Estimation method and estimation system

Abstract

To provide a technique for calculating blood flow change information from time-series images of a predetermined region of a user's body surface and estimating a mental subjective evaluation level and a physical subjective evaluation level.SOLUTION: An estimation method estimates a user's mental subjective evaluation level and physical subjective evaluation level on the basis of images obtained by imaging the user's body surface by an imaging device, and comprises: an image acquisition step of acquiring time-series images of a predetermined region of the user's body surface; a blood flow change calculation step of calculating a numerical value correlated with a temporal change in the blood flow on the basis of the time-series images; a periodic blood flow amount calculation step of calculating blood flow change information representing a temporal change in the blood flow amount within a blood vessel for at least one cycle of pulses on the basis of a change in the numerical value correlated with the calculated temporal change in the blood flow; and a subjective evaluation level estimation step of estimating the user's mental subjective evaluation level and physical subjective evaluation level on the basis of the calculated blood flow change information.SELECTED DRAWING: Figure 1

Description

[Technical Field]

[0001] The present invention relates to a method for estimating a user's mental subjective assessment level and a user's physical subjective assessment level. [Background technology]

[0002] There is a method for measuring the blood flow rate in the skin by the laser speckle method (Patent Document 1). There is also a method for evaluating heat fatigue, mental fatigue, and physical fatigue based on pulse waves measured by a pulse wave measuring device and indicators such as environmental conditions (Patent Document 2). [Prior art documents] [Patent documents]

[0003] [Patent Document 1] Patent No. 6507639 [Patent Document 2] Japanese Patent Application Publication No. 2019-136114 Summary of the Invention [Problem to be solved by the invention]

[0004] In Patent Document 1, measurements are made using a light intensity image captured by irradiating a laser beam, and therefore it is not suitable for users to measure the blood flow rate in the skin in their daily lives. Furthermore, in Patent Document 2, the pulse wave is measured using a pulse wave measuring device, and measurements other than the pulse wave are also required, making it unsuitable for estimating the mental subjective assessment level and the physical subjective assessment level in daily life.

[0005] The present invention has been made in view of the above-mentioned problems, and relates to a method for estimating a user's mental subjective evaluation level and a user's physical subjective evaluation level based on an image of the user's body surface captured by an imaging device. [Means for solving the problem]

[0006] The present invention relates to an estimation method for estimating a mental subjective assessment level and a physical subjective assessment level of a user based on images of the user's body surface captured by an imaging device, the estimation method including: an image acquisition step for acquiring time-series images of a predetermined area of ​​the user's body surface; a blood flow change calculation step for calculating a numerical value correlating with a change in blood flow over time based on the time-series images; a periodic blood flow rate calculation step for calculating blood flow change information, which is a change in blood flow rate over time in blood vessels for at least one pulse cycle, based on the calculated change in the numerical value correlating with the change in blood flow over time; and a subjective assessment level estimation step for estimating the mental subjective assessment level and the physical subjective assessment level of the user based on the calculated blood flow change information.

[0007] The present invention also relates to an estimation system that uses a control device to estimate a mental subjective evaluation level and a physical subjective evaluation level of a user based on images of the user's body surface captured by an imaging device, the estimation system including: image acquisition means for acquiring time-series images of a predetermined area of ​​the user's body surface; blood flow change calculation means for calculating a numerical value correlating with a change in blood flow over time based on the time-series images; periodic blood flow calculation means for calculating blood flow change information, which is a change in blood flow over time in blood vessels for at least one pulse cycle, based on the calculated change in the numerical value correlating with the change in blood flow over time; and subjective evaluation level estimation means for estimating the mental subjective evaluation level and the physical subjective evaluation level of the user based on the calculated blood flow change information. [Effects of the Invention]

[0008] According to the method provided by the present invention, blood flow change information can be calculated based on values ​​correlated with changes in blood flow over time calculated from acquired time-series images, and the user's mental subjective assessment level and physical subjective assessment level can be estimated, thereby enabling daily mental and physical health management. [Brief explanation of the drawings]

[0009] [Figure 1] FIG. 10 is a conceptual diagram of a method for calculating blood flow change information. [Figure 2] FIG. 10 is a diagram showing the results of a comparison between a case in which blood flow change information is extracted by LSFG and tissue hemodynamic indices are calculated, and a case in which blood flow change information is extracted by the estimation method of the present invention and tissue hemodynamic indices are calculated. [Figure 3] FIG. 10 is a diagram showing the results of a comparison between a case in which blood flow change information is extracted by LSFG and tissue hemodynamic indices are calculated, and a case in which blood flow change information is extracted by the estimation method of the present invention and tissue hemodynamic indices are calculated. [Figure 4] 1 is a flowchart of an estimation method. [Figure 5] 10 is a flowchart showing a blood flow change calculation process. [Figure 6] 10 is a flowchart showing a periodic blood flow rate calculation process. [Figure 7] (1) is a diagram for explaining the calculation process of blood flow change information, (2) is a diagram for explaining the calculation process of blood flow change information, and (3) is a diagram for explaining the calculation process of blood flow change information. [Figure 8] FIG. 1 is a diagram illustrating each tissue hemodynamic index. [Figure 9] 10 is a flowchart for calculating tissue hemodynamic indices. [Figure 10] (1-1) is a diagram showing the calculation results, (1-2) is a diagram showing the calculation results, and (2) is a diagram showing the calculation results. [Figure 11] (1) is a diagram showing the calculation results, (2) is a diagram showing the calculation results, and (3) is a diagram showing the calculation results. [Figure 12] FIG. 10 is a diagram showing evaluation results. [Figure 13] FIG. 10 is a diagram showing evaluation results. [Figure 14] FIG. 10 is a diagram showing the relationship between principal components and chronological age. [Figure 15] FIG. 10 is a diagram showing evaluation results. [Figure 16] FIG. 1 is a diagram illustrating an example of an evaluation process. [Figure 17] FIG. 1 is a conceptual diagram of an estimation system. DETAILED DESCRIPTION OF THE INVENTION

[0010] Hereinafter, preferred embodiments of the present invention will be described with reference to the drawings. Note that the drawings of the present embodiments are 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 designated by similar reference numerals, and duplicated descriptions will be omitted as appropriate.

[0011] <Summary> An outline of a method for calculating blood flow change information and a subjective evaluation level estimation method (hereinafter sometimes referred to as this method) for estimating a user's mental subjective evaluation level and a user's physical subjective evaluation level in this embodiment will be described. This method includes an image acquisition step of acquiring time-series images of a predetermined area of ​​the user's body surface; a blood flow change calculation step of calculating a numerical value correlating with a change in blood flow over time based on the acquired time-series images; a periodic blood flow calculation step of calculating blood flow change information, which is a change in blood flow over time in the blood vessels for at least one pulse cycle, based on the calculated change in the numerical value correlating with the change in blood flow over time; and a subjective evaluation level estimation step of estimating the user's mental subjective evaluation level and the user's physical subjective evaluation level based on the calculated change in blood flow over time in the blood vessels.

[0012] When calculating blood flow change information from body surface observations, for example, as disclosed in Patent Document 1, LSFG (Laser Speckle Flowgraphy), a technology that visualizes blood flow distribution using reflected and scattered laser light, has been used. However, LSFG requires a device for irradiating laser light, making it difficult for general users to obtain blood flow change information on a daily basis at home, etc. Therefore, the inventors have developed a method for calculating blood flow change information on a daily basis by calculating values ​​correlating with changes in blood flow over time from time-series images of the body surface. Furthermore, by estimating the user's mental subjective assessment level and the user's physical subjective assessment level from the calculated blood flow change information, it becomes possible to understand the user's mental and physical conditions on a daily basis.

[0013] Figure 1 shows a conceptual diagram of this method. As shown in Figure 1, this method involves capturing images of the body surface (facial skin in this embodiment) of a user (hereinafter also referred to as a subject) using a visible light camera, such as a camera attached to a personal computer, a camera built into a tablet terminal, a camera built into a smartphone, or a digital video camera. This method extracts blood flow change information (blood flow waveform), which is a time-dependent change in blood flow volume within blood vessels, based on changes in values ​​correlated with blood flow changes, and therefore the captured images must be time-series images. The captured time-series images contain not only the blood flow (signal) required for this method, but also noise such as the subject's movement and uneven lighting during imaging. Therefore, the RGB waveform of each pixel in the time-series images is subjected to independent component analysis, separated into hemoglobin, melanin, and shading components, and then subjected to a specified filter process to extract the waveform of only the hemoglobin component (blood flow waveform). In this embodiment, a known technique (for example, a pigment component analysis method from a skin color image (Reference: Norimichi Tsumura, Nobutoshi Ojima, Kayoko Sato, Mitsuhiro Shiraishi, Hideto Shimizu, Hirohide Nabeshima, Syuuichi Akazaki, Kimihiko Hori, Yoichi Miyake, Image-based skin color and texture analysis / synthesis by extracting hemoglobin and melanin information in the skin, ACM Transactions on Graphics, Vol. 22, No. 3, pp. 770-779 (2003). (Proceedings of ACM SIGGRAPH 2003))) is used to extract the waveform of only the hemoglobin component. Note that in this method, the amount of change in hemoglobin amount is used as the change in value correlated with the change in blood flow, and the blood flow waveform is extracted based on the amount of change in hemoglobin amount. However, other components may be used as long as they are numerical values ​​correlated with the hemoglobin amount, and it is not necessary to use only the hemoglobin amount.

[0014] Next, Figures 2 and 3 show the results of a comparison between the case where blood flow waveforms (corresponding to "blood flow change information") are extracted by LSFG and tissue hemodynamic indices are calculated, and the case where blood flow waveforms are extracted and tissue hemodynamic indices are calculated using this method. "Tissue hemodynamic indices" are indices that can be calculated from the average one pulse waveform and can be used to evaluate the continuity of blood flow, etc. The measurement conditions here are as follows: Subjects: 7 people in their 30s to 50s (total of men and women) Method: Resting facial skin blood flow was measured for 10 seconds Camera imaging conditions: 30 [fps], 10 seconds of imaging Image compression: None Lighting: LED (5000K) Measurement area: left cheek Measurement area: approx. 4cm 2 (2cm x 2cm) Number of pixels: Approximately 5000 2 and 3 show the BOT (Blowout Time) among the tissue hemodynamic indices, but as will be described later, similar results can be obtained with other tissue hemodynamic indices. As shown in Figure 2, when the blood flow values ​​calculated using LSFG and the blood flow values ​​calculated by this method are graphed together, the waveforms of the two are in good agreement, and as a result, it can be seen that the BOT values ​​calculated by this method have waveforms that are close to the BOT values ​​calculated using LSFG. Furthermore, as shown in Figure 3, it can be seen that there is a high correlation between the BOT values ​​calculated by this method and the BOT values ​​calculated using LSFG. As described above, the results of extracting blood flow waveforms and calculating tissue hemodynamic indices using this method are close to the results of extracting blood flow waveforms and calculating tissue hemodynamic indices using LSFG. Therefore, it is possible to extract blood flow waveforms and measure (calculate) tissue hemodynamic indices in everyday life. Furthermore, it is possible to estimate mental subjective assessment levels and physical subjective assessment levels using blood flow waveforms or tissue hemodynamic indices calculated from blood flow waveforms. These are thought to be useful for health management.

[0015] "Body surface" refers to the surface of the body, including the skin, lips, etc. Also, parts such as the eyeballs, palpebral conjunctiva, and gums that are not visible (cannot be touched) when the eyes or mouth are closed, but which become visible when the eyes or mouth are opened, in other words, parts that can be observed from the outside without medical intervention such as surgery, are considered to be included in the body surface. The "predetermined area on the body surface" may be any area on the body surface, and in this embodiment, the predetermined area is set on the cheek or forehead of the face. "Images captured by an imaging device" refers to images captured by a visible light camera, regardless of the type or performance of the imaging device. "Time-series images" are images obtained by capturing images of a predetermined area of ​​the body surface for a predetermined period of time. The number of frames per second of the time-series images should be 5 [fps] or more, and preferably 30 [fps] or more. The capturing time of the time-series images should be 2 seconds or more, and preferably 10 seconds or more. The time-series images can also be considered as moving images made up of multiple images. The "image acquisition process" is a process of acquiring time-series images of a specified area of ​​the body surface, and the source of the time-series images does not matter, such as acquisition from a specified medium, acquisition via a network, or acquisition directly from an imaging device (direct import from the imaging device). The "value correlating with the change in blood flow over time" is a value correlating with the flow of blood, and may be a value correlating with the amount of a specific component moving through the blood, such as the amount of change in hemoglobin. The "blood flow change calculation process" is a process of calculating a numerical value that correlates with the change in blood flow over time, extracting only a predetermined component in the blood for each frame and calculating the amount of the predetermined component for each pixel. In this embodiment, it is a process of extracting only the hemoglobin component for each frame of the acquired time-series images and calculating the amount of hemoglobin for each pixel. The calculation method will be described later. "Changes in numerical values ​​correlating with changes in blood flow over time" refers to time-dependent changes in numerical values ​​correlating with changes in blood flow over time, and the changes are understood based on values ​​calculated for each frame of the time-series image. In this embodiment, this refers to time-dependent changes in hemoglobin amount, and the changes are understood based on values ​​calculated for each frame of the time-series image. A "pulse" is a periodic movement that occurs when the pressure of blood in arterial blood vessels fluctuates due to the beating of the heart, and a "pulse" or "one cycle" is the period during which the pressure of blood in arterial blood vessels goes from its lowest value to its highest value before returning to its lowest value. "Intravascular blood flow" refers to the amount of blood flowing through a blood vessel per unit time, and since it changes depending on the heartbeat, it changes over time. When the pressure inside the blood vessel is high, the blood flow is high, and when the pressure inside the blood vessel is low, the blood flow is low. "Changes in blood flow volume within a blood vessel over time for one cycle" refers to the change in blood flow volume within a blood vessel per unit time in one cycle, which is the transition of blood flow volume. By showing this transition as a numerical value, waveform, etc., the blood flow volume can be grasped from the change in blood flow volume within the blood vessel. "Blood flow change information, which is the change in blood flow volume within a blood vessel over time for one cycle" refers to continuous information (values) of blood flow volume from the change in blood flow volume within the blood vessel per unit time for one cycle, and can be information regarding the flow of blood flow (flow velocity or flow volume), or a waveform (blood flow waveform) showing blood flow. The "periodic blood flow calculation process" is a process for calculating blood flow change information, and includes calculating continuous values ​​of blood flow from changes in blood flow in the blood vessels per unit time for one cycle, calculating a waveform indicating blood flow from changes in blood flow in the blood vessels for one pulse, and calculating a graph showing the relationship between the elapsed time for one pulse and blood flow in the blood vessels. "Mental subjective assessment level" is an index that shows how the user perceives (recognizes) their own mental state, and the index can be expressed in any way, including numerical values, words, or illustrations. The mental state refers to a state that expresses feelings such as anxiety, relief, restlessness, fidgeting, worry, ability to concentrate, motivation, excitement, depression, and irritability. The "physical subjective assessment level" is an index that indicates how the user perceives (recognizes) their own physical condition, and the index can be expressed in any way, such as numerical values, words, or illustrations. The physical condition is a state that indicates physical condition, such as feeling extremely tired, exhausted, sluggish, light-hearted, feeling refreshed, awake easily, unable to sleep, energetic, having an appetite, or having no appetite. "Estimating the user's mental subjective assessment level and the user's physical subjective assessment level" means estimating the mental subjective assessment level and the physical subjective assessment level based on calculated blood flow change information. As will be described in detail later, the inventors have found that there is a high correlation between the results of a questionnaire about a subject's mental subjective items and the subject's blood flow change information. Therefore, information showing the correlation between the results of a questionnaire about the mental subjective items of multiple subjects and the blood flow change information of the multiple subjects (e.g., a formula showing the correlation) is obtained, and the mental subjective assessment level is estimated using this information and blood flow change information calculated by capturing images of the user's body surface. The inventors have also found that there is a high correlation between the results of a questionnaire about a subject's physical subjective items and the subject's blood flow change information. Therefore, information showing the correlation between the results of interviews regarding physical subjective items for multiple subjects and the blood flow change information for the multiple subjects (for example, an equation showing the correlation) is obtained, and the physical subjective assessment level is estimated using this information and the blood flow change information calculated by imaging the user's body surface.

[0016] <Method for estimating mental and physical subjective assessment levels> A method for estimating the mental subjective evaluation level and the physical subjective evaluation level will now be described. Flowcharts of this method are shown in Figures 4 to 6. Note that Figures 4 to 6 only show characteristic processes of this method. The main flowchart of this method is shown in Figure 4. This method consists of an image acquisition step, a blood flow change calculation step, a periodic blood flow calculation step, and a subjective assessment level estimation step.

[0017] The image acquisition process (step S100) is a process of acquiring time-series images of a predetermined area of ​​the body surface for a predetermined time. In this process, the time-series images may be acquired from any source, such as from a predetermined medium, via a network, or from an imaging device.

[0018] The blood flow change calculation step (step S200) is a step of calculating a numerical value correlating with the change in blood flow over time for each pixel from the acquired time-series image data. Figure 5 shows a flowchart of the blood flow change calculation step.

[0019] In step S210, red, green, and blue information for each pixel is calculated for each frame of the acquired time-series image data. Since this method uses images captured by a visible light camera, it is possible to calculate RGB information for each pixel and extract RGB waveforms.

[0020] Step S220 is a process of extracting numerical values ​​that correlate with changes in blood flow over time from the RGB waveform. In this embodiment, hemoglobin component values ​​are used as the numerical values ​​that correlate with changes in blood flow over time, so this process extracts hemoglobin component values ​​(extracts the waveform of hemoglobin amount). Here, we will explain how to calculate hemoglobin components using this method. Oxyhemoglobin present in blood vessels (arteries) has the property of absorbing specific incident light. This property can be utilized to monitor blood flow, which changes with cardiac pulsation. The extracted RGB waveform contains not only the hemoglobin component but also melanin components, shadow components, and other components. In this method, components other than the hemoglobin component constitute noise. Therefore, independent component analysis is performed on the RGB waveform to extract only the hemoglobin component. By extracting only the hemoglobin component in this way (creating a waveform containing only the hemoglobin component), blood flow can be monitored. In this embodiment, the pigment component analysis method from a skin-color image described above is used to extract only the hemoglobin component from the RGB waveform.

[0021] In step S230, the extracted hemoglobin amount waveform is inverted (positive / negative inversion). When blood flow is monitored using LSFG, reflected light is monitored. When blood flow is monitored using an image captured by a visible light camera, as in the present method, hemoglobin absorbance is monitored. Because the relationship between reflected light and absorbance must be inverted, accurate evaluation cannot be achieved by comparing the extracted waveform with the one calculated using LSFG. In this embodiment, the tissue hemodynamic indices calculated from the blood flow waveform calculated by the present method are compared with the tissue hemodynamic indices calculated from the blood flow waveform calculated using LSFG. To evaluate the effectiveness of the blood flow waveform calculated by the present method, the extracted waveform is inverted. The inversion process (step S230) is necessary when comparing the tissue hemodynamic indices calculated from the blood flow waveform calculated by the present method with the tissue hemodynamic indices calculated from the blood flow waveform calculated using LSFG. However, if comparison is not performed, the inversion process may or may not be performed.

[0022] Returning to FIG. 4, the periodic blood flow rate calculation step (step S300) is a step of extracting one pulse cycle using the waveform of a value correlated to the calculated blood flow change and calculating an average one pulse waveform. As described above, in this embodiment, the hemoglobin amount is used as the value correlated to the blood flow change, so the calculation is performed using the waveform of the hemoglobin amount. FIG. 6 shows a flowchart of the periodic blood flow rate calculation step. The processing content of the periodic blood flow rate calculation step will be explained in conjunction with the graph shown in FIG. 7.

[0023] Step S310 detects the peaks of the waveform and performs processing to cut out each pulse waveform. FIG. 7(1) shows the waveform of hemoglobin amount (waveform after inversion processing in step S230). The negative peak position of the hemoglobin amount waveform is detected as a minimum value, and each pulse is extracted. In the case of FIG. 7(1), a waveform for 11 pulses can be extracted. In this embodiment, only frames within a predetermined value of 20% of the median number of frames constituting one pulse are used. This is to eliminate waveform disturbances due to measurement errors and determine tissue hemodynamic indices. The data range used for processing (predetermined value 20%) can be set appropriately.

[0024] In step S320, normalization is performed for each pulse waveform extracted in step S310. The normalization may be performed on both the hemoglobin component amount (vertical axis) and the time (horizontal axis) for each pulse waveform, or on either one of them. In this embodiment, normalization is performed on the hemoglobin component amount (vertical axis). FIG. 7(2) shows a graph in which waveforms extracted for each pulse waveform are normalized and then superimposed.

[0025] Step S330 is a process for calculating an average pulse waveform. Since normalization is performed for each pulse waveform in step S320, an average is calculated for each time.

[0026] In step S340, the calculated average pulse waveform is normalized. In this embodiment, the normalization in this step is performed on the hemoglobin component amount (vertical axis) and time (horizontal axis). Figure 7(3) shows the calculated average pulse waveform.

[0027] In this way, the periodic blood flow rate calculation step (corresponding, for example, to step S300) is assumed to include an averaging step (corresponding, for example, to step S330) of calculating multiple pulse cycles (corresponding, for example, to step S310) and averaging the waveforms of the multiple cycles to obtain an average waveform of the hemoglobin amount. The periodic blood flow rate calculation step may also include a waveform normalization step (corresponding, for example, to step S320) of normalizing the waveform showing the change in the hemoglobin amount over the calculated multiple pulse cycles by the hemoglobin amount, and calculate one pulse cycle based on the normalized waveform (corresponding, for example, to step S310). Furthermore, the method is assumed to include an averaging step (corresponding, for example, to step S330) of obtaining the waveform.

[0028] Returning to FIG. 4, the subjective assessment level estimation step (step S400) is a step of estimating the user's mental subjective assessment level and the user's physical subjective assessment level based on the calculated blood flow change information. As described above, the mental subjective assessment level is estimated by obtaining information (e.g., a formula showing the correlation) showing the correlation between the results of interviews regarding the mental subjective items of multiple subjects and the blood flow change information of the multiple subjects, and using this information and the blood flow change information calculated by imaging the user's body surface. The physical subjective assessment level is estimated by obtaining information (e.g., a formula showing the correlation) showing the correlation between the results of interviews regarding the physical subjective items of multiple subjects and the blood flow change information of the multiple subjects, and using this information and the blood flow change information calculated by imaging the user's body surface. The content of the interviews administered to the multiple subjects will now be described.

[0029] In this embodiment, the level of "anxiety" is estimated as the mental subjective evaluation level. "Anxiety" refers to a state of feeling unsettled, restless, and unable to get worries out of one's head due to worries, concerns, or other issues. Furthermore, the level of "fatigue" is estimated as the physical subjective evaluation level. "Fatigue" refers to a state of feeling tired, listless, and malaise, and a desire to rest or not to move. Common interview items for measuring anxiety and fatigue include, for example, the Occupational Stress Assessment Questionnaire, the Chalder Fatigue Scale, and the WHO-5 Mental Health Status Questionnaire. Therefore, in this embodiment, the levels of anxiety and fatigue (hereinafter sometimes referred to as "anxiety score" and "fatigue score") are measured using these interview items that are commonly used in interviews. Among the multiple interview items, one or more interview items suitable for measuring anxiety and one or more interview items suitable for measuring fatigue are selected, and a score is assigned to each interview item to measure the anxiety score and fatigue score. The number of questionnaire items used to measure each score may be one or more. The number of questionnaire items used to measure the anxiety score and the number of questionnaire items used to measure the fatigue score may be the same or different. Then, information is created showing the correlation between the anxiety scores and fatigue scores measured from multiple subjects and the blood flow change information calculated from multiple subjects using this method.

[0030] Next, we will explain information showing the correlation between each score and blood flow change information. In this embodiment, we will explain two types of information: one based on tissue hemodynamic indices estimated based on blood flow change information, and one based on the analysis results of principal component analysis of blood flow change information.

[0031] <In the case of tissue hemodynamic indicators> FIG. 8 shows tissue hemodynamic indices estimated based on blood flow change information in this embodiment. BOT (Blowout Time): The continuity of high blood flow is an index showing the continuity of high MBR values, and the BOT value is expressed by the following formula using the half-width (time) (W) of the MBR value and the heartbeat width (time) (F) shown in Figure 8, as well as a proportionality constant "C." Note that the proportionality constant "C" in the following formula is a value determined for each formula. (BOT)=C·(W) / (F) Rising rate: A value indicating the time variation of the rate of blood flow rise, and is expressed by the following formula ("C" is a constant, and "S1" and "Sall" are the areas shown in Figure 4). Rising rate=C×(S1 / Sall) Falling rate: The time variation of the blood flow falling rate is an index that shows the time variation of the rate of fall from the maximum MBR value in the time waveform of the MBR value per heartbeat. Using (Sall) and (S2) shown in Figure 8, the falling rate can be expressed by the following equation. In the following, "C" is a proportionality constant. (Falling rate)=C·(S2) / (Sall) FAI: The maximum acceleration of blood flow during an increase indicates the maximum instantaneous blood flow rate during an increase in blood flow. ATI: The blood flow peak position is the proportion of the time during which the maximum MBR value (MBRmax in FIG. 8) of the MBR time waveform is reached in one heartbeat. RI (Resistivity Index): Peripheral vascular resistance is an index that indicates peripheral vascular resistance, and the RI value is obtained by dividing the difference between the maximum MBR value (MBRmax in Figure 8) and the minimum MBR value (MBRmin in Figure 8) by the maximum MBR value.

[0032] 9 shows the flow of the process of calculating tissue hemodynamic indices from the average one pulse waveform (tissue hemodynamic indices calculation step). The process of calculating tissue hemodynamic indices is performed before step S400 because the calculated tissue hemodynamic indices are used in the subjective assessment level estimation step in step S400. Steps S371 to S377 in FIG. 9 differ in the types of features related to changes in hemoglobin amount extracted from one pulse cycle, and only the necessary features need to be calculated depending on the tissue hemodynamic index to be calculated (only the necessary processing from steps S371 to S377 needs to be performed), and it is not necessary to perform all processing.

[0033] Step S371 is a process of calculating a first time, which is the half-width of the maximum value of the hemoglobin amount, based on the average one pulse waveform. Step S372 is a process of calculating a second time period, which is the total length from the rising edge to the falling edge of the hemoglobin amount, based on the average one pulse waveform. Step S373 is a process of calculating a third time period from the rising time of the hemoglobin amount to the peak time when the hemoglobin amount reaches its maximum value, based on the average one pulse waveform. Step S374 is a process for calculating a fourth time period from the peak to the fall of the hemoglobin amount based on the average one pulse waveform. Step S375 is a process for calculating the maximum amount of hemoglobin based on the average one pulse waveform. Step S376 is a process for calculating the minimum value of the hemoglobin amount based on the average one pulse waveform. Step S377 is a process of calculating the maximum increase in the amount of hemoglobin per predetermined time based on the average one pulse waveform. Step S378 is a process of calculating tissue hemodynamic indices (for example, BOT, ATI, falling rate, RI, and FAI). BOT is calculated using the first time and the second time. The ATI is calculated using the second and third times. The falling rate is calculated using the fourth time and the maximum value. RI is calculated using the maximum and minimum values. The FAI is calculated using the maximum increase.

[0034] Next, the calculation results in this embodiment will be described. <Measurement conditions> Subjects: Healthy men and women in their 20s to 70s N=100 Analysis area: Cheek Imaging conditions for this method: 30 [fps] 10 seconds of imaging Image compression: None Lighting: LED (5000K) Measurement area: forehead Measurement area: approx. 4cm 2 (2cm x 2cm) Number of pixels in the measurement area: Approximately 10,000 pixels Figure 10 (1-1) is a graph plotting the BOT values ​​calculated using LSFG on the vertical axis and the subject's age on the horizontal axis, and (1-2) is a graph plotting the BOT values ​​calculated using this method on the vertical axis and the subject's age on the horizontal axis. In the case of (1-1), there was a negative correlation between BOT value and age, and in the case of (1-2), there was also a negative correlation between BOT value and age. FIG. 10(2) shows the correlation coefficients between each index calculated using LSFG and the age of the subject, and the correlation coefficients between each index calculated using this method and the age of the subject. In the case of (2-1), the content is the same as that shown in FIG. 10(1), so the explanation will be omitted. (2-2) shows the rising rate. In the case of LSFG, there was a weak negative correlation between the rising rate and age, and in the case of the present method, there was a negative correlation between the rising rate and age. (2-3) shows the falling rate. In the case of LSFG, there was a weak positive correlation between the falling rate and age, and in the case of the present method, there was a positive correlation between the falling rate and age. (2-4) shows the RI, and in the case of LSFG, there was a positive correlation between RI and age, and in the case of this method, there was a weak positive correlation between RI and age. From these findings, it can be said that the tissue hemodynamic indices obtained by this method correspond to those obtained using LSFG.

[0035] As explained in Fig. 6, in this embodiment, when calculating the average one-pulse waveform in the periodic blood flow calculation step, normalization processing is performed on the hemoglobin component amount and elapsed time (see steps S320 to S340). The elapsed time is the time elapsed from the start point of one extracted cycle. Although tissue hemodynamic indices can be calculated without normalization processing, it is preferable to perform normalization processing as described below because a higher correlation coefficient can be obtained when normalization processing is performed compared to when normalization processing is not performed. Figure 11 shows the BOT value calculation results with and without normalization under the same measurement conditions as Figure 10. (1) shows the results when normalization was not performed on the hemoglobin component amount and elapsed time, and the BOT value calculated using this method was compared with the BOT value calculated using LSFG. (2) shows the results when normalization was performed on the hemoglobin component amount (intensity), and the BOT value calculated using this method was compared with the BOT value calculated using LSFG. (3) shows the results when normalization was performed on the elapsed time, and the BOT value calculated using this method was compared with the BOT value calculated using LSFG. As is clear from (1) to (3), the results when normalization was performed on the hemoglobin component amount and the elapsed time both showed a strong correlation with the BOT value calculated using LSFG. Furthermore, as is clear from (2) and (3), the results when normalization was performed on the hemoglobin component amount and the elapsed time showed a strong correlation with the BOT value calculated using LSFG. For these reasons, in this method, tissue hemodynamic indices are calculated using an average pulse waveform that has been normalized for hemoglobin amount and / or elapsed time.

[0036] We found that the fatigue level calculated using tissue hemodynamic indices (hereinafter referred to as the "fatigue score") was related to equation (1), which was created by logistic regression analysis using tissue hemodynamic indices, heart rate, and gender as explanatory variables. Fatigue score = 0.085 × BOT - 5,883 (1) The fatigue probability is calculated from the calculated fatigue score using equation (2). Fatigue probability p1 = -1 / (1 + exp(-1 × fatigue score)) (2) If the fatigue probability p1 was less than 0, it was determined that the subject was not fatigued, and if it was 0 or more, it was determined that the subject was fatigued. Table 1 shows the estimation results. [Table 1]

[0037] As shown in Table 1, a high rate of correct answers was achieved.

[0038] The anxiety score calculated using the tissue hemodynamic index (hereinafter referred to as the "anxiety score") is related to equation (3). Equation (3) was created by logistic regression analysis using tissue hemodynamic index, heart rate, and gender as explanatory variables. Anxiety score = 0.073 × BOT - 0.055 × ATI + 0.796 × Rising rate - 4.311 (3) The anxiety probability is calculated from the calculated anxiety score using equation (4). Anxiety probability p2 = -1 / (1 + exp(-1 × anxiety score)) (4) If the anxiety probability p2 was less than 0, it was determined to be "no anxiety," and if it was 0 or more, it was determined to be "anxious." Table 2 shows the estimation results. [Table 2]

[0039] As shown in Table 2, a high rate of correct answers was achieved.

[0040] <In the case of principal component analysis> Principal component analysis is performed on the blood flow change information, and principal components with a contribution rate of a predetermined value or more are analyzed (analysis step). In this embodiment, a regression equation is created using components with a contribution rate of 1% or more. In this embodiment, principal components with a contribution rate of 1% or more are used, but other percentage values ​​may be used, or a predetermined number of principal components may be used. In the principal component analysis of the blood flow change information, a regression equation was created by logistic regression analysis (forward variable addition) using components PC1 to PC7 with a contribution rate equal to or greater than a predetermined value (1 percent or greater in this embodiment), heart rate, and gender.The fatigue score using the predetermined principal components had the relationship shown in equation (5). That is, components PC1, PC2, and PC4 were adopted in equation (5). Fatigue score = 0.312 × PC1 score + 0.397 × PC2 score + 0.140 × PC4 score - 0.156 (5) The fatigue probability is calculated from the calculated fatigue score using equation (6). Fatigue probability p1 = -1 / (1 + exp(-1 × fatigue score)) (6) If the fatigue probability p1 was less than 0, it was determined that the subject was not fatigued, and if it was 0 or more, it was determined that the subject was fatigued. Table 3 shows the estimation results. [Table 3]

[0041] As shown in Table 3, a high rate of correct answers was achieved.

[0042] A regression equation was created by logistic regression analysis (forward variable addition) using components PC1 to PC7, heart rate, and gender, whose contribution rates were greater than a predetermined value (more than 1 percent in this embodiment) in the principal component analysis of blood flow change information.The anxiety score using the predetermined principal components had the relationship shown in equation (7).In other words, components PC1 and PC2 were adopted in equation (7). Anxiety score = 0.344 × PC1 score + 0.396 × PC2 score - 0.144 (7) The anxiety probability is calculated from the calculated anxiety score using equation (8). Anxiety probability p2 = -1 / (1 + exp(-1 × anxiety score)) (8) If the anxiety probability p2 was less than 0, it was determined to be "no anxiety," and if it was 0 or more, it was determined to be "anxious." Table 4 shows the estimation results. [Table 4]

[0043] As shown in Table 4, a high rate of correct answers was achieved.

[0044] Next, Tables 5 and 6 show the results of a comparison between estimating fatigue and anxiety from heart rate alone and estimating from heart rate and blood flow change information using specified principal components. [Table 5]

[0045] [Table 6]

[0046] As shown in Tables 5 and 6, the accuracy rate for both fatigue and anxiety was higher than when estimating using only heart rate. Therefore, it can be said that estimating fatigue and anxiety using blood flow change information, as in this method, is effective.

[0047] <Recommendations for lifestyle improvement methods> A process for presenting a method for recommending a lifestyle improvement technique using the estimated mental subjective assessment level and physical subjective assessment level will be described. Figure 12 shows an example of a visual display that allows users to understand the current state of their own mental and physical subjective assessment levels. The horizontal axis represents the anxiety score calculated using the above method, and the vertical axis represents the fatigue score. The quadrants to which the estimated anxiety and fatigue scores correspond are highlighted. This output allows users to understand their self-perceived mental and physical state and proactively address their concerns. Furthermore, as shown in Figure 12, when a user's condition falls within quadrants 2 to 4, lifestyle improvements are necessary. Therefore, a product suitable for improving the condition is recommended as one of the improvement methods. This allows users to identify products appropriate for their mental and physical state, which can be useful for lifestyle improvement. Recommended products include products made from processed and refined raw materials, as well as products containing ingredients suitable for improvement, such as soap with a certain scent, fabric softener with a certain scent, or beverages containing certain ingredients.

[0048] Figure 13 shows a presentation method in which the anxiety score is plotted on the horizontal axis and the fatigue score on the vertical axis, and the estimated anxiety and fatigue scores are plotted. By presenting the scores in this way, even if the scores are in the same quadrant as last time, the user can grasp minute changes such as whether they are improving, staying the same, or getting worse.

[0049] It is also possible to estimate an objective evaluation level related to the user's blood flow based on the calculated blood flow change information (objective evaluation level estimation process). The "objective evaluation level" is an index used when comparing and evaluating the tissue hemodynamic index estimated based on the calculated blood flow change information, or the results of analyzing the principal components with high contribution rates by performing principal component analysis on the blood flow change information, with those of other subjects. For example, it may be compared with the values ​​of subjects of the same age, gender, or body type. In this embodiment, the skin blood flow age (also referred to as "vascular age") is calculated from the blood flow change information as the objective evaluation level. The "skin blood flow age (vascular age)" is an index that numerically represents the condition of blood vessels. If the vascular age is higher than the actual age, the vascular condition is evaluated as poor, and if the vascular age is lower than the actual age, the vascular condition is evaluated as good. The horizontal axis of FIG. 14 represents the actual age, and the vertical axis represents the sum of PC1 and PC2 of the analysis results of the principal component analysis. As is clear from Figure 14, there is a negative correlation between the sum of PC1 and PC2 and actual age. From these, vascular age can be estimated using the following equation (9). Vascular age = (2.3477-(PC1+PC2)) / 0.9458 (9) However, the upper limit was set to 80 years and the lower limit to 20 years, and if the vascular age was estimated to be 15 years, it was output as 20 years. This is because in this embodiment, there was less data for subjects in their teens or younger and less data for subjects in their 90s or older than those in their 20s to 80s. In this embodiment, the vascular age was estimated using PC1 and PC2 from the analysis results of principal component analysis, but since the vascular age is also correlated with tissue hemodynamic indices and actual age, it can also be estimated using tissue hemodynamic indices. Figure 15 shows a graph with the anxiety score shown in Figure 12 on the horizontal axis and the fatigue score on the vertical axis, and also outputs the position, blood pressure level, and skin blood flow age of the tissue hemodynamic index (BOT in Figure 15) compared with subjects of the same age as objective evaluation levels. Here, the state of blood vessels can be classified into functional changes due to short-term lifestyle influences (referred to as "short-term functional changes") and functional changes due to long-term lifestyle influences (referred to as "long-term functional changes"). "Short-term functional changes" are conditions caused by short-term lifestyle changes, and may be improved or maintained by improving or maintaining the lifestyle over a short period of time. On the other hand, "long-term functional changes" encompass short-term functional changes. For example, if a short-term disruption of lifestyle habits causes short-term functional changes with a tendency toward deterioration, and if this condition continues, there is a high possibility that long-term functional changes with a tendency toward deterioration will occur. Furthermore, for example, if a state in which long-term functional changes with a tendency toward deterioration occurs is caused, there is a high possibility that long-term functional changes with a tendency toward improvement will occur after a state of short-term functional changes with a tendency toward improvement. Therefore, since long-term functional changes change (worsening or improving) over a period of time, changes can be confirmed by continuously measuring blood flow change information and observing each evaluation level. Here, "short-term" refers to a period of a few days, specifically about 10 days. "Long-term" refers to a period of about one month or more. The short-term period is included in the long-term period. The physical and mental effects of vascular damage initially result in mental and physical fatigue that can be resolved in the short term due to irregular lifestyle habits, etc. If this condition continues, it becomes difficult to resolve in the short term, and a condition occurs in which improvement cannot be expected unless irregular lifestyle habits, etc. are resolved in the long term. In this way, the state of blood vessels can be divided into states where function has changed over a short period of time and states where function has changed over a long period of time, and by using the objective assessment level, mental subjective assessment level, and physical subjective level, it is possible to evaluate the state of blood vessels in the short and long term. A method for evaluating the state of a user's blood vessels using this will be described.

[0050] The evaluation process for evaluating the state of blood vessels based on the mental subjective evaluation level, the physical subjective evaluation level, and the objective evaluation level will be described with reference to FIG. This method captures images of the body surface once a day for one week, and estimates the mental subjective assessment level, physical subjective assessment level, and objective assessment level. In this embodiment, it is determined whether the number of days estimated to have anxiety at the mental subjective assessment level and fatigue at the physical subjective assessment level is a predetermined number or more (e.g., five days). Note that the determination here does not necessarily require the number of days estimated to have anxiety or fatigue for both fatigue and anxiety to be a predetermined number or more; it is sufficient if the number of days estimated to have fatigue or anxiety is a predetermined number or more. If the number of days estimated to have fatigue and anxiety is less than five, it is determined that there is no problem with vascular function. In this case, the user may be advised to continue their current lifestyle. If the number of days estimated to have fatigue and anxiety is five or more, the vascular age, which is one of the objective assessment levels, is further determined. Here, the objective assessment level is estimated every day for one week, and it is determined whether the average estimated vascular age is a predetermined number of years (e.g., 10 years) higher than the actual age. If the patient is 10 years or older, it is judged to be a long-term change in vascular function that is on a downward trend. "Long-term change in vascular function that is on a downward trend" is a condition in which vascular function is expected to have declined over a long period of time, and as vascular function cannot be expected to improve without lifestyle improvements, lifestyle improvements are suggested. If the patient is not 10 years or older, it is judged to be a short-term change in vascular function that is on a downward trend. "Short-term change in vascular function that is on a downward trend" is a condition in which vascular function is expected to have declined over a short period of time, and as such, vascular function can be expected to improve in a relatively short period of time, such as by relaxing and resting. As improvement measures, care products are suggested based on the anxiety and fatigue scores, and suggestions are made for, for example, reducing fatigue with bath salts or using aromatic oils for relaxation. Here, if the evaluation is based only on the mental subjective evaluation level and the physical subjective evaluation level, it is difficult to determine whether the fatigue or anxiety is due to long-term damage to the blood vessels. Also, if the evaluation is based only on the objective evaluation level, it is difficult to determine whether the blood vessels are damaged by short-term fatigue or anxiety. In this way, by using the mental subjective evaluation level, the physical subjective evaluation level, and the objective evaluation level, it is possible to determine whether the change in blood vessel function is caused by short-term factors or long-term factors, and it is possible to propose appropriate improvement measures. In the evaluation process of FIG. 16, the current state is evaluated using the mental subjective evaluation level, the physical subjective evaluation level, and the objective evaluation level, making it possible to present an appropriate improvement plan. The estimation results are preferably stored in a data server (not shown) provided in the estimation system 200 using the present method (described later) or in an information processing terminal (not shown) owned by the user, and the vascular condition shown in FIG. 16 is evaluated using the stored estimation results. The user simply images their body surface every day, and the estimation system 200 determines the measurement period, estimates the mental subjective assessment level, and, based on the estimation results, estimates the physical subjective assessment level and the objective assessment level, and outputs the estimation results. This makes it possible to evaluate short-term and long-term changes in vascular function without imposing a workload on the user. Furthermore, the output content may be such that only information at the time of measurement, such as heart rate and blood pressure, is output daily, and the quadrants corresponding to the vascular age, anxiety score, and fatigue score are also output every predetermined period (e.g., five days). The user may also be able to specify the output items. Since the information desired to be confirmed may vary depending on the user's condition and user preferences, it is preferable to easily accommodate these changes.

[0051] <Estimation System> The estimation system 200 will be described with reference to FIG. The estimation system 200 in this embodiment is composed of an image acquisition unit 210, a blood flow change calculation unit 220, a periodic blood flow calculation unit 230, and a subjective assessment level estimation unit 240. It also includes an information processing terminal (not shown) capable of executing various processes, and the information processing terminal is equipped with the image acquisition unit 210, the blood flow change calculation unit 220, the periodic blood flow calculation unit 230, and the subjective assessment level estimation unit 240. The information processing terminal is equipped with input devices such as a keyboard and a pointing device, a processing unit, a memory unit, etc. It is preferable that the information processing terminal is equipped with a display device, but it may also be provided externally to the information processing terminal and connected via a network. The information processing terminal may also be equipped with a built-in or external camera (visible light camera).

[0052] The image acquisition unit 210 is a means for acquiring time-series images of a predetermined area of ​​the user's body surface, and the source of the time-series images does not matter, such as acquisition from a predetermined medium, acquisition via a network, acquisition from an imaging device, etc. The image acquisition unit 210 also acquires time-series images captured by a digital camera or a visible light camera provided on a mobile terminal. The blood flow change calculation unit 220 is a means for calculating a value correlating with the change in blood flow over time based on the acquired time-series images. In this embodiment, the hemoglobin component is calculated as the value correlating with the change in blood flow over time. The periodic blood flow rate calculation unit 230 is a means for calculating blood flow change information, which is a time-dependent change in blood flow rate in a blood vessel for at least one pulse cycle, based on a change in a numerical value correlated with the calculated blood flow change. The subjective assessment level estimating section 240 is means for estimating the user's mental subjective assessment level and the user's physical subjective assessment level based on the calculated blood flow change information. The subjective assessment level estimating section 240 is means for estimating the mental subjective assessment level and the physical subjective assessment level. The processing performed by the image acquisition unit 210, blood flow change calculation unit 220, periodic blood flow calculation unit 230, and subjective assessment level estimation unit 240 is the same as that described above in the method for estimating the mental subjective assessment level and the physical subjective assessment level.

[0053] <Modification> In this embodiment, the output mode is as shown in FIG. 15, but is not limited to this. For example, the method may include a step of displaying a character or avatar representing the user on a display unit from the acquired time-series images (display step), and the display mode of the character or avatar representing the user may be based on the estimated user's mental subjective assessment level, physical subjective assessment level, and objective assessment level. For example, in the processing flow shown in Figure 16, the display mode may be such that the character's complexion looks worse when a "long-term vascular functional change" is determined than when a "short-term vascular functional change" is determined, and as the condition improves, the character's physical condition improves and becomes more lively. By displaying in this manner, the user can easily grasp the condition of their own blood vessels, and as the condition of the blood vessels improves, the character representing the user's physical condition changes to show a more energetic state, which can motivate the user to continue working to improve their lifestyle habits.

[0054] In this embodiment, as shown in Fig. 16, as a result of one week of measurement, the mental subjective assessment level and the physical subjective assessment level are used to determine whether or not there are a predetermined number of days (e.g., five days) or more on which anxiety at the mental subjective assessment level and fatigue at the physical subjective assessment level are estimated. However, this is not limited to this. For example, it may be determined whether or not the total number of days on which at least one of fatigue and anxiety is estimated is a predetermined number or more. When proposing a lifestyle improvement method, the mental subjective assessment level, the physical subjective assessment level, and the objective assessment level may be used to make the determination. [Explanation of symbols]

[0055] 200 Estimation System 210 Image acquisition unit 220 Blood flow change calculation unit 230 Periodic blood flow calculation section 240 Subjective evaluation level estimation unit

Claims

1. 1. A method for estimating a mental subjective assessment level and a physical subjective assessment level of a user based on an image of a body surface of the user captured by an imaging device, the method comprising: an image acquisition step of acquiring time-series images of a predetermined area of ​​a user's body surface; a blood flow change calculation step of calculating a value correlated with a change in blood flow over time based on the time-series images; a periodic blood flow rate calculation step of calculating blood flow rate change information, which is a time-dependent change in blood flow rate in the blood vessel for at least one pulse period, based on the change in the value correlated with the time-dependent change in the calculated blood flow rate; a subjective evaluation level estimating step of estimating the user's mental subjective evaluation level and the user's physical subjective evaluation level based on the calculated blood flow change information; An estimation method, including:

2. 2. The estimation method according to claim 1, wherein the periodic blood flow rate calculation step further includes an averaging step of calculating the blood flow change information for a plurality of periods and averaging the blood flow change information that satisfies a predetermined condition.

3. The method further includes a tissue hemodynamic index calculation step of calculating a tissue hemodynamic index indicating a blood circulation state based on the calculated blood flow change information, 3. The estimation method according to claim 1, wherein the subjective assessment level estimation step estimates the user's mental subjective assessment level and the user's physical subjective assessment level based on the tissue hemodynamic index.

4. The method further includes an analysis step of performing a principal component analysis on the calculated blood flow change information and analyzing principal components whose contribution ratio is equal to or greater than a predetermined value, 3. The estimation method according to claim 1, wherein the subjective assessment level estimation step estimates the user's mental subjective assessment level and the user's physical subjective assessment level based on the analysis results.

5. The method further includes an objective evaluation level estimating step of estimating an objective evaluation level related to the user's blood flow based on the calculated blood flow change information, further comprising an evaluation step of evaluating the state of the user's blood vessels based on the estimated objective evaluation level, the user's mental subjective evaluation level, and the user's physical subjective evaluation level; The estimation method according to claim 1 or 2, characterized in that the evaluation step evaluates whether the user's blood vessels are in a short-term vascular functional change state, a long-term vascular functional change state that includes the short-term vascular functional change state, or a vascular state other than that.

6. The method further includes a presentation step of presenting a recommendation method for a product or a lifestyle improvement method that affects the blood flow change information, 3. The estimation method according to claim 1, wherein the presenting step presents the product or the lifestyle improvement method based on the estimated mental subjective evaluation level and the estimated physical subjective evaluation level of the user.

7. The method further includes an objective evaluation level estimating step of estimating an objective evaluation level related to the user's blood flow based on the calculated blood flow change information, 7. The estimation method according to claim 6, wherein the presenting step presents the product or the lifestyle improvement method based on the estimated mental subjective evaluation level of the user, the estimated physical subjective evaluation level of the user, and the estimated objective evaluation level.

8. a display step of displaying a character representing the user on a display means; The estimation method according to claim 7, wherein the display step displays a display mode of the character based on the estimated mental subjective evaluation level of the user, the estimated physical subjective evaluation level of the user, and the estimated objective evaluation level.

9. An estimation system that estimates a mental subjective evaluation level and a physical subjective evaluation level of a user based on an image of a body surface of the user captured by an imaging device using a control device, the estimation system comprising: image acquisition means for acquiring time-series images of a predetermined area of ​​the user's body surface; a blood flow change calculation means for calculating a value correlating with a change in blood flow over time based on the time-series images; a periodic blood flow rate calculation means for calculating blood flow rate change information, which is a change in blood flow rate over time in the blood vessel for at least one pulse period, based on the change in the value correlated with the calculated change in blood flow over time; a subjective assessment level estimating means for estimating the user's mental subjective assessment level and the user's physical subjective assessment level based on the calculated blood flow change information; An estimation system comprising:

Images