JP5527277B2 - Signal processing apparatus, signal processing method, and biological information measuring apparatus - Google Patents

Description

  The present invention relates to a signal processing device, a signal processing method, and a biological information measurement device that remove noise components from a time-series signal.

  Conventionally, techniques relating to signal processing for removing noise components from time-series data on which noise components are superimposed have been applied to various signal processing apparatuses. In particular, when the time-series data includes information related to biological information, the above signal processing device is called a biological information measuring device. The biological information measuring device is a device that non-invasively detects biological information from biological tissue, specifically, a measuring device called a pulse wave meter and a pulse oximeter that measures the pulse waveform and pulse rate of a living body called a photoelectric pulse wave meter. It is a measuring device or the like that measures the arterial blood oxygen saturation concentration. The principle of these measuring devices is that a living body such as the concentration of a light-absorbing substance in blood is obtained based on a signal component obtained by receiving light transmitted or reflected through a living tissue and corresponding to fluctuations due to pulsation of the living tissue. It seeks information.

  In general, various noise components are superimposed on data necessary for detection of biological information, which is obtained by receiving light transmitted or reflected through biological tissue. The noise component is mainly due to body movement such as movement of the body when the biological information measuring device is used. If the noise component is superimposed on the signal component, it causes an error in the calculation of biological information, and therefore it is desired to remove the noise component.

  In view of this, a technique has been proposed for calculating biological information based on a direct-current alternating current ratio in the intensity of light transmitted or reflected through a living tissue when a living body is irradiated with a plurality of lights having different wavelengths.

International Publication No. 2010/073908 Specification

  Here, when the noise component is superimposed on the signal component, the DC / AC ratio for each wavelength is represented by the signal component and the noise component.

  As a technique for removing the noise component represented in this way, for example, a technique using a cross-correlation between a signal component and a noise component has been proposed. In a certain technique, the DC component ratio for each wavelength is obtained when removing the noise component. Under the assumption that the noise component is included above a predetermined frequency and the ratio of the noise component to the wavelength is constant over the entire frequency range. Further, the ratio of the noise component depending on the wavelength is calculated, and the noise component removal waveform is calculated by using the cross-correlation between the signal component and the noise component. In another technique, on the condition that the correlation between the signal component and the noise component is small, the ratio by the wavelength of the signal component and the ratio by the wavelength of the noise component that maximize the power of the signal component are obtained. Noise component is removed. In another technique, a technique is proposed in which a signal component is extracted by using periodicity from data including a signal component having periodicity generated based on measured data, and a noise component is removed from the data. (See Patent Document 1 etc.).

  As described above, a plurality of techniques have been proposed as techniques for removing noise components. However, since each technique has advantages and disadvantages, variations in the technique are desired.

  The present invention has been made in view of the above circumstances, and an object thereof is to provide a new technique for removing noise components.

  As a result of various studies, the present inventor has found that the above object is achieved by the present invention described below.

A signal processing apparatus according to an aspect of the present invention includes a first time-series signal including a first signal component having periodicity and a first noise component, and a first relationship having a predetermined first relationship with the first signal component. A delay time that is a time estimated as a period of the first signal component from two signal components and a second time-series signal including a second noise component having a second relationship with the first noise component. A signal generator for generating a first delayed signal obtained by delaying the first time-series signal and a second delayed signal obtained by delaying the second time-series signal by the delay time; and a first predetermined time range. Using the first time-series signal and the second time-series signal and the first delay signal and the second delay signal generated by the signal generation unit, the predetermined time range in the first predetermined time range. And an estimation unit for estimating the second relationship.

  A signal processing method according to another aspect of the present invention is a signal processing method, the first time-series signal including a first signal component having periodicity and a first noise component, and the first The period of the first signal component is estimated from the second signal component having the first relationship with the signal component and the second time-series signal including the second noise component having the second relationship with the first noise component. A signal generation step of generating a first delay signal obtained by delaying the first time series signal by a delay time that is a delay time and a second delay signal obtained by delaying the second time series signal by the delay time; Using the first time-series signal and the second time-series signal in a first predetermined time range, and the first delay signal and the second delay signal generated by the signal generation unit, An estimating step for estimating the second relationship in a predetermined time range; Characterized in that it comprises.

  In the signal processing apparatus having such a configuration, a predetermined second relationship between the first noise component and the second noise component can be obtained using the delay signal.

  Further, in the above-described signal processing device, the estimation unit assumes that the first signal component included in the first time-series signal and the first signal component included in the first delay signal are substantially equal to each other. A correlation between the time-series signal itself, a first difference between the correlation between the first time-series signal and the first delayed signal, a correlation between the second time-series signal itself, the second time-series signal, and the first A second difference from the correlation with the two delayed signals, a correlation of the signal itself based on the first time series signal and the second time series signal, the first time series signal and the second time series signal And the third difference between the correlation between the first delay signal and the delay signal based on the second delay signal is used to estimate the predetermined second relationship.

  In the conventional technology, the amount of processing for removing the noise component is relatively large, and thus power consumption increases. This is a serious problem in terms of power consumption, especially in portable biological information measuring devices, which are usually driven by batteries. In the signal processing apparatus having such a configuration, since the first signal component is assumed to have the same waveform even if delayed by the period thereof, the difference between the time-series signal and the delayed signal is used. The arithmetic expression for obtaining the two relations can be simplified. That is, since the amount of calculation processing can be reduced, the required CPU performance can be kept low, and the power consumption associated with the calculation of noise component removal can be suppressed. Specifically, a predetermined first of the first noise component and the second noise component is obtained by any one of Expression (23), Expression (24), Expression (25), Expression (26), and Expression (27) described later. Two relationships can be obtained. Note that the correlation of the first time-series signal and the correlation of the second time-series signal refer to the mean square.

  In the above signal processing device, the estimation unit has a sufficiently small signal noise correlation between the first signal component included in the first time series signal and the first noise component included in the first time series signal, The signal noise delay correlation between the first signal component included in the first time-series signal and the delay component of the first noise component included in the first time-series signal is also sufficiently small, and is included in the first time-series signal. The noise signal delay correlation between the delay component of one signal component and the first noise component included in the first time series signal is also sufficiently small, or the average of the signal noise delay correlation and the noise signal delay correlation and the signal noise correlation Is further premised on that the second relation is estimated using any two of the first difference, the second difference, and the third difference.

  That is, signal noise correlation (correlation between the first signal component and the first noise component included in the first time series signal), signal noise delay correlation (the first signal component and the first delay signal included in the first time system signal) (Correlation with the delay component of the first noise component included), noise signal delay correlation (correlation between the delay component of the first signal component included in the first delay signal and the first noise component included in the first time-series signal) ) Are all assumed to be 0 (zero), or the second relation is estimated on the premise that the difference between the signal noise delay correlation and the average of the noise signal delay correlation and the signal noise correlation is approximately 0 (zero). .

  In the signal processing device having such a configuration, the correlation between the first noise component and the second noise component and a signal obtained by delaying them by the period of the first signal component is assumed to be sufficiently small. An arithmetic expression for obtaining the predetermined second relationship using a difference with a signal can be further simplified. That is, since the amount of calculation processing can be reduced, the required CPU performance can be kept low, and the power consumption accompanying the calculation of noise component removal can also be suppressed. Specifically, the predetermined second relationship between the first noise component and the second noise component can be obtained by any one of Equation (25), Equation (26), and Equation (27) described later.

  Further, in the above-described signal processing device, the estimator includes the estimated second relationship, the first time-series signal or the first delay signal, and the second time-series signal or the second delay signal. The first relationship is estimated.

  According to the signal processing device having such a configuration, the predetermined second relationship can be easily obtained, and thus the predetermined first relationship can also be easily obtained.

  Moreover, in the above-described signal processing device, the signal generation unit is configured to generate the first signal based on the second relationship estimated by the estimation unit, the first time series signal, and the second time series signal. A period determination signal that is estimated to have the same period as the period of the component is generated, the period of the first signal component or the period of the second signal component is obtained from the period of the period determination signal, and the obtained period is It is characterized by a delay time.

  According to the signal processing device having such a configuration, the delay signal is generated with an appropriate delay time, and therefore it is possible to obtain a more accurate predetermined second relationship between the first noise component and the second noise component. .

  Further, in the above-described signal processing device, the signal generation unit may calculate from the period of the period determination signal when the degree of fluctuation of the period of the period determination signal is within the predetermined range in the first predetermined time range. The obtained time is set as the delay time.

  According to the signal processing device having such a configuration, the delay signal is generated with a more reliable delay time, and therefore, a more accurate predetermined second relationship between the first noise component and the second noise component can be obtained. It becomes possible.

  Moreover, in the above-described signal processing device, the estimation unit may perform the method different from the method according to any one of claims 1 to 3 when the degree of fluctuation of the period of the period determination signal is out of a predetermined range. The second relationship is calculated.

  Moreover, in the above-described signal processing device, the estimation unit indicates that the reliability of the second relationship and / or the first relationship is low when the degree of fluctuation of the cycle of the cycle determination signal is out of a predetermined range. A warning is output.

  According to the signal processing apparatus having such a configuration, when the degree of fluctuation of the period of the periodicity determination signal is not within a predetermined range, there is a high possibility that the delay time cannot be set appropriately, and therefore the second relationship However, there is a high possibility that the second relationship is not properly estimated. Therefore, the second relationship is estimated by a conventional method such as the method of Patent Document 1 in which the second relationship can be accurately estimated although the calculation amount is slightly increased. An appropriate delay time can be determined by estimating the period of the first signal component from the second relationship, the first time series signal, and the second time series signal. Also, a warning can be performed.

  Moreover, in the above-described signal processing device, the estimation unit includes information on a ratio between the first noise component and the first signal component as an index for determining whether to calculate the second relationship. An index is calculated, and when the index is compared with a predetermined threshold and it is determined that the first noise component is small, the index is directly expressed by the first time-series signal and the second time-series signal. The first relationship is estimated using a relational expression.

  According to the signal processing apparatus having such a configuration, when the magnitude of the first noise component or the second noise component is smaller than the magnitude of the first signal component or the second signal component, the first relationship is determined. Therefore, it can be determined that it is not necessary to determine the second relationship. In this case, the first relationship can be directly determined by a known conventional method with a small amount of calculation. From this predetermined first relationship, the oxygen saturation, which is biological information, can be obtained. Note that the relational expression directly expressed by the first time series signal and the second time series signal is one calculation formula having the first time series signal and the second time series signal as elements. (Refer to formula (31) and the like to be described later), which means that the calculation formula derived indirectly using a plurality of calculation formulas having the first time series signal and the second time series signal as elements is excluded.

  The signal processing apparatus may further include an output unit that outputs a reliability level, and the estimation unit further calculates a noise reliability level indicating an error level included in the second relationship, and the noise reliability level is calculated. When a predetermined threshold value is exceeded, the output unit outputs a warning indicating that the noise reliability has exceeded a predetermined threshold value.

  According to the signal processing device having such a configuration, since the reliability of the predetermined second relationship between the estimated first noise component and second noise component is determined, a warning may be output if the reliability is inferior. it can. In addition, the predetermined second relationship can be obtained by another method.

  In addition, the biological information measuring device according to one aspect of the present invention is obtained by irradiating a living body with a plurality of lights having different wavelengths and receiving each of the lights transmitted or reflected through the living body. A biological information measuring apparatus for measuring biological information of the living body based on measurement data or second measurement data, and measuring first measurement data including a first signal component having periodicity and a first noise component. Measure second measurement data including a first measurement unit, a second signal component having a predetermined first relationship with the first signal component, and a second noise component having a predetermined second relationship with the first noise component. A second measurement unit, a pulsation interval obtaining unit for obtaining an interval between pulsations of arterial blood of the living body, and the first measurement data and the second measurement data as the delay time. Late A signal generation unit that generates the first delay data that is the first measurement data and the second delay data that is the second measurement data delayed by the delay time; and a first predetermined time range. Using the first measurement data and the second measurement data, and the first delay data and the second delay data generated by the signal generation unit, the predetermined second in the first predetermined time range. And an estimation unit for estimating the relationship.

  According to the biological information measuring apparatus having such a configuration, it is possible to provide a biological information measuring apparatus that measures the blood oxygen saturation of the living body using the delay signal.

  In addition, since the calculation formula can be simplified by using the delay signal, it is possible to provide a biological information measuring apparatus that measures the blood oxygen saturation of a living body with reduced calculation processing amount and reduced power consumption. it can. In addition, since the amount of calculation processing is reduced, it is less necessary to provide a high-performance processing function, and it is possible to realize a reduction in price, size, and weight. Therefore, the biological information measuring device is not only for operating rooms, intensive care units, etc., but also for respiratory failure patients, home oxygen therapy patients in daily life respiratory data collection and management, sleep apnea syndrome screening, It is possible to provide a biological information measuring device that realizes downsizing, weight reduction, power saving, price reduction, etc. corresponding to the current situation that is being used even for sports wear such as mountain climbing. .

  Further, in the above-described biological information measuring device, the pulsation interval obtaining unit obtains the pulsation interval of arterial blood of the living body based on data obtained from the outside of the own device.

  In the biological information measuring apparatus having such a configuration, a more accurate heartbeat cycle can be acquired from the outside, so that a delay signal can be generated with an appropriate delay time.

  The biological information measuring apparatus may further include an output unit that outputs reliability, and the signal generation unit may include the second relationship estimated by the estimation unit, the first measurement data, and the second measurement data. And generating a period determination signal estimated to have the same period as the period of the first signal component, obtaining the period of the first signal component from the period of the period determination signal, and acquiring the beat interval When the difference between the interval obtained by the unit and the cycle of the cycle determination signal is greater than or equal to a predetermined value, the output unit outputs a warning indicating that the difference has exceeded a predetermined value .

  In the biological information measuring device having such a configuration, when there is a difference in period, it can be determined that the predetermined second relationship estimated by the estimation unit is not appropriate, and thus a warning can be output when the appropriateness is inferior. In addition, the predetermined second relationship can be obtained by another method.

  The signal processing device, the signal processing method, and the biological information measurement device according to the present invention are devices using a new technology for removing noise components, and can reduce the amount of signal processing necessary for noise component removal. Thus, it is possible to suppress power consumption accompanying signal processing for noise component removal.

It is a block diagram which shows the structure of the biological information measuring device in embodiment. It is a flowchart (the 1) which shows the biometric information measurement process which acquires the pulse cycle from the outside in the biometric information measuring apparatus of embodiment. It is a flowchart (the 2) which shows the biometric information measurement process which acquires the pulse cycle from the outside in the biometric information measuring apparatus of embodiment. It is a flowchart (the 1) which shows the biometric information measurement process which acquires the pulse period from a pulse wave signal in the biometric information measuring apparatus of embodiment. It is a flowchart (the 2) which shows the biometric information measurement process which acquires the pulse period from a pulse wave signal in the biometric information measuring apparatus of embodiment.

The prior art and embodiments that are the premise of the present invention will be described below. For convenience, a biological information measuring device is taken as an example of signal processing devices, but the present invention is applicable not only to a biological information measuring device but also to a signal processing device that removes noise components.
<Principle of the present invention>
First, the principle of the present invention will be described. In this description, as an example, based on measurement data obtained by irradiating a living body with a plurality of lights having different wavelengths IR and R, respectively, and receiving or transmitting each light transmitted or reflected by the living body. A case where blood oxygen saturation is measured as the biological information of the living body will be described.

  According to Lambert-Beer's law, the ratio of the alternating current component to the direct current component in the intensity of light having a certain wavelength transmitted or reflected through living tissue is approximated to be equal to the change in absorbance of the living tissue at that wavelength.

  By using the Lambert-Beer law approximation described above, the infrared orthogonal ratio IR_signal, which is the ratio of the direct current component and the alternating current component of the transmitted or reflected light intensity for the infrared wavelength IR, It can be regarded as equal to the change in the absorbance of the tissue. Similarly, the red orthogonal ratio R_signal, which is the ratio of the direct current component to the alternating current component of the intensity of transmitted light or reflected light for the red wavelength R, may also be regarded as equal to the change in the absorbance of the living tissue for the wavelength R. it can.

  The infrared orthogonal ratio IR_signal is expressed as shown in Equation (1).

Here, s is a signal component corresponding to a change in absorbance, and n is a noise component superimposed on the signal component.

  The red orthogonal ratio R_signal is expressed by Expression (2).

Where k_a is the ratio of the signal component s of the absorbance change at the wavelength IR to the signal component of the absorbance change at the wavelength R, and k_v is the noise component n and the wavelength superimposed on the signal component of the wavelength IR. This is the ratio of the noise component superimposed on the R signal component.

  It is known that k_a and arterial blood oxygen saturation in the formula (2) correspond one-to-one, and the arterial oxygen saturation can be obtained by obtaining k_a.

  Further, the equation (3) is obtained by multiplying the equation (1) by k_v, and the following equation (4) is obtained by subtracting the equation (2) from the equation (3).

  Similarly, equation (5) is obtained by multiplying the above equation (1) by k_a, and the following equation (6) is obtained by subtracting equation (2) from equation (5).

Here, the relationship that the signal component s and the noise component n are independent, that is, the following relational expression (7) is used, and under the condition that k_a and k_v are constant within a short time ( Equation (8) is obtained by correlating equations 4) and (6).

Here, Σ is the sum for a short time such that k_a and k_v are constant. i is the data number of the time-series data IR_signal and R_signal corresponding to the change in the intensity of light, and the measurement time interval of the data is Δt, the measurement start time is t0, and t = Δt * i + t0 Tied.
Since Equation (8) contains two unknowns k_v and k_a, k_a and k_v cannot be obtained from Equation (8) alone.

Here, if k_v can be obtained, the obtained k_v is substituted into the equation (8) to obtain k_a when the equation (8) is satisfied, and based on this k_a, blood oxygen with reduced noise components is obtained. Saturation can be determined.
<Embodiment>
In the present embodiment, k_v is obtained by using delayed signals of IR_signal and R_signal, and the amount of calculation processing at that time is greatly reduced as compared with the prior art.

  Here, how to obtain k_v will be described. In this embodiment, two ways of obtaining are shown.

  First, the first method of obtaining will be described. Hereinafter, in the formula, IR_signal and R_signal are described as IR and R, respectively.

  V_IR, V_R, and V_R_IR at a certain time T are defined as follows. These are obtained by performing a predetermined calculation on a certain signal and the signal itself or another signal. N is the number of data necessary for the calculation of the oxygen saturation, for example, a value of 200 or the like, and is the number of data measured for a predetermined period, for example, 6 seconds, going back from the time T. T is an index of measurement data measured continuously. Further, Σ is a sum taken from 1 to N with respect to j, and the subscript j represents the j-th measurement data among N pieces of measurement data. Hereinafter, V_IR, V_R, and V_R_IR are collectively referred to as correlation data.

V_IR = ΣIR (j) ² (11 ′)
= Σs (j) ² + Σn (j) ² + 2 * Σs (j) * n (j) (11)
V_R = ΣR (j) ² (12 ′)
= ka ² * Σs (j) ² + kv ² * Σn (j) ² + 2 * ka * kvΣs (j) * n (j) (12)
V_R_IR = ΣR (j) * IR (j) (13 ′)
= ka * Σs (j) ² + kv * Σn (j) ² + (ka + kv) * Σs (j) * n (j) (13)
Next, V_IR_τ, V_R_τ, and V_R_IR_τ at time T are defined as follows. These are obtained by performing a predetermined calculation on a certain signal and a signal obtained by delaying the signal itself or another signal by τ time. The delay time τ corresponds to the pulse period and is indicated by the number of indexes of the measurement data. Specifically, the calculation is performed using N data retroactive from time T and N data retroactive from time (T-τ). Hereinafter, V_IR_τ, V_R_τ, and V_R_IR_τ are collectively referred to as delayed correlation data.

V_IR_τ = ΣIR (j) * IR (j−τ) (14 ′)
= Σs (j) * s (j-τ) + Σn (j) * n (j-τ)
+ 2 * {Σs (j) * n (j−τ) + Σn (j) * s (j−τ)} / 2 (14)
V_R_τ = ΣR (j) * R (j−τ) (15 ′)
= ka ² * Σs (j) * s (j-τ) + kv ² * Σn (j) * n (j-τ)
+ 2 * ka * kv * {Σs (j) * n (j-τ) + Σn (j) * s (j-τ)} / 2 (15)
V_R_IR_τ = {ΣR (j) * IR (j−τ) + ΣIR (j) * R (j−τ)} / 2 (16 ′)
= ka * Σs (j) * s (j-τ) + kv * Σn (j) * n (j-τ)
+ (ka + kv) * {Σs (j) * n (j−τ) + Σn (j) * s (j−τ)} / 2 (16)
here,
Vs = Σs (j) ²
Vn = Σn (j) ²
Csn = Σs (j) * n (j)
Vs_τ = Σs (j) * s (j-τ)
Vn_τ = Σn (j) * n (j-τ)
Csn_τ = {Σs (j) * n (j-τ) + Σn (j) * s (j-τ)} / 2
Is expressed as follows: (11) to (16) can be expressed as follows.

V_IR = Vs + Vn + 2 * Csn (11A)
V_R = ka ² * Vs + kv ² * Vn + 2 * ka * kv * Csn (12A)
V_R_IR = ka * Vs + kv * Vn + (ka + kv) * Csn (13A)
V_IR_τ = Vs_t + Vn_τ + 2 * Csn_τ (14A)
V_R_τ = ka ² * Vs_τ + kv ² * Vn_τ + 2 * ka * kv * Csn_τ (15A)
V_R_IR_τ = ka * Vs_τ + kv * Vn_τ + (ka + kv) * Csn_τ (16A)
Next, the difference between the correlation data and the delayed correlation data is obtained.

V_IR-V_IR_τ = {Vs-Vs_τ} + {Vn-Vn_τ} + 2 * {Csn-Csn_τ} (17)
V_R-V_R_τ = ka ² * {Vs-Vs_τ} + kv ² * {Vn-Vn_τ} + 2 * ka * kv * {Csn-Csn_τ}… (18)
V_R_IR-V_R_IR_τ = ka * {Vs-Vs_τ} + kv * {Vn-Vn_τ} + (ka + kv) * {Csn-Csn_τ}… (19)
Here, when τ is approximately equal to the period of s and the product-sum time is approximately an integral multiple of the period, the signal component s due to the heartbeat has substantially the same waveform as the signal component shifted by the period of the pulse, so that A relationship is established.

Vs-Vs_τ ≒ 0
Applying this relationship to Equation (17), Equation (18), and Equation (19) gives the following.

V_IR-V_IR_τ≈ {Vn-Vn_τ} + 2 * {Csn-Csn_τ} (17A)
V_R-V_R_τ≈kv ² * {Vn-Vn_τ} + 2 * ka * kv * {Csn- {Csn_τ} (18A)
V_R_IR-V_R_IR_τ≈kv * {Vn-Vn_τ} + (ka + kv) * {Csn-Csn_τ} (19A)
here,
V_IR-V_IR_τ = dV_IR
V_R-V_R_τ = dV_R
V_R_IR-V_R_IR_τ = dV_R_IR
The following two equations (20) and (21) using the equations (17A), (18A), and (19A) are considered.

(18A) -kv * (19A) = dV_R-kv * dV_R_IR (20)
= (2 * ka * kv-ka * kv-kv ² ) * {Csn-Csn_τ}
= -kv * (kv-ka) * {Csn-Csn_τ}
(19A) -kv * (17A) = dV_R_IR-kv * dV_IR (21)
= (ka + kv-2 * kv) * {Csn-Csn_τ}
=-(kv-ka) * {Csn-Csn_τ}
From the equations (20) and (21), the following equations are derived:
(dV_R-kv * dV_R_IR) / (dV_R_IR-kv * dV_IR) = kv
(kv * dV_IR-dV_R_IR) * kv-kv * dV_R_IR + dV_R = 0
Thus, the following equation (22) is derived.

kv ² * dV_IR-2 * kv * dV_R_IR + dV_R = 0 (22)
Solving this equation (22)
kv = {dV_R_IR ± (dV_R_IR ² -dV_IR * dV_R) ^0.5 } / dV_IR
Is obtained. Let these two solutions be kv_m and kv_p.

{dV_R_IR- (dV_R_IR ² -dV_IR * dV_R) ^0.5 } / dV_IR = kv_m (23)
{dV_R_IR + (dV_R_IR ² -dV_IR * dV_R) ^0.5 } / dV_IR = kv_p (24)
Since these errors are approximately the same, the larger kv_p and kv_m are used as the estimated value kv_es of k_v so that the ka estimated value becomes a positive error.

  Next, the second method of obtaining will be described.

Vs-Vs_τ = dVs
Csn-Csn_τ = dCsn
Vn-Vn_τ = dVn
And When dCsn is negligible in the above formula (17), formula (18), and formula (19)
dV_IR≈dVn (17B)
dV_R≈kv ² * dVn (18B)
dV_R_IR≈kv * dVn (19B)
It becomes. From these equations (17B), (18B), and (19B), three types of k_v, that is, kv_1, kv_2, and kv_3 can be obtained.

kv_1 = dV_R / dV_R_IR (25)
kv_2 = dV_R_IR / dV_IR (26)
kv_3 = {dV_R / dV_IR} ^0.5 (27)
Of these three, kv_1 has a small error, and this is used as an estimated value kv_es of k_v in the embodiment.

  DESCRIPTION OF EXEMPLARY EMBODIMENTS Hereinafter, an embodiment of the invention will be described with reference to the drawings. In addition, the structure which attached | subjected the same code | symbol in each figure shows that it is the same structure, The description is abbreviate | omitted suitably.

<Configuration>
FIG. 1 is a diagram illustrating a configuration of a biological information measurement device according to an embodiment. The solid line in the figure represents the main flow among the blocks of electric signal components corresponding to the pulse-series time-series data described later.

  The biological information measuring apparatus 100 in the embodiment is an apparatus that measures biological information related to a living body by measuring a physiological phenomenon of the living body that is a measurement target. The biological information is, for example, a pulse rate and blood oxygen saturation. Such biological information can be obtained by using a fluctuation component in the amount of transmitted or reflected light of biological tissue caused by pulsation of arterial blood, and the basic principle is described in the above section <Principle of the present invention>. Street.

  For example, as shown in FIG. 1, such a biological information measuring apparatus 100 measures a predetermined physiological phenomenon of a living body and outputs measurement data, and the measurement data measured by the sensor unit 40. Based on, for example, a calculation control unit 10 that calculates biological information such as a pulse rate and blood oxygen saturation, and a display unit 30 that displays the biological information calculated by the calculation control unit 10 so as to be recognized from the outside. Is done.

  The sensor unit 40 is connected to the arithmetic control unit 10, and in this embodiment, is a device that measures information related to blood in a living tissue as a physiological phenomenon of the living body. More specifically, the sensor unit 40 is a device that measures, as a physiological phenomenon of a living body, a fluctuation component in the amount of transmitted or reflected light of a living tissue caused by pulsation of arterial blood due to a heartbeat.

  As a method for measuring the physiological phenomenon of the living body, for example, a method using the light absorption characteristic of hemoglobin in the living tissue can be mentioned. Oxygen is transported to each cell of the living body by hemoglobin, but hemoglobin combines with oxygen in the lung to become oxygenated hemoglobin, and returns to hemoglobin (reduced hemoglobin) when oxygen is consumed in the cells of the living body. Blood oxygen saturation is defined as the percentage of oxyhemoglobin in the blood (in the blood). The absorbance of each of these hemoglobin and oxyhemoglobin has a wavelength dependency, and hemoglobin absorbs more light than oxyhemoglobin for red light (red wavelength region light), for example, while infrared light (infrared light) Less light is absorbed than oxyhemoglobin. In other words, when hemoglobin is oxidized to oxygenated hemoglobin, the absorption of red light decreases and the absorption of infrared light increases. Conversely, when it is reduced to return to hemoglobin, the absorption of red light increases and the absorption of infrared light increases. It has an optical property that absorption is reduced. The biological information measuring apparatus 100 according to the present embodiment uses such a difference in light absorption characteristics of hemoglobin and oxyhemoglobin with respect to red light and infrared light, for example, a living body such as a pulse rate and blood oxygen saturation. It seeks information.

  Because of such a method, the sensor unit 40 of the present embodiment measures, for example, a sensor (R) unit 41 that measures the light absorption characteristics in the biological tissue with respect to red light, and the light absorption characteristics in the biological tissue with respect to infrared light. A sensor (IR) unit 42 is provided, and is connected to the calculation control unit 10. The sensor (R) unit 41 includes, for example, an R light emitting element such as a light emitting diode that irradiates the biological tissue with red light having a wavelength λ1, and a red light that is irradiated with the R light emitting element and transmitted or reflected by the biological tissue. For example, the sensor (IR) unit 42 irradiates the living tissue with infrared light having a wavelength λ2 different from the wavelength λ1, for example, a light emitting diode. And an IR light receiving element such as a silicon photodiode that receives infrared light that is irradiated by the IR light emitting element and transmitted or reflected by the biological tissue. The sensor unit 40 can use such a transmission type or reflection type sensor.

  The sensor unit 40 is set in a predetermined living tissue such as a finger, an earlobe, or the back of the hand, wrist, or foot of an infant, and measured by the sensor (R) unit 41 and the sensor (IR) unit 42. The measured data is output to the calculation control unit 10. More specifically, in the sensor (R) unit 41 having such a configuration, the R light emitting element irradiates the biological tissue with red light, and the R light receiving element uses the R light emitting element to transmit the biological tissue. The red light R that is transmitted or reflected through the biological tissue of the red light irradiated on the light is received, and the received red light is photoelectrically converted, so that an electric signal corresponding to the amount of the received light is used as the measurement data as an arithmetic control unit. 10 is output. Similarly, in the sensor (IR) unit 42, the IR light emitting element irradiates the biological tissue with infrared light, and the IR light receiving element irradiates the biological tissue with the infrared light. Infrared light transmitted or reflected through the living tissue is received, and the received infrared light is photoelectrically converted to output an electrical signal corresponding to the received light amount to the arithmetic control unit 10 as the measurement data.

  The arithmetic control unit 10 is connected to the display unit 30 and is a device that obtains biological information based on measurement data measured by the sensor unit 40 and controls the entire biological information measuring device 100. The arithmetic control unit 10 acquires time-series data of measurement data from the sensor unit 40 by, for example, sampling measurement data measured by the sensor unit 40 at a predetermined sampling period (for example, a frequency of 37.5 Hz). is there. Further, for example, the arithmetic control unit 10 acquires measurement data from the sensor unit 40 as time series data by driving the sensor unit 40 at a predetermined cycle, that is, by causing each operation of light emission and light reception to be performed. Further, for example, the sensor unit 40 samples the measurement data as time-series data by sampling at a predetermined sampling period, and outputs the measurement data of the time-series data to the arithmetic control unit 10. The measurement data may be analog data. However, in the present embodiment, the measurement data is digital data. Conversion from analog data to digital data (AD conversion) is performed by the sensor unit 40 or the arithmetic control unit 10. Further, if necessary, the sensor unit 40 or the calculation control unit 10 may further include an amplification unit that amplifies the measurement data before AD conversion.

  More specifically, the arithmetic control unit 10 obtains predetermined biological information related to the measurement target biological body based on the measurement data measured by the sensor unit 40, and includes, for example, a microprocessor, a memory, and its surroundings. It is comprised by the microcomputer provided with a circuit. The memory includes various programs such as a biological information calculation program for obtaining biological information based on measurement data measured by the sensor unit 40, a control program for controlling the entire biological information measuring device 100, and a sensor unit. For example, an EEPROM (Electrically Erasable Programmable Read Only Memory), which is a rewritable non-volatile memory element, or a non-volatile memory that stores various data such as the measurement data measured at 40 and data necessary for the execution of the program. A ROM (Read Only Memory) which is an element, and a RAM (Random Access Memory) which is a so-called working memory of the microprocessor, for example, which is a volatile storage element, is configured. Central Processing Unit) etc., by executing the program Functionally, for example, an AC / DC (R) unit 11, an AC / DC (IR) unit 12, a BPF (R) unit 13, a BPF (IR) unit 14, an R correlation calculation unit 15, and an IR Correlation calculator 16, cross-correlation calculator 17, R delay correlation calculator 18, IR delay correlation calculator 19, cross delay correlation calculator 20, kv initial value calculator 21, kv calculator 22 , An SpO2 calculating unit 23, a pulse rate calculating unit 24, a τ calculating unit 25, a periodic stability determining unit 26, a reliability calculating unit 27, and subtracting units 28A, 28B, and 28C.

The AC / DC (R) unit 11 and the AC / DC (IR) unit 12 perform predetermined preprocessing on the measurement data input from the sensor unit 40. More specifically, the AC / DC (R) unit 11 corrects the dark current in the R light receiving element with respect to the measurement data related to the red light input from the sensor (R) unit 41, so-called dark. Then, a first ratio (red light _AC / DC ratio) R (= R _AC / R _DC ) of the _AC component R _AC with respect to the DC component R _DC is calculated, and this first ratio R is calculated by the BPF (R) unit 13. Notification (output).

The AC / DC (IR) unit 12 performs so-called dark processing for correcting dark current in the IR light receiving element on the measurement data related to infrared light input from the sensor (IR) unit 42. Then, a second ratio (infrared light _AC / DC ratio) IR (= IR _AC / IR _DC ) of the _AC component IR _AC with respect to the DC component IR _DC is calculated, and the second ratio IR is notified to the BPF (IR) unit 14. (Output. For the dark process, a known method is used. For example, an output value (dark current value) Rdark output from the R light receiving element in a light-shielded state is subtracted from the measurement data related to the red light, and the infrared light is subtracted from the infrared light. This is performed by subtracting the output value (dark current value) IRdark output from the IR light receiving element in the light shielding state from the measurement data concerned. The output values Rdark and IRdark output from the light-receiving R light-receiving element and the IR light-receiving element are measured in advance.

  The BPF (R) unit 13 and the BPF (IR) unit 14 are filters for removing predetermined noise components from the measurement data measured by the sensor unit 40, and fluctuations in the amount of transmitted or reflected light in the living tissue caused by pulsation of arterial blood. It removes frequency components other than the frequency components normally included as components.

  The BPF (R) unit 13 is a filter having a predetermined frequency band including a frequency component normally included as a variation component in the amount of transmitted or reflected light of biological tissue caused by arterial blood pulsation with respect to red light as a pass band. The ratio R is filtered (filtered), and R_signal which is the first ratio R time-series data after the filtering is notified to each of the R correlation calculating unit 15 to kv initial value calculating unit 21 and the pulse rate calculating unit 24. .

  The BPF (IR) unit 14 is a filter having a predetermined frequency band including a frequency component that is normally included as a fluctuation component in the amount of transmitted or reflected light of living tissue caused by pulsation of arterial blood with respect to infrared light as a pass band. 2 ratio IR is filtered (filtered), and the second ratio IR after the filtering is notified to each of the R correlation calculating unit 15 to kv initial value calculating unit 21 and the pulse rate calculating unit 24 as time series data IR_signal. .

  The R correlation calculation unit 15 calculates the correlation data V_R of R_signal related to red light using the equation (12 ′), and uses the calculated correlation data V_IR as the subtraction unit 28A, the kv initial value calculation unit 21, and the reliability calculation. This is notified to each unit of the unit 27.

  The IR correlation calculation unit 16 calculates IR_signal correlation data V_IR related to infrared light using the equation (11 ′), and uses the calculated correlation data V_IR as the subtraction unit 28B, the kv initial value calculation unit 21, and the reliability. This is notified to each unit of the calculation unit 27.

  The cross-correlation calculation unit 17 calculates correlation data V_R_IR between R_signal related to red light and IR_signal related to infrared light using Expression (13 ′), and the calculated correlation data V_R_IR is subtracted by the subtraction unit 28C, kv initial This is notified to each of the value calculation unit 21 and the reliability calculation unit 27.

  The R delay correlation calculation unit 18 calculates the delay correlation data V_R_τ of R_signal using the equation (15 ′), and notifies the calculated delay correlation data V_R_τ to the subtraction unit 28A.

  The IR delay correlation calculation unit 19 calculates the delay correlation data V_IR_τ of IR_signal using the equation (14 ′), and notifies the subtraction unit 28B of the calculated delay correlation data V_IR_τ.

  The cross delay correlation calculation unit 20 calculates the delay correlation data V_R_IR_τ between R_signal and IR_signal using the equation (16 ′), and notifies the subtraction unit 28C of the calculated delay correlation data V_R_IR_τ.

  The IR_signal, R_signal, correlation data, and delay correlation data calculated by the BPF (R) unit 13 to the cross delay correlation calculation unit 20 are stored in the memory and can be referred to from other functional units.

  The subtractor 28A calculates a result dV_R obtained by subtracting the delayed correlation data V_R_τ calculated by the R delay correlation calculator 18 from the correlation data V_R calculated by the R correlation calculator 15 (see the left side of Expression (18)). The calculated difference dV_R is notified to the kv calculation unit 22.

  The subtractor 28B calculates a result dV_IR obtained by subtracting the delayed correlation data V_IR_τ calculated by the IR delayed correlation calculator 19 from the correlation data V_IR calculated by the IR correlation calculator 16 (see the left side of Expression (17)). The calculated difference dV_IR is notified to the kv calculation unit 22.

  The subtractor 28C calculates a result dV_R_IR obtained by subtracting the delayed correlation data V_R_IR_τ calculated by the cross delay correlation calculator 20 from the correlation data V_R_IR calculated by the cross correlation calculator 17 (see the left side of Expression (19)). The calculated difference dV_R_IR is notified to the kv calculation unit 22.

  The kv calculation unit 22 uses the difference dV_R calculated by the subtraction unit 28A, the difference dV_IR calculated by the subtraction unit 28B, and the difference dV_R_IR calculated by the subtraction unit 28C, among the equations (25), (26), and (27). Kv_es is calculated using any one of the above, and the calculated kv_es is notified to the SpO2 calculation unit 23. In this embodiment, Formula (25) is used.

  The kv initial value calculation unit 21 includes an R_signal calculated by the BPF (R) unit 13, an IR_signal calculated by the BPF (IR) unit 14, an R_signal correlation data V_R calculated by the R correlation calculation unit 15, and an IR correlation calculation unit 16 Based on the calculated correlation data V_IR of IR_signal and the correlation data V_R_IR between R_signal and IR_signal calculated by the cross-correlation calculation unit 17, an estimated value kv_es of k_v is calculated using a conventional technique. For example, kv_es is calculated using the following equation.

P (ω) = P [{IR_signal * k_v-R_signal} ^2- (1 / N) Σ {IR_signal * k_v-R_signal} ² ]
Here, P is a Fourier transform, and ω is a frequency. Using the peak height / peak width of P (ω) as an index, k_v is obtained from ω that maximizes the peak height and set as kv_es. Moreover, you may calculate by another method. For example, k_a may be obtained from the ratio of the autocorrelation and cross-correlation of R_signal and IR_signal using any one of the following equations (31), (32), and (33), and k_v may be obtained from k_a. .

  The SpO2 calculation unit 23 calculates the estimated value ka_es of k_a from the kv_es obtained by the kv calculation unit 22 using the following formula (28) or formula (29).

ka_es = {kv * V_R_IR-V_R} / {kv * V_IR-V_R_IR}… (28)
ka_es = {kv * V_R_IR_τ-V_R_τ} / {kv * V_IR_τ-V_R_IR_τ}… (29)
Then, the oxygen saturation SpO ₂ of venous blood is obtained from ka_es, and the obtained oxygen saturation SpO ₂ is notified to the display unit 30. Although the pulse wave signal is described as an original waveform, it may be a time difference waveform.

Further, when the SpO2 calculation unit 23 receives a notification from the cycle stability determination unit 26 that the cycle is not stable, the larger of kv_m and kv_p calculated using the equations (13) and (14) Is calculated as kv_es, an estimated value ka_es of k_a is calculated, and oxygen saturation SpO ₂ of venous blood is calculated.

  The pulse rate calculation unit 24 obtains the pulse rate from R_signal calculated by the BPF (R) unit 13, IR_signal calculated by the BPF (IR) unit 14, and kv_es calculated by the kv calculation unit 22 or the kv initial value calculation unit 21. The display unit 30 is notified, and the pulse rate and the cycle determination signal (the signal represented by the left side of the following equation (30)) are output to the cycle stability determination unit 26. More specifically, since the following equation (30) (same as equation (4)) holds, the pulse rate calculation unit 24 calculates the period of R (j) -kv_es * IR (j) within a predetermined time. The average value is calculated.

R (j) -kv_es * IR (j) ≈ (ka-kv) * s (j) (j = i- (N-1) to i) (30)
Then, the pulse rate is obtained as the reciprocal of the cycle. In calculating the period, either the differential waveform or the original waveform can be used, but the original waveform is desirable.

  In <first operation> described later, an electrocardiogram signal or the like is acquired from the outside, a pulse cycle is obtained from the electrocardiogram signal or the like, and the pulse rate obtained from the obtained pulse cycle is output to the τ calculator 25. (Indicated by a dotted line in FIG. 1).

  When the cycle stability determination unit 26 receives the pulse rate and the cycle determination signal from the pulse rate calculation unit 24, the cycle stability determination unit 26 determines the stability of the cycle of the cycle determination signal. Is notified to the τ calculation unit 25, and if the stability is not acceptable, the SpO2 calculation unit 23 is notified of this. The determination of the stability is based on the variation of each cycle of the cycle determination signal within a predetermined range, for example, a value obtained by subtracting the minimum value from the maximum value of the cycle within a predetermined time (T_PR) is equal to or less than the predetermined value, and the average cycle Is determined to be stable when the deviation from the previous average period is within a predetermined range. If the period is stable, it can be determined that kv_es can be properly estimated.

  In addition, when the heartbeat cycle can be obtained from an external electrocardiogram signal or the like, if the difference from the cycle of the signal acquired by the biological information measuring device 100 from the pulse rate calculation unit 24 is equal to or greater than a predetermined value, the stable In other words, it may be determined that kv_es has not been properly estimated. Moreover, the period stability determination part 26 is good also as displaying a warning etc. on the display part 30, when a period is not stable.

  The τ calculating unit 25 calculates τ, that is, an index of measurement data, from the pulse rate calculated by the periodic stability determination unit 26 (pulse rate calculating unit 24 in <first operation> described later) and the sampling period of the measurement data. And the calculated τ is notified to each of the R delay correlation calculation unit 18, the IR delay correlation calculation unit 19, and the mutual delay correlation calculation unit 20.

  The reliability calculation unit 27 includes the oxygen saturation calculated by the SpO2 calculation unit 23, the correlation data V_R calculated by the R correlation calculation unit 15, the correlation data V_IR calculated by the IR correlation calculation unit 16, and the cross correlation calculation unit 17 A predetermined reliability is calculated based on V_R_IR calculated by the above, and the calculated reliability is output to the display unit 30.

  The reliability is an index (degree) indicating how reliable the calculated value related to biological information is. Such reliability can be obtained by any of the following formulas (B1) to (B6), for example. In the reliability z obtained by such an equation, the reliability of the blood oxygen saturation level decreases as the absolute value of the value z increases.

z = (ΣR (j) * IR (j)) / (Σ {IR (j)} ² )-(Σ {R (j)} ² ) / (ΣR (j) * IR (j)) ・ ・ ・(B1)
z = (Σ {IR (j)} ² ) / (ΣR (j) * IR (j))-[(Σ {R (j)} ² ) / (Σ {IR (j)} ² )] ^2. .. (B2)
z = (Σ {R (j)} ² ) / (Σ {IR (j)} ² )-[(ΣR (j) * IR (j)) / (Σ {IR (j)} ² )] ²・.. (B3)
z = [(1 / N) * ΣR (j) / IR (j)] ² − (Σ {R (j)} ² ) / (Σ {IR (j)} ² ) (B4)
z = (ΣR (j) * IR (j)) / (Σ {IR (j)} ² )-(1 / N) * ΣR (j) / IR (j) (B5)
z = (Σ {R (j)} ² ) / (ΣR (j) * IR (j))-(1 / N) * ΣR (j) / IR (j) (B6)
In addition, the reliability calculation unit 27 may calculate the reliability of k_a or the reliability of k_v as appropriate. The reliability of k_a is a value that represents the degree of error included in k_a, and similarly, the reliability of k_v is a value that represents the degree of error included in k_v.

  The display unit 30 is a device that displays (outputs) the operating state of the biological information measuring device 100, biological information obtained by the arithmetic control unit 10, and the like, for example, a liquid crystal display device (LCD), an organic EL display device, A printer or the like. In this embodiment, for example, the display unit 30 includes a pulse rate output unit 32 that displays the pulse rate calculated by the pulse rate calculation unit 24, and an SpO2 output unit that displays the oxygen saturation calculated by the SpO2 calculation unit 23. 31 and a reliability output unit 33 that displays the reliability calculated by the reliability calculation unit 27. The reliability output unit 33 outputs a warning when the reliability calculated by the reliability calculation unit 27, for example, the reliability of k_a or the reliability of k_v exceeds the respective thresholds.

  The R delay correlation calculation unit 18, the IR delay correlation calculation unit 19, the cross delay correlation calculation unit 20, the SpO2 calculation unit 23, the τ calculation unit 25, the periodic stability determination unit 26, the subtraction unit 28, and the like solve the problem. The signal generation unit disclosed in the means for realizing the above is realized, and the estimation unit is realized by the kv initial value calculation unit 21, the kv calculation unit 22, the SpO2 calculation unit 23, the periodic stability determination unit 26, the reliability calculation unit 27, and the like. The

<Operation>
Next, the operation of the biological information measuring apparatus 100 of the embodiment will be described.

  Here, two operations will be described. There are cases where the pulse cycle can be acquired based on information such as an electrocardiogram signal from the outside of the biological information measuring apparatus 100 and when it cannot. In other words, when an accurate pulse period can be acquired based on information from the outside, the delay time τ can be easily obtained, but when it cannot be acquired, it is necessary to calculate the pulse period.

<First operation>
First, the case where a pulse cycle can be acquired based on information from the outside will be described. In this case, the pulse rate calculation unit 24 of the arithmetic control unit 10 does not calculate using the equation (30) as described above, but calculates the heartbeat cycle from the electrocardiogram signal.

  2 and 3 are flowcharts showing processing for obtaining oxygen saturation and pulse rate in the biological information.

  In the biological information measuring apparatus 100, for example, measurement of biological information of a living body to be measured is started by turning on a power switch (not shown) or turning on a measurement start switch (not shown) after turning on the power switch. The

  The arithmetic control unit 10 starts sampling the measurement data measured by the sensor unit 40 at a predetermined sampling period, and acquires time-series data of the measurement data from the sensor unit 40.

  Specifically, the sensor (R) unit 41 of the sensor unit 40 measures the measurement data Rsignallanddark (including dark current) related to red light and the dark current Rdark, and converts the analog signal into a digital signal. The sensor (IR) section 42 measures the measurement data IR signal (including dark current) related to infrared light and the dark current IR dark and converts the analog signal into a digital signal.

  Subsequently, the AC / DC (R) unit 11 of the display unit 30 performs dark processing (Rsignalland-Rdark) on the measurement data Rsignallandmark related to the red light input from the sensor (R) unit 41, and R_signal ( In FIG. 2, R_s (j) is calculated), and the AC / DC (IR) unit 12 calculates the IR measurement signal IRsignallandmark related to the infrared light input from the sensor (IR) unit 42. Dark processing (Rsignalland-Rdark) is executed, and IR_signal (indicated as IR_s (j) in FIG. 2) is calculated. Subsequently, the R_signal output from the AC / DC (R) unit 11 is filtered by the BPF (R) unit 13 and output from the AC / DC (IR) unit 12 by the BPF (IR) unit 14. The IR_signal is filtered and output to the R correlation calculation unit 15 to the mutual delay correlation calculation unit 20 and the like.

  The arithmetic control unit 10 initializes variables used in the process at the same time as starting sampling. Specifically, 0 (zero) is set in each of V_R_int, V_IR_int, V_R_IR_int, V_IR_τ_int, V_R_τ_int, and V_R_IR_τ_int (step S10). V_R_int, V_IR_int, and V_R_IR_int correspond to the correlation data V_IR, V_R, and V_R_IR, respectively. V_IR_τ_int, V_R_τ_int, and V_R_IR_τ_int correspond to the delayed correlation data V_IR_τ, V_R_τ, and V_R_IR_τ, respectively. Further, 0 (zero) is set to the arrays V_R (m), V_IR (m), V_R_IR (m), V_R_τ (m), V_IR_τ (m), and V_R_IR_τ (m) of m = 0 to N−1 (step) S11). These arrays store data serving as a basis for calculating V_R_int, V_IR_int, V_R_IR_int, V_IR_τ_int, V_R_τ_int, and V_R_IR_τ_int, respectively.

  When the initialization is completed, the pulse rate calculation unit 24 calculates the pulse rate from the electrocardiogram signal, and outputs the calculated pulse rate to the τ calculation unit 25. In addition, the pulse rate calculation unit 24 outputs the calculated pulse rate to the pulse rate output unit 32 of the display unit 30 (step S12). The pulse rate output unit 32 displays the acquired pulse rate.

  The τ calculation unit 25 that has acquired the pulse rate calculates the delay time τ, that is, the number of indexes of the measurement data, from the pulse period, and the R delay correlation calculation unit 18, the IR delay correlation calculation unit 19, and the mutual delay correlation calculation unit 20 (Step S13).

The R correlation calculation unit 15 to the cross delay correlation calculation unit 20 obtain R_signal or IR_signal from the BPF (R) unit 13 or the BPF (IR) unit 14 (step S14), and calculate each correlation value and delay correlation value. (Step S15). That, is calculated by R correlation calculating section 15 R_signal (j) ² is set to V_R (j), is set is calculated by IR correlation calculating unit 16 IR_signal (j) ² is the V_IR (j), IR correlation R_signal (j) * IR_signal (j) is calculated by the calculation unit 16 and set to V_R_IR (j). Also, R_signal (j) * R_signal (j-τ) is calculated by the R delay correlation calculation unit 18 and set to V_R_τ (j), and IR_signal (j) * IR_signal (j-τ) is set by the IR delay correlation calculation unit 19. Is set to V_IR_τ (j), and (R_signal (j) * IR_signal (j-τ) + R_signal (j-τ) * IR_signal (j)) / 2 is calculated by the mutual delay correlation calculation unit 20 Set to V_R_IR_τ (j).

  Until acquisition of the predetermined number of data (N) is completed (step S16: No), step S14 to step S16 are executed. When the predetermined number of data is acquired (step S16: Yes), m = 0 to N_1 adds V_R (m), V_IR (m), V_R_IR (m), V_R_τ (m), V_IR_τ (m), V_R_IR_τ (m), V_R_int, V_IR_int, V_R_IR_int, V_IR_τ_int, V_R_τ_int, V_R_IR_τ_int is calculated (step S17). Differences dV_R, dV_IR, and dV_R_IR are calculated by the subtraction units 28 </ b> A to 28 </ b> C and output to the kv calculation unit 22 from the data calculated by the R correlation calculation unit 15 to the cross delay correlation calculation unit 20. The kv calculation unit 22 calculates kv_es using Expression (25).

  Subsequently, the SpO2 calculating unit 23 determines whether or not kv_es_b or ka_es_b is indefinite, that is, whether or not kv_es or ka_es that is reliable even once has been measured (step S18). This determination can be made, for example, by setting a flag, or setting an initial value that cannot be in kv_es, etc., and determining that the value is indeterminate if it is not possible, or using a value measured in kv_es, etc. If it is set, a flag is set. If the flag is not set, it is determined that the flag is indefinite.

  If determined to be indefinite (step S18: Yes), the SpO2 calculation unit 23 sets kv_es calculated by the kv initial value calculation unit 21 using equation (31) or the like as kv_es_b, calculates ka_es, and ka_es_b (Step S19). When it is determined that it is not indefinite (step S18: No), kv_es calculated in the previous time is set in kv_es_b, and ka_es calculated in the previous time is set in ka_es_b.

  Subsequently, the SpO2 calculation unit 23 estimates an SN ratio that is a ratio of a signal component due to heartbeat and a noise component due to body motion from V_R_IR_int, V_IR_int, kv_es_b, and ka_es_b (step S20).

  Here, the S / N ratio is represented by the ratio between the intensity of the noise component and the intensity of the signal component, for example, as shown in Expression (34). Let the SN ratio be k_sn.

N_square, which is a value related to the intensity of the noise component, and s_square, which is a value related to the intensity of the signal component, are calculated by substituting kv_es_b and ka_es_b for k_v and k_a, respectively, using Expressions 35 and 36 below.

  When the S / N ratio is equal to or smaller than the predetermined value (step S21: Yes), that is, when the influence of noise is large, the SpO2 calculation unit 23 is configured such that the kv calculation unit 22 is represented by the formula (25), the formula (23), or the formula Kv_es calculated using (24) is acquired (step S23), ka_es is obtained from the acquired kv_es using equation (28) or equation (29) (step S24), and oxygen saturation SpO2 is calculated (step) S25).

  On the other hand, when the S / N ratio exceeds a predetermined value (step S21: No), that is, when the influence of noise is small, the SpO2 calculation unit 23 uses a conventionally known formula such as formula (31), formula (32), and formula (33). The ka_es is calculated by the method (step S22), and the arterial oxygen saturation SpO2 is calculated (step S25). Further, kv_es is calculated from the predetermined relationship α (ka_es) with ka_es (step S22). α (ka_es) is an equation related to the fact that the oxygen saturation of venous blood is, for example, 10% lower than the oxygen saturation of arterial blood.

  The SpO2 calculating unit 23 that has calculated the oxygen saturation SpO2 outputs the calculated oxygen saturation SpO2 to the SpO2 output unit 31, and the SpO2 output unit 31 displays the acquired oxygen saturation SpO2 (step S25).

  The SpO2 calculation unit 23 sets the calculated kv_es and ka_es to kv_es_b and ka_es_b, respectively (step S26).

  Subsequently, the reliability calculation unit 27 calculates a predetermined reliability, and the calculated reliability is output to the reliability output unit 33. The reliability output unit 33 displays or warns the acquired reliability ( Step S27). The reliability may be an amount corresponding to the difference between the heartbeat cycle based on the electrocardiogram signal and the pulse cycle obtained from the cycle of R_signal-kv_es * IR_signal, or an amount corresponding to equations (B1) to (B6), etc. It may be. In addition, when the reliability of kv_es and ka_es exceeds each threshold value, kv_es and ka_es may be recalculated by a conventional method. Further, the reliability may be calculated every time kv_es and ka_es are calculated.

<Second operation>
Next, a case where information for obtaining the pulse cycle cannot be acquired from the outside will be described.

  4 and 5 are flowcharts showing processing for obtaining oxygen saturation and pulse rate in the biological information. Of the processes in the flowcharts of FIGS. 4 and 5, the process having the same number as the step number in the flowcharts of FIGS. 2 and 3 is the same as the corresponding process in the flowcharts of FIGS.

  When the biological information measuring apparatus 100 starts measuring biological information of a living body that is a measurement target, the arithmetic control unit 10 starts sampling the measurement data measured by the sensor unit 40 at a predetermined sampling period, and measures the measurement data. R_signal acquired from the sensor unit 40 and processed by the AC / DC (R) unit 11 and the BPF (R) unit 13, and the AC / DC (IR) unit 12 and the BPF (IR) unit 14 are acquired from the sensor unit 40. The IR_signal processed in step 1 is output to the R correlation calculating unit 15 to the mutual delay correlation calculating unit 20 and the like.

  The arithmetic control unit 10 initializes variables used in the process simultaneously with sampling (step S10, step S11).

When the initialization is completed, the R correlation calculation unit 15 to the cross delay correlation calculation unit 20 acquire R_signal or IR_signal from the BPF (R) unit 13 or the BPF (IR) unit 14 (step S14), and obtain each correlation value. Calculation is performed (step S15). That, is calculated by R correlation calculating section 15 R_signal (j) ² is set to V_R (j), is set is calculated by IR correlation calculating unit 16 IR_signal (j) ² is the V_IR (j), IR correlation R_signal (j) * IR_signal (j) is calculated by the calculation unit 16 and set to V_R_IR (j) (step S30).

  Subsequently, if the delay time τ is not indefinite (step S31: No), R_signal (j) * R_signal (j−τ) is calculated by the R delay correlation calculating unit 18 and set to V_R_τ (j), and the IR delay IR_signal (j) * IR_signal (j-τ) is calculated by the correlation calculation unit 19 and set to V_IR_τ (j), and (R_signal (j) * IR_signal (j-τ) + R_signal () is calculated by the cross delay correlation calculation unit 20. j-τ) * IR_signal (j)) / 2 is calculated and set to V_R_IR_τ (j) (step S32).

  On the other hand, when the delay time τ is indefinite (step S31: Yes), V_R_τ (j), V_IR_τ (j), and V_IR_τ (j) are treated as invalid. Alternatively, the R delay correlation calculation unit 18, the IR delay correlation calculation unit 19, and the cross delay correlation calculation unit 20 may be controlled not to calculate V_R_τ (j), V_IR_τ (j), and V_IR_τ (j). Whether or not the delay time τ is indeterminate is determined using an initial value, a flag, or the like.

  Until acquisition of the predetermined number of data (N) is completed (step S16: No), step S14 to step S16 are executed. When the predetermined number of data is acquired (step S16: Yes), m = 0 to Each of V_R (m), V_IR (m), and V_R_IR (m) is integrated by N-1 to calculate V_R_int, V_IR_int, and V_R_IR_int (step S33).

  Subsequently, when the delay time τ is not indefinite (step S34: No), V_R_τ (m), V_IR_τ (m), and V_R_IR_τ (m) are integrated by m = 0 to N−1, and V_IR_τ_int, V_R_τ_int V_R_IR_τ_int is calculated (step S35).

  On the other hand, when the delay time τ is indefinite (step S34: Yes), V_R_τ (m), V_IR_τ (m), and V_R_IR_τ (m) are treated as V_IR_τ_int, V_R_τ_int, and V_R_IR_τ_int, which are integration results, as invalid.

  Differences dV_R, dV_IR, and dV_R_IR are calculated by the subtraction units 28 </ b> A to 28 </ b> C and output to the kv calculation unit 22 from the data calculated by the R correlation calculation unit 15 to the cross delay correlation calculation unit 20. The kv calculation unit 22 calculates kv_es using Expression (25).

  Subsequently, the SpO2 calculation unit 23 determines whether kv_es_b or ka_es_b is indefinite (step S18).

  If determined to be indefinite (step S18: Yes), the SpO2 calculation unit 23 sets kv_es calculated by the kv initial value calculation unit 21 using equation (31) or the like as kv_es_b, calculates ka_es, and ka_es_b (Step S19).

  Subsequently, the SpO2 calculation unit 23 estimates the SN ratio from V_R_IR_int, V_IR_int, kv_es_b, and ka_es_b (step S20).

  If the SN ratio is less than or equal to the predetermined value (step S21: Yes), the SpO2 calculation unit 23 determines whether or not the delay time τ is indefinite, and if not (step S36: No), the kv calculation unit 22 The calculated kv_es is acquired (step S23).

  The pulse rate calculation unit 24 obtains the pulse rate from the kv_es acquired from the kv calculation unit 22 and the IR_signal and R_signal stored in the memory (step S37), notifies the display unit 30, and the pulse rate. And the period determination signal (signal represented by the left side of Expression (30)) are notified to the period stability determination unit 26.

  The periodic stability determination unit 26 determines the stability of the period of the predetermined period (T_PR) of the periodic determination signal, and determines that it is stable (step S38: Yes), that is, kv_es can be properly estimated. If it can be determined, the pulse rate received from the pulse rate calculation unit 24 is output to the τ calculation unit 25, and the τ calculation unit 25 calculates the delay time τ from the acquired period (step S41).

  On the other hand, when it is determined that the cycle is not stable (step S38: No), the cycle stability determination unit 26 notifies the SpO2 calculation unit 23 accordingly.

  The SpO2 calculation unit 23 that has received the notification that it is not stable means that the period is not stable because the reliability of kv_es calculated by the kv calculation unit 22 is low, so the amount of calculation increases slightly, but the patent Kv_es is calculated by a method of the prior art such as the method of Document 1 and output to the pulse rate calculator 24 (step S39). Note that the cycle stability determination unit 26 that has determined that the cycle is not stable may display a message to that effect or a warning on the display unit 30.

  The pulse rate calculation unit 24 obtains the pulse rate from kv_es acquired from the SpO2 calculation unit 23 (step S40), notifies the display unit 30 of the pulse rate and the cycle determination signal. To the τ calculation unit 25. The τ calculation unit 25 calculates the delay time τ from the acquired pulse rate (step S41). In this case, since the reliability of kv_es is high, there is a high possibility that the periodic stability determination unit 26 determines that the period is stable.

  In step S36, when the delay time τ is indefinite (step S36: Yes), the SpO2 calculation unit 23 is obtained in the same manner as when the determination that the cycle is not stable is acquired from the cycle stability determination unit 26 in step S38. Calculates kv_es using Equation (23) and Equation (24), and outputs them to the pulse rate calculator 24 (Step S39), and Step S40 is performed. That is, since the delay time τ has not yet been calculated at the beginning of the measurement, kv_es is obtained by a calculation method with a large amount of calculation as in step S39. If τ is calculated, as in step S23. Kv_es can be obtained by a method with a small amount of calculation.

  In step S21, when the SN ratio exceeds a predetermined value (step S21: No), the SpO2 calculation unit 23 calculates ka_es by a conventionally known method such as formula (31), formula (32), or formula (33). (Step S22) The arterial blood oxygen saturation SpO2 is calculated (Step S25). Further, kv_es is calculated from the predetermined relationship α (ka_es) with ka_es (step S22). The calculated kv_es is output to the pulse rate calculation unit 24. The pulse rate calculation unit 24 obtains the pulse rate from the acquired kv_es (step S40).

  Subsequently, the SpO2 calculating unit 23 obtains ka_es (step S24), calculates the oxygen saturation SpO2, and outputs it to the SpO2 output unit 31 (step S25).

  The SpO2 output unit 31 displays the oxygen saturation acquired from the SpO2 calculation unit 23, and the pulse rate output unit 32 displays the pulse rate acquired from the pulse rate calculation unit 24 (step S42).

  The SpO2 calculation unit 23 sets the calculated kv_es and ka_es to kv_es_b and ka_es_b, respectively (step S26).

  Subsequently, the reliability calculation unit 27 calculates a predetermined reliability, and the calculated reliability is output to the reliability output unit 33. The reliability output unit 33 displays or warns the acquired reliability ( Step S27).

  Since it operates in this way, the biological information measuring apparatus 100 according to the embodiment can quickly measure biological information such as a pulse rate and oxygen saturation more accurately even when noise occurs due to, for example, body movement of the living body. Can do.

  In order to express the present invention, the present invention has been properly and fully described through the embodiments with reference to the drawings. However, those skilled in the art can easily change and / or improve the above-described embodiments. It should be recognized that this is possible. Therefore, unless the modifications or improvements implemented by those skilled in the art are at a level that departs from the scope of the claims recited in the claims, the modifications or improvements are not covered by the claims. To be construed as inclusive.

DESCRIPTION OF SYMBOLS 10 Measurement part 11 AC / DC (R) conversion part 12 AC / DC (IR) conversion part 13 BPF (R) part 14 BPF (IR) part 15 R correlation calculation part 16 IR correlation calculation part 17 Cross correlation calculation part 18 R Delay correlation calculation unit 19 IR delay correlation calculation unit 20 Cross delay correlation calculation unit 21 kv initial value calculation unit 22 kv calculation unit 23 SpO2 calculation unit 24 Pulse rate calculation unit 25 τ calculation unit 26 Periodic stability determination unit 27 Reliability calculation unit 28 subtraction unit 30 output unit 31 SpO2 output unit 32 pulse rate output unit 33 reliability output unit 40 sensor unit 41 sensor (R) unit 42 sensor (IR) unit 100 biological information measuring device

Claims (14)

A first time-series signal including a first signal component having periodicity and a first noise component; a second signal component having a predetermined first relationship with the first signal component; and the first noise component; A first time-series signal delayed by a delay time that is a time estimated as a period of the first signal component from a second time-series signal including a second noise component having a predetermined second relationship. A signal generator that generates a delayed signal and a second delayed signal obtained by delaying the second time-series signal by the delay time;
Using the first time-series signal and the second time-series signal in a first predetermined time range, and the first delay signal and the second delay signal generated by the signal generation unit, A signal processing apparatus comprising: an estimation unit configured to estimate the predetermined second relationship in a predetermined time range. In claim 1,
The estimation unit assumes that the first signal component included in the first time-series signal and the first signal component included in the first delayed signal are substantially equal, and the correlation of the first time-series signal itself, The first difference between the correlation between the first time series signal and the first delayed signal, the correlation between the second time series signal itself, and the correlation between the second time series signal and the second delayed signal. Two differences, a signal correlation based on the first time-series signal and the second time-series signal, a signal based on the first time-series signal and the second time-series signal, and the first The signal processing apparatus, wherein the predetermined second relationship is estimated using a third difference between a delayed signal and a correlation between the delayed signal based on the second delayed signal. In claim 2,
The estimation unit has a sufficiently small signal noise correlation between the first signal component included in the first time series signal and the first noise component included in the first time series signal, and is included in the first time series signal. The signal noise delay correlation between the first signal component and the delay component of the first noise component included in the first time-series signal is also sufficiently small, and the delay component of the first signal component included in the first time-series signal and the first delay component. The noise signal delay correlation with the first noise component included in the time series signal is also sufficiently small,
Or, further assuming that the average of the signal noise delay correlation and the noise signal delay correlation and the signal noise correlation are substantially equal,
The signal processing apparatus, wherein the second relation is estimated using any two of the first difference, the second difference, and the third difference. In any one of Claims 1 thru | or 3,
The estimation unit estimates the first relationship from the estimated second relationship, the first time series signal or the first delay signal, and the second time series signal or the second delay signal. A signal processing device. In any one of Claims 1 to 4,
The signal generation unit has the same period as the period of the first signal component based on the second relationship estimated by the estimation unit, the first time series signal, and the second time series signal. An estimated period determination signal is generated, the period of the first signal component or the period of the second signal component is obtained from the period of the period determination signal, and the obtained period is set as the delay time. Signal processing device. In claim 5,
The signal generation unit uses the time obtained from the period of the period determination signal as the delay time when the degree of fluctuation of the period of the period determination signal is within the predetermined range in the first predetermined time range. A signal processing device characterized by the above. In claim 5 or claim 6,
The said estimation part calculates the said 2nd relationship by the method different from the method in any one of Claim 1 thru | or 3, when the degree of the fluctuation | variation of the period of the said period determination signal remove | deviates from the predetermined range. A signal processing device. In claim 5 or claim 6,
The estimation unit outputs a warning indicating that the reliability of the second relationship and / or the first relationship is low when the degree of fluctuation of the cycle of the cycle determination signal is out of a predetermined range. Signal processing device. In any one of Claims 1 to 8,
The estimation unit calculates an index having information on a ratio between the first noise component and the first signal component as an index for determining whether to calculate the second relationship, When the first noise component is determined to be small by comparing with the threshold value of the first time series signal, the first relation is expressed using a relational expression directly expressed by the first time series signal and the second time series signal. A signal processing device characterized by estimating. In any one of Claims 1 thru | or 9,
It further includes an output unit for outputting the reliability,
When the estimation unit further calculates a noise reliability indicating the degree of error included in the second relationship, and the noise reliability exceeds a predetermined threshold,
The signal processing apparatus, wherein the output unit outputs a warning indicating that the noise reliability exceeds a predetermined threshold. A signal processing method comprising:
A first time-series signal including a first signal component having periodicity and a first noise component; a second signal component having a first relationship with the first signal component; and the first noise component and second A first delay signal obtained by delaying the first time series signal by a delay time that is a time estimated as a period of the first signal component from a second time series signal including a second noise component having a relationship; A signal generation step of generating a second delay signal obtained by delaying the second time-series signal by the delay time;
Using the first time-series signal and the second time-series signal in a first predetermined time range, and the first delay signal and the second delay signal generated by the signal generation unit, An estimation step for estimating the second relationship in a predetermined time range. Based on at least the first measurement data or the second measurement data obtained by irradiating the living body with a plurality of lights having different wavelengths and receiving the light transmitted or reflected through the living body, respectively, the living body of the living body A biological information measuring device for measuring information,
A first measurement unit that measures first measurement data including a first signal component having periodicity and a first noise component;
A second measuring unit for measuring second measurement data including a second signal component having a predetermined first relationship with the first signal component and a second noise component having a predetermined second relationship with the first noise component; ,
A pulsation interval obtaining unit for obtaining an interval between pulsations of arterial blood of the living body;
From the first measurement data and the second measurement data, the first delay data which is the first measurement data delayed by the delay time as the delay time and the second delay delayed by the delay time A signal generator for generating second delay data as measurement data;
Using the first measurement data and the second measurement data in a first predetermined time range, and the first delay data and the second delay data generated by the signal generator, the first predetermined time A biological information measurement device comprising: an estimation unit that estimates the predetermined second relationship in a range. In claim 12,
The pulsation interval obtaining unit obtains the pulsation interval of arterial blood of the living body based on data obtained from the outside of the own device. In claim 12,
It has an output unit that outputs reliability,
The signal generation unit is estimated to have the same cycle as the cycle of the first signal component based on the second relationship estimated by the estimation unit, the first measurement data, and the second measurement data. A period determination signal is generated, the period of the first signal component is determined from the period of the period determination signal, and the difference between the interval obtained by the beat interval acquisition unit and the period of the period determination signal is equal to or greater than a predetermined value If
The biological information measuring device, wherein the output unit outputs a warning indicating that the difference exceeds a predetermined value.

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