WO2024166481A1 - Biometric information measuring device - Google Patents

Abstract

In the present invention, a biological signal having a harmonic structure is input to a bandpass filter. The bandpass filter passes components of a frequency band including the fundamental frequency and one frequency among a plurality of harmonics contained in the biological signal, attenuates other frequency components, and outputs a first signal. A frequency analysis unit that receives the first signal outputs a second signal that includes information about the frequency of the input signal. A biometric information acquisition unit acquires biometric information from the second signal.

Description

Biological information measuring device

The present invention relates to a bioinformation measuring device.

A bioinformation measuring device that measures bioinformation by analyzing biosignals such as pulse waves is known (Patent Document 1). This bioinformation measuring device includes a phase-locked loop circuit to which the biosignal is input. The phase-locked loop circuit includes a phase frequency comparator, a loop filter, and a voltage-controlled oscillator. A variable low-pass filter blocks signals of a predetermined frequency band contained in the deviation signal that has passed through the loop filter. The bioinformation is obtained from the signal that has passed through the variable low-pass filter.

International Publication No. 2015/045939

Biological signals include signals related to the biological information of the measurement target as well as signals related to biological information that is not the target of measurement. For example, a ballistocardiogram (BCG) obtained to measure heart rate includes low-frequency signals caused by breathing, etc. If signals generated by other biological phenomena are superimposed on the signals related to the biological information of the measurement target, the measurement accuracy of the biological information of the measurement target will decrease. Furthermore, the obtained signals may also include noise caused by the environment, such as vibration.

The object of the present invention is to provide a bioinformation measuring device that can suppress a decrease in the measurement accuracy of bioinformation even if signals generated due to other biological phenomena or the environment are superimposed on a signal related to the bioinformation of the measurement subject.

According to one aspect of the present invention,
a bandpass filter that receives a biological signal having a harmonic structure, passes a component of a frequency band including a fundamental frequency and one of a plurality of harmonics included in the biological signal, and attenuates components of other frequencies to output a first signal;
a frequency calculation unit that receives the first signal and outputs a second signal including information about a frequency of the input signal;
and a biological information acquiring unit that acquires biological information from the second signal.

By inputting the first signal output from the bandpass filter to the frequency calculation unit, it is possible to perform frequency analysis without being affected by signals in the frequency range attenuated by the bandpass filter. As a result, it is possible to suppress a decrease in the measurement accuracy of biological information.

FIG. 1A is a block diagram of a bioinformation measuring device according to a first embodiment and a diagram showing an example of a signal waveform, and FIG. 1B is a graph showing a heart rate waveform as an example of a biosignal SigB. FIG. 2 is a graph showing an example of a spectrum obtained by performing a spectral analysis on the biological signal SigB. FIG. 3 is a block diagram of the bandpass filter and the frequency calculation unit. FIG. 4 is a diagram showing an example of the spectrum and signal waveform of the biological signal SigB to be measured and the signal SigR caused by respiration or the like superimposed on the biological signal SigB. FIG. 5 is a graph showing an example of waveforms of the biological signal SigB and the first signal Sig1, and a time change in the frequency of the fundamental wave of the biological signal SigB and the first signal Sig1. FIG. 6 is a block diagram of a biological information measuring device according to the second embodiment. FIG. 7 is a flowchart showing a procedure for the signal analysis unit to determine the target order n. FIG. 8 is a flowchart showing a control procedure executed by the input control unit. FIG. 9 is a graph for explaining the control of the input control unit. FIG. 10A is a block diagram of a biological information measuring device according to the third embodiment, and FIG. 10B is a block diagram of a frequency calculation unit. FIG. 11 is a block diagram of a biological information measuring device according to the fourth embodiment. FIG. 12 is a graph showing the relationship between the pass frequency bands of a plurality of filter units BPF _i . FIG. 13 is a block diagram of the output control unit. FIG. 14 is a graph showing the relationship between the previous frequency ft _p , the pass frequency band of the filter unit BPF _i , and the selected phase locked loop PLL _i . FIG. 15 is a table showing an example of cutoff frequencies and threshold values for switching the phase locked loop. FIG. 16 is a block diagram of a biological information measuring device according to a modification of the fourth embodiment.

[First embodiment]
A bioinformation measuring device according to a first embodiment will be described with reference to Fig. 1A to Fig. 5. Fig. 1A is a block diagram of the bioinformation measuring device according to the first embodiment, and a diagram showing an example of a signal waveform. Fig. 1B is a graph showing a heart rate waveform as an example of a biosignal SigB. The horizontal axis of Fig. 1B represents time, and the vertical axis represents sensor output.

The bioinformation measuring device according to the first embodiment includes a sensor 70, a bandpass filter 10, a frequency calculation unit 20, a bioinformation acquisition unit 30, and a display device 60. The sensor 70 is, for example, an acceleration sensor that acquires a ballistocardiogram (BCG).

In the first embodiment, it is assumed that the sensor 70 is used by being placed around the human body, for example on a seat or bed, or by being in direct contact with the human body. Heartbeat vibrations are detected by the sensor 70. The functions of the bandpass filter 10, frequency calculation unit 20, and bioinformation acquisition unit 30 are realized in software by a microcontrol unit (MCU). The sensor 70 detects the biosignal SigB, and the biosignal SigB shown in FIG. 1B is input to the bandpass filter 10. The signal output from the sensor 70 may be an analog signal or a digital signal. If the signal output from the sensor 70 is an analog signal, it is converted to a digital signal by an AD converter in the MCU.

ここで、ｔは時間、ｆ_ｒは周波数、φ_ｒは位相、ａ_ｒは振幅を表す。 Next, a general formula expressing the biosignal SigB will be described.
For example, when a heartbeat signal is captured by a ballistocardiogram, an electrocardiogram, a pulse wave signal, or the like, these signals often mimic a structure composed of multiple sine waves. A signal representing breathing can also be confirmed to have a similar structure if it is periodic. The waveform y'(t) of these periodic biosignals SigB, such as heartbeat and breathing, can often be described by the following equation:

Here, t represents time, f _r represents frequency, φ _r represents phase, and a _r represents amplitude.

式（２）の右辺の第１項が基本波を表しており、第２項が高調波を表している。 When the biosignal SigB is composed of a fundamental wave having a fundamental frequency f ₀ and a harmonic having a frequency _kr times the fundamental wave, the waveform y(t, f ₀ ) of the biosignal SigB can be expressed by the following equation.

The first term on the right side of equation (2) represents the fundamental wave, and the second term represents the harmonic wave.

In a biosignal such as a heartbeat signal, in addition to the change in intensity depending on time t, the fundamental frequency _f0 also changes. The change in fundamental frequency _f0 is a factor that changes the heartbeat interval. To represent this change in the heartbeat interval, the argument of the function y includes the fundamental frequency _f0 .

In formula (2), when the influence of disturbances can be ignored, the amplitude components ( _a0 , _ar ), frequency components ( _f0 , _kr ), phase components ( _φ0 , _φr ), etc. become values specific to the vibration transmission path or the living body. When the biosignal SigB can be expressed as a sum of a fundamental wave and harmonics up to order N, the waveform y(t, _f0 ) of the biosignal SigB can be expressed by the following formula.

For example, the frequency components of a heartbeat signal (e.g., a BCG waveform) acquired by a specific sensor are _f0 , _2f0 , _3f0 , _4f0 , and _5f0 , assuming that the maximum order N of the constituent signals is 5. Each frequency component has its own amplitude _A1 , _A2 , _A3 , _A4 , and _A5 . In this case, the fundamental frequency _f0 is called the heartbeat frequency, and its reciprocal 1/ _f0 is called the heartbeat (pulse wave) interval.

Generally, the biosignal SigB (Figure 1B) has a harmonic structure expressed by equation (3). That is, the biosignal SigB is composed of a fundamental wave and its harmonics. In Figure 1B, the period of the fundamental wave of the heartbeat waveform is marked as T. The period T of the fundamental wave corresponds to the heartbeat interval, and its reciprocal corresponds to the heartbeat frequency.

The bandpass filter 10 passes signals in one of the fundamental frequency band and the frequency bands of the multiple harmonics of the inputted biosignal SigB, and attenuates signals in the other frequency bands. Hereinafter, a case will be described in which the pass frequency band of the bandpass filter 10 corresponds to the frequency band of the nth harmonic of the biosignal SigB. When n=1, the bandpass filter 10 passes signals in the fundamental frequency band of the biosignal SigB. When the fundamental frequency of the biosignal SigB is _f0 , the waveform of the first signal Sig1 that has passed through the bandpass filter 10 becomes a shape close to a sine wave with a frequency of _nf0 .

The frequency calculation unit 20 analyzes the first signal Sig1 that has passed through the band-pass filter 10, and outputs a second signal Sig2 that includes information about the frequency nf ₀ of the first signal Sig1. For example, the second signal Sig2 has a value of frequency nf _0. Note that when the frequency calculation unit 20 is configured with an analog circuit, the second signal Sig2 has a voltage value corresponding to the frequency nf ₀ .

The bioinformation acquiring unit 30 acquires the bioinformation infB from the second signal Sig2. For example, the bioinformation acquiring unit 30 obtains a fundamental frequency _f0 from the second signal Sig2. When the biosignal infB is a heartbeat signal, the bioinformation infB is a heartbeat frequency, and its value is given by the fundamental frequency _f0 . The heartbeat interval is given by its reciprocal 1/ _f0 .

The display device 60 displays information related to the bioinformation infB acquired by the bioinformation acquisition unit 30. For example, it displays the heartbeat frequency or heartbeat interval as numbers or a graph.

Next, referring to FIG. 2, an overview of the processing performed by the bandpass filter 10, frequency calculation unit 20, and bioinformation acquisition unit 30 of the bioinformation measuring device according to the first embodiment will be described. FIG. 2 is a graph showing an example of a spectrum obtained by spectral analysis of the biosignal SigB. The horizontal axis represents frequency, and the vertical axis represents signal strength for each frequency.

The biological signal SigB includes a fundamental wave with a fundamental frequency _f0 and second to fifth harmonics with frequencies _2f0 , _3f0 , _4f0 , and _5f0 . The bandpass filter 10 passes signals in a frequency band including the second harmonic frequency _2f0 , for example. The lower cutoff frequency on the low frequency side of the bandpass filter 10 is higher than the fundamental frequency _f0 , and the upper cutoff frequency on the high frequency side is lower than the third harmonic frequency _3f0 . In other words, the bandpass filter 10 passes signals in one of the frequency bands of the fundamental wave and each of the multiple harmonics of the biological signal SigB, and attenuates signals in the other frequency bands.

The frequency calculation unit 20 uses the first signal Sig1 (second harmonic) that has passed through the bandpass filter 10 to calculate its frequency _2f0 , and outputs it as the second signal Sig2. The order of the harmonic that is the subject of calculation by the frequency calculation unit 20 is referred to as the target order n. The bioinformation acquisition unit 30 calculates the fundamental frequency _f0 by dividing the value indicated by the second signal Sig2 by 2.

2, the order n of the harmonic wave passed by the bandpass filter 10 is set to 2, but the fundamental frequency _f0 can be obtained by similar processing when n=3, 4, or 5. In this manner, the fundamental frequency _f0 is calculated without directly using the signal in the fundamental frequency band of the biological signal SigB. Note that when the bandpass filter 10 passes the signal in the fundamental frequency band and attenuates the signal in the harmonic frequency band, the second signal Sig2 output from the frequency calculation unit 20 represents the fundamental frequency _f0 .

Next, the configuration of the frequency calculation unit 20 will be described with reference to FIG. 3. FIG. 3 is a block diagram of the bandpass filter 10 and the frequency calculation unit 20. The functions of each block of the frequency calculation unit 20 are realized, for example, by software. Note that it is also possible to realize these functions by hardware circuits.

The bandpass filter 10 passes signals in a predetermined specific frequency band among the frequency bands of the fundamental wave and multiple harmonics of the biosignal SigB. Taking into account the expected heart rate frequency band, a fourth-order infinite impulse response (IIR) digital filter can be used as the bandpass filter 10 that passes signals in a frequency band including the second harmonic. The lower cutoff frequency is set to, for example, 2 Hz, and the upper cutoff frequency is set to 4 Hz. If large output delay is not a problem or if a steep cutoff characteristic is not required, a finite impulse response (FIR) digital filter may be used as the bandpass filter 10.

The frequency calculation unit 20 includes a phase locked loop 21, a frequency conversion unit 26, and a low pass filter 27. The phase locked loop 21 includes a phase comparison unit 22, a loop filter 23, and a numerically controlled oscillator 24. The phase locked loop 21 is designed to be able to track signals in the frequency band that is passed by the band pass filter 10, among the frequency bands of the fundamental wave and multiple harmonics of the biosignal SigB.

The numerically controlled oscillator 24 changes the frequency and phase of the tracking signal Sigt that it outputs according to the output of the loop filter 23. The initial frequency at the start of operation of the numerically controlled oscillator 24 and the range of frequencies that the tracking signal Sigt tracks (hereinafter sometimes referred to as tracking frequencies) can be initialized by an external control signal. In addition, the operation of the phase locked loop circuit 21 can be stopped (tracking stopped) by an external control signal. Note that the phase locked loop circuit 21 may be a free-running phase locked loop circuit that can track a specific frequency band without parameter settings or external control signal input. In addition, when the function of the phase locked loop circuit 21 is realized by a hardware circuit, a voltage controlled oscillator is used instead of the numerically controlled oscillator 24.

The phase comparator 22 compares the input first signal Sig1 with the tracking signal Sigt output from the numerically controlled oscillator 24, and calculates the phase difference between them. The loop filter 23 outputs an appropriate control signal for controlling the numerically controlled oscillator 24 based on the phase difference calculated by the phase comparator 22.

The frequency conversion unit 26 converts the control signal output from the loop filter 23 into frequency information. More specifically, it converts the control value of the control signal input to the numerically controlled oscillator 24 into the current tracking frequency of the phase-locked loop circuit 21. Depending on the configurations of the loop filter 23 and the numerically controlled oscillator 24, the output of the loop filter 23 may contain frequency information. In such cases, the frequency conversion unit 26 is not necessary.

The low-pass filter 27 smooths the time change in the control value of the control signal output from the loop filter 23. For example, depending on the design of the loop filter 23 and the numerically controlled oscillator 24, ripple noise of a magnitude that cannot be ignored may be superimposed on the output of the loop filter 23. The low-pass filter 27 is provided for the purpose of removing this ripple noise. Note that if the design of the loop filter 23 and the numerically controlled oscillator 24 can suppress the ripple noise to a negligible level, or if the ripple noise is not a problem for downstream display control or applications, then the low-pass filter 27 does not need to be provided.

In the first embodiment, as an example, the initial frequency of the phase locked loop 21 is 2.5 Hz, and the tracking frequency range of the numerically controlled oscillator 24 is 2 Hz to 4 Hz. A fourth-order IIR digital filter is used as the low-pass filter 27, and the cutoff frequency of the low-pass filter 27 is 0.6 Hz. Note that if a large output delay is not a problem or if a steep cutoff characteristic is not required, an FIR digital filter may be used as the low-pass filter 27.

Next, the advantageous effects of the first embodiment will be described with reference to FIGS.
FIG. 4 is a diagram showing an example of the spectrum and signal waveform of the biological signal SigB to be measured and the signal SigR caused by respiration or the like superimposed on the biological signal SigB.

The spectrum Sph of the biological signal SigB shows peaks of the fundamental wave at frequency f ₀ , the second harmonic at frequency 2f ₀ , the third harmonic at frequency 3f ₀ , the fourth harmonic at frequency 4f ₀ , and the fifth harmonic at frequency 5f _0. In addition, the spectrum Spr of the signal SigR caused by breathing, etc. appears. The frequency band of the spectrum Spr overlaps with the frequency band of the fundamental wave of the biological signal SigB.

For example, the heart rate is generally said to be between 60 and 85 bpm, which, when converted to frequency, gives a heart rate of between 1 and 1.4 Hz. On the other hand, the respiratory rate is generally between 12 and 20 bpm, which, when converted to frequency, gives a respiratory rate of between 0.2 and 0.3 Hz. In terms of frequency, the two do not overlap. However, on the body surface, movement caused by breathing is often several times greater than movement caused by the heart rate. When body surface movement is captured with an acceleration sensor, the signal due to movement caused by breathing appears relatively large.

Furthermore, the signal SigR caused by breathing has a gentle triangular wave shape, and as shown in FIG. 4, its harmonics can extend into the frequency band of the fundamental wave of the biosignal SigB while maintaining a large amplitude level. If a signal combining the signal SigR caused by breathing, etc. and the biosignal SigB caused by the heartbeat is directly input to the phase-locked loop 21 (FIG. 3), it will be influenced by the signal SigR caused by breathing, etc., and will make it difficult to accurately track the fundamental wave of the biosignal SigB caused by the heartbeat.

In the first embodiment, the second harmonic, rather than the fundamental wave of the biological signal SigB, is input to the frequency calculation unit 20 (FIG. 1A), and the fundamental wave of the biological signal SigB and the signal SigR caused by breathing, etc. are attenuated by the bandpass filter 10 (FIG. 1A) and are not input to the frequency calculation unit 20 (FIG. 1A). Therefore, the frequency 2f ₀ of the second harmonic can be calculated with high accuracy without being affected by the signal SigR caused by breathing, etc. The biological information acquisition unit 30 calculates the frequency f ₀ of the fundamental wave from the frequency 2f ₀ calculated by the frequency calculation unit 20, so that the frequency f ₀ of the fundamental wave can be calculated without being affected by the signal SigR caused by breathing, etc.

FIG. 5 is a graph showing an example of the waveforms of the biosignal SigB and the first signal Sig1, and the time change in frequency of the fundamental wave of the biosignal SigB and the first signal Sig1. The horizontal axis represents time, the first graph represents the waveform of the biosignal SigB, and the second graph represents the waveform of the first signal Sig1 that has passed through the bandpass filter 10. Note that the waveform shown in the upper part of FIG. 5 has signals other than BCG and noise excluded. In the example shown in FIG. 5, the target order n is set to 2. As an example, the frequency of the first signal Sig1, which is the second harmonic, is in the range of 2 Hz to 4 Hz.

The vertical axis of the third graph represents frequency. The solid line in the third graph represents the change over time in frequency of the first signal Sig1 (i.e., the change over time in frequency of the second harmonic of the biosignal SigB), and the dashed line represents the change over time in the fundamental wave of the biosignal SigB (i.e., the change over time in heart rate frequency). In Figure 5, the frequency range of the spectrum Spr (Figure 4) of the signal SigR resulting from breathing, etc. is hatched.

Depending on the time period, the heartbeat frequency may fall within the frequency range of the spectrum Spr of the signal SigR caused by breathing, etc. In this case, as explained with reference to FIG. 4, the heartbeat frequency cannot be accurately determined based on the fundamental wave of the biosignal SigB. Since the frequency of the first signal Sig1, which is the second harmonic of the biosignal SigB, does not overlap with the frequency range of the spectrum of the signal caused by breathing, etc., the frequency of the first signal Sig1 can be accurately determined in any time period. As a result, it becomes possible to accurately determine the heartbeat frequency.

Next, a modification of the first embodiment will be described.
In the first embodiment, the bandpass filter 10 (FIG. 1A) passes the second harmonic of the biosignal SigB, but may pass harmonics of other orders. In the example shown in FIG. 4, the frequency band of the third or higher harmonics does not overlap with the frequency band of the spectrum of the signal SigR caused by breathing or the like. Therefore, the bandpass filter 10 may pass any of the third or higher harmonics. In this case, the bioinformation acquisition unit 30 (FIG. 1A) may divide the value of the second signal Sig2 by the order of the harmonic passing through the bandpass filter 10.

In addition, if the spectrum of another signal does not overlap the frequency band of the fundamental wave of the biological signal SigB, but the spectrum of another signal overlaps the frequency band of the harmonic, the bandpass filter 10 may pass the fundamental wave and attenuate the second and higher harmonics.

In the first embodiment, an acceleration sensor is used as the sensor 70 (FIG. 1A), but other sensors capable of acquiring a BCG, such as a piezoelectric sensor, may also be used. Also, in the first embodiment, a signal representing a BCG waveform is adopted as the biosignal SigB input to the bandpass filter 10, but other signals may also be used. For example, a signal representing an electrocardiogram (ECG) waveform or a signal representing a pulse wave waveform may be used as the biosignal SigB. The signal representing an ECG waveform can be acquired, for example, using an electrocardiograph. The signal representing a pulse wave waveform can be acquired, for example, using a photoplethysmograph sensor.

In the first embodiment, the biosignal SigB is a signal corresponding to the heartbeat of the living body, but the biosignal SigB may be a signal having another harmonic structure. For example, a signal that changes in response to respiration may be used as the biosignal SigB. Also, in the first embodiment, the signal to be calculated by the frequency calculation unit 20 is selected from a fundamental wave or a harmonic having a frequency that is an integer multiple of the frequency of the fundamental wave, but the frequency band of the signal to be calculated by the frequency calculation unit 20 does not have to be an integer multiple of the fundamental frequency.

[Second embodiment]
Next, a biological information measuring device according to a second embodiment will be described with reference to Figures 6 to 9. Below, a description of the configuration common to the biological information measuring device according to the first embodiment described with reference to Figures 1A to 5 will be omitted.

FIG. 6 is a block diagram of a bioinformation measuring device according to the second embodiment. The bioinformation measuring device according to the second embodiment includes a signal analysis unit 40 and an input control unit 50 in addition to the sensor 70, bandpass filter 10, frequency calculation unit 20, bioinformation acquisition unit 30, and display unit 60 of the bioinformation measuring device according to the first embodiment. A biosignal SigB is input to the signal analysis unit 40.

In the first embodiment, the harmonic order n (target order n) that the bandpass filter 10 passes is determined in advance, but in the second embodiment, the signal analysis unit 40 analyzes the biosignal SigB to determine the target order n.

Next, a method for determining the target order n will be described with reference to FIG. 7. FIG. 7 is a flowchart showing the procedure by which the signal analysis unit 40 determines the target order n.

First, while the human body is at rest, the signal analysis unit 40 analyzes the input signal (step SA1). Based on the analysis result, it is determined whether or not the input signal contains a biosignal SigB such as a heartbeat signal (step SA2). For example, in step SA1, the input signal is Fourier transformed, and if the result of the Fourier transform has a harmonic structure expressed by equation (3), it is determined in step SA2 that a biosignal SigB is present. Alternatively, in step SA1, the root mean square (RMS) of the intensity of the input signal is calculated, and if the calculation result is equal to or greater than a threshold value, it is determined in step SA2 that a biosignal SigB is present.

If the input signal does not contain the biosignal SigB, steps SA1 and SA2 are repeated until it is determined that the biosignal SigB is present. If it is determined that the input signal contains the biosignal SigB, the target order n is determined, and various parameters of the bandpass filter 10 and the frequency calculation unit 20 are determined and set (step SA3). The target order n may be, for example, the order of a peak that appears in the frequency band with the smallest noise floor on the frequency axis in the spectrum obtained by performing a Fourier transform or the like on the biosignal SigB. For example, the cutoff frequency of the bandpass filter 10, the initial frequency of the numerically controlled oscillator 24 (Figure 3), and the parameters of the loop filter 23 are determined and set.

When the biological information measuring device is operated with these parameters set, the value of the second signal Sig2 output from the frequency calculation section 20 (FIG. 6) becomes the frequency _nf0 of the nth harmonic.

In the second embodiment, the bioinformation acquisition unit 30 (FIG. 6) includes a divider 32 and an inverse calculator 33. The signal analysis unit 40 notifies the divider 32 of the target order n. The divider 32 divides the frequency nf ₀ indicated by the second signal Sig2 input from the frequency calculation unit 20 by the target order n to generate bioinformation infB indicating the value of the fundamental frequency f ₀ of the biosignal SigB. The bioinformation infB represents the heartbeat frequency. The inverse calculator 33 calculates the inverse of the bioinformation infB output from the divider 32 to generate information T representing the heartbeat interval. The obtained heartbeat frequency and heartbeat interval information are displayed on the display device 60.

Next, the function of the input control unit 50 (FIG. 6) will be described with reference to FIG. 8. FIG. 8 is a flowchart showing the control procedure executed by the input control unit 50.

The input control unit 50 analyzes the first signal Sig1 output from the bandpass filter 10 (step SB1). Based on the analysis result, it is determined whether the bandpass filter 10 outputs a first signal Sig1 (hereinafter referred to as a significant first signal Sig1) whose magnitude can be calculated by the frequency calculation unit 20 (step SB2). If the bandpass filter 10 outputs a significant first signal Sig1, it turns on the signal input to the frequency calculation unit 20 (step SB3). This causes the frequency calculation unit 20 to calculate the frequency (step SB4). If the bandpass filter 10 does not output a significant first signal Sig1, it turns off the signal input to the frequency calculation unit 20 (step SB5). In other words, no signal is input to the frequency calculation unit 20. Furthermore, it initializes the frequency calculation unit 20 (step SB6).

Next, the control performed by the input control unit 50 will be described with reference to FIG. 9. FIG. 9 is a graph for explaining the control of the input control unit 50. The upper graph in FIG. 9 represents the time change in the root mean square (RMS) of the intensity of the first signal Sig1 output from the bandpass filter 10, and the lower graph is a timing chart of the on/off of the signal input to the frequency calculation unit 20 (FIG. 6). The horizontal axis represents time, the vertical axis of the upper graph represents RMS, and the vertical axis of the lower graph represents the on/off of the signal input to the frequency calculation unit 20.

The input control unit 50 calculates the RMS of the first signal Sig1. When the signal input to the frequency calculation unit 20 is currently off, if the RMS value becomes equal to or greater than the on threshold THon (time _t1 ), the input control unit 50 switches the signal input to the frequency calculation unit 20 from off to on. When the signal input to the frequency calculation unit 20 is currently on, if the RMS value becomes equal to or less than the off threshold THoff (time _t2 ), the input control unit 50 switches the signal input to the frequency calculation unit 20 from on to off. The on threshold THon is greater than the off threshold THoff.

If the bandpass filter 10 is not outputting a significant first signal Sig1 and the first signal Sig1 is white noise, the input of the signal to the frequency calculation unit 20 can be turned off to prevent the phase synchronization circuit 21 (Figure 3) of the frequency calculation unit 20 from tracking a signal of an incorrect frequency. By initializing the frequency calculation unit 20 in step SB6, the next time a significant first signal Sig1 is input, analysis can be performed from the initial state.

In addition, if the phase-locked loop 21 has characteristics that prevent malfunction even when the first signal Sig1 is white noise, the input control unit 50 does not need to be provided. The input control unit 50 may have functions to adjust the gain of the input signal to the frequency calculation unit 20 and adjust the sampling rate.

In the analysis of step SB1, the output signal of the bandpass filter 10 is Fourier transformed, and in the determination of step SB2, if a peak exists in the frequency band of the target order n, it may be determined that a significant first signal Sig1 is being output.

Next, the advantageous effects of the second embodiment will be described.
In the second embodiment, the target order n is determined by analyzing the signal input from the sensor 70 (FIG. 6). For this reason, among the fundamental wave and multiple harmonics of the biological signal SigB, the fundamental wave or the harmonic of the order that is least susceptible to noise is input to the frequency calculation unit 20. By determining a preferable target order n according to the noise situation, the calculation accuracy of the frequency calculation unit 20 can be improved.

[Third Example]
Next, a biological information measuring device according to a third embodiment will be described with reference to Fig. 10A and Fig. 10B. Below, a description of the configuration common to the biological information measuring device according to the second embodiment described with reference to Figs. 6 to 9 will be omitted.

FIG. 10A is a block diagram of a bioinformation measuring device according to the third embodiment, and FIG. 10B is a block diagram of a frequency calculation unit 20. In the second embodiment (FIG. 6), the control value that the loop filter 23 (FIG. 3) uses to control the numerically controlled oscillator 24 is output from the frequency calculation unit 20 as a second signal Sig2 via the frequency conversion unit 26 and the low-pass filter 27.

In contrast, in the third embodiment, the frequency calculation unit 20 includes a frequency counter 29. As shown in FIG. 10B, the tracking signal Sigt generated by the numerically controlled oscillator 24 is input to the frequency counter 29. The frequency counter 29 counts the frequency of the tracking signal Sigt and outputs the counting result as the second signal Sig2. The frequency counter 29 has a function of sequentially resetting the counter value internally. In addition, a function may be provided to initialize the counter value by a command from the input control unit 50 depending on the state of the first signal Sig1 that has passed through the bandpass filter 10.

Furthermore, in the third embodiment, the tracking signal Sigt generated by the numerically controlled oscillator 24 is divided by the frequency divider 25 and input to the phase comparison unit 22. The frequency division ratio m is set so that the frequency of the signal divided by the frequency divider 25 and the frequency of the first signal Sig1 are included in the same frequency band. A fractional PLL may be used as the frequency calculation unit 20.

When the frequency of the first signal Sig1 input to the frequency calculation unit 20 is nf ₀ , the control value output by the loop filter 23 to the numerically controlled oscillator 24 becomes nf _0. At this time, the numerically controlled oscillator 24 generates a signal having a frequency of mnf ₀ as the tracking signal Sigt. Therefore, the value of the second signal Sig2 output from the frequency counter 29 becomes mnf ₀ .

The input control unit 50 has the same functions as the input control unit 50 (FIG. 6) of the bioinformation measuring device according to the second embodiment. In addition, the input control unit 50 may have a function of initializing the phase synchronization circuit 21 and the frequency counter 29 of the frequency calculation unit 20 in step SB6 of FIG. 8.

The signal analysis unit 40 has the same functions as the signal analysis unit 40 (Fig. 6) of the bioinformation measuring device according to the second embodiment. Furthermore, the signal analysis unit 40 determines the division ratio m to be set in the divider 25 based on the oscillation frequency of the numerically controlled oscillator 24 (Fig. 10B) and the target order n. The division ratio m can be determined by dividing the oscillation frequency of the numerically controlled oscillator 24 (Fig. 10B) when the heartbeat frequency is 1 Hz by the target order n.

For example, when the heartbeat frequency is 1 Hz, if the oscillation frequency of the numerically controlled oscillator 24 is 1024 Hz and the frequency band of the tracking signal is the second harmonic of the heartbeat signal (target order n=2), the division ratio m is 512. Also, when the target order n is 4, the division ratio m is 256.

In the third embodiment, as an example, the oscillation frequency of the numerically controlled oscillator 24 is designed to be 1000 Hz when the heartbeat frequency is 1 Hz. If the heartbeat frequency range is assumed to be 0.5 Hz or more and 2.5 Hz or less, a numerically controlled oscillator 24 capable of oscillating in a frequency range of 500 Hz or more and 2500 Hz or less is used. When the target order n is 2, the division ratio m should be set to 500.

The signal analysis unit 40 notifies the phase synchronization circuit 21 of the frequency calculation unit 20 of the division ratio m, and notifies the divider 32 of the bioinformation acquisition unit 30 of the division ratio m and the target order n. The divider 25 of the phase synchronization circuit 21 divides the tracking signal Sigt by the division ratio m, and provides the divided signal to the phase comparison unit 22.

The divider 32 obtains bioinformation infB by dividing the value _mnf0 of the second signal Sig2 counted by the frequency counter 29 by the product of the target order n and the division ratio m. The value of the bioinformation infB is equal to the fundamental frequency _f0 of the bioinformation measuring device SigB. The reciprocal calculator 33 has the same function as the reciprocal calculator 33 of the bioinformation measuring device according to the second embodiment.

The product of the target order n and the division ratio m may be stored in the divider 32 as the heartbeat calculation counter value. The divider 32 can obtain the bioinformation infB by dividing the value of the second signal Sig2 by the heartbeat calculation counter value. As an example, when the counter value of the frequency counter 29 is 1050 and the heartbeat calculation counter value is 1024, the bioinformation infB (heartbeat frequency) is 1.025.

Next, the advantageous effects of the third embodiment will be described.
In the third embodiment, similarly to the second embodiment, the calculation accuracy of the frequency calculation unit 20 can be improved by determining a preferable target order n depending on the noise situation. Also, in the third embodiment, the loop filter 23 (FIG. 3) outputs the second signal Sig2 by counting the frequency of the tracking signal Sigt generated by the phase locked loop circuit 21 with the frequency counter 29 without referring to the control value that controls the numerically controlled oscillator 24. This makes it easier to realize the function of the frequency calculation unit 20 with hardware.

Next, a biological information measuring device according to a modification of the third embodiment will be described.
The counter value by the frequency counter 29 may be interpreted as a fixed-point number, and the divider 32 may be omitted. For example, when the product of the target order n and the division ratio m is 1000, it may be interpreted that there is a decimal point between the hundreds and thousands digits of the counter value by the frequency counter 29. For example, when the counter value is 1000, the bioinformation infB (heartbeat frequency) is 1.000, and when the counter value is 825, the bioinformation infB (heartbeat frequency) is 0.825. In this case, the counter value may be displayed as it is on the display device 60.

[Fourth embodiment]
Next, a biological information measuring device according to a fourth embodiment will be described with reference to Fig. 11 to Fig. 14. Hereinafter, a description of the configuration common to the biological information measuring device according to the second embodiment described with reference to Fig. 6 to Fig. 9 will be omitted.

Fig. 11 is a block diagram of a bioinformation measuring device according to the fourth embodiment. In the second embodiment (Fig. 6), when the target order n is determined, the upper and lower cutoff frequencies of the bandpass filter 10 are determined according to the target order n. In contrast, in the fourth embodiment, the bandpass filter 10 includes a plurality of filter units BPF _i having different pass frequency bands. Here, i represents a serial number assigned to the plurality of filter units. A common biosignal SigB is input to the plurality of filter units BPF _i .

Fig. 12 is a graph showing the relationship of the pass frequency band of a plurality of filter units BPF _i . The horizontal axis represents frequency, and the vertical axis represents pass rate. Fig. 12 shows an example in which the number of filter units BPF _i is five. The plurality of filter units BPF _i are labeled BPF ₁ , BPF ₂ , BPF ₃ , BPF ₄ , and BPF ₅ in order from the lowest center frequency of the pass frequency band.

Among the multiple filter units BPF _i , the pass frequency bands of two filter units BPF _i whose center frequencies are adjacent to each other partially overlap. For example, a part of the high frequency side of the pass frequency band of filter unit BPF _i and a part of the low frequency side of the pass frequency band of filter unit BPF _i+1 overlap with each other. Also, the pass frequency bands of filter units BPF _i whose center frequencies are not adjacent to each other do not overlap with each other. For example, the pass frequency band of filter unit BPF _i and the pass frequency band of filter unit BPF _i+2 do not overlap with each other.

The lower cutoff frequency of the filter unit BPF _i is denoted as f _iL , and the upper cutoff frequency is denoted as f _iH . At this time, the cutoff frequencies of the multiple filter units BPF _i are set so that the following inequality is satisfied.
f _i+1,L < f _iH
f _iH < f _i+2,L

The frequency calculation section 20 (FIG. 11) includes a plurality of phase synchronization circuits 21 and an output control section 28. The number of phase synchronization circuits 21 is the same as the number of filter units BPF _i , and there is a one-to-one correspondence between the phase synchronization circuits 21 and the filter units BPF _i . The phase synchronization circuits 21 corresponding to the filter units BPF ₁ , BPF ₂ , BPF ₃ , BPF ₄ , and BPF ₅ are denoted as PLL ₁ , PLL ₂ , PLL ₃ , PLL ₄ , and PLL ₅ , respectively.

The first signal Sig1 that has passed through the filter unit BPF _i is input to the corresponding phase locked loop PLL _i . The phase locked loop PLL _i outputs the frequency (tracking frequency) value nf ₀ of the tracking signal Sigt. The output control unit 28 selects one of the tracking frequency values output from each of the multiple phase locked loops PLL _i and outputs it as the second signal Sig2.

The function of the biometric information acquisition unit 30 is the same as the function of the biometric information acquisition unit 30 of the biometric information measuring device according to the second embodiment.

The input control unit 50 inputs the first signal Sig1, which is the output of the filter unit BPF _i , to the corresponding phase locked loop PLL _i . Furthermore, the input control unit 50 performs the same control as the input control unit 50 of the bioinformation measuring device according to the second embodiment (FIG. 6) for the pair of the mutually corresponding filter unit BPF _i and the phase locked loop PLL _i .

The input control unit 50 also controls the output control unit 28. The control of the output control unit 28 will be explained later.

The signal analysis unit 40 has the same functions as the signal analysis unit 40 of the bioinformation measuring device according to the second embodiment (FIG. 6). For example, the signal analysis unit 40 determines the target order n by analyzing the input biosignal SigB. Once the target order n is determined, the signal analysis unit 40 determines the cutoff frequency of each of the multiple filter units BPF _i , and sets the cutoff frequency to each of the filter units BPF _i . Furthermore, the signal analysis unit 40 individually controls each of the multiple phase-locked loops PLL _i .

The signal analysis unit 40 also controls the output control unit 28. The control of the output control unit 28 will be explained later.

Next, the function of the output control unit 28 will be described with reference to Fig. 13. Fig. 13 is a block diagram of the output control unit 28. The output control unit 28 includes a selector 28A and a delay unit 28B. The tracking frequency ft _i output from each of the phase locked loops PLL _i is input to the selector 28A. Furthermore, the tracking frequency ft output from the selector 28A is delayed by the delay unit 28B and input to the selector 28A. The tracking frequency delayed by the delay unit 28B and input to the selector 28A is referred to as the previous frequency ft _p .

The selector 28A compares the previous frequency _ftp with a threshold value set in the selector 28A, and determines the tracking frequency ft to be output this time from among a plurality of tracking frequencies _fti based on the comparison result. An initial value _finit of the previous frequency _ftp is set in the delay unit 28B. At the time of the first control or the first control after initialization, the delay unit 28B outputs the initial value _finit as the previous frequency _ftp . The initial value _finit is set by a command from the signal analysis unit 40 or the input control unit 50.

Next, the operation of the selector 28A will be described with reference to Fig. 14. Fig. 14 is a graph showing the relationship between the previous frequency _ftp , the pass frequency band of the filter unit BPF _i , and the selected phase locked loop PLL _i . The horizontal axis represents the previous tracking frequency _ftp , and the vertical axis represents the selected phase locked loop PLL _i .

In FIG. 14, the lower cutoff frequency of the pass frequency band of the filter unit BPF _i is marked as f _iL , and the upper cutoff frequency is marked as f _iH .

An upper threshold value f _i,i+1 and a lower threshold value f _i+1,i are set in the range where the pass frequency bands of filter units BPF _i and BPF _i+1 overlap. The upper threshold value f _i,i+1 is higher than the lower threshold value f _i+1,i . A case where the output of phase locked loop circuit PLL _i is currently selected will be described. When the previous tracking frequency ft _p is equal to or higher than the lower threshold value f _i,i-1 and equal to or lower than the upper threshold value f _i,i+1 , the output of phase locked loop circuit PLL _i is also selected this time.

If the previous tracking frequency ft _p exceeds the upper threshold value f _i,i+1 , the output of the phase locked loop PLL _i+1 is selected this time.If the previous tracking frequency ft _p is less than the lower threshold value f _i,i-1 , the output of the phase locked loop PLL _i-1 is selected this time.

That is, when the previous tracking frequency ft _p approaches the upper limit of the frequency band covered by the output of the currently selected phase locked loop PLL _i , the selected phase locked loop is switched to the output of the phase locked loop PLL _i+1 , which covers a higher frequency band. When the previous tracking frequency ft _p approaches the lower limit of the frequency band covered by the output of the currently selected phase locked loop PLL _i , the selected phase locked loop is switched to the output of the phase locked loop PLL _i-1 , which covers a lower frequency band. Hysteresis is provided to prevent frequent switching near the threshold for switching the output of the phase locked loop.

15 is a table showing an example of cutoff frequencies and thresholds for switching the phase locked loop. For example, the lower cutoff frequency _f2L of the filter unit _BPF2 is 1.8 Hz, and the upper cutoff frequency _f2H is 2.8 Hz. The lower threshold _f21 for switching the phase locked loop from _PLL2 to _PLL1 is 1.9 Hz, and the upper threshold _f23 for switching from _PLL2 to _PLL3 is 2.7 Hz.

Next, the control of the output control unit 28 by the input control unit 50 (FIG. 11) will be described.
When the significant first signal Sig1 is not included in any output of the filter unit BPF _i , the output of the phase control circuit PLL _i selected by the selector 28A is controlled to be fixed. Also, when the significant first signal Sig1 is not included in any output of the filter unit BPF _i , the previous tracking frequency ft _p of the delay unit 28B (FIG. 13) is initialized. That is, the previous tracking frequency ft _p is controlled to be set to an initial value f _init .

Next, the control of the output control unit 28 by the signal analysis unit 40 (FIG. 11) will be described.
The signal analysis unit 40 has a function of determining the initial value f _init of the previous tracking frequency _ftp of the delay unit 28B (FIG. 13) of the output control unit 28. For example, when the subject is at rest and there is no body movement, the signal analysis unit 40 extracts signals from the lower cutoff frequency _f1L of the filter unit _BPF1 on the lowest frequency side to the upper cutoff frequency _f5H of the filter unit _BPF5 on the highest frequency side through a bandpass filter. The signal that has passed through the bandpass filter is subjected to a spectrum analysis to detect a spectrum peak. The frequency at which the peak appears is adopted as the initial value f _init of the previous tracking frequency _ftp of the delay unit 28B.

Alternatively, when the biological signal SigB input to the signal analysis section 40 does not contain a significant signal, a control may be performed in which a predetermined initial frequency is provided as the initial value f _init of the delay section 28B.

Next, the excellent effects of the fourth embodiment will be described in comparison with a comparative example.
In the comparative example, a pass frequency band covered by a plurality of filter units BPF _i as a whole, i.e., a frequency band from the lower cutoff frequency f _1L of filter unit BPF ₁ to the upper cutoff frequency f _5H of filter unit BPF ₅ , is realized by one filter unit. In this configuration, not only a specific harmonic of the target order n, but also harmonics of other orders and noise are likely to be input to the frequency calculation unit 20. As a result, the frequency calculation unit 20 is affected by signals other than the harmonic of the target order n, and the frequency calculation accuracy decreases.

In contrast to this, in the fourth embodiment, only a signal that has passed through one filter unit BPF _i having a narrow pass frequency band is input to one phase locked loop PLL _i , which makes the phase locked loop PLL _i less susceptible to noise, and makes it possible to improve the accuracy of frequency calculation.

In another comparative example, the bandpass filter 10 (Figure 11) is realized by a single filter unit with a narrow pass frequency bandwidth. In this comparative example, fluctuations in the frequency of the fundamental wave of the biological signal SigB make it easier for the frequency of the harmonic of the target order n to fall outside the pass frequency band of the bandpass filter 10. If the frequency of the harmonic of the target order n falls outside the pass frequency band of the bandpass filter 10, the frequency calculation unit 20 will no longer be able to track the harmonic of the target order n. This narrows the range of measurable heartbeat frequencies.

In contrast to this, in the fourth embodiment, a wide pass frequency band can be covered as a whole by using a plurality of filter units BPF _i , thereby widening the range of measurable frequencies of biosignals.

Next, a biological information measuring device according to a modification of the fourth embodiment will be described.
In the fourth embodiment, the number of filter units BPF _i constituting the bandpass filter 10 (FIG. 11) is five, but it may be any other number.

Next, a bioinformation measuring device according to another modified example of the fourth embodiment will be described with reference to FIG. 16. FIG. 16 is a block diagram of a bioinformation measuring device according to this modified example.

In the fourth embodiment, as shown in Fig. 11, the frequency calculation unit 20 is composed of a plurality of phase synchronization circuits PLL _i , and an output control unit 28 is arranged in the subsequent stage of the plurality of phase synchronization circuits PLL _i . In this modification, as shown in Fig. 16, one phase synchronization circuit 21 is arranged in the subsequent stage of the output control unit 28. The output control unit 28 selects one of the plurality of filter units BPF _i , and inputs the first signal Sig1 output from the selected filter unit BPF _i to the phase synchronization circuit 21.

In this modified example, as in the fourth embodiment, it is possible to improve the accuracy of calculating the frequency of a biological signal and widen the range of measurable frequencies.

The above-described embodiments are merely illustrative, and it goes without saying that partial substitution or combination of the configurations shown in different embodiments is possible. No reference is made to similar effects resulting from similar configurations in multiple embodiments. Furthermore, the present invention is not limited to the above-described embodiments. For example, it will be obvious to those skilled in the art that various modifications, improvements, combinations, etc. are possible.

REFERENCE SIGNS LIST 10 Band-pass filter 20 Frequency calculation unit 21 Phase synchronization circuit 22 Phase comparison unit 23 Loop filter 24 Numerical control oscillator 25 Frequency divider 26 Frequency conversion unit 27 Low-pass filter 28 Output control unit 28A Selector 28B Delay unit 29 Frequency counter 30 Biometric information acquisition unit 32 Divider 33 Reciprocal calculator 40 Signal analysis unit 50 Input control unit 60 Display device 70 Sensor

Claims (9)

a bandpass filter that receives a biological signal having a harmonic structure, passes a component of a frequency band including a fundamental frequency and one of a plurality of harmonics included in the biological signal, and attenuates components of other frequencies to output a first signal;
a frequency calculation unit that receives the first signal and outputs a second signal including information about a frequency of the input signal;
and a biological information acquiring unit that acquires biological information from the second signal. The bioinformation measuring device according to claim 1, wherein the bandpass filter passes components of any harmonic frequency of the second harmonic or higher of the biosignal. The bioinformation measuring device according to claim 2, wherein the bioinformation acquiring unit calculates the frequency of the fundamental wave of the biosignal based on the order of the harmonic passed by the bandpass filter and the second signal, and acquires the bioinformation based on the frequency of the fundamental wave. the frequency calculation unit includes a phase synchronous circuit that generates a tracking signal synchronized with the phase of an input signal;
The biological information measuring device according to claim 1 , wherein the second signal is a signal indicating a frequency value of the tracking signal. The bioinformation measuring device according to claim 4, wherein the frequency calculation unit includes a frequency counter that counts the frequency of the tracking signal and outputs the counting result of the frequency counter as the second signal. the bandpass filter includes a plurality of filter units having pass frequency bands with different center frequencies,
Among the plurality of filter units, the pass frequency bands of two filter units having center frequencies adjacent to each other partially overlap each other,
Each of the plurality of filter units outputs the first signal;
The bioinformation measuring device according to any one of claims 1 to 3, wherein the frequency calculation unit outputs the second signal based on one of the first signals selected from the first signals that have passed through each of the multiple filter units. the frequency calculation unit includes a plurality of phase locked loop circuits to which the first signals output from the plurality of filter units are input,
each of the plurality of phase locked loops generates a tracking signal that tracks the first signal input thereto;
The bioinformation measuring device of claim 6, wherein the frequency calculation unit selects one of the tracking signals generated by the multiple phase synchronization circuits, and outputs the second signal based on the selected one of the tracking signals. The bioinformation measuring device according to any one of claims 1 to 3 further comprises a signal analysis unit that sets parameters that define the operation of the bandpass filter, the frequency calculation unit, and the bioinformation acquisition unit based on the biosignal. The bioinformation measuring device of claim 6 further comprises a signal analysis unit that sets parameters that define the operation of the bandpass filter, the frequency calculation unit, and the bioinformation acquisition unit based on the biosignal.

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