JP2017225808A - Heart rate variability analyzer and heart rate variability detection method using the same - Google Patents

Abstract

PROBLEM TO BE SOLVED: To provide a heart rate variability analyzer for precisely analyzing a frequency region of heart rate variability, and a heart rate variability detection method.SOLUTION: A heart rate variability analyzer includes a converter, an R-peak detection section, a frequency conversion section, and a heart rate variability analysis section. The converter receives an analog electrocardiogram signal and converts it into a digital electrocardiogram signal. The R-peak detection section receives the digital electrocardiogram signal, detects an R-peak value, and generates an RR interval time series signal on the basis of the R-peak value. The frequency conversion section includes a frequency shift part, a low-pass filter, and a fast Fourier transformation part. The frequency shift part extracts a signal of an object frequency band from the RR interval time series signal to generate an object frequency signal. The heart rate variability analysis section generates a heart rate variability signal on the basis of the object frequency signal.SELECTED DRAWING: Figure 3

Description

  The present invention relates to detection and analysis of heart rate variability, and more particularly to a heart rate variability analyzer and a heart rate variability detection method using the same.

  The autonomic nervous system regulates organ function and metabolism of substances, and is involved in the maintenance of life support activities and body homeostasis by achieving an appropriate balance against changes in environmental factors inside and outside the body. The autonomic nervous system is involved in various mental illnesses, physical illnesses, and stressful illnesses. Therefore, environmental stress can be evaluated by analyzing the state of the autonomic nervous system. The analysis of heart rate variability quantitatively evaluates sympathetic and parasympathetic states.

  The analysis method of the heart rate variability includes a time domain analysis method and a frequency domain analysis method. The time domain analysis method is a method of analyzing the heart rate variability based on the time interval of the QRS wave. For example, time domain analysis methods include SDN, NSSAN, NRMSS, DNN50, and pNN50. Although the time domain analysis method is easy to calculate, there is a disadvantage that the activity of the sympathetic nervous system and the parasympathetic nervous system cannot be differentiated or the balance of the autonomic nervous system cannot be quantified.

  On the other hand, the frequency domain analysis method is a method for detecting the characteristics of the heart rate variability for each frequency band and evaluating the power value of the corresponding band. The frequency domain analysis method can quantify and show the balance of the autonomic nervous system related to the sympathetic nerve and the parasympathetic nerve. Therefore, there is a continuous demand for a heart rate variability analyzer and method for analyzing the frequency domain.

  The present invention provides a heart rate variability analyzer capable of precisely analyzing the frequency domain of heart rate variability and a heart rate variability detection method using the same.

  The heart rate variability analyzer according to the embodiment of the present invention includes a converter, an R-peak detector, a frequency converter, and a heart rate variability analyzer.

  The converter receives an analog electrocardiogram signal including a QRS wave and converts it into a digital electrocardiogram signal. The converter generates a digital electrocardiogram signal sampled at a sampling frequency.

  The R-peak detection unit receives a digital electrocardiogram signal, detects an R-peak value, and generates an RR interval time series signal based on the R-peak value.

  The frequency conversion unit extracts a target frequency band signal from the RR interval time-series signal to generate a target frequency signal. The frequency conversion unit includes a frequency shift unit, a low-pass filter, a decimator, a data insertion unit, and a fast Fourier transform unit.

  The frequency shifter generates a shifting detection signal by moving the target frequency band of the RR interval time-series signal to the base band. The frequency shifter generates an I channel signal by applying the first sine signal to the RR interval time series signal, and generates a Q channel signal by applying the second sine signal to the RR interval time series signal. The first sine signal and the second sine signal have a phase difference of 90 degrees, and the frequencies of the first sine signal and the second sine signal are based on the center frequency of the target frequency band. The low-pass filter receives the shifting detection signal and passes the baseband shifting detection signal. The decimator decreases the sampling rate of the shifting detection signal. The data insertion unit inserts zero data into the shifting detection signal.

  The heart rate variability analyzer generates a heart rate variability for the target frequency band based on the target frequency signal. The heart rate variability signal includes a power spectrum signal in the target frequency band. Based on the power spectrum signal, the heart rate variability analyzer is at least one of a high frequency band power value, a low frequency band power value, a very low frequency band power value, and a low frequency band power ratio to the high frequency band. Is calculated.

  The heart rate variability analyzer further includes a band selection unit that provides target frequency information corresponding to the target frequency band mode to the frequency conversion unit. The target frequency band mode includes a high frequency band mode, a low frequency band mode, and an ultra-low frequency band mode.

  A method for detecting a heart rate variability according to an embodiment of the present invention includes a step of receiving an electrocardiogram signal, a step of detecting an R-peak value, a frequency converting step, and a step of calculating and analyzing the heart rate variability signal. . The frequency conversion step includes a step of moving a target frequency band of the RR interval time series signal to a base band, a step of filtering with a low-pass filter, a step of reducing a sampling rate of the RR interval time series signal, and an RR interval time Inserting zero data into the sequence signal; and a fast Fourier transform step.

  The heart rate variability analyzing apparatus and the heart rate variability detecting method using the same according to the embodiment of the present invention can detect and precisely analyze the heart rate variability in the target frequency band.

It is a graph which shows the waveform of an electrocardiogram signal. It is a graph which shows the frequency power spectrum of a heart rate variation signal. 1 is a block diagram of a heart rate variability analyzer according to an embodiment of the present invention. FIG. It is a block diagram of a frequency conversion unit according to an embodiment of the present invention. 5 is a graph showing a process in which the frequency conversion unit of FIG. 4 detects a signal in a target frequency band. 5 is a graph showing a process in which the frequency conversion unit of FIG. 4 detects a signal in a target frequency band. 5 is a graph showing a process in which the frequency conversion unit of FIG. 4 detects a signal in a target frequency band. 5 is a graph showing a process in which the frequency conversion unit of FIG. 4 detects a signal in a target frequency band. It is a block diagram of the heartbeat variation analyzer according to another embodiment of the present invention. FIG. 3 is a flow chart illustrating a heart rate variability detection method according to an embodiment of the present invention. FIG. 6 is a flowchart illustrating steps of converting a frequency according to an embodiment of the present invention.

  Hereinafter, embodiments of the present invention will be described clearly and in detail so that those skilled in the art can easily practice the present invention.

  FIG. 1 is a graph showing a waveform of an electrocardiogram signal.

  An electrocardiogram (ECG) is a graph showing the electrical activity generated from the myocardium by the heartbeat. Referring to FIG. 1, an electrocardiogram signal includes a P wave, a Q wave, an R wave, an S wave, and a T wave. FIG. 1 shows P wave, Q wave, R wave, S wave and T wave by one heart beat, but such a waveform is repeatedly formed.

  P waves are due to atrial contraction. The interval between the P wave and the Q wave corresponds to the time during which the electrical stimulation of the atrium is conducted to the atrioventricular node. In general, the interval between the P wave and the Q wave is formed within 0.2 seconds. The Q wave is a downward wave in which the electrical activity current of the heart decreases. The R wave is an upward wave in which the electrical activity current of the heart increases after the Q wave. The electrocardiogram has a maximum value due to the R wave, and such maximum value is defined as the R-peak value. The S wave is a downward wave in which the electrical activity current of the heart decreases after the R wave. The Q wave, R wave, and S wave are caused by the depolarization process of the ventricular muscle. T waves result from a repolarization process that is restored and relaxed after ventricular contraction due to depolarization. Q waves, R waves, and S waves are defined as QRS waves, and QRS waves are generated by depolarization in which electrical stimulation starting from the sinoatrial node is conducted to the ventricle through the atrioventricular node and contracts the ventricle. Generally, QRS waves are formed between 0.06 seconds and 0.1 seconds.

  The waveform of the electrocardiogram signal in FIG. 1 shows the electrical activity of the heart with respect to time. The heart rate variability analyzer of the present invention detects an R-peak value of a waveform of an electrocardiogram signal, and frequency-converts the waveform of a heart rate tachogram (heart rate tachogram) that continuously indicates an interval between the R-peak values. To analyze the frequency domain of heart rate variability. The specific frequency conversion of the electrocardiogram signal and the generation process of the heart rate variability signal will be described later.

  FIG. 2 is a graph showing the frequency power spectrum of the heart rate variability signal.

Heart rate variability (HRV) refers to fluctuations in the heart rate between beats, and detects the amount of change in the period by measuring the instantaneous period of the heart rate. Heart rate variability reflects sympathetic and parasympathetic interactions.

Referring to FIG. 2, a power spectral density (PSD) with respect to the frequency domain is illustrated as a waveform of the heart rate variability signal. The interval between heartbeats, such as the interval between R-peak values, is measured in units of time, and such a time interval generates a signal for frequency conversion. When calculating the power spectrum, the unit of the signal is squared. Since the analysis of the heart rate variability calculates the power spectrum based on the interval between the R-peak values obtained from the time measurement, the unit of the vertical axis is defined as msec ² units.

  The waveform of the heart rate variability signal is divided into a high frequency band (High frequency band, HF), a low frequency band (Low frequency band, LF), and an extremely low frequency band (Very low frequency band, VLF). The power values of the high frequency band, the low frequency band, and the very low frequency band are used to determine the activity of the sympathetic nervous system or the parasympathetic nervous system.

  A high frequency band (HF) is defined as a frequency band between 0.15 and 0.4 Hz. The high frequency band is used as an index for the activity of the parasympathetic nervous system. The high frequency band is related to the respiratory cycle. The high frequency band is related to the electrical stability of the heart. Therefore, cardiopulmonary activity, cardiac electrical stability, and the like can be determined by analyzing the power value in the high frequency band.

  The low frequency band (LF) is defined as the frequency band between 0.04 and 0.15 Hz. The low frequency band is associated with changes in heart rate due to baroreceptor reflex or blood pressure regulation. The low frequency band is used as an index for the activity of the sympathetic nervous system. For example, when the activity of the sympathetic nervous system is excessively shown like a migraine patient, the fluctuation range of the low frequency band is greatly shown. However, the present invention is not limited to this, and the low frequency band LF is used as an index for the activity of the sympathetic nervous system and the parasympathetic nervous system.

  The very low frequency band (VLF) is defined as a band between 0.003 and 0.04 Hz. The very low frequency band is used as an index for the activity of the sympathetic nervous system. For example, in a patient with sleep apnea syndrome, the sympathetic nerve is stimulated during apnea, and the power value in the very low frequency band increases. The ultra-low frequency band is used as an index for body temperature regulation, hormones, vasomotion, and the like.

  FIG. 3 is a block diagram of a heart rate variability analyzer according to an embodiment of the present invention.

Referring to FIG. 3, the heart rate variability analysis apparatus 1000 includes a converter 100, an R peak detection unit 200, a frequency conversion unit 300, a heart rate variability analysis unit 400, a band selection unit 500, a storage unit 600, and a display unit 700.

  The converter 100 receives an analog signal and converts it into a digital signal. The converter 100 receives an analog electrocardiogram signal (ECGT) and converts it into a digital electrocardiogram signal (ECGn). The converter 100 is connected to an electrocardiogram sensor (not shown), and the electrocardiogram sensor that senses the user's electrocardiogram provides the converter 100 with an analog electrocardiogram signal. The analog ECG signal is converted to a digital ECG signal using the converter 100 during a specified time. The digital electrocardiogram signal is a discrete signal.

  The converter 100 receives the sampling signal (fs). The sampling signal includes information regarding the sampling frequency of the electrocardiogram signal. The sampling frequency value is formed between 200 and 500 Hz, but is not limited thereto. The converter 100 determines the data amount of the converted digital electrocardiogram signal based on the sampling signal. If the frequency value of the sampling signal is large, a digital electrocardiogram signal having high stability is generated, and if the frequency value of the sampling signal is small, a digital electrocardiogram signal having small data is generated.

  The R-peak detection unit 200 receives a digital electrocardiogram signal from the converter 100. The R-peak detection unit 200 detects an R-peak value from the digital electrocardiogram signal. The R-peak detection unit 200 includes a QRS wave detection algorithm for detecting an R-peak value. For example, the R-peak detection unit 200 includes a Pan & Topkins algorithm or a Hamilton & Topkins algorithm. The R-peak detection unit 200 detects a plurality of R waves existing during the measurement time through the QRS wave detection algorithm, and sequentially detects R-peak values that are peak values of the R waves.

  The R-peak detection unit 200 generates an RR interval time series signal (RPn) based on sequentially detected R-peak values. The R-peak detection unit 200 calculates an RR interval (P-peak to R-peak Interval, RRI) that is an interval between R-peak values that are sequentially detected over time. The R-peak detection unit 200 interpolates the RR interval (RRI) to generate an RR interval time series signal corresponding to the RRI tachogram (Tacogram). For example, the R-peak detection unit 200 may convert a geometric pattern such as a sample density distribution of a duration of an RR interval or a sample density distribution of an adjacent RR interval difference based on continuous information of the RR interval. An RR interval time series signal is generated through interpolation.

  The frequency conversion unit 300 receives the RR sensation time series signal from the R-peak detection unit 200. The frequency converter 300 extracts the target frequency band (ft) of the RR interval time series signal to generate the target frequency signal (Tf). The frequency conversion unit 300 converts the RR interval time series signal into a frequency series signal using a fast Fourier transform (FFT).

  The frequency conversion unit 300 extracts a signal value corresponding to the target frequency band of the RR interval time series signal before performing the frequency conversion of the RR interval time series signal. In order to extract a signal value corresponding to the target frequency band, the frequency conversion unit 300 receives frequency band information (fti) from a band selection unit 500 described later.

  The target frequency band means a frequency band to be analyzed in the RR interval time series signal. For example, if the analysis target is a high frequency band, the target frequency band includes a band between 0.15 and 0.4 Hz. If the analysis target is a low frequency band, the target frequency band includes a band between 0.04 and 0.15 Hz. If the analysis target is an ultra-low frequency band, the target frequency band includes a band between 0.003 and 0.04 Hz. The frequency converter 300 generates a target frequency signal based on the target frequency band information. The target frequency signal is a heart rate variability signal corresponding to the frequency domain and corresponding to the target frequency band. A specific configuration of the frequency conversion unit 300 and a process of generating the target frequency signal will be described later.

  The heart rate variability analyzer 400 receives the target frequency signal from the frequency converter 300. The heart rate variability analyzer 400 analyzes the heart rate variability based on the target frequency signal. The heart rate variability analyzer 400 generates a heart rate variability signal (HRV) for the target frequency band based on the target frequency signal. The heart rate variability signal includes a power spectrum signal (PSD) in the target frequency band. The heart rate variability signal is generated by calculating the intensity with respect to the target frequency signal and calculating the power value and the like.

  For example, the heartbeat variation signal is one of a power value in a high frequency band, a power value in a low frequency band, or a power value in a very low frequency band, depending on the target frequency band. As described above, the power value in the high frequency band, the power value in the low frequency band, or the power value in the very low frequency band is used as an index for the activity of the autonomic nervous system.

  The heart rate variability signal includes a power ratio (LF / HF) of a low frequency band to a high frequency band. A high power ratio means that the sympathetic nerve is activated or the parasympathetic nerve activity is suppressed. The power ratio allows the balance between the sympathetic and parasympathetic nervous systems to be quantified and analyzed. The heart rate variability signal is not limited to this, and includes various analysis signals such as a power value of an ultra-low frequency band (Ultra-low frequency band). Based on such various heart rate variability signals, analysis of heart rate variability is performed.

  The band selection unit 500 provides target frequency band information to the frequency conversion unit 300. The target frequency band information includes information regarding the target frequency band or the center frequency (fc) of the target frequency band. The band selection unit 500 provides target frequency band information corresponding to the target frequency band mode to the frequency conversion unit 300 so that the heart rate variation analysis unit 400 generates a heart rate variation signal of the target frequency band.

  The target frequency band mode includes a plurality of frequency band modes. The target frequency band mode includes a high frequency band mode, a low frequency band mode, and an ultra-low frequency band mode, and may include more band modes. The target frequency bands in the respective target frequency band modes are not superimposed on each other. In each target frequency band mode, the band selection unit 500 provides target frequency band information corresponding to each target frequency band to the frequency conversion unit 300.

  In the high frequency band mode, the band selection unit 500 provides the high frequency band information to the frequency conversion unit 300. The frequency converter 300 that has received the high frequency band information generates a target frequency signal for the high frequency band. The heart rate variability analyzer 400 generates a heart rate variability signal for the high frequency band based on the target frequency signal.

  In the low frequency band mode, the band selection unit 500 provides the low frequency band information to the frequency conversion unit 300. The frequency conversion unit 300 that has received the low frequency band information generates a target frequency signal for the low frequency band. The heart rate variability analysis unit 400 generates a heart rate variability signal for the low frequency band based on the target frequency signal.

  In the ultra-low frequency band mode, the band selection unit 500 provides the ultra-low frequency band information to the frequency conversion unit 300. The frequency converter 300 that has received the ultra-low frequency band information generates a target frequency signal for the ultra-low frequency band. The heart rate variability analyzer 400 generates a heart rate variability signal for the very low frequency band based on the target frequency signal.

  The target frequency band mode is changed according to time. For example, the band selection unit 500 operates in the high frequency band mode for a predetermined time to provide target frequency band information regarding the high frequency band, and then changes the target frequency band mode to display the target frequency band information for the low frequency band. provide. Therefore, the frequency conversion unit 300 generates target frequency signals for various frequency bands by changing the mode of the band selection unit 500. In addition, based on this, the heart rate variability analyzer 400 generates various heart rate variability signals and enables multi-dimensional analysis of the heart rate variability.

  The storage unit 600 is used as a storage device for the heart rate variability analysis unit 400. The storage unit 600 receives and stores the heart rate variation signal, the target frequency signal, the target frequency band information, and the like from the heart rate variation analysis unit 400.

  The storage unit 600 includes a ROM (Read Only Memory), a PROM (Programmable ROM), an EPROM (Electrically Programmable ROM), an EEPROM (Electrically Erasable and Programmable ROM), a flash memory device, and a PRAM (PRAM (MRAM), PRAM (PRAM). , Including at least one of non-volatile memory devices such as RRAM (Resistive RAM) or FRAM (Ferroelectric RAM), and volatile such as SRAM (Static RAM), DRAM (Dynamic RAM), or SDRAM (Synchronous DRAM) Memory device Of which contain at least one.

  The display unit 700 receives a heart rate variation signal generated by the heart rate variation analysis unit 400, a target frequency signal generated by the frequency conversion unit 300, or an image signal (IHRV) based on data stored in the storage unit 600. And display.

  The display unit 700 includes at least one of an LCD (Liquid Crystal Display), an OLED (Organic Light Emitting Diode), an AMOLED (Active Matrix OLED), a flexible display, and electronic ink.

  FIG. 4 is a block diagram illustrating the frequency converter 300 according to an embodiment of the present invention. 5 to 8 are graphs for explaining a process in which the frequency conversion unit 300 of FIG. 4 detects a signal in the target frequency band.

  Referring to FIG. 4, the frequency converting unit 300 includes frequency moving units 311 and 312, low-pass filters 312 and 322, decimators 331 and 332, data inserting units 341 and 342, and a fast Fourier transform unit 350. However, unlike FIG. 4, the frequency conversion unit 300 may not include some of the components. For example, the frequency conversion unit 300 may not include the decimators 331 and 332 or may not include the data insertion units 341 and 342.

  The frequency moving units 311 and 312 include a first frequency moving unit 311 and a second frequency moving unit 312. The first frequency moving unit 311 and the second frequency moving unit 312 receive the RR interval time series signal from the R-peak detecting unit 200.

  The first frequency moving unit 311 receives the RR interval time series signal and generates an I (In-phase) channel signal. The first frequency shift unit 311 applies the first sine signal (Ift) to the RR interval time series signal in order to generate an I channel signal. If the RR interval time series signal is a discrete signal for n, the first sine signal is defined as cos (2 * pi * fc * n * ts). The fc of the first sine signal is defined as the center frequency of the target frequency band to be analyzed. The ts of the first sine signal corresponds to the reciprocal of the sampling frequency.

  The second frequency moving unit 312 receives the RR interval time series signal and generates a Q (quadture-phase) channel signal. The second frequency moving unit 312 applies the second sine signal (Qft) to the RR interval time series signal to generate a Q channel signal. If the RR interval time series signal is a discrete signal for n, the second sine signal is defined as -sin (2 * pi * fc * n * ts). The first frequency moving unit 311 and the second frequency moving unit 312 divert the RR interval time series signal into an I channel signal and a Q channel signal. The first frequency moving unit 311 extracts the real part of the RR interval time series signal, and the second frequency moving unit 312 extracts the imaginary part of the RR interval time series signal.

  The frequency converter 300 further includes a shunt (not shown) for generating the first sine signal and the second sine signal to shunt the RR time series signal. The shunt generates a first sine signal and a second sine signal. Since the frequencies of the first sine signal and the second sine signal are based on the target frequency band and the sampling frequency, the shunt receives the target frequency band information from the band selection unit 500 and receives the sampling signal. In contrast, the shunt is provided to the band selection unit 500 to provide the first sine signal and the second sine signal to the first frequency moving unit 311 and the second frequency moving unit 312. Alternatively, the shunt may be provided as a separate component in the heart rate variability analyzer 1000.

  When the first sine signal or the second sine signal is applied to the RR interval time series signal, the RR interval time series signal moves by the center frequency in the frequency domain. That is, the target frequency band moves to the baseband. The first frequency shift unit 311 and the second frequency shift unit 312 shunt the RR interval time series signal into the I channel and Q channel signals, and shift the target frequency band to the base band, respectively, A shifting detection signal is generated by applying the sine signal.

  The first low-pass filter 321 and the second low-pass filter 322 receive the shifting detection signal. The first low pass filter 321 receives the I channel signal, and the second low pass filter 322 receives the Q channel signal. The first low-pass filter 321 and the second low-pass filter 322 pass the baseband shifting detection signal and block the high frequency band shifting detection signal. Therefore, a signal corresponding to the target frequency band can be selectively extracted from the RR interval time series signal. In addition, since the frequency band signal to be analyzed is extracted and the remaining band signals are blocked, unnecessary data can be removed to reduce the amount of data.

  The first low-pass filter 321 and the second low-pass filter 322 convert the cutoff frequency according to the target frequency band mode of the band selection unit 500. For example, the high frequency bandwidth in the high frequency band mode is about 0.25 Hz, the low frequency bandwidth in the low frequency band mode is about 0.11 Hz, and the ultra low frequency band in the ultra low frequency band mode. The width is about 0.04 Hz. Therefore, a cut-off frequency of about 0.125 Hz is required in the high-frequency band mode, a cut-off frequency of about 0.055 Hz is required in the low-frequency band mode, and an ultra-low frequency bandwidth is a cut-off frequency of about 0.02 Hz. Is required. Accordingly, the first low-pass filter 321 and the second low-pass filter 322 receive the target frequency band information from the band selection unit 500 and convert the cutoff frequency. The target frequency band information includes bandwidth information for the target frequency band mode.

  The first decimator 331 receives the shifting detection signal that has passed through the first low-pass filter 321, and the second decimator 332 receives the shifting detection signal that has passed through the second low-pass filter 322. The first decimator 331 and the second decimator 332 decrease the sampling rate of the signal. For example, when the first decimator 331 and the second decimator 332 perform fourth-order decimation, the sampling frequency is decreased by ¼ of the conventional sampling frequency. In this case, the data of the shifting detection signal is reduced by ¼. In addition, the baseband shifting detection signal is shown as a waveform expanded four times with reference to the sampling frequency in the frequency domain. When the first decimator 331 and the second decimator 332 perform M-th order decimation, the frequency resolution is determined based on the M value. When performing M-th order decimation, the frequency resolution is defined as (sampling frequency / M / (number of FFT points)).

  The first decimator 331 and the second decimator 332 receive the magnification signal (MM) and determine the order of decimation. Although not shown, the frequency converter 300 further includes a multiplier that generates a magnification signal and provides the magnification signal to the first decimator 331 and the second decimator 332. Alternatively, the multiplier may be provided as a separate component in the heart rate variability analyzer 1000.

  The first data insertion unit 341 and the second data insertion unit 342 insert zero data into the decimation signal. Data of 0 is inserted between the data of the shifting detection signals. The first data insertion unit 341 and the second data insertion unit 342 are configured such that the number of data when the signals output from the first and second decimators 331 and 332 are directly input to the fast Fourier transform unit 350 is the reference FFT point. If it is smaller than the number, data of 0 is inserted by the difference in the number of data, thereby improving the frequency resolution and improving the precision of the signal.

  The first decimator 331 and the second decimator 332 receive the padding signal (PP) and determine the number of inserted data. Although not shown, the frequency conversion unit 300 further includes a resolution adjuster that generates a padding signal and provides the padding signal to the first data insertion unit 341 and the second data insertion unit 342. Alternatively, the resolution adjuster may be included in the heart rate variability analyzer 1000 as a separate component.

  The first decimator 331 and the second decimator 332 concentrate and observe the RR interval time series signals for the target frequency band, thereby reducing the amount of data. The first data insertion unit 341 and the second data insertion unit 342 insert data in order to improve the frequency resolution of the RR interval time-series signal with respect to the target frequency band and improve the precision. Therefore, the first data insertion unit 341 and the second data insertion unit 342 are removed from the viewpoint of data efficiency and processing speed.

  The fast Fourier transform unit 350 receives a signal in which 0 data is inserted from the first data insertion unit 341 and the second data insertion unit 342. The fast Fourier transform unit 350 transmits the RR interval time series transmitted through the first and second low-pass filters 321 and 322, the first and second decimators 331 and 332, and the first and second data insertion units 341 and 342. Fast Fourier transform the signal. The fast Fourier transform unit 350 includes a fast Fourier transform algorithm that reduces the complex computation of the discrete Fourier transform (Discrete Fourier Transform), and generates a target frequency signal based on the fast Fourier transform algorithm.

  FIG. 5 exemplarily shows signals input to the frequency conversion unit 300. The waveform in FIG. 5 is a graph obtained by frequency-converting a signal input to the frequency converter 300. The user inputs target frequency band information to the frequency conversion unit 300 in order to observe the target frequency band.

  FIG. 6 shows the magnitude of the signal obtained by converting the signal of FIG. 5 by the first frequency moving unit 511 and the second frequency moving unit 512. The first frequency moving unit 511 or the second frequency moving unit 512 applies the first sine signal or the second sine signal to the signal of FIG. 5 to move the signal in the target frequency band in the base band. In the frequency domain, the signal of FIG. 5a moves in the negative direction by the center frequency.

  FIG. 7 shows the magnitude of the signal obtained by converting the signal in FIG. 6 by the first and second low-pass filters 321 and 322. The first and second low-pass filters 321 and 322 have a cutoff frequency value of the target frequency band / 2. The first and second low-pass filters 321 and 322 leave the signal of FIG. 6 by the baseband waveform and remove the remaining waveform.

  FIG. 8 shows the magnitude of the signal obtained by converting the signal of FIG. 7 by the first and second decimators 331 and 332. The first and second decimators 331 and 332 perform M-th order decimation. Decimation reduces the sampling frequency by 1 / M. Therefore, the first and second decimators 331 and 332 focus and observe signals in the target frequency band like the signals in FIG.

  FIG. 9 is a block diagram of a heart rate variability analyzer according to another embodiment of the present invention.

Referring to FIG. 9, the heart rate variability analyzer 2000 includes a converter 2100, an R-peak detector 2200, a first frequency converter 2300a, a second frequency converter 2300b, a third frequency converter 2300c, and a heart rate variability analyzer. 2400. The configurations of converter 2100, R-peak detection unit 2200, and heart rate variability analysis unit 2400 in FIG. 9 correspond to converter 100, R-peak detection unit 200, and heart rate variability analysis unit 400 in FIG. The detailed explanation is omitted.

  The first frequency converter 2300a receives the RR interval time-series signal from the R-peak detector 2200 and outputs the first target frequency signal (Tf1). The first frequency conversion unit 2300a extracts a signal for the first target frequency band (ft1) from the RR interval time series signal. For example, the first target frequency band is a high frequency band.

  The second frequency converter 2300b receives the RR interval time series signal from the R-peak detector 2200 and outputs the second target frequency signal (Tf2). The second frequency converter 2300b extracts a signal for the second target frequency band (ft2) from the RR interval time series signal. For example, the second target frequency band is a low frequency band.

  The third frequency converter 2300c receives the RR interval time series signal from the R-peak detector 2200 and outputs a third target frequency signal (Tf3). The third frequency converter 2300c extracts a signal for the third target frequency band (ft3) from the RR interval time series signal. For example, the third target frequency band is an extremely low frequency band.

  Compared to the heart rate variability analyzer 1000 of FIG. 3, the heart rate variability analyzer 2000 of FIG. 9 includes a plurality of frequency converters. Therefore, heart rate variability signals in various frequency bands can be analyzed simultaneously. For example, the heart rate variability analyzer 2000 simultaneously calculates and analyzes heart rate variability in a high frequency band, a low frequency band, and an ultra-low frequency band. Compared with the heart rate variability analyzer 2000 of FIG. 9, the heart rate variability analyzer 1000 of FIG. 3 analyzes the heart rate variability with a relatively small data capacity.

  FIG. 10 is a flowchart illustrating a heart rate variability detection method S1000 according to another embodiment of the present invention.

  Referring to FIG. 10, the heart rate variability detection method S1000 calculates and analyzes a step S100 for receiving an electrocardiogram signal, a step S200 for detecting an R-peak value, a step S300 for converting a frequency, and a heart rate variability signal. Step S400.

  In step S100 for receiving an electrocardiogram signal, the heartbeat variability detecting device receives an analog electrocardiogram signal from the outside. Receiving the ECG signal S100 includes converting the analog ECG signal into a digital ECG signal. The step S100 for receiving an electrocardiogram signal is performed by the analog-to-digital converters 100 and 2100. In this case, the analog electrocardiogram signal is converted into a digital electrocardiogram signal based on the sampling frequency included in the sampling signal received by the analog-digital converters 100 and 2100.

  In step S200 for detecting the R-peak value, the heartbeat variability detecting device detects the R-peak value of the electrocardiogram signal. Step S200 for detecting the R-peak value is performed by the R-peak detection units 200 and 2200. The step S200 of detecting the R-peak value includes a step of generating an RR interval time series signal based on the R-peak value. The RR interval time series signal is generated by calculating the RR interval based on sequentially detected R-peak values.

  In the frequency conversion number step S300, the heartbeat variability detecting device extracts the target frequency band of the RR time series signal and converts it into the target frequency signal. The frequency conversion step S300 is performed by the frequency conversion unit 300 of FIG. 3 or the first to third frequency conversion units 2300a, 2300b, and 2300c of FIG. Specific contents will be described later.

  In step S400 of calculating and analyzing the heart rate variability signal, the heart rate variability detecting device generates a heart rate variability signal for the target frequency band based on the target frequency signal. Step S400 for calculating and analyzing the heart rate variability signal is performed by the heart rate variability analyzers 400 and 2400. In step S400 for calculating and analyzing the heart rate variability signal, the heart rate variability analyzers 400 and 2400 calculate a power value in a high frequency band, a power value in a low frequency band, or a power value in a very low frequency band, a power ratio, and the like. Analyzes and analyzes activities such as autonomic nervous system to diagnose mental health.

  FIG. 11 is a flowchart showing step S300 for converting the frequency of FIG.

  Referring to FIG. 11, the step S300 for converting the frequency includes a step S310 for diverting the Q channel and the I channel, a step S320 for moving to the base band, a step S330 for filtering with a low-pass filter, and a step S340 for decimation. , Zero padding step S350 and fast Fourier transform step S360. Each step of FIG. 8 is performed by the frequency conversion unit 300 of FIG. 3 or the first to third frequency conversion units 2300a, 2300b, and 2300c of FIG.

  In step S310 for diverting the Q channel and the I channel, the heart rate variability analyzer separates the RR interval time series signal into the I channel corresponding to the real part and the Q channel corresponding to the imaginary part. The step S310 of diverting the Q channel and the I channel includes the step of generating the I channel by applying the first sine signal to the RR interval time series signal and the step of generating the Q channel by applying the second sine signal to the RR interval time series signal. . The step of generating the I channel is performed by the moving unit 311 of the first frequency, and the step of generating the Q channel is performed by the moving unit 312 of the second frequency.

  In step S320 of moving to the base band, the heartbeat variability analyzer moves the target frequency band of the RR interval time series signal to the base band to generate a shifting detection signal. Step S320 of moving to the base band is performed by the first frequency moving unit 311 and the second frequency moving unit 312. In step S320 of moving to the base band, the RR interval time-series signal moves by the center frequency of the target frequency band. In order to move to the baseband, the first sine signal and the second sine signal are sine wave functions, and the frequency of the sine wave function is proportional to the center frequency. The step S310 for diverting the Q channel and the I channel and the step S320 for moving to the base band are simultaneously performed by the first frequency moving unit 311 and the second frequency moving unit 312.

  In step S330 of filtering with a low-pass filter, the heartbeat variability analyzer passes the baseband shifting detection signal and removes the remaining frequency band shifting detection signals. The step S330 of filtering with the low-pass filter is performed by the first and second low-pass filters 312 and 322.

  In decimation step S340, the heart rate variability analyzer reduces the sampling rate of the filtered shifting detection signal. The decimation step S340 is performed by the first and second decimators 331 and 332. In decimation step S340, the amount of data is reduced and the sampling frequency is reduced by the decimation order.

  In step S350 of zero padding, the heart rate variability analyzer inserts zero data into the filtered shifting detection signal. The step S350 of zero padding is performed by the first and second data insertion units 341 and 342. In the step S350 of zero padding, when the data is decreased in the step S340 of decimation, if the number of data input to the fast Fourier transform unit 350 is less than the number of reference FFT points, the first and second data insertion units 341 , 342 insert zero data by the difference in the number of data. In step 350 of zero padding, the amount of data is increased and the frequency resolution is improved.

  In step S360 of performing fast Fourier transform, the heart rate variability analyzer performs fast Fourier transform of the filtered, decimation, and zero-padded shift detection signal from the time domain to the frequency domain. Step S360 for performing the fast Fourier transform is performed by the fast Fourier transform unit 350.

  What has been described above is a specific example for carrying out the present invention. The present invention should include not only the above-described embodiments but also simple design changes and embodiments that can be easily changed. Further, the present invention should include a technique that can be easily modified and implemented using the above-described embodiments.

1000, 2000: Heart rate variability analyzer 100, 2100: Converter 200, 2200: R-peak detector 300, 2300a, 2300b, 2300c: Frequency converter 400, 2400: Heart rate variability analyzer 500: Band selector fs: Sampling signal ft: Target frequency band fc: Center frequency ECGT: Analog ECG signal ECGn: Digital ECG signal RRn: RR interval time series signal Tf: Target frequency signal HRV: Heart rate variability signal

Claims (16)

A converter that receives an analog ECG signal including a QRS wave and converts it into a digital ECG signal;
An R-peak detector that receives the digital electrocardiogram signal, detects an R-peak value, and generates an RR interval time-series signal based on the R-peak value;
A frequency converter that generates a target frequency signal by extracting a signal in a target frequency band from the RR interval time-series signal;
A heart rate variability analyzer that generates a heart rate variability signal for the target frequency band based on the target frequency signal,
The frequency converter is
A frequency shifter that shifts a target frequency band of the RR interval time-series signal to a baseband to generate a shifting detection signal;
A low-pass filter that receives the shifting detection signal and passes the shifting detection signal of the baseband;
And a fast Fourier transform unit that generates a target frequency signal based on the shifting detection signal that has passed through the low-pass filter. The frequency moving unit is
The heart rate variability analyzer according to claim 1, wherein the shift detection signal including an I (In-phase) channel signal and a Q (quadture-phase) channel signal is generated. The frequency moving unit is
A first sine signal is applied to the RR interval time series signal to generate an I channel signal, a second sine signal is applied to the RR interval time series signal to generate a Q channel signal,
The first sine signal and the second sine signal have a phase difference of 90 degrees, and the frequencies of the first sine signal and the second sine signal are based on a center frequency of the target frequency band. Heart rate variability analyzer. The converter is
The heart rate variability analyzer according to claim 1, wherein the digital electrocardiogram signal sampled at a sampling frequency is generated. The frequency converter is
The heart rate variability analyzer according to claim 4, further comprising a decimator that reduces a sampling rate of the shifting detection signal that has passed through the low-pass filter. The frequency converter is
The heart rate variability analyzer according to claim 4, further comprising a data insertion unit that inserts zero data into the shifting detection signal that has passed through the low-pass filter.   The heart rate variability analyzer according to claim 1, further comprising a band selection unit that provides target frequency band information corresponding to a target frequency band mode to the frequency conversion unit. The frequency band mode is
Including high frequency band mode, low frequency band mode, and ultra-low frequency band mode,
The band selection unit includes:
Providing the high frequency band information to the frequency conversion unit in the high frequency band mode; providing the low frequency band information to the frequency conversion unit in the low frequency band mode; The heart rate variability analyzer according to claim 7, wherein frequency band information is provided to the frequency converter. The target frequency band includes a high frequency band,
The heart rate variability analyzer according to claim 8, wherein the high frequency band includes a band between 0.15 and 0.4 Hz. The target frequency band includes a low frequency band,
The heart rate variability analyzer according to claim 8, wherein the low frequency band includes a band between 0.04 and 0.15 Hz. The target frequency band includes a very low frequency band,
The heart rate variability analyzer according to claim 8, wherein the ultra-low frequency band includes a band between 0.003 and 0.04 Hz.   The heart rate variability analyzer according to claim 1, wherein the heart rate variability signal includes a power spectrum signal of the target frequency band. The target frequency band includes a high frequency band and a low frequency band,
The heart rate variability analyzing unit calculates at least one of a power value of the high frequency band, a power value of the low frequency band, and a power ratio of the low frequency band to the high frequency band based on the power spectrum signal. The heart rate variability analyzer according to claim 12. Receiving an electrocardiogram signal;
Detecting an R-peak value of the electrocardiogram signal;
A frequency conversion step of generating a target frequency signal by extracting a target frequency band of the RR interval time-series signal generated based on the R-peak value;
Calculating and analyzing a heart rate variability signal for the target frequency band based on the target frequency signal; and
The frequency conversion step is
Moving the target frequency band of the RR interval time-series signal to a baseband;
Filtering the RR interval time series signal moved to the baseband with a low-pass filter;
And a fast Fourier transform step on the filtered RR interval time-series signal. The frequency conversion step includes
The heart rate variability detection method according to claim 14, further comprising a step of diverting the RR interval time series signal into an I (In-phase) channel signal and a Q (quadture-phase) channel signal. The frequency conversion step includes
Reducing the sampling rate of the filtered RR interval time series signal;
The heart rate variability detection method according to claim 15, further comprising: inserting zero data into the filtered RR interval time series signal.

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