Biometric information acquisition device and biological information acquisition program

Abstract

The output signals for the R, G, and B channels in a moving image of a living body's face captured by an imaging device are all different. This difference in output signals can sometimes reduce the accuracy of pulse wave signal detection. [Solution] The biological information acquisition device includes an imaging unit that images reflected light reflected by a living body, including first wavelength light of a first wavelength and second wavelength light of a second wavelength different from the first wavelength, and outputs a first output value related to the first wavelength light and a second output value related to the second wavelength light; a data processing unit that performs data correction on the first output value to bring it closer to the median value of the output resolution of the imaging unit; and a calculation unit that calculates biological information based on the first output value and the second output value.

Description

[Technical Field]

[0001] This disclosure relates to a biological information acquisition device and a biological information acquisition program. [Background technology]

[0002] Pulse wave measurement devices that acquire biological information such as pulse waves are known. A pulse wave measurement device is an example of a biological information acquisition device. The pulse wave measurement device described in Patent Document 1 comprises an imaging device, a display device, and an input device. The imaging device has three channels: R (Red), G (Green), and B (Blue). The pulse wave measurement device measures the pulse wave signal of a living organism using a moving image of the facial region of the living organism captured by the imaging device. [Prior art documents] [Patent Documents]

[0003] [Patent Document 1] Japanese Patent Publication No. 2021-183079 [Overview of the project] [Problems that the invention aims to solve]

[0004] The output signals for the R, G, and B channels in a moving image of a living body's face captured by an imaging device are all different. This difference in output signals can sometimes reduce the accuracy of pulse wave signal detection. [Means for solving the problem]

[0005] The biological information acquisition device of this disclosure includes: an imaging unit that images reflected light reflected by a living body, including first wavelength light of a first wavelength and second wavelength light of a second wavelength different from the first wavelength, and outputs a first output value related to the first wavelength light and a second output value related to the second wavelength light; a data processing unit that performs data correction on the first output value to bring it closer to the median value of the output resolution of the imaging unit; and a calculation unit that calculates biological information based on the first output value and the second output value.

[0006] The biological information acquisition device of this disclosure includes a color filter that allows reflected light reflected by a living organism, including first wavelength light of a first wavelength and second wavelength light of a second wavelength different from the first wavelength, to pass through; an imaging unit that images the reflected light that has passed through the color filter and outputs a first output value related to the first wavelength light and a second output value related to the second wavelength light; and a calculation unit that calculates biological information based on the first output value and the second output value, wherein the color filter has a light transmittance that brings the first output value closer to the median value of the output resolution of the imaging unit.

[0007] The biological information acquisition program of this disclosure causes a computer connected to an imaging unit, which includes an imaging unit that captures reflected light reflected by a living organism, including first wavelength light of a first wavelength and second wavelength light of a second wavelength different from the first wavelength, and outputs a first output value related to the first wavelength light and a second output value related to the second wavelength light, to calculate biological information based on the first output value and the second output value, which have been data-corrected to approach the median output resolution of the imaging unit. [Brief explanation of the drawing]

[0008] [Figure 1] A diagram showing the schematic configuration of the measuring device. [Figure 2] A diagram showing the schematic configuration of the imaging unit. [Figure 3] A diagram showing the block configuration of the measuring device. [Figure 4] A diagram showing an example of signal values. [Figure 5] A diagram showing an example of signal values. [Figure 6] A diagram showing an example of grayscale values. [Figure 7] A diagram showing an example of grayscale values. [Figure 8] A diagram showing an example of signal values. [Figure 9] A diagram showing an example of signal values. [Figure 10] A diagram showing an example of signal values. [Figure 11] A diagram showing an example of a detection area. [Figure 12]Figure showing an example of a gradation detection value. [Figure 13] Figure showing an example of an analysis procedure for detecting a pulse wave signal. [Figure 14] Figure showing the analysis result of a noise removal signal. [Figure 15] Figure showing an example of a control flow executed by a measuring device.

Embodiments for Carrying Out the Invention

[0009] FIG. 1 shows a schematic configuration of a measuring device 10. The measuring device 10 corresponds to an example of a biological information acquisition device. The measuring device 10 detects a pulse wave signal of a measurer using moving image data. The pulse wave signal is a signal indicating the pulse wave of the measurer and is an example of biological information. The measurer corresponds to an example of a living body. The measuring device 10 calculates biological information such as pulse rate, pulse rate variation, oxygen saturation concentration, blood pressure, etc. based on the pulse wave signal. The measuring device 10 may perform an evaluation such as sleep apnea syndrome based on the biological information. The measuring device 10 displays biological information including the pulse wave signal.

[0010] The measuring device 10 is composed of an information processing device. The measuring device 10 shown in FIG. 1 shows a smartphone, but is not limited thereto. The measuring device 10 may be a device having a function of capturing a moving image or a device connectable to a device that captures a moving image. The measuring device 10 is composed of a desktop personal computer, a notebook personal computer, a tablet terminal, etc. The measuring device 10 includes an imaging unit 20, a display unit 30, and a control unit 40.

[0011] The imaging unit 20 captures the reflected light L reflected by the measurer. The reflected light L includes external light. The imaging unit 20 generates moving image data including the face of the measurer by capturing the reflected light L. The moving image data is composed of a plurality of image data. The image data is composed of a plurality of signal values. The image data is data for causing the display unit 30 to display a captured image 100. The captured image 100 is a still image. The imaging unit 20 captures images at a predetermined frame rate and generates moving image data.

[0012] The imaging unit 20 shown in FIG. 1 is a smartphone camera built into the measuring device 10. The imaging unit 20 may also be an external camera externally attached to the measuring device 10. The external camera is a near-infrared camera, a web camera, or the like. The imaging unit 20 may include a lens unit, an optical filter, etc. externally attached to the built-in smartphone camera.

[0013] The display unit 30 displays various information such as the captured image 100. The display unit 30 displays various biometric information including a pulse wave signal. The display unit 30 may display comments or the like based on the biometric information. The display unit 30 is composed of a liquid crystal panel, an organic EL (electro-luminescence) panel, or the like.

[0014] The display unit 30 has a touch input function. The display unit 30 functions as an input unit. The display unit 30 receives various input operations by the measurer. The display unit 30 generates various input signals according to the input operations. The display unit 30 shown in FIG. 1 has a touch input function, but is not limited thereto. An externally attached mouse, keyboard, touch panel, etc. may be used as the input device of the measuring device 10.

[0015] The control unit 40 controls various units such as the imaging unit 20 and the display unit 30. The control unit 40 controls various units and causes the measuring device 10 to measure biometric information including a pulse wave signal. The control unit 40 may control various units and cause the measuring device 10 to execute operations other than the measurement of biometric information.

[0016] The operator operates the measuring device 10 at a position opposite the imaging unit 20 of the measuring device 10. The operator operates the measuring device 10 when they want the measuring device 10 to detect biological information. The operator may also operate the measuring device 10 when performing tasks such as document creation. The measuring device 10 detects the operator's biological information in the background while the operator is performing tasks such as document creation. By detecting biological information in the background, the measuring device 10 can detect the operator's biological information in a normal activity state.

[0017] Figure 2 shows a schematic configuration of the imaging unit 20. The imaging unit 20 comprises an optical element 21, a substrate 22, an imaging sensor 23, a color filter 24, and an image processing circuit group 25.

[0018] The optical element 21 forms an image of reflected light L on the image sensor 23. The optical element 21 is composed of one or more lenses, mirrors, diffraction gratings, etc. The configuration of the optical element 21 is not limited as long as it is configured to form an image of reflected light L on the image sensor 23.

[0019] The substrate 22 supports the imaging sensor 23 and the image processing circuit group 25. The substrate 22 may also support a support frame (not shown), which supports the optical element 21. The substrate 22 supports the optical element 21 via the support frame.

[0020] The image sensor 23 converts the brightness of the reflected light L, which is imaged by the optical element 21, into an electrical signal. The image sensor 23 is composed of a CCD (Charge Coupled Device), CMOS (Complementary Metal Oxide Semiconductor), etc. The image sensor 23 has multiple image elements. The image sensor 23 converts the brightness of the reflected light L into an electrical signal for each image element.

[0021] The color filter 24 selectively transmits light of a predetermined wavelength. For example, the color filter 24 selectively transmits red light RL, green light GL, and blue light BL. Red light RL corresponds to an example of first wavelength light. Green light GL corresponds to an example of second wavelength light. Blue light BL corresponds to an example of third wavelength light. Red light RL, green light GL, and blue light BL are light with different wavelengths. The red wavelength of red light RL is 600 nm to 800 nm. The red wavelength corresponds to an example of first wavelength light. The green wavelength of green light GL is 520 nm to 550 nm. The green wavelength corresponds to an example of second wavelength light. The blue wavelength of blue light BL is 430 nm to 490 nm. The blue wavelength corresponds to an example of third wavelength light.

[0022] The color filter 24 has a first portion that transmits red light RL, a second portion that transmits green light GL, and a third portion that transmits blue light BL. The first, second, and third portions are each positioned opposite the image element. The color filter 24 separates reflected light L into red light RL, green light GL, and blue light BL. The color filter 24 is, for example, a Bayer filter. The color filter 24 may also include a portion that transmits near-infrared light, etc.

[0023] Multiple image elements in the imaging sensor 23 capture red light RL, green light GL, and blue light BL, respectively. The image element facing the first part converts red light RL into a red electrical signal. The image element facing the second part converts green light GL into a green electrical signal. The image element facing the third part converts blue light BL into a blue electrical signal. The red electrical signal, green electrical signal, and blue electrical signal are signals output for each pixel. The red electrical signal, green electrical signal, and blue electrical signal are analog signals. The imaging sensor 23 outputs each electrical signal to the image processing circuit group 25. The imaging sensor 23 corresponds to an example of an imaging unit.

[0024] The image processing circuit group 25 receives the red, green, and blue electrical signals output from the imaging sensor 23 and performs various processing such as adjustment. The image processing circuit group 25 converts each electrical signal into a digital signal using A / D conversion. A / D conversion is an abbreviation for analog-to-digital conversion. The image processing circuit group 25 performs various digital signal processing on the A / D converted digital signals and outputs them to the control unit 40.

[0025] Figure 3 shows the block configuration of the measuring device 10. The measuring device 10 comprises an imaging unit 20, a display unit 30, a control unit 40, and a storage unit 50. The measuring device 10 may also include a communication unit and the like (not shown). The storage unit 50 stores a biological analysis program PG and the like.

[0026] The imaging unit 20 generates gradation values ​​corresponding to each signal value based on the signal values ​​of each electrical signal, and outputs dynamic image data including the gradation values ​​to the control unit 40. The gradation values ​​are digital signals and include a red gradation value Gr related to red light RL, a green gradation value Gg related to green light GL, and a blue gradation value Gb related to blue light BL. The imaging unit 20 includes an image processing circuit group 25. The image processing circuit group 25 has an analog signal processing circuit 26 and a digital signal processing circuit 27.

[0027] The analog signal processing circuit 26 receives each electrical signal output from the image sensor 23 and adjusts the signal value, which is the signal intensity of each electrical signal. The analog signal processing circuit 26 receives the red signal value Sr, the green signal value Sg, and the blue signal value Sb as signal values. The analog signal processing circuit 26 performs adjustment processing on each signal value. By performing adjustment processing on each signal value, the measuring device 10 can improve the detection accuracy of the pulse wave signal. The adjustment processing corresponds to an example of data correction. As an example, the analog signal processing circuit 26 performs adjustment processing to adjust the signal amplification ratio for each signal value. The analog signal processing circuit 26 increases or decreases the signal value by adjusting the signal amplification ratio for each signal value. By performing adjustment processing, the analog signal processing circuit 26 brings each signal value closer to the output median value MV of the output resolution of the image sensor 23. The analog signal processing circuit 26 corresponds to an example of data processing.

[0028] The analog signal processing circuit 26 converts each adjusted signal value into a grayscale value. The analog signal processing circuit 26 converts the red signal value Sr, the green signal value Sg, and the blue signal value Sb into a red grayscale value Gr, a green grayscale value Gg, and a blue grayscale value Gb, respectively. The analog signal processing circuit 26 outputs the grayscale value, including the red grayscale value Gr, the green grayscale value Gg, and the blue grayscale value Gb, to the digital signal processing circuit 27.

[0029] One example of the adjustment process performed by the analog signal processing circuit 26 is a color temperature adjustment process using color temperature. In the color temperature adjustment process, the analog signal processing circuit 26 detects the color temperature of the image data based on the electrical signal. The imaging unit 20 acquires moving image data in a preparation step before measuring the pulse wave signal. The imaging unit 20 detects the color temperature of the image data contained in the moving image data. The imaging unit 20 determines the correction coefficients to be used in the adjustment process using the detected color temperature and the correction coefficient table. The correction coefficients correct the signal intensity of each electrical signal.

[0030] Figure 4 shows an example of signal values. Figure 4 shows the red signal value Sr, the green signal value Sg, and the blue signal value Sb. The red signal value Sr indicates the signal intensity of the electrical signal related to the red light RL. The red signal value Sr corresponds to an example of the first output value. The green signal value Sg indicates the signal intensity of the electrical signal related to the green light GL. The green signal value Sg corresponds to an example of the second output value. The blue signal value Sb indicates the signal intensity of the electrical signal related to the blue light BL. The blue signal value Sb corresponds to an example of the third output value.

[0031] Figure 4 shows the saturation value SV and the median output value MV of the imaging sensor 23. The saturation value SV is the value at which the signal value detected by the imaging sensor 23 saturates. The median output value MV corresponds to the median output resolution of the imaging sensor 23.

[0032] Figure 4 shows the first red signal value Sr1, the first green signal value Sg1, and the first blue signal value Sb1, which are the red signal value Sr, the green signal value Sg, and the blue signal value Sb, respectively, before the adjustment process is performed. The first red signal value Sr1, the first green signal value Sg1, and the first blue signal value Sb1 shown in Figure 4 are output based on the reflected light L reflected from the skin of the observer's face. On the skin of the face, due to the influence of hemoglobin in the blood, red light RL is easily reflected by the skin, while green light GL and blue light BL are easily absorbed by the skin. The first red signal value Sr1 is higher than the first green signal value Sg1 and the first blue signal value Sb1. The analog signal processing circuit 26 corrects the first red signal value Sr1, the first green signal value Sg1, and the first blue signal value Sb1 using correction coefficients determined using the color temperature and the correction coefficient table.

[0033] The correction coefficient table is a data table that associates color temperature with correction coefficients. The correction coefficient table is pre-stored in the storage unit 50. The correction coefficients include a red signal correction coefficient kr, a green signal correction coefficient kg, and a blue signal correction coefficient kb. The red signal correction coefficient kr increases, decreases, or maintains the red signal value Sr. The red signal correction coefficient kr corresponds to an example of a first correction value. The green signal correction coefficient kg increases, decreases, or maintains the green signal value Sg. The green signal correction coefficient kg corresponds to an example of a second correction value. The blue signal correction coefficient kb is a coefficient that increases, decreases, or maintains the blue signal value Sb. The blue signal correction coefficient kb corresponds to an example of a third correction value. The analog signal processing circuit 26 adjusts each signal value using, as an example, the following equations (1), (2), and (3). Sr² = kr × Sr¹ (1) Sg2 = kg × Sg1(2) Sb² = kb × Sb¹ (3) Here, the second red signal value Sr2, the second green signal value Sg2, and the second blue signal value Sb2 represent the adjusted red signal value Sr, the adjusted green signal value Sg, and the adjusted blue signal value Sb, respectively. When the correction factor is less than 1, the signal value decreases. When the correction factor is greater than 1, the signal value increases. When the correction factor is 1, the signal value does not change.

[0034] Figure 5 shows an example of signal values. Figure 5 shows the red signal value Sr, the green signal value Sg, and the blue signal value Sb. Figure 5 shows the second red signal value Sr2, the second green signal value Sg2, and the second blue signal value Sb2 after adjustment processing has been performed on the first red signal value Sr1, the first green signal value Sg1, and the first blue signal value Sb1.

[0035] As shown in Figure 5, the analog signal processing circuit 26 reduces the first red signal value Sr1 to the second red signal value Sr2 using a red signal correction coefficient kr. The analog signal processing circuit 26 brings the second red signal value Sr2 closer to the output median value MV by performing a color temperature adjustment process. By performing the color temperature adjustment process, the analog signal processing circuit 26 can suppress the influence of ambient light color temperature and other factors on the red signal value Sr.

[0036] The analog signal processing circuit 26 may reduce the first green signal value Sg1 to the second green signal value Sg2 using a green signal correction coefficient kg. The analog signal processing circuit 26 brings the second green signal value Sg2 closer to the output median value MV by performing a color temperature adjustment process. By performing the color temperature adjustment process, the analog signal processing circuit 26 can suppress the influence of ambient light color temperature, etc., on the green signal value Sg.

[0037] The analog signal processing circuit 26 may increase the first blue signal value Sb1 to the second blue signal value Sb2 using a blue signal correction coefficient kb. The analog signal processing circuit 26 brings the second blue signal value Sb2 closer to the output median value MV by performing a color temperature adjustment process. By performing the color temperature adjustment process, the analog signal processing circuit 26 can suppress the influence of ambient light color temperature, etc., on the blue signal value Sb.

[0038] The second red signal value Sr2, the second green signal value Sg2, and the second blue signal value Sb2 shown in Figure 5 are adjusted within the tolerance range TR. The tolerance range TR represents a predetermined signal intensity range centered on the output median value MV. The analog signal processing circuit 26 preferably adjusts the second red signal value Sr2, the second green signal value Sg2, and the second blue signal value Sb2 within the tolerance range TR by performing adjustment processing. By adjusting the second red signal value Sr2, the second green signal value Sg2, and the second blue signal value Sb2 within the tolerance range TR, the detection accuracy of the pulse wave signal is improved.

[0039] Figures 6 and 7 show examples of gradation values. Figures 6 and 7 show examples of red gradation value Gr, green gradation value Gg, and blue gradation value Gb. Figure 6 shows the gradation values ​​when each signal value shown in Figure 4 is A / D converted. Figure 6 shows the gradation values ​​when A / D converted to signal values ​​without adjustment processing. Figure 7 shows the gradation values ​​when each signal value shown in Figure 5 is A / D converted. Figure 7 shows the gradation values ​​when A / D converted to signal values ​​after adjustment processing.

[0040] Figure 6 shows the first red gradation value Gr1, the first green gradation value Gg1, and the first blue gradation value Gb1. The first red gradation value Gr1, the first green gradation value Gg1, and the first blue gradation value Gb1 are examples of red gradation value Gr, green gradation value Gg, and blue gradation value Gb, respectively. The first red gradation value Gr1, the first green gradation value Gg1, and the first blue gradation value Gb1 are the values ​​obtained by A / D conversion of the first red signal value Sr1, the first green signal value Sg1, and the first blue signal value Sb1, respectively. As shown in Figure 6, the first red gradation value Gr1 corresponding to the first red signal value Sr1 without adjustment processing is close to the upper limit of the gradation. If the first red gradation value Gr1 is close to the upper limit of the gradation, the detection accuracy of the pulse wave signal may decrease.

[0041] Figure 7 shows the second red gradation value Gr2, the second green gradation value Gg2, and the second blue gradation value Gb2. The second red gradation value Gr2, the second green gradation value Gg2, and the second blue gradation value Gb2 are examples of the red gradation value Gr, the green gradation value Gg, and the blue gradation value Gb, respectively. The second red gradation value Gr2, the second green gradation value Gg2, and the second blue gradation value Gb2 are the values ​​obtained when the second red signal value Sr2, the second green signal value Sg2, and the second blue signal value Sb2 are converted using A / D conversion, respectively. As shown in Figure 7, the second red gradation value Gr2 corresponding to the second red signal value Sr2 after adjustment processing is close to the median value of the gradation. When the second red gradation value Gr2 is close to the median value of the gradation, the decrease in the detection accuracy of the pulse wave signal is suppressed.

[0042] The adjustment process performed by the analog signal processing circuit 26 may also be a threshold adjustment process using a predetermined output threshold TH. The output threshold TH corresponds to an example of a threshold. The output threshold TH is stored in the storage unit 50 in advance. The analog signal processing circuit 26 receives each electrical signal of the image data acquired in the preparation step as input. The analog signal processing circuit 26 compares each signal value with the output threshold TH.

[0043] Figure 8 shows an example of signal values. Figure 8 shows the red signal value Sr, the green signal value Sg, and the blue signal value Sb. Figure 8 shows the first red signal value Sr1, the first green signal value Sg1, and the first blue signal value Sb1 before threshold adjustment processing is performed. Figure 8 shows the saturation value SV and the output median value MV of the imaging sensor 23. Figure 8 shows an example of the first output threshold TH1 and the second output threshold TH2. The first output threshold TH1 and the second output threshold TH2 are examples of output thresholds TH.

[0044] The first output threshold TH1 indicates the upper limit. In the region where the output value exceeds the first output threshold TH, the variation in the grayscale value corresponding to the signal value decreases. In the region where the signal value exceeds the first output threshold TH1, the detection accuracy of the pulse wave signal decreases due to the decrease in the variation in the grayscale value.

[0045] The second output threshold TH2 indicates the lower limit. In the region where the signal value is smaller than the second output threshold TH, the variation in the grayscale value corresponding to the signal value decreases. In the region where the signal value is smaller than the second output threshold TH2, the detection accuracy of the pulse wave signal decreases due to the decrease in the variation in grayscale value.

[0046] The analog signal processing circuit 26 compares the output threshold TH with the first red signal value Sr1, the first green signal value Sg1, and the first blue signal value Sb1 shown in Figure 8. The analog signal processing circuit 26 determines that the first red signal value Sr1 is higher than the first output threshold TH1. The analog signal processing circuit 26 performs signal processing to reduce the first red signal value Sr1. By performing signal processing to reduce the first red signal value Sr1, the analog signal processing circuit 26 brings the adjusted first red signal value Sr1 closer to the output median value MV.

[0047] As shown in Figure 8, the first green signal value Sg1 and the first blue signal value Sb1 are higher than the second output threshold TH2. The analog signal processing circuit 26 does not perform signal processing to increase the first green signal value Sg1 and the first blue signal value Sb1. When any of the first red signal value Sr1, the first green signal value Sg1, and the first blue signal value Sb1 are lower than the second output threshold TH2, the analog signal processing circuit 26 performs signal processing to increase the signal value lower than the second output threshold TH2.

[0048] Figure 9 shows an example of signal values. Figure 9 shows the red signal value Sr, the green signal value Sg, and the blue signal value Sb. Figure 9 shows the second red signal value Sr2, the second green signal value Sg2, and the second blue signal value Sb2 after threshold adjustment processing has been performed on the first red signal value Sr1, the first green signal value Sg1, and the first blue signal value Sb1 shown in Figure 8.

[0049] The second red signal value Sr2 shown in Figure 9 is smaller than the first red signal value Sr1 shown in Figure 8. The analog signal processing circuit 26 performs threshold adjustment on the first red signal value Sr1, reducing it. The analog signal processing circuit 26 performs threshold adjustment on the first red signal value Sr1, bringing it closer to the output median value MV. The first red signal value Sr1 is adjusted to the second red signal value Sr2. By performing threshold adjustment on the first red signal value Sr1, which brings it closer to the output median value MV, the measuring device 10 can improve the detection accuracy of the red light RL.

[0050] The adjustment process performed by the analog signal processing circuit 26 may also be a calculation adjustment process using a calculated adjustment amount generated using the image data acquired in the preparation step. The image data corresponds to an example of imaging data. The analog signal processing circuit 26 receives each electrical signal of the image data acquired in the preparation step as input. As an example, the analog signal processing circuit 26 acquires the output median value MV of the output resolution of the imaging sensor 23. The analog signal processing circuit 26 may also acquire the average signal intensity value, which is the average value of each signal value.

[0051] The analog signal processing circuit 26 calculates the adjustment amount using the output median value MV. The analog signal processing circuit 26 calculates the difference value obtained by subtracting the red signal value Sr by the output median value MV as the red adjustment amount Cr. The red adjustment amount Cr corresponds to an example of the first adjustment amount. The analog signal processing circuit 26 calculates the difference value obtained by subtracting the green signal value Sg by the output median value MV as the green adjustment amount Cg. The green adjustment amount Cg corresponds to an example of the second adjustment amount. The analog signal processing circuit 26 calculates the difference value obtained by subtracting the blue signal value Sb by the output median value MV as the blue adjustment amount Cb. As an example, the analog signal processing circuit 26 adjusts the first red signal value Sr1, the first green signal value Sg1, and the first blue signal value Sb1 to the second red signal value Sr2, the second green signal value Sg2, and the second blue signal value Sb2 using the following equations (4), (5), and (6). Sr2 = Sr1 - Cr (4) Sg2 = Sg1 - Cg (5) Sb² = Sb₁ - Cb (6) Here, when the calculated adjustment amount is positive, the signal value decreases. When the calculated adjustment amount is negative, the signal value increases. When the calculated adjustment amount is 0, the signal value does not change.

[0052] The calculated adjustment amount may be calculated using the average signal intensity. The average signal intensity is used in place of the output median MV. The calculated adjustment amount may also be generated by calculating the ratio between the signal value and the output median MV.

[0053] The adjustment process performed by the analog signal processing circuit 26 may also be a comparison adjustment process that compares each signal value of the image data acquired in the preparation step and corrects each signal value based on the comparison result. The analog signal processing circuit 26 receives each electrical signal of the image data acquired in the preparation step as input. The analog signal processing circuit 26 compares the red signal value Sr, the green signal value Sg, and the blue signal value Sb.

[0054] As an example, the analog signal processing circuit 26 compares the first green signal value Sg1 with the first red signal value Sr1 and the first blue signal value Sb1. Green light GL is more easily detected for pulse wave signals than red light RL and blue light BL. The analog signal processing circuit 26 calculates the ratio of the first red signal value Sr1 and the first blue signal value Sb1 to the first green signal value Sg1 as a reference. The analog signal processing circuit 26 calculates the first signal intensity ratio Sr / Sg and the second signal intensity ratio Sb / Sg. The first signal intensity ratio Sr / Sg is the ratio of the first red signal value Sr1 to the first green signal value Sg1. The second signal intensity ratio Sb / Sg is the ratio of the first blue signal value Sb1 to the first green signal value Sg1.

[0055] The analog signal processing circuit 26 compares the first signal intensity ratio Sr / Sg and the second signal intensity ratio Sb / Sg with a standard ratio value. The standard ratio value is a predetermined value and is stored in the memory unit 50. The standard ratio value corresponds to an example of a ratio value. The standard ratio value includes a first standard ratio value which is the upper limit and a second standard ratio value which is the lower limit.

[0056] Figure 10 shows an example of signal values. Figure 10 shows the red signal value Sr, the green signal value Sg, and the blue signal value Sb. Figure 10 shows the first red signal value Sr1, the first green signal value Sg1, and the first blue signal value Sb1 before performing the comparison adjustment process. Figure 10 shows the saturation value SV and the output median value MV of the imaging sensor 23.

[0057] As shown in Figure 10, the first red signal value Sr1 is greater than the first green signal value Sg1. The analog signal processing circuit 26 compares the first signal intensity ratio Sr / Sg with the first standard ratio value. If the analog signal processing circuit 26 determines that the first signal intensity ratio Sr / Sg is greater than the first standard ratio value, it performs signal processing on the first red signal value Sr1. The analog signal processing circuit 26 performs signal processing to reduce the first red signal value Sr1. The analog signal processing circuit 26 adjusts the first red signal value Sr1 to a second red signal value Sr2 that is close to the output median value MV. If the analog signal processing circuit 26 determines that the first signal intensity ratio Sr / Sg is less than the first standard ratio value, it does not perform signal processing on the first red signal value Sr1.

[0058] As shown in Figure 10, the first blue signal value Sb1 is smaller than the first green signal value Sg1. The analog signal processing circuit 26 compares the second signal intensity ratio Sb / Sg with the second standard ratio value. If the analog signal processing circuit 26 determines that the second signal intensity ratio Sb / Sg is smaller than the second standard ratio value, it performs signal processing on the first blue signal value Sb1. The analog signal processing circuit 26 performs signal processing to increase the first blue signal value Sb1. The analog signal processing circuit 26 adjusts the first blue signal value Sb1 to a second blue signal value Sb2 that is close to the output median value MV. If the analog signal processing circuit 26 determines that the second signal intensity ratio Sb / Sg is larger than the second standard ratio value, it does not perform signal processing on the first blue signal value Sb1.

[0059] The digital signal processing circuit 27 shown in Figure 3 receives the gradation values ​​output from the analog signal processing circuit 26. The gradation values ​​include the red gradation value Gr, the green gradation value Gg, and the blue gradation value Gb. The digital signal processing circuit 27 performs corrections on the gradation values, such as pixel interpolation, gamma correction, color correction, edge enhancement, and noise reduction. The digital signal processing circuit 27 outputs motion image data including the corrected gradation values ​​to the control unit 40.

[0060] The imaging unit 20 may output the analog signals, namely the red signal value Sr, the green signal value Sg, and the blue signal value Sb, to the control unit 40 in the moving image data. The control unit 40 acquires the red signal value Sr, the green signal value Sg, and the blue signal value Sb.

[0061] The display unit 30 displays various images based on the control of the control unit 40. The display unit 30 receives display data from the control unit 40 and displays various images based on the display data. The display unit 30 may also display moving images captured by the imaging unit 20 based on moving image data. The display unit 30 may also display captured images 100 based on image data included in the moving image data.

[0062] The display unit 30 transmits an input signal to the control unit 40. By transmitting the input signal to the control unit 40, the display unit 30 causes the control unit 40 to perform various controls. For example, the display unit 30 transmits a display instruction signal to the control unit 40 as an input signal to display biological information. Based on the display instruction signal, the control unit 40 generates biological information display data to display the biological information on the display unit 30. The control unit 40 transmits the biological information display data to the display unit 30. Based on the biological information display data, the display unit 30 displays a screen containing the biological information.

[0063] The control unit 40 is a control controller that controls the operation of various units. The control unit 40 is, for example, a processor having a CPU (Central Processing Unit). The control unit 40 is composed of one or more processors. The control unit 40 is connected to the imaging unit 20, the display unit 30, etc., in a communicative manner. By executing the biological analysis program PG, the control unit 40 functions as a region setting unit 41, an analysis unit 43, and a display control unit 45. The control unit 40 may also function as a signal processing unit 47 by executing the biological analysis program PG. The control unit 40 may also function as a functional unit other than the region setting unit 41, the analysis unit 43, the display control unit 45, and the signal processing unit 47 by executing the biological analysis program PG. The control unit 40 corresponds to an example of a computer.

[0064] The region setting unit 41 acquires moving image data transmitted from the imaging unit 20. The region setting unit 41 acquires multiple image data contained in the moving image data. The region setting unit 41 performs face recognition processing on each image data. Face recognition processing is a process that detects feature points contained in the image data and extracts the face image region 121 by matching the feature points with a pre-registered face image database. Feature points contained in the image data include, for example, the positions and contours of the eyes, nose, and mouth. The face image database is pre-stored in the storage unit 50. If the measuring device 10 is connected to a server via a network, the face image database may be pre-stored on the server. The measuring device 10 acquires the face image database from the server. The face image region 121 is the region where the face of the person being measured is displayed. The region setting unit 41 identifies the face image region 121 by performing face recognition processing.

[0065] The region setting unit 41 identifies the face image region 121 and then determines the detection region 201. For example, the region setting unit 41 determines the detection region 201 based on the setting region information SI described later. The region setting unit 41 may also determine the detection region 201 using moving image data output from the imaging unit 20.

[0066] Figure 11 shows an example of the detection region 201. The detection region 201 is determined by the region setting unit 41 by excluding the non-detection region 131 from the face image region 121. The region setting unit 41 determines a portion of the face image region 121 as the detection region 201. Figure 11 shows the face image region 121, the detection region 201, and the non-detection region 131 superimposed on the captured image 100. The captured image 100 is an example of an image included in a moving image captured by the imaging unit 20.

[0067] The detection region 201 is determined by excluding the non-detection region 131 from the face image region 121. The non-detection region 131 includes regions that are susceptible to noise such as body movement, regions where pulse wave signals are difficult to detect, etc. The measuring device 10 detects the pulse wave signal using the detection region 201 from which the non-detection region 131 has been excluded. By detecting the pulse wave signal using the detection region 201, the measuring device 10 can improve the detection accuracy of the pulse wave signal.

[0068] The analysis unit 43 shown in Figure 3 calculates a pulse wave signal using the red tone value Gr, the green tone value Gg, and the blue tone value Gb. The red tone value Gr, the green tone value Gg, and the blue tone value Gb are generated by A / D conversion of the red signal value Sr, the green signal value Sg, and the blue signal value Sb, respectively. The analysis unit 43 calculates a pulse wave signal based on the red signal value Sr, the green signal value Sg, and the blue signal value Sb. The analysis unit 43 calculates biological information based on the pulse wave signal. The analysis unit 43 acquires multiple image data contained in the moving image data from the imaging unit 20. The analysis unit 43 acquires the detection region 201 from the region setting unit 41. The analysis unit 43 detects each tone value within the detection region 201 from the image data and detects the pulse wave signal of the examiner M based on each tone value. The analysis unit 43 identifies multiple pixels corresponding to the detection region 201. The analysis unit 43 detects the tone value of each of the identified multiple pixels. The analysis unit 43 generates a grayscale detection value using multiple grayscale values ​​within the detection area 201. The grayscale detection value is the average value of the grayscale values ​​of pixels within the detection area 201. The grayscale detection value is calculated for each image data within the moving image data. The analysis unit 43 detects the pulse wave signal of the measurer M using the grayscale detection value. The analysis unit 43 corresponds to an example of the calculation unit.

[0069] The analysis unit 43 detects the pulse wave signal using each grayscale detection value. As an example, the analysis unit 43 detects the pulse wave signal using at least one of the red grayscale detection value Dr, the green grayscale detection value Dg, and the blue grayscale detection value Db. The red grayscale detection value Dr is calculated using the red grayscale value Gr obtained by A / D conversion of the red signal value Sr output from the image element corresponding to the detection region 201. The green grayscale detection value Dg is calculated using the green grayscale value Gg obtained by A / D conversion of the green signal value Sg output from the image element corresponding to the detection region 201. The blue grayscale detection value Db is calculated using the blue grayscale value Gb obtained by A / D conversion of the blue signal value Sb output from the image element corresponding to the detection region 201. The pulse wave signal is detected based on the green grayscale detection value Dg. The pulse wave signal is detected based on the difference between the green grayscale detection value Dg and at least one of the red grayscale detection value Dr and the blue grayscale detection value Db.

[0070] Figure 12 shows an example of grayscale detection values. Figure 12 shows the red grayscale detection value Dr, the green grayscale detection value Dg, and the blue grayscale detection value Db. Figure 12 shows the time-dependent changes of the red grayscale detection value Dr, the green grayscale detection value Dg, and the blue grayscale detection value Db as waveform signals. Figure 12 shows the red grayscale detection value Dr, the green grayscale detection value Dg, and the blue grayscale detection value Db in the body movement interval S1 and the red grayscale detection value Dr, the green grayscale detection value Dg, and the blue grayscale detection value Db in the resting interval S2. The body movement interval S1 is the interval in which facial movement and changes in expression occur. The resting interval S2 is the interval in which facial movement and changes in expression are smaller than a predetermined amount of change.

[0071] The green tone detection value Dg fluctuates due to body movement during the movement interval S1. During the movement interval S1, the pulse wave signal included in the green tone detection value Dg is difficult to detect due to fluctuating noise. During the rest interval S2, the influence of fluctuating noise due to body movement decreases, and the analysis unit 43 becomes able to detect the pulse wave signal using the green tone detection value Dg.

[0072] The red tone detection value Dr fluctuates in the motion interval S1 due to the effects of body movement. In the motion interval S1, the pulse wave signal included in the red tone detection value Dr is difficult to detect due to fluctuating noise. In the resting interval S2, the effect of fluctuating noise due to body movement decreases, but the signal-to-noise ratio of the red tone detection value Dr is small, making it difficult for the analysis unit 43 to detect the pulse wave signal.

[0073] The blue tone detection value Db fluctuates in the motion interval S1 due to the effects of body movement. In the motion interval S1, the pulse wave signal included in the blue tone detection value Db is difficult to detect due to fluctuating noise. In the resting interval S2, the effect of fluctuating noise due to body movement decreases, but the signal-to-noise ratio of the blue tone detection value Db is small, making it difficult for the analysis unit 43 to detect the pulse wave signal.

[0074] The analysis unit 43 detects the pulse wave signal using the red gradation detection value Dr, the green gradation detection value Dg, and the blue gradation detection value Db shown in Figure 12. As an example, the analysis unit 43 detects the pulse wave signal using the analysis procedure shown in Figure 13.

[0075] Figure 13 shows an example of the analysis procedure for detecting a pulse wave signal. Figure 13 shows an example of the analysis procedure as a flowchart. The analysis procedure shown in Figure 13 is performed by the analysis unit 43. The analysis procedure shown in Figure 13 detects the pulse wave signal using the red gradation detection value Dr, the green gradation detection value Dg, and the blue gradation detection value Db.

[0076] In step S101, the analysis unit 43 performs sampling of each grayscale detection value at predetermined time intervals. The time interval and sampling frequency are set as appropriate. Preferably, the time interval is a time that includes one or more pulse waves. For example, the time interval is 3 to 10 seconds. For example, the sampling frequency is 10 Hz to 50 Hz. The analysis unit 43 acquires sampling data by performing sampling. The sampling data includes the sampled red grayscale detection value Dr, green grayscale detection value Dg, and blue grayscale detection value Db.

[0077] After performing sampling, the analysis unit 43 normalizes the sampled data in step S103. The analysis unit 43 normalizes the multiple green tone detection values ​​Dg included in the sampled data.

[0078] The analysis unit 43 calculates the average value of multiple green tone detection values ​​Dg, which is the green mean Gmean, and the standard deviation of multiple green tone detection values ​​Dg, which is the green standard deviation Gstd. The analysis unit 43 normalizes each green tone detection value Dg using the following formula (7). Gnorm n =(Gn-Gmean) / Gstd (7) Here, n is any integer greater than or equal to 1. Gn is the nth green tone detection value Dg. Gnorm n This is the normalized value of the nth green tone detection value Dg.

[0079] The analysis unit 43 normalizes a plurality of red tone detection values Dr and a plurality of blue tone detection values Db included in the sampling data, similar to the green tone detection value Dg. The analysis unit 43 calculates a red average value Rmean, which is the average value of the plurality of red tone detection values Dr, and a red standard deviation value Rstd, which is the standard deviation value of the plurality of red tone detection values Dr. The analysis unit 43 calculates a blue average value Bmean, which is the average value of the plurality of blue tone detection values Db, and a blue standard deviation value Bstd, which is the standard deviation value of the plurality of blue tone detection values Db. The analysis unit 43 normalizes each red tone detection value Dr and each blue tone detection value Db using the following formulas (8) and (9). Rnorm n =(Rn - Rmean) / Rstd (8) Bnorm n =(Bn - Bmean) / Bstd (9) Here, n is an arbitrary integer greater than or equal to 1. Rn is the nth red tone detection value Dr. Rnorm n is the value obtained by normalizing the nth red tone detection value Dr. Bn is the nth blue tone detection value Db. Bnorm n is the value obtained by normalizing the nth blue tone detection value Db.

[0080] After normalizing the sampling data, the analysis unit 43 performs noise removal processing in step S105. The analysis unit 43 performs noise removal processing using the normalized green tone detection value Dg, the normalized red tone detection value Dr, and the blue tone detection value Db. The analysis unit 43 performs noise removal processing using the following formula (10) to generate a noise removal signal S. Sn = Gnorm n + αBnorm n + βRnorm n (10) Here, n is an arbitrary integer greater than or equal to 1. Sn is the nth noise removal signal S. α is the first coefficient, and β is the second coefficient.

[0081] For example, α and β are -0.5 and -0.5, respectively. When α and β are negative values, the analysis unit 43 detects the noise reduction signal S by subtracting the normalized red tone detection value Dr and the normalized blue tone detection value Db from the normalized green tone detection value Dg. At least one of α and β may be 0. When α=0 and β=-1, the analysis unit 43 detects the noise reduction signal S by calculating the difference between the green tone detection value Dg and the red tone detection value Dr. When α=-1 and β=0, the analysis unit 43 detects the noise reduction signal S by calculating the difference between the green tone detection value Dg and the blue tone detection value Db. α and β are set appropriately depending on the noise reduction status.

[0082] Figure 14 shows the analysis results of the denoised signal S. Figure 14 shows the denoised signal S analyzed based on the red gradation detection value Dr, green gradation detection value Dg, and blue gradation detection value Db shown in Figure 12. Figure 14 shows the denoised signal S when α = -0.5 and β = -0.5 are substituted into equation (10). Figure 14 shows the denoised signal S for the movement section S1 and the resting section S2.

[0083] As shown in Figure 14, the denoised signal S corresponds to the pulse wave signal. Noise components such as body movement are removed from the denoised signal S. The analysis unit 43 detects the denoised signal S as a pulse wave signal. The denoised signal S in the resting section S2 shows a clearer signal waveform compared to the green gradation detection value Dg. The denoised signal S in the moving section S1 is adjusted to a signal waveform corresponding to the pulse wave signal. Due to the noise reduction processing, the analysis unit 43 can detect the pulse wave signal in the moving section S1 and the resting section S2.

[0084] The analysis unit 43 calculates biological information such as pulse waves using the noise-reduced signal S. The analysis unit 43 acquires the noise-reduced signal S as a pulse wave signal. The analysis unit 43 calculates biological information such as pulse rate by calculating the period, amplitude, etc., of the pulse wave signal. The analysis unit 43 transmits the biological information, including the pulse wave signal, to the display control unit 45. The analysis unit 43 may store the biological information, etc., in the storage unit 50.

[0085] The display control unit 45 shown in Figure 3 controls the display by the display unit 30. The display control unit 45 acquires biological information, including pulse wave signals, from the analysis unit 43. The display control unit 45 generates biological information display data to display the biological information. The display control unit 45 transmits the biological information display data to the display unit 30. The display control unit 45 displays the biological information display data on the display unit 30. By displaying the biological information display data on the display unit 30, the display control unit 45 can notify the person performing the measurement of the detection results of the biological information.

[0086] The display control unit 45 may generate message data indicating the operating status of the biological analysis program PG. The message data may include a start message, an execution message, and an end message. The start message indicates that the detection of biological information has begun. The execution message indicates that biological information is being detected. The end message indicates that the detection of biological information has ended. The display control unit 45 transmits the message data to the display unit 30. The display control unit 45 causes the display unit 30 to display the message data.

[0087] The signal processing unit 47 performs adjustment processing on the signal values ​​when the control unit 40 receives each signal value from the imaging unit 20. The signal processing unit 47 performs A / D conversion of the adjusted signal values ​​to grayscale values. The signal processing unit 47 functions as an analog signal processing circuit 26 and a digital signal processing circuit 27. The signal processing unit 47 may also acquire the detection region 201 from the region setting unit 41 and perform adjustment processing using the detection region 201.

[0088] The memory unit 50 stores various programs, various data, etc. The memory unit 50 stores a bioanalysis program PG and setting area information SI. The memory unit 50 stores document creation programs, spreadsheet programs, etc. The memory unit 50 may also store various data such as video data and biometric information. The memory unit 50 may also store a correction coefficient table, output threshold TH, etc. The correction coefficient table includes a red signal correction coefficient kr, a green signal correction coefficient kg, and a blue signal correction coefficient kb. The memory unit 50 may also store a facial image database. The memory unit 50 is composed of semiconductor memory such as RAM (Random Access Memory) and ROM (Read Only Memory). The memory unit 50 may also function as a work area for the control unit 40. The memory unit 50 corresponds to an example of a memory unit.

[0089] The bioanalysis program PG is a program that causes the measuring device 10 to detect biological information, including pulse wave signals. The bioanalysis program PG is executed by the control unit 40. By executing the bioanalysis program PG in the control unit 40, the control unit 40 functions as various functional units. The bioanalysis program PG detects various biological information based on the pulse wave signals. The bioanalysis program PG may be executed in the background when the control unit 40 is running a document creation program or the like. The bioanalysis program PG corresponds to an example of a biological information acquisition program.

[0090] The setting region information SI is information relating to the undetected region 131. The undetected region 131 is used when the control unit 40 determines the detection region 201. The undetected region 131 is included in the face image region 121. The control unit 40 determines the detection region 201 by excluding the undetected region 131 from the face image region 121. The undetected region 131 includes one or more body parts. The setting region information SI is, as an example, information indicating that one or more body parts are in the undetected region 131. Body parts include marginal regions, head regions, hair regions, orbital regions, nasal cavity regions, lip regions, forehead regions, mandibular regions, etc. The marginal region is a region that includes marginal parts such as the contour of the face and the boundary with the hair. The head region is a region corresponding to the head. The hair region is a region that includes the hair. The orbital region is a region that corresponds to the orbit. The nasal cavity region is a region that corresponds to the nasal cavity. The lip region is a region that corresponds to the lips. The forehead region is the region corresponding to the forehead. The mandibular region is the region corresponding to the mandible.

[0091] The measuring device 10 includes an imaging sensor 23 that images reflected light L reflected by the observer, which includes red light RL of a red wavelength and green light GL of a green wavelength different from the red wavelength, and outputs a red signal value Sr related to the red light RL and a green signal value Sg related to the green light GL; an analog signal processing circuit 26 that performs adjustment processing on the red signal value Sr to bring it closer to the output median value MV of the output resolution of the imaging sensor 23; and an analysis unit 43 that calculates biological information based on the red signal value Sr and the green signal value Sg. The measuring device 10 can improve the detection accuracy of the pulse wave signal by performing adjustment processing on the red signal value Sr, etc.

[0092] When the red signal value Sr is higher than a predetermined output threshold TH, the analog signal processing circuit 26 preferably reduces the red signal Sr. The measuring device 10 can suppress the decrease in detection accuracy due to red light RL by reducing the red signal value Sr.

[0093] When the ratio of the red signal value Sr to the green signal value Sg is higher than a predetermined standard ratio value, the analog signal processing circuit 26 preferably reduces the red signal value Sr. The measuring device 10 can suppress the decrease in detection accuracy due to red light RL by reducing the red signal value Sr.

[0094] The analog signal processing circuit 26 preferably performs adjustment processing on the green signal value Sg. The measuring device 10 can improve the detection accuracy of the pulse wave signal by performing adjustment processing on the green signal value Sg.

[0095] The analog signal processing circuit 26 preferably adjusts the red signal value Sr and the green signal value Sg to the output median value MV of the output resolution as an adjustment process. The measuring device 10 can improve the detection accuracy of pulse wave signals by adjusting the red signal value Sr and the green signal value Sg to the output median value MV of the output resolution of the imaging sensor 23.

[0096] The analog signal processing circuit 26 preferably performs adjustment processing on the red signal value Sr and the green signal value Sg by adjusting the signal amplification factor. The measuring device 10 allows for easy adjustment of the red signal value Sr and the green signal value Sg.

[0097] The measuring device 10 includes a storage unit 50 that stores a red signal correction coefficient kr for correcting the red signal value Sr and a green signal correction coefficient kg for correcting the green signal value Sg. The analog signal processing circuit 26 preferably performs adjustment processing on the red signal value Sr and the green signal value Sg using the red signal correction coefficient kr and the green signal correction coefficient kg. The measuring device 10 allows for easy adjustment of the red signal value Sr and the green signal value Sg.

[0098] The imaging unit 20 captures reflected light L and generates image data. The analog signal processing circuit 26 preferably calculates a red calculation adjustment amount Cr to adjust the red signal value Sr and a green calculation adjustment amount Cg to adjust the green signal value Sg based on the image data, and performs adjustment processing on the red signal value Sr and the green signal value Sg using the red calculation adjustment amount Cr and the green calculation adjustment amount Cg. The measuring device 10 allows for easy adjustment of the red signal value Sr and the green signal value Sg.

[0099] The imaging unit 20 outputs a blue signal value Sb related to blue light BL, which has a blue wavelength different from the red and green wavelengths. The analog signal processing circuit 26 preferably performs adjustment processing on the blue signal value Sb. The measuring device 10 can improve the detection accuracy of pulse wave signals.

[0100] Figure 15 shows an example of the control flow performed by the measuring device 10. Figure 15 shows the control flow in which each signal value is input and biological information, including pulse wave signals, is detected using each signal value. The control flow is performed by the control unit 40 running the biological analysis program PG. Figure 15 shows the control flow as a flowchart.

[0101] In step S201, the measuring device 10 detects each signal value. The imaging unit 20 of the measuring device 10 captures the reflected light L reflected from the face of the person being measured. The imaging unit 20 generates moving image data by capturing the reflected light L. The moving image data includes multiple image data. The imaging unit 20 detects each signal value that constitutes the image data. The analog signal processing circuit 26 of the imaging unit 20 detects, as signal values, the red signal value Sr related to the red light RL of the red wavelength, the green signal value Sg related to the green light GL of the green wavelength, and the blue signal value Sb related to the blue light BL of the blue wavelength.

[0102] After detecting each signal value, the measuring device 10 performs an adjustment process for each signal value in step S203. The analog signal processing circuit 26 increases or decreases each signal value by adjusting the signal amplification factor for each signal value, as an example. By increasing or decreasing each signal value, the analog signal processing circuit 26 brings each signal value closer to the output median value MV of the output resolution of the imaging sensor 23 included in the imaging unit 20. As an adjustment process, the analog signal processing circuit 26 performs at least one of the following: color temperature adjustment process, threshold adjustment process, calculation adjustment process, and comparison adjustment process.

[0103] The measuring device 10 performs adjustment processing on each signal value, and then in step S205, performs A / D conversion on each signal value. The analog signal processing circuit 26 performs A / D conversion on the red signal value Sr, the green signal value Sg, and the blue signal value Sb to the red gradation value Gr, the green gradation value Gg, and the blue gradation value Gb, respectively. The digital signal processing circuit 27 performs various digital correction processing on the red gradation value Gr, the green gradation value Gg, and the blue gradation value Gb. After the digital signal processing circuit 27 has performed digital correction processing on each gradation value, the imaging unit 20 outputs moving image data, including image data composed of the red gradation value Gr, the green gradation value Gg, and the blue gradation value Gb, to the control unit 40.

[0104] The measuring device 10 performs A / D conversion on each signal value, and then in step S207, detects biological information including a pulse wave signal. The analysis unit 43 of the control unit 40 acquires the moving image data and the detection region 201 determined by the region setting unit 41. The analysis unit 43 uses the image data contained in the moving image data and the detection region 201 to acquire the red gradation detection value Dr, the green gradation detection value Dg, and the blue gradation detection value Db within the detection region 201. The analysis unit 43 detects a pulse wave signal based on the red gradation detection value Dr, the green gradation detection value Dg, and the blue gradation detection value Db. The analysis unit 43 detects biological information using the pulse wave signal.

[0105] The biological analysis program PG causes a control unit 40, which is connected to an imaging unit 20 that includes an imaging sensor 23, to capture reflected light L reflected by the observer, including red light RL of a red wavelength and green light GL of a green wavelength different from red, and output a red signal value Sr related to the red light RL and a green signal value Sg related to the green light GL. The control unit 40 calculates biological information based on the red signal value Sr and green signal value Sg, which have been adjusted to approach the output median value MV of the output resolution of the imaging sensor 23. The measuring device 10 can improve the detection accuracy of the pulse wave signal by performing adjustment processing on the red signal value Sr, etc.

[0106] The measuring device 10 shown in Figure 3 performs adjustment processing using an analog signal processing circuit 26 to bring each signal value closer to the output resolution of the imaging sensor 23. The measuring device 10 may also perform processing corresponding to the adjustment processing by changing the configuration of the color filter 24. The measuring device 10 may also be equipped with a dedicated color filter for measuring biological information in place of the color filter 24. The dedicated color filter is an example of the color filter 24. As an example, the dedicated color filter is designed so that the light transmittance of red light RL is lower than the light transmittance of green light GL and blue light BL. In the reflected light L reflected by the measurer, the light intensity of red light RL is higher than the light intensity of green light GL and blue light BL. By providing a dedicated color filter in which the light transmittance of red light RL is lower than the light transmittance of green light GL and blue light BL, the red signal value Sr related to red light GL approaches the output median value MV of the output resolution of the imaging sensor 23. As the red signal value Sr approaches the output median value MV of the output resolution of the imaging sensor 23, the measuring device 10 can suppress the decrease in the measurement accuracy of the pulse wave signal.

[0107] The dedicated color filter may be configured such that each signal value matches or approximately matches the light transmittance of the median output MV of the image sensor 23. Here, "approximately matches the median output MV of the image sensor 23" means that each signal value is within a predetermined tolerance range TR. The light transmittance of the red light RL is set to a range in which the red signal value Sr matches or approximately matches the median output MV of the image sensor 23. The light transmittance of the green light GL is set to a range in which the green signal value Sg matches or approximately matches the median output MV of the image sensor 23. The light transmittance of the blue light BL is set to a range in which the blue signal value Sb matches or approximately matches the median output MV of the image sensor 23.

[0108] The dedicated color filter, like the color filter 24, has a first portion that transmits red light RL, a second portion that transmits green light GL, and a third portion that transmits blue light BL. The dedicated color filter may have a configuration in which the first portion is smaller than the second and third portions. When the first portion is smaller than the second and third portions, the red signal value Sr decreases. The red signal value Sr approaches the output median value MV of the output resolution of the image sensor 23. By the red signal value Sr approaching the output median value MV of the output resolution of the image sensor 23, the measuring device 10 can suppress the decrease in the measurement accuracy of the pulse wave signal.

[0109] The measuring device 10 includes a dedicated color filter that allows reflected light L, which includes red light RL of a red wavelength and green light GL of a green wavelength different from that of the measuring device, to pass through; an imaging sensor 23 that images the reflected light L that has passed through the dedicated color filter and outputs a red signal value Sr related to the red light RL and a green signal value Sg related to the green light GL; and an analog signal processing circuit 26 that calculates biological information based on the red signal value Sr and the green signal value Sg. The dedicated color filter has a light transmittance that brings the red signal value Sr closer to the output median value MV of the output resolution of the imaging sensor 23. The measuring device 10 can improve the accuracy of pulse wave signal measurement. [Explanation of Symbols]

[0110] 10... Measuring device, 20... Imaging unit, 21... Optical element, 22... Substrate, 23... Imaging sensor, 24... Color filter, 25... Image processing circuit group, 26... Analog signal processing circuit, 27... Digital signal processing circuit, 30... Display unit, 40... Control unit, 41... Area setting unit, 43... Analysis unit, 45... Display control unit, 47... Signal processing unit, 100... Captured image, 121... Face image area, 131... Undetectable area, 201... Detection area, BL... Blue light, Db... Blue gradation detection value, Dg... Green gradation detection value, Dr... Red gradation detection value, Gb... Blue gradation value, Gb1... First blue gradation value, Gb2... Second blue gradation value, Gg... Green gradation value, G g1...First green tone value, Gg2...Second green tone value, GL...Green light, Gr...Red tone value, Gr1...First red tone value, Gr2...Second red tone value, L...Reflected light, MV...Output median value, PG...Biological analysis program, RL...Red light, S1...Body movement interval, S2...Rest interval, Sb...Blue signal value, Sb1...First blue signal value, Sb2...Second blue signal value, Sg...Green signal value, Sg1...First green signal value, Sg2...Second green signal value, SI...Setting area information, Sr...Red signal value, Sr1...First red signal value, Sr2...Second red signal value, SV...Saturation value, TH...Output threshold, TH1...First output threshold, TH2...Second output threshold, TR...Tolerance range.

Claims

1. An imaging unit captures reflected light reflected by a living organism, including first wavelength light of a first wavelength and second wavelength light of a second wavelength different from the first wavelength, and outputs a first output value related to the first wavelength light and a second output value related to the second wavelength light. A data processing unit performs data correction on the first output value to bring it closer to the median output resolution of the imaging unit, A calculation unit that calculates biological information based on the first output value and the second output value, A biological information acquisition device equipped with the following features.

2. When the aforementioned first output value is higher than a predetermined threshold, The data processing unit reduces the first output value. A biological information acquisition device according to claim 1.

3. When the ratio of the first output value to the second output value is higher than a predetermined ratio value, The data processing unit reduces the first output value. A biological information acquisition device according to claim 1.

4. The aforementioned data processing unit The data correction is performed on the second output value. A biological information acquisition device according to claim 1.

5. The data processing unit adjusts the first output value and the second output value to the median value of the output resolution as data correction. A biological information acquisition device according to claim 4.

6. The data processing unit performs the data correction on the first output value and the second output value by adjusting the signal amplification factor. A biological information acquisition device according to claim 4.

7. The system includes a storage unit that stores a first correction value for correcting the first output value and a second correction value for correcting the second output value. The data processing unit performs the data correction on the first output value and the second output value using the first correction value and the second correction value. A biological information acquisition device according to claim 4.

8. The imaging unit captures the reflected light and generates imaging data. The data processing unit calculates a first adjustment amount for adjusting the first output value and a second adjustment amount for adjusting the second output value based on the imaging data. Using the first adjustment amount and the second adjustment amount, the data correction is performed on the first output value and the second output value. A biological information acquisition device according to claim 4.

9. The imaging unit outputs a third output value related to a third wavelength light that is different from the first and second wavelengths. The data processing unit performs the data correction on the third output value. A biological information acquisition device according to claim 4.

10. A color filter that allows reflected light reflected by a living organism to pass through, including first wavelength light of a first wavelength and second wavelength light of a second wavelength different from the first wavelength, An imaging unit that images the reflected light that has passed through the color filter and outputs a first output value related to the first wavelength light and a second output value related to the second wavelength light, The system comprises a calculation unit that calculates biological information based on the first output value and the second output value, The color filter has a light transmittance that brings the first output value closer to the median output resolution of the imaging unit. A device for acquiring biological information.

11. A computer connected to an imaging unit includes an imaging unit that captures reflected light reflected by a living organism, including first wavelength light of a first wavelength and second wavelength light of a second wavelength different from the first wavelength, and outputs a first output value related to the first wavelength light and a second output value related to the second wavelength light. Based on the first and second output values, which have undergone data correction to approach the median output resolution of the imaging unit, biological information is calculated. A program for acquiring biometric information.

Images