CN1428128A - Automatic far-end control method for evaluating autonomic nervous system function and its system - Google Patents
Automatic far-end control method for evaluating autonomic nervous system function and its system Download PDFInfo
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Abstract
The present invention relates to an autoamtic remote control method for estimating hart rate variability (HRV). Said method is characterized by that the signal of heart rate of user can be collected, digitized and implied at the customer terminal of a master-slave system, then these digitized signals can be transferred into service terminal by means of a network system, in which its automatic ANS functions analysis system can be used for on-line analyzing these digitized signals, and can provide index of autonmoic nervous system, and can transfere these indexes into user (customer terminal) and/or medical specialist for making further verification and help.
Description
Technical field
The invention relates to the method and system of assessment autonomic nervous system function.Particularly relevant for a kind of automatic remote control method and system in order to the measurement heart rate variability.
Background technology
Autonomic nervous system (Autonomic Nervous System is called for short ANS) comprises two parts---sympathetic nerve and parasympathetic nervous.Most organ is accepted the pulsation from two parts, and under normal situation, two parts are worked together, and normal organ dysfunction is provided, and the demand that adapts to life.When autonomic nervous system disorder, can cause many problems, comprise chronic and acute illness, such as heart disease or hypertension etc., emergency cases such as severe patient even initiation sudden death.Even more not serious symptom, such as problems such as cardiopalmus, gastrointestinal disorder, dyspnea and insomnia think all that generally these symptoms are with autonomic relevant unusually.
Previous instrument and the method that many diagnosis autonomic nervous system functions that on clinical medicine, developed.These methods comprise deep breathing heart rate variability method (heart rate variation withdeep breathing), blood pressure (orthostatic blood pressure recordings), frozen water cause when holding one's breath reaction (Valsalva response), perspiration functions (sudomotorfunction), posture changing by force booster reaction (cold pressor test) and biochemical investigation (biochemistry test) etc.Yet above-mentioned part method need be invaded the body check, the essential diagnostic instruments that uses costliness of part method.Therefore, these technology and be not suitable for using widely.
In recent years, because the fast development of computer hardware and software engineering impels the various technology of diagnosis autonomic nervous system function to succeed in developing in succession.Heart rate variability (Heart RateVariability is called for short HRV), when it stopped for human body, the minor variations of heart rate had been developed into autonomic functional parameter.HRV is an important breakthrough autonomic nerve diagnostic method, the most important thing is that the experimenter must not bear any misery because this technology is non-diagnostic techniques of invading body.Secondly, the hardware cost that this technology is used is very cheap, therefore can very popularly use.In addition, also passed through many animals and human experimentation, confirmed that HRV can accurately react sympathetic nerve and parasympathetic activity and balance.
The adult when rest, about 70 times of the heart beating of per minute.The heart beating of this kind rule is to be controlled by the electrocardiosignal of conducting between the cardiac muscle cell.Heart is accepted from autonomic sympathetic nerve and parasympathetic control signal, and it is with the homeostasis control running normally of health.Yet, if during somatotonia, can be by the sympathetic nervous system master control, and cause heart rate and increased blood pressure.After the state of emergency is removed, can replace by parasympathetic nervous system, heart rate and blood pressure are reduced.
Even under the condition of having a rest, normal person's heart rate also cyclically-varying can occur.These cyclically-varyings can be quick, slow or irregular.Suitable little of the amplitude of these variations, thereby be difficult to use common analytical method to detect.Yet,, can obtain better HRV assessment by frequency-domain analysis to the derivative data doing mathematics computing of ECG because the analytical tool of recent electromechanical engineering field is significantly progressive.
Research worker finds that according to spectrum analysis, HRV can quantitatively become two Main Ingredients and Appearances: high frequency (High Frequency Power is called for short HF) composition and low frequency (Low FrequencyPower is called for short LF) composition.The breath signal of high frequency composition and animal is synchronous, in per approximately 3 seconds of human body once.Real the rising of low frequency composition carried on as before under study for action, and supposition may be relevant with vasomotion or pressure-sensitive reflection, and approximately per 10 seconds once in human body.Partly the scholar more is subdivided into the low frequency composition low frequency composition and extremely low frequency (Very Low Frequency is called for short VLF) composition.At present, existing many physiologists and the doctor of division of cardiology agree high frequency variability (HF) or general power (Total Power, be called for short TP) can represent parasympathetic function, and the ratio (LF/HF) of low frequency variability and high frequency variability can react sympathetic activity (Akselrod et al.1981; Malliani et al 1991).HRV also has and discovers that HRV reacts various biological information except as the autonomic nervous system index.
For example, its heart rate variability of patient of rising of cerebral can descend (Lowensohn et al.1977).If research is in addition also found older's HRV and is lower than a standard deviation that then its mortality rate is 1.7 times (Tsjui et al.1994) of ordinary person.The low frequency variability meeting complete obiteration (Kuo et al.1997) of discovering the brain death patient that the applicant is previous finds also that in addition the difference of age and sex can influence sympathetic nerve and parasympathetic functions (Kuo et al.1999).In gynecologic field, existing report pregnant woman's sympathetic nerve function can improve, but if overresponse may be accompanied by the generation (Yang et al.2000) of the preceding disease of dangerous eclamposia.
Though autonomic nervous system (Autonomic Nervous System is called for short ANS) function provides the significant reflection of many physiological statuss,, at present by measuring HRV with reflection ANS.In order to obtain the information about autonomic nervous function, user must have electrocardiogram (Electrocardiogram is called for short ECG) module to use.Also a plurality of electrodes suitably must be pasted different parts during acquisition ECG signal at human body.Electrocardiosignal also needs the personnel and the technology of specialty to handle and analyze, and significant ANS function just can be provided.Because this kind technology is easy-to-use inadequately, also be not easy to be applied to the patient, therefore the application of common skill can't be used at large.
Summary of the invention
Therefore, the purpose of this invention is to provide a kind of by measuring heart rate variability (Heart RateVariability, be called for short HRV) obtain the method and system of autonomic nervous system index, wherein can measure heart rate signal originally with very cheap one-tenth, and very convenient for user.
In addition, can provide significative results immediately, provide and further verify and assist, the chance of surviving that reduces potential unfavorable result and increase user to user and/or Medical Technologist.
For achieving the above object, the present invention proposes a kind of method of assessing autonomic nervous system function, wherein collects the physiological signal of implicit heart rate in one first end.Via a network system those digitized physiological signals are delivered to one second end, in wherein analyzing those digitized physiological signals automatically, so as to those ANS indexs are provided.This method more comprises via this network system the result of those analyses is offered user and/or Medical Technologist.In addition, those physiological signals of implicit this cardiac cycle of collecting in this first end according to the present invention comprise ECG signal, blood pressure signal, blood flow signal, contrafluxion amount signal, local oxygen content signal, and cardiechema signals, use present physiological monitor, personal computer, personal digital assistant, mobile phone or microchip cheaply.
The present invention proposes a kind of automatic remote control system of assessing autonomic nervous system function.This automatic remote control system comprises a heart rate signal acquisition system, in order to collect a heart rate signal and a diagnostic system, in order to the index of analyzing those heart rate signals and this autonomic nervous system function being provided.This automatic remote control system more comprises a network system, in order to by this heart rate signal acquisition system those heart rate signals are sent to this diagnostic system and by this diagnostic system those indexs of this ANS function are sent to this heart rate signal acquisition system.
Therefore, the acquisition of the physiological signal of implicit heart beat cycle is collected at one first end, carries out automatically at one second end so as to obtaining significant index and analyze physiological signal.So, can finish the collection of physiological signal by user at an easy rate, and cost is very cheap.In other words, this HRV technology can more easily be applied to the patient, even normal testee.
Its result is that the data of production ANS function that can be a large amount of are so as to promoting the research and development about the functional dependency between HRV and the various pathological symptom.User can be taken the points for attention of relevant its healthy situation immediately, so as to getting rid of disadvantageous result.
Must understand, the general remark of front and the detailed description of back all are exemplary, and are to be used to provide of the present inventionly further to explain, as declare.
Description of drawings
Fig. 1 is the flow chart according to the method for the diagnosis autonomic nervous system function of preferred embodiment of the present invention;
Fig. 2 A to Fig. 2 C is the demonstration of controlling the website (web site) of ANS functional diagnosis system according to automatic remote of the present invention;
Fig. 3 is the example of frequency spectrum of the various parameters of quantitative heart rate variability;
Fig. 4 is diagnosis commonsense method of autonomic nervous function and the comparison between the method for the present invention, with Electrocardiographic analysis as example.
The specific embodiment
At present, most commercialization physiological function monitoring arrangement provides digitized signal, for example, and signals such as monitoring blood pressure, blood flow, contrafluxion amount, local oxygen content and hear sounds.The signal of these different types comprises the information of cardiac cycle, thereby can be with deciding heart rate variability.Because the progress of Internet technology, the Internet can be used for transmission information in master-slave system (Client-Server system).Therefore anyly can provide instrument can be regarded as client about heart rate information, service end then provides the service of real-time conversion, utilize the automatic HRV analytical technology (Kuo et al.1999) of previous development to convert original physiologic signal (comprising ECG, blood pressure, blood flow, contrafluxion amount, local oxygen content and hear sounds) to significant autonomic nervous system (Autonomic Nervous System is called for short ANS) index.Therefore, can produce data in a large number, so as to promoting research and development about the functional dependency between HRV and the various pathological symptom about the ANS function.Further, the HRV technology can universalness, and can be applied to the patient at an easy rate, or even the normal testee in each place.
Heart rate variability is normally come out by ECG (electrocardiogram) derivation, and it is the electric record of myocardial contraction.Derive the indirect signal that obtains except ECG, blood pressure signal, blood flow signal, contrafluxion amount signal, local oxygen content signal, cardiechema signals and by aforementioned signal, also comprise information about cardiac cycle, these physiological signals, though need not decide HRV usually, but these physiological signals can be used for being used as the information source about HRV, use widely so as to promoting the HRV technology.
Fig. 1 is the flow chart according to autonomic nervous system function diagnostic method of the present invention.
As shown in Figure 1, the electrocardiogram that uses electrode, transducer (transducer) or mike to collect 5 minutes, or signals (step 100) such as blood pressure, blood flow, contrafluxion amount, local oxygen content and hear sounds.Then 5 minutes physiological signal is amplified, and with band-pass filter (step 102).Signal after the processing is 256 to 2048Hz extremely numeral (Analog-to-Digital, A/D) transducer sampling (step 104) of simulation again through sampling rate.Data sampling is to use computer installation to reach, and this computer installation comprises normal structures such as microprocessor and memorizer at least.After this, deliver to service end, carry out on-line analysis with digitized signal compression (step 106) and via network.
The information of client is sent to (step 108) of service end via LAN or the Internet, and the medium of transmission can be cable, optical fiber or electromagnetic wave.
Please still with reference to Fig. 1, service end receives after the digitized physiological signal, for example, ECG, blood pressure, blood flow, contrafluxion amount, local oxygen content and hear sounds, at first these digitized signals are decompressed (step 110), and then analyze, so as to calculating heart rate variability.Use spike detection algorithm (Kuo and Chan 1992) to detect all spikes (spike) of digitized physiological signal at this.The spike of each heart beating is defined as the time point (step 112) of this heart beating, at present and heart beating to the eartbeat interval between the heart beating of back be defined as the heart beat cycle (step 114) of this heart beating.Measure parameters such as the height of all heart beating spikes and persistent period, be used for calculating the meansigma methods and the standard deviation of each parameter, as standard form.Compare each heart beating with standard form then.If have the comparison result of any heart beating spike to drop on outside three standard deviations of standard form, then by as noise or wrong and it is abandoned.
Then qualified heart beat cycle sequence is taken a sample and the value preserving program with the frequency of 7.11Hz, so as to keeping the continuity (step 116) of its time.After this, use fast fourier transform (Fast Fourier Transform is called for short FFT) to carry out the analysis (step 118) of frequency domain.At first the interference of low-frequency band is avoided in the straight line drift of erasure signal, and uses the Hamming computing to avoid the mutual seepage (leakage) of individual frequencies composition in the frequency spectrum.The data (or 2048 points) of then getting 288 seconds are implemented fast fourier transform, rated output density frequency spectrum (powerspectral density), and with the power-density spectrum compensation that obtains because the decay that sampling and Hamming computing are caused.By integration power-density spectrum is quantized into the standard frequency domain parameter then, comprises low frequency (LF 0.04-0.15Hz) and high frequency (HF 0.15-0.40Hz), general power (TP) and low frequency/high frequency power ratio (LF/HF) (step 120).
All analysis results comprising various ANS indexs, frequency spectrum and suggestion, can be sent client (step 122) back to via network.Therefore user can be taken the points for attention about its healthy situation immediately.When sympathetic nerve and/or parasympathetic functions had the situation of imbalance, no matter be Tai Gao or too low, service end also can be designed to notify automatically doctor or other Medical Technologist, so as to user being provided real-time assistance.According to the present invention, have the quick diagnosis and the conversion of data, and can measure HRV to user at an easy rate, the chance of surviving that can reduce potential unfavorable result and increase user.
Fig. 2 A to Fig. 2 C is the demonstration of controlling the website (web site) of ANS functional diagnosis system according to automatic remote of the present invention.Shown in Fig. 2 A to Fig. 2 C, the computer system of client is connected to the website of service end after collecting the ECG signal, and the computer archives that will comprise the ECG signal are delivered to service end.Within the several seconds, service end is promptly replied the ANS index, comprising about the HF of parasympathetic function and about the LF/HF of orthosympathetic function.Service end more can provide gives client with the original signal spectrum figure of the quantitative parameter of HRV (rawpower spectrum), is used for doing the checking of off-line.
Many present physiological function monitoring arrangements provide the digitized function of physiological signal, for example, ECG, blood pressure, blood flow, contrafluxion amount, local oxygen content and hear sounds, and handle these digitized signals, give user so as to supply about the information of moment or average heart rate.If these digitized signals are sent to automatic remote control ANS functional diagnosis service end via the Internet, then the ANS function of user can in seconds obtain soon.Thereby can be used as automatic remote control ANS function system in order to the digital physiological function monitoring arrangement of measuring above-mentioned relevant heart rate signal, even without extra software design is provided, as long as these devices comprise the network input/output capabilities.
Fig. 4 uses ECG signal to be used as physiological signal for the commonsense method of diagnosis ANS function and the comparison between the method for the present invention.As shown in Figure 4, client just is responsible for the output of data collection and data.Need not the analysis of data in client.Therefore, client only needs hardware cheaply, for example, and physiological function surveillance, personal computer, personal digital assistant (Personal Digital Assistant is called for short PDA), mobile phone or microchip.Its result is, can mass production about the data of ANS function, so as to promoting development about the emic research between HRV and the various pathological symptom.In addition, the method can be widely used and be easy to be applied to patient or or even normal testee everywhere.
Please still with reference to Fig. 4, service end is designed to the rapid analysis that data are provided, and for example, uses the high-speed computer (Kuo et al., 1999) with automatic heart rate parser.After converting primary physiological signal to various ANS indexs, send client back to, accurately service fast again of user is provided.
Therefore, the additional functionality that present physiological moniyoting device is possessed provides the diagnosis autonomic nervous system required function, so the cost that automatic remote of the present invention is controlled ANS functional diagnosis system is also reduced significantly.
In addition, because heart rate signal of the present invention obtains by measuring the derivation of original physiologic signal, comprise blood pressure, blood flow, contrafluxion amount, local oxygen content, hear sounds and ECG, so this HRV technology can be applied even more extensively.In fact, certain during these are measured some can allow user (client) carry out in the family of user oneself, as long as use cheaply hardware to collect data, such as personal computer, PDA, microchip etc.So can use very low cost quick diagnosis ANS function, and user can carry out easily.In addition, the present invention also provides automatic HRV Analysis server, by the heart rate signal that receives and analyze by network system from user, and immediately significant ANS index is offered user.User can obtain the points for attention of relevant its healthy situation at once.Because service end also can be designed to notify automatically doctor or other Medical Technologist when realizing that sympathetic nerve and/or parasympathetic functions have the situation of imbalance, be used for providing real-time assistance, therefore the chance of surviving that can reduce potential unfavorable result and increase user to user.
Claims (20)
1, a kind of method of assessing autonomic nervous system function is characterized in that, this method comprises:
Collect the physiological signal of implicit heart rate in one first end;
Those physiological signals are delivered to one second end via a network system; And
Analyze those physiological signals in this second end and it is characterized in that, quantize the frequency domain parameter of those physiological signals automatically, so as to a quantitative heart rate variability.
2, the method for claim 1 is characterized in that, those physiological signals comprise digitized physiological signal.
3, the method for claim 1 is characterized in that, after this second end is analyzed those digitized physiological signals, sends this first end back in order to the frequency domain parameter of quantitative this heart rate variability.
4, the method for claim 1 is characterized in that, this second end is designed to notify one the 3rd end, in order to the frequency domain parameter of quantitative this heart rate variability.
5, method as claimed in claim 4 is characterized in that, the 3rd end comprises a Medical Technologist.
6, the method for claim 1, it is characterized in that those physiological signals of implicit this heart rate are by an ECG signal, a blood pressure signal, a blood flow signal, a contrafluxion amount signal, a local oxygen content signal, a cardiechema signals or by those physiological signals selected come out in the group that the indirect signal that obtains forms that derived.
7, the method for claim 1 is characterized in that, those physiological signals are collected with an electrode, a transducer or a mike.
8, the method for claim 1 is characterized in that, this method is to use a physiology function surveillance, a personal computer, a personal digital assistant, a mobile phone or a microchip to transmit those physiological signals.
9, the method for claim 1 is characterized in that, before transmitting those physiological signals, those physiological signals are exaggerated and with a band-pass filter.
10, the method for claim 1 is characterized in that, those frequency domain parameters comprise low frequency (Low Frequency is called for short LF), high frequency (High Frequency is called for short HF), general power (Total Power is called for short TP) and LF/HF.
11, the method for claim 1 is characterized in that, analyzes those digitized physiological signals at this second end and comprises and carry out an automatic heart rate Variability Analysis algorithm.
12, method as claimed in claim 11 is characterized in that, this automatic heart rate Variability Analysis algorithm comprises:
Calculate heart beat cycle according to those digitized physiological signals;
Convert those heart beat cycles to a frequency spectrum; And
Quantize the composition of a frequency distribution of this heart rate variability.
13, the method for claim 1 is characterized in that, this first end comprises a client of a master-slave system.
14, the method for claim 1 is characterized in that, this second end comprises a service end of a master-slave system.
15, the method for claim 1 is characterized in that, this network system comprises a Internet or a LAN.
16, the automatic remote control system of a kind of assessment autonomic nervous system (Autonomic Nervous System is called for short ANS) function is characterized in that this system comprises:
One heart rate signal acquisition system, it collects heart rate signal;
One diagnostic system, it analyzes those heart rate signals, wherein quantizes the frequency domain parameter of those heart rate signals, so as to the index of this autonomic nervous system function is provided; And
One network system, it is sent to this diagnostic system by this heart rate signal acquisition system with those heart rate signals, makes on-line analysis, and by this diagnostic system those indexs of this ANS function is sent to this heart rate signal acquisition system.
17, as claim 16 a described system, it is characterized in that those heart rate signals that this heart rate signal acquisition system is collected comprise an ECG signal, a blood pressure signal, a blood flow signal, a contrafluxion amount signal, a local oxygen content signal, reach a cardiechema signals.
18, as claim 16 a described system, it is characterized in that, this heart rate signal acquisition system more comprises an amplifier, a wave filter and a computer system, with those heart rate signal digitizeds and by this network system those digitized heart rate signals is sent to this diagnostic system.
As claim 16 a described system, it is characterized in that 19, this heart rate signal acquisition system comprises a physiology function surveillance, a personal computer, a personal digital assistant, a mobile phone or a microchip.
20, as claim 16 a described system, it is characterized in that, this diagnostic system comprises an automatic ANS functional analysis system, in order to automatic calculating at present and the heart beat cycle between the heart beating of back, the composition that those heart beat cycles are converted to a frequency spectrum and quantize a frequency distribution of a heart rate variability.
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| CN1316940C (en) * | 2004-04-26 | 2007-05-23 | 天津大学 | Bioelectricity checking circuit and checking method |
| CN102799794A (en) * | 2012-08-28 | 2012-11-28 | 史荣涛 | Self-service evaluation system and evaluation method thereof of organism physiological statuses |
| CN103445767A (en) * | 2013-08-30 | 2013-12-18 | 邝建 | Sensing monitoring interaction control fully automatic autonomic nerve function detection instrument and detection method |
| CN104840186A (en) * | 2015-05-07 | 2015-08-19 | 中山大学 | Evaluation method of autonomic nervous function of patient suffering from CHF (Congestive Heart-Failure) |
| CN105455797A (en) * | 2014-08-19 | 2016-04-06 | 吴健康 | Method and device for measuring autonomic nerve heart regulation and control function |
| CN105496377A (en) * | 2014-10-08 | 2016-04-20 | 吴健康 | Heart rate variability biofeedback exercise systematic method and apparatus |
| CN106108882A (en) * | 2016-09-07 | 2016-11-16 | 深圳前海慧练天下网络科技有限公司 | A kind of heart rate variability monitoring underwear and system |
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| CN1316940C (en) * | 2004-04-26 | 2007-05-23 | 天津大学 | Bioelectricity checking circuit and checking method |
| CN102799794A (en) * | 2012-08-28 | 2012-11-28 | 史荣涛 | Self-service evaluation system and evaluation method thereof of organism physiological statuses |
| CN102799794B (en) * | 2012-08-28 | 2015-09-23 | 史荣涛 | The self-service evaluating system of life entity physiological situation |
| CN108568031A (en) * | 2013-06-13 | 2018-09-25 | 迪彦希斯有限公司 | The stimulation diathermy controlled using autonomic nerves system |
| CN103445767A (en) * | 2013-08-30 | 2013-12-18 | 邝建 | Sensing monitoring interaction control fully automatic autonomic nerve function detection instrument and detection method |
| CN103445767B (en) * | 2013-08-30 | 2016-03-23 | 邝建 | The full-automatic autonomic nervous function detector of sensor monitoring interactive controlling |
| CN105455797A (en) * | 2014-08-19 | 2016-04-06 | 吴健康 | Method and device for measuring autonomic nerve heart regulation and control function |
| CN105455797B (en) * | 2014-08-19 | 2020-01-07 | 南京茂森电子技术有限公司 | Autonomic nerve heart regulation function measuring method and device |
| CN105496377A (en) * | 2014-10-08 | 2016-04-20 | 吴健康 | Heart rate variability biofeedback exercise systematic method and apparatus |
| CN104840186A (en) * | 2015-05-07 | 2015-08-19 | 中山大学 | Evaluation method of autonomic nervous function of patient suffering from CHF (Congestive Heart-Failure) |
| CN106108882A (en) * | 2016-09-07 | 2016-11-16 | 深圳前海慧练天下网络科技有限公司 | A kind of heart rate variability monitoring underwear and system |
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