CN101642369A - Autonomic nervous function biological feedback method and system - Google Patents
Autonomic nervous function biological feedback method and system Download PDFInfo
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Abstract
The invention relates to an autonomic nervous function biological biological feedback method and an autonomic nervous function biological biological feedback system. Based on the acquisition of heartrate variability physiological parameter values by testing, the state of the autonomic nervous function reflected by the acquired heart rate variability physiological parameters is output in remindingsignals which are easy to detect in a feedback mode, so that a user can visually understand the state of own autonomic nervous function, and is further assisted to learn to regulate the activities ofvisceral organs by consciousness within a certain range to correct the visceral activities deviated from a normal range. In addition, the method is easy to implement.
Description
Technical field
Present specification relates to the autonomic nervous function biofeedback technology.
Background technology
Along with science and technology development, the mankind have created many effective methods that tackle physiological decease, and by contrast, the ability that tackles mental illness then proves definitely inferior, and human health is constituted a threat to as anxiety neurosis, depression etc.Facts have proved in a large number, tackle this class disease, depend merely on therapies such as medicine, operation and gene, effect is not good enough.
People's mental status not only can reflect from emotion, also can be reflected on the autonomic nervous system active level.Autonomic nervous system (ANS, Autonomic Nervous System) is meant the nerve that is assigned to the heart, lung, digestive tube and other internal organs, comprises sympathetic nerve and parasympathetic nervous.Most of internal organs are accepted sympathetic nerve and parasympathetic control simultaneously.Under the normal condition, the daily operation of internal organs and the secretion of body of gland are regulated in both co-ordinations, make internal milieu, keep stable as blood pressure, heart rate, body temperature etc.When ANS lacks of proper care, can cause a lot of problems, the lighter can cause that some are not very serious symptoms, for example gastrointestinal disorder, cardiopalmus, dyspnea etc., weight person can cause various acute and chronic diseases, and for example heart disease, hypertension etc. are serious even can cause sudden death etc.
Summary of the invention
The embodiment of autonomic nervous function biological feedback method comprises: according to bioelectrical signals, obtain the heart rate variability physiologic parameter value; According to described heart rate variability physiologic parameter value, the alerting signal that output is corresponding.
The embodiment of autonomic nervous function biological feedback system comprises: test cell according to bioelectrical signals, obtains the heart rate variability physiologic parameter value; The feedback reminding unit, according to described heart rate variability physiologic parameter value, the alerting signal that output is corresponding.
The another kind of embodiment of autonomic nervous function biological feedback system comprises: data capture unit, detected electro-physiological signals is handled, and obtain the time domain heart rate data in the predetermined time interval; Treatment facility, described time domain heart rate data is converted to the frequency domain heart rate data,, obtains the heart rate variability physiologic parameter value based on spectrum analysis and calculating to described frequency domain heart rate data, and according to described heart rate variability physiologic parameter value, the alerting signal that output is corresponding; Output unit is exported described alerting signal.
Above-mentioned embodiment is obtaining by test on the basis of heart rate variability physiologic parameter value, the autonomic nervous functions information that is reflected according to the heart rate variability physiologic parameter value that is obtained, the alerting signal that output is easy to discover, thereby make the user vivid understanding can be arranged to the autonomic nervous function situation of self, and then can assisted user association pass through the activity that consciousness is regulated and control internal organs within the specific limits, correction departs from the visceral motility of normal range, and easy to implement.
Description of drawings
Fig. 1 is the flow chart of autonomic nervous function biological feedback method embodiment;
Fig. 2 is a normal ECG waveform sketch map;
Fig. 3 be among the D2 shown in Figure 1 according to the heart rate variability physiologic parameter value, the flow chart of the alerting signal specific embodiment that output is corresponding;
Fig. 4 be shown in Figure 3 in the sketch map of heart rate variability physiologic parameter value and its range of normal value among the S21;
Fig. 5 (a) is the sketch map of extroverted people's heart rate variability physiological parameter trendgram;
Fig. 5 (b) is the sketch map of introverted people's heart rate variability physiological parameter trendgram;
Fig. 6 (a) is the sketch map of the clear-headed resting heart rate variability physiological parameter trendgram of normal person;
Fig. 6 (b) is the sketch map of normal person's emotion heart rate variability physiological parameter trendgram when being interfered;
Fig. 7 is the sketch map of autonomic nervous function biological feedback system embodiment;
Fig. 8 is the sketch map of the test cell N1 specific embodiment shown in Figure 7;
Fig. 9 is the sketch map of the data capture unit M1 specific embodiment shown in Figure 8;
Figure 10 is the sketch map of the pretreatment unit M1b specific embodiment shown in Figure 9;
Figure 11 is the circuit diagram of first amplifying unit, 1101 specific embodiments shown in Figure 10;
Figure 12 is the circuit diagram of second amplifying unit, 1102 specific embodiments shown in Figure 10;
Figure 13 is the circuit diagram of filtering amplifying unit 1103 specific embodiments shown in Figure 10;
Figure 14 is the circuit diagram of detection shaping unit specific embodiment shown in Figure 9;
Figure 15 is the sketch map of the physiological parameter computing unit specific embodiment shown in Figure 8;
Figure 16 is the sketch map of the feedback reminding unit specific embodiment shown in Figure 7;
Figure 17 is the sketch map of the another kind of embodiment of autonomic nervous function biological feedback system;
Figure 18 is the sketch map that feeds back alerting signal and stimulus signal in the specific embodiment shown in Figure 17.
Figure 19 is the sketch map of autonomic nervous function biological feedback system embodiment.
The specific embodiment
With reference to figure 1, the embodiment of autonomic nervous function biological feedback method comprises:
Step D1 obtains the heart rate variability physiologic parameter value according to bioelectrical signals; Step D2, according to described heart rate variability physiologic parameter value, the alerting signal that output is corresponding.
Heart rate variability (HRV, Heart Rate Variability) physiological parameter can reflect the information of autonomic nervous system function, and patient's psychologic situation can be provided to the doctor, thereby formulates the therapeutic scheme that more meets the state of an illness.
The heart rate of human body is not an absolute rule, a few tens of milliseconds was arranged between twice heart beating interval even surpass 100 milliseconds time difference.Under the normal condition, the variation of healthy popular feeling hopscotch phase is because sympathetic nerve and parasympathetic nervous change caused with factors such as breathings.Heart rate variability just is meant the time difference between heart beating interval one by one.Heart rate variability is the reflection heart carries out capacity of self-regulation to external or internal stimulation a parameter.HRV is high more, shows that heart can more quickly adapt to outside or inner influence, between the sympathetic and parasympathetic nervous system good interaction is arranged; HRV is low to represent that then the adaptive capacity of body is poor.Can reflect the effect that the sinuatrial node self-disciplining is regulated by autonomic nervous system by size and the speed of measuring normal IBI variation.
Total HRV signal is made up of many single-frequencies, analyze by frequency spectrum these frequencies, research worker is found parameter sum frequency power (TP, Total frequency Power), high frequency power (HF, High Frequency Power), low frequency power (LF, Low Frequency Power), ratio (LF/HF) extremely low and intrasonic power (VLF, Very Low Frequency Power) and low frequency power and high frequency power is the parameter of reflection autonomic nervous function.Wherein, the HF part is synchronous with the breath signal of animal, and HF or TP can reflect parasympathetic function; LF, VLF and LF/HF can reflect orthosympathetic activity.
Step D1 obtains the heart rate variability physiologic parameter value according to bioelectrical signals, can comprise in concrete embodiment:
Step S11 according to bioelectrical signals, obtains heart rate data; Specifically, comprise the calculating of amplification, filtering, the detection of QRS wave group and shaping, analog digital conversion and heart rate data to detected bioelectrical signals.
Physiological signal generally can be divided into two classes, and a class is the deutero-signal of the signal of telecommunication and electrical activity, and for example electrocardiosignal and mcg-signals etc. can be referred to as electro-physiological signals; Another kind of is non-electrical signal, comprises contraction, partial pressure of carbon dioxide, partial pressure of oxygen, pH value of body temperature, blood pressure, breathing, hear sounds, muscle etc.
It is the intravital power supply of people that heart cans be compared to, and in each cardiac cycle, pacemaker, atrium, ventricle are excited in succession.Has the tissue of electric conductivity and body fluid around the heart with the summation conduction of countless myocardial cell potential change and be reflected to body surface.In the each point that body surface distributes, the current potential between some point equates, exists potential difference between some point.In one embodiment, the process to the detection of electro-physiological signals can comprise: by the potential difference between the non-isoelectric point on the sensor measurement body surfaces such as electrode electrocardiosignal is noted.In other embodiments, also can mcg-signals etc. be changed into the signal of telecommunication and note, the described electro-physiological signals that acquisition can be handled for subsequent analysis by contactless SQUIT system.
Described amplification is meant detected bioelectrical signals is amplified, and other interfering signals such as itself and trunk signal are distinguished, and the signal data of enough big Gong the analytic record of amplitude is provided, and the restriction electric current flows into human body.
Described filtering is meant that the bioelectrical signals that will amplify filters, and keeps the signal of certain frequency scope, comprising High frequency filter and low frequency filtering.
Described QRS wave group detects and shaping, is meant to detect the QRS wave group, and the QRS waveform that obtains is carried out shaping, obtains R ripple signal.
Waveform in the electrocardiogram is to be named by unified English alphabet, and with reference to figure 2, normal electrocardiogram comprises P ripple, PR section, QRS wave group, ST section and T ripple etc.Wherein, the P ripple be meant at first occur be positioned at the above forward wave of reference levels line, the potential change when its cause is an atrium depolarization before atrial systole; The PR section is meant that the P ripple begins the persistent period that begins to the QRS wave group, and just the atrium depolarization begins blanking time of beginning to sequences of ventricular depolarization; Potential change when the QRS wave group results from sequences of ventricular depolarization before the ventricular systole; Potential change when the T ripple is ventricular bipolar; The ST section is the line segment the end begins to the T ripple eventually from the QRS wave group, and this moment, ventricle all was in the depolarization state, and no potential difference exists, thus just often concordant with baseline, be called equipotential line.In the QRS wave group, the Q ripple is meant first negative wave, and the R ripple is meant first forward wave, and the S ripple is meant first negative wave after the R ripple, and the QS ripple is meant that the QRS ripple has only negative wave.
Described analog digital conversion is meant the electro-physiological signals after the R ripple signal that will obtain and described amplification are filtered, and through analog digital conversion, is converted to digital signal.
In the process of calculating heart rate data, described heart rate data is meant the spacing of adjacent two R wave-wave peaks between the corresponding time, be the RR interval, the calculating of heart rate data is comprised: the sample frequency during according to the number conversion of R ripple signal mode, by calculating the interval that obtains between the R wave crest point.Specifically can be that the interval between the data point be multiply by number of data points between the adjacent R wave crest point, obtain the RR interval.
On the basis that obtains heart rate data, just can carry out follow-up processing and analysis, to obtain the heart rate variability physiologic parameter value.
Need to prove,, there is certain requirement in heart rate data for making the subsequent analysis processing process can obtain result preferably.In an embodiment, should obtain the interior at interval heart rate data of certain hour.Usually, interval can be 15-40 minute.Be lower than 15 minutes, the lazy weight of the heart rate data of being gathered; Be longer than 40 minutes, and made user's anxiety easily, emotion is affected, thereby influences test result.
Step S12 preserves the heart rate data that is obtained; Specifically, can select manually to preserve or preserve automatically.
Under the mode of automatically preserving, in case when interval reached the integral multiple of period 1, automatic centering rate data and heart rate data quantity were preserved, and enter step S13.Wherein, the period 1 can be 15 to 40 minutes.
Under manual preserving type, when interval meets or exceeds first setting value, the heart rate data and the heart rate data quantity that are obtained are preserved; If do not reach first setting value, then heart rate data and heart rate data quantity refused record; Wherein, first setting value is less than the period 1, and under the normal condition, the ordinary people is not more than 3 minutes from anxious state of mind to the completely stable time, first setting value should be slightly larger than from anxious state of mind to the completely stable time cycle, to guarantee to note anxious state of mind at least once.In specific embodiment, first setting value can be 3 to 8 minutes.
Step S13 divides into groups to the heart rate data of being preserved.
Specifically, be meant that the heart rate data that step S12 is preserved divides into groups, the quantity that makes every group of heart rate data is second setting value; If lazy weight second setting value of last group heart rate data, usable levels are that zero data are replenished.Wherein, second setting value is determined by first setting value, determines the second corresponding setting value numerical value according to the value of first setting value; Specifically, when first setting value was 3 minutes, second setting value was 256; When first setting value was 4 to 8 minutes, second setting value can be the arbitrary integer between 256 to 540.
The step-length of grouping can be between zero and second any integer value that sets value.Give an example, 3 minutes the heart rate data of being preserved for step S13, with 128 is that step-length is divided into groups, making every group of heart rate data quantity is 256, that is to say, the 1st to the 256th heart rate data is first group, the 129th to the 384th heart rate data is second group, by that analogy, when last group heart rate data lazy weight second setting value, be that zero data are replenished with value.This sentences that certain step-length divides into groups is for each physiological parameter trend curve among the follow-up physiology parameter trend figure is played the level and smooth effect of filtering.When grouping, if step-length approaches second setting value more, then operand is smaller, but a little less than the smoothing effect; When step-length reduced, smoothing effect was good more, but operand is relatively also big more.
Step S14, calculate resulting each the group heart rate data meansigma methods.
Specifically, comprising: calculate each group heart rate data sum; With the quantity of resulting heart rate data sum, promptly divided by second setting value divided by this group heart rate data.
Step S15 calculates the value of each heart rate data in each group and the difference of this group heart rate data meansigma methods respectively.
Step S16 according to resulting difference, obtains the frequency domain heart rate data.
In a kind of concrete embodiment, the frequency domain heart rate data can obtain by following steps: adopt window function that resulting difference is carried out data truncation, obtain time domain data to be analyzed; According to time domain data to be analyzed, obtain corresponding frequency domain data.
Wherein, the reason of carrying out data truncation is: owing to can not measure and computing the signal of endless, therefore from signal, intercept a time slice, carrying out periodic extension with the signal time fragment of observing then handles, obtain the signal of virtual endless, again signal is carried out correlation analysis on this basis and handle.
Described window function can comprise hamming window, Hanning window, cloth Alexandra kdemand window, Gaussian window etc.
In specific embodiment, use the hamming window that difference is handled.First side lobe attenuation of hamming window is-its frequency spectrum of 42dB. during by 3 rectangles the frequency spectrum of window synthetic, its weight coefficient can make secondary lobe reach littler.The time function expression formula of used hamming window is:
Its window spectrum is:
Wherein T is the hamming window time cycle, and its length need cover all heart rate datas in every group, can be described second setting value in specific embodiment;
On this basis, time domain data to be analyzed can be realized by the mode of fast Fourier transform (FFT) to the conversion of frequency domain data.
In the concrete embodiment of another kind, the acquisition of frequency domain heart rate data can comprise step: by autoregression (AR) algorithm resulting difference is converted to corresponding frequency domain heart rate data.The AR algorithm that is adopted is a conventional method, does not repeat them here.
Step S17 according to resulting frequency domain heart rate data, calculates the heart rate variability physiologic parameter value.
Described physiological parameter comprises LFnorm (low frequency power markization value), HFnorm (high frequency power markization value), LF/HF (low frequency power/high frequency power) etc.Low frequency power LF is arranged by cardiac sympathetic nerve mainly, can be used as the sympathetic parameter that spreads out of level of activation of the heart; And high spectrum has been represented the heart rate volatility parameter that is derived from vagus nerve (parasympathetic nervous), so the big I of high frequency power HF is used as the quantitative observation mental confusion due to heart disorder and walks to spread out of active parameter.LF/HF ratio can be used as in weighing sympathetic nerve-parasympathetic nervous harmony.
The calculating of heart rate variability physiologic parameter value specifically, comprising: calculated rate at interval; According to the frequency interval that calculates, calculated rate power; According to the frequency power that calculates, calculated rate power markization value and frequency ratio.
Described frequency interval is in every group of heart rate data, the frequency interval between the frequency domain data of each heart rate data correspondence.The inverse of the frequency domain data average that can be by every group of heart rate data correspondence and the product of this group heart rate data quantity, promptly the inverse of the frequency domain data average of every group of heart rate data correspondence and second product that sets value obtains described frequency interval.
According to frequency interval, can calculate the number of the heart rate data that comprised in the frequency range that corresponds respectively to each wavelength coverage of heart rate variability, the power addition of all frequency domain datas of these heart rate data correspondences is just obtained corresponding frequency power value.Specifically, according to the definition of HRV wavelength coverage, extremely low frequency power VLF is the power less than the frequency of 0.04Hz, and low frequency power LF is the power of frequency in 0.04Hz to 0.15Hz scope, and high frequency power HF is the power of frequency in 0.15Hz to 0.4Hz scope.Therefore, described according to frequency interval, calculated rate power comprises, calculates sum frequency power TP, calculates LF, calculates HF and calculates VLF; Wherein, calculating TP is meant in the calculating certain frequency scope, specifically, can be meant in the 0.4Hz scope, the power summation of all frequency domain datas of heart rate data correspondence is about to the power addition of each frequency domain data corresponding with heart rate data, obtains sum frequency power TP; Calculate the power sum that LF can be meant all frequency domain datas of calculating heart rate data correspondence in 0.04Hz to 0.15Hz scope; Calculate the power sum that HF can be meant all frequency domain datas of calculating heart rate data correspondence in 0.15Hz to 0.4Hz scope; Calculate the power sum that VLF can be meant the frequency domain data of calculating heart rate data correspondence in the 0.04Hz scope.
Obtain after the value of frequency power, the process of calculated rate power markization value specifically can comprise: calculate LFnorm, HFnorm and LF/HF according to the resulting LF of calculated rate power, HF and TP.Calculate LF/HF and be meant the ratio that calculates LF and HF.In one embodiment, the process of calculating LFnorm, HFnorm comprises: with the value of LF, the HF of the correspondence difference divided by general power and VLF, again the result be multiply by 100, obtain low frequency/high frequency power markization value.
Next enter step D2.
With reference to figure 3, step D2 exports corresponding alerting signal according to described heart rate variability physiologic parameter value.In concrete embodiment, can comprise:
Step S21 with the heart rate variability physiologic parameter value, compares with its range of normal value, obtains the time dependent trend of each parameter.
In specific embodiment, the value of the LFnorm in the 50-58nU scope, the value of HFnorm in the 26-32nU scope and the value of the LF/HF in 1.5～2. scopes can be decided to be normal range.With reference to figure 4, the B district among the parameter trend figure is the normal range of setting; When LFnorm or LF/HF are higher than normal value, when perhaps HFnorm was lower than normal value, it was leading to think that sympathetic nerve accounts for, and the A district among Fig. 4 parameter trend figure is the leading district of described sympathetic nerve; When LFnorm or LF/HF were lower than normal value or HFnorm and are higher than normal value, it was leading to think that parasympathetic nervous accounts for, and the C district among Fig. 4 parameter trend figure is the leading district of described parasympathetic nervous.Usually, its LF, LF/HF were lower than normal value when the normal person slept, and the trendgram curve is all in the C district, and as shown in Figure 4, parasympathetic nervous plays a leading role and matches when being in sleep state on this and the physiology, and curve is very stable.
User's personal characteristics also can have influence on LF, HF, LF/HF parameter trend distributing position.With reference to figure 5, figure (a) is the comparatively resulting heart rate variability physiological parameter of an extravert trendgram of personality, and its curve major part is in the A district; With reference to figure 5, figure (b) is the comparatively resulting heart rate variability physiological parameter of an introvert trendgram of personality, and its curve major part is in the C district; But generally speaking, no matter each heart rate variability physiological parameter of normal person is to be partial to the A district or to be partial to the C district if distributing, and all is near the B district, perhaps floats near the B district.
Find through a large amount of experiments, when the normal person in clear-headed quiet state following time, its LF, HF, LF/HF trend curve are shown in Fig. 6 (a), and be relatively more steady; But when emotion was interfered, shown in Fig. 6 (b), trend curve showed than great fluctuation process.
Step S22 according to comparative result and the time dependent trend of each parameter, obtains described autonomic nervous functions.
Step S23, according to described autonomic nervous functions, the alerting signal that output is corresponding.
Give an example, when being in quiescent condition, if user's LF, LF/HF, illustrate then that the sympathetic nervous system movable function is hyperfunction apparently higher than range of normal value, described user may be an anxiety patient; Again for example, raise, or LF raises, HF reduces when LF occurring, or LF/HF increase in three kinds of situations any or when several, can think user's existential anxiety obstacle; When HF rising or LF/HF reduction, can think that there is depressive disorder in the user.
Corresponding different autonomic nervous functions can be made as alerting signal the some grades that have with its similar number, corresponding output.Wherein, alerting signal can be with the form output of the combination of image or sound or image and sound, and the alerting signal of corresponding different brackets is provided with the combination of different pictures or sound or picture and sound.For example, corresponding to anxiety, normal, depressed three kinds of states, alerting signal is divided into A, B, C Three Estate, with three kinds of cartoon shape of face pictures of frowning, smiling and crying output form as alerting signal.When alerting signal is the A grade, show the cartoon shape of face picture of frowning; When alerting signal is the B grade, show the cartoon shape of face picture of grinning and laughing at; When alerting signal is the C grade, show the cartoon shape of face picture of crying.
Another embodiment of above-mentioned autonomic nervous function biological feedback method can also comprise step: produce and the lasting stimulus signal with setpoint frequency scope of exporting.
Specifically, this stimulus signal is used for assisting stablizes user's emotion, makes its sensation tranquil.Described setpoint frequency scope can adopt industry to generally believe to make human body feel comfortable and stabile frequency range promptly to be not more than 2Hz.In one embodiment, stimulation signal frequencies can be set at 0.25Hz or 0.5Hz or 0.75Hz or 1Hz or 2Hz.Show that through a large amount of experiments under all identical situation of other experiment condition, the user watches the single pendulum of setpoint frequency for a long time attentively, it is emotionally stable.And, adopt which kind of figure can't limit to some extent effect as the form of expression of this stimulus signal, for example, also can adopt mobile straight rod, mobile ball, metronome etc.
With reference to figure 7, the embodiment of autonomic nervous function biological feedback system comprises:
Test cell N1 according to bioelectrical signals, obtains the heart rate variability physiologic parameter value; Feedback reminding unit N2, according to described heart rate variability physiologic parameter value, the alerting signal of output different brackets.
With reference to figure 8, described test cell N1 in a kind of concrete embodiment, comprising:
Data capture unit M1 according to bioelectrical signals, obtains heart rate data; Data record unit M2 preserves resulting heart rate data and heart rate data quantity; Packet unit M3 divides into groups to the acquired signal of being preserved; Equal value cell M4, calculates resulting each organize the meansigma methods of heart rate data; Difference computational unit M5 calculates the value of each heart rate data in each group and the difference of resulting this group heart rate data meansigma methods; Frequency domain data computing unit M6 according to resulting difference, obtains the frequency domain heart rate data; Physiological parameter computing unit M7 according to resulting frequency domain heart rate data, calculates the heart rate variability physiologic parameter value.
In a kind of specific embodiment, with reference to figure 9, data capture unit M1 can comprise pretreatment unit M1b, detection shaping unit M1c, AD conversion unit M1d and heart rate data computing unit M1e.The detected bioelectrical signals of bioelectrical signals detecting unit M1a, the processing through pretreatment unit M1b, detection shaping unit M1c, AD conversion unit M1d and heart rate data computing unit M1e obtains heart rate data.
Wherein, the electro-physiological signals of electro-physiological signals detecting unit M1a human body in a kind of specific embodiment, comprises the electrode that links to each other with human body, detects electrocardiosignal; In another kind of specific embodiment, comprise the mcg-signals of human body being converted into signal of telecommunication SQUIT system.
Pretreatment unit M1b amplifies the bioelectrical signals that is obtained and filters, and in one embodiment, described pretreatment unit M1b satisfies following technical parameter: amplification is not less than 1000; Frequency response is 0.05～100Hz; Input impedance is not less than 3M Ω; Common mode rejection ratio is not less than 100dB; Own ship's noise is not more than 3 μ V
Pp
With reference to Figure 10, pretreatment unit M1b comprises first amplifying unit 1101, second amplifying unit 1102 and filtering amplifying unit 1103.Wherein, the bioelectrical signals that inputs to pretreatment unit M1b is amplified by first amplifying unit 1101 and second amplifying unit 1102, filters through filtering amplifying unit 1103 again.
In specific embodiment, with reference to Figure 11, first amplifying unit 1101 can comprise five operational amplifiers 1201,1202,1203,1204,1205, play other interfering signals such as distinguishing electro-physiological signals and trunk signal, high input impedance is provided, the restriction electric current flows into the effect of human body, wherein, signal A and A ' are the electro-physiological signals that is received, and signal B and B ' are the one-level amplifying signal of output, signal B
1For suppressing signal, feedback inputs to the user, and the restriction electric current flows into human body.
With reference to Figure 12, second amplifying circuit 1102 further amplifies bioelectrical signals, so that trailer record analysis, can comprise amplifier 1301, it is equivalent to the equivalent circuit of three operational amplifiers, can adapt to wider frequency domain scope, wherein, signal B and B ' are the one-level amplifying signal that is received, and signal C is the secondary amplifying signal of output.
With reference to Figure 13, the bioelectrical signals of 1103 pairs of amplifications of filtering amplifying unit filters, and comprises the low frequency filtering that 0.05Hz is following, and the above High frequency filter of 100Hz.Can comprise the filter amplification circuit that is made of operational amplifier 1401, wherein signal C is the secondary amplifying signal of reception, and signal D is the trap signal of output.
A normal ecg wave form comprises P ripple, QSR wave group and T ripple, the excited pulse period property repetition that these ripples produce according to sinuatrial node, wherein, the R ripple is compared to other waveforms, have higher amplitude, frequency bands such as T ripple, P ripple, baseline drift are all beyond the bottom of QRS wave group frequency band simultaneously.Therefore can in the above-described embodiments, detect the QRS wave group, and the QRS waveform that obtains is carried out shaping by detecting and isolating the QRS wave group, can obtain comparatively significantly R ripple by described detection shaping unit M1c.
With reference to Figure 14, detection shaping unit M1c comprises detection unit 1501 and filter unit 1502; The bioelectrical signals that detection unit 1501 receives through pretreatment unit M1b output obtains R ripple signal; The R ripple signal of 1502 pairs of described acquisitions of filter unit carries out denoising, and outstanding R ripple.Wherein, described detection unit 1501 comprises peaker 111 and full-wave detection circuit 112: described full-wave detection circuit 212 comprises that operational amplifier, diode D5 and D6 and feedback resistance R19, R20, R21, R22, R23, R24 and R25 constitute; Described filter unit 1502 can comprise second-order low-pass filter.Bioelectrical signals through pretreatment unit M1b output, be signal D, after peaker 111 and 112 rectifications of full-wave detection circuit, obtain the signal that waveform is unidirectional multimodal impulse waveform, again through filter unit 1502 low-pass filtering, waveform is carried out smoothing processing, show the form waveform of R wave-wave peak position especially, i.e. R ripple signal.
AD conversion unit M1d receives the electro-physiological signals after described R ripple signal and the described amplification filtration, carries out analog digital conversion, obtains corresponding digital signal.Particularly, can realize by analog to digital conversion circuit.
Heart rate data computing unit M1e calculates based on described digital signal, obtains the RR interval, i.e. heart rate data.In one embodiment, its concrete work process can comprise: receive the digital signal that described AD conversion unit M1d provides, obtain the digital signal of R wave-wave peak position correspondence, sample frequency during according to this digital signal and according to analog digital conversion, obtain number of data points between adjacent R R, described number of data points and interval are multiplied each other, obtain the RR interval.
Data record unit M2 in one embodiment, comprises preserving type selected cell and memory element.Wherein, preserving type comprises automatic preservation or manually preserves, memory element can memory time at interval, heart rate data and heart rate data quantity.
In one embodiment, specifically, under the mode of preserving automatically, when interval reaches the integral multiple of period 1, automatically heart rate data and heart rate data quantity are saved to memory element.In specific embodiment, the period 1 can be 15 to 40 minutes.Under manual preserving type, when interval reaches first setting value, respectively heart rate data and heart rate data quantity are saved to memory element; If do not reach first setting value, then heart rate data and the heart rate data quantity in this interval is not noted down; Wherein, first setting value is less than the period 1.Under the normal condition, the ordinary people is not more than 3 minutes from anxious state of mind to the completely stable time, and first setting value should be slightly larger than from anxious state of mind to the completely stable time cycle, to guarantee to note anxious state of mind at least once.In specific embodiment, first setting value can be 3 to 8 minutes.
Packet unit M3, its work process specifically can comprise: the heart rate data of being preserved is divided into groups, and the quantity that makes every group of heart rate data is second setting value; If lazy weight second setting value of last group heart rate data, usable levels are that zero data are replenished.Wherein, second setting value is determined by first setting value, determines the second corresponding setting value numerical value according to the value of first setting value; Specifically, when first setting value was 3 minutes, second setting value was 256; When first setting value was 4 to 8 minutes, second setting value can be the arbitrary integer between 256 to 540.
Equal value cell M4, calculates resulting each organize the meansigma methods of heart rate data.Its work process specifically can comprise: calculate each group heart rate data sum; With the quantity of resulting heart rate data sum, promptly divided by second setting value divided by the corresponding heart rate data of this group;
Difference computational unit M5 calculates the value of each heart rate data in each group and the difference of resulting this group heart rate data meansigma methods.
Frequency domain data computing unit M6 according to described difference, obtains the frequency domain heart rate data.Its work process specifically can comprise: produce window function, described difference is carried out data truncation, obtain time domain data; Realize FFT, convert described time domain data to corresponding frequency domain data.
With reference to Figure 15, in one embodiment, physiological parameter computing unit M7 comprises frequency interval computing unit M7a, frequency power computing unit M7b and markization value computing unit M7c.
Wherein, frequency interval computing unit M7a calculates the inverse of the product of the average of described frequency domain heart rate data and this group heart rate data quantity, obtains frequency interval.
Frequency power computing unit M7b receives described frequency interval, calculating corresponds respectively to the number of the heart rate data that is comprised in the frequency range of each wavelength coverage of heart rate variability, with the power addition of all frequency domain datas of these heart rate data correspondences, thereby obtain corresponding frequency power value.Its work process specifically can comprise: calculate the power sum of the frequency domain data of heart rate data correspondence in the 0.4Hz scope, obtain sum frequency power; Calculate the power sum of the frequency domain data of each heart rate data correspondence in 0.04Hz to the 0.15Hz scope, obtain low frequency power; Calculate the power sum of the frequency domain data of each heart rate data correspondence in 0.15Hz to the 0.4Hz scope, obtain high frequency power; Calculate the power sum of 0.04Hz scope, obtain extremely low frequency power with the frequency domain data of interior each heart rate data correspondence.
Markization value computing unit M7c calculates high frequency power markization value HFnorm, low frequency power markization value LFnorm and low-and high-frequency power ratio LF/HF according to described sum frequency power, high frequency power, low frequency power and extremely low frequency power.
With reference to Figure 16, described feedback reminding unit N2 comprises in concrete embodiment:
State classification unit M8 classifies represented autonomic nervous functions according to the magnitude relationship and the time dependent trend of each physiological parameter of each heart rate variability physiologic parameter value and normal value.Its work process specifically can comprise: whether the value of judging the heart rate variability physiologic parameter value is in the range of normal value that sets; Judge the time dependent trend of this heart rate variability physiologic parameter value; According to judged result, obtain the autonomic nervous functions classification.
Feedback output unit M9, according to described autonomic nervous functions classification, it is mapped as corresponding alerting signal, and, reminds its autonomic nervous function situation of user the form feedback output of alerting signal according to the combination of image or sound or image and sound; In one embodiment, can comprise the combination of display or loudspeaker or display and loudspeaker.
With reference to Figure 17, in the another kind of embodiment of autonomic nervous function biological feedback system, also comprise the stimulus signal generating unit, produce and the lasting stimulus signal of exporting with setpoint frequency scope.
In one embodiment, the stimulus signal generating unit can comprise signal generating apparatus.Signal generating apparatus produces the signal of setpoint frequency, make single pendulum, or the straight rod that moves is swung with this setpoint frequency, wherein, described setpoint frequency can adopt the medically generally acknowledged frequency range that can make the human feeling arrive calmness, promptly be not more than 2Hz, concrete, stimulation signal frequencies can be set at 0.25Hz or 0.5Hz or 0.75Hz or 1Hz or 2Hz.
In another embodiment, the stimulus signal generating unit can also comprise image display, with single pendulum or mobile straight rod etc., with pictorial form, rather than physical form shows, and the single pendulum of this pictorial form or straight rod are swung according to setpoint frequency.The form of expression of described stimulus signal is not subjected to the restriction into material object or virtual image, and is same, is not restricted to pictorial form yet, and can make the object by the setpoint frequency motion is metronome, perhaps is the shape of mobile ball.
With reference to Figure 18, in specific embodiment, alerting signal shows with smiling face's form, and stimulus signal shows with the pictorial form of single pendulum.Single pendulum is in the kinestate of fixed-frequency, and the situation of its current autonomic nervous function of alerting signal prompting user makes the user keep watching attentively picture always in the implementation process.When the user was interfered, the smiling face of alerting signal was changed the face of crying into, and the prompting user has been subjected to interference.The user sees after the prompting, keeps watching single pendulum attentively, and carries out the oneself and adjust under doctor's guidance, thereby the mental status is improved.
With reference to Figure 19, the embodiment of autonomic nervous function biological feedback system comprises:
Data capture unit E1 handles detected electro-physiological signals, obtains the time domain heart rate data in the predetermined time interval.
In one embodiment, described predetermined time interval can be 15 to 40 minutes.
Treatment facility E2, described time domain heart rate data is converted to the frequency domain heart rate data,, obtains the heart rate variability physiologic parameter value based on spectrum analysis and calculating to described frequency domain heart rate data, and according to described heart rate variability physiologic parameter value, the alerting signal that output is corresponding.
When specific implementation, treatment facility E2 can be each class of electronic devices with data-handling capacity, for example computer, server, single-chip microcomputer or microcontroller etc.Can comprise memorizer, time domain heart rate data, frequency domain heart rate data and each intermediate data are preserved.
In one embodiment, treatment facility E2 also comprises the stimulus signal generating unit, produces and continue the stimulus signal of output setpoint frequency scope.The specific implementation of described stimulus signal generating unit can be with reference to the specific descriptions of previous embodiment, and this does not give unnecessary details.
Output unit E3 exports described alerting signal.
When specific implementation, output unit E3 can select in any mode of the combination of image or sound or image and sound alerting signal to be exported.In one embodiment, output unit E3 can comprise display or loudspeaker.
The specific implementation of data capture unit E1 can be with reference to the description of previous embodiment, and this does not give unnecessary details.
Above-mentioned embodiment also can be realized by following manner: with described step, comprise heart rate data is preserved, the heart rate data of being preserved is divided into groups, calculate the meansigma methods of each group heart rate data, calculate the value of each heart rate data in each group and the difference of this group heart rate data meansigma methods respectively, obtain the frequency domain heart rate data according to described difference, described frequency domain heart rate data is carried out spectrum analysis and calculates obtaining the heart rate variability physiologic parameter value, export corresponding alerting signal based on the autonomic nervous functions that the heart rate variability physiologic parameter value is reflected, be described with executable program code, the storage medium that stores above-mentioned executable program code is offered system or equipment directly or indirectly, and the said procedure code is read and carried out to the computer in this system or equipment or CPU (CPU).
At this moment, as long as this system or equipment have the function of performing a programme, then embodiment is not limited to program, and this program also can be form arbitrarily, for example, and program that target program, interpreter are carried out or the shell script that offers operating system etc.
Above-mentioned these machinable mediums include but not limited to: various memorizeies and memory element, semiconductor equipment, disk cell be light, magnetic and magneto-optic disk for example, and other is suitable for the medium of stored information etc.In addition, client computer is by being connected to the corresponding website on the Internet, and computer program code downloaded and be installed to carry out this program in the computer then, also can realize said process.
Above-mentioned embodiment, on the basis that obtains the heart rate variability physiological parameter, the autonomic nervous functions that described heart rate variability physiological parameter is reflected is exported with the alerting signal feedback that is easy to discover, make the user vivid understanding be arranged to the autonomic nervous function situation of self, thereby assisted user is having under the situation of guidance the prompting message oneself according to being fed back adjust, and easy to implement.
Claims (23)
1. autonomic nervous function biological feedback method comprises:
According to bioelectrical signals, obtain the heart rate variability physiologic parameter value;
According to described heart rate variability physiologic parameter value, the alerting signal that output is corresponding.
2. biological feedback method as claimed in claim 1, wherein described according to the heart rate variability physiologic parameter value, the corresponding alerting signal of output comprises:
With described heart rate variability physiologic parameter value, compare with its range of normal value, obtain the time dependent trend of each parameter;
According to described comparative result and described each parameter trend, obtain autonomic nervous functions;
According to described autonomic nervous functions, the alerting signal that output is corresponding.
3. biological feedback method as claimed in claim 2, wherein, described alerting signal has the number of degrees with the state similar number of described autonomic nervous function.
4. biological feedback method as claimed in claim 1 wherein, also comprises continuing the stimulus signal that output has the setpoint frequency scope.
5. biological feedback method as claimed in claim 1 wherein, according to bioelectrical signals, obtains the heart rate variability physiologic parameter value, comprising:
According to bioelectrical signals, obtain heart rate data;
Described heart rate data is handled, obtained the frequency domain heart rate data;
According to described frequency domain heart rate data, obtain the heart rate variability physiologic parameter value.
6. biological feedback method as claimed in claim 5, wherein described according to bioelectrical signals, obtain heart rate data, comprising:
To bioelectrical signals amplify, filtering;
QRS wave group in the detection of biological signal of telecommunication carries out waveform shaping to obtain R ripple signal to the QRS wave group that is obtained;
Will through amplify, the bioelectrical signals of filtering, and detect and the R ripple signal of shaping through the QRS wave group, convert digital signal to.
7. biological feedback method as claimed in claim 5 wherein, is describedly handled heart rate data, obtains the frequency domain heart rate data and comprises:
Described heart rate data is divided into groups;
Calculate the meansigma methods of each group heart rate data;
Calculate the value of each heart rate data in each group and the difference of described this group heart rate data meansigma methods respectively;
Obtain the frequency domain heart rate data according to described difference.
8. biological feedback method as claimed in claim 7 wherein, divides into groups to described heart rate data, comprising: the quantity that makes every group of heart rate data is second setting value; If during the lazy weight of heart rate data second setting value, be that zero data are replenished with value.
9. biological feedback method as claimed in claim 5, wherein described according to the frequency domain heart rate data, obtain the heart rate variability physiologic parameter value, comprising:
Calculate the frequency interval between the frequency domain heart rate data;
According to described frequency interval, calculate the frequency power of each physiologic parameter value place wavelength coverage of heart rate variability respectively;
According to described frequency power, calculated rate power markization value and frequency power ratio.
10. biological feedback method as claimed in claim 9, wherein, the frequency power of each physiologic parameter value place wavelength coverage of described heart rate variability comprises the value of sum frequency power, high frequency power, low frequency power and extremely low frequency power.
11. an autonomic nervous function biological feedback system comprises:
Test cell according to bioelectrical signals, obtains the heart rate variability physiologic parameter value;
The feedback reminding unit, according to described heart rate variability physiologic parameter value, the alerting signal that output is corresponding.
12. biological feedback system as claimed in claim 11, wherein, described feedback reminding unit comprises:
The state classification unit is according to described heart rate variability physiologic parameter value, with represented autonomic nervous functions classification;
The feedback output unit according to described status categories, is mapped as corresponding alerting signal with it, feedback output alerting signal.
13. biological feedback system as claimed in claim 12, wherein, whether the value of described state classification unit judges heart rate variability physiologic parameter value is in the range of normal value that sets; Judge the time dependent trend of this heart rate variability physiologic parameter value; According to judged result, obtain the autonomic nervous functions classification.
14. biological feedback system as claimed in claim 11 wherein, also comprises: the stimulus signal generating unit produces and the lasting stimulus signal with setpoint frequency scope of exporting.
15. biological feedback system as claimed in claim 11, wherein, described test cell comprises:
Data capture unit according to bioelectrical signals, obtains heart rate data;
Processing unit is handled described heart rate data, obtains the frequency domain heart rate data;
The physiological parameter computing unit according to described frequency domain heart rate data, calculates the heart rate variability physiologic parameter value.
16. biological feedback system as claimed in claim 15, wherein, described data capture unit comprises:
Pretreatment unit amplifies and filters described bioelectrical signals;
The detection shaping unit detects the QRS wave group in the described bioelectrical signals, and the QRS wave group is carried out shaping to obtain R ripple signal;
AD conversion unit with described R ripple signal and through amplification, filtering bioelectrical signals, is carried out analog digital conversion, obtains digital signal;
The heart rate data computing unit calculates based on described digital signal, obtains heart rate data.
17. feedback system as claimed in claim 16, wherein, described pretreatment unit comprises at least one amplifying unit and filter unit.
18. feedback system as claimed in claim 16, wherein, described detection shaping unit comprises detection unit and filter unit.
19. feedback system as claimed in claim 18, wherein, described detection unit comprises peaker and full-wave detection circuit.
20. feedback system as claimed in claim 15, wherein, described processing unit comprises:
The packet unit divides into groups to described heart rate data;
Equal value cells, calculates resulting each organize the meansigma methods of heart rate data;
Difference computational unit is calculated the value of each heart rate data in each group and the difference of resulting this group heart rate data meansigma methods;
The frequency domain data computing unit according to resulting difference, obtains the frequency domain heart rate data.
21. feedback system as claimed in claim 15, wherein, described physiological parameter computing unit comprises:
The frequency interval computing unit calculates the frequency interval between the frequency domain heart rate data;
The frequency power computing unit according to described frequency interval, calculates the frequency power of each physiologic parameter value place wavelength coverage of heart rate variability respectively;
Markization value computing unit, according to described frequency power, calculated rate power markization value and frequency power ratio.
22. an autonomic nervous function biological feedback system comprises:
Data capture unit is handled detected bioelectrical signals, obtains the time domain heart rate data in the predetermined time interval;
Treatment facility, described time domain heart rate data is converted to the frequency domain heart rate data,, obtains the heart rate variability physiologic parameter value based on spectrum analysis and calculating to described frequency domain heart rate data, and according to described heart rate variability physiologic parameter value, the alerting signal that output is corresponding;
Output unit is exported described alerting signal.
23. biological feedback system as claimed in claim 22, wherein, described treatment facility also comprises the stimulus signal generating unit, produces and continue the stimulus signal of output setpoint frequency scope.
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