JP4243605B2 - Autonomic nerve inspection device - Google Patents

Description

  The present invention relates to an autonomic nerve examination apparatus. More specifically, the present invention relates to an autonomic nerve test apparatus with improved accuracy using the heart rate variability.

Heart Rate Variability (hereinafter referred to as HRV) refers to a periodic change in heart rate over time, which is a constant of the autonomic nervous system with respect to internal and external environmental factors. It is an important key to tracking the homeostasis regulation mechanism.
The autonomic nerve test device analyzes minute changes in heartbeats according to the degree of heartbeat variability through waveforms, and visualizes the response of the human autonomic nerve to stress to confirm the current health state and psychophysiological stability state. It can be equipped.
Autonomic nerves are nerves that control the functions of internal organs and blood vessels, and can be classified as sympathetic nerves and parasympathetic nerves. Since this autonomic nerve is involved in the smooth action of the human body's internal organs and hormones, the stable antagonism of the autonomic nerve is an absolute element for maintaining a healthy and comfortable mind and body. Autonomic nerves are centered in the hypothalamus of the diencephalon, and the periphery is located in all organs and organization in the body. In charge of important regulatory functions in life activities such as metabolism.

Autonomic nervous system activity and heartbeat movement are closely related. Therefore, the activity of the autonomic nervous system can be estimated by measuring the heart rate variability. In particular, the method of analyzing the activity of the autonomic nervous system by measuring the heart rate variability is excellent in reproducibility and can be applied to a non-wetting inspection method.
More specifically, the heart rate is determined by the autonomic nervous system affecting the intrinsic spontaneity of heart rhythm cells in the eastern nodule. The eastern nodule is under the control of both sympathetic and parasympathetic nerves, and the mutually opposing effects of sympathetic and parasympathetic nerves balance each other to determine the heart rate. Thus, short-term heart rate variation is determined by respiration, baroreceptor, chemoreceptor, and autonomic nervous system activity. Long-term heart rate variations contribute not only to breathing, baroreceptors, chemoreceptors, and autonomic nervous system activity, but also to body temperature, metabolic rate, and sleep cycle.

HRV is associated with the interaction between the sympathetic and parasympathetic nerves that affect the eastern nodule, which does not mean the change in heart rate represented on the record over time, but the heart rate and RR interval ( Reflects changes in the interval from the R point to the next R point on the ECG. That is, it means a minute variation between one heart week and the next heart week.
In general, heart rate mutation is measured using an electrocardiogram (hereinafter referred to as ECG) and oxygen saturation (hereinafter referred to as PPG). The heart rate interval is obtained by detecting the peak in the waveform on the electrocardiogram or oxygen saturation signal and measuring the interval from peak to next peak. It is continuously changed around 800msec. If such a heart beat interval is measured in real time, it can be expressed in real time as a heart beat rate per minute (heart rate per minute) again by a mathematical formula. The change graph of the heart rate calculated from the heartbeat interval measured in this way is called an HRT (Heart Rate turbulence) tachogram.

FIG. 1a is an example of a heart rate change of a normal person, and FIG. 1b is an example of a heart rate change of a sick person.
Figures 1a and 1b record changes in heart rate during the recording time, but if the interval between peaks on ECG or PPG, i.e. RR interval or NN (Normal to Normal) interval is measured. Then, the instantaneous heart rate is calculated, and the graphs as shown in FIGS. 1a and 1b are drawn.
In the healthy person in FIG. 1a, the graph as described above appears irregular and complicated, but in the case of the person in the diseased state in FIG. 1b, the minute change of the heartbeat appears very monotonously. That is, the meaning of HRV reduction means that the complexity of the dynamic change of heartbeat has been reduced, which means that the body's ability to adapt to a constantly changing environment has been reduced. From the minute changes between beats, the regulation mechanism of homeostasis in the autonomic nervous system can be estimated. A healthy and well-regulated person can respond to oxygen levels in the blood, body temperature, blood pressure, etc. sensitively and quickly reach a physiological equilibrium in a short time. Otherwise, a physiological equilibrium cannot be reached.

HRV analysis methods are roughly classified into time domain analysis and frequency domain analysis.
Time domain analysis is a technique that statistically processes the RR interval between heartbeats, typically analyzing data over a 24-hour period, but in both European and North American heart rhythm and electrophysiology (the The Task Force of the European Society of Cardiology and the North American Society of Pacing and Electrophysiology (hereinafter referred to as NASPE) says that even a 5-minute record is possible. The heart rate and the interval between normal pulses are measured at a specific time. RR interval and instantaneous heartbeat are determined from continuous ECG or PPG waveforms. The heart rate variability in the time range mainly reflects the influence of the parasympathetic nervous system, and all units of time range analysis are msec. In the time range analysis, a series of materials can be obtained in two types. One of them is obtained by direct measurement of the RR interval and instantaneous heartbeat, and the other is obtained from the difference in the RR interval. Parameters obtained through time range analysis are the mean heart rate (Mean Heart rate), the standard deviation of the entire RR interval (hereinafter referred to as SDNN), and the average square root of the difference between adjacent RR intervals (hereinafter referred to as RMSSD). )

Frequency domain analysis FFT (fast Fourier transform: Fast Fourier Transform) to analyze the frequency range by using an analytical method to evaluate separated each frequency band constituting the HRV variation signal. In other words, each HRV signal is combined with frequency signals in other bands and appears as one complex signal, so the intensity (PSD: Power Spectral Density) of each frequency band that makes up such an HRV signal is separated. This is a method to evaluate. The parameters required through frequency range analysis are the intensity of very low frequency (hereinafter referred to as VLF), the intensity of low frequency (hereinafter referred to as LF), and the high frequency band (High frequency). ) (Hereinafter referred to as HF) intensity, 5-minute total power (hereinafter referred to as TP), low frequency to high frequency band intensity ratio (LF / HF ratio), normalization There are low and high frequency band strengths (normalized LF and HF).

However, there are cases where the parameters of the conventional autonomic nerve test apparatus are erroneously measured due to dynamic noise or the like. In many cases, the conventional autonomic nerve test apparatus gives a wrong result because the reference value for the test value does not match the Oriental. Since these standard values use the standard values defined by NASPE, these standard values are measured based on Westerners, so they are appropriate for Easterners such as Japan including Korea. is not.
Therefore, there is a demand for an autonomic nerve examination apparatus with improved accuracy.

  In the present invention, not only the time domain analysis but also the frequency domain analysis is performed, and the autonomic nerve test apparatus is provided with a reference value suitable for the Oriental who removes dynamic noise and uses the heart rate variability. provide.

The present invention also provides an autonomic nerve test apparatus having an index capable of quantitatively analyzing a compression index (physical stress index) and a sensory state (mental stress index).
In addition, the present invention can perform quantitative analysis on autonomic nervous system activity to simultaneously analyze sympathetic and parasympathetic nerve activities, and the present invention can confirm the degree of autonomic nervous system balance. Can predict health status, can confirm the body's response to stress, understand the acute / chronic degree of response to stress, and understand the degree of physical / mental stress Autonomic nerve testing device that can predict the risk of stress-related diseases and easily check the degree of fatigue of the subject, and can predict the electrical stability of the heart and autonomic neurological interpretation of functional digestive disorders I will provide a.
That is, the object of the present invention is to be able to analyze sympathetic and parasympathetic activities at the same time, to confirm the degree of balance of the autonomic nervous system, and to be able to confirm the body reaction due to stress. It is to provide a neurological examination apparatus.

Another object of the present invention is to provide an autonomic nerve examination apparatus that quantitatively analyzes a compression index and a sensuous state.
Another object of the present invention is to provide an autonomic nerve test apparatus using a heart rate variability with improved accuracy by removing dynamic noise.
Another object of the present invention is to provide a database constructed according to gender and age for normal reference values suitable for oriental people including Korea and Japan. An object of the present invention is to provide an autonomic nerve test apparatus capable of more accurately analyzing the degree of health.

  The present invention that achieves the above object includes a signal detection unit that detects an electrocardiogram signal or an oxygen saturation signal, an A / D converter that converts an output signal of the signal detection unit into a digital signal, and the A / D Peak detector for detecting R point and RR interval of electrocardiogram signal from converter output signal, dynamic noise remover for removing dynamic noise from output signal of said peak detector, and output signal of said dynamic noise remover Enter the time analysis unit for determining parameters on the time domain from the frequency analysis unit for determining parameters on the frequency domain from the output signal of the dynamic noise removal unit, and subject information including gender and age. A data input unit that temporarily stores data, a database that stores data for setting a reference range based on the gender, age, and parameters of Orientals, the time analysis unit, and the frequency analysis unit. Et outputted parameter comprises a parameter analysis unit for comparing whether there within the reference range of the.

  The time analysis unit includes, as parameters on the time domain, the average heart rate (mean HRT), the standard deviation of the entire RR interval (SDNN), and the square root of the average value of squared differences between adjacent RR intervals ( RMSSD), consecutive RR interval difference (SRD), and compression index (PI).

The frequency analysis unit includes parameters on the frequency domain, such as very low frequency band (VLF) intensity (power spectral density) (PSD), low frequency band (LF) intensity (PSD), and high frequency band (HF) intensity (PSD). ), Overall intensity (TP) for 5 minutes, normalized intensity in the low frequency band (normalized LF), normalized intensity in the high frequency band (normalized HF), band intensity ratio between low frequency and high frequency (LF / HF) ratio), emotional state (ES), and mental stress index (MSI).

  The parameter analysis unit obtains the maximum reference value and the maximum reference value of each parameter according to sex and age as the reference range of each parameter. In addition, by using the maximum reference value and the maximum reference value of each parameter, it is determined whether the parameter received from the time analysis unit or the frequency analysis unit is within the reference range.

For example, when the gender of the subject input from the data input unit is a male, the parameter analysis unit is configured such that the maximum reference value (y _max ) of the average heart rate is
y _max = -0.1x + 89.1 (where y _max is the maximum reference value for average heart rate and x is age)
The minimum reference value (y _min ) of the average heart rate is
y _min = -0.1x + 67.1 (where y _min is the minimum reference value for average heart rate and x is age)
It is calculated by.

In addition, when the subject's gender input from the data input unit is a girl, the maximum reference value (ymax) of the average heart rate is
y _max = -0.16x + 91.1 (where y _max is the maximum reference value for average heart rate and x is age)
The minimum reference value (y _min ) of the average heart rate is
y _min = -0.16x + 71.1 (where y _min is the minimum reference value for average heart rate and x is age)
It is calculated by.
Other parameters can also be obtained from the mathematical formula of the present invention with age as a variable (x) depending on gender.

As explained above, the autonomic nerve test apparatus of the present invention has quantitatively analyzed the degree of compression, the degree of emotional state, and the degree of mental stress, and has improved accuracy by removing dynamic noise. .
In addition, the autonomic nerve test apparatus of the present invention comprises a database constructed by sex and age, with normal reference values appropriate for orientals including Korea and Japan, and includes physical status, mental status, and sensibility. A more accurate analysis of the degree of general health, including the condition.
In addition, the autonomic nervous test apparatus of the present invention can perform quantitative analysis on autonomic nervous system activity to simultaneously analyze sympathetic and parasympathetic activity, and can confirm the degree of balance of the autonomic nervous system. Predict physical health and confirm the body's reaction due to stress, understand the grade of the class / lateness of the response to stress, and the degree of physical / mental stress It is possible to grasp and predict the risk of stress related diseases, easily check the fatigue level of the subject, predict the electrical stability of the heart, and autonomic neurology such as functional digestive disorders Can be interpreted.

Hereinafter, the configuration and operation of an autonomic nerve test apparatus according to an embodiment of the present invention will be described in detail with reference to the accompanying drawings.
FIG. 2 is a block diagram for schematically explaining the configuration of an autonomic nerve test apparatus according to a preferred embodiment of the present invention, as a signal detection unit (1000), an A / D converter (1300), a peak detection unit (1600). ), A time analysis unit (2000), a frequency analysis unit (3000), a parameter analysis unit (4000), a reference value database (5000), a data input unit (5500), and an analysis result display unit (6000).
The signal detector (1000) is for detecting an electrocardiogram (ECG) signal and an oxygen saturation (PPG) signal from the body of the subject, and the ECG signal detector (100) and the PPG signal detector (500) are connected to each other. It has.
The ECG signal detection unit (100) is composed of two electrocardiogram electrodes, an amplifier, and a filter. After detecting and amplifying an electrocardiogram signal from the two electrocardiogram electrodes, noise is removed.
The PPG signal detection unit 500 includes an optical sensor, an amplifier, and a filter, and detects and amplifies the PPG signal from the optical sensor, and then removes noise.
The A / D converter (1300) converts the output signals of the ECG signal detector (100) and the PPG signal detector (500) of the signal detector (1000) into digital signals.

The peak detection unit (1600) detects an R point that is a peak of the electrocardiogram signal from the output signal of the A / D converter (1300), calculates an RR interval, and calculates a heart rate. In general, an electrocardiogram signal in one week period has P, Q, R, S, and T points, and since the point corresponding to the peak point is the R point, the R point is detected here. Then, the RR interval, that is, the interval from the R point to the next R point is obtained. The RR interval is the heart rate cycle. The heart rate at the corresponding time is calculated from the value of the RR interval and stored during the measurement. When the measurement is completed, the stored value is transmitted to the time analysis unit (2000).
The time analysis unit (2000) uses statistical techniques to calculate time domain parameters: mean heart rate (mean HRT), standard deviation of the entire RR interval (SDNN) (hereinafter referred to as SDNN), and adjacent RR intervals. The square root of the difference (RMSSD) (hereinafter referred to as RMSSD), successive RR interval difference (hereinafter referred to as SRD), approximate entropy (hereinafter referred to as APEN) ), And a pressure index (hereinafter referred to as PI). In particular, the compression index (PI) can be said to be a physical stress index (hereinafter referred to as PSI).

  Frequency analysis (3000) calculates the intensity of frequency domain parameters, i.e., the results obtained through FFT transformation, by region in the very low frequency band (VLF), low frequency band (LF), and high frequency band (HF). Using this, the total intensity (TP) for 5 minutes, normalized intensity in the low frequency band (normalized LF), normalized intensity in the high frequency band (normalized HF), band intensity ratio of low frequency to high frequency ( LF / HF ratio) is calculated. The emotional state (hereinafter referred to as ES) is determined from the low frequency to high frequency band intensity ratio (LF / HF ratio). In particular, the emotional state (ES) can be said to be a mental stress index (hereinafter referred to as MSI).

The reference value database (5000) is a database for normal ranges based on gender and age obtained from clinical data of about 5,000 normal persons. Based on this, it is possible to determine whether there is normality, that is, whether it is normal. The reference value database (5000) is a database suitable for Oriental people including Korea and Japan.
The data input unit (5500) inputs the gender and age of the subject and temporarily stores them.
Parameter analysis unit (4000) is a parameter obtained from time analysis unit (2000) and frequency analysis unit (3000), that is, average heart rate, SDNN, RMSSD, APEN, SRD, PI, TP, VLF intensity, LF Intensity, HF intensity, normalized intensity in low frequency band (normalized LF), normalized intensity in high frequency band (normalized HF), low frequency to high frequency band intensity ratio (LF / HF ratio), ES The reference value database (500) is compared with the reference range using the values already constructed and analyzed. And by analogy with the relationship between the biological signal and clinical results detected for each parameter detected from the time analysis unit (2000) and frequency analysis unit (3000), the activity of the autonomic nerve, the degree of balance of the autonomic nerve, the degree of stress resistance Analyze stress index, fatigue level, heart stability, abnormal heart rate, etc.

The peak detection unit (1600), the time analysis unit (2000), the frequency analysis unit (3000), and the parameter analysis unit (4000) are constituted by a microprocessor.
The analysis result display unit (6000) displays the analysis result by two methods. The first display method is a general display method that displays a unique value of each parameter with reference to a normal region, and displays a compression index (PI), emotional state (ES), and the like.
The second display method analogizes the relationship between vital signs and clinical results for each parameter, autonomic nerve activity, autonomic balance, stress resistance, stress index, fatigue, average heart rate, heart stability Displays the degree, abnormal heart rate, etc.
FIG. 3 is a block diagram for explaining the signal detection unit of FIG. 3 (a) is a block diagram for explaining the ECG signal detection unit (100) of FIG. 2, and FIG. 3 (b) is a block diagram for explaining the PPG signal detection unit (500) of FIG. FIG.

In FIG. 3 (a), the ECG signal detection unit (100) includes two electrocardiogram electrodes (110), an amplifier (130), and a filter unit (160). Two electrocardiogram electrodes (110) detect an electrocardiogram signal. Finally, an electrocardiogram electrode (110) can be used with a lead that is worn on both wrists. The amplifier (130) differentially amplifies the output signal of the electrocardiogram electrode (110). The filter unit (160) removes noise such as 60 Hz noise.
In FIG. 3 (b), the PPG signal detection unit (500) includes an optical sensor (510), an amplifier (530), and a filter unit (560). Two optical sensors (510) convert the blood flow signal into an electrical signal. The amplifier (130) amplifies the output signal of the optical sensor (510). The filter unit (160) removes noise such as 60 Hz noise.

FIG. 4 is a block diagram for explaining the configuration of the peak detection unit of FIG.
The peak detection unit (1600) includes a noise removal unit (1610), an R point detection unit (1620), an RR interval detection unit (1630), a heart rate calculation unit (1640), and a buffer unit (1650, 1660).
The noise removing unit (1610) removes an artifact from the electrocardiogram signal received from the A / D converter (1300).
The R point detection unit (1620) differentiates the output signal of the noise removal unit (1610), searches for the inflection point with the differentiated waveform, and calculates the value and time position of the first peak and the second peak from the inflection point. To detect. Here, the first peak corresponds to the first R point, and the second peak corresponds to the second R point.
The RR interval detection unit (1630) obtains an RR interval, that is, a time interval from the second R point to the first R point, from the output signal of the R point detection unit (1620).
A heart rate calculation unit (1640) calculates the number of heartbeats per minute (heart rate per minute) by dividing the number of data input for one minute from the A / D converter (1300) by the RR interval.
The buffer unit (1650, 1660) buffers the RR interval and heart rate per minute determined by the RR interval detection unit (1630) and heart rate calculation unit (1640), and outputs them to the time control unit (1600) To do.

The peak detection unit (1600) of FIG. 2 will be described in more detail with reference to FIG.
FIG. 5 is a procedure diagram for explaining the peak detection unit of FIG.
Artifacts are removed from the electrocardiogram signal received from the A / D converter (1300) (S110) by passing through a 30 Hz third-order low-pass filter (LPF) (S120). Then, it is differentiated and an inflection point is searched for with the differentiated waveform (S130).
The time position where the first peak is located, that is, the first peak time position is obtained from the inflection point searched in this way, and the first peak value at the first peak time position is obtained (S140). If the first peak thus obtained meets a predetermined R setting criterion, it is obtained as the first peak (S150). If the first peak does not meet the predetermined R setting criterion, the process ends (S160). The first peak is a first R point, and this R point corresponds to a predetermined R setting standard and corresponds to a normal R point.
In the differential waveform, the inflection point is searched after the first peak time position, the time position where the second peak is located, that is, the second peak time position is obtained, and the second peak value at the time position is obtained ( S170). If the second peak thus obtained meets a predetermined R setting criterion, it is obtained as the second peak (S180). If the second peak does not meet the predetermined R setting criteria, the process ends (S190). The second peak is a peak immediately adjacent to the first peak, and the second peak is the second R point. The second R point is an R point corresponding to a predetermined R setting standard, and corresponds to a normal R point. The second R point is the next R point immediately after the first R point.

The time interval from the second R point to the first R point, which is the RR interval, instantly, the time interval from the second peak time position to the first peak time position is the second peak time position to the first peak time. The RR interval is obtained by subtracting (subtracting) the position (S200). Since the RR interval is an interval from a normal R point to a normal R point, it is also called an NN interval. The RR interval can be said to be a time interval corresponding to one week of the electrocardiogram, that is, one heartbeat.
Therefore, the heart rate per minute is the number of data per minute by multiplying the sampling frequency of the A / D converter (1300) by 60, and if this is divided by the RR interval, the heart rate per minute (the heart rate per minute) Number) (210).
The following describes the parameters analyzed on the time domain in the present invention.
The time analysis unit (2000) is the RR interval obtained by the time analysis unit (2000), the heart rate per minute using a statistical technique, the average heart rate (mean HRT), the standard deviation (SDNN) of the overall RR interval, The average square root (RMSSD), approximate entropy (APEN), consecutive RR interval difference (SRD), and compression index (PI) are obtained by squaring the difference between adjacent RR intervals.
The N RR intervals (RRI) acquired during the measurement time can be expressed as Equation 1.

RRI = {I (1), I (2), I (3), ..., I (N)} (Formula 1)

In Equation 1, RRI is N RR intervals acquired during the measurement time, and I (1), I (2), I (3)... I (N) are RR intervals.
The N heart rate (hereinafter referred to as HRT) data acquired during the measurement time can be expressed as Equation 2.

HRT = {hr (1), hr (2), hr (3), ..., hr (N)} (Formula 2)

HRT is the N heart rates acquired during the measurement time, and hr (1), hr (2), hr (3),..., Hr (N) are each the heart rate. hr (1), hr (2), hr (3), ..., hr (N) are the RR intervals of Equation 1, i.e., I (1), I (2), I (3), ... , I (N) is the heart rate obtained.

（式4）
式4において、Nは総心拍数であり、hr(i)はi番目の心拍数である。平均心拍数(mean HRT)は分当りの心拍動数で、単位がbpmである。 The i-th heart rate can be expressed as Equation 3.

hr (i) = (total number of samples per minute) / I (i) (Formula 3)

If the sampling frequency of the A / D converter is 500 Hz, the total number of samples per minute (60 seconds) is 500 × 60, which is 30000.
Therefore, the average heart rate during the recording time is referred to as the average heart rate (mean HRT), which can be expressed as Equation 4.

(Formula 4)
In Equation 4, N is the total heart rate, and hr (i) is the i-th heart rate. The average heart rate (mean HRT) is the heart rate per minute and the unit is bpm.

（式5）
式5において、meanRRIは平均RR間隔であり、I(i)はi番目のRR間隔である。
隣接したRR間隔の差を二乗した値の平均の平方根(RMSSD)は式6によって求める。

（式6）
連続されるRR間隔差(successive RRI difference)(SRD)は式7によって求める。

（式7）
SRDは5分の区間の中において前部分の日程区間をベースラインとして取って、変化の程度を測定することで、SRDのデータは心拍が一定な状態(status)を維持するのかとうかを分かる指数になる。 The standard deviation (SDNN) of the entire RR interval is obtained by Equation 5.

(Formula 5)
In Equation 5, meanRRI is the average RR interval, and I (i) is the i-th RR interval.
The average square root (RMSSD) of the value obtained by squaring the difference between adjacent RR intervals is obtained by Equation 6.

(Formula 6)
The consecutive RRI difference (SRD) is obtained by Equation 7.

(Formula 7)
SRD can measure whether the SRD data maintains a constant status by measuring the degree of change by taking the previous schedule as a baseline within a 5-minute interval Become an exponent.

（式8） The compression index (PI) is obtained by Equation 8.

(Formula 8)

（式9） In Equation 8, VS is a variation scope, that is, a range of variation in the RR interval. MO is the most probable meaning of the RR intervals in the RR interval data, and MOA is the number of the most probable meanings of the RR intervals in the RR interval data, that is, the MO It is a number.
Since the compression index (PI) is the same as the physical stress index (PSI), it can be expressed as in Equation 9.

(Formula 9)

（式10）
ただし、この時、Pm(i)は集合RRIの連続されたm個の元素で構成された部分集合であり、Pm={Pm(1)、Pm(2)、Pm(3)、・・・、Pm(N-m+1)}として表すことができる。
そして、0≦k＜mである時、Pm(i)とPm(j)とが｜I(i+k)-I(j+k)｜＜rを満足すれば、二つのパターンであるPm(i)とPm(j)とが「類似である」と定義して、集合PmでPm(i)と「類似である」パターンの個数をn_im(r)という。 In addition, the time analysis part (2000) calculates approximate entropy (APEN), so APEN statistically quantifies how complex the signal is in the time series. Here, it is a numerical value that quantifies a series of complexity of the total heartbeat time.
Approximate entropy (APEN) is obtained by Equation 10.

(Formula 10)
However, at this time, Pm (i) is a subset composed of consecutive m elements of the set RRI, and Pm = {Pm (1), Pm (2), Pm (3),. , Pm (N−m + 1)}.
When 0 ≦ k <m, if Pm (i) and Pm (j) satisfy | I (i + k) −I (j + k) | <r, two patterns Pm (i) and Pm (j) are defined as “similar”, and the number of patterns “similar” to Pm (i) in the set Pm is called n _im (r).

FIG. 6 includes a dynamic noise removing unit (2100), a time calculation processing unit (2050), and a time buffer unit (2700) as a block diagram for explaining the configuration of the time analysis unit (2000) in FIG. The time calculation processing unit (2050) includes an average heart rate calculation unit (2200), an SDNN calculation unit (2300), an RMSSD calculation unit (2400), an SRD calculation unit (2500), and a PI calculation unit (2600). Buffer part (700) is the first time buffer part (2150), the second time buffer part (2250), the third time buffer part (2350), the fourth time buffer part (2450), the fifth time buffer part (2550) And a sixth time buffer unit (2650).
The dynamic noise removal unit (2100) removes data erroneously detected by motion artifacts from the data input by the peak detection unit (1600) and replaces the data with clean data with no dynamic noise. Put.

The average heart rate calculation unit (2200) obtains an average heart rate (mean HRT) by Equation 4 using the output signal of the dynamic noise removal unit (2100).
The SDNN calculation unit (2300) obtains the standard deviation (SDNN) of the entire RR interval by Equation 5 using the output signal of the dynamic noise removal unit (2100) and the output signal of the average heart rate calculation unit (2200).
The RMSSD calculation unit (2400) obtains an average square root (RMSSD) of values obtained by squaring the difference between adjacent RR intervals using Equation 6 using the output signal of the dynamic noise removal unit (2100).
The SRD calculation unit (2500) obtains a continuous RR interval difference (SRD) according to Equation 7 using the output signal of the dynamic noise removal unit (2100).
The PI calculation unit (2600) obtains PI according to Equation 8 using the output signal of the average heart rate calculation unit (2200).
Although not shown in the drawings, the time analysis unit 2000 further includes an APEN calculation unit (not shown) and a buffer unit using the APEN calculation unit.

  The first to sixth time buffer units (2150, 2250, 2350, 2450, 2550, 2650) are a dynamic noise removal unit (2100), an average heart rate calculation unit (2200), an SDNN calculation unit (2300), an RMSSD calculation unit ( 2400), the SRD calculation unit (2500), and the PI calculation unit (2600) output signals are buffered, and these output signals are transmitted to the frequency analysis unit (3000) and the parameter detection unit (4000).

The following describes the parameters analyzed on the frequency domain in the present invention.
The frequency analysis unit (3000) separates and evaluates the strength (POWER) of each frequency band (VLF, LF, HF) that constitutes the heart rate variation (HRV) signal. This is for evaluating the relative strength of the signal in the frequency domain, that is, the power spectral density (PSD).
The frequency analysis unit (3000) performs FFT conversion to proceed with frequency analysis from the output signal of the peak detection unit (1600). The intensity obtained for each region of the very low frequency band (VLF), low frequency band (LF), and high frequency band (HF) is calculated from the results obtained through the FFT conversion, and the total intensity for 5 minutes is calculated using these. TP), normalized intensity of low frequency band (normalized LF), normalized intensity of high frequency band (normalized HF), intensity ratio of low frequency band to high frequency band (LF / HF ratio), and the like.

The main frequency bands of VLF, LF, and HF and the distribution of their power spectrum are not fixed, but appear variously according to the respiration and the regulation of the autonomic nervous system for the heart. The size of the HRV in the high frequency region (HF) is related to the parasympathetic activity of the vagus nerve by breathing, and the size of the HRV in the low frequency region affects both the vagus nerve activity and the sympathetic nerve activity. receive. The ratio of the size of the low frequency region / the size of the high frequency region becomes an index reflecting the balance between the activity of the sympathetic nerve and the activity of the parasympathetic nerve.
In general, the main frequency band of a 5-minute heart rate variability (HRV) signal is between 0.04 Hz and 0.4 Hz. FIG. 7 shows an example of the power spectral density (hereinafter referred to as PSD) in the main frequency band of the heart rate variation (HRV) signal.

（式11）
式11で、VLFはVLFでのPSDを表す。
LF(low frequency)のPSDは0.04〜0.15Hzの周波数帯域のPSDであり、血圧の調節及びメカニズムの活動を反映する0.1Hzの附近の相対的な低周波成分であり、交感神経系や副交感神経系の活動を同時に反映する。LFのPSDは式12のように表れる。

（式12）
式12で、LFはLFでのPSDを表す。 The power spectral density (PSD (x)) of the heart rate variability (HRV) signal, that is, PSD (x) is the power spectral density with the frequency x, and x is 0.0 ≦ x ≦ 0.4.
VLF (Very low frequency) PSD is a PSD in the frequency band of 0.0033 to 0.04 Hz, and provides additional information on sympathetic nerves. The PSD of VLF appears as shown in Equation 11.

(Formula 11)
In Equation 11, VLF represents PSD at VLF.
LF (low frequency) PSD is a PSD in the 0.04-0.15 Hz frequency band, a relative low frequency component of 0.1 Hz that reflects blood pressure regulation and mechanism activity, and is sympathetic and parasympathetic. Reflect the activities of the system at the same time. The PSD of LF appears as shown in Equation 12.

(Formula 12)
In Equation 12, LF represents PSD at LF.

（式13）
式13で、HFはHFでのPSDを表す。
5分間全体強度(5-minute total power)(TP)はVLF、LF、HFのPSDを含む5分間のすべてのパワー(power)を意味する。これは基本的な影響の因子である交感神経の活動だけではなく、自律神経系の全体的な活動を反映する。TPは式14のように表す。

（式14）
式14においてVLF、LF、HFはVLF、LF、HFのPSDを表す。すなわち、5分間の全体強度(TP)は周波数xが0.0033≦x≦0.4であるパワースペクトル密度(PSD)である。 HF (High frequency) PSD is a PSD with a frequency band of 0.15-0.4 Hz, and this frequency band is a respiratory band, i.e. a relative high frequency associated with respiratory activity. It is an ingredient. The PSD of HF is an index for the activity of the parasympathetic nervous system (vagus nerve). The PSD of HF appears in Equation 13.

(Formula 13)
In Equation 13, HF represents PSD at HF.
5-minute total power (TP) means all power for 5 minutes including PSD of VLF, LF and HF. This reflects the overall activity of the autonomic nervous system, not just the sympathetic activity, which is a fundamental factor of influence. TP is expressed as in Equation 14.

(Formula 14)
In Expression 14, VLF, LF, and HF represent PSDs of VLF, LF, and HF. That is, the total intensity (TP) for 5 minutes is the power spectral density (PSD) where the frequency x is 0.0033 ≦ x ≦ 0.4.

（式15）
式15でLF、HFはLF、HFのPSDを表す。
高周波数帯域の正規化した強度(normalized HF)(HFnorm)はLFのPSDとHFのPSDとを合わせた値でHFのPSDを正規化したものである。高周波数帯域の正規化した強度(HFnorm)は式16のように表れる。

（式16）
式16でLF、HFはLF、HFのPSDを表す。 The normalized intensity (LFnorm) of the low frequency band is obtained by normalizing the PSD of the LF with a value obtained by combining the PSD of the LF and the PSD of the HF. The normalized intensity (LFnorm) of the low frequency band is expressed as in Equation 15.

(Formula 15)
In Equation 15, LF and HF represent PSD of LF and HF.
The normalized intensity (HFnorm) of the high frequency band is a value obtained by normalizing the PSD of the HF by a value obtained by combining the PSD of the LF and the PSD of the HF. The normalized intensity (HFnorm) of the high frequency band is expressed as in Equation 16.

(Formula 16)
In Equation 16, LF and HF represent PSD of LF and HF.

（式17）
式17でLFnormは低周波数帯域の正規化した強度であり、HFnormは高周波数帯域の正規化した強度であり、Ratioは低周波数対高周波数の帯域強度比を表す。 The degree of regulation and balance of the two systems of the autonomic nervous system can be understood from the normalized intensity (LFnorm) in the low frequency band and the normalized intensity (HFnorm) in the high frequency band.
The low-frequency to high-frequency band intensity ratio (LF / HF) is the ratio between LF and HF, and the low-frequency to high-frequency band intensity ratio (Ratio) is between the sympathetic and parasympathetic nerves. Reflects the overall equilibrium. The low frequency to high frequency band intensity ratio (LF / HF ratio) is proportional to the sympathetic activity and inversely proportional to the parasympathetic activity. The band intensity ratio (Ratio) between the low frequency and the high frequency is expressed as Equation 17.

(Formula 17)
In Equation 17, LFnorm is the normalized intensity of the low frequency band, HFnorm is the normalized intensity of the high frequency band, and Ratio represents the band intensity ratio of the low frequency to the high frequency.

（式18） The emotional state (ES) and the mental stress index (MSI) are the low-frequency to high-frequency band intensity ratio (LF / HF ratio). It will be like 18.

(Formula 18)

  FIG. 8 is a block diagram for explaining the configuration of the frequency analysis unit in FIG. 2; FFT calculation processing unit (3100), TP calculation unit (3200), VLF calculation unit (3300), LF calculation unit (3400), HF A calculation unit (3500), a normalization calculation unit (3600), an intensity ratio calculation unit (3700), and first to sixth frequency buffer units (3250, 3350, 3450, 3550, 3650, 3750) are included.

The FFT processing unit (3100) is a signal received through the first time buffer unit (2150) from the dynamic noise removal unit (2100) of the time analysis unit (2000), that is, the dynamic noise removal unit of the time analysis unit (2000). The FFT is obtained from the electrocardiogram signal obtained by removing the dynamic noise from (2100) and replacing the portion where the dynamic noise is present with clean data without the dynamic noise.
The TP calculation unit (3200) uses the output signal of the FFT calculation processing unit (3100) to obtain the total intensity (TP) for 5 minutes, that is, the total PSD for 5 minutes.
The VLF calculation unit (3300) obtains a PSD in the frequency band of 0.0033 to 0.04 Hz by Expression 11 using the output signal of the FFT calculation processing unit (3100).
The LF calculation unit (3400) obtains a PSD in the frequency band of 0.04 to 0.15 Hz by Expression 12 using the output signal of the FFT calculation processing unit (3100).
The HF calculation unit (3500) obtains a PSD in the frequency band of 0.15 to 0.4 Hz by Expression 13 using the output signal of the FFT calculation processing unit (3100).
The normalization calculation unit (3600) uses the output signals of the LF calculation unit (3400) and the HF calculation unit (3500) to normalize the low frequency band (LFnorm) and the high frequency band according to Equations 15 and 16. Obtain normalized intensity (HFnorm).
The intensity ratio calculation unit (3700) uses the output signal of the normalization calculation unit (3600) to calculate the band intensity ratio (LF / HF ratio) (Ratio) of low frequency (LF) to high frequency (HF) using Equation 17. Ask. The low-frequency (LF) to high-frequency (HF) band intensity ratio (LF / HF ratio) (Ratio) corresponds to emotional state (ES) and mental stress index (MSI).

  The first to sixth frequency buffer units (3250, 3350, 3450, 3550, 3650, 3750) are TP calculation unit (3200), VLF calculation unit (3300), LF calculation unit (3400), HF calculation unit (3500), The output signals of the normalization calculation unit (3600) and the intensity ratio calculation unit (3700) are buffered and transmitted to the parameter unit (4000).

Next, the reference value database constructed in the present invention will be described.
The reference value database (5000) is a database relating to normal ranges according to sex and age obtained based on clinical data of about 5,000 normal people.
FIG. 9 is an example of the average heart rate according to the age of Korean boys, and FIG. 10 is an example of the average heart rate according to the age of Korean girls.

From Fig. 9, the equation of the fitting line for the average heart rate of Korean boys was obtained as shown in Equation 19. At this time, the standard deviation is about ± 11.

y = -0.1x + 78.1 (Formula 19)

Here, y represents the average heart rate and x represents the age. Therefore, the database stores a coefficient of -0.1, an intercept of 78.1, and a standard deviation of ± 11 for the average heart rate of an oriental man.

From Fig. 10, the equation of the fitting line with respect to the average heart rate of Korean girls is obtained as shown in Equation 20. At this time, the standard deviation is about ± 10.

y = -0.16x + 81.1 (Formula 20)

Here, y represents the average heart rate and x represents the age. Thus, the database stores a coefficient of -0.16 for the average heart rate of Oriental girls, 81.1 for the intercept, and ± 10 for the standard deviation.
That is, FIG. 9 and FIG. 10 are examples of graphs in which statistical work has been performed to construct a reference value database. Other parameters were also obtained by the same method, and a reference range was obtained through the fitting line of the graph.

The parameter analysis unit (4000) determines whether it is within the reference range based on the database (5000). The reference value database (5000) constructed in the present invention is a database suitable for Oriental people including Korea and Japan.
That is, in the present invention, the reference range of each parameter can be expressed as shown in Equation 21.

y _max = Ax + B + C
y _min = Ax + B-C (Formula 21)

Here, y _max represents the maximum reference value of the parameter, y _min represents the minimum reference value of the parameter, and y _max and y _min are greater than zero. X represents age, and C represents standard deviation. A, B, and C are values that vary depending on gender and parameters, and are already stored in the database. A corresponds to the coefficient of the parameter. B is the intercept of that parameter. That is, when the value of each parameter is within the maximum reference value and the minimum reference value of the parameter, the parameter is determined to be within the reference range.

FIG. 11 is a block diagram for explaining the configuration of the parameter analysis unit in FIG. 2, an average heart rate analysis unit (4100), an SDNN analysis unit (4150), an RMSSD analysis unit (4200), and an SRD analysis unit (4250). , PI analyzer (4300), TP analyzer (4400), VLF analyzer (4450), LF analyzer (4500), HF analyzer (4550), normalized LF analyzer (4600), normalized HF An analysis unit (4650) and an intensity ratio analysis unit (4700) are provided. In the following, the mathematics related to frequency analysis is displayed on a log scale.
The parameter analyzer (4000) receives the average heart rate, SDNN, RMSSD, SRD, PI, and APEN from the time analyzer (2000), and the TP, VLF intensity (PSD), and LF from the frequency analyzer (3000). Receives strength (PSD), HF strength (PSD), normalized LF strength, normalized HF strength, and LF to HF band strength ratio. In addition, the sex and age of the subject are received from the data input unit (5500). Based on the gender of the subject, reference data composed of coefficients, intercepts, standard deviations, etc. corresponding to the respective parameters is read from the database (5000), and the maximum reference value and the minimum reference value of each parameter are obtained by Equation 21. Then, each parameter received from the time analysis unit (2000) or the frequency analysis unit (3000) is compared with the maximum reference value and the minimum reference value of each parameter.

The average heart rate analysis unit (4100) receives the average heart rate from the time analysis unit (2000), and receives the sex and age of the subject from the data input unit (5500). The maximum reference value and the minimum reference value of the average heart rate are obtained by Expression 21 from predetermined average heart rate reference data read from the database (5500) according to the sex of the subject. Then, the average heart rate received from the time analysis unit (2000) is compared with the maximum reference value and the minimum reference value of the average heart rate. That is, the average heart rate analysis unit (4100) has an average heart rate received from the time analysis unit (2000) that is greater than or equal to the minimum reference value of the average heart rate and less than or equal to the maximum reference value of the average heart rate. (Minimum reference value of average heart rate ≦ average heart rate ≦ maximum reference value of average heart rate). In the present invention, when the subject's gender input from the data input unit (5500) is a male, the predetermined average heart rate reference data read from the database (5500) has a coefficient of -0.1, an intercept of 78.1, a standard The deviation is 11, so the maximum reference value and the minimum reference value of the average heart rate of boys are as shown in Equation 22. And in the present invention, when the gender of the subject input from the data input unit (5500) is a girl, the predetermined average heart rate reference data read from the database (5500) has a coefficient of -0.16, an intercept of 81.1, The standard deviation is 10. Therefore, the maximum reference value and the minimum reference value of the average heart rate of the girl are as shown in Equation 23.

y _max = -0.1x + 78.1 + 11 = -0.1x + 89.1
y _min = -0.1x + 78.1-11 = -0.1x + 67.1 (Formula 22)

y _max = -0.16x + 81.1 + 10 = -0.16x + 91.1
y _min = -0.16x + 81.1-10 = -0.16x + 71.1 (Formula 23)

Here, y _max is the maximum reference value of average heart rate, y _min is the minimum reference value of average heart rate, and x is age. The unit of y _max and y _min is bpm (bit / minute).

The SDNN analysis unit (4150) receives the SDNN from the time analysis unit (2000), and receives the sex and age of the subject from the data input unit (5500). The maximum reference value and the minimum reference value of SDNN are obtained from the predetermined SDNN reference data read from the database (5500) according to the sex of the subject, using Equation 21. Then, the SDNN received from the time analysis unit (2000) is compared with the maximum reference value and the minimum reference value of the SDNN. That is, the SDNN analysis unit (4150) compares whether the SDNN received from the time analysis unit (2000) is smaller than or equal to the SDNN maximum reference value and greater than or equal to the SDNN minimum reference value (SDNN minimum Reference value ≤ SDNN ≤ SDNN maximum reference value). In the present invention, when the sex of the subject input from the data input unit (5500) is a boy, the predetermined SDNN reference data read in the database (5500) has a coefficient of -0.52, an intercept of 60.4, and a standard deviation of 20. Therefore, the maximum reference value and the minimum reference value of the boy's SDNN are as shown in Equation 24. And in the present invention, when the gender of the subject input from the data input unit (5500) is a girl, the predetermined SDNN reference data read in the database (5500) has a coefficient of -0.44, an intercept of 55, a standard deviation Is 16.1, so the maximum and minimum reference values of SDNN for girls are as shown in Equation 25.

y _max = -0.52x + 60.4 + 20 = -0.52x + 80.4
y _min = -0.52x + 60.4-20 = -0.52x + 40.4 (Formula 24)

y _max = -0.44x + 55 + 16.1 = -0.44x + 71.1
y _min = -0.44x + 55-16.1 = -0.44x + 38.9 (Formula 25)

Here, y _max is the maximum standard value of SDNN, y _min is the minimum standard value of SDNN, and x is age. When y _max and y _min obtained by Expression 24 and Expression 25 are smaller than 0, the value is set to 0.

The parameter SDNN is an index representing heart rate variability (HRV), which means how much difference each normal RR interval (NN interval) represents from the average, so when SDNN is large Means that the heart rate variability signal is so irregular, on the other hand, the small SDNN means that the heart rate variability signal is so monotonous.
The RMSSD analysis unit (4200) receives the RMSSD from the time analysis unit (2000), and receives the sex and age of the subject from the data input unit (5500). The maximum reference value and the minimum reference value of RMSSD are obtained from the predetermined RMSSD reference data read from the database (5500) according to the gender of the subject, using Equation 21. The RMSSD received from the time analysis unit (2000) is compared with the maximum reference value and the minimum reference value of the RMSSD. That is, the RMSSD analysis unit (4200) compares whether the RMSSD received from the time analysis unit (2000) is smaller than or equal to the RMSSD maximum reference value and greater than or equal to the RMSSD minimum reference value (RMSSD minimum Reference value ≤ RMSSD ≤ RMSSD maximum reference value). In the present invention, when the gender of the subject input from the data input unit (5500) is a boy, the predetermined RMSSD reference data read in the database (5500) has a coefficient of -0.35, an intercept of 41.5, and a standard deviation of Therefore, the maximum reference value and minimum reference value of the boy's RMSSD are as shown in Equation 26. In the present invention, when the gender of the subject input from the data input unit (5500) is a girl, the predetermined RMSSD reference data read from the database (5500) has a coefficient of -0.35, an intercept of 43.2, and a standard deviation of 15.7. Therefore, the maximum reference value and the minimum reference value of RMSSD for girls are as shown in Equation 27.

y _max = -0.35x + 41.5 + 15.4 = -0.35x + 56.9
y _min = -0.35x + 41.5-15.4 = -0.35x + 26.1 (Formula 26)

y _max = -0.35x + 43.2 + 15.7 = -0.35x + 58.9
y _min = -0.35x + 43.2-15.7 = -0.35x + 27.5 (Formula 27)

Here, y _max is the maximum standard value of RMSSD, y _min is the minimum standard value of RMSSD, and x is age. When y _max and y _min obtained by the equations 26 and 27 are smaller than 0, the values (y _max , y _min ) are set to 0. The mean square root (RMSSD) of the squared difference between adjacent RR intervals is a variable used when trying to evaluate parasympathetic nerve activity among the autonomic nerves involved in the heart.

The SRD analysis unit (4250) receives the SRD from the time analysis unit (2000), and receives the sex and age of the subject from the data input unit (5500). The maximum reference value and the minimum reference value of the SRD are obtained from the predetermined SRD reference data read from the database (5500) according to the sex of the subject, using Equation 21. Then, the SRD received from the time analysis unit (2000) is compared with the maximum reference value and the minimum reference value of the SRD. That is, the SRD analysis unit (4250) compares whether the SRD received from the time analysis unit (2000) is smaller than or equal to the SRD maximum reference value and greater than or equal to the SRD minimum reference value (SRD minimum Reference value ≤ SRD ≤ SRD maximum reference value). In the present invention, when the sex of the subject input from the data input unit (5500) is a boy, the predetermined SRD reference data read from the database (5500) has a coefficient of 0.0009, an intercept of 0.92, and a standard deviation of 0.13. Therefore, the maximum reference value and the minimum reference value of the boy's SRD are as shown in Equation 28. In the present invention, when the sex of the subject input from the data input unit (5500) is a girl, the predetermined SRD reference data read from the database (5500) has a coefficient of 0.0013, an intercept of 0.9, and a standard deviation of 0.11. Therefore, the maximum reference value and the minimum reference value of SRD for girls are as shown in Equation 29.

y _max = 0.0009x + 0.92 + 0.13 = 0.0009x + 1.05
y _min = 0.0009x + 0.92-0.13 = 0.0009x + 0.79 (Formula 28)

y _max = 0.0013x + 0.9 + 0.11 = 0.0013x + 1.01
y _min = 0.0013x + 0.9-0.11 = 0.0013x + 0.79 (Formula 29)

Here, y _max is the maximum reference value of SRD, y _min is the minimum reference value of SRD, and x is age.

The PI analysis unit (4300) receives the PI from the time analysis unit (2000) and receives the sex and age of the subject from the data input unit (5500). The maximum reference value and the minimum reference value of PI are obtained from the predetermined PI reference data read from the database (5500) according to the sex of the subject, using Equation 21. Then, the PI received from the time analysis unit (2000) is compared with the maximum reference value and the minimum reference value of the PI. That is, the PI analysis unit (4300) compares whether the PI received from the time analysis unit (2000) is smaller than or equal to the PI maximum reference value and greater than or equal to the PI minimum reference value (PI minimum Reference value ≤ PI ≤ PI maximum reference value). When the gender of the subject input from the data input unit (5500) in the present invention is a boy, the predetermined PI reference data read in the database (5500) has a coefficient of 1.88, an intercept of -13.1, and a standard deviation of 27. Therefore, the maximum reference value and the minimum reference value of the boy's PI are as shown in Equation 30. In the present invention, when the gender of the subject input from the data input unit (5500) is a girl, the predetermined PI reference data read in the database (5500) has a coefficient of 1.54, an intercept of -0.3, and a standard deviation of 30. Therefore, the maximum reference value and the minimum reference value of PI for girls are as shown in Equation 31.

y _max = 1.88x-13.1 + 27 = 1.88x + 13.9
y _min = 1.88x-13.1-27 = 1.88x-40.1 (Equation 30)

y _max = 1.54x-0.3 + 30 = 1.54x + 29.7
y _min = 1.54x-0.3-30 = 1.54x-30.3 (Formula 31)

Here, y _max is the maximum reference value of PI, y _min is the minimum reference value of PI, and x is age. When y _max and y _min determined by the equations 30 and 31 are smaller than 0, the values (y _max and y _min ) are set to 0.

In general, an increase in HRV does not mean an increase in heart rate, but an increase in the rate of change in heart rate. An increase in HRV means that the heart beat is physiologically irregular and complex, and a decrease in HRV means that the heart beat is regular and constant.
Although not shown in the drawing, the parameter analysis unit (4000) further includes an APEN analysis unit (not shown). The APEN analysis unit receives APEN from the time analysis unit (2000), and receives the sex and age of the subject from the data input unit (5500). The maximum reference value and the minimum reference value of APEN are obtained by Formula 21 from predetermined APEN reference data read from the database (5500) according to the sex of the subject. Then, the APEN received from the time analysis unit (2000) is compared with the maximum reference value and the minimum reference value of the APEN.

The TP analysis unit (4400) receives the TP from the frequency analysis unit (3000), and also receives the sex and age of the subject from the database (5500). The maximum reference value and the minimum reference value of TP are obtained by Expression 21 from predetermined TP reference data read from the database (5500) according to the sex of the subject. Then, the TP received from the frequency analysis unit (3000) is compared with the maximum reference value and the minimum reference value of the TP. That is, the TP analysis unit (4400) determines whether the TP received from the frequency analysis unit (3000) is smaller than or equal to the TP maximum reference value, which is the TP reference range, and greater than or equal to the TP minimum reference value. Compare (TP minimum reference value ≤ TP ≤ TP maximum reference value). When the gender of the subject input from the data input unit (5500) in the present invention is a boy, the predetermined TP reference data read in the database (5500) has a coefficient of -0.031, an intercept of 8, and a standard deviation of 0.93. Therefore, the maximum reference value and the minimum reference value of a boy's TP are as shown in Equation 32. In the present invention, when the sex of the subject input from the data input unit (5500) is a girl, the predetermined TP reference data read in the database (5500) has a coefficient of -0.27, an intercept of 7.75, and a standard deviation of 0.86. Therefore, the maximum reference value and the minimum reference value of TP for girls are as shown in Equation 33.

y _max = -0.031x + 8 + 0.93 = -0.031x + 8.93
y _min = -0.031x + 8-0.93 = -0.031x + 7.07 (Formula 32)

y _max = -0.27x + 7.75 + 0.86 = -0.27x + 8.61
y _min = -0.27x + 7.75-0.86 = -0.27x + 6.89 (Formula 33)

Here, y _max is the maximum reference value of TP, y _min is the minimum reference value of TP, and x is age. Here, the unit of TP is ms ² / Hz.

  The VLF analysis unit (4450) receives the VLF intensity (PSD) from the frequency analysis unit (3000), and also receives the sex and age of the subject from the database (5500). The maximum reference value and the minimum reference value of the VLF intensity are obtained from the reference data of the predetermined VLF intensity read by the database (5500) according to the gender of the subject using Equation 21 Then, the VLF intensity received from the frequency analysis unit (3000) is compared with the maximum reference value and the minimum reference value of the VLF intensity. That is, the VLF analyzer (4450) determines whether the VLF intensity received from the frequency analyzer (3000) is less than or equal to the maximum reference value of the VLF intensity and greater than or equal to the minimum reference value of the VLF intensity. (VLF minimum reference value ≤ VLF ≤ VLF maximum reference value).

The LF analysis unit (4500) receives the LF intensity (PSD) from the frequency analysis unit (3000), and also receives the sex and age of the subject from the database (5500). The maximum reference value and the minimum reference value of the LF intensity are obtained from the reference data of the predetermined LF intensity read from the database (5500) according to the gender of the subject by Expression 21. Then, the LF intensity received from the frequency analysis unit (3000) is compared with the maximum reference value and the minimum reference value of the LF intensity. That is, the LF analysis unit (4500) determines whether the LF intensity received from the frequency analysis unit (3000) is less than or equal to the maximum reference value of the LF intensity and greater than or equal to the minimum reference value of the LF intensity. (LF minimum reference value ≤ LF ≤ LF maximum reference value). When the gender of the subject input from the data input unit (5500) in the present invention is a male, the reference data of the predetermined LF intensity read in the database (5500) has a coefficient of -0.044, an intercept of 7.3, and a standard deviation of Therefore, the maximum reference value and the minimum reference value of the boy's LF intensity are as shown in Expression 34. In the present invention, when the sex of the subject input from the data input unit (5500) is a girl, the reference data of the predetermined LF intensity read in the database (5500) is a coefficient of -0.038, an intercept of 6.75, a standard deviation Is 1.01, and therefore the maximum reference value and the minimum reference value of the LF intensity for girls are as shown in Equation 35.

y _max = -0.044x + 7.3 + 1.08 = -0.044x + 8.38
y _min = -0.044x + 7.3-1.08 = -0.044x + 6.22 (Formula 34)

y _max = -0.038x + 6.75 + 1.01 = -0.038x + 7.76
y _min = -0.038x + 6.75-1.01 = -0.038x + 5.74 (Formula 35)

Here, y _max is the maximum reference value of LF intensity, y _min is the minimum reference value of LF intensity, and x is age. Here, the unit of LF intensity is ms ² / Hz. The intensity of LF reflects the activities of the sympathetic and parasympathetic nervous systems at the same time, but is generally used as an index of sympathetic nervous activity.

The HF analysis unit (4550) compares and analyzes the HF intensity (PSD) received from the frequency analysis unit (3000) and the predetermined HF reference data read by the database (5500). At this time, the HF reference data read by the database (5500) is the HF maximum reference data and the HF minimum reference data. That is, the HF analysis unit (4550) is whether the HF intensity (PSD) received from the frequency analysis unit (3000) is less than or equal to the HF maximum H reference data and greater than or the same as the HF minimum reference data. (HF minimum reference value ≤ HF ≤ HF maximum reference value). In the present invention, when the sex of the subject input from the data input unit (5500) is a male, the reference data of a predetermined HF intensity read in the database (5500) has a coefficient of -0.034, an intercept of 6.23, and a standard deviation of Therefore, the HF maximum reference value and the HF minimum reference value for boys are as shown in Equation 36. In the present invention, when the gender of the subject input from the data input unit (5500) is a girl, the reference data of the predetermined HF intensity read in the database (5500) has a coefficient of -0.035, an intercept of 6.39, and a standard deviation Is 1.16. Therefore, the maximum HF reference value and the minimum HF reference value for girls are as shown in Equation 37.

y _max = -0.034x + 6.23 + 1.19 = -0.034x + 7.42
y _min = -0.034x + 6.23-1.19 = -0.034x + 5.04 (Formula 36)

y _max = -0.035x + 6.39 + 1.16 = -0.035x + 7.55
y _min = -0.035x + 6.39-1.16 = -0.035x + 5.23 (Formula 37)

Here, y _max is the HF maximum reference value, y _min is the HF minimum reference value, and x is the age. Here, the unit of HF intensity is ms ² / Hz.

Since the intensity of HF is an index to the activity of the parasympathetic nervous system (vagus nerve), it is known to be closely related to the electrical stability of the heart. Generally, when HF increases, HRV generally increases.
The normalized LF analysis unit (4600) receives the normalized LF intensity (PSD) from the frequency analysis unit (3000), and also receives the sex and age of the subject from the database (5500). The maximum reference value and the minimum reference value of LF intensity normalized by Equation 21 are obtained from reference data of predetermined normalized LF intensity read by the database (5500) according to the sex of the subject. Then, the normalized LF intensity received from the frequency analysis unit (3000) is compared with the maximum reference value and the minimum reference value of the normalized LF intensity. That is, the normalized LF analysis unit (4600) has the normalized LF intensity received from the frequency analysis unit (3000) is smaller than or equal to the maximum reference value of the normalized LF intensity, and the normalized LF intensity Are compared with each other if they are greater than or equal to the minimum reference value (normalized LF intensity minimum reference value ≦ normalized LF intensity ≦ normalized LF intensity maximum reference value).

  The normalized HF analysis unit (4650) receives the normalized HF intensity (PSD) from the frequency analysis unit (3000), and also receives the sex and age of the subject from the database (5500). The maximum reference value and the minimum reference value of HF intensity normalized by Equation 21 are obtained from reference data of predetermined normalized HF intensity read by the database (5500) according to the sex of the subject. Then, the normalized HF intensity received from the frequency analysis unit (3000) is compared with the maximum reference value and the minimum reference value of the normalized HF intensity. That is, the normalized HF analysis unit (4650) is the normalized HF intensity received from the frequency analysis unit (3000) is smaller than or equal to the maximum reference value of the normalized HF intensity, Are compared with each other if they are greater than or equal to the minimum reference value (normalized HF intensity minimum reference value ≦ normalized HF intensity ≦ normalized HF intensity maximum reference value).

The normalized LF intensity means the ratio of the LF intensity when the sum of the LF intensity and the HF intensity is 100, as shown in Equation 15. The normalized HF intensity means the ratio of the intensity of HF when the sum of the intensity of LF and the intensity of HF is set to 100 as shown in Equation 16. These are important indices to evaluate the balance between sympathetic and parasympathetic nerves along with the LF to HF band intensity ratio.
The intensity ratio analysis unit (4700) receives the intensity ratio of the LF to HF band from the frequency analysis unit (3000), and receives the sex and age of the subject from the database (5500). The maximum reference value and the minimum reference value of the intensity ratio are obtained from the reference data of the predetermined intensity ratio read from the database (5500) according to the gender of the subject by Expression 21.
Then, the intensity ratio received from the frequency analysis unit (3000) is compared with the maximum reference value and the minimum reference value of the intensity ratio. In other words, the intensity ratio analysis unit (4700) determines whether the intensity ratio received from the frequency analysis unit (3000) is less than or equal to the maximum reference value of the intensity ratio and greater than or equal to the minimum reference value of the intensity ratio. Compare the values (minimum standard value of intensity ratio ≤ intensity ratio ≤ maximum standard value of intensity ratio). In the present invention, when the sex of the subject input from the data input unit (5500) is a male, the reference data of the predetermined intensity ratio read in the database (5500) has a coefficient of -0.015, an intercept of 3.57, and a standard deviation of Therefore, the maximum reference value and the minimum reference value of the boy's intensity ratio are as shown in Equation 38. In the present invention, when the sex of the subject input from the data input unit (5500) is a girl, the reference data of the predetermined intensity ratio read in the database (5500) is a coefficient of -0.003, an intercept of 2.04, a standard deviation Is 2.07. Therefore, the maximum reference value and the minimum reference value of the intensity ratio of the girls are as shown in Equation 39.

y _max = -0.015x + 3.57 + 2.0 = -0.015x + 5.57
y _min = -0.015x + 3.57-2.0 = -0.015x + 1.57 (Formula 38)

y _max = -0.003x + 2.04 + 2.07 = -0.003x + 4.11
y _min = -0.003x + 2.04-2.07 = -0.003x -0.03 (Formula 39)

Here, y _max is the maximum reference value of the intensity ratio, y _min is the minimum reference value of the intensity ratio, and x is the age. When y _min obtained by Equation 38 or Equation 39 is smaller than 0, the value is set to 0.

The emotional state (Emotional State) and the mental stress index (MSI) are obtained by the frequency analysis unit (3000) according to Equation 18, that is, the band intensity ratio of LF to HF. Therefore, the intensity ratio analysis unit (4700) analyzes the emotional state (Emotional State) and the mental stress index (MSI).
Since the band intensity ratio of LF to HF means the ratio between LF and HF, this reflects the balance between sympathetic and parasympathetic nerves, that is, the overall balance of autonomic nerves. In some cases, the band intensity ratio of LF to HF may be used as an index for sympathetic activity. The LF to HF band intensity ratio is proportional to sympathetic activity and inversely proportional to parasympathetic activity.

FIG. 12 is an example in which the stress index is displayed in the analysis result display section of FIG.
The stress index is displayed on the screen of the analysis result display section (6000), and the pressure index (PI) (Pressure Index) indicates the physical stress index (PSI), and the band strength of LF vs. HF The ratio represents emotional state (Emotional State), mental stress index (MSI).

  The present invention is not limited by what has been described above and illustrated in the drawings, but it will be appreciated by those skilled in the art that many more modifications and variations are possible within the scope of the following claims. .

FIG. 1a is an example of a heart rate change of a normal person. FIG. 1b is an example of heart rate changes in a sick person. FIG. 2 is a block diagram for schematically explaining the configuration of an autonomic nerve testing apparatus according to a preferred embodiment of the present invention. FIG. 3 is a block diagram for explaining the signal detection unit of FIG. FIG. 4 is a block diagram for explaining the configuration of the peak detection unit of FIG. FIG. 5 is a procedure diagram for explaining the peak detection unit of FIG. FIG. 6 is a block diagram for explaining the configuration of the time analysis unit of FIG. FIG. 7 is an example of the power spectral density (PSD) in the main frequency band of the heart rate variation (HRV) signal. FIG. 8 is a block diagram for explaining the configuration of the frequency analysis unit of FIG. Fig. 9 shows an example of average heart rate according to the age of Korean boys. Fig. 10 shows an example of the average heart rate according to the age of Korean girls. FIG. 11 is a block diagram for explaining the configuration of the parameter analysis unit of FIG. FIG. 12 is an example in which the stress index is displayed on the analysis result display section of FIG.

Explanation of symbols

100 ECG signal detector
110 ECG electrodes
130 Amplifier
160 Filter section
500 PPG signal detector
510 optical sensor
530 amplifier
560 Filter section
1000 Signal detector
1300 A / D converter
1600 Peak detector
1610 Noise reduction unit
1620 R point detector
1630 RR interval detector
1640 Heart rate calculator
1650 buffer
1660 Buffer section
2000 Time Analysis Department
2100 Dynamic noise canceller
2150 1st time buffer
2050 Time calculation processing section
2200 Average heart rate calculator
2250 Second time buffer
2300 SDNN calculation unit
2350 3rd time buffer
2400 RMSSD calculator
2450 4th time buffer
2500 SRD operation part
2550 5th time buffer
2600 PI calculator
2650 6th time buffer
2700 hour buffer section
3000 Frequency analyzer
3100 FFT processor
3200 TP calculator
3250 1st frequency buffer
3300 VLF calculator
3350 Second frequency buffer
3400 LF calculation unit
3450 Third frequency buffer
3500 HF calculator
3550 4th frequency buffer
3600 Normalization operation part
3650 5th frequency buffer
3700 intensity ratio calculator
3750 6th frequency buffer
4000 Parameter analysis section
4100 Average heart rate analyzer
4150 SDNN Analysis Department
4200 RMSSD analyzer
4250 SRD analyzer
4300 PI analyzer
4400 TP analyzer
4450 VLF analyzer
4500 LF analyzer
4550 HF analyzer
4600 Normalized LF analyzer
4650 Normalized HF analyzer
4700 intensity ratio analyzer
5000 standard value database
5500 Data input section
6000 analysis result display

Claims (33)

A signal detector for detecting an electrocardiogram signal or an oxygen saturation signal;
An A / D converter that converts the output signal of the signal detection unit with a digital signal;
Removing the dynamic noise from the output signal of the A / D converter, a peak detection unit for detecting the peak signal and the peak signal interval of the waveform ,
A time analysis unit for obtaining a parameter on a time domain from an output signal of the peak detection unit;
A frequency analysis unit for obtaining a parameter on the frequency domain from the output signal of the peak detection unit;
A data input unit for temporarily storing patient information including gender and age; and
A database for storing data for setting the reference range by gender, age and parameters of Orientals;
In an autonomic nerve test apparatus comprising a parameter analysis unit that compares whether the parameter output from the time analysis unit or the frequency analysis unit is within the reference range ,
Including at least the compression index (PI) as a parameter on the time domain,
The parameter analysis unit includes at least a PI analysis unit that compares whether the compression index (PI) received from the time analysis unit is smaller than or equal to the PI maximum reference value, greater than or equal to the PI minimum reference value. An autonomic nerve examination apparatus characterized by comprising . Including at least mean heart rate (mean HRT) as a parameter on the time domain,
The parameter analysis unit determines whether the average heart rate received from the time analysis unit is less than or equal to the maximum reference value of the average heart rate and greater than or equal to the minimum reference value of the average heart rate. The autonomic nerve examination apparatus according to claim 1, further comprising at least an average heart rate analysis unit to be compared. In the average heart rate analysis unit,
When the gender of the subject input from the data input unit is a boy,
The maximum reference value (y _max ) of the average heart rate is
y _max = -0.1x + 89.1
(Where y _max is the maximum reference value for average heart rate and x is age)
As required by
The minimum reference value for the average heart rate (y _min ) is
y _min = -0.1x + 67.1
(Where y _min is the minimum reference value for average heart rate and x is age)
The autonomic nerve test apparatus according to claim 2, wherein the autonomic nerve test apparatus is obtained by: In the average heart rate analysis unit,
When the gender of the subject input from the data input unit is a girl,
The maximum reference value (y _max ) of the average heart rate is
y _max = -0.16x + 91.1
(Where y _max is the maximum reference value for average heart rate and x is age)
As required by
The minimum reference value for the average heart rate (y _min ) is
y _min = -0.16x + 71.1
(Where y _min is the minimum reference value for average heart rate and x is age)
The autonomic nerve test apparatus according to claim 2, wherein the autonomic nerve test apparatus is obtained by: Including at least the standard deviation (SDNN) of the overall RR interval as a parameter on the time domain,
The parameter analysis unit determines whether the standard deviation (SDNN) of the entire RR interval received from the time analysis unit is smaller than or equal to the SDNN maximum reference value and greater than or equal to the SDNN minimum reference value. The autonomic nerve test apparatus according to claim 1, further comprising at least an SDNN analysis unit for comparing the two. In the SDNN analysis section,
When the gender of the subject input from the data input unit is a boy,
The SDNN maximum reference value (y _max ) is
y _max = -0.52x + 80.4
(However, y _max is the SDNN maximum reference value, x is the age, to 0 to y _max when the y _max small Ku consisting 0)
As required by
The SDNN minimum reference value (y _min ) is
y _min = -0.52x + 40.4
(However, y _min is SDNN minimum reference value, x is the age, to 0 to y _min when the y _min small Ku consisting 0)
The autonomic nerve test apparatus according to claim 5, wherein the autonomic nerve test apparatus is obtained by: In the SDNN analysis section,
When the gender of the subject input from the data input unit is a girl,
The SDNN maximum reference value (y _max ) is
y _max = -0.44x + 71.1
(However, y _max is the SDNN maximum reference value, x is the age, to 0 to y _max when the y _max small Ku consisting 0)
As required by
The SDNN minimum reference value (y _min ) is
y _min = -0.44x + 38.9
(However, y _min is SDNN minimum reference value, x is the age, to 0 to y _min when the y _min small Ku consisting 0)
The autonomic nerve test apparatus according to claim 5, wherein the autonomic nerve test apparatus is obtained by: Including at least the mean square root (RMSSD) of the squared difference of adjacent RR intervals as a parameter on the time domain,
The parameter analysis unit has an average square root (RMSSD) of a value obtained by squaring the difference between adjacent RR intervals received from the time analysis unit, which is smaller than or equal to the RMSSD maximum reference value, and less than the RMSSD minimum reference value. The autonomic nerve test apparatus according to claim 1, further comprising at least an RMSSD analysis unit that compares whether they are large or the same. In the RMSSD analysis section,
When the gender of the subject input from the data input unit is a boy,
The RMSSD maximum reference value (y _max ) is
y _max = -0.35x + 56.9
(However, y _max is the RMSSD maximum reference value, x is the age, to 0 to y _max when the y _max small Ku consisting 0)
As required by
The RMSSD minimum reference value (y _min ) is
y _min = -0.35x + 26.1
(However, y _min is RMSSD minimum reference value, x is the age, to 0 to y _min when the y _min small Ku consisting 0)
The autonomic nerve test apparatus according to claim 8, wherein the autonomic nerve test apparatus is obtained by: In the RMSSD analysis section,
When the gender of the subject input from the data input unit is a girl,
The RMSSD maximum reference value (y _max ) is
y _max = -0.35x + 58.9
(However, y _max is the RMSSD maximum reference value, x is the age, to 0 to y _max when the y _max small Ku consisting 0)
Sought by
The RMSSD minimum reference value (y _min ) is
y _min = -0.35x + 27.5
(However, y _min is RMSSD minimum reference value, x is the age, to 0 to y _min when the y _min small Ku consisting 0)
The autonomic nerve test apparatus according to claim 8, wherein the autonomic nerve test apparatus is obtained by: Including at least the consecutive RR interval difference (SRD) as a parameter on the time domain,
The parameter analysis unit determines whether the consecutive RR interval difference (SRD) received from the time analysis unit is smaller than or equal to the SRD maximum reference value and greater than or equal to the SRD minimum reference value. The autonomic nerve examination apparatus according to claim 1, further comprising at least an SRD analysis unit to be compared. In the SRD analysis section,
When the gender of the subject input from the data input unit is a boy,
The SRD maximum reference value (y _max ) is
y _max = 0.0009x + 1.05
(Where y _max is the SRD maximum reference value and x is the age)
As required by
The SRD minimum reference value (y _min ) is
y _min = 0.0009x + 0.79
(However, y _min is the SRD minimum reference value and x is the age.)
The autonomic nerve test apparatus according to claim 11, wherein the autonomic nerve test apparatus is obtained by: In the SRD analysis section,
When the gender of the subject input from the data input unit is a girl,
The SRD maximum reference value (y _max ) is
y _max = 0.0013x + 1.01
(Where y _max is the SRD maximum reference value and x is the age)
As required by
The SRD minimum reference value (y _min ) is
y _min = 0.0013x + 0.79
(However, y _min is the SRD minimum reference value and x is the age.)
The autonomic nerve test apparatus according to claim 11, wherein the autonomic nerve test apparatus is obtained by: In the PI analysis section,
When the gender of the subject input from the data input unit is a boy,
The PI maximum reference value (y _max ) is
y _max = 1.88x + 13.9
(Where y _max is the PI maximum reference value and x is the age)
As required by
The PI minimum reference value (y _min ) is
y _min = 1.88x-40.1
(However, y _min is PI minimum reference value, x is the age, to 0 to y _min when the y _min small Ku consisting 0)
The autonomic nerve test apparatus according to claim 1 , wherein the autonomic nerve test apparatus is obtained by: In the PI analysis section,
When the gender of the subject input from the data input unit is a girl,
The PI maximum reference value (y _max ) is
y _max = 1.54x + 29.7
(Where y _max is the PI maximum reference value and x is the age)
As required by
The PI minimum reference value (y _min ) is
y _min = 1.54x-30.3
(However, y _min is PI minimum reference value, x is the age, to 0 to y _min when the y _min small Ku consisting 0)
The autonomic nerve test apparatus according to claim 1, wherein the autonomic nerve test apparatus is obtained by: Including at least 5 minutes total intensity (power spectral density) (TP) as a parameter on the frequency domain,
The parameter analysis unit compares whether the total intensity (TP) for 5 minutes received from the frequency analysis unit is less than or equal to the TP maximum reference value and whether it is greater than or equal to the TP minimum reference value. The autonomic nerve test apparatus according to claim 1, further comprising at least a TP analysis unit. In the TP analysis section,
When the gender of the subject input from the data input unit is a boy,
The TP maximum reference value (y _max ) is
y _max = -0.031x + 8.93
(Where y _max is the TP maximum reference value and x is the age)
As required by
The TP minimum reference value (y _min ) is
y _min = -0.031x + 7.07
(However, y _min is the TP minimum reference value and x is the age)
The autonomic nerve test apparatus according to claim 16, wherein the autonomic nerve test apparatus is obtained by: In the TP analysis section,
When the gender of the subject input from the data input unit is a girl,
The TP maximum reference value (y _max ) is
y _max = -0.27x + 8.61
(Where y _max is the TP maximum reference value and x is the age)
As required by
The TP minimum reference value (y _min ) is
y _min = -0.27x + 6.89
(However, y _min is the TP minimum reference value and x is the age)
The autonomic nerve test apparatus according to claim 16, wherein the autonomic nerve test apparatus is obtained by: Including at least a low frequency band (LF) intensity ( power spectrum ) as a parameter on the frequency domain,
The parameter analysis unit compares whether the low frequency band (LF) intensity received from the frequency analysis unit is smaller than or equal to the LF maximum reference value and greater than or equal to the LF minimum reference value. The autonomic nerve test apparatus according to claim 1, further comprising at least an LF analysis unit. In the LF analysis section,
When the gender of the subject input from the data input unit is a boy,
The LF maximum reference value (y _max ) is
y _max = -0.044x + 8.38
(Where y _max is the LF maximum reference value and x is the age)
As required by
The LF minimum reference value (y _min ) is
y _min = -0.044x + 6.22
(However, y _min is the LF minimum reference value and x is the age)
The autonomic nerve test apparatus according to claim 19, wherein the autonomic nerve test apparatus is obtained by: In the LF analysis unit,
When the gender of the subject input from the data input unit is a girl,
The LF maximum reference value (y _max ) is
y _max = -0.038x + 7.76
(Where y _max is the LF maximum reference value and x is the age)
Sought by
The LF minimum reference value (y _min ) is
y _min = -0.038x + 5.74
(However, y _min is the LF minimum reference value and x is the age)
The autonomic nerve test apparatus according to claim 19, wherein the autonomic nerve test apparatus is obtained by: Including at least the high frequency band (HF) intensity ( power spectrum ) as a parameter on the frequency domain,
In the parameter analysis unit, the high frequency band (HF) intensity (power spectral density) received from the frequency analysis unit is less than or equal to the HF maximum reference value and greater than or the same as the HF minimum reference value. The autonomic nerve examination apparatus according to claim 1, further comprising at least an HF analysis unit for comparing whether or not the In the HF analysis section,
When the gender of the subject input from the data input unit is a boy,
The HF maximum reference value (y _max ) is
y _max = -0.034x + 7.42
(However, y _max is the HF maximum reference value and x is the age)
As required by
The HF minimum reference value (y _min ) is
y _min = -0.034x + 5.04
(However, y _min is the HF minimum reference value and x is the age.)
The autonomic nerve test apparatus according to claim 22, wherein the autonomic nerve test apparatus is obtained by: In the HF analysis section,
When the gender of the subject input from the data input unit is a girl,
The HF maximum reference value (y _max ) is
y _max = -0.035x + 7.55
(However, y _max is the HF maximum reference value and x is the age)
As required by
The HF minimum reference value (y _min ) is
y _min = -0.035x + 5.23
(However, y _min is the HF minimum reference value and x is the age.)
The autonomic nerve test apparatus according to claim 22, wherein the autonomic nerve test apparatus is obtained by: At least including normalized low frequency band (LF) intensity (power spectral density), normalized high frequency band (HF) intensity (power spectral density) as parameters on the frequency domain,
The parameter analysis unit is
The normalized low frequency band (LF) intensity received from the frequency analyzer is less than or equal to the maximum normalized LF intensity reference value and greater than or equal to the normalized normalized LF intensity reference value. A normalized LF analyzer that compares whether there is,
The normalized high frequency band (HF) intensity received from the frequency analyzer is less than or equal to the maximum normalized HF intensity reference value and greater than or equal to the normalized normalized HF intensity reference value. The autonomic nerve inspection apparatus according to claim 1, further comprising: a normalized HF analysis unit that compares whether or not. The normalized LF intensity is a low frequency band (LF) intensity normalized by a combination of the LF intensity and the HF intensity,
26. The autonomic nerve examination apparatus according to claim 25, wherein the normalized HF intensity is obtained by normalizing a high frequency band (HF) intensity with a combination of an LF intensity and an HF intensity. . Including at least a low frequency to high frequency band intensity ratio (LF / HF ratio) as a parameter on the frequency domain,
The parameter analysis unit receives a low-frequency to high-frequency band intensity ratio (LF / HF ratio) received from the frequency analysis unit, which is smaller than or equal to the maximum reference value of the intensity ratio, and has a minimum intensity ratio. The autonomic nerve test apparatus according to claim 1, further comprising at least an intensity ratio analysis unit that compares whether or not the reference value is greater than or equal to the reference value. In the intensity ratio analysis unit,
When the gender of the subject input from the data input unit is a boy,
The maximum reference value (y _max ) of the intensity ratio is
y _max = -0.015x + 5.57
(However, y _max is the maximum reference value of intensity ratio, and x is age)
As required by
The minimum reference value (y _min ) of the intensity ratio is
y _min = -0.015x + 1.57
(However, y _min is the minimum reference value of the intensity ratio, x is the age, to 0 to y _min when the y _min small Ku consisting 0)
The autonomic nerve test apparatus according to claim 27, wherein the autonomic nerve test apparatus is obtained by: In the intensity ratio analysis unit,
When the gender of the subject input from the data input unit is a girl,
The maximum reference value (y _max ) of the intensity ratio is
y _max = -0.003x + 4.11
(However, y _max is the maximum reference value of intensity ratio, and x is age)
As required by
The minimum reference value (y _min ) of the intensity ratio is
y _min = -0.003x-0.03
(However, y _min is the minimum reference value of the intensity ratio, x is the age, to 0 to y _min when the y _min small Ku consisting 0)
The autonomic nerve test apparatus according to claim 27, wherein the autonomic nerve test apparatus is obtained by: The frequency analysis unit includes the emotional state (ES) as a parameter on the frequency domain,
The above emotional state (ES) is

(However, LFnorm is the low frequency band (LF) intensity (PSD) normalized to the combination of the low frequency band (LF) intensity (PSD) and the high frequency band (HF) intensity (PSD). (Low frequency band (LF) intensity (PSD) normalized to low frequency band (LF) intensity (PSD) and high frequency band (HF) intensity (PSD))
The autonomic nerve test apparatus according to claim 1, wherein the autonomic nerve test apparatus is obtained by the following formula. The frequency analysis unit includes a mental stress index (MSI) as a parameter on the frequency domain,
Mental stress index (MSI)

(However, LFnorm is the low frequency band (LF) intensity (PSD) normalized to the combination of the low frequency band (LF) intensity (PSD) and the high frequency band (HF) intensity (PSD). (Low frequency band (LF) intensity (PSD) normalized to low frequency band (LF) intensity (PSD) and high frequency band (HF) intensity (PSD))
The autonomic nerve test apparatus according to claim 1, wherein the autonomic nerve test apparatus is obtained by the following formula. The time analysis part includes the compression index (PI) as a parameter on the time domain,
Pressure index (PI)

(However, VS is the range of RR interval variation, MO is the most probable meaning of RR interval in RR interval data, and MOA is the most frequent RR interval in RR interval data. (The number of average probable meanings, that is, the number of MOs)
The autonomic nerve test apparatus according to claim 1, wherein the autonomic nerve test apparatus is obtained by the following formula. The time analysis part includes the physical stress index (PSI) as a parameter on the time domain,
Physical stress index (PSI) is

(However, VS is the range of RR interval variation, MO is the most probable meaning of RR interval in RR interval data, and MOA is the most frequent RR interval in RR interval data. (The number of average probable meanings, that is, the number of MOs)
The autonomic nerve test apparatus according to claim 1, wherein the autonomic nerve test apparatus is obtained by the following formula.

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