4）Wavelet reconstruction processing module：Including low-frequency reconfiguration wave filter and high frequency reconstruction wave filter；Approximation coefficient is adopted upper
After sample, it is filtered processing by low-frequency reconfiguration wave filter, obtains low frequency filtering result；Detail coefficients up-sampling after,
It is filtered processing by high frequency reconstruction wave filter, obtain High frequency filter result；By above-mentioned low frequency filtering result and high frequency filter
Ripple results added has then obtained wavelet reconstruction result.
Based on above-mentioned technical scheme, the technique effect that the present invention obtains is：
（1）Rate calculation method, the statistical characteristics according to acceleration signal and crest characteristic value that the present invention provides, to motion
State is classified；Photosignal after wavelet decomposition is processed carries out wavelet reconstruction with reference to motion state after denoising,
Calculated heart rate result precision is high, good stability.Meanwhile, it is under different motion state environment in user, use
The system of the rate calculation method of the present invention may determine that the motion state residing for user, and then calculates heart rate value, meter further
The heart rate result reliability obtaining is good.
（2）In addition, in order to prevent the erroneous judgement to motion state, the present invention pass through with reference to motion state, calculated the
One heart rate value and the heart rate threshold setting, the correction to the first heart rate value of the local motion state being mistaken for mass motion,
The confidence level that general warranty heart rate value calculates.
Brief description
Fig. 1 is the schematic flow sheet of the rate calculation method of embodiments of the invention.
Fig. 2 is the correction of first heart rate value to the local motion state being mistaken for mass motion of embodiments of the invention
Schematic flow sheet.
Specific embodiment
The invention will be further described with specific embodiment below in conjunction with the accompanying drawings, but does not limit the scope of the present invention.
Embodiment 1
As shown in figure 1, giving a kind of rate calculation method based on wavelet analysis in the present embodiment.Wavelet analysis is Fourier
One kind of analysis, Fourier analysis is to represent the translation of a function cosine function and stretching, and wavelet analysis is to use
Generating function to represent through translating and stretching.
With reference to the schematic flow sheet of Fig. 1, this rate calculation method specifically includes following steps：Signal data acquisition 100,
The acceleration signal of acquisition units time and photosignal respectively；Analysis acceleration signal 211, this is included to acceleration signal
Statistical characteristics and crest characteristic value next be analyzed and calculate, static, office to be carried out to the motion state of user
Portion's motion and the classification of motions of mass motion, obtain the first motion state 212；Simultaneously it is also desirable to process to photosignal,
Based on the principle of wavelet analysis, this time N rank wavelet decomposition 221 is carried out to photosignal, obtained N rank coefficient of wavelet decomposition
deccoeff 222；After having respectively obtained the first above-mentioned motion state and N rank coefficient of wavelet decomposition deccoeff, the two knot
Altogether so that denoising 300, in the present embodiment, N=6 are carried out to N rank coefficient of wavelet decomposition.Execute wavelet reconstruction afterwards,
Signal reccoeff after being processed, and the extreme point of the signal reccoeff after processing is carried out positioning 400, it is calculated
First heart rate value 500.
In the present embodiment, obtain the first motion state 212 in order to more fully understand analysis acceleration signal 211 with classifying
Concrete steps, are this time described for classification of motions：
Calculate the statistical characteristics of acceleration signal, such as average and variance；Meanwhile, positioning, meter are entered to the crest of acceleration signal
Calculation obtains crest characteristic value, such as the distance between crest number, the height of each crest, adjacent peaks, is calculated flat further
All crest height and average peak away from；Statistical characteristics according to acceleration signal and crest characteristic value, to needing to carry out heart rate survey
The motion state of fixed user carries out the classification of motions of static, local motion and mass motion, obtains the first motion state.Classification
Method is as follows：
If average is less than average threshold value, variance is less than variance threshold values, and crest number is less than crest number first threshold, then first
Motion state is set to inactive state；
If crest number is more than crest number Second Threshold, average crest height is more than the threshold value of average crest height, averagely
Peak away from less than average peak away from threshold value, then the first motion state be set to local motion state；By comparing crest number, average
Crest height and average peak away from corresponding threshold value, can by shaking hand, the high-frequency action such as brush teeth correctly be divided into local fortune
In the middle of dynamic.
In addition to above two situation, remaining first motion state is set to mass motion state.
In the present embodiment, as further describing of denoising 300 step, the step for specifically include：
, calculate the mean μ of i-th layer of coefficient of wavelet decomposition respectively taking i-th layer of coefficient of wavelet decomposition as a exampleiAnd variances sigmai；According to
The first motion state 212 arriving, determines the λ value of denoising function；
When the first motion state is inactive state, λ=σi；When the first motion state is local motion state, λ=μi；When
When one motion state is mass motion state, λ=μi-pσi, p value can be 0.1 or 0.2 or 0.3, permissible in debugging process
P value is carried out with test and obtains suitable debugging value；
As needed, suitable denoising function, such as soft-threshold function or hard threshold function are selected, and according to the denoising letter determining
The λ value of number, carries out denoising to coefficient of wavelet decomposition,
Soft-threshold function is：；
Hard threshold function is：.
The rate calculation method based on wavelet analysis, the statistical characteristics according to acceleration signal and ripple that the present invention provides
Peak characteristic value, classifies to motion state；Photosignal after wavelet decomposition is processed combines motion state through denoising
After carry out wavelet reconstruction, calculated heart rate result precision is high, good stability.
Embodiment 2
As shown in Fig. 2 during due to only distinguishing local motion and mass motion with acceleration signal, some local motions can be drawn
Assign in mass motion.In order to reduce the erroneous judgement of motion state, in this embodiment, it is mistaken for overall fortune in rate calculation method
The correction of the first heart rate value of dynamic local motion state.With reference to Fig. 2 to the local motion state being mistaken for mass motion
The schematic flow sheet of the correction of the first heart rate value, specific modification method is：If first obtained by motion state classification
Motion state is mass motion state 21, and the first heart rate value obtaining after execution denoising and wavelet reconstruction step is less than and sets
The heart rate threshold 22 reserved, the heart rate threshold of the present embodiment is the threshold value setting in advance, a usually empirical value.This
Sample, then be modified to local motion state 30 by the first motion state, and execute again and carry out denoising to coefficient of wavelet decomposition
40 and the operation of wavelet reconstruction 50 step, and the first heart rate value is modified, obtain the second heart rate value 60.Second heart rate value is
Obtain after being modified, by wavelet decomposition twice and wavelet reconstruction, improve the accuracy in computation of heart rate value.
Embodiment 3
Based on the rate calculation method of motion state classification, wavelet decomposition and wavelet reconstruction, present embodiments provide one kind and be based on
The rate calculation system of wavelet analysis, specifically includes signal acquisition module, acceleration signal analysis module, the little wavelength-division of photosignal
Solution module, denoising module and wavelet reconstruction processing module.Wherein, signal acquisition module passes through acceleration transducer and photoelectric sensing
The device acceleration signal of acquisition units time and photosignal respectively.In acceleration signal analysis module, to the acceleration collecting
Degree signal carries out statistical analysis, obtains the statistical characteristics of average and variance；Positioning is entered to the crest of acceleration signal, calculates
To crest characteristic value, including the distance between crest number, the height of each crest, adjacent peaks, and it is calculated average crest
Height and average peak away from.In photosignal wavelet decomposition module, the photosignal collecting is divided by wavelet-decomposing method
Solve as multilayer, after low frequency resolution filter is to original signal data filtering process, then carry out down-sampled obtaining approximation coefficient；?
After high-frequency decomposition wave filter is to original signal data filtering process, then carry out down-sampled obtaining detail coefficients.Denoising module, then exist
After the λ value of denoising function has determined, select denoising function, denoising is carried out to coefficient of wavelet decomposition.At wavelet reconstruction
Reason module, including low-frequency reconfiguration wave filter and high frequency reconstruction wave filter；Approximation coefficient, after up-sampling, is filtered by low-frequency reconfiguration
Ripple device is filtered processing, and obtains low frequency filtering result；Detail coefficients, after up-sampling, are carried out by high frequency reconstruction wave filter
Filtering process, obtains High frequency filter result；Above-mentioned low frequency filtering result and High frequency filter results added have then been obtained small echo
Reconstruction result.
It is under different motion state environment in user, the system with the rate calculation of the present embodiment may determine that use
Motion state residing for family, and then calculate heart rate value further, so calculated heart rate result reliability is good.
Above content is only the method for the present invention and system example and explanation, and its description is more concrete and detailed
Carefully, but therefore can not be interpreted as the restriction to the scope of the claims of the present invention.It should be pointed out that the common skill for this area
For art personnel, without departing from the inventive concept of the premise, some deformation can also be made and improve, these are obvious
Alternative forms belong to protection scope of the present invention.
Claims (6)
1. a kind of rate calculation method based on wavelet analysis is it is characterised in that comprise the following steps：
S1. acceleration signal and the photosignal of acquisition units time are distinguished；
S2. the analysis statistical characteristics of acceleration signal and crest characteristic value, carries out static, locally to the motion state of user
Motion and the classification of motions of mass motion, obtain the first motion state；
S3. N rank wavelet decomposition is carried out to photosignal, obtain N rank coefficient of wavelet decomposition deccoeff；The first fortune in conjunction with S2
Dynamic state carries out denoising to N rank coefficient of wavelet decomposition deccoeff, carries out wavelet reconstruction, the signal after being processed afterwards
reccoeff；
S4. the extreme point of the signal reccoeff after processing is positioned, be calculated the first heart rate value.
2. the rate calculation method based on wavelet analysis according to claim 1 is it is characterised in that described rate calculation
Method, also includes the correction of the first heart rate value to the local motion state being mistaken for mass motion：
If the first motion state obtained by S2 is mass motion state, the first heart rate obtaining after execution step S3 and S4
Value is less than the heart rate threshold that sets, then the first motion state is modified to local motion state, and again execution step S3 and
The operation of S4, is modified to the first heart rate value, obtains the second heart rate value.
3. the rate calculation method based on wavelet analysis according to claim 1 is it is characterised in that the fortune of described step S2
Dynamic classification, specifically includes following steps：
（1）Calculate the statistical characteristics of acceleration signal：Average and variance；Positioning is entered to the crest of acceleration signal, calculates
To crest characteristic value：The distance between crest number, the height of each crest, adjacent peaks, and it is calculated average crest height
With average peak away from；
（2）Statistical characteristics according to acceleration signal and crest characteristic value, carry out static, local fortune to the motion state of user
The dynamic classification of motions with mass motion, obtains the first motion state：
If a. average is less than average threshold value, variance is less than variance threshold values, and crest number is less than crest number first threshold, then
First motion state is set to inactive state；
If b. crest number is more than crest number Second Threshold, average crest height is more than the threshold value of average crest height, puts down
All peak away from less than average peak away from threshold value, then the first motion state be set to local motion state；
C., in addition to a and b, remaining first motion state is set to mass motion state.
4. according to claim 1 based on the rate calculation method of wavelet analysis it is characterised in that going of described step S3
Make an uproar process, specifically include following steps：
（1）Calculate the mean μ of i-th layer of coefficient of wavelet decompositioniAnd variances sigmai,
（2）According to the first motion state obtained by S2, determine the λ value of denoising function；
A. when the first motion state is inactive state, λ=σi；
B. when the first motion state is local motion state, λ=μi；
C. when the first motion state is mass motion state, λ=μi-pσi, described p value is 0.1 or 0.2 or 0.3；
（3）Select denoising function soft-threshold function or hard threshold function, and the λ value according to the denoising function determining, to small echo
Decomposition coefficient carries out denoising,
Described soft-threshold function is：；
Described hard threshold function is：.
5. the rate calculation method based on wavelet analysis according to claim 1 is it is characterised in that described N=6.
6. a kind of rate calculation system based on wavelet analysis, using as described in any one of claim 1-4 based on little wavelength-division
The rate calculation method of analysis is it is characterised in that include：
Signal acquisition module：By acceleration transducer and the photoelectric sensor acceleration signal of acquisition units time and light respectively
Electric signal；
Acceleration signal analysis module：Statistical analysis is carried out to the acceleration signal collecting, obtains the statistics of average and variance
Characteristic value；Positioning is entered to the crest of acceleration signal, is calculated crest characteristic value：Crest number, the height of each crest, adjacent
The distance between crest, and be calculated average crest height peace all peaks away from；
Photosignal wavelet decomposition module：By wavelet-decomposing method, multilayer is decomposed into the photosignal collecting, in low frequency
After resolution filter is to original signal data filtering process, then carry out down-sampled obtaining approximation coefficient；In high-frequency decomposition wave filter
After original signal data filtering process, then carry out down-sampled obtaining detail coefficients；
Denoising module：The λ value of the denoising function determining, selects denoising function, carries out denoising to coefficient of wavelet decomposition；
Wavelet reconstruction processing module：Including low-frequency reconfiguration wave filter and high frequency reconstruction wave filter；Approximation coefficient up-sampling after,
It is filtered processing by low-frequency reconfiguration wave filter, obtain low frequency filtering result；Detail coefficients up-sampling after, by high frequency
Reconfigurable filter is filtered processing, and obtains High frequency filter result；By above-mentioned low frequency filtering result and High frequency filter result phase
Plus then obtained wavelet reconstruction result.
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| CN109199355A (en) * | 2018-09-18 | 2019-01-15 | 深圳和而泰数据资源与云技术有限公司 | Heart rate information detection method, device and detection device |
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| CN109009059B (en) * | 2018-09-11 | 2021-03-30 | 江苏鹿得医疗电子股份有限公司 | Heart rate calculation method based on heart sounds |
| CN109199355A (en) * | 2018-09-18 | 2019-01-15 | 深圳和而泰数据资源与云技术有限公司 | Heart rate information detection method, device and detection device |
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