Estimation method, estimation system, and evaluation method

Abstract

To provide a technology to estimate a tissue hemodynamic index on the basis of a change with time in blood volume in a blood vessel from a physical amount based on time-series internal reflection light in a predetermined region of a subject's body surface.SOLUTION: An estimation method of a tissue hemodynamic index includes: a reflection light intensity acquisition process for acquiring a physical amount based on time-series internal reflection light in a predetermined region of a body surface; a blood volume change calculation process for calculating a change with time in the blood volume in a blood vessel for at least one cycle of a pulse on the basis of the physical amount; and a tissue hemodynamic index estimation process for estimating a tissue hemodynamic index showing a blood circulation state on the basis of the calculated change with time in the blood volume in the blood vessel.SELECTED DRAWING: Figure 1

Description

[Technical field]

[0001] The present invention relates to a method for estimating a tissue hemodynamic index, a system for estimating a tissue hemodynamic index, and a method for evaluating a tissue hemodynamic index. [Background technology]

[0002] There is a method for measuring the blood flow rate in the skin by the laser speckle method (Patent Document 1). Non-Patent Documents 1 and 2 will be described later. [Prior art documents] [Patent documents]

[0003] [Patent Document 1] Patent No. 6507639 [Non-patent literature]

[0004] [Non-Patent Document 1] Frans F. Jobsis (umlaut) “Noninvasive, infrared monitoring of cerebral and myocardial oxygen sufficiency and circulatory parameters” SCIENCE Vol.198, No.4323 1264-1267 23 December 1977 [Non-Patent Document 2] Michael S. Patterson, B. Chance, and BC Wilson “Time resolved reflectance and transmittance for the noninvasive measurement of tissue”APPLIED OPTICS Vol. 28, No. 12 2331-2336 15 June 1989 Summary of the Invention [Problem to be solved by the invention]

[0005] In Patent Document 1, the measurement is performed using a light intensity image captured by irradiating a laser beam, and therefore is not suitable for a user to measure the blood flow rate in the skin in their daily lives.

[0006] The present invention has been made in view of the above problems, and relates to a method for calculating a time-dependent change in blood volume in blood vessels (hereinafter also referred to as "intravascular blood volume") as a blood flow rate from a physical quantity based on time-series internally reflected light in a predetermined area of ​​a body surface, and estimating a tissue hemodynamic index indicating a hemocirculatory state based on the calculated time-dependent change in blood volume in blood vessels. In this specification, the terms "method for estimating tissue hemodynamic index" and "method for evaluating tissue hemodynamic index" refer to estimation of a tissue hemodynamic index of a subject and evaluation of the tissue hemodynamic index for non-medical purposes, and include an estimation method and an evaluation method of a tissue hemodynamic index that can be performed by a person other than a specialist. Specifically, the evaluation method of a tissue hemodynamic index includes a method for advising on prevention of lifestyle-related diseases and a method for advising on improvement of a blood vessel condition. [Means for solving the problem]

[0007] The present invention relates to a method for estimating a tissue hemodynamic index, comprising a reflected light intensity acquisition step of acquiring a physical quantity based on time-series internally reflected light in a predetermined area of ​​a body surface, a blood flow change calculation step of calculating a change over time in the blood volume in a blood vessel for at least one pulse cycle based on the physical quantity, and a tissue hemodynamic index estimation step of estimating a tissue hemodynamic index indicating a hemocirculatory state based on the calculated change over time in the blood volume in the blood vessel.

[0008] The present invention also relates to a system for estimating tissue hemodynamic indicators, comprising: a reflected light intensity acquisition means for acquiring a physical quantity based on time-series internally reflected light in a specified area of ​​the body surface; a blood flow change calculation means for calculating a change in blood volume in a blood vessel over time for at least one pulse cycle based on the physical quantity; and a tissue hemodynamic indicator estimation means for estimating a tissue hemodynamic indicator indicating a hemocirculatory state based on the calculated change in blood volume in the blood vessel over time.

[0009] The present invention also relates to a method for evaluating a tissue hemodynamic index, comprising: a reflected light intensity acquisition step of acquiring a physical quantity based on time-series internally reflected light in a predetermined area of ​​a body surface; a blood flow change calculation step of calculating a change over time in the blood volume in a blood vessel for at least one pulse cycle based on the physical quantity; a tissue hemodynamic index estimation step of estimating a tissue hemodynamic index indicating a hemocirculatory state based on the calculated change over time in the blood volume in the blood vessel; and an evaluation step of evaluating a vascular state based on the tissue hemodynamic index. Effect of the Invention

[0010] According to the method provided by the present invention, the change in blood volume over time in blood vessels can be calculated from a physical quantity based on the time-series internally reflected light in a predetermined region of the body surface, and a tissue hemodynamic index indicating the state of blood circulation can be estimated based on the calculated change in blood volume over time in the blood vessels. In addition, since the time-series internally reflected light in the predetermined region of the body surface can be received by a light receiving device mounted on a smartphone, a smartwatch, or the like, the blood volume in blood vessels can be easily observed in daily life. [Brief description of the drawings]

[0011] [Figure 1] (a) is an image diagram showing how physical quantities are obtained based on time-series internally reflected light, and (b) is an image diagram showing the screen when tissue hemodynamic indices are estimated. [Diagram 2] (a) is an illustration of how physical quantities are obtained based on time-series internal reflected light, and (b) is an illustration showing the bottom side of a smartwatch. [Diagram 3] 1 is a main flowchart of a method for estimating a tissue hemodynamic index. [Figure 4] 13 is a flowchart of a blood flow change calculation process. [Diagram 5] (a) is a waveform showing the change over time in blood volume calculated from physical quantities based on time-series internally reflected light, (b) is a waveform cut out for one cycle, (c) is a waveform used in the tissue hemodynamic index estimation process by the judgment process, (d) is a waveform obtained by normalizing the waveform in (c), and (e) is an estimated tissue hemodynamic index, etc. [Figure 6] 13 is a flowchart of a determination process. [Figure 7] FIG. 13 shows tissue hemodynamic indices. [Figure 8] 13 is a flowchart of a tissue hemodynamic index estimation process. [Figure 9] FIG. 1 shows the test results of Test 1. [Figure 10] FIG. 13 is a diagram showing the test results of Test 2. [Figure 11] FIG. 13 shows the test results of Test 3. [Figure 12] FIG. 13 shows the test results of Test 4. [Figure 13] FIG. 11 shows the test results of Test 5, in which (a) is the average one-beat pulse wave waveform without the judgment process being performed, (b) is the waveform of (a) after processing to normalize the intravascular blood volume (vertical axis) and time (horizontal axis) of the waveform of (a), (c) is tissue hemodynamics indices, etc. without the judgment process, (d) is the average one-beat pulse wave waveform after processing to normalize the intravascular blood volume (vertical axis) and time (horizontal axis) of the waveform of (d), and (f) is tissue hemodynamics indices, etc. with the judgment process being performed. [Figure 14] FIG. 11 shows the test results of Test 6, in which (a) shows the proportion of the pulse waveform of the blood volume within a blood vessel analyzed from the internal reflected light obtained using green LED illumination light, (b) shows the proportion of the pulse waveform of the blood volume within a blood vessel analyzed from the internal reflected light obtained using red LED illumination light, and (c) shows the proportion of the pulse waveform of the blood volume within a blood vessel analyzed from the internal reflected light obtained using near-infrared LED illumination light. [Figure 15]FIG. 13 shows the test results of Test 6, in which (a) is a pulse waveform of the blood volume in blood vessels normalized using green LED light, with the blood volume in blood vessels on the vertical axis and time on the horizontal axis, where the upper row is the waveform for young people and the lower row is the waveform for middle-aged and elderly people; (b) is a pulse waveform of the blood volume in blood vessels normalized using red LED light, with the blood volume in blood vessels normalized on the vertical axis and time on the horizontal axis, where the upper row is the waveform for young people and the lower row is the waveform for middle-aged and elderly people; and (c) is a pulse waveform of the blood volume in blood vessels normalized using near-infrared LED light, with the blood volume in blood vessels normalized on the vertical axis and time on the horizontal axis, where the upper row is the waveform for young people and the lower row is the waveform for middle-aged and elderly people. [Figure 16] FIG. 13 shows the results of Test 6, comparing the sustained high blood volume in blood vessels (BOT) between different age groups when measuring pulse waves at different wavelengths. [Figure 17] FIG. 1 is a block diagram of a tissue hemodynamic index estimation system. [Figure 18] (a) is an image of blood vessels near the wrist, and (b) is a cross-sectional image of (a). DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0012] Hereinafter, preferred embodiments of the present invention will be described with reference to the drawings. The drawings of the present embodiment are all intended to explain the technical concept, configuration, and operation of the present invention, and are not intended to specifically limit the configuration. In addition, in all drawings, similar components are given similar reference numerals, and duplicated descriptions are omitted as appropriate.

[0013] The method for estimating tissue hemodynamic indices in this embodiment (hereinafter sometimes referred to as "this estimation method") receives time-series reflected light from a predetermined area on the body surface and uses the received time-series reflected light. 1 and 2 are conceptual diagrams showing how time-series internally reflected light is received. In this system, the internal reflected light from the subject's body surface is received by a visible light camera or near-infrared camera such as a light receiving element built into a wearable device that can be attached to the body surface such as an arm, finger, foot, or ear and can be linked to a smartphone, a webcam attached to a personal computer, a camera built into a tablet device, a camera built into a smartphone, or a digital video camera, or by a device with a built-in visible light or near-infrared light receiving element. In this embodiment, as shown in FIG. 1(a), a configuration in which internally reflected light from the body surface (finger pad) is received by a camera built into a smartphone, and as shown in FIG. 2(a), a configuration in which internally reflected light from the body surface (wrist) is received by a light receiving element built into a watch-type wearable terminal worn on the arm, are described.

[0014] When using a camera 11 built into a smartphone 10, as shown in FIG. 1(a), the flash of the LED 12 is turned on, and the finger pad is brought into contact with or close to the camera 11 (lens) to receive the internally reflected light of the finger pad. As will be described in detail later, since the tissue hemodynamic index is estimated based on the change over time in the amount of blood in the blood vessels, it is necessary to continuously receive the internally reflected light for a predetermined period of time (i.e., time-series reflected light), and light is received for, for example, 30 seconds. As shown in FIG. 1(b), the pulse wave, estimated pulse rate, estimated tissue hemodynamic index, etc. calculated from the received time-series internally reflected light are displayed on the display screen 13 of the smartphone 10. Here, the camera 11 of the smartphone 10 will be described. In this embodiment, a camera 11 having a lens and a CMOS sensor is used on the back surface (the surface opposite to the display screen 13) of the smartphone 10. Note that the image sensor is not limited to a CMOS sensor and may be any type. In this embodiment, in order to obtain a physical quantity based on the internally reflected light of a predetermined region of the body surface, it is preferable to receive as little light as possible other than the internally reflected light of the predetermined region from the viewpoint of accurately estimating tissue hemodynamic indices. Therefore, the finger pad is brought into contact with the camera (lens) 11 so as to cover the camera (lens) 11, so that the camera 11 is less likely to receive light other than the internally reflected light of the predetermined region. Here, "becoming difficult to receive light" means to proactively not receive light other than internally reflected light, such as by providing the camera 11 at a position where light other than internally reflected light is received as little as possible, providing the camera 11 at a position where light other than internally reflected light cannot be received, positioning the body surface at a position where light other than internally reflected light is received as little as possible, or positioning the body surface at a position where light other than internally reflected light cannot be received, and is not intended to completely not receive light other than internally reflected light, but to make the amount of internally reflected light received greater than the amount of light other than internally reflected light (since the amount of internally reflected light received is greater than the amount of light other than internally reflected light, this also includes receiving only internally reflected light and not receiving light other than internally reflected light). In addition, "contact" does not only mean direct contact with the camera (lens) 11, but also means that, for example, when a protective cover is provided on the camera (lens) 11, the finger pad comes into contact with the protective cover and not with the camera (lens) 11, but in this embodiment, this is included in "contact". In addition, it is preferable to dispose the smartphone 10 in such a position that the camera (lens) 11 (light receiving part) can be covered by a predetermined area of ​​the body surface, so that the camera (lens) 11 is unlikely to receive light other than the internally reflected light of a predetermined area. When the camera (lens) 11 receives the internally reflected light of a predetermined area of ​​the body surface, it is preferable to provide the smartphone 10 in a position where the amount of internally reflected light received is greater than the amount of light other than the internally reflected light, and the amount of internally reflected light received is greater than the amount of surface reflected light received. For example, it is preferable to provide the smartphone 10 in a position recessed a predetermined depth inward from the surface of the back surface. In addition, a convex enclosure (cover) may be provided on the outside at a predetermined height so as to cover the periphery of the camera (lens) 11.

[0015] When using a camera built into a wristwatch-type wearable terminal 30 (smartwatch 30 in this embodiment), as shown in Fig. 2(a), the bottom side (opposite to the display screen) of the smartwatch 30 is brought into contact with or close to the back side of the hand (hereinafter also referred to as the back side) of the left hand joint (wrist) to receive internally reflected light from the back side of the wrist. Although details will be described later, since tissue hemodynamic indexes are estimated based on changes over time in the amount of blood in blood vessels, it is necessary to continuously receive internally reflected light for a predetermined period of time (i.e., time-series internally reflected light), and light is received for, for example, 30 seconds. FIG. 2( b ) shows the bottom side of the smart watch 30 . The smart watch 30 is provided with photodiodes (PD) 31 and 32 that receive internally reflected light, an LED 33 that emits near-infrared light (940 nm), an LED 34 that emits green visible light (530 nm), and an LED 35 that emits red visible light (655 nm). In this embodiment, as in the above, in order to obtain a physical quantity based on the internal reflection light of a predetermined region of the body surface, it is preferable from the viewpoint of estimating the tissue hemodynamic index with high accuracy that the received light does not contain light other than the internal reflection light of the predetermined region. Therefore, the wrist is made to contact so as to cover the PDs 31 and 32 so that light other than the internal reflection light of the predetermined region is difficult to receive by the PDs 31 and 32. Here, "contact" does not only mean direct contact with the PDs 31 and 32, but also means that, for example, when a protective cover is provided on the PDs 31 and 32, the wrist contacts the protective cover and not the PDs 31 and 32, but in this embodiment, this is included in "contact". In addition, it is preferable that the PDs 31 and 32 are provided in a position where it is difficult to receive light other than the internal reflection light of the predetermined region, for example, a position recessed a predetermined depth inward from the surface of the back surface with respect to the smart watch 30.

[0016] FIG. 3 shows a main flow chart of the method for estimating tissue hemodynamic indices. This estimation method includes a reflected light intensity acquisition step (step S100), a blood flow change calculation step (step S200), and a tissue hemodynamics index estimation step (step S300).

[0017] The "reflected light intensity acquisition step" is a step of acquiring a physical quantity based on time-series internally reflected light from a predetermined region of the body surface. "Body surface" refers to the surface of the body, including the skin, lips, etc. In addition, parts such as the eyeballs, palpebral conjunctiva, and gums that are not visible (cannot be touched) when the eyes or mouth are closed but are visible when the eyes or mouth are opened, in other words, parts that can be observed from the outside without medical procedures such as surgery, are included in the body surface. Any part of the body surface can be touched or brought close to a device with a built-in camera or light-receiving element when acquiring internally reflected light. The "predetermined area on the body surface" may be any area on the body surface, and in this embodiment, it is set to be provided on the pad of a finger or the back of the wrist. "Internal reflected light" refers to light that is irradiated onto the body surface and then absorbed by substances in the blood (e.g., hemoglobin) and then reflected, and the internal reflected light for a predetermined period of time is called "time-series internal reflected light." For example, it is light received (detected) for a predetermined period of time (e.g., 30 seconds) by the camera 11 shown in Fig. 1(a) and the light receiving elements (PDs 31 and 32) shown in Fig. 2(b). The "physical quantity" refers to the intensity of the received internally reflected light, the amount of the received internally reflected light, the amount of the irradiated light absorbed by substances in the blood, etc. In this estimation method, the physical quantity based on the time series of internally reflected light changes according to the cardiac output. Also, the waveform represented as the time on the horizontal axis and the physical quantity based on the time series of internally reflected light (the intensity of the received light) on the vertical axis is the "pulse wave" and represents the pulse. The "pulse wave" is a wave created by the cardiac output, but in a certain area of ​​the body surface, it is an accumulation of conductive waves propagated to the peripheral blood vessels. Therefore, the pulse wave is made up of many factors resulting from the hemodynamics of the tissue, such as 1) the force of blood leaving the heart, 2) the behavior of the contraction and expansion of the heart, 3) the properties of the vascular wall, 4) the way the blood vessels branch, 5) the diameter of the blood vessel, 6) the intravascular pressure generated, and 7) the vasomotor nerve response. The pulse wave may be detected by any of the following methods: pressure pulse wave (oscillometric method, tonometry method, Liberocchi-Korotkoff method), volume pulse wave (photoelectric pulse wave, video pulse wave, strain gauge pulse wave, air pulse wave, impedance pulse wave, water pulse wave), or velocity pulse wave (pulse wave propagation velocity); however, in this embodiment, the pulse wave detected by the photoelectric volume pulse wave method is used. "Acquire" means acquiring the physical quantity based on the time-series internal reflected light from a specified medium, acquiring via a network, acquiring from the smartphone 10, acquiring from the smart watch 30, etc., and the source from which the physical quantity based on the time-series internal reflected light is acquired is not important.

[0018] The "blood flow rate change calculation step" is a step of calculating the change over time in the blood volume within a blood vessel for at least one pulse cycle as the blood flow rate based on a physical quantity. A "pulse" is a periodic movement that occurs when the blood pressure in an arterial blood vessel fluctuates due to the beating of the heart, and one "cycle of a pulse" is the period during which the blood pressure in an arterial blood vessel goes from its minimum value to its maximum value before reaching its minimum value. "Intravascular blood volume" refers to the amount of blood in a blood vessel per unit time, and since it changes with the beating of the heart, it changes over time. When the pressure in a blood vessel is high, the blood flow rate is high, and when the pressure in a blood vessel is low, the blood flow rate is low. "Changes in blood volume in blood vessels over time for one cycle" refers to the change in blood volume in blood vessels per unit time in one cycle, which is the transition in blood flow. The transition can be shown as a numerical value, a waveform, etc., and the blood flow can be grasped from the change in blood volume in the blood vessels. "Calculation of changes in blood volume in blood vessels over time for one cycle" refers to calculating continuous values ​​of blood flow from the change in blood volume in blood vessels per unit time for one cycle, calculating a waveform showing blood flow from the change in blood volume in blood vessels for one pulse, calculating a graph showing the relationship between the elapsed time for one pulse and the blood volume in blood vessels, etc.

[0019] FIG. 4 is a flowchart showing detailed processing of the blood flow change calculation step (step S200). 5 shows waveforms calculated when estimating tissue hemodynamic indices, estimated tissue hemodynamic indices, etc. The blood flow change calculation step will be described with reference to FIGS.

[0020] Step S210 is a process of selecting a wavelength band, and corresponds to a wavelength band selection process. In this embodiment, since the internal reflection light of visible light and near-infrared light is used, the acquired physical quantity is one of the B waveform, G waveform, R waveform, and near-infrared waveform. This process selects which waveform to use (which wavelength band to use), and at least one is sufficient, and may be multiple. In this embodiment, the wavelength band is selected in the blood flow change calculation process, but in the reflected light intensity acquisition process (step S100), a wavelength band may be selected when irradiating light, and time-series internal reflection light of the selected wavelength band may be received, or light of the selected wavelength band may be irradiated. In this way, it is possible to either acquire physical quantities based on time-series internal reflection light of all wavelength bands and calculate the time-series change in blood volume in blood vessels for one cycle, and estimate tissue hemodynamic indexes based on the selected wavelength band, or acquire physical quantities based on time-series internal reflection light of the selected wavelength band and calculate the time-series change in blood volume in blood vessels for one cycle, and estimate tissue hemodynamic indexes.

[0021] Step S220 is a process for calculating the amount of blood in the blood vessel. Since hemoglobin exists in the blood in the blood vessel, it has the property of absorbing incident light, and since the amount of absorption changes according to the blood flow rate, the detected internal reflected light also changes. Therefore, the change in the amount of blood in the blood vessel over time is calculated from the physical quantity based on the acquired time-series internal reflected light.

[0022] In step S230, an inversion process (positive / negative inversion process) is performed on the waveform created from the time-dependent change in blood volume in the blood vessel calculated in step S220, with the horizontal axis representing time and the vertical axis representing blood volume. When blood flow is monitored using the laser speckle method, i.e., LSFG (Laser Speckle Flowgraphy), a difference in the optical path of the reflected light occurs when coherent laser light is irradiated onto red blood cells (hemoglobin) in the blood vessel, and a spotted pattern called a speckle pattern is created by mutual interference. Since red blood cells move in the blood vessel while changing their relative positions, the speckle pattern changes randomly with time. The blood flow is calculated by statistically analyzing the fluctuation of this speckle pattern. In this estimation method, internally reflected light after visible light or near-infrared light is absorbed by hemoglobin is used. Therefore, when comparing and evaluating the tissue hemodynamic index calculated by LSFG and the tissue hemodynamic index estimated by this estimation method, accurate results cannot be obtained by using the waveform created from the time-dependent change in blood flow calculated in step S220 as it is. In this embodiment, a comparison process is performed between the tissue hemodynamic index calculated by this estimation method and the tissue hemodynamic index calculated using LSFG, and the created waveform is inverted to evaluate the effectiveness of the calculation method of the tissue hemodynamic index by this estimation method. Figure 5(a) shows the waveform after inversion.

[0023] Step S240 is a process of cutting out each pulse waveform from the waveform created in step S230 (the waveform shown in FIG. 5(a)). As shown in Figure 5(a), the positive and negative peak positions are detected from the waveform, and the waveform is cut out from the negative peak position to the negative peak position as one pulse. The cut out waveform is shown in Figure 5(b).

[0024] In this embodiment, as described above, the waveform created from the change over time in the blood volume in the blood vessels calculated in step S220 is inverted and then cut out for each pulse waveform, but it is also possible to cut out for each pulse waveform before inversion.

[0025] The blood flow rate change calculation step (step S200) may include a process (determination step) of calculating a change in blood volume over time in a blood vessel for multiple cycles and determining whether each of the calculated changes in blood volume over time in the blood vessel for multiple cycles satisfies a predetermined condition. By including a process of determining whether a predetermined condition is satisfied and using only the changes in blood volume over time in the blood vessel that satisfy the predetermined condition for calculating the tissue hemodynamic index in the tissue hemodynamic index estimation step (step S300), the estimation accuracy can be improved and the tissue hemodynamic index can be stably estimated without impairing the characteristics of the changes in blood volume over time in the blood vessel (e.g., pulse wave). The "predetermined condition" is a condition (reference value) for determining whether a specific characteristic amount (e.g., peak arrival time, period, ratio of average fluctuation component to steady component, average blood volume in blood vessel, maximum blood volume in blood vessel, minimum blood volume in blood vessel) satisfies each of the predetermined conditions among the changes in blood volume over time in the blood vessel for multiple cycles, and is a condition set according to the tissue hemodynamic index to be estimated. The specified condition (reference value) may be set so as to define a range of changes in blood volume over time in blood vessels that can improve the accuracy of estimating tissue hemodynamic indices among the changes in blood volume over time in blood vessels for multiple cycles, and a range of changes in blood volume over time in blood vessels that can stably estimate tissue hemodynamic indices without compromising the characteristics of the changes in blood volume over time in blood vessels (e.g., pulse waves) among the changes in blood volume over time in blood vessels. Step S250 is a process for determining whether or not each pulse waveform cut out in step S240 satisfies a predetermined condition. The pulse waveform cut out for each of a plurality of pulses is identified by a determination process that can remove artifacts without impairing the characteristics that the pulse waveform originally has. Specifically, six components that are the main components of the pulse waveform are extracted, and for each main component, outliers are determined from the probability distribution by a statistical analysis method using standard deviation (i.e., a predetermined condition is determined by a statistical analysis method, and outliers that do not satisfy the predetermined condition are determined as outliers), and a process for removing them is performed. The "predetermined condition" in this embodiment is each value shown in each determination process (steps S251 to S256) in FIG. 6. By determining whether or not the pulse waveform cut out for each pulse satisfies the predetermined condition, only waveforms including physical quantities that are unintentionally generated when receiving internally reflected light can be removed, and therefore, accurate estimation can be performed. FIG. 6 shows a flowchart of the determination step (step S250).

[0026] Steps S251 to S256 are the predetermined conditions in the determination step. Note that the order of steps S251 to S256 is not limited to that shown in Fig. 6. As shown in steps S251 to S256, there are a plurality of conditions to be determined in the determination step (step S250), but it is not necessary to use the change over time in the amount of blood in the blood vessel for one cycle that satisfies all of the conditions. It is preferable to be able to select which of the plurality of conditions to use depending on the type of blood vessel, the position of the blood vessel, etc. in the predetermined region, as will be described in detail later.

[0027] Step S251 is a process for determining whether the peak arrival time is outside the range. It is determined whether the data has a time to reach the peak position of blood volume that is 0.05 seconds or less or 0.8 seconds or more, preferably 0.1 seconds or less or 0.5 seconds or more, and data outside the range is excluded. Step S252 is a process for determining whether or not the data is outside the period range. It is determined whether or not the data exceeds ±2SD from the average period of the waveform, and preferably exceeds ±3SD, and any data that exceeds this range is excluded. Step S253 is a process for determining whether the ratio of the average fluctuation component to the steady-state component is outside the standard. It is determined whether the ratio of the average fluctuation component to the steady-state component of the waveform exceeds ±2SD, preferably ±3SD, and any data that exceeds this standard is excluded. Step S254 is a process for determining whether the average intravascular blood volume value is outside the standard, where a determination is made as to whether the waveform exceeds ±2SD from the average intravascular blood flow volume, preferably ±3SD, and any data that exceeds this limit is excluded. Step S255 is a process for judging whether or not the value is outside the range of the maximum intravascular blood flow rate, and judges whether or not the value exceeds ±2SD, preferably ±3SD, and excludes data that exceeds the range. Step S256 is a process for judging whether or not the value is outside the range of the minimum intravascular blood flow rate, and judges whether or not the value exceeds ±2SD, preferably ±3SD, and excludes data that exceeds the range. The waveform that is determined to satisfy the conditions in the determination step is shown in FIG. Step S257 is a process (averaging process) in which the time and blood flow rate are averaged for the change in blood flow rate over time that has been determined by the judgment process to satisfy the condition (data for multiple cycles that have been determined to satisfy the condition (data that returns NO in each of the processes in steps S251 to S256)), and the blood flow rate over time for an average one pulse beat and the average one pulse beat waveform are calculated. Step S258 is a process for preventing data that does not satisfy the judgment condition (data for which YES is returned in each of steps S251 to S256) from being used in the tissue hemodynamic index estimation process (step S300), for example, by attaching a flag to the data so that the data is not used in subsequent processes. In the above embodiment, the tissue hemodynamic index is estimated based on the data averaged in the averaging process (step S257), but a process of normalizing the blood volume (vertical axis) and time (horizontal axis) of the calculated average one pulse waveform may be performed. The normalized waveform is shown in FIG. 5(d). For one pulse waveform, normalization processing may be performed on both the intravascular blood volume (vertical axis) and time (horizontal axis), or on either one of them. The normalized waveform allows visualization of tissue hemodynamic characteristics and comparison of the waveforms even before estimating tissue hemodynamic indices. However, as in this embodiment, when the body surface is brought into contact with the light receiving device (camera 11 of smartphone 10, PDs 31 and 32 of smartwatch 30), it is difficult to be affected by disturbance light, so the incident light intensity and light receiving sensitivity can be kept constant to a certain extent. Therefore, it is possible to calculate the tissue hemodynamic indices without performing normalization processing in the blood flow calculation process. It is sufficient to determine whether or not to perform normalization processing by taking into consideration the type, installation position, processing capacity, etc. of the light receiving device. Note that FIG. 5(d) shows a waveform normalized with the minimum value of the internal reflection light intensity set to 0 and the maximum value set to 100 on the vertical axis, and with the minimum value of the time of one pulse waveform set to 0 and the maximum value set to 100 on the horizontal axis.

[0028] The "tissue hemodynamics index estimating step" is a step of estimating a tissue hemodynamics index indicating the state of blood circulation based on the calculated change over time in the blood volume in the blood vessel. The "tissue hemodynamic index" is an index showing the state of blood circulation in the skin tissue of the body surface, and may be information that can be an index of blood flow rate from the change in blood volume in blood vessels over time, such as IVBV (Intra Vascular Blood Volume): blood volume in blood vessels, Fluctuation: rate of change in blood volume, Skew: deviation of pulse wave waveform, BOS (Blowout Score): steady flow of pulse wave, BOT (Blowout Time): persistence of high IVBV value, Rising rate: change in blood flow rate over time when pulse wave rises, Falling rate: change in blood flow rate over time when pulse wave falls, FAI: instantaneous maximum blood flow rate when pulse wave rises, ATI: position of intravascular blood volume peak, RI (Resistivity Index): peripheral vascular resistance, etc. Although details will be described later, by evaluating the tissue hemodynamic indexes, especially BOT, Falling rate, or ATI, the state of blood vessels (whether blood vessels are flexible (can expand and contract) or stiff blood vessels (cannot expand and contract)) can be grasped (estimated). The "tissue hemodynamic index estimating step" is a step of estimating at least one tissue hemodynamic index.

[0029] Based on FIG. 7, the tissue hemodynamic index will be explained. IVBV is the relative intravascular blood volume, and its change over time is the relative blood flow rate. In the laser speckle method, MBR is the relative blood flow rate, which is obtained by applying the average MBR value to the linear regression equation: blood flow rate mL / (min 100g) = 41.7 × MBR value - 15.1. Fluctuation is an index that shows the coefficient of variation of IVBV. Skew is an index that indicates the deviation of the pulse waveform. BOS is an index indicating the steady flow of the pulse wave, and is expressed by the following formula using the maximum IVBV value (IVBVmax in FIG. 7), the minimum IVBV value (IVBVmin in FIG. 7), and the average IVBV value. (BOS)={2-(IVBVmax-IVBVmin) / IVBVave} / 2·100 BOT is an index showing the sustainability of high IVBV values, and the BOT value is expressed by the following formula using the half-width (time) (W) and one-beat width (time) (F) of the IVBV value shown in Figure 7, and a proportional constant "C". (BOT)=C·(W) / (F) The rising rate is an index showing the change in blood flow rate over time when the pulse wave rises. Using (Sall) and (S1) shown in Figure 7, the rising rate can be expressed by the following formula. In the following, "C" is a proportionality constant. (Rising rate)=C·(S1) / (Sall) The falling rate is an index showing the change in blood flow rate over time when the IVBV value per heartbeat falls from the maximum IVBV value in the time waveform. Using (Sall) and (S2) shown in Figure 7, the falling rate can be expressed by the following formula. In the following, "C" is a proportionality constant. (Falling rate)=C·(S2) / (Sall) FAI is an index that indicates the instantaneous maximum blood flow when the pulse wave rises, and can be expressed by the following formula. (FAI)=ΔIVBVmax ATI is the ratio of the time during which the IVBV waveform reaches the maximum IVBV value (IVBVmax in Figure 7) in one pulse. ATI can be expressed by the following formula, where "P" is the peak width and "F" is the width of one pulse. (ATI)=P / F·100 RI is an index of peripheral vascular resistance, and the RI value is obtained by dividing the difference between the maximum IVBV value (IVBVmax in FIG. 7) and the minimum IVBV value (IVBVmin in FIG. 7) by the maximum IVBV value. RI can be expressed by the following formula. (RI)=(IVBVmax-IVBVmin) / IVBVmax

[0030] A detailed flowchart of the tissue hemodynamic index estimation step (step S300) is shown in Fig. 8. Steps S310 to S380 in Fig. 8 differ in the types of feature values ​​related to the change over time in blood volume in blood vessels extracted from one pulse cycle, and only the necessary feature values ​​need to be calculated according to the tissue hemodynamic index to be calculated (only the necessary processing from step S310 to step S380 needs to be performed), and all processing does not need to be performed.

[0031] Step S310 is a process of calculating a first time, which is a half-width of the maximum value of the intravascular blood volume, based on the blood flow volume over time for an average one pulse beat. Step S320 is a process of calculating a second time period that is the total length from the rise time to the fall time of the intravascular blood volume, based on the blood flow volume over time for an average one pulse beat. Step S330 is a process for calculating a third time from the rise of the intravascular blood volume to the peak time when the blood volume reaches a maximum value, based on the blood flow volume over time for an average of one pulse beat. Step S340 is a process for calculating a fourth time from the peak to the fall of the intravascular blood volume based on the blood flow volume over time for an average of one pulse beat. Step S350 is a process for calculating the maximum intravascular blood volume based on the blood flow volume over time for an average one pulse beat. Step S360 is a process for calculating an average intravascular blood volume based on the blood flow volume over time for an average one pulse beat. Step S370 is a process for calculating the minimum intravascular blood volume based on the blood flow volume over time for an average pulse beat. Step S380 is a process for calculating the maximum increase in the amount of blood in the blood vessels per predetermined time based on the blood flow rate over time for an average pulse beat. Step S385 is a process for calculating an area ratio from the rise of intravascular blood volume to the peak, which is the maximum value, based on the average one-pulse pulse waveform. Step S390 is a process for calculating the area ratio from the peak to the fall of the intravascular blood volume based on the average one-pulse pulse waveform. Step S395 is a process of calculating a tissue hemodynamic index (for example, at least one of FAI, ATI, BOT, a falling rate, RI, a rising rate, and BOS). The FAI is calculated using the maximum increase. The ATI is calculated using the second and third times. The BOT is calculated using the first time and the second time. The falling rate is calculated based on the fourth time and the average one-pulse pulse waveform, using the area ratio from the peak to the falling edge of the intravascular blood volume. RI is calculated using the maximum and minimum values. The rising rate is calculated based on the third time and the average one-pulse pulse waveform, using the area ratio from the rising time of the intravascular blood volume to the maximum peak time. The BOS is calculated using the maximum, average, and minimum values.

[0032] In this way, the method further includes a feature calculation process (e.g., steps S310 to S340) for calculating feature amounts related to the change in blood flow rate over time from the intravascular blood volume and one cycle of the pulse. The feature calculation process calculates as feature amounts one or more of the following: a first time which is the half-width of the maximum value of the intravascular blood volume (e.g., step S310); a second time which is the total length from the rise of the intravascular blood volume to the fall of the intravascular blood volume (e.g., step S320); a third time which is the time from the rise of the intravascular blood volume to its peak, at which it becomes its maximum value (e.g., step S330); and a fourth time which is the time from the peak of the intravascular blood volume to the fall of the intravascular blood volume (e.g., step S340). The tissue hemodynamic index estimation process calculates a vascular elasticity index (e.g., ATI, BOT, ATI, Rising rate, Falling rate) using one or more of the first time, second time, third time, and fourth time (e.g., step S395). The method further includes a feature calculation process (e.g., steps S350 to S380) for calculating features related to changes in blood flow over time from the intravascular blood volume and one cycle of the pulse. The feature calculation process calculates one or more of the maximum intravascular blood volume (e.g., step S350), the average intravascular blood volume (e.g., step S360), the minimum intravascular blood volume (e.g., step S370), and the maximum increase among the increases in intravascular blood volume per specified time (e.g., step S380) as features. The tissue hemodynamics index estimation process calculates tissue hemodynamic indexes (e.g., FAI, RI, BOS) using one or more of the maximum intravascular blood volume, the average intravascular blood volume, the minimum intravascular blood volume, and the maximum increase in intravascular blood volume (e.g., step S395).

[0033] Next, tests carried out in this embodiment will be described. Six types of tests were carried out. Test 1: Comparison of skin blood flow measurement system (LSFG) and smartphone <Test conditions> Subjects: 18 men (ages 20-60, average age 43.8 ± 12.7) 13 women (ages 20-60, average age 39.7 ± 12.8) Measurement area: Palm of the first joint of the second finger (index finger) Measurement time: 30 seconds Sampling rate: 30fps Indicator: BOT value among tissue hemodynamic indicators Measuring equipment: Skin blood flow measurement system (SoftCare LSFG-Prototype) Laser speckle method Floodlight: Laser diode (830nm) Receiver: CCD camera Non-contact measurement (measurement distance: 25 cm) Smartphone (Apple iPhone(R) X) Photoplethysmography Floodlight: LED flashlight (pseudo white light in the visible light range) Receiver: CMOS camera green sensor (G component from RGB waveform) Contact Measurement <Test Method> a) The test method for the skin blood flow measurement system (LSFG) is as follows. 1) The palmar side of the left index finger is placed 25 cm away from the probe unit, and skin blood flow is measured using a continuous measurement method at 30 fps. 2) The peaks of the blood flow waveform are detected and the blood flow waveform is extracted for each pulse beat. 3) The blood flow waveforms extracted for each pulse are classified by a process that can remove artifacts without compromising the characteristics of the blood flow waveform. Specifically, the six main components of the blood flow waveform are extracted, and for each main component, outliers are determined from the probability distribution using a statistical analysis method that uses standard deviation, and these are then removed. a) Pulse period (waveforms exceeding ±3SD from the mean period of the waveform are excluded as outliers.) b) Peak arrival time (waveforms with peak values ​​of 0.1 s or less or 0.5 s or more are excluded as outliers.) c) Ratio of average fluctuation component to stationary component (waveforms that are more than ±3SD from the ratio of the average fluctuation component to the stationary component of the waveform are excluded as outliers.) d) Minimum MBR (MBR of the waveform min Waveforms that are beyond ±3SD from the above are excluded as outliers.) e) Average MBR (MBR of the waveform ave Waveforms that are beyond ±3SD from the above are excluded as outliers.) f) Maximum MBR (MBR of waveform max Waveforms that are beyond ±3SD from the above are excluded as outliers.) 4) The blood flow waveforms extracted for each pulse beat selected in the waveform selection process are made into an average pulse blood flow waveform. 5) The BOT is calculated from the average pulse blood flow waveform obtained. The test method for smartphones is as follows: 1) Place the index finger of the left hand so as to cover the camera 11 and LED flash 12 (see Figure 1 (a)). The LED flash 12 illuminates the area to be examined at the maximum of its four levels of light intensity. The light receiving sensitivity of the CMOS is adjusted according to the ISO sensitivity. The internally reflected light from the area to be examined is received by the green sensor of the CMOS camera, and the pulse wave is measured for 30 seconds at 30 fps. While capturing the brightness value in real time, the pulse waveform is inverted, the waveform peaks are detected, and the pulse waveform is extracted for each pulse beat. The process of inverting the pulse waveform corresponds to step S230, and the process of extracting the pulse waveform for each pulse beat corresponds to step S240. 2) The pulse waveform extracted for each of the multiple pulse beats is subjected to processing that can remove artifacts without compromising the inherent characteristics of the pulse waveform, and the pulse waveform is identified. Specifically, the six components that are the main components of the pulse waveform are extracted, and for each main component, outliers are determined from the probability distribution using a statistical analysis method that uses standard deviation, and these are removed. The pulse waveform identification process corresponds to the judgment process in step S250 (steps S251 to S256). a) Pulse period (waveforms exceeding ±3SD from the mean period of the waveform are excluded as outliers.) b) Peak arrival time (waveforms with peak values ​​of 0.1 s or less or 0.5 s or more are excluded as outliers.) c) Ratio of average fluctuation component to stationary component (waveforms that are more than ±3SD from the ratio of the average fluctuation component to the stationary component of the waveform are excluded as outliers.) d) Minimum vascular blood volume (waveforms that are more than ±3SD from the minimum vascular blood volume of the waveform are excluded as outliers.) e) Mean intravascular blood volume (waveforms that are more than ±3SD from the mean intravascular blood volume of the waveform are excluded as outliers.) f) Maximum intravascular blood volume (waveforms exceeding ±3SD from the maximum intravascular blood volume of the waveform are excluded as outliers.) 3) The selected pulse waveforms cut out for each pulse beat are converted into an average one-pulse waveform. Note that the process of converting the pulse waveform into an average one-pulse waveform corresponds to step S257. 4) The BOT value is calculated from the acquired average pulse waveform by a tissue hemodynamic index estimation process (step S300).

[0034] Figure 9 shows the results of Test 1. The horizontal axis shows the BOT value measured by LSFG, and the vertical axis shows the BOT value estimated by this estimation method using a smartphone. As shown in Fig. 9, there is a significant difference between the BOT value measured by LSFG and the BOT value estimated by this estimation method using a smartphone. 2 = 0.70 (r = 0.84), p < 0.01, indicating a significant positive correlation. From these results, it can be said that the tissue hemodynamic indices obtained by this estimation method correspond to those obtained using LSFG.

[0035] Test 2: Comparison of wrist skin blood flow measurement system and smart watch (G component) <Test conditions> Subjects: 12 men (ages 20-60, average age 44.3 ± 11.3) 9 women (ages 20-60, average age 44.2 ± 12.3) Measurement area: Back of left hand (wrist) Measurement time: 30 seconds Indicator: BOT value among tissue hemodynamic indicators Measuring equipment: Skin blood flow measurement system (SoftCare LSFG-Prototype) Laser speckle method Floodlight: Laser diode (830 nm) Receiver: CCD camera Non-contact measurement (measurement distance: 25 cm) Sampling rate: 30fps Smartwatch (Maxim Integrated MAXREFDES103#) Photoplethysmography Floodlight: Green LED (530 nm) Receiver: PD Contact Measurement Sampling rate:25fps(100sps,4sample averaging) <Test Method> a) The test method for the skin blood flow measurement system (LSFG) is as follows. 1) The dorsal part of the left wrist is placed 25 cm away from the probe unit, and skin blood flow is measured using a continuous measurement method at 30 fps. Regarding 2) to 5), since they are similar to Test 1 (a) Skin blood flow measurement system (LSFG), explanations are omitted. a) The test method for smart watches is as follows. 1) The belt is worn on the left wrist, about one finger's width from the bone (ulnar styloid process) toward the arm. This smartwatch has three LEDs (33-35) and two PDs (31, 32) arranged alternately. The green LED 34 at the center of the back of the sensor irradiates the test area with pulsed light. (One PD (31, 32) can capture light of multiple wavelengths.) The PDs (31, 32) receive the internally reflected light from the test area, and the pulse wave is measured for 30 seconds at 25 fps. While capturing the luminance value in real time, the pulse wave waveform is inverted, the peak of the waveform is detected, and the pulse wave waveform is cut out for each pulse beat. The process of inverting the pulse wave waveform corresponds to step S230, and the process of cutting out the pulse wave waveform for each pulse beat corresponds to step S240. 2) The pulse waveform extracted for each of the multiple pulse beats is subjected to processing that can remove artifacts without compromising the inherent characteristics of the pulse waveform, and the pulse waveform is identified. Specifically, the six components that are the main components of the pulse waveform are extracted, and for each main component, outliers are determined from the probability distribution by a statistical analysis method using standard deviation, and these are removed. The pulse waveform identification process corresponds to the judgment process in step S250 (steps S251 to S256). a) Pulse period (waveforms exceeding ±3SD from the mean period of the waveform are excluded as outliers.) b) Peak arrival time (waveforms with peak values ​​of 0.1 s or less or 0.5 s or more are excluded as outliers.) c) Ratio of average fluctuation component to stationary component (waveforms that are more than ±3SD from the ratio of the average fluctuation component to the stationary component of the waveform are excluded as outliers.) d) Minimum vascular blood volume (waveforms that are more than ±3SD from the minimum vascular blood volume of the waveform are excluded as outliers.) e) Mean intravascular blood volume (waveforms that are more than ±3SD from the mean intravascular blood volume of the waveform are excluded as outliers.) f) Maximum intravascular blood volume (waveforms exceeding ±3SD from the maximum intravascular blood volume of the waveform are excluded as outliers.) 3) The selected pulse waveforms cut out for each pulse beat are converted into an average one-pulse waveform. Note that the process of converting the pulse waveform into an average one-pulse waveform corresponds to step S257. 4) The BOT value is calculated from the acquired average pulse waveform by a tissue hemodynamic index estimation process (step S300).

[0036] Figure 10 shows the results of Test 2. The horizontal axis shows the BOT value measured by LSFG, and the vertical axis shows the BOT value estimated by this estimation method using a smartwatch (G component). As shown in Fig. 10, there is a significant difference between the BOT value measured by LSFG and the BOT value estimated by this estimation method using a smartwatch (G component). 2= 0.41 (r = 0.64), p < 0.01, indicating a significant positive correlation. From these results, it can be said that the tissue hemodynamic indices obtained by this estimation method correspond to those obtained using LSFG.

[0037] Test 3: Comparison of skin blood flow measurement system and smart watch (NIR component) <Test conditions> Subjects: 12 men (ages 20-60, average age 44.3 ± 11.3) 9 women (ages 20-60, average age 44.2 ± 12.3) Measurement area: Back of left hand (wrist) Measurement time: 30 seconds Indicator: BOT value among tissue hemodynamic indicators Measuring equipment: Skin blood flow measurement system (SoftCare LSFG-Prototype) Laser speckle method Floodlight: Laser diode (830nm) Receiver: CCD camera Non-contact measurement (measurement distance: 25 cm) Sampling rate: 30fps Smartwatch (Maxim Integrated MAXREFDES103#) Photoplethysmography Floodlight: Near-infrared LED (940nm) Receiver: PD Contact Measurement Sampling rate:25fps(100sps,4sample averaging) <Test Method> The test method for a) skin blood flow measurement system (LSFG) is the same as that for a) skin blood flow measurement system (LSFG) in Test 2, so the explanation will be omitted. a) The test method for smart watches is as follows. 1) The belt is worn about one finger's width from the bone (ulnar styloid process) of the left wrist toward the arm. This smartwatch has three LEDs (33-35) and two PDs (31, 32) arranged alternately. The near-infrared LED 33 at the center of the back of the sensor irradiates the test area with pulsed light. (One PD (31, 32) can capture light of multiple wavelengths.) The PDs (31, 32) receive the internally reflected light from the test area, and the pulse wave is measured for 30 seconds under the condition of 25 fps. While capturing the luminance value in real time, the pulse wave waveform is inverted, the peak of the waveform is detected, and the pulse wave waveform is cut out for each pulse beat. The process of inverting the pulse wave waveform corresponds to step S230, and the process of cutting out the pulse wave waveform for each pulse beat corresponds to step S240. Regarding 2) to 4), the explanation is omitted since it is the same as the test method for the smart watch in Test 2 (a).

[0038] Figure 11 shows the results of Test 3. The horizontal axis shows the BOT value measured by LSFG, and the vertical axis shows the BOT value estimated by this estimation method using a smart watch (NIR component). As shown in Fig. 11, there is a significant difference between the BOT value measured by LSFG and the BOT value estimated by this estimation method using a smartwatch (NIR component). 2 = 0.43 (r = 0.66), p < 0.01, indicating a significant positive correlation. From these results, it can be said that the tissue hemodynamic indices obtained by this estimation method correspond to those obtained using LSFG.

[0039] Test 4: Comparison of skin blood flow measurement system and smart watch (R component) <Test conditions> Subjects: 12 men (ages 20-60, average age 44.3 ± 11.3) 9 women (ages 20-60, average age 44.2 ± 12.3) Measurement area: Back of left hand (wrist) Measurement time: 30 seconds Indicator: BOT value among tissue hemodynamic indicators Measuring equipment: Skin blood flow measurement system (SoftCare LSFG-Prototype) Laser speckle method Floodlight: Laser diode (830 nm) Receiver: CCD camera Non-contact measurement (measurement distance: 25 cm) Sampling rate: 30fps Smartwatch (Maxim Integrated MAXREFDES103#) Photoplethysmography Floodlight: Red LED (655 nm) Receiver: PD Contact Measurement Sampling rate:25fps(100sps,4sample averaging) <Test Method> The test method for a) skin blood flow measurement system (LSFG) is the same as that for a) skin blood flow measurement system (LSFG) in Test 2, so the explanation will be omitted. a) The test method for smart watches is as follows. 1) The belt is worn on the left wrist, about one finger's width from the bone (ulnar styloid process) toward the arm. This smartwatch has three LEDs (33-35) and two PDs (31, 32) arranged alternately. The red LED 35 at the center of the back of the sensor irradiates the test area with pulsed light. (One PD (31, 32) can capture light of multiple wavelengths.) The PDs (31, 32) receive the internally reflected light from the test area, and the pulse wave is measured for 30 seconds at 25 fps. While capturing the luminance value in real time, the pulse wave waveform is inverted, the peak of the waveform is detected, and the pulse wave waveform is cut out for each pulse beat. The process of inverting the pulse wave waveform corresponds to step S230, and the process of cutting out the pulse wave waveform for each pulse beat corresponds to step S240. Regarding 2) to 4), the explanation is omitted since it is the same as the test method for the smart watch in Test 2 (i).

[0040] Figure 12 shows the results of Test 4. The horizontal axis shows the BOT value measured by LSFG, and the vertical axis shows the BOT value estimated by this estimation method using a smartwatch (R component). As shown in Fig. 12, there is a significant difference between the BOT value measured by LSFG and the BOT value estimated by this estimation method using a smartwatch (R component). 2 = 0.38 (r = 0.62), p < 0.01, indicating a significant positive correlation. From these results, it can be said that the tissue hemodynamic indices obtained by this estimation method correspond to those obtained using LSFG.

[0041] Test 5: Comparison of cases where the pulse waveform judgment process (steps S251 to S256) was performed and not performed <Test conditions> Target: Men in their 60s Measurement area: Back of left hand (wrist) Measurement time: 30 seconds Sampling rate:25fps(100sps,4sample averaging) Measurement equipment: Smart watch (Maxim Integrated MAXREFDES103#) Photoplethysmography Floodlight: Green LED (530 nm) Receiver: PD Contact Measurement <Test Method> 1) The belt is worn on the left wrist, about one finger's width from the bone (ulnar styloid process) toward the arm. This smartwatch has three LEDs (33-35) and two PDs (31, 32) arranged alternately. The green LED 34 at the center of the back of the sensor irradiates the test area with pulsed light. (One PD (31, 32) can capture light of multiple wavelengths.) The PDs (31, 32) receive the internally reflected light from the test area, and the pulse wave is measured for 30 seconds at 25 fps. While capturing the luminance value in real time, the pulse wave waveform is inverted, the peak of the waveform is detected, and the pulse wave waveform is cut out for each pulse beat. The process of inverting the pulse wave waveform corresponds to step S230, and the process of cutting out the pulse wave waveform for each pulse beat corresponds to step S240. 2) The pulse waveform extracted for each of the multiple pulse beats is subjected to processing that can remove artifacts without compromising the inherent characteristics of the pulse waveform, and the pulse waveform is identified. Specifically, the six components that are the main components of the pulse waveform are extracted, and for each main component, outliers are determined from the probability distribution by a statistical analysis method using standard deviation, and these are removed. The pulse waveform identification process corresponds to the judgment process in step S250 (steps S251 to S256). a) Pulse period (waveforms exceeding ±3SD from the mean period of the waveform are excluded as outliers.) b) Peak arrival time (waveforms with peak values ​​of 0.1 s or less or 0.5 s or more are excluded as outliers.) c) Ratio of average fluctuation component to stationary component (waveforms that are more than ±3SD from the ratio of the average fluctuation component to the stationary component of the waveform are excluded as outliers.) d) Minimum vascular blood volume (waveforms that are more than ±3SD from the minimum vascular blood volume of the waveform are excluded as outliers.) e) Mean intravascular blood volume (waveforms that are more than ±3SD from the mean intravascular blood volume of the waveform are excluded as outliers.) f) Maximum intravascular blood volume (waveforms exceeding ±3SD from the maximum intravascular blood volume of the waveform are excluded as outliers.) 3) The pulse waveforms cut out for each of the selected pulse beats are taken as an average pulse waveform (selected data). Note that the process of taking the pulse waveform and converting it into an average pulse waveform corresponds to step S257. 4) The process in 2) above is not performed, and all of the pulse waveforms extracted for each pulse beat are treated as an average pulse waveform (accepted / rejected data). 5) In a tissue hemodynamic index estimation step (step S300), tissue hemodynamic indexes are estimated from the acquired average one-beat pulse waveform (accepted data) and average one-beat pulse waveform (accepted / unaccepted data).

[0042] <Test Results> The results of Test 5 are shown in Figure 13. Figure 13(a) shows the average pulse wave waveform (adopted / unadopted data) without the above process 2) (judgment step), Figure 13(b) shows the waveform of Figure 13(a) normalized to the blood volume in blood vessels (vertical axis) and time (horizontal axis), Figure 13(c) shows tissue hemodynamics indices and the like without the judgment step, Figure 13(d) shows the average pulse wave waveform (adopted data) subjected to the above process 2) (judgment step), Figure 13(e) shows the waveform of Figure 13(d) normalized to the blood volume in blood vessels (vertical axis) and time (horizontal axis), and Figure 13(f) shows tissue hemodynamics indices and the like with the judgment step. As shown in FIG. 13, by removing outliers in the judgment process, it was possible to obtain a stable index of tissue hemodynamics without compromising the inherent characteristics of the pulse wave.

[0043] Test 6: Comparison by age of subjects <Test conditions> Target: Women in their 20s (younger generation) Women in their 50s (middle-aged and older) Measurement area: Back of left hand (wrist) Measurement time: 800 seconds Sampling rate:25fps(100sps,4sample averaging) Measurement equipment: Smart watch (Maxim Integrated MAXREFDES103#) Photoplethysmography Floodlight: Green LED (530 nm) Red LED (655 nm) Near-infrared LED (940nm) Receiver: PD Contact Measurement <Test Method> 1) The belt is worn about one finger's width from the bone (ulnar styloid process) of the left wrist toward the arm. Three LEDs (33-35) and two PDs (31, 32) are arranged alternately in this smartwatch. The test site is irradiated with pulsed light by the green LED 34, red LED 35, and near-infrared LED in the center of the back of the sensor. The internally reflected light from the test site is received by the two PDs at multiple wavelengths, and the pulse wave is measured for 800 seconds under the condition of 25 fps. While capturing the luminance value in real time, the pulse wave waveform is inverted, the peak of the waveform is detected, and the pulse wave waveform is cut out for each pulse beat. The process of inverting the pulse wave waveform corresponds to step S230, and the process of cutting out the pulse wave waveform for each pulse beat corresponds to step S240. 2) The pulse waveform extracted for each of the multiple pulse beats is subjected to processing that can remove artifacts without compromising the inherent characteristics of the pulse waveform, and the pulse waveform is identified. Specifically, the six components that are the main components of the pulse waveform are extracted, and for each main component, outliers are determined from the probability distribution using a statistical analysis method that uses standard deviation, and these are removed. The pulse waveform identification process corresponds to the judgment process in step S250 (steps S251 to S256). a) Pulse period (waveforms exceeding ±3SD from the mean period of the waveform are excluded as outliers.) b) Peak arrival time (waveforms with peak values ​​of 0.1 s or less or 0.5 s or more are excluded as outliers.) c) Ratio of average fluctuation component to stationary component (waveforms that are more than ±3SD from the ratio of the average fluctuation component to the stationary component of the waveform are excluded as outliers.) d) Minimum vascular blood volume (waveforms that are more than ±3SD from the minimum vascular blood volume of the waveform are excluded as outliers.) e) Mean intravascular blood volume (waveforms that are more than ±3SD from the mean intravascular blood volume of the waveform are excluded as outliers.) f) Maximum intravascular blood volume (waveforms exceeding ±3SD from the maximum intravascular blood volume of the waveform are excluded as outliers.) 3) The pulse waveforms cut out for each of the selected pulse beats are taken as an average pulse waveform (selected data). Note that the process of taking the pulse waveform and converting it into an average pulse waveform corresponds to step S257. 4) The obtained average pulse waveform is normalized with respect to the intravascular blood volume on the vertical axis and time on the horizontal axis.

[0044] <Test Results> The results of Test 6 are shown in FIG. 14 to FIG. Fig. 14(a) shows the ratio of the pulse waveform of blood volume in blood vessels normalized by one pulse time after irradiating the test site (predetermined area) with pulsed light from a green LED 34, performing the above-mentioned processing on the acquired internally reflected light, and showing the ratio. Similarly, Fig. 14(b) shows the test site (predetermined area) irradiated with pulsed light from a red LED 35, and Fig. 14(c) shows the test site (predetermined area) irradiated with pulsed light from a near-infrared LED 33. In all of Figs. 14(a) to (c), the light solid lines show a woman in her 20s, and the dark solid lines show a woman in her 50s. In Fig. 15(a), the test site (predetermined area) is irradiated with pulsed light from a green LED 34, the internal reflection light is acquired, and the above-mentioned processing is performed to obtain an average pulse wave waveform normalized with respect to the blood volume in the blood vessels on the vertical axis and the time on the horizontal axis, with the upper waveform being for young people and the lower waveform being for middle-aged and elderly people. Similarly, Fig. 15(b) shows the test site (predetermined area) irradiated with pulsed light from a red LED 35, and Fig. 15(c) shows the test site (predetermined area) irradiated with pulsed light from a near-infrared LED 33. The values ​​in Figs. 15(a) to (c) are shown as the mean ± standard deviation. Figure 16 shows the comparison results of sustained high blood volume in blood vessels (BOT) depending on age group when measuring pulse waves with different wavelengths. The following can be seen from Figures 14 to 16. Compared to the middle-aged and elderly group, the younger group showed a significant increase in the persistence of intravascular blood volume (BOT) with green light at a significance level of 5%, but furthermore, a significant increase in BOT was observed with red and near-infrared light at a significance level of 1%. Furthermore, in the younger group, no significant difference was observed in the persistence of intravascular blood volume due to differences in wavelength, but in the middle-aged and elderly group, a significant decrease in the persistence of intravascular blood volume (p<0.01) was observed with red and near-infrared light compared to green light. These results confirmed that age-related differences in pulse waveforms were due to differences in the wavelengths measured. It is predicted that the longer the wavelength, the deeper the measurement depth will be, suggesting the possibility that changing the wavelength may enable the selection of blood vessels to be measured.

[0045] <System for estimating tissue hemodynamic indices> The tissue hemodynamic index estimation system 100 will be described with reference to FIG. The tissue hemodynamic index estimation system 100 in this embodiment is composed of a reflected light intensity acquisition unit 210, a blood flow rate change calculation unit 220, and a tissue hemodynamic index estimation unit 230. The system also includes an information processing device 200 capable of executing various processes, and the information processing device 200 includes the reflected light intensity acquisition unit 210, the blood flow rate change calculation unit 220, and the tissue hemodynamic index estimation unit 230. The information processing device 200 includes an input device such as a keyboard or a pointing device, an arithmetic processing device, a storage unit, and the like. The information processing device 200 preferably includes a display device, but may be provided outside the information processing device 200 and connected via a network.

[0046] The reflected light intensity acquisition unit 210 is a part that acquires a physical quantity based on time-series internally reflected light of a predetermined region of the body surface, and the source of the physical quantity based on time-series internally reflected light can be any source, such as from a predetermined medium, via a network, or from the smartphone 10. In addition, the reflected light intensity acquisition unit 210 acquires a physical quantity based on time-series internally reflected light received by the smartphone 10 or the smart watch 30. The blood flow rate change calculation section 220 is a part that calculates the change over time in blood flow rate in blood vessels for at least one pulse cycle, based on a physical quantity based on the acquired time-series internally reflected light. The tissue hemodynamics index estimating unit 230 is a part that estimates a tissue hemodynamics index. The processes performed by the reflected light intensity acquisition section 210, the blood flow change calculation section 220, and the tissue hemodynamic index estimation section 230 are similar to those described above in the method of estimating a tissue hemodynamic index. Moreover, the tissue hemodynamic index estimation system 100 preferably includes a smartphone 10 (corresponding to a mobile terminal) or a smart watch 30 (corresponding to a wearable terminal) that can be linked with the smartphone 10. 1(a), the smartphone 10 is equipped with a camera 11 and an LED 12 on the back of the smartphone 10. The smartphone 10 irradiates visible light using the LED 12 (corresponding to a light-emitting means) and captures (receives) the internally reflected light of the irradiated light using the camera 11 (corresponding to a light-receiving means). As shown in Fig. 2(a), the smart watch 30 that can be linked with the smartphone 10 is provided on the back of the smart watch 30 with PDs (photodiodes) 31 and 32, a near-infrared LED 33 that irradiates near-infrared light, a green LED 34 that irradiates visible light, and a red LED 35. The PDs 31 and 32 correspond to light receiving means, and the near-infrared LED 33, the green LED 34, and the red LED 35 correspond to light emitting means.

[0047] <Evaluation of tissue hemodynamic indices> The method for evaluating tissue hemodynamic indexes includes a reflected light intensity acquisition step, a blood flow rate change calculation step, a tissue hemodynamic index estimation step, and an evaluation step. The reflected light intensity acquisition step, the blood flow rate change calculation step, and the tissue hemodynamic index estimation step are the same as those of the above-mentioned tissue hemodynamic index estimation method. In the evaluation step, it is possible to evaluate the state of blood circulation and the state of blood vessels based on the estimated tissue hemodynamic index. It is preferable that the estimated values ​​and the created graphs can be displayed on a display device or output, such as by printing, so that the evaluator can easily make the evaluation. It is also preferable that the estimated results of other subjects can be displayed and output for comparison. In general, by observing the change in the value of the tissue hemodynamic index, it is possible to grasp the risk of lifestyle-related diseases. For example, the value of the tissue hemodynamic index allows the inflow of blood into the tissue, the continuity of blood into the tissue, the outflow of blood from the tissue, the variability of blood volume, and the like to be grasped, so it is possible to grasp the reaction of blood vessels to the pulsation of the pulse wave. When blood is stored in the tissue blood vessels, the efficiency of material exchange between the blood and the vascular tissue decreases, so it can be estimated that the blood vessels are hard with reduced vascular elasticity. In addition, since it is known that there is a correlation between the continuity of blood volume in the tissue blood vessels and age, it is also possible to estimate whether the vascular age is appropriate for the actual age from the value of the tissue hemodynamic index. Therefore, by observing the change in the value of the tissue hemodynamic index, it can be used to predict the risk of lifestyle-related diseases associated with the deterioration of the vascular condition, to present advice on lifestyle habits to improve the vascular condition, and to present advice on lifestyle habits to improve the vascular age, and it is possible to utilize it for the prevention of lifestyle-related diseases and health promotion. In general, by observing the condition of blood vessels and blood flow on the surface of the body (just below the skin), it is possible to understand (evaluate) the moisture state of the skin, the elasticity of the skin, and the condition of the gums, and this can also be used to provide advice to improve these conditions.

[0048] As described above, the present invention has been described by showing specific embodiments, but the present invention is not limited to the above-described embodiments and also includes various modifications, improvements, and other aspects as long as the object of the present invention is achieved. <Modification>

[0049] In this embodiment, the physical quantity based on the internally reflected light is acquired to measure the pulse wave, but for example, if the predetermined area is a thin tissue such as an earlobe, a fingertip, or gums, the pulse wave can be measured from the physical quantity based on the transmitted light, and it is also possible to estimate the tissue hemodynamic index from the physical quantity based on the transmitted light. When the transmitted light is used, red light or near-infrared light is irradiated onto a predetermined area of ​​the body surface, and the remaining light that is reflected, scattered, and absorbed passes through the body, and the pulse wave can be measured from the physical quantity based on the time-series change of the transmitted light including the forward scattered light. This pulse wave contains a wealth of information on the hemodynamics in the body from the shallow part through which the light has passed to the deep part, and it is also possible to estimate the tissue hemodynamic index from the physical quantity based on the transmitted light.

[0050] The selection conditions in the selection of the wavelength band (step S210) will be described. FIG. 18(a) is an image of blood vessels near the wrist, and the thickness of the lines varies depending on the type of blood vessel. FIG. 18(b) is a cross-sectional image of FIG. 18(a), and shows that the distance from the body surface to which light reaches varies depending on the wavelength band of the irradiated light. Also, as is clear from FIG. 18(b), thicker blood vessels are located at a position farther from the body surface. Also, the normal value of the tissue hemodynamic index varies depending on the type of blood vessel. Also, as is clear from Test 6, differences in pulse waveforms depending on age are observed due to differences in wavelength. Therefore, it is preferable to select the wavelength band to be used depending on factors such as the type of blood vessel in the specified area, the position of the blood vessel, the value of the tissue hemodynamic index to be estimated, and the age of the subject. That is, it is preferable that the wavelength band selection step determines the wavelength band to be selected based on at least one of the type of blood vessel in the specified area, the position of the blood vessel in the specified area, and the biological information of the subject. Also, when selecting a wavelength band, for example, an appropriate wavelength band may be selected by inputting the type of blood vessel, or an appropriate wavelength band may be selected by inputting the age and health condition of the subject (particularly, the presence or absence of lifestyle-related diseases). As described in Non-Patent Document 1, hemoglobin has the property of absorbing light between visible light and near infrared light. However, the wavelength range of 700 nm to 1300 nm is called the optical window, and light can penetrate deeply into biological tissues relatively without being absorbed. Light with a wavelength longer than the optical window is absorbed by water. Also, as described in Non-Patent Document 2, when the light-emitting element and the light-receiving element of the photoelectric sensor are arranged on the same plane of the living body, the average depth of light into the living body is about half the distance between the light-emitting element and the light-receiving element, and it is also possible to utilize the property that a hemispherical area with the diameter of the light-transmitting and receiving distance becomes the measurement area. In this way, it is possible to measure and analyze the optimal pulse wave by adjusting the wavelength band and the light-transmitting and receiving distance to the blood vessel to be measured and controlling at least one of the light emission amount of the light-emitting element and the light-receiving sensitivity of the light-receiving element. Furthermore, the normalized waveform using this pulse wave measurement data can visualize the characteristics of tissue hemodynamics and compare the waveforms even before estimating the tissue hemodynamics index. The types of blood vessels handled by this estimation method are elastic arteries, muscular arteries, small arteries and arterioles, peripheral circulation, peripheral vascular beds, venules and venules.Once the type of blood vessel to be measured is selected, it is possible to estimate from indices of tissue hemodynamics whether the specific functions of that blood vessel are functioning normally, such as a decrease in vascular endothelial function resulting in a loss of vascular flexibility, changes in functional vascular tone due to regulation of sympathetic nerves and humoral factors, the efficiency of material exchange between blood and tissues, irreversible hardening of the organic vascular wall resulting in vascular wall thickening and plaque formation, and regulation of local blood volume.

[0051] In this embodiment, in the judgment step (step S250), whether or not to use the data in the tissue hemodynamic index estimation step is judged for each cycle with respect to the six conditions described above, and the data that satisfies all the conditions is used, but this is not limited to this. Each condition is related to the type of blood vessel in the specified area, the position of the blood vessel, the age of the subject, and the value of the tissue hemodynamic index to be estimated, so it is only necessary to decide which condition to use by taking these into consideration.

[0052] In this embodiment, as shown in the flowchart of Fig. 6, the averaging process (step S257) is performed on the data that has been subjected to the determination process (steps S251 to S256), but this is not limited to the above. For example, before step S251, a selection of whether or not to perform the determination process may be added, and if it is selected not to perform the determination process, the averaging process may be performed using all the waveforms.

[0053] In this estimation method, the reflected light intensity acquisition process (step S100) is configured to acquire a physical quantity based on internally reflected light, but the reflected light intensity acquisition process may also include an irradiation process in which light is irradiated onto a predetermined area of ​​the body surface from a light-emitting device (LED 12 of smartphone 10, near-infrared LED 33, green LED 34, red LED 35 of smart watch 30), and a light-receiving process in which the internally reflected light of the predetermined area of ​​the body surface is received by a light-receiving device (camera 11 of smartphone 10, PDs 31, 32 of smart watch 30) arranged in a position where it is difficult to receive anything other than the internally reflected light of the light irradiated onto the predetermined area of ​​the body surface.

[0054] In this embodiment, the judgment is made using the standard deviation in the judgment step, but this is not limiting, and the Smirnoff-Grubbs test, trimmed mean, and box plot / interquartile range may also be used. [Explanation of symbols]

[0055] 10. Smartphones 11 Camera 12 LED 13 Display screen 30 Smartwatch 31 PD 32PD 33 Near-infrared LED 34 Green LED 35 Red LED 100 Tissue Hemodynamic Index Estimation System 200 Information processing device 210 Reflected light intensity acquisition unit 220 Blood flow change calculation unit 230 Tissue hemodynamic index estimation section

Claims

1. a reflected light intensity acquisition step of acquiring a physical quantity based on time-series internally reflected light of a predetermined region of a body surface; a blood flow rate change calculation step of calculating a change in blood volume over time in a blood vessel for at least one pulse cycle based on the physical quantity; a tissue hemodynamics index estimating step of estimating a tissue hemodynamics index indicating a hemocirculatory state based on the calculated change over time in the blood volume in the blood vessel; A method for estimating tissue hemodynamic indexes, comprising:

2. The method for estimating tissue hemodynamic indicators according to claim 1, characterized in that the blood flow change calculation process includes a wavelength band selection process for selecting a physical quantity based on internally reflected light in a predetermined wavelength band from the physical quantities acquired in the reflected light intensity acquisition process.

3. The blood flow rate change calculation step calculates a change in the blood flow rate in the blood vessel over a plurality of periods, 3. The method for estimating a tissue hemodynamic index according to claim 1, wherein the tissue hemodynamic index estimation step estimates the tissue hemodynamic index based on a change over time in the blood volume in the blood vessel that satisfies a predetermined condition.

4. The predetermined conditions include a plurality of conditions, The method for estimating tissue hemodynamic indicators according to claim 3, characterized in that a specified condition to be used is selected from the plurality of specified conditions based on at least one of the type of blood vessel within the specified region, the position of the blood vessel within the specified region, or the subject's biometric information.

5. The method for estimating a tissue hemodynamic index according to claim 3 or 4, characterized in that the tissue hemodynamic index estimation process includes an averaging process of averaging the change over time in the blood volume in the blood vessel determined to satisfy the specified condition.

6. The method further includes a feature amount calculation step of calculating a feature amount related to a blood volume in the blood vessel and a change in the blood volume in the blood vessel over time, The feature amount calculation step includes: A first time that is a half-width of the maximum value of the blood volume in the blood vessel; A second time which is the total length from the time when the blood volume in the blood vessel rises to the time when the blood volume falls; A third time from the time when the blood volume in the blood vessel rises to the time when the blood volume reaches a maximum value; a fourth time from the peak time to the fall time of the blood volume in the blood vessel as the feature amount, A method for estimating a tissue hemodynamic index according to any one of claims 1 to 5, characterized in that the tissue hemodynamic index estimation step estimates the tissue hemodynamic index using one or more of the first time, the second time, the third time, or the fourth time.

7. The method further includes a feature amount calculation step of calculating a feature amount related to a blood volume in the blood vessel and a change in the blood volume in the blood vessel over time, The feature amount calculation step includes: a maximum blood volume in the blood vessel; the average blood volume in the blood vessel; a minimum blood volume in the blood vessel; a maximum increase in the amount of blood in the blood vessel per a predetermined time period; and A method for estimating a tissue hemodynamic index according to any one of claims 1 to 5, characterized in that the tissue hemodynamic index estimation process estimates the tissue hemodynamic index using one or more of the maximum blood volume in the blood vessel, the average blood volume in the blood vessel, the minimum blood volume in the blood vessel, or the maximum increase among the increases in blood volume in the blood vessel.

8. a reflected light intensity acquisition means for acquiring a physical quantity based on time-series internally reflected light of a predetermined region of a body surface; a blood flow rate change calculation means for calculating a change in blood flow rate over time in a blood vessel for at least one pulse cycle based on the physical quantity; a tissue hemodynamics index estimating means for estimating a tissue hemodynamics index indicating a blood circulation state based on the calculated change over time in the blood volume in the blood vessel; A system for estimating tissue hemodynamic indices, comprising:

9. A light emitting means for irradiating visible light or near infrared light; and a light receiving means for receiving internally reflected light of the light irradiated onto the predetermined area of ​​the body surface by the light emitting means, the light receiving means is mounted on a mobile terminal or a wearable terminal capable of linking with a mobile terminal, The reflected light intensity acquisition means The system for estimating a tissue hemodynamic index according to claim 8, further comprising a step of acquiring a physical quantity based on the time-series internally reflected light received by the light receiving means.

10. a reflected light intensity acquisition step of acquiring a physical quantity based on time-series internally reflected light of a predetermined region of a body surface; a blood flow rate change calculation step of calculating a change in blood volume over time in a blood vessel for at least one pulse cycle based on the physical quantity; a tissue hemodynamics index estimating step of estimating a tissue hemodynamics index indicating a hemocirculatory state based on the calculated change over time in the blood volume in the blood vessel; An evaluation step of evaluating a blood vessel state based on the tissue hemodynamic index; A method for evaluating tissue hemodynamic indicators, comprising:

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