JP2025101014A - Automatic blood sampling device and automatic blood sampling method - Google Patents

Abstract

【assignment】
To provide an automatic blood sampling device and an automatic blood sampling method capable of calculating a more accurate puncture suitability taking into consideration not only the clarity of blood vessels but also the depth by presenting a blood sampling site such as a finger or an arm.
[Solution]
The automatic blood sampling device 1, which collects blood by inserting a needle into a biological part 115 including a finger or an arm, comprises a light receiving unit that receives light in a wavelength range that can penetrate into the living body up to the maximum depth of a blood vessel included in the puncturing target range and light in a wavelength range that can penetrate only to near the surface, an image acquisition unit 106 that acquires measurement images of the backscattered light in each wavelength range, an emphasis observation unit that selectively emphasizes and observes blood vessels that exist between the surface layer and the maximum depth based on the difference between the measurement images in each wavelength range, a puncturing suitability calculation unit that calculates an index value indicating whether or not the blood vessel is suitable for puncturing from the obtained characteristics of blood vessel darkness and/or thickness as a puncturing suitability, and a puncturing suitability determination unit 11 that determines whether or not the puncturing is suitable based on the puncturing suitability.
[Selected Figure] Figure 1

Description

The present invention relates to a method and device for automating blood sampling from a living body using a machine, and in particular to an automatic blood sampling device and automatic blood sampling method that automatically determines a suitable needle insertion position to obtain a sufficient amount of blood.

Blood tests have become essential in the medical field as they provide basic information for diagnosing various diseases. They are also expected to be used for early diagnosis of disease signs in order to curb ever-increasing medical costs, and the demand for blood tests is expected to continue to increase in the future. As this demand increases, there are concerns about the increased burden on medical professionals who collect blood, and automatic blood collection devices that mechanize blood collection with as little manual effort as possible have been attracting attention in recent years. In particular, there is a demand for small, space-saving blood collection devices that can be placed without taking up space in the limited space available at medical facilities.

A conventional example of this type of automatic blood sampling device is the device described in Patent Document 1. In this device, when a fingertip is presented at a specific position on the device, a needle automatically moves to puncture the fingertip, creating a small wound, and blood is collected by being collected in a collection container. The device is made smaller by using the fingertip as the blood sampling target site. However, there are parts of the fingertip that are suitable for blood sampling and parts that are not. The above device does not perform such suitability judgment, and only discloses that the needle is mechanically pierced at a fixed position. Therefore, there is a possibility that a sufficient amount of blood may not be collected due to individual differences in the finger and changes in the posture and position of the presented finger. When blood is collected from the arm by a technique performed in the medical field, it is common for doctors and nurses to look for a thick vein that can be visually confirmed and puncture it. Although it is difficult to see the veins on the fingertip with the naked eye as much as on the arm, it is thought that the amount of blood collected can be stabilized by visualizing the veins in some way and targeting similarly thick veins. Therefore, the device described in Patent Document 2 discloses a method of taking an image of the fingertip using a near-infrared camera that can see through blood vessels, identifying the blood vessels from the captured image through image analysis, and determining the clearest point on the blood vessel where blood is assumed to be most locally concentrated. This makes it possible to select a location where a large amount of blood can be collected, and then puncture and collect blood, just as if a doctor or nurse were visually inspecting the area.

As an approach to improving the amount of blood collected, there have been studies that focus not only on the clarity of blood vessels, but also on the depth at which the blood vessels exist. Because blood vessels run three-dimensionally within the biological tissue under the skin, their depth varies depending on the location. When collecting blood, if the needle does not accurately reach the blood vessel, it is natural that a sufficient amount of blood cannot be collected. To address this issue, for example, Patent Document 3 discloses a method of measuring the depth of the blood vessel through stereoscopic vision using two cameras, and controlling the puncture so that the needle reaches the blood vessel in accordance with the measurement data. This makes it possible to reliably collect blood by targeting the blood vessel.

Patent No. 6994910 JP 2023-049080 A Japanese Patent Application Publication No. 8-168477

The above prior art is based on the premise that the site and conditions for blood sampling are accepted as presented and the best possible blood sampling is performed within those conditions. However, if the conditions are unsuitable for blood sampling, it may be more desirable to take measures such as not sampling at all or changing the site from which blood is sampled. In particular, when sampling from the fingertips, since there are multiple fingers, even if one finger is unsuitable, another finger may be more suitable.

The automatic blood sampling device described in Patent Document 2 also calculates a suitability index (hereinafter referred to as puncture suitability) based on the clarity of the blood vessel, specifically the curvature rate described later, based on image analysis for the point to be punctured, making it possible to quantitatively determine whether the point is suitable for puncturing. However, simply focusing on image features such as the clarity of the blood vessel may not provide a correlation with the amount of blood collected due to factors other than those that appear as features in the image. It is necessary to be able to calculate the puncture suitability in a form that removes factors that affect blood collection. Here, one of the above-mentioned influencing factors is that even if the clarity of the blood vessel is sufficient, the blood vessel may be located deep. Even if the blood vessel is located deep, if the clarity is more pronounced than the depth, the puncture suitability on that blood vessel will show a high value. However, in reality, blood collection itself is difficult because the needle is difficult to reach, and the amount of blood collected is not as much as expected from the clarity of the blood vessel on the image. Another reason is that the S/N ratio of the captured image may decrease due to the influence of the surrounding environment at the time of image capture, especially external light, and the original clarity of the blood vessel may not be accurately reflected in the image. For example, if ambient light is reflected on the imaging surface, such as the fingertip, the signal-to-noise ratio of blood vessels will decrease relatively. If the puncture suitability is calculated while leaving the deterioration of image quality due to such environmental factors unchanged, a reversal will occur, such as a low puncture suitability but a large amount of blood being collected. Thus, in order to obtain a high correlation between the puncture suitability and the amount of blood collected, it is necessary to make a comprehensive judgment that takes into account information other than that which has been focused on so far.

As for the depth of blood vessels, as described above, in the automatic blood collection device described in Patent Document 3, a method is disclosed in which the needle can be reliably reached to a certain depth of the blood vessel by controlling the needle depth direction. However, depending on the blood collection method, the needle cannot necessarily reach a certain depth of the blood vessel. In particular, in the case of the lancet blood collection method disclosed in Patent Document 1, in which a needle is used to make a small wound on the fingertip and blood that bleeds from the wound is collected, a needle that can only penetrate to a shallow part of about 2 mm is often used. In addition, using a needle that can reach deep and monitoring and controlling the needle's reach depth in real time during puncturing requires fine control of the needle and highly accurate measurement, which complicates the device mechanism and creates problems in terms of cost and maintainability as a blood collection device. Therefore, at the stage of selecting a blood vessel to be punctured, it is desirable to be able to determine that a medium-sized and thick blood vessel in a shallow layer that the needle can easily reach has a higher puncturing suitability than a thicker and thicker blood vessel in a deep layer that the needle cannot easily reach. For this reason, a measurement and calculation method that gives priority to blood vessels in the shallow layer is required when calculating the puncturing suitability.

Regarding the other aspect, image quality, a prior evaluation of whether the quality of the captured image itself is sufficient prior to the calculation of the puncture suitability can be performed to prevent erroneous calculation of the puncture suitability due to low image quality and to correct the puncture suitability to a level commensurate with the deterioration in quality. Therefore, a method is required that can detect deterioration in image quality that may affect the calculation of the puncture suitability and quantitatively evaluate the degree of that deterioration.

Therefore, the present invention provides an automatic blood sampling device and an automatic blood sampling method that can calculate a more accurate puncture suitability by taking into account the depth as well as the clarity of the blood vessels, by simply presenting the blood sampling site, such as a finger or arm.

In order to solve the above problems, the automatic blood sampling device of the present invention is an automatic blood sampling device that collects blood by inserting a needle into a body part including a finger or an arm, and is characterized by comprising: a light receiving unit that receives light in a wavelength range that can penetrate into the body to the maximum depth of the blood vessels included in the puncture target area and light in a wavelength range that can only penetrate to near the surface; an image acquiring unit that acquires measurement images of the backscattered light in each wavelength range; an emphasis observation unit that selectively emphasizes and observes blood vessels that exist between the near the surface and the maximum depth based on the difference between the measurement images in each wavelength range; a puncture suitability calculation unit that calculates an index value of suitability for puncturing from the obtained characteristics of the blood vessel thickness and/or thickness as a puncture suitability; and a puncture suitability judgment unit that judges suitability for puncturing based on the puncture suitability.

The automatic blood sampling method according to the present invention is an automatic blood sampling method for sampling blood by inserting a needle into a body part including a finger or an arm, and is characterized by having a light receiving step in which the light receiving unit receives light in a wavelength range capable of penetrating the body to the maximum depth of blood vessels included in the puncture target range and light in a wavelength range capable of penetrating only to the vicinity of the surface layer, an image acquiring step in which the image acquiring unit acquires measurement images of backscattered light in each wavelength range, an emphasis observing step in which the emphasis observing unit selectively emphasizes and observes blood vessels present between the vicinity of the surface layer and the maximum depth based on the difference between the measurement images in each wavelength range, a suitability calculating step in which the puncturing suitability calculating unit calculates an index value indicating whether or not puncturing is suitable from the obtained characteristics of the blood vessel thickness and/or width as the puncturing suitability, and a puncturing suitability determining step in which the puncturing suitability determining unit determines whether or not puncturing is suitable based on the puncturing suitability.

According to the present invention, it is possible to provide an automatic blood sampling device and an automatic blood sampling method that can calculate a more accurate puncture suitability by taking into account not only the clarity of the blood vessels but also the depth by simply presenting the blood sampling site such as a finger or arm.
Problems, configurations and effects other than those described above will become apparent from the following description of the embodiments.

1 is a configuration diagram of an automatic blood sampling device according to a first embodiment of the present invention. FIG. 2 is a functional block diagram of a calculation unit shown in FIG. 1 . FIG. 2 is a top view of the drive unit shown in FIG. 1 . 1 is a diagram showing an outline of a method for selectively measuring blood vessels in a shallow layer using an automatic blood sampling device according to a first embodiment of the present invention. FIG. 4 is a diagram showing an example of sensitivity characteristics of each RGB wavelength range. FIG. 13 is a diagram showing an example of a difference image when a color camera is placed directly under a finger. 4 is a flowchart showing a process flow of the automatic blood sampling device according to the first embodiment of the present invention. FIG. 11 is a schematic explanatory diagram of a method for automatically adjusting an α value. FIG. 11 is a functional block diagram of a calculation unit constituting an automatic blood sampling device according to a second embodiment of the present invention. 10 is a flowchart showing a processing flow for performing image quality evaluation. FIG. 13 is a diagram showing an example of puncture point selection. FIG. 11 is a functional block diagram of a calculation unit constituting an automatic blood sampling device according to a third embodiment of the present invention. FIG. 13 is a schematic explanatory diagram of the processing of the continuity evaluation unit 19 and the reliability calibration unit 20 shown in FIG. 12 .

The following describes an embodiment of the present invention with reference to the drawings.

Fig. 1 is a configuration diagram of an automatic blood sampling device according to a first embodiment of the present invention, and is a schematic diagram of a hardware configuration. As shown in Fig. 1, a calculation unit 101 built into the automatic blood sampling device 1 is further composed of a CPU 102, a memory 103, an auxiliary storage 104, and an interface (I/F) 105, which are interconnected by an internal bus. These may be interconnected by a dedicated bus for the purpose of increasing speed, etc.
The CPU 102 is a calculation device that executes programs. The CPU 102 also executes the calculation process of the puncture suitability from an image and the reliability evaluation described below. The memory 103 stores the processing program itself and data necessary for processing. Data that is to be permanently stored is written to and read from a recording medium such as a flash memory or a hard disk shown as an auxiliary memory 104.

The interface (I/F) 105 connects the calculation unit 101 to various other functional blocks and is used to exchange data. For example, when connected to the communication unit 109, the calculation unit 101 can perform various types of communication with the outside. The communication unit 109 makes it possible to share some or all of the processing associated with blood collection with an external device, i.e., a host calculation device, and to link with various services on the cloud.

A functional block for automatically collecting blood is connected to the calculation unit 101 via an interface (I/F) 105. The image input unit 106 is connected to a color camera 112, captures an image of a body part 115 (a finger is shown here as an example) from which blood is to be collected, and sends the image data to the calculation unit 101. The image input unit 106 has a function of converting the output signal of the color camera 112 into a format that is easy for the calculation unit 101 to handle, but the color camera 112 may have an equivalent function built in, in which case it functions simply as a data transmission relay. The captured image is stored in the memory 103, and the CPU 102 processes it. At this time, two long-wavelength light sources 110 and a short-wavelength light source 111 connected to the light source control unit 108 irradiate light onto the finger, which is the body part 115, from the same side as the color camera 112, and the output and balance of the long-wavelength light source 110 and the short-wavelength light source 111 are feedback-controlled by a program executed by the CPU 102 so that the blood vessel pattern is most clearly visible in the captured image. The output adjustment of the long wavelength light source 110 and the short wavelength light source 111 is performed by changing the power supply level by PWM (Pulse Width Modulation) control or the like according to the set value from the CPU 102. The long wavelength light source 110 and the short wavelength light source 111 are light sources in the long wavelength range and the short wavelength range, respectively, and LEDs (Light Emitting Diodes) with high degree of freedom in wavelength selection are suitable as components to be used. However, LEDs generally have strong directivity, and in the case of a reflected light shooting method in which light is irradiated from the same side as the color camera 112 as shown in FIG. 1, only a part of the irradiation target tends to be irradiated with too strong light. Therefore, it is better to attach a diffuser (diffusion plate) 113 to the long wavelength light source 110 and the short wavelength light source 111 so that the irradiation target can be evenly illuminated over a wide area to capture an image with less uneven brightness. In addition, some of the light emitted from the long wavelength light source 110 and the short wavelength light source 111 does not penetrate into the inside of the finger, which is the biological part 115, but is directly reflected (specularly reflected) on the skin surface and reaches the color camera 112, which may cause noise during shooting and deteriorate the image quality. Therefore, a polarizing plate 114 is further added to the long wavelength light source 110 and the short wavelength light source 111, and a similar polarizing plate 114 is installed on the color camera 112 side so as to shift the phase from the light source side. The light emitted from the long wavelength light source 110 and the short wavelength light source 111 reaches the finger, which is the biological part 115, with the phase limited by the polarizing plate 114, but while the light specularly reflected on the surface of the finger does not change in phase, the light that penetrates into the inside of the finger and returns by backscattering has a disturbed phase. Therefore, the polarizing plate 114 attached to the color camera 112 weakens the specularly reflected light, and the backscattered light reflecting the blood vessels is transmitted as it is. This enables blood vessel imaging with reduced specular reflection. The captured image thus obtained is analyzed by the CPU 102, and after a blood vessel pattern enhancement process, the degree of puncturing suitability is calculated and the reliability is evaluated. Then, the most suitable point in the image is selected, and when it is decided to puncture at that point, the coordinate value of the puncturing point is sent to the mechanism control unit 107, which controls the driving unit 116 to move the puncturing needle 117 to the position of the finger, which is the corresponding actual living body part 115, and puncture is performed. Prior to this, calibration is performed in advance so that the coordinates of any point of the finger shown on the captured image coincide with the actual point of the finger to be punctured by the puncturing needle 117, and the correspondence is stored. When puncturing is performed, the puncturing needle 117 moves away from the finger, and the blood collection tube 118 receives the bleeding blood, and blood collection is completed by waiting until a specified volume is obtained. It is also possible to use a thin tubular needle similar to an injection needle for the puncture needle 117, connect it to the blood collection tube 118 with a tube or the like, and leave it in the puncture state until a specified volume is accumulated in the blood collection tube 118.

2 is a functional block diagram of the calculation unit shown in FIG. 2. As shown in FIG. 2, the calculation unit 101 has an emphasis observation unit 11, a puncture suitability calculation unit 12, a puncture suitability determination unit 13, a puncture position selection unit 14, a blood vessel evaluation unit 15, a memory 103, an auxiliary storage 104, and an interface (I/F) 105, which are connected to each other via an internal bus. Here, the emphasis observation unit 11, the puncture suitability calculation unit 12, the puncture suitability determination unit 13, the puncture position selection unit 14, and the blood vessel evaluation unit 15 are realized by the CPU 102 shown in FIG. 1 and a memory 103 storing various programs. The emphasis observation unit 11 selectively emphasizes and observes blood vessels present between the surface layer and the maximum depth based on the difference between the measured images of backscattered light of a wavelength range that can penetrate into the living body to the maximum depth of the blood vessels included in the puncture target range and a wavelength range that can penetrate only to the surface layer via the image input unit 106, which is an image acquisition unit. The puncturing suitability calculation unit 12 calculates an index value indicating whether or not puncturing is suitable from the obtained characteristics of the blood vessel thickness and/or width as puncturing suitability. The puncturing suitability determination unit 13 determines whether or not puncturing is suitable based on the calculated puncturing suitability. The puncturing suitability determination unit 13 may be configured to obtain a correlation between the puncturing suitability and the amount of blood to be collected by a pre-analysis of data, and to collect blood only when the puncturing suitability is such that a blood collection amount equal to or greater than a predetermined standard can be expected. The puncturing position selection unit 14 selects the most suitable position for puncturing within the target living body part according to the level of the puncturing suitability.
Furthermore, as shown in FIG. 2, the vascular evaluation unit 15 is designed so that the puncture suitability for each point on the image is such that the more the point is located on a blood vessel, the more pronounced the thickness and darkness of the blood vessel is, and the more shallow the blood vessel is, the higher or lower the value it indicates.

Figure 3 is a top view of the drive unit 116 shown in Figure 1. Here, the drive unit 116 is the same as the blood collection mechanism of the small blood collection device of Patent Document 1. Here, the drive unit 116 is composed of a turntable rotated by a motor or the like and a mechanism for pushing the puncture needle 117 from the turntable surface toward the finger, which is the biological part 115, and has two degrees of freedom: rotation and pushing. The puncture needle 117 and the blood collection tube 118 are arranged side by side on the same circumferential orbit on the turntable, and when the drive unit 116 rotates and the puncture needle 117 comes to rest directly under the finger, the puncture needle 117 is pushed out and the finger is punctured. After the puncture, the turntable rotates and the blood collection tube 118 comes to rest directly under the finger, and the bleeding blood is collected. With this drive system, blood collection can be achieved with just two degrees of freedom: rotation of the turntable and pushing out the puncture needle 117. Another advantage is that consumables that are used only once per blood collection, such as the puncture needle 117 and blood collection tube 118, can be easily managed together on the turntable surface. The simple structure is also advantageous in realizing a compact device. On the other hand, the range in which the puncture needle 117 can move is limited to a circular orbit.

Figure 4 is a diagram showing an outline of a method for selectively measuring blood vessels in a shallow layer using the automatic blood sampling device 1 according to this embodiment. In Figure 4, a visible light photographed image 400 shows an example of photographing when the color camera 112 is placed directly under the finger. The visible light photographed image 400 is a color image, and the fingertip, which is the biological part 115, is shown in the center in a state where the long wavelength light source 110 and the short wavelength light source 111 are simultaneously irradiated, and within the fingertip area, information on the fingertip surface such as a fingerprint and information on the blood vessel pattern, which is difficult to distinguish with the naked eye, are superimposed and observed.

In this embodiment, the visible light image 400, which is a color image, is first divided into a long wavelength component image 402 and a short wavelength component image 404. The long wavelength component image 402 is mainly composed of light irradiated from the long wavelength light source 110, penetrated into the finger, and returned as backscattered light, and the short wavelength component image 404 is mainly composed of light irradiated from the short wavelength light source 111 and similarly backscattered light. In general, in the color camera 112, filters of the three primary colors of RGB are arranged alternately in correspondence with each pixel of the image sensor according to a rule called the Bayer arrangement, so that the R component of RGB selectively transmits long wavelengths, the B component transmits short wavelengths, and the G component transmits intermediate wavelengths between them. This converts the intensity of each wavelength range into digital data as the brightness value of the pixel and reconstructs it as an image. This principle is utilized as it is to extract the component images of each captured wavelength range.

Figure 5 is a diagram showing an example of the sensitivity characteristics of each of the RGB wavelength ranges. As shown in Figure 5, there is overlap among the three wavelength ranges, but if we focus on the two wavelength ranges of R and B, they can be considered to be almost independent. In other words, the biological information obtained by irradiation with the long wavelength range light source 110 (Figure 1) is captured in the R component image, and the biological information obtained by irradiation with the short wavelength range light source 111 (Figure 1) is captured in the B component image, each with a high degree of independence.

Among the component images obtained in this way, the long wavelength component image 402 (Figure 4) is in the red visible light wavelength range of about 620 nm, and has the property of relatively emphasizing the vascular pattern compared to the short wavelength component image 404 (Figure 4). This is because the depth to which light incident from the skin can penetrate into biological tissue varies depending on the wavelength, and the longer the wavelength, the deeper it reaches. Since relatively thick blood vessels to be punctured are located in deeper layers, it is difficult to observe them without light of a long wavelength. However, if the wavelength is too long, it will reach too deep, and will clearly show blood vessels that the puncture needle 117 cannot easily reach. Specifically, light in the near infrared region is said to penetrate to a depth of about 5 mm, and will show blood vessels that are much deeper than the puncture depth of 2 mm used in the lancet blood collection method. On the other hand, the penetration depth of visible light is about 2 mm to 3 mm, and blood vessels that the needle cannot reach will not be shown, or will be shown faintly or unclearly, even if they are actually thick and thick. Since the density of blood vessels is an important parameter in calculating the puncture suitability, thin blood vessels have a low puncture suitability and are less likely to be selected as puncture points. Since the penetration depth of visible light varies depending on the wavelength, the maximum depth of the blood vessel to be punctured can be freely determined by appropriately selecting the wavelength of the long wavelength light source 110 (Figure 1).

The other short-wavelength component image 404 is in the blue visible light wavelength range of about 470 nm, and has the property of relatively emphasizing the skin surface patterns such as fingerprints and wrinkles compared to the long-wavelength component image 402 (Figure 4). This is because light in the short-wavelength range does not penetrate deep layers and returns as backscattered light from the epidermis to the upper dermis, and is less susceptible to absorption by blood vessels inside the body. Here, the skin surface patterns are also reflected in the long-wavelength component image 402 (Figure 4), and if you pay attention to observing the blood vessels, you can say that they are buried in noise and have low contrast. Therefore, by subtracting the short-wavelength component image 404 (Figure 4) from the long-wavelength component image 402 (Figure 4), a difference image 406 (Figure 4) in which only the blood vessels are emphasized is obtained. This difference image (blood vessel image) 406 is adjusted so that only the superficial blood vessels are darkened, and is suitable as a base image for calculating the puncture suitability. The subsequent calculation process for the puncture suitability can be carried out essentially according to the procedure described in Patent Document 2.

Figure 6 is a diagram showing an example of a difference image 406 when the color camera 112 is placed directly under the finger. As shown in Figure 6, the fingertip, which is the biological part 115, is captured in the center of the difference image (blood vessel image) 406, and a blood vessel pattern 301 appears within the finger area. Points on this blood vessel pattern indicate areas with a relatively large amount of blood. In addition, blood vessels located deep within the area, which are determined by the wavelength set for the long-wavelength light source 110, are not clearly captured. The arc trajectory 300 in Figure 6 indicates the movable range of the puncture needle 117 in the structure shown in Figure 3. In this case, the optimal puncture point needs to be extracted from each point on this arc trajectory 300, and among them, the intersection point with the blood vessel estimated to have a large amount of blood is selected. In general, since the blood vessel pattern 301 is formed in a mesh-like shape, the arc trajectory 300 and the blood vessel pattern 301 often intersect at multiple points. Therefore, among these intersection points, the point with the highest puncture suitability is extracted, and the point where the puncture needle 117 should actually be inserted is determined. In the above example, the movable range of the puncture needle 117 is limited to the arc trajectory 300, but the method of realizing the movement of the puncture needle 117 is not limited to the mechanism shown in FIG. 3, and the movable range changes depending on the realization method. If the degree of freedom of the movement of the puncture needle 117 is increased, the movable range will also be wider, and it is possible to make it a band-like range with width rather than a line as described above. Of course, it does not have to be an arc shape, and it can be a straight line, a rectangle, or even a sector shape.

Figure 7 is a flowchart showing the process flow of the automatic blood sampling device 1 according to this embodiment. As shown in Figure 7, the process starts in step S501, and includes various processes to be executed and initialization of hardware. In step S502, the color camera 112 is started and starts taking images, and the taken images are taken into a memory area accessible to the CPU 102. In the following step S503, detection processing of a body part 115 such as a finger is executed. Specifically, image recognition is performed on the input image, and in particular, a large image change caused by a finger or arm being presented to the device is detected. In step S504, if the image change detected in step S503 is large, it is determined that a body part 115 has been presented, and the process proceeds to step S505. In step S504, preparation for blood sampling is started, and the user is notified as necessary. A dedicated sensor can also be used to detect a body part. In addition, as a method of notifying that the presentation of a body part has been detected, a method optimal for the application environment is selected from display of text or an icon on a display or the like, or a voice announcement or an alarm sound. On the other hand, if the image change is not significant, return to step S502 and repeat the subsequent steps.

In step S505, the long wavelength light source 110 and the short wavelength light source 111 (FIG. 1) for photographing are turned on, and the light source light quantity is changed until the finger, which is the biological part 115, is photographed with appropriate brightness. The brightness is judged to be appropriate by analyzing the image input each time, and based on whether the average brightness of the finger area is within a predetermined range and whether there are any extremely bright or dark parts locally (step S506). In the following step S507, the balance of the light quantity of the long wavelength light source 110 and the short wavelength light source 111 (FIG. 1) is confirmed. In the above outline explanation using FIG. 4, it was mentioned that the difference between the long wavelength component and the short wavelength component is taken, but if the balance is poor, the value when the difference is taken may be extremely small, and the blood vessel image extracted from it will be an image with low gradation and insufficient information. In that case, it is difficult to calculate the accuracy of the puncture suitability. Therefore, the light quantity of each of the light sources of the long wavelength light source 110 and the short wavelength light source 111 (FIG. 1) is controlled so that the amount of information of the difference image (blood vessel image) 406 is increased. The amount of information can be easily determined from the average luminance of the difference image (blood vessel image) 406. However, if too much priority is given to balance, one side may become too bright or too dark, so the light amount adjustment is performed by returning to step S502 and checking that both the light amount and balance are satisfied. At this time, if the target area of the image becomes saturated due to excessive light, no information can be obtained from that area, so priority is given to control so as not to have excessive light. Some color cameras 112 allow the color balance to be set using items such as color balance and color temperature, which are used for adjustment as necessary. Once light adjustment has been completed in this manner, the process proceeds to the extraction process of the optimal puncture point from step S509.

The first step S509 of the optimum puncture point extraction process is a process of separating the long and short wavelength components of the blood vessel. As described above, data is arranged so that R and B form one image from the data of each RGB component captured in the Bayer array, and each component image is formed as a long wavelength component and a short wavelength component. That is, a long wavelength component image 402 (FIG. 4) and a short wavelength component image 404 (FIG. 4) are formed. Some color cameras 112 output color information packed in a format such as RGB, YUV, or YCbCr for each pixel or for each set of adjacent pixels. In that case, the packed color information is converted to an RGB format that has a clear correspondence with the wavelength, and then the R component image and the B component image are separated and extracted. In the following process 510, the difference between the R component and B component images is taken. At this time, the luminance values of the component images are not simply subtracted from each other, but the following formula (1) is used.
diff = R - α×B ... (1)
Weighting is performed using a weight α so that the brightness of the image portion related to the skin surface contained in the long wavelength component image 402 and the short wavelength component image 404 differs between the component images, so that the skin surface image is offset by the difference by setting an appropriate α and adjusting the level. Since the value of α varies depending on the imaging conditions and the color of the presented finger, it is desirable to automatically adjust it appropriately according to the image to be captured.

FIG. 8 is a schematic diagram of an automatic adjustment method of the α value. The upper diagram of FIG. 8 illustrates the above formula (1). The lower diagram vertically shows three examples of difference images when the value of α in formula (1) is changed. The top image 410 is an image when α=0, and is completely the same as the long wavelength component image 402 as is clear from formula (1). The bottom image 414 is an image when α=1, which is R-B, that is, a simple difference between the long wavelength component image 402 and the short wavelength component image 404. Image 412 shows a state in which an appropriate α value m is found, the image components of the skin surface are removed, and only the image components of the blood vessels are emphasized. Here, the image components of the skin surface are never smooth and uniform, and the presence of a fingerprint or the like causes fine changes in brightness. If a cross-sectional profile of brightness is obtained for a part of the finger region of the difference image (α=0) 410, a profile curve 416 in which the brightness changes from high to low in the figure is obtained. On the other hand, when the profile of the same part is obtained for the difference image (α=1) 414, a profile curve 420 with high and low brightness in the figure is obtained, which is a profile curve that is inverted from the top to bottom of the profile curve 416. This inversion occurs because the value of α is too large, and the concave parts are filled in excessively to become convex parts. Conversely, when α is an appropriate value, the unevenness on the skin surface disappears, resulting in a smooth profile. Therefore, when the inflection rate is obtained for the concave or convex part of the profile, the optimal value m is the value of α when it becomes zero. Here, the inflection rate represents the rate of change in brightness at each point of the cross-sectional profile, and takes a maximum positive value at the bottom of the concave part where the brightness is lowest, and conversely takes a minimum negative value at the top of the convex part where the brightness is highest. The higher the inflection rate, the sharper the image change, and the clearer the fingerprint or blood vessels are. Here, the inflection rate C(x) at the point P(x) of the x coordinate on the profile is expressed as follows, when the width of the unevenness to be calculated is δ:
C(x)={P(x+δ,y)-P(x,y)}+{P(x-δ,y)-P(x,y)}...(2)
In this case, the change in the inflection rate from α=0 to α=1 can be roughly approximated by a linear line, and by calculating the inflection rate when α=0 and the inflection rate when α=1, it is easy to calculate α=m when the inflection rate becomes 0. However, since it is uncertain to use the change in the inflection rate at only one point as the α of the entire image, α is calculated from the change in the inflection rate for each point in the finger region in the same way, and the average is used as the α of the entire image. Since it is sufficient to obtain a statistically stable value, sampling may be appropriately thinned out as long as a sufficient number of samples can be obtained. In addition, when calculating the inflection rate, by setting δ in the above formula (2) to a value that easily captures the luminance change caused by the fingerprint, it is easy to obtain a result that meets the purpose of blood vessel enhancement. On the other hand, some luminance changes in the image are caused by the blood vessel pattern, and it is considered that the above formula (2) also picks up such luminance changes and reflects them in the inflection rate. Therefore, by not using the luminance changes in the vicinity of the blood vessels, the performance of removing the image components on the skin surface can be improved, and the effect of blood vessel enhancement can be improved. However, since it is difficult to extract the vascular pattern in the state of the difference image (α=0) 410 or the difference image (α=1) 414, α is first calculated from the inflection rate of all points in the finger region, and a temporary vascular enhancement image 412 is synthesized using the calculated α, and vascular extraction is performed from the vascular image. After the blood vessels are identified in the image in which the blood vessels are relatively clear, the difference image (α=0) 410 and the difference image (α=1) 414 are returned to and the inflection rate is calculated again for each point in the finger region excluding the blood vessel vicinity region, and α is derived from the average. This allows the enhancement observation unit 11 (FIG. 2) to obtain a less-noisy difference image (α=m) 412 (vascular enhancement image) from which information on the skin surface has been more appropriately removed, and it is expected that the accuracy of calculating the puncture suitability will be improved.

Now, let us return to the explanation of FIG. 7. In step S511, the puncture suitability calculation unit 12 (FIG. 2) calculates the puncture suitability of each point in the finger region for the difference image (α=m) 412 (vascular enhancement image) obtained by the enhancement observation unit 11 (FIG. 2). In calculating the puncture suitability, in this embodiment, the puncture suitability calculation unit 12 (FIG. 2) extracts a vascular pattern from the difference image (α=m) 412 (vascular enhancement image) and calculates the puncture suitability for each point on the center line based on the density and/or thickness and length of the blood vessel. This can be indexed by analyzing image features such as the brightness level at each point, the width between blood vessel boundaries, and the continuity of the blood vessel as a line. If it is only necessary to find the optimal puncture point on the puncture needle 117 trajectory shown in FIG. 6, the puncture suitability is calculated for only the points that intersect with the blood vessel on the trajectory. In step S512, the puncture suitability of each point thus obtained is compared, and the puncture suitability calculation unit 12 (FIG. 2) extracts the point that shows the maximum suitability within the movable range of the puncture needle 117.

In this embodiment, the purpose is not only to find the optimal puncture point in the captured image, but also to estimate the expected blood collection amount and determine whether or not puncture can be performed. For the data on which the blood collection amount is estimated, a sufficient number of subjects are recruited in advance to be statistically significant, and for the points where the blood is actually punctured, the puncture suitability is obtained from the image immediately before puncture, and a correspondence relationship with the blood collection amount obtained by puncturing is obtained in pairs. From this correspondence data, a regression equation between the puncture suitability and the blood collection amount is obtained, and the blood collection amount is estimated from the puncture suitability using this equation. At this time, if the correlation coefficient is not high enough, the estimated value will be uncertain, so the internal parameters in the calculation of the puncture suitability are adjusted to increase the correlation coefficient. For example, by changing the weighting of features such as the density, width, length, and depth of the blood vessels, the characteristics of the puncture suitability can also be flexibly changed, and a combination parameter of characteristics that is highly correlated with the blood collection amount is finally selected. If the puncturing suitability determination unit 13 determines that the amount of blood to be collected estimated from the puncturing suitability thus obtained does not reach a preset amount, it quantitatively determines whether to refrain from collecting blood or to change the target area to another area. If the puncturing suitability determination unit 13 determines that it is suitable for blood collection, in step S513, the puncturing position selection unit 14 controls the drive unit 116 (Figure 1) to move the needle to and puncture the actual body area corresponding to the optimal puncturing point position selected above. This starts blood collection, and ends when the required amount of blood is collected. Then, in step S514, the automatic blood collection device 1 is returned to its initial state, and is prepared for blood collection from the next user.

As described above, according to this embodiment, by calculating the puncture suitability based on an index that reflects the depth in addition to the thickness and density of the blood vessel, it becomes possible to determine the suitability of puncture with a higher correlation with the amount of blood to be collected.

In this embodiment, the long wavelength light source 110 and the short wavelength light source 111 are irradiated simultaneously, and component separation is performed from the color image. However, the present invention is not limited to simultaneous irradiation, and it is also possible to obtain two types of captured images by alternately irradiating the long wavelength light source 110 and the short wavelength light source 111, and use them as the long wavelength component image 402 and the short wavelength component image 404. In this case, since the overlap of the long and short wavelength regions does not occur in principle, more independent image analysis is possible. However, on the other hand, in the case of alternate irradiation, the target biological part 115 may move or fluctuate between two captures, and it is necessary to correct the fluctuation before using the two long wavelength component images 402 and the short wavelength component images 404. In addition, instead of using two light sources, the long wavelength light source 110 and the short wavelength light source 111, it is also possible to use a white light source that can irradiate light with a wider wavelength range. Only one light source is required, and conditions such as the spread of the light beam can be matched for long and short. However, if the wavelength range of the white light source is too wide in the long wavelength range, the penetration depth into the subcutaneous tissue will be large, which is contrary to the purpose of the present invention, which is to selectively measure only shallow blood vessels. Therefore, in the case of a white light source, the characteristics of the long wavelength range must be carefully examined. If the light flux conditions are to be uniform, it is possible to use a light source component that incorporates multiple light emitting elements of long and short wavelengths in the same package. Furthermore, a multi-wavelength light source that further increases the number of light emitting elements in the long wavelength range can be used. By making the emission wavelength in the long wavelength range variable according to the blood vessel depth to be measured, the optimal wavelength according to the depth that the puncture needle can reach can be selected.

The puncture suitability is calculated for each point on the image by the vascular evaluation unit 15, which is designed to show a higher or lower value the more prominent the thickness and darkness of the blood vessel and the shallower the blood vessel is, if that point is located on a blood vessel. Furthermore, a more stable and accurate calculation of the puncture suitability is performed by using the total output value of the vascular evaluation unit 15 for each point in the entire neighborhood centered on the point to be calculated. In calculating the total value of the neighborhood, the vascular evaluation unit output value is weighted by the distance from the center of the area, so that the more points with high vascular evaluation unit output values are concentrated near the center, the higher the suitability is.

As described above, according to this embodiment, it is possible to provide an automatic blood sampling device and an automatic blood sampling method that can calculate a more accurate puncture suitability by taking into account not only the clarity of the blood vessels but also the depth by simply presenting the blood sampling site such as a finger or arm.
Furthermore, according to this embodiment, it is possible to determine whether or not puncturing is appropriate with a higher correlation to the amount of blood to be collected.

9 is a functional block diagram of the calculation unit 101a constituting the automatic blood sampling device according to this embodiment. As shown in FIG. 9, the calculation unit 101a according to this embodiment differs from the above-mentioned embodiment 1 in that it further includes a reliability evaluation unit 16, a usage restriction unit 17, and a puncture suitability correction unit 18. In the following, the same components as those in embodiment 1 are given the same reference numerals, and duplicated explanations are omitted. In this embodiment, in order to obtain a puncture suitability that has a high correlation with the blood sampling volume, it is focused on the fact that one of the issues is to suppress the influence of image quality degradation. Therefore, before calculating the puncture suitability, a pre-evaluation of whether the quality of the captured image itself is sufficient can be performed to prevent erroneous calculation of the puncture suitability due to low image quality, and a measure can be taken to correct the puncture suitability to a level commensurate with the quality degradation. Such image quality evaluation is effective not only for the calculation of the puncture suitability based on the superficial blood vessel measurement using visible light described above, but also for the extraction of blood vessels using near-infrared light described in Patent Document 2.

As shown in FIG. 9, the calculation unit 101a constituting the automatic blood sampling device according to this embodiment further includes a reliability evaluation unit 16, a usage restriction unit 17, and a puncture suitability correction unit 18. Here, the reliability evaluation unit 16, the usage restriction unit 17, and the puncture suitability correction unit 18 are realized by the CPU 102 shown in FIG. 1 and the memory 103 storing various programs. The reliability evaluation unit 16 quantitatively determines the image quality of the blood vessel at the candidate puncture position in the captured blood vessel image as the reliability, using the brightness inflection rate, etc. The usage restriction unit 17 restricts the use of the puncture suitability as low reliability when the determined reliability is low. Furthermore, the puncture suitability correction unit 18 corrects the puncture suitability according to the reliability.

Figure 10 is a flowchart showing the process flow for image quality evaluation. In image quality evaluation, evaluation is performed on the original image as it was captured so that the fundamental factors are not buried by other image processing. In step S601, initialization processing for image quality evaluation processing is performed. Next, in step S602, the finger area is cut out, and in the following step S603, the vascular pattern is extracted. The reason for focusing on the vascular pattern is that the effect of image quality degradation is most easily seen in the vascular area, and blood vessels in areas with reduced image quality tend to lose clarity (sharpness). In addition, the vascular pattern is also extracted as described above in the calculation of the puncture suitability, but in this case, the vascular pattern can be extracted more stably by performing a smoothing process in advance or normalizing to suppress brightness unevenness before performing the extraction process. In particular, measurement of the vascular pattern using visible light tends to be noisy because it deals with a relatively small amount of difference, so the effect of suppressing noise by smoothing processing and emphasizing the vascular part is great. However, the blood vessel pattern thus obtained is suppressed not only by general noise but also by factors that reduce image quality specific to the captured image, making it difficult to correctly evaluate the sharpness. Therefore, it is necessary to go back to the original image and extract the blood vessel pattern separately from the blood vessel pattern extraction performed in the calculation of the puncture suitability. Then, the reliability evaluation unit 16 calculates the sharpness index value (contrast index value on the blood vessel) for each point on the blood vessel of the extracted original image (step S604). Here, the inflection rate of each point is used as the simplest index. The sharper the blood vessel, the steeper the luminance change in the blood vessel part, so the inflection rate also takes a large value. At this time, the original image as it is is somewhat noisy and rough as an image, and the inflection rate value may also differ greatly between adjacent points. Therefore, in the image quality evaluation, the sum of the inflection rates included in a certain range of areas near the target point is calculated, and this is used as the image quality evaluation value of the target point (step S605). In this embodiment, the sum of the curvatures included in a certain range of regions near the target point is used, but the maximum value, minimum value, median, etc. may be used depending on the tendency of the obtained image characteristics. In step S606, the obtained image quality evaluation value is sent to a higher-level execution program as the reliability of the target point, and finally a finalization process is performed. The higher-level program may be the program shown in the processing flow of FIG. 7 described in the above-mentioned embodiment 1, and can perform image quality evaluation when a candidate puncture point is selected (after step S512 in FIG. 7), and if the quality is low, it is possible to determine that the calculation result of the puncture suitability is also low in reliability and not to adopt it.

Figure 11 is a diagram showing an example of puncture point selection. Here, a case is shown in which the point most suitable for puncture is selected on the trajectory of the puncture needle 117. The puncture suitability is calculated for multiple points on the trajectory of the puncture needle 117 that intersect with blood vessels, but if the reliability of the point with the highest puncture suitability value is lower than a predetermined threshold value T, the point with the highest puncture suitability among the second and lower values, whose reliability indicates a value equal to or greater than the predetermined threshold value T, is selected as the puncture candidate point. This makes it possible to select a puncture candidate based on a highly reliable judgment result.

In addition, in the above image quality evaluation or reliability calculation, the focus was on the clarity of blood vessels, but a similar evaluation can also be performed by focusing on differences in the clarity of patterns such as fingerprints on the skin surface. In the case of the skin surface, for example, when light is deflected, changes in image features may occur, such as excessive emphasis on the unevenness of the surface. Therefore, it is possible to determine that image quality is low when there are many points with extremely high curvatures.

As described above, according to this embodiment, in addition to the effects of the first embodiment, it is possible to eliminate the disturbance of the puncturing suitability due to unreliable information, and to increase the correlation with the amount of collected blood.
Furthermore, it is possible to exclude points where the estimation of the amount of collected blood is unstable from the candidate puncturing points, and to preferentially select only points where the estimation is stable as the candidate puncturing points.

Figure 12 is a functional block diagram of the calculation unit 101b constituting the automatic blood sampling device according to this embodiment. As shown in Figure 12, the calculation unit 101b according to this embodiment differs from the above-mentioned embodiment 2 in that the reliability evaluation unit 16 has a continuity evaluation unit 19 and a reliability calibration unit 20. In the following, the same components as those in embodiment 2 are given the same reference numerals, and duplicated explanations are omitted. Here, the continuity evaluation unit 19 and the reliability calibration unit 20 are realized by the CPU 102 shown in Figure 1 and the memory 103 storing various programs. The continuity evaluation unit 19 evaluates the continuity of the blood vessel. When a sudden discontinuity due to noise, epidermal damage, etc. is confirmed, the reliability calibration unit 20 interpolates the discontinuity based on the continuity of the blood vessel to calibrate the reliability.

Figure 13 is a schematic diagram of the process of the continuity evaluation unit 19 and the reliability calibration unit 20 shown in Figure 12. When calculating the puncture suitability, sudden discontinuities due to epidermal damage may occur in the blood vessel part in the captured image. This will alter the image features around the relevant part regardless of information such as the original density, thickness, and depth of the blood vessel. Therefore, when calculating the puncture suitability, the continuity evaluation unit 19 checks the continuity of the blood vessel near the target candidate point, and if a discontinuity is confirmed in the middle of a blood vessel that is determined to have continuity, the reliability calibration unit 20 calculates an interpolation path for the discontinuous part based on the continuity of the blood vessel, and the value of the puncture suitability is also interpolated and estimated based on the puncture suitability on the blood vessels before and after the interpolated path. In addition, as for the method of judging the continuity, a line tracing process is performed for a certain section from the part where the blood vessel discontinuity occurred, a direction vector in that section is obtained, and when the direction vector is inverted and extrapolated from the discontinuous part as the starting point, it is evaluated whether it can be smoothly connected to the other discontinuous part. In this case, it is possible that the cause of the discontinuity is the three-dimensional movement of blood vessels under the skin, and that the discontinuity occurs simply because the blood vessels dive deep. In cases of the above causes, it is not necessarily appropriate to perform interpolation, and therefore interpolation of the puncture suitability should not be performed either. On the other hand, if it is based on such natural changes in depth, the brightness change caused by the discontinuity will not be sudden, but will tend to fade gradually and become invisible. Therefore, by focusing on the steepness of the brightness change in the discontinuous parts, interpolation is performed only in cases of abrupt changes.

As described above, according to this embodiment, even if a blood vessel is interrupted, the puncture suitability value that should be present can be compensated for from the continuity, and a puncture point that is expected to yield a sufficient amount of blood can be selected without fail.

The present invention is not limited to the above-described embodiments, but includes various modified examples. For example, the above-described embodiments have been described in detail to clearly explain the present invention, and the present invention is not necessarily limited to those having all of the configurations described. In addition, it is possible to replace part of the configuration of one embodiment with the configuration of another embodiment, and it is also possible to add the configuration of another embodiment to the configuration of one embodiment.

1... Automatic blood sampling device 11... Enhancement observation unit 12... Puncture suitability calculation unit 13... Puncture suitability determination unit 14... Puncture position selection unit 15... Blood vessel evaluation unit 16... Reliability evaluation unit 17... Usage restriction unit 18... Puncture suitability correction unit 19... Continuity evaluation unit 20... Reliability calibration unit 101, 101a, 101b... Calculation unit 102... CPU
103: Memory 104: Auxiliary storage 105: Interface (I/F)
106: Image input unit 107: Mechanism control unit 108: Light source control unit 109: Communication unit 110: Long wavelength range light source 111: Short wavelength range light source 112: Color camera 113: Diffuser (diffusion plate)
114...polarizing filter 115...biological part 116...drive unit 117...puncture needle 118...blood collection tube 300...needle movable range 301...blood vessel pattern 400...visible light photographed image 402...long wavelength component image 404...short wavelength component image 406...difference image 410...difference image (α=0)
412...Difference image (α=m)
414...Difference image (α=1)
416: Luminance cross-sectional profile of the difference image 410; 418: Luminance cross-sectional profile of the difference image 412; 420: Luminance cross-sectional profile of the difference image 414

Claims (12)

An automatic blood sampling device that samples blood by puncturing a body part including a finger or arm,
a light receiving unit that receives light in a wavelength range that can penetrate into the living body to the maximum depth of a blood vessel included in the puncture target area and light in a wavelength range that can only penetrate to the vicinity of the surface layer;
an image acquisition unit that acquires a measurement image of the backscattered light in each wavelength range;
an enhancement observation unit that selectively enhances and observes blood vessels that are present between the surface layer and the maximum depth based on the difference between the measurement images of the respective wavelength ranges;
a puncturing suitability calculation unit that calculates an index value indicating whether or not the blood vessel is suitable for puncturing based on the obtained blood vessel darkness and/or width characteristics as a puncturing suitability;
and a puncturing suitability determination unit that determines whether puncturing is appropriate based on the puncturing suitability. 2. The automatic blood sampling device according to claim 1,
An automatic blood sampling device characterized in that the light receiving unit simultaneously or alternately receives light in a wavelength range that can penetrate into the living body to the maximum depth of the blood vessels included in the puncture target area, and light in a wavelength range that can only penetrate to near the surface. 3. The automatic blood sampling device according to claim 2,
The automatic blood sampling device is characterized in that the puncture suitability determination unit determines the correlation between the puncture suitability and the amount of blood to be collected by prior analysis of data, and performs blood sampling only in cases where the puncture suitability is such that an amount of blood to be collected equal to or greater than a predetermined standard is expected. 4. The automatic blood sampling device according to claim 3,
a puncture position selection unit that selects a position that is most suitable for puncturing within a target biological site according to the degree of suitability for puncturing;
a drive unit which moves the puncture needle to the position selected by the puncture position selection unit and performs the puncture. 3. The automatic blood sampling device according to claim 2,
This automatic blood sampling device is characterized in that the puncture suitability is calculated for each point on the image by a vascular evaluation unit designed to show a higher or lower value the more the point is located on a blood vessel, the more noticeable the thickness and darkness of the blood vessel, and the more shallow the blood vessel is. 3. The automatic blood sampling device according to claim 2,
a reliability evaluation unit that quantitatively determines the reliability of an image quality of the blood vessel at the candidate puncture position in the captured blood vessel image based on a curvature of brightness;
a usage restriction unit that restricts usage of the puncture suitability as being of low reliability when the reliability is low;
and a puncture suitability correction unit that corrects the puncture suitability in accordance with the reliability. 7. The automatic blood sampling device according to claim 6,
The reliability evaluation unit includes a continuity evaluation unit that evaluates the continuity of blood vessels, and a reliability calibration unit that, when a sudden discontinuity due to noise or epidermal damage is confirmed, interpolates the discontinuity based on the continuity of blood vessels to calibrate the reliability. An automatic blood sampling method for sampling blood by puncturing a body part including a finger or an arm, comprising:
a light receiving step in which the light receiving unit receives light in a wavelength range capable of penetrating into the living body to the maximum depth of a blood vessel included in the puncture target area and light in a wavelength range capable of penetrating only to the vicinity of a surface layer;
an image acquiring step in which an image acquiring unit acquires a measurement image of the backscattered light in each wavelength range;
an enhancement observation step in which an enhancement observation unit selectively enhances and observes blood vessels present between the surface layer and the maximum depth based on a difference between the measurement images of the wavelength ranges;
a suitability calculation step of calculating an index value indicating whether or not puncturing is suitable based on the obtained characteristics of the blood vessel thickness and/or width, as a suitability for puncturing, by the puncturing suitability calculation unit;
a puncturing suitability determining step in which a puncturing suitability determining unit determines whether puncturing is appropriate based on the puncturing suitability. 9. The automatic blood sampling method according to claim 8,
The light receiving step is an automatic blood sampling method characterized in that the light receiving unit simultaneously or alternately receives light in a wavelength range that can penetrate into the living body to the maximum depth of the blood vessels included in the puncture target area, and light in a wavelength range that can only penetrate to near the surface. 10. The automatic blood sampling method according to claim 9,
An automatic blood sampling method characterized in that the puncture suitability determination unit determines the correlation between the puncture suitability and the amount of blood to be collected by prior analysis of data, and performs blood sampling only in cases where the puncture suitability is such that an amount of blood to be collected equal to or greater than a predetermined standard is expected. 10. The automatic blood sampling method according to claim 9,
a reliability evaluation unit quantitatively determining, as reliability, image quality of the blood vessel at the candidate puncture position in the captured blood vessel image based on a curvature of brightness;
a usage restriction unit restricting usage of the device when the reliability is low, as the puncture suitability is also low reliable;
and a puncturing suitability correcting unit correcting the puncturing suitability in accordance with the reliability. 10. The automatic blood sampling method according to claim 9,
A continuity assessment unit assesses the continuity of a blood vessel;
and when a sudden discontinuity due to noise or epidermal damage is confirmed, the reliability calibration unit calibrates the reliability by interpolating the discontinuity based on the continuity of the blood vessel.

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