CN104887215A - Signal processing method in heart rate measurement - Google Patents
Signal processing method in heart rate measurement Download PDFInfo
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- CN104887215A CN104887215A CN201510323890.4A CN201510323890A CN104887215A CN 104887215 A CN104887215 A CN 104887215A CN 201510323890 A CN201510323890 A CN 201510323890A CN 104887215 A CN104887215 A CN 104887215A
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- 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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- A—HUMAN NECESSITIES
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Abstract
The invention provides a signal processing method in heart rate measurement, which comprises the following steps: judging the acceptance or rejection of the time domain data by using a statistical method; frequency domain data, frequencies below the minimum possible heart rate being discarded, peaks in the neighborhood of the minimum possible heart rate of each main peak being discarded; the adopted frequency spectrum peaks are judged and determined one by one according to several possible frequency multiplication relations; in the case that the frequency multiplication component in the original data is small, differentiating the original data to highlight frequency multiplication; and finally, determining whether the heart rate result is adopted or not according to the quality of straight line fitting and the straight line intercept. The invention can obtain a relatively accurate heart rate value and has wide and profound application prospect in the field of heart rate measurement.
Description
Technical field
The present invention relates to medical treatment and signal processing field, particularly relate to the signal processing method in a kind of heart rate measurement.
Background technology
Along with the progress of society, growth in the living standard, the health status of people to self is more and more paid close attention to; The health concerns point developing into people of electronic technology, computer technology, low-power consumption computing technique provides the realization rate of technology.Traditional medicine apparatus can provide enough accurate measurement result, but, because traditional medicine apparatus needs to use at Code in Hazardous Special Locations, use also comfortable not, measure simultaneously and cannot carry out at any time.These restrictive conditions cannot allow everybody in comfortable environment, the mood loosened, understand health status whenever and wherever possible.
Due to the development of chip technology, a lot of low-power consumption, the processor of miniaturization and sensor are there is.Collaborative by these processors and sensor; the physiological data of a lot of human body can be measured in real time, continuously, easily; such as walking, motion, in the daily routines process such as diet; the data that can describe human body physical sign can be obtained; in conjunction with related algorithm, the physiological parameters such as body temperature, heart rate, blood oxygen, respiratory frequency, muscle tone can be obtained.Whole process can ignore these processors completely and depositing of sensor is carried out in case people.The important application of Internet of Things industry in measuring of human health field that Here it is rises gradually.
The heart rate of people is an important indicator of human body physical sign, uses frequent in clinical, motion, routine health monitoring.At present, heart rate measurement is a very important application direction in measuring of human health field.Reliable heart rate measurement device allows the user moved with usual household the heart rate situation current to oneself can have certain understanding, is conducive to there is an anticipation to ongoing activity or motion.The method of heart rate measurement is a lot, can be time-domain analysis also can be frequency-domain analysis.Time-domain analysis is easily limited by interfering signal, and time-domain signal is forwarded to frequency-region signal by Fourier transform, to greatest extent various interfering signal is separated, and obtains heart rate signal accurately by filtering and various judgement, further, can calculate heart rate.
In view of the above, be necessary to provide the signal processing method in a kind of heart rate measurement, to improve the accuracy that heart rate calculates.
Summary of the invention
The shortcoming of prior art in view of the above, the object of the present invention is to provide the signal processing method in a kind of heart rate measurement, for solving the accurate not problem of heart rate measurement in prior art.
For achieving the above object and other relevant objects, the invention provides the signal processing method in a kind of heart rate measurement, described signal processing method comprises step:
1) the heart rate initial data of a period of time is gathered with certain sample frequency;
2) by the segmentation of heart rate initial data, calculate mean square deviation and the peak-to-peak value of every segment data, if certain section of mean square deviation and peak-to-peak value are greater than variance threshold values and peak-to-peak value threshold value, then this segment data is judged as irrational data segment;
3) irrational data segment reasonable data is replaced, the selection of reasonable data makes the data segment after replacing and does not have saltus step between data segment its last period, adjust all data segments below simultaneously and guarantee do not have saltus step, Using such method obtains the data rebuild;
4) do fast fourier transform to the data rebuild, delivery obtains the spectrum value data of domain space;
5) for the spectrum value data of domain space, the spectrum value that frequency is less than lowest frequency value all gets 0, and wherein, described lowest frequency value is frequency values corresponding to human body minimal heart rate;
6) search for spectral peak, according to the height descending at peak, the peak after arrangement, searches for backward from first peak, and the peak appeared in this left and right, peak lowest frequency value is directly deleted;
7) retain three the highest peaks, and revise the position at each peak;
8) for the frequency location at the highest three peaks, judge its optimal frequency position relationship, if optimal frequency position relationship criterion is less than judgment threshold, then exit calculating, otherwise continue to calculate;
9) fitting a straight line of frequency is done according to optimal frequency position relationship, and the frequency values at each peak after digital simulation, the goodness of fit is lower than fit threshold, or the intercept absolute value of fitting a straight line is greater than intercept threshold value, then exit calculating, otherwise continues to calculate;
10) frequency at the place, three peaks obtained by the frequency location relation matching adopted, digital simulation data, get average as final heart rate result respectively.
As a kind of preferred version of the signal processing method in heart rate measurement of the present invention, step 8) in, if optimal frequency position relationship criterion is less than judgment threshold, then forward step to a) to do centered difference to heart rate initial data and obtain new original data, wherein, in new original data, the n-th data are that in old initial data, (n+1)th data deducts (n-1)th data, and, using the original data of new original data as subsequent step; Wherein, step a) performs in step 1) and step 2) between;
If performed step a) ~ step 8) after, optimal frequency position relationship criterion is still less than judgment threshold, then exit calculating, otherwise continue calculate.
As a kind of preferred version of the signal processing method in heart rate measurement of the present invention, step 9) in, if the goodness of fit is lower than fit threshold, or the intercept absolute value of fitting a straight line is greater than intercept threshold value, then forward step to a) to do centered difference to heart rate initial data and obtain new original data, wherein, in new original data, the n-th data are that in old initial data, (n+1)th data deducts (n-1)th data, further, using the original data of new original data as subsequent step; Wherein, step a) performs in step 1) and step 2) between;
If performed step a) ~ step 9) after, the goodness of fit is still lower than fit threshold, or the intercept absolute value of fitting a straight line is still greater than intercept threshold value, then exit calculating, otherwise continue calculate.
As a kind of preferred version of the signal processing method in heart rate measurement of the present invention, step 1) in, Minimum sample rate meets: the peak frequency that needs adopt is three times of the frequency that people's maximum possible heart rate is corresponding, and the sample frequency determined according to sampling thheorem is at least the twice of this peak frequency.
As a kind of preferred version of the signal processing method in heart rate measurement of the present invention, step 2) in, the segmentation of heart rate initial data is according to being: may consider by heart rate so that people is minimum, every segment data all comprises at least one complete heart rate cycle.
As a kind of preferred version of the signal processing method in heart rate measurement of the present invention, step 2) in, variance threshold values and peak-to-peak value threshold value can set a fixed value, also can produce in real time in program is run, or two kinds of methods are comprehensive, comprising:
The value that initial setting one is larger, the judgement later at every turn calculated thinks that acceptable mean square deviation becomes new variance threshold values and peak-to-peak value threshold value after multiplying factor with after original threshold value weighted average respectively respectively; Or
After each data sectional, get from each section minimum mean square deviation respectively after multiplying factor as threshold value, simultaneously, this threshold value can not more than a numerical value, and namely maximum threshold value, exceedes this max-thresholds, then all data segments are all unacceptable, cannot carry out follow-up calculating.
As a kind of preferred version of the signal processing method in heart rate measurement of the present invention, step 2) in, variance threshold values and peak-to-peak value threshold value determination method are: after each data sectional, the section of Minimum Mean Square Error is selected from each section, with three of its mean square deviation times for variance threshold values, nine times is peak-to-peak value threshold value.
As a kind of preferred version of the signal processing method in heart rate measurement of the present invention, step 3) in, irrational data segment is carried out replacement and comprises:
Direct use fixed value replaces unreasonable data segment, and the straightway after replacement and front and back data segment do not have saltus step; Or
Repeat fill-error data segment with rational data segment, the data segment after replacement and front and back data segment do not have saltus step, if all data segments are all wrong, then stop calculating, wait for next group data; If all data segments are reasonable, data are constant.
As a kind of preferred version of the signal processing method in heart rate measurement of the present invention, step 5) in, described human body minimal heart rate is for being not less than 40 beats/min, and described lowest frequency value is for being not more than 0.67Hz.
As a kind of preferred version of the signal processing method in heart rate measurement of the present invention, step 7) in, adopt the position at each peak of method correction of fitting of parabola, Gaussian function form fit or Cauchy-Lorenz function form fit.
As a kind of preferred version of the signal processing method in heart rate measurement of the present invention, step 8) in, for the frequency location at the highest three peaks, judge that its position relationship comprises: 1:2:3,1:3:4,1:2:4, preferentially judge with the position relationship of last computation, first time gives tacit consent to and judges 1:2:3, gets optimum, as optimal frequency position relationship after judgement.
As mentioned above, the invention provides the signal processing method in a kind of heart rate measurement, there is following beneficial effect: the present invention's statistical method judges the choice of time domain data; Frequency domain data, the frequency lower than minimum possibility heart rate is given up, and the peak in the minimum possibility heart rate neighborhood of each main peak is given up; The spectral peak adopted judges to determine according to possible several frequency multiplication relations one by one, and the situation that harmonic is less in initial data, to initial data difference with outstanding frequency multiplication; The quality of last fitting a straight line and Linear intercept determine whether heart rate result adopts.The present invention can obtain more accurate heart rate value, has extensive and far-reaching application prospect in heart rate measurement field.
Accompanying drawing explanation
Fig. 1 is shown as the steps flow chart schematic diagram of the signal processing method in heart rate measurement of the present invention.
Fig. 2 is shown as in the signal processing method in heart rate measurement of the present invention, the position relationship of each spectral peak judges schematic diagram, wherein, the >4 peak, >3 peak, >2 peak, intensity No. 1 peak at peak is shown as in figure.
Element numbers explanation
1 No. 1 peaks
2 No. 2 peaks
3 No. 3 peaks
4 No. 4 peaks
S1 ~ S10 step 1) ~ step 10)
Detailed description of the invention
Below by way of specific instantiation, embodiments of the present invention are described, those skilled in the art the content disclosed by this description can understand other advantages of the present invention and effect easily.The present invention can also be implemented or be applied by detailed description of the invention different in addition, and the every details in this description also can based on different viewpoints and application, carries out various modification or change not deviating under spirit of the present invention.
Refer to shown in Fig. 1 ~ Fig. 2.It should be noted that, the diagram provided in the present embodiment only illustrates basic conception of the present invention in a schematic way, then only the assembly relevant with the present invention is shown in graphic but not component count, shape and size when implementing according to reality is drawn, it is actual when implementing, and the kenel of each assembly, quantity and ratio can be a kind of change arbitrarily, and its assembly layout kenel also may be more complicated.
As shown in Fig. 1 ~ Fig. 2, the present embodiment provides the signal processing method in a kind of heart rate measurement, and described signal processing method comprises step:
As shown in Figure 1, first carry out step 1) S1, the heart rate initial data of a period of time is gathered with certain sample frequency.
Exemplarily, Minimum sample rate meets: the peak frequency that needs adopt is three times of the frequency that people's maximum possible heart rate is corresponding, and the sample frequency determined according to sampling thheorem is at least the twice of this peak frequency.
Particularly, because the heart rate range of people is generally at 40 ~ 220bpm (number of times per minute), corresponding frequency is exactly 0.67 ~ 3.67Hz, because the present invention needs the second harmonic using heart rate, also be 11Hz, therefore sample frequency is at least 22Hz, or higher.The present invention needs to carry out fast fourier transform at low power processor, and therefore data volume is as far as possible little, and such as, in the present embodiment, adopt the sample frequency of 25Hz, sampled data 128 is approximately 5.12s; The interval that heart rate calculates is less than this time, calculates the data participation calculating that start time pushes away forward 5.12s.
As shown in Figure 1, then carry out step 2) S2, by the segmentation of heart rate initial data, calculate mean square deviation and the peak-to-peak value of every segment data, if certain section of mean square deviation and peak-to-peak value are greater than variance threshold values and peak-to-peak value threshold value, then this segment data is judged as irrational data segment.
Exemplarily, the segmentation of heart rate initial data is according to being: may consider by heart rate so that people is minimum, every segment data all comprises at least one complete heart rate cycle.
Particularly, heart rate initial data can be divided into two sections, every section comprises 16 ~ 128 data, and in the present embodiment, every section comprises 64 data.Certainly, also initial data can be divided into 4 sections etc., every section of data amount check comprised also reasonably can adjust according to demand, is not limited to cited example herein.
Exemplarily, variance threshold values and peak-to-peak value threshold value can set a fixed value, also can produce in real time in program is run, or two kinds of methods are comprehensive, comprising:
The value that initial setting one is larger, the judgement later at every turn calculated thinks that acceptable mean square deviation becomes new variance threshold values and peak-to-peak value threshold value after multiplying factor with after original threshold value weighted average respectively respectively; Or
After each data sectional, get from each section minimum mean square deviation respectively after multiplying factor as threshold value, simultaneously, this threshold value can not more than a numerical value, and namely maximum threshold value, exceedes this max-thresholds, then all data segments are all unacceptable, cannot will carry out follow-up calculating.
In the present embodiment, variance threshold values and peak-to-peak value threshold value determination method are: after each data sectional, from each section, select the section of Minimum Mean Square Error, with three of its mean square deviation times for variance threshold values, nine times is peak-to-peak value threshold value
As shown in Figure 1, then carry out step 3) S3, irrational data segment reasonable data is replaced, the selection of reasonable data makes the data segment after replacing and does not have saltus step between data segment its last period, adjust all data segments below simultaneously and guarantee do not have saltus step, Using such method obtains the data rebuild.
Exemplarily, irrational data segment is carried out replacement to comprise:
Direct use fixed value replaces unreasonable data segment, and the straightway after replacement and front and back data segment do not have saltus step; Or
Repeat fill-error data segment with rational data segment, the data segment after replacement and front and back data segment do not have saltus step, if all data segments are all wrong, then stop calculating, wait for next group data; If all data segments are reasonable, data are constant.
As shown in Figure 1, then carry out step 4) S4, do fast fourier transform to the data rebuild, delivery obtains the spectrum value data of domain space.
As shown in Figure 1, then carry out step 5) S5, for the spectrum value data of domain space, the spectrum value that frequency is less than lowest frequency value all gets 0, and wherein, described lowest frequency value is frequency values corresponding to human body minimal heart rate.
In the present embodiment, described human body minimal heart rate is for being not less than 40 beats/min, and described lowest frequency value is for being not more than 0.67Hz, and in the present embodiment, the lowest frequency value of employing is 0.67Hz.
As shown in Figure 1, then carry out step 6) S6, search spectral peak, according to the height descending at peak, the peak after arrangement, searches for backward from first peak, and the peak appeared in this left and right, peak lowest frequency value is directly deleted.
Due to the effective heart rate of peak general proxy the highest in certain limit, and the minimal heart rate of general human body is for being not less than 40 beats/min, corresponding frequency is 0.67Hz, therefore, if there is peak again within the scope of this highest left and right, peak 0.67Hz, then can be judged to be invalid peak, it is directly deleted the accuracy that greatly can improve heart rate measurement.
As shown in Figure 1, then carry out step 7) S7, retain three the highest peaks, and revise the position at each peak.
Exemplarily, the position at each peak of method correction of fitting of parabola, Gaussian function form fit or Cauchy-Lorenz function form fit can be adopted.
In the present embodiment, the position at each peak of method correction of fitting of parabola is adopted, using the frequency values of parabolical vertex correspondence as the revised frequency location in this peak.
As shown in Figures 1 and 2, then carry out step 8) S8, for the frequency location at the highest three peaks, judge its optimal frequency position relationship, if optimal frequency position relationship criterion is less than judgment threshold, exit calculating, otherwise continue to calculate.
As shown in Figure 2, particularly, for the frequency location at the highest three peaks, judge that its position relationship comprises: 1:2:3, 1:3:4, 1:2:4 and 2:3:4, preferentially judge with the position relationship of last computation, first time gives tacit consent to and judges 1:2:3, optimum is got after judgement, as optimal frequency position relationship, Figure 2 shows that optimum position relationship is 1:2:3, this is more common a kind of position relationship, namely putting in order of the highest peak is followed successively by No. 1 peak, No. 2 peaks, No. 3 peaks and No. 4 peaks, strength relationship is >4 peak, >3 peak, >2 peak, No. 1 peak.Certainly, owing to gathering or signal disturbing equal error, also likely occur as situations such as 1:2:4,1:3:4, this relation also can accept.The situation then less appearance of 2:3:4.
In addition, in the embodiment that another is more excellent, if optimal frequency position relationship criterion is less than judgment threshold, then forward step to a) to do centered difference to heart rate initial data and obtain new original data, wherein, in new original data, the n-th data are that in old initial data, (n+1)th data deducts (n-1)th data, and, using the original data of new original data as subsequent step; Wherein, step a) performs in step 1) and step 2) between.
If re-executed step a) ~ step 8) after, optimal frequency position relationship criterion is still less than judgment threshold, then exit calculating, otherwise continue calculate.
As shown in Figure 1, then carry out step 9) S9, the fitting a straight line of frequency is done according to optimal frequency position relationship n1:n2:n3, and the frequency values at each peak after digital simulation, the goodness of fit (GOF) is lower than fit threshold, or the intercept absolute value of fitting a straight line is greater than intercept threshold value, exits calculating, otherwise continue to calculate.
In addition, in the embodiment that another is more excellent, if the goodness of fit is lower than fit threshold, or the intercept absolute value of fitting a straight line is greater than intercept threshold value, then forward step to a) to do centered difference to heart rate initial data and obtain new original data, wherein, in new original data, the n-th data are that in old initial data, (n+1)th data deducts (n-1)th data, further, using the original data of new original data as subsequent step; Wherein, step a) performs in step 1) and step 2) between.
If re-executed step a) ~ step 9) after, the goodness of fit is still lower than fit threshold, or the intercept absolute value of fitting a straight line is still greater than intercept threshold value, then exit calculating, otherwise continue calculate.
As shown in Figure 1, finally carry out step 10) S10, the frequency at the place, three peaks obtained by the frequency location relation matching adopted, digital simulation data, get average as final heart rate result respectively.
After the present embodiment adopts place, multiple peak frequency to carry out matching, then the heart rate result that the method be averaged obtains, there is higher reliability, greatly can improve the accuracy of heart rate measuring and calculating.
As mentioned above, the invention provides the signal processing method in a kind of heart rate measurement, described signal processing method comprises step: the heart rate initial data 1) gathering a period of time with certain sample frequency; 2) by the segmentation of heart rate initial data, calculate mean square deviation and the peak-to-peak value of every segment data, if certain section of mean square deviation and peak-to-peak value are greater than variance threshold values and peak-to-peak value threshold value, then this segment data is judged as irrational data segment; 3) irrational data segment reasonable data is replaced, the selection of reasonable data makes the data segment after replacing and does not have saltus step between data segment its last period, adjust all data segments below simultaneously and guarantee do not have saltus step, Using such method obtains the data rebuild; 4) do fast fourier transform to the data rebuild, delivery obtains the spectrum value data of domain space; 5) for the spectrum value data of domain space, the spectrum value that frequency is less than lowest frequency value all gets 0, and wherein, described lowest frequency value is frequency values corresponding to human body minimal heart rate; 6) search for spectral peak, according to the height descending at peak, the peak after arrangement, searches for backward from first peak, and the peak appeared in this left and right, peak lowest frequency value is directly deleted; 7) retain three the highest peaks, and revise the position at each peak; 8) for the frequency location at the highest three peaks, judge its optimal frequency position relationship, if optimal frequency position relationship criterion is less than judgment threshold, then forward step to a) to do centered difference to heart rate initial data and obtain new original data, wherein, in new original data, the n-th data are that in old initial data, (n+1)th data deducts (n-1)th data, and, using the original data of new original data as subsequent step; Wherein, step a) performs in step 1) and step 2) between; 9) fitting a straight line of frequency is done according to optimal frequency position relationship, and the frequency values at each peak after digital simulation, if the goodness of fit is lower than fit threshold, or the intercept absolute value of fitting a straight line is greater than intercept threshold value, then forward step to a) to do centered difference to heart rate initial data and obtain new original data, wherein, in new original data, the n-th data are that in old initial data, (n+1)th data deducts (n-1)th data, further, using the original data of new original data as subsequent step; Wherein, step a) performs in step 1) and step 2) between; 10) frequency at the place, three peaks obtained by the frequency location relation matching adopted, digital simulation data, get average as final heart rate result respectively.The present invention's statistical method judges the choice of time domain data; Frequency domain data, the frequency lower than minimum possibility heart rate is given up, and the peak in the minimum possibility heart rate neighborhood of each main peak is given up; The spectral peak adopted judges to determine according to possible several frequency multiplication relations one by one; The situation that harmonic is less in initial data, to initial data difference with outstanding frequency multiplication; The quality of last fitting a straight line and Linear intercept determine whether heart rate result adopts.The present invention can obtain more accurate heart rate value, has extensive and far-reaching application prospect in heart rate measurement field.So the present invention effectively overcomes various shortcoming of the prior art and tool high industrial utilization.
Above-described embodiment is illustrative principle of the present invention and effect thereof only, but not for limiting the present invention.Any person skilled in the art scholar all without prejudice under spirit of the present invention and category, can modify above-described embodiment or changes.Therefore, such as have in art usually know the knowledgeable do not depart from complete under disclosed spirit and technological thought all equivalence modify or change, must be contained by claim of the present invention.
Claims (11)
1. the signal processing method in heart rate measurement, is characterized in that, described signal processing method comprises step:
1) the heart rate initial data of a period of time is gathered with certain sample frequency;
2) by the segmentation of heart rate initial data, calculate mean square deviation and the peak-to-peak value of every segment data, if certain section of mean square deviation and peak-to-peak value are greater than variance threshold values and peak-to-peak value threshold value, then this segment data is judged as irrational data segment;
3) irrational data segment reasonable data is replaced, the selection of reasonable data makes the data segment after replacing and does not have saltus step between data segment its last period, adjust all data segments below simultaneously and guarantee do not have saltus step, Using such method obtains the data rebuild;
4) do fast fourier transform to the data rebuild, delivery obtains the spectrum value data of domain space;
5) for the spectrum value data of domain space, the spectrum value that frequency is less than lowest frequency value all gets 0, and wherein, described lowest frequency value is frequency values corresponding to human body minimal heart rate;
6) search for spectral peak, according to the height descending at peak, the peak after arrangement, searches for backward from first peak, and the peak appeared in this left and right, peak lowest frequency value is directly deleted;
7) retain three the highest peaks, and revise the position at each peak;
8) for the frequency location at the highest three peaks, judge its optimal frequency position relationship, if optimal frequency position relationship criterion is less than judgment threshold, then exit calculating, otherwise continue to calculate;
9) fitting a straight line of frequency is done according to optimal frequency position relationship, and the frequency values at each peak after digital simulation, the goodness of fit is lower than fit threshold, or the intercept absolute value of fitting a straight line is greater than intercept threshold value, then exit calculating, otherwise continues to calculate;
10) frequency at the place, three peaks obtained by the frequency location relation matching adopted, digital simulation data, get average as final heart rate result respectively.
2. the signal processing method in heart rate measurement according to claim 1, it is characterized in that: step 8) in, if optimal frequency position relationship criterion is less than judgment threshold, then forward step to a) to do centered difference to heart rate initial data and obtain new original data, wherein, in new original data, the n-th data are that in old initial data, (n+1)th data deducts (n-1)th data, and, using the original data of new original data as subsequent step; Wherein, step a) performs in step 1) and step 2) between
If performed step a) ~ step 8) after, optimal frequency position relationship criterion is still less than judgment threshold, then exit calculating, otherwise continue calculate.
3. the signal processing method in heart rate measurement according to claim 1 and 2, it is characterized in that: step 9) in, if the goodness of fit is lower than fit threshold, or the intercept absolute value of fitting a straight line is greater than intercept threshold value, then forward step to a) to do centered difference to heart rate initial data and obtain new original data, wherein, in new original data, the n-th data are that in old initial data, (n+1)th data deducts (n-1)th data, further, using the original data of new original data as subsequent step; Wherein, step a) performs in step 1) and step 2) between.
If performed step a) ~ step 9) after, the goodness of fit is still lower than fit threshold, or the intercept absolute value of fitting a straight line is still greater than intercept threshold value, then exit calculating, otherwise continue calculate.
4. the signal processing method in heart rate measurement according to claim 1, it is characterized in that: step 1) in, Minimum sample rate meets: the peak frequency that needs adopt is three times of the frequency that people's maximum possible heart rate is corresponding, and the sample frequency determined according to sampling thheorem is at least the twice of this peak frequency.
5. the signal processing method in heart rate measurement according to claim 1, is characterized in that: step 2) in, the segmentation of heart rate initial data is according to being: may consider by heart rate so that people is minimum, every segment data all comprises at least one complete heart rate cycle.
6. the signal processing method in heart rate measurement according to claim 1, it is characterized in that: step 2) in, variance threshold values and peak-to-peak value threshold value can set a fixed value, also can produce in real time in program is run, or two kinds of methods is comprehensive, comprising:
The value that initial setting one is larger, the judgement later at every turn calculated thinks that acceptable mean square deviation becomes new variance threshold values and peak-to-peak value threshold value after multiplying factor with after original threshold value weighted average respectively respectively; Or
After each data sectional, get from each section minimum mean square deviation respectively after multiplying factor as threshold value, simultaneously, this threshold value can not more than a numerical value, and namely maximum threshold value, exceedes this max-thresholds, then all data segments are all unacceptable, cannot will carry out follow-up calculating.
7. the signal processing method in heart rate measurement according to claim 1, it is characterized in that: step 2) in, variance threshold values and peak-to-peak value threshold value determination method are: after each data sectional, the section of Minimum Mean Square Error is selected from each section, with three of its mean square deviation times for variance threshold values, nine times is peak-to-peak value threshold value.
8. the signal processing method in heart rate measurement according to claim 1, is characterized in that: step 3) in, irrational data segment is carried out replacement and comprises:
Direct use fixed value replaces unreasonable data segment, and the straightway after replacement and front and back data segment do not have saltus step; Or
Repeat fill-error data segment with rational data segment, the data segment after replacement and front and back data segment do not have saltus step, if all data segments are all wrong, then stop calculating, wait for next group data; If all data segments are reasonable, data are constant.
9. the signal processing method in heart rate measurement according to claim 1, is characterized in that: step 5) in, described human body minimal heart rate is for being not less than 40 beats/min, and described lowest frequency value is for being not more than 0.67Hz.
10. the signal processing method in heart rate measurement according to claim 1, is characterized in that: step 7) in, adopt the position at each peak of method correction of fitting of parabola, Gaussian function form fit or Cauchy-Lorenz function form fit.
Signal processing method in 11. heart rate measurements according to claim 1, it is characterized in that: step 8) in, for the frequency location at the highest three peaks, judge that its position relationship comprises: 1:2:3,1:3:4,1:2:4, preferentially judge with the position relationship of last computation, first time gives tacit consent to and judges 1:2:3, gets optimum, as optimal frequency position relationship after judgement.
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