Virus dispersion range measurement method, virus dispersion visualization method, and virus dispersion visualization device

Abstract

To provide a virus scattering range measuring method, a virus scattering visualization method, and a virus scattering visualization device.SOLUTION: A device (camera 101) uses an imaging optical system 12 for infrared light 11 with a wavelength of 3 μm or more and 5 μm or less, and an image sensor 13 in which pixel elements 14 made of an infrared photodetecting element having a photoelectric conversion layer that converts infrared light into an electric signal are arranged in a matrix, and infrared light is imaged on the image sensor through the imaging optical system, and the range in which a grayscale image is obtained by image formation in the observed atmospheric environment is defined as the virus scattering range.SELECTED DRAWING: Figure 1

Description

[Technical field]

[0001] The present invention relates to a virus dispersion range measuring method, a virus dispersion visualization method, and a virus dispersion visualization device. [Background technology]

[0002] Pandemics caused by the spread of viruses such as COVID-19 have become a major issue, dealing a major blow to society on a global scale in terms of the number of deaths, the collapse of the medical system, and economic losses due to state of emergency declarations and lockouts.

[0003] In order to prevent the spread of viruses, it is important to develop medical technologies such as vaccines and treatments, as well as to understand and monitor the process by which the virus spreads. Viruses are often transmitted through droplets or the air.

[0004] For COVID-19, supercomputers such as Fugaku have been used to simulate the spread of droplets, and these have been used to create standards for the Three Cs (closed spaces, crowded places, and close contact) and for operational standards in cafeterias and other places. In this way, it is extremely important to visualize the spread of the virus through droplets and airborne infection, and the range of influence from exhalation and coughing. In particular, visualization of the actual situation in medical and nursing care settings, living environments, etc., has a huge impact on preventing the spread of the virus and formulating prevention measures. In addition, in order to visualize the range of exhaled breath, coughs, etc., there is a method of measuring using the Schlieren method by focusing on the fact that the refractive index of exhaled breath is slightly different from that of the atmosphere, and this method is disclosed in, for example, Patent Document 1. [Prior art documents] [Patent documents]

[0005] [Patent Document 1] Patent No. 6796306 [Non-patent literature]

[0006] [Non-Patent Document 1] J.E.Bertie and Z.Lan,Applied Spectroscopy,50,1047-1057(1996) [Non-Patent Document 2] EVKochanov,et al.J.Quant.Spectrosc.Radiat.Transfer,177,15-30(2016) [Non-Patent Document 3] John C.Russ, The Image Processing Handbook, 2nd. Ed., CRC Press, Inc., pp211-480, 1995 Summary of the Invention [Problem to be solved by the invention]

[0007] The object of the present invention is to provide a method for determining the spatial area affected when a virus is airborne or droplet-transmitted through exhaled breath, etc., i.e., the virus dispersion range, and to provide a method for visualizing the situation in which the virus is dispersed. Another object of the present invention is to provide a method for measuring the range of virus dispersion and visualizing virus dispersion using a portable device that can easily perform measurements in real time in real environments such as medical and nursing care settings and living environments. Another object of the present invention is to provide an apparatus for visualizing virus dispersion.

[0008] The method based on the Schlieren method disclosed in Patent Document 1 uses a slight difference in refractive index, so it is susceptible to the effects of the measurement environment, such as uneven air temperature, temperature distribution of the environment such as walls, and air currents such as wind, and the device tends to be relatively large-scale, using a projector, etc. Furthermore, there is also the problem that it is difficult to capture droplets with this method. [Means for solving the problem]

[0009] The configuration of the present invention for solving the problems is shown below. (Configuration 1) an imaging optical system for infrared light having a wavelength of 3 μm or more and 5 μm or less; An image sensor is used in which pixel elements each made of an infrared light sensing element having a photoelectric conversion layer for converting the infrared light into an electric signal are arranged in a matrix form, The infrared light is imaged onto the image sensor via the imaging optical system; A method for measuring the range of virus dispersion, in which the range in which a grayscale image is obtained by the imaging in the observed atmospheric environment is determined as the virus dispersion range. (Configuration 2) A method for measuring the range of virus dispersion according to configuration 1, wherein the wavelength of the infrared light is 4.15 μm or more and 4.40 μm or less. (Configuration 3) A method for measuring the range of virus dispersion according to configuration 1, wherein the wavelength of the infrared light is 4.20 μm or more and 4.35 μm or less. (Configuration 4) 4. A method for measuring the range of virus dispersion described in any one of configurations 1 to 3, wherein the photoelectric conversion layer is made of InSb. (Configuration 5) A bandpass filter that transmits only infrared light of the wavelength is placed in front of or behind the imaging optical system, A method for measuring the range of virus dispersion described in any one of configurations 1 to 4, wherein the infrared light is imaged on the image sensor via the bandpass filter. (Configuration 6) A method for measuring the range of virus dispersion as described in configuration 5, wherein the bandpass filter is cooled. (Configuration 7) A method for measuring the range of virus dispersion according to configuration 6, wherein the cooling temperature is 50K or higher and 250K or lower. (Configuration 8) A method for measuring the range of virus dispersion described in any one of configurations 1 to 7, which separately indicates the range of airborne infection and the range of droplet infection using the spatial frequency distribution of the grayscale image acquired by the image sensor. (Configuration 9) A method for measuring the range of virus dispersion described in any one of configurations 1 to 7, which acquires brightness information of each pixel of the image sensor, extracts pixels that show a brightness outside a predetermined brightness range, and displays the image area occupied by the pixels outside the brightness range as the range affected by droplet infection. (Configuration 10) an imaging optical system for infrared light having a wavelength of 3 μm or more and 5 μm or less; An image sensor is used in which pixel elements each made of an infrared light sensing element having a photoelectric conversion layer for converting the infrared light into an electric signal are arranged in a matrix form, The infrared light is imaged onto the image sensor via the imaging optical system; Obtaining a video of a grayscale image formed by the imaging in an observation atmospheric environment; A virus dispersion visualization method for visualizing the change over time in the range of the grayscale image as a change in the virus dispersion range. (Configuration 11) 11. A virus scattering visualization method according to claim 10, wherein the wavelength of the infrared light is 4.15 μm or more and 4.40 μm or less. (Configuration 12) 11. A virus scattering visualization method according to claim 10, wherein the wavelength of the infrared light is 4.20 μm or more and 4.35 μm or less. (Configuration 13) 13. The virus dispersion visualization method according to any one of claims 10 to 12, wherein the photoelectric conversion layer is made of InSb. (Configuration 14) A bandpass filter that transmits only infrared light of the wavelength is placed in front of or behind the imaging optical system, A virus dispersion visualization method described in any one of configurations 10 to 13, wherein the infrared light is imaged on the image sensor via the bandpass filter. (Configuration 15) A virus dispersion visualization method described in any one of configurations 10 to 14, which uses the spatial frequency distribution of the grayscale image acquired by the image sensor to separately visualize the range affected by airborne infection and the range affected by droplet infection. (Configuration 16) A virus dispersion visualization method described in any one of configurations 10 to 14, which acquires brightness information of each pixel of the image sensor, extracts pixels that show a brightness outside a predetermined brightness range, and visualizes the diffusion status of droplets using the arrangement distribution of the pixels outside the brightness range. (Configuration 17) A virus dispersion visualization method described in any one of configurations 10 to 14, which acquires brightness information of each pixel of the image sensor, extracts pixels that show a brightness outside a predetermined brightness range, and visualizes the diffusion status of droplets using the temporal trajectory of the pixels outside the brightness range. (Configuration 18) A camera and an image processing means are provided, The camera includes an imaging optical system for infrared light having a wavelength of 3 μm or more and 5 μm or less; a pixel element including an infrared light sensing element having a photoelectric conversion layer for converting the infrared light into an electric signal, the pixel element having an image sensor arranged in a matrix; The image processing means of the virus dispersion visualization device calculates the spatial frequency distribution of the grayscale image acquired by the image sensor, and / or acquires brightness information of each pixel of the image sensor, extracts pixels that show a brightness outside a predetermined brightness range, and calculates the temporal trajectory of the pixels outside the brightness range. (Configuration 19) 19. A virus scattering visualization device according to configuration 18, wherein the wavelength of the infrared light is 4.15 μm or more and 4.40 μm or less. (Configuration 20) 19. A virus scattering visualization device according to configuration 18, wherein the wavelength of the infrared light is 4.20 μm or more and 4.35 μm or less. (Configuration 21) 21. A virus dispersion visualization device according to any one of configurations 18 to 20, wherein the photoelectric conversion layer is made of InSb. (Configuration 22) A bandpass filter that transmits only infrared light of the wavelength is placed in front of or behind the imaging optical system, A virus dispersion visualization device described in any one of configurations 18 to 21, wherein the infrared light is imaged onto the image sensor via the bandpass filter. Effect of the Invention

[0010] According to the present invention, there is provided a method for determining the range of virus dispersion when a virus is airborne or droplet-transmitted through exhaled breath, etc., and a method for visualizing the state in which the virus is dispersed. Furthermore, according to the present invention, there is also provided an apparatus for visualizing virus dispersion. Here, a method for measuring the range of virus dispersion and visualizing virus dispersion can be provided by a portable device that can easily perform measurements in real time in actual environments such as medical and nursing care sites and living environments. [Brief description of the drawings]

[0011] [Figure 1] FIG. 1 is an explanatory diagram showing a configuration of an apparatus according to the present invention. [Diagram 2] 1 is a characteristic diagram showing the absorption spectra of CO2, liquid phase H2O, and gas phase H2O. [Diagram 3] This is a characteristic diagram showing the relationship between the thickness of CO2, liquid phase H2O, and gas phase H2O and the absorptance of infrared light with a wavelength of 4.20-4.35 μm traveling through them. [Figure 4] 1 is a photograph of a portable measuring device used in the examples. [Diagram 5] FIG. 4 is a characteristic diagram showing the transmission spectrum of a bandpass filter used in the examples. [Figure 6] FIG. 11 is a characteristic diagram showing the temperature characteristics of the radiation intensity of the bandpass filter used in the examples. [Figure 7] 1 is a photograph showing an example of observing exhaled breath according to the present invention. [Figure 8] 4 is a photograph showing an example of exhaust observation according to the present invention. [Figure 9] 13 is a photograph showing the change over time in water droplets sprayed by a mist spray. [Figure 10] These are photographs showing an example of an eruption of gaseous H2O over time. [Figure 11] 1 is a photograph showing an example of sneezing observation according to the present invention. [Figure 12] FIG. 1 is an explanatory diagram showing a configuration of an apparatus according to the present invention. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0012] Hereinafter, an embodiment of the present invention will be described with reference to the drawings. In addition, AB in the text means greater than or equal to A and less than or equal to B.

[0013] (Embodiment 1) Because viruses are so small, measuring less than a few hundred nanometers in size, it is difficult to directly observe the viruses to determine the range of airborne or droplet infection or to visualize how they spread. In this invention, we focus on the fact that viruses spread through exhaled breath, and measure the range of airborne virus infection with carbon dioxide (CO2) contained in high concentrations in exhaled breath, and the range of droplet infection with viruses with minute water droplets. In addition, we monitor and visualize the ranges of these infections using video.

[0014] The concentration of CO2 in the atmosphere has been increasing year by year due to the effects of global warming, but as of 2020 it was around 400 ppm (0.04%). Concentrations are generally higher indoors where people are crowded together, but the Building Management Act stipulates that the CO2 concentration in buildings used by an unspecified number of people must be kept below a maximum of 1000 ppm (0.1%), which sets the upper limit for the concentration in the general environment. Meanwhile, the concentration of CO2 in a person's breath is around 1% at rest and around 9% when performing heavy work, with the daily average being around 3%, which is equivalent to light work. Since human breath contains CO2 at a concentration one or two orders of magnitude higher than that in the environment, the range and flow of breath can be monitored by CO2 measurement in everyday life and in medical settings while sufficiently suppressing the baseline (measurement noise) from the environment and with sufficient sensitivity, and therefore ensuring a sufficient S / N ratio. Here, as mentioned above, the range and flow of breath can be considered equivalent to the range and spread of the virus.

[0015] The main component of droplets expelled in the breath is water (liquid-phase H2O molecules). Therefore, droplets containing viruses can be monitored by detecting water droplets of a similar size. The size of droplets in the breath ranges from 10 nm to several mm, but the number concentration peaks at approximately 2 μm and 120-150 μm. Therefore, it is sufficient to measure water droplets of this size.

[0016] Living environments and medical facilities have a wide range of humidity levels, from extremely high, close to 100%, to extremely dry, close to 0%. There is a demand for visualization of the range and spread of viruses in a wide range of humidity environments, from dry environments where influenza is prevalent to high humidity environments that are said to suppress viral activity. Humidity is, of course, due to gaseous water (H2O molecules in the gas phase). For this reason, in order to measure droplets in a high-humidity environment, it is necessary to be able to detect water droplets of about 100 μm with sufficient sensitivity, but not to detect gaseous water. Furthermore, from an operational standpoint, it is desirable to be able to measure airborne and droplet infections simultaneously using a single, simple device.

[0017] Based on the inventor's long experience in molecular detection using infrared light, the inventor has investigated a measurement method that meets the above requirements: (1) the ability to detect CO2 gas with high sensitivity, (2) the ability to detect water droplets of about 100 μm with sufficient sensitivity but not detect gaseous water, and (3) the ability to measure #1 and #2 simultaneously using a single simple device.

[0018] As a result of detailed experiments, the present invention was created, which involves capturing images with a so-called camera using an imaging means (imaging optical system) and an image sensor in the infrared light band with a wavelength of 3 μm or more and 5 μm or less, or 4.15 μm or more and 4.40 μm or less to further improve sensitivity and S / N, and 4.20 μm or more and 4.35 μm or less to further improve sensitivity and S / N.

[0019] FIG. 1( a ) shows the main components of the camera 101 . The camera 101 has an imaging means 12 adapted to receive infrared light 11 of the above wavelength, and an image sensor 13 in which image elements 14 made of infrared light sensing elements are arranged in a matrix.

[0020] The imaging means 12 is not particularly limited as long as it has sufficient imaging performance as a camera, but for example, a lens imaging system using optical lenses made of Ge, Si, ZnSe, ZnS, or sapphire, a reflective optical system using a mirror, or a composite optical system using a mirror and a lens can be used. A short focal length lens or a zoom lens can also be used. There are no particular limitations on the magnification, F-number, allowable aberration, etc., and an appropriate selection can be made in consideration of cost, ease of use, weight, resolution, field of view, etc.

[0021] As the pixel element 14 (infrared light sensing element), a photoelectric conversion element having sensitivity in the wavelength band of 3 μm or more and 5 μm or less, such as InSb, HgCdTe, InAs / GaSb superlattice, InGaAs / InAlAs quantum well, GaAs / AlGaAs quantum well, etc., may be used. Also, a thermal type infrared light sensing element using a bolometer, thermopile, or pyroelectric element may be used. Among these, InSb is particularly preferred because of its excellent sensitivity and S / N characteristics in this wavelength band. The pixel size and the number of pixels of the pixel element 14 are not particularly limited. If the pixel size is reduced, the size of the image sensor 13 also becomes smaller, and it becomes easier to miniaturize the imaging means 12. If the pixel size is large, it becomes easier to improve the sensitivity and S / N ratio, and it becomes easier to increase the resolution. For example, the pixel size is 10×10-30×30 μm. 2 It is acceptable to do so. The number of pixels is not particularly limited, and may be set appropriately in consideration of the size of the device, the required resolution, etc. The number of pixels may be, for example, 64×64-1920×1536.

[0022] To narrow the wavelength of the infrared light 11 to be measured to 4.15 μm or more and 4.40 μm or less, or 4.20 μm or more and 4.35 μm or less, it is effective to use a bandpass filter. The bandpass filter is small, lightweight, and easy to handle, and can be removed as necessary. Note that the bandpass filter may be, for example, a multilayer film made of SiO, ZnS, Ge, etc. formed on a sapphire or germanium substrate. The bandpass filter may be placed in front of the imaging means 12 as viewed from the image sensor 13, as shown by bandpass filter 15a in camera 102 in Fig. 1(b), or may be placed behind the imaging means 12, as shown by bandpass filter 15b in camera 103 in Fig. 1(c). Placing the filter in front has the advantage of making it easy to replace or remove the bandpass filter, while placing the filter behind has the advantage that the bandpass filter can be small and can be cooled together with the image sensor 13 when cooling, as described below, is performed.

[0023] It is preferable to cool the bandpass filters 15a and 15b and the image sensor 13. Cooling them can reduce noise caused by thermal radiation from the environment, components, etc. In particular, when the bandpass filters 15a and 15b are at room temperature, thermal radiation from them is superimposed on the signal from the image sensor 13 as a large baseline, significantly reducing the contrast of the obtained image. Cooling methods include Stirling coolers, Peltier elements, and liquid nitrogen cooling, among which Stirling coolers and Peltier elements are preferred because they are easy to handle. Stirling coolers are particularly preferred because they are handy, can cool to 80K or less, and can be operated with batteries.

[0024] The cooling temperature is preferably 50K or higher and 250K or lower. By keeping it at 250K or lower, the noise level can be improved by one order of magnitude or more. The lower the temperature, the lower the noise level, but at 50K, the noise level is 20 orders of magnitude lower than when used at room temperature, and at this level, noise due to other factors such as voltage fluctuations becomes dominant. Since convenience and ease of handling decrease when the temperature is extremely low, it is preferable to use it at 50K or higher.

[0025] Three molecules are involved in this invention: H2O molecules in the liquid phase, H2O molecules in the gas phase, and CO2 molecules in the gas phase. The absorption coefficients of these three molecules are shown in Figure 2. (a) is a wide-area view of the entire mid-infrared region, and (b) is an enlarged view of the vicinity of 4.2 μm. Liquid phase H2O: 2.7-3.5μm, 5.7-6.5μm It is located at In addition to the main absorption band, it has a weak absorption band (1 in Figure 2(a)) at wavelengths of 4.15-5.2 μm. The absorption coefficient of gaseous H2O in Figure 2 is the absorption coefficient of air containing gaseous H2O up to the saturated vapor pressure in air at 1 atmosphere and 25°C (air containing H2O at a volume concentration of 3.1%). This corresponds to a relative humidity of 100%, and indicates the upper limit at which gaseous H2O will not be contained. As is well known, gaseous H2O molecules exhibit large absorption at wavelengths of 5-8 μm. This is the cause of dividing the mid-infrared range into the mid-wave band (MWIR) of 3-5 μm and the long wave band (LWIR) of 8-12 μm. However, the absorption of gaseous H2O is extremely low at wavelengths of around 4 μm, and is 8 to 10 orders of magnitude lower than that of liquid-phase H2O. In order to solve the problem of measuring and visualizing the dispersion range of viruses, one of the foundations of this patent is the fact that there is such a large contrast in the absorption coefficient of the same H2O molecule due to the difference in the state between the liquid phase and the gas phase. End

[0026] On the other hand, the absorption band of CO2 gas is at wavelengths of 4.20-4.35 μm, as shown in Figure 2. This absorption coefficient is the absorption coefficient when gaseous CO2 is contained at a volume concentration of 1% in air at 1 atmosphere and 25°C. As mentioned above, this is a conservative estimate that corresponds to a state in which the CO2 concentration is particularly low in human breath. In general, human breath contains several to nearly 10 times this amount of CO2. Absorption at 4.20-4.35 μm is very strong, and in this wavelength band, despite the conservative estimate of 1%, it shows a large absorption coefficient that is closer to that of liquid phase H2O than the same gaseous H2O. Another basis of this patent is that we focused on the existence of this strong absorption band of CO2 molecules in the 3-5 μm wavelength band, where high-performance infrared light detection elements and cameras are easily available, in order to solve the problem of measuring and visualizing the dispersion range of viruses. In FIG. 2, the absorption coefficient of liquid H2O follows Non-Patent Document 1. In addition, the absorption coefficients of gas-phase H2O and CO2 were obtained using the database HITRAN and the HITRAN Application Programming Interface (HAPI) provided by Non-Patent Document 2.

[0027] At room temperature, all objects radiate infrared light according to Planck's law. According to Wien's displacement law, the thermal radiation of a perfect black body at 25°C has a peak at a wavelength of 9.7 μm. However, black body radiation is distributed over a wide wavelength range, and objects at 25°C also radiate infrared light with a wavelength of around 4 μm. Therefore, at room temperature, all objects in the background act as natural light sources. The infrared light 11 in Figure 1 is the infrared light radiated by such background objects. However, if necessary, a heat source such as a black body furnace or a hot plate can be used as a light source. If there is an absorber that absorbs light of a specific wavelength between the background and the cameras 101, 102, and 103, the intensity of the light of that absorption band wavelength that passes through the absorber will change. Because the background emits light over a wide wavelength range, the overall change is minimal if only light of a narrow absorption band is absorbed. However, if the wavelengths to be detected are limited to the absorption wavelength band of the absorber, the presence of the absorber will sensitively change the intensity of the infrared light that reaches the camera with large contrast. In this way, the presence of the absorber can be visualized.

[0028] When the temperature of the absorber is equal to or lower than the temperature of the background, the absorber simply absorbs the infrared light from the background, and the intensity of the infrared light reaching the camera becomes weaker. However, when the temperature of the absorber is higher than that of the background, according to Kirchhoff's law, which shows the reversibility of absorption and thermal radiation, the absorber emits light at the wavelength it absorbs, and the intensity of the infrared light reaching the camera becomes stronger. More precisely, the way in which the intensity change occurs in the infrared light reaching the camera due to the presence of the absorber changes depending on various factors, such as the absorber's absorptivity and emissivity (both are equal according to Kirchhoff's law), the emissivity of the background, the imaging lens 12, and the optical relationship determined by the imaging lens 12, in addition to the temperature. Here, we will explain the simplest case in which the background has an emissivity close to that of a perfect black body and the absorber's temperature is equal to that of the background. In this case, the presence of the absorber absorbs the infrared light, and the observed infrared light 11 becomes weaker.

[0029] Figure 3 shows the percentage of infrared light emitted from the background that is absorbed in the wavelength range of 4.20-4.35 μm when liquid phase H2O, gas phase H2O (1 atm, 25°C, 3.1%), and gas phase CO2 (1 atm, 25°C, 1%) shown in Figure 2 are present at a certain thickness between the background and the camera. These are estimates based on the average absorption coefficients of each molecule in the wavelength range of 4.20-4.35 μm in Figure 2. The average absorption coefficient is 236 cm for liquid phase H2O, 236 cm for gas phase CO2, and 236 cm for gas phase CO2. -1 , CO2 is 0.297 cm -1 , and the gas phase H2O is 2.17 × 10 -7 cm -1 It is.

[0030] Due to differences in absorption coefficients across several orders of magnitude in this wavelength range, the distance dependence varies greatly depending on the type of absorber. The horizontal axis of Figure 3 is displayed in a wide range from 1 nm to 1 km. For example, when the intensity of infrared light can be measured with a resolution of 7 bits (128 gradations), a change in intensity due to absorption of about 1% can be detected. The vertical axis of Figure 3 is 10 -2 If we calculate the thickness as these, the liquid phase H2O is 0.43 μm, the CO2 is 0.34 mm, and the gas phase H2O is 460 m. The absorption of liquid H2O in this wavelength range is weaker than others. However, the above values ​​mean that a detectable change in intensity occurs when light passes through liquid H2O of only 0.43 μm in size. In other words, droplets (water droplets) of 1 μm or less in size that may contain viruses and are contained in exhaled breath can be visualized by focusing on this wavelength range.

[0031] The spread of human breath can range from a few centimeters to a few tens of centimeters. The results in Figure 3 show that CO2 with a concentration of 1% can be detected with a thickness of 0.34 mm, so by focusing on this wavelength range, breath that may contain viruses can be visualized. -2 The thickness of 0.34 mm that gives the absorption of CO2 is the hypothetical detection limit thickness when it is assumed that the breath diffuses while maintaining a concentration of 1%, and this value gives the limit value of the product of the concentration of CO2 and the thickness through which it is distributed. For example, even if the breath diffuses and the concentration (the increase from the original CO2 concentration in the environment) drops to 1 / 100, or 0.01%, or 100 ppm, if it is distributed over a thickness of 100 times, or 34 mm, then the detection limit of 10 -2 This produces a change in intensity that is visible. In reality, various image enhancement methods have been established, and the detectable intensity change is 10 -2 This means that the measurement and visualization capabilities for the actual airborne and droplet infection areas will be much higher.

[0032] On the other hand, in order for gas-phase H2O at 100% humidity to produce a detectable change in intensity, it must propagate a distance of several hundred meters. When considering measurements at practical distances of several tens of centimeters to several meters, the absorption of gas-phase H2O can be practically ignored. By focusing on this wavelength range, CO2 can be stably visualized without any hindrance in any humidity environment. As we have seen, the wavelength of 3-5 μm covers the absorption bands of gaseous CO2, liquid H2O, and gaseous H2O, making it possible to visualize them. In particular, the wavelengths of 4.15-4.40 μm and 4.20-4.35 μm cover the absorption band of CO2 gas and overlap with the weak absorption band of water. This makes it possible to meet the requirements (1)-(3) above.

[0033] Next, consider what kind of grayscale image is formed by light of the absorption band wavelength that passes through an absorber that absorbs light of a specific wavelength, such as CO2 gas or water droplets. In the case of a gas such as CO2 gas, this grayscale image has a spatial spread with gradually changing density, in other words, an image with a grayscale distribution with a low spatial frequency. On the other hand, in the case of a minute particle such as a water droplet, the image has a local spread of dark spots and bright spots, in other words, an image with a grayscale distribution with a high spatial frequency. Alternatively, depending on the concentration of CO2 gas or the size of the water droplet, the brightness values ​​of both may be distributed in different regions, and they may be distinguishable from the brightness value.

[0034] In this invention, by utilizing the difference in the characteristics of the two-dimensional distribution of the intensity images of gaseous CO2 and liquid H2O, airborne and droplet infections of viruses are separated and their ranges and spreads are visualized. Alternatively, by utilizing the difference in the time-dependent changes in the two-dimensional distribution of the intensity images, airborne and droplet infections of viruses are separated and their ranges and spreads are visualized. The method of image processing based on spatial frequency is not particularly limited, but examples include a method using a low-pass filter or a high-pass filter based on Fourier transform. In addition, edge enhancement methods such as a Laplacian filter, a Sobel filter, and differential processing may be used to extract droplets. In this way, dark and bright spots can be extracted from the grayscale image, the extent of the dark and bright spots can be determined as the range reached by droplets, and this range can be displayed to visualize the droplet diffusion situation using a video or the like.

[0035] One method involves obtaining brightness information for each pixel on the image sensor, extracting pixels that show a brightness outside a predetermined brightness range, and displaying the area of ​​the image occupied by the pixels that fall outside that range as the area affected by droplet infection, or visualizing the spread of droplets using the distribution of the pixels that fall outside that range. It is also possible to obtain the brightness information of each pixel of the image sensor, extract pixels that show brightness outside a predetermined brightness range, and separate droplets from other things based on the time trajectory of pixels that are outside the brightness range obtained by methods such as optical flow. In addition, by visualizing the spread of droplets using such video processing methods, it becomes possible to visually understand the spread of droplet infection. As specific image processing methods, various methods have already been developed and established, and are summarized in, for example, Non-Patent Document 3. Since these are known technologies, detailed explanations will be omitted here. Since all of the image processing methods described above can be applied in real time, measurements can be easily performed in real time in a real environment.

[0036] FIG. 12 is a schematic diagram showing the configuration of a virus scattering visualization device 201. The virus dispersion visualization device 201 comprises a camera 51 and an image processing means 52. The camera 51 has an imaging optical system 12 for infrared light 11 having a wavelength of 3 μm or more and 5 μm or less as shown in FIG. 1, and an image sensor 13 in which pixel elements 14 consisting of infrared light sensing elements having a photoelectric conversion layer that converts infrared light into an electrical signal are arranged in a matrix form. The image processing means 52 calculates the spatial frequency distribution of the grayscale image acquired by the image sensor 13, and / or acquires luminance information of each pixel of the image sensor, extracts pixels that show a luminance outside a predetermined luminance range, and calculates the temporal trajectory of the pixels outside the luminance range.

[0037] As described in the above method, the wavelength of the infrared light 11 is preferably 4.15 μm or more and 4.40 μm or less, and more preferably 4.20 μm or more and 4.35 μm or less. As described in the above method, the photoelectric conversion layer is preferably made of InSb. Furthermore, as described in the above method, it is preferable to place a bandpass filter that transmits only infrared light of a certain wavelength in front of (15a) or behind (15b) the imaging optical system, and image the infrared light 11 on the image sensor through the bandpass filter. EXAMPLES

[0038] Example 1 In Example 1, the configuration of the device and an example of observation using the device will be described. Naturally, the present invention is not limited to such a specific form, and the technical scope of the present invention is defined by the claims.

[0039] An overall photograph of the apparatus used is shown in FIG. The device is a portable device consisting of a camera, a PC for control, observation and display, a battery to drive them, and a tripod to hold the camera. The camera weighs about 2.5 kg, and the battery weighs about 5 kg. With this camera, you can take pictures as easily as with a home video camera.

[0040] The configuration of the camera 103 is shown in FIG. The camera 103 is a FLIR A6796 model, and has an imaging means (imaging lens) 12 adapted to infrared light in the 3-5 μm wavelength range, a bandpass filter 15b with a central transmission wavelength of about 4.25 μm, and an image sensor 13 in which image elements 14 made of infrared light sensing elements using InSb are arranged in a 640 x 512 matrix. Here, the bandpass filter 15b is cooled to 80K together with the image sensor 13 (pixel element 14) by a battery-powered Stirling cooler. The image sensor 13 (pixel element 14) has a gradation of 14 bits and a sensitive wavelength band of 3-5 μm. As the imaging lens 12, those with focal lengths of 25 mm, 50 mm, and 100 mm and F-number of 2.5 are available, for example.

[0041] The transmission wavelength characteristic of the bandpass filter 15b cooled to 80K is shown in Fig. 5. It transmits infrared light in the wavelength range of 4.0-4.4 µm. Moreover, the effect of cooling the bandpass filter 15b is shown in Figure 6. The vertical axis represents the total amount of infrared light intensity emitted by this bandpass filter within the 3-5 μm wavelength sensitivity range of the InSb infrared light sensing element, i.e., the infrared light signal level derived from the bandpass filter, and it shows that by cooling the filter to 80 K, a clear image with high contrast can be obtained with a baseline reduced by 10 orders of magnitude or more compared to room temperature (300 K).

[0042] Figure 7 shows a still image of a moment extracted from a video of exhaled breath taken in a normal room with a room temperature of 25°C and a humidity of 60%. As can be seen, (a) is an image of the exhaled breath directly, (b) is an image of the breath through a nonwoven mask, and (c) is an image of the breath through a mouth shield. Breath contains an order of magnitude more CO2 gas than air. The range that breath can reach, which is the range of airborne infection, can be clearly visualized as the range in which CO2 gas floats. In this case, the exhaled CO2 is observed to be bright as a light source, even though it is an absorbent, reflecting the fact that the temperature of the exhaled CO2 is body temperature (approximately 37°C), which is higher than room temperature. The effect of Kirchhoff's law mentioned above is apparent here. Figure 8 shows a similar observation of high-temperature CO2. The warm CO2 emitted from the exhaust port of a fan heater is observed as bright light.

[0043] Figure 8 shows still images taken every 0.1 seconds from a video of water droplets, which are like droplets containing viruses, being sprayed from a sprayer. The droplets were sprayed between 0.85 and 0.95 seconds. The droplets were 10-100 μm in diameter when converted into a sphere, which is expected to be about the same size as droplets expelled from a human mouth. The trajectory of the droplets was determined based on the shutter speed, and it can be seen that after being sprayed with force, they fall down in a parabolic curve under the influence of gravity. The cutting speed per frame was 40 ms. It has been confirmed that if the time is shortened, the floating droplets can be visualized in a state closer to grains. This experiment was conducted in a general room with a temperature of 25°C and humidity of 60%.

[0044] FIG. 10 shows a video of gaseous H2O ejected from a nozzle in an environment with a temperature of 25°C and a humidity of 60%, taken from 0s to 1s, and cut out every 0.25s and arranged as still images. Here, the gaseous H2O was generated by bubbling N2 gas into water. The gas was stored in a sealed plastic bag and measured using a hygrometer, and it was confirmed that it had almost reached saturated water vapor (humidity 100%). The nozzle is located on the left side of the image, and gaseous H2O is ejected from there across the image from left to right, but no characteristics indicating this are observed in FIG. 10. It was confirmed that the method of the present invention can observe droplets and visualize the way the droplets spread without being affected by the humidity of the environment.

[0045] Example 2 The most effective method for visualizing breath and droplets using a camera with a wavelength of 3-5 μm is shown in Example 1, but a simpler method for achieving the same effect is introduced in Example 2. The pixel element 14 (infrared light sensing element) envisioned in this patent mainly requires cooling, but the need for cooling decreases the shorter the observation wavelength. By shortening the wavelength of interest, higher detection ability can be achieved at the same cooling temperature, and equivalent performance can be achieved at a higher cooling temperature, and in some cases cooling may not be necessary.

[0046] According to FIG. 2(a), the absorption of gas-phase H2O is generally small in the wavelength range of 3-5 μm, except for the wavelength range of 3.00-3.35 μm, where the absorption is somewhat high. Human breath contains 1-9% CO2, but the molecule that is equally or more stable is gas-phase H2O. The breath exhaled from the lungs can be considered to be saturated, that is, with a relative humidity of 100%. Therefore, the gas-phase H2O in Figure 2 can be said to give the absorption coefficient of the breath. The average absorption coefficient for wavelengths of 3.00-3.35 μm is 1.50×10 -4 cm -1 Although it is not particularly high, it is three orders of magnitude higher than 4.20-4.35μm. Therefore, it is possible to use this wavelength band to measure and visualize the airborne infection zone using H2O instead of CO2. The drawback is that it is affected by humidity, but since the H2O concentration in exhaled breath is stably maintained at the saturation concentration, visualization is possible except in special situations where the humidity of the environment reaches 100%. Even if the humidity of the environment is 100%, visualization is possible depending on the difference in gas temperature.

[0047] In this case, the absorption rate is 10 -2 The thickness of the absorber that gives this is 67 cm. As mentioned above, in reality, it is possible to distinguish absorption smaller than this, so the absorption rate is 10 -3 The thickness of the absorber that gives this is 6.7 cm. If the thickness of the breath is 6.7 cm, it is possible to visualize the extent to which the exhaled gas phase H2O is distributed. On the other hand, the absorption of liquid-phase H2O in this wavelength range is 1-2 orders of magnitude higher than that of 4.20-4.35 μm, making it easier to visualize droplets. In this way, by changing the bandpass filter of the device configuration used in Example 1 to one with a wavelength of 3.00-3.35 μm, it is possible to measure and visualize the airborne infection zone and the droplet infection zone with a less expensive camera. In this case, too, the spread of gaseous HO and liquid HO can be separated by image processing focusing on spatial frequency and brightness.

[0048] Example 3 A sneezing image was obtained under the same imaging conditions as in Example 1. However, the cutting speed per frame in the imaging conditions was changed from 40 ms to 20 ms. An example of the results is shown in Figure 11. In Figure 11, time differentiation is performed to enhance the contrast. The exhaled air and droplets that accompany a sneeze are clearly visible, and it can be seen that at the time of the image capture, the droplets fly farther than the exhaled air. On the other hand, it can also be seen that the exhaled air spreads widely. [Industrial Applicability]

[0049] The present invention makes it possible to indicate the range of virus dispersion when a virus is airborne or droplet-transmitted and to visualize the dispersion situation using a device that is portable and can be easily used in a real environment. Viruses such as the new coronavirus and influenza have a significant negative impact on society as a whole, including health, economy, and lifestyle. This invention makes it possible to grasp the situation when the virus spreads, and provide feedback to masks, exhaust, partitions, etc. to prevent the spread of the virus. Therefore, it is believed that the present invention will have a large impact on society and will also have a large influence on industry. [Explanation of symbols]

[0050] 1: H2O absorption band 11: Infrared light 12: Imaging means (imaging lens) 13: Image sensor 14: Pixel element (infrared light sensing element) 15a: Bandpass filter 15b: Bandpass filter 101: Camera 102: Camera 103: Camera 51: Camera 52: Image processing means 201: Virus dispersion measuring device

Claims

1. an imaging optical system for infrared light having a wavelength of 3 μm or more and 5 μm or less; An image sensor is used in which pixel elements each made of an infrared light sensing element having a photoelectric conversion layer for converting the infrared light into an electric signal are arranged in a matrix form, The infrared light is imaged onto the image sensor via the imaging optical system; A method for measuring a virus dispersion range, in which a range in which a grayscale image is obtained by the imaging, which is caused by light absorption by gas phase CO 2 and liquid phase H 2 O in the observed atmospheric environment, is determined to be a virus dispersion range.

2. 2. A method for measuring the range of virus dispersion according to claim 1, wherein the wavelength of the infrared light is 4.15 μm or more and 4.40 μm or less.

3. 2. A method for measuring the range of virus dispersion according to claim 1, wherein the wavelength of the infrared light is 4.20 μm or more and 4.35 μm or less.

4. The method for measuring the range of virus dispersion according to claim 1 , wherein the photoelectric conversion layer is made of InSb.

5. A bandpass filter that transmits only infrared light of the wavelength is placed in front of or behind the imaging optical system, The method for measuring the range of virus dispersion according to claim 1 , wherein the infrared light is focused on the image sensor via the bandpass filter.

6. 6. The method for measuring the range of virus dispersion according to claim 5, wherein the bandpass filter is cooled.

7. 7. The method for measuring the range of virus dispersion according to claim 6, wherein the cooling temperature is between 50K and 250K.

8. A virus dispersion range measurement method described in any one of claims 1 to 7, which separately indicates the range affected by airborne infection and the range affected by droplet infection using the spatial frequency distribution of the grayscale image acquired by the image sensor.

9. A method for measuring the range of virus dispersion described in any one of claims 1 to 7, which acquires brightness information of each pixel of the image sensor, extracts pixels that show a brightness outside a predetermined brightness range, and displays the area of ​​the image occupied by the pixels outside the brightness range as the range affected by droplet infection.

10. an imaging optical system for infrared light having a wavelength of 3 μm or more and 5 μm or less; An image sensor is used in which pixel elements each made of an infrared light sensing element having a photoelectric conversion layer for converting the infrared light into an electric signal are arranged in a matrix form, The infrared light is imaged onto the image sensor via the imaging optical system; Obtaining a video of a grayscale image due to the imaging caused by light absorption by gas phase CO 2 and liquid phase H 2 O in the observed atmospheric environment; A virus dispersion visualization method for visualizing the change over time in the range of the grayscale image as a change in the virus dispersion range.

11. The virus scattering visualization method according to claim 10, wherein the wavelength of the infrared light is 4.15 μm or more and 4.40 μm or less.

12. The virus scattering visualization method according to claim 10, wherein the wavelength of the infrared light is 4.20 μm or more and 4.35 μm or less.

13. The virus dispersion visualization method according to claim 10 , wherein the photoelectric conversion layer is made of InSb.

14. A bandpass filter that transmits only infrared light of the wavelength is placed in front of or behind the imaging optical system, The virus scattering visualization method according to claim 10 , wherein the infrared light is focused onto the image sensor via the bandpass filter.

15. A virus dispersion visualization method described in any one of claims 10 to 14, which uses the spatial frequency distribution of the grayscale image acquired by the image sensor to separately visualize the range affected by airborne infection and the range affected by droplet infection.

16. 15. A virus dispersion visualization method according to any one of claims 10 to 14, further comprising acquiring brightness information for each pixel of the image sensor, extracting pixels that exhibit a brightness outside a predetermined brightness range, and visualizing the dispersion status of droplets using the distribution of the pixels that are outside the brightness range.

17. A virus dispersion visualization method described in any one of claims 10 to 14, which acquires brightness information of each pixel of the image sensor, extracts pixels that show a brightness outside a predetermined brightness range, and visualizes the diffusion status of droplets using the temporal trajectory of the pixels outside the brightness range.

18. A camera and an image processing means are provided, The camera includes an imaging optical system for infrared light having a wavelength of 3 μm or more and 5 μm or less; a pixel element including an infrared light sensing element having a photoelectric conversion layer for converting the infrared light into an electric signal, the pixel element having an image sensor arranged in a matrix; The image processing means calculates the spatial frequency distribution of the grayscale image caused by the light absorption of gas phase CO2 and liquid phase H2O acquired by the image sensor, and / or acquires brightness information caused by the light absorption of gas phase CO2 and liquid phase H2O at each pixel of the image sensor, extracts pixels that show a brightness outside a predetermined brightness range, and calculates the temporal trajectory of the pixels outside the brightness range.

19. The virus scattering visualization device according to claim 18, wherein the wavelength of the infrared light is 4.15 μm or more and 4.40 μm or less.

20. The virus scattering visualization device according to claim 18, wherein the wavelength of the infrared light is 4.20 μm or more and 4.35 μm or less.

21. 21. The virus scattering visualization device according to claim 18, wherein the photoelectric conversion layer is made of InSb.

22. A bandpass filter that transmits only infrared light of the wavelength is placed in front of or behind the imaging optical system, 22. A virus scattering visualization device according to claim 18, wherein the infrared light is focused onto the image sensor via the bandpass filter.

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