Urine test device based on medical test

Abstract

The invention relates to the field of medical examination, in particular to a urine examination device based on medical examination, which comprises an automatic urine examination machine, a test tube conveying table is arranged below a sampling port of the automatic urine examination machine, and the test tube conveying table is used for conveying urine test tubes; a plurality of opposite light beam emitters and light beam receivers are arranged on the test tube conveying table, are positioned below a sampling opening of the automatic urine testing machine, and are respectively used for detecting the quantity of particles in each liquid layer of the urine test tube through a spectral effect; the system further comprises a controller, a BP neural network is arranged in the controller, and the BP neural network is used for inputting the amount of particles in each liquid layer of the urine test tube and outputting the residence time. By adopting the technical scheme provided by the invention, the retention time of the urine sample is fed back by detecting the quantity proportion of the particles in different liquid layers in the urine test tube, so that medical personnel are helped to screen out samples without reference significance.

Description

Technical Field

[0001] The present invention relates to the field of medical testing, and in particular to a urine testing device based on medical testing. Background Art

[0002] A urinalyzer is an automated instrument for measuring certain chemical components in urine. It is a crucial tool for automated urine testing in medical laboratories, offering advantages such as ease of operation and rapid speed. Under computer control, the instrument collects and analyzes the color information of various reagent blocks on a test strip, undergoes a series of signal conversions, and ultimately outputs the measured chemical component content in the urine. A urinalyzer generally consists of a test strip, mechanical system, optical system, circuit system, and input / output systems.

[0003] The results of routine urine tests are affected by a variety of factors, including poor urine cleanliness, incorrect urine collection method, incorrect urine collection time, and delayed urine testing. When urine is not promptly tested, its composition changes over time. For example, a urine sample left for one hour will show a higher white blood cell count, pH, and specific gravity. After two hours, the pH and specific gravity of the urine sample will also change, rendering the test results meaningless. Summary of the Invention

[0004] To solve the above problems, the present invention provides a urine testing device based on medical examination, which is used to feedback the retention time of urine samples by detecting the ratio of the amount of particles in different liquid layers in the urine test tube, helping medical personnel to screen out samples with no reference value.

[0005] To achieve the above-mentioned object, the technical solution of the present invention is as follows: a urine testing device based on medical examination, comprising an automatic urine testing machine, the automatic urine testing machine being used to sample and test urine from a urine test tube through a sampling port, a test tube conveying platform being provided below the sampling port of the automatic urine testing machine, the test tube conveying platform being used to convey urine test tubes;

[0006] The test tube conveyor is provided with a plurality of opposing light beam emitters and light beam receivers, both of which are located below the sampling port of the automatic urine testing machine. The light beam emitters and light beam receivers are respectively used to detect the amount of particles in each liquid layer of the urine test tube through spectral effects;

[0007] It also includes a controller, which has a BP neural network. The BP neural network is trained based on samples of different retention times and the proportion of the amount of particles in each liquid layer of the urine test tube. The BP neural network is used to input the amount of particles in each liquid layer of the urine test tube and output the retention time.

[0008] The above scheme has the following beneficial effects:

[0009] 1. The particle precipitation in urine, also known as urine sediment, refers to the solid components in urine observed under a microscope. It is usually composed of cells, crystals, casts, microorganisms, etc., and will gradually sink due to gravity, but at a slow speed. In 0-30 minutes, large particles begin to sink slowly, and most of the solids begin to precipitate in 1h-2h. Therefore, the residence time can be determined by using the change in particle concentration in each liquid layer caused by precipitation during the particle precipitation process. Conventional particles, such as urine sediment, are observed under a microscope to obtain urine detection information, but the automatic urine testing machine itself is able to complete the detection of urine information, so a light beam transmitter and a light beam receiver are used for spectral detection. According to the different material components in the spectral effect, they will absorb, scatter or emit light of a specific wavelength to determine the amount of particles in each liquid layer, and the residence time is determined based on the particle ratio.

[0010] 2. In this scheme, since there are many changes in the retention time, a BP neural network is used for training to obtain the mapping relationship between different parameter changes and the retention time, so as to more accurately feedback the retention time of each urine test tube to be tested.

[0011] 3. In this solution, after outputting the retention time, it can assist users in identifying invalid urine samples and reduce misjudgment of the patient's pathological condition.

[0012] Furthermore, a light shielding box is fixedly connected to the test tube conveying table, and the light beam transmitter and the light beam receiver are both located in the light shielding box. The light shielding box is respectively provided with openings for sampling and for urine test tubes to enter.

[0013] Beneficial effect: Natural light indoors and outdoors will interfere with the spectrum detection process, so a light-shielding box is used to reduce the interference of other light sources on the spectrum detection.

[0014] Furthermore, the BP neural network is also trained based on the total amount of particles in each liquid layer of the urine test tube of the sample. The BP neural network is used to establish a mapping relationship between the total amount of particles in each liquid layer of the urine test tube, the ratio of the amount of particles in each liquid layer of the urine test tube and the retention time.

[0015] Beneficial Effects: The ratio of particles within each liquid layer is also affected by the total number of particles. According to Stokes' law in fluid mechanics, the settling velocity of particles is directly proportional to particle size and density difference, and inversely proportional to the liquid viscosity. Therefore, a mapping relationship between the total number of particles within each liquid layer of a urine test tube, the ratio of particles within each liquid layer within the urine test tube, and the retention time is introduced to better reflect the retention time.

[0016] Furthermore, the BP neural network is trained based on the total amount of particles in each liquid layer of urine test tubes collected at different retention times under the same sample, the ratio of the amount of particles in each liquid layer of the urine test tube, and the urine test results. The BP neural network is used to output the deviation value of the urine test results caused by different retention times.

[0017] Beneficial effect: The test results of urine samples will be affected by the length of retention time. After obtaining the retention time through the ratio of the amount of particles in each liquid layer of the urine test tube, the deviation of the current urine sample test result can be calculated based on the retention time, thereby better evaluating the test results.

[0018] Furthermore, the controller is used to obtain the test results of the automatic urine testing machine, and invert the test results when the urine test tube is not retained according to the retention time and deviation value output by the BP neural network.

[0019] Beneficial effect: When the deviation value is known, the test result can be corrected using the deviation value, thereby obtaining test data that is closer to a fresh urine sample.

[0020] Furthermore, the controller signal is connected to an alarm, and the controller is used to control the alarm to sound an alarm when the retention time output by the BP neural network is greater than 2h.

[0021] Beneficial effect: When the output retention time is greater than 2 hours, the parameters of the urine sample have drifted significantly, and the detection value is relatively small. The alarm can be controlled to sound an alarm to remind medical staff to pay attention to the current test sample.

[0022] Furthermore, the controller is also used to obtain the current time node. A standard collection period is preset in the controller. The controller obtains the urine collection time by subtracting the retention time output by the BP neural network from the current time node. When the urine collection time exceeds the standard collection period, the control alarm sounds an alarm.

[0023] Benefits: Morning urine is the best sample, so in most cases, patients are required to collect urine in the early morning. The controller can deduce the urine collection time by subtracting the retention time from the current time, thereby determining whether the patient collected urine within the specified time.

[0024] Furthermore, the controller is preset with a standard particle amount range value. When the particle amount detected by the light beam receiver exceeds the standard particle amount range value, the controller controls the alarm to sound an alarm.

[0025] Beneficial Effects: Most urine test tubes are labeled, and different hospitals may place labels in different locations. Consequently, the beam from the beam transmitter could potentially hit the label, resulting in erroneous data. Therefore, a standard particle count range is set. When the beam hits the label, the result exceeds the standard particle count range, and the controller controls the alarm to sound an alarm to alert medical staff.

[0026] Furthermore, the number of the light beam emitters and the number of light beam receivers are both at least 2, and the light beam emitters and the light beam receivers are both slidably connected to the light shielding box.

[0027] Beneficial effects: The light beam emitter and the light beam receiver detect particles in at least two liquid layers for comparison. In addition, since the label cannot completely cover the urine test tube, the user can adjust the position by sliding the light beam emitter and the light beam receiver to avoid the light beam hitting the label.

[0028] Furthermore, the alarm is one or more of a buzzer, an LED light, and a vibration motor.

[0029] Beneficial effects: The alarm can sound a buzzer, flash an LED light, and vibrate a vibration motor to give an alarm.

[0030] Additional aspects and advantages of the present invention will be set forth in part in the description which follows and, in part, will be obvious from the description which follows, or may be learned by practice of the present invention. BRIEF DESCRIPTION OF THE DRAWINGS

[0031] Figure 1 This is an axonometric diagram of an embodiment of a urine testing device based on medical testing according to the present invention;

[0032] Figure 2 A schematic side view of an embodiment of a urine testing device for medical testing according to the present invention;

[0033] Figure 3 for Figure 2 Schematic cross-sectional view of the light shielding box in part A.

[0034] The reference numerals in the drawings of the specification include: 1. automatic urine testing machine; 2. test tube conveyor; 3. light beam transmitter; 4. light beam receiver; 5. light shielding box; 6. alarm; 7. urine test tube. DETAILED DESCRIPTION

[0035] The technical solution of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the embodiments described are only some embodiments of the present invention, not all embodiments. All other embodiments obtained by ordinary technicians in this field based on the embodiments of the present invention without making any creative efforts shall fall within the scope of protection of the present invention.

[0036] In the description of the present invention, it should be noted that the terms "center," "upper," "lower," "left," "right," "vertical," "horizontal," "inner," and "outer," etc., indicating orientations or positional relationships, are based on the orientations or positional relationships shown in the accompanying drawings and are intended solely to facilitate and simplify the description of the present invention. They are not intended to indicate or imply that the devices or components referred to must have, be constructed, or operate in a specific orientation, and therefore should not be construed as limitations on the present invention. Furthermore, the terms "first," "second," and "third" are used for descriptive purposes only and should not be construed as indicating or implying relative importance.

[0037] In the description of the present invention, it should be noted that, unless otherwise expressly specified or limited, the terms "mounted," "connected," and "connected" should be understood in a broad sense. For example, they may refer to fixed, detachable, or integral connections; mechanical or electrical connections; direct or indirect connections through an intermediate medium; and internal communication between two components. Those skilled in the art will understand the specific meanings of the above terms in the present invention based on the specific circumstances.

[0038] The following is further described in detail through specific implementation methods:

[0039] Example 1:

[0040] As attached Figure 1-Figure 3 As shown: A urine testing device based on medical examination includes an automatic urine testing machine 1, which is used to sample and test urine from a urine test tube 7 through a sampling port. A test tube conveying platform 2 is provided below the sampling port of the automatic urine testing machine 1, and the test tube conveying platform 2 is used to convey the urine test tube 7.

[0041] The test tube transfer platform 2 is equipped with a plurality of opposing light beam emitters 3 and light beam receivers 4. Both light beam emitters 3 and light beam receivers 4 are located below the sampling port of the automatic urine testing machine 1. The light beam emitters 3 and light beam receivers 4 are respectively used to detect the amount of particles in each liquid layer of the urine test tube 7 through spectral effects. A light shielding box 5 is bolted to the test tube transfer platform 2. Both light beam emitters 3 and light beam receivers 4 are located within the light shielding box 5. The light shielding box 5 has openings for sampling from the sampling port and for entering the urine test tube 7. The number of light beam emitters 3 and light beam receivers 4 is at least two, and both light beam emitters 3 and light beam receivers 4 are slidably connected to the light shielding box 5.

[0042] The system also includes a controller, which includes a BP neural network. The BP neural network is trained based on samples of different retention times, the total number of particles in each liquid layer of the urine test tube 7, and the ratio of the particle amount in each liquid layer of the urine test tube 7. The number of training samples for the BP neural network is greater than 800, and the learning rate is between 0.2 and 0.5. The BP neural network is used as input to determine the particle amount in each liquid layer of the urine test tube 7 and outputs the retention time.

[0043] The particle precipitation in urine is also called urine sediment, which refers to the solid components in urine observed under a microscope. It is usually composed of cells, crystals, tubular shapes, microorganisms, etc., and will gradually sink due to gravity, but at a slow speed. In 0-30 minutes, large particles begin to sink slowly, and most of the solids begin to precipitate in 1h-2h. Therefore, the residence time can be determined by using the change in particle concentration of each liquid layer due to precipitation during the particle precipitation process. Conventional particles, such as urine sediment, are observed microscopically to obtain urine detection information, but the automatic urine testing machine 1 itself can complete the detection of urine information, so a light beam emitter 3 and a light beam receiver 4 are used for spectral detection. Different material components in the spectral effect will absorb, scatter or emit light of a specific wavelength to determine the amount of particles in each liquid layer, and the residence time is determined based on the particle ratio.

[0044] The ratio of particles within each liquid layer is also affected by the total number of particles. According to Stokes' law in fluid mechanics, the settling velocity of particles is directly proportional to particle size and density difference, and inversely proportional to the liquid viscosity. Therefore, a mapping relationship between the total number of particles within each liquid layer of urine test tube 7, the ratio of particles within each liquid layer within urine test tube 7, and the retention time is introduced to better reflect the retention time.

[0045] Because retention time can vary in many ways, a BP neural network is trained to map the changes in different parameters to retention time, thereby accurately providing feedback on the retention time of each urine test tube 7 to be tested. Outputting the retention time can help users identify invalid urine samples and reduce misdiagnosis of patient pathological conditions.

[0046] During use, the user needs to ensure that the storage environment where the urine test tube 7 is temporarily stored can remain stable, and carry it to the automatic urine testing machine 1, and load the urine test tube 7 onto the test tube conveyor table 2. After loading, slide the light beam emitter 3 and the light beam receiver 4 so that they avoid the labels on the test tubes and align with each other. Start the test tube conveyor table 2, and the test tube conveyor table 2 will convey the urine test tubes 7 into the light shielding box 5 one by one. The light beam emitter 3 and the light beam receiver 4 will detect the amount of particles in the liquid layer of the corresponding urine test tube 7. During this process, the light shielding box 5 will shield the detection process of the light beam emitter 3 and the light beam receiver 4 from external ambient light, thereby reducing the interference of external ambient light on the detection.

[0047] The controller obtains the total number of particles and the particle ratio within each layer of urine test tube 7 as detected by the light beam transmitter 3 and light beam receiver 4. These total number of particles and the particle ratio within each layer of urine test tube 7 are input into the BP neural network, which outputs the retention time. The automatic urine testing machine 1 automatically extracts a sample from the urine test tube 7 through the sampling port, completing the urine sample test.

[0048] Example 2:

[0049] The difference from the above embodiment is that the BP neural network is trained based on the total amount of particles in each liquid layer of the urine test tube 7 collected at different retention times under the same sample, the ratio of the amount of particles in each liquid layer of the urine test tube 7, and the urine test results. The BP neural network is used to output the deviation value of the urine test result caused by different retention times.

[0050] The controller is used to obtain the test result of the automatic urine testing machine 1 and invert the test result when the urine test tube 7 is not retained according to the retention time and deviation value output by the BP neural network.

[0051] The test results of urine samples are affected by the length of the retention time. Once the retention time is obtained by calculating the ratio of the particle amount in each liquid layer of the urine test tube 7, the deviation of the test result of the current urine sample can be calculated based on the retention time, thereby better evaluating the test results. Once the deviation value is known, the test results can be corrected using the deviation value, thereby obtaining test data that is closer to that of a fresh urine sample.

[0052] Example 3:

[0053] The difference from the above embodiment is that the controller signal is connected to the alarm 6, and the controller is used to control the alarm 6 to issue an alarm when the retention time output by the BP neural network is greater than 2h.

[0054] The controller is also used to obtain the current time node. A standard collection period is preset in the controller. The controller obtains the urine collection time by subtracting the retention time output by the BP neural network from the current time node. When the urine collection time exceeds the standard collection period, the control alarm 6 sounds an alarm.

[0055] When the output retention time is greater than 2 hours, the urine sample parameters have significantly drifted, and the detection value is low. The alarm 6 can be controlled to sound an alarm, reminding medical staff to pay attention to the current test sample. Morning urine is the best urine sample, so in most cases, patients are required to collect urine in the early morning. The controller can deduce the urine collection time by subtracting the retention time from the current time, thereby determining whether the patient collected urine within the specified time.

[0056] Example 4:

[0057] The difference from the above embodiment is that the controller presets a standard particle amount range value, and when the particle amount detected by the light beam receiver 4 exceeds the standard particle amount range value, the controller controls the alarm 6 to sound an alarm.

[0058] Most urine test tubes 7 are labeled, and different hospitals may place labels in different locations. Consequently, the light beam from the light beam transmitter 3 may strike the label, resulting in erroneous data. Therefore, a standard particle count range is set. If the light beam strikes the label, the result will exceed the standard particle count range, and the controller controls the alarm 6 to sound an alarm to alert medical staff.

[0059] Example 5:

[0060] The difference from the above embodiment is that the alarm 6 is one or more of a buzzer, an LED light and a vibration motor.

[0061] The alarm device 6 can generate an alarm by means of a buzzer, a flashing LED light, and a vibration motor.

[0062] Obviously, the above embodiments are merely examples for clarity of explanation and are not intended to limit the implementation methods. Those skilled in the art will readily appreciate that other variations or modifications based on the above descriptions are possible. It is not necessary and impossible to enumerate all implementation methods here. Obvious variations or modifications arising therefrom remain within the scope of protection of the present invention.

Claims

1. A urine testing device based on medical testing, characterized in that: The automatic urine testing machine (1) is used to sample and test urine from a urine test tube (7) through a sampling port. A test tube conveying platform (2) is provided below the sampling port of the automatic urine testing machine (1). The test tube conveying platform (2) is used to convey the urine test tube (7). A plurality of light beam emitters (3) and light beam receivers (4) are provided on the test tube conveying platform (2). The light beam emitters (3) and light beam receivers (4) are both located below the sampling port of the automatic urine testing machine (1). The light beam emitters (3) and light beam receivers (4) are used to detect the amount of particles in each liquid layer of the urine test tube (7) through spectral effects. The invention also includes a controller, wherein a BP neural network is provided in the controller. The BP neural network is trained based on samples of different retention times and the proportion of the amount of particles in each liquid layer of the urine test tube (7). The BP neural network is used to input the amount of particles in each liquid layer of the urine test tube (7) and output the retention time.

2. The urine testing device based on medical testing according to claim 1, characterized in that: A light shielding box (5) is fixedly connected to the test tube conveying platform (2), and the light beam emitter (3) and the light beam receiver (4) are both located in the light shielding box (5). The light shielding box (5) is provided with openings for sampling and for the urine test tube (7) to enter.

3. The urine testing device based on medical testing according to claim 2, characterized in that: The BP neural network is also trained based on the total amount of particles in each liquid layer of the urine test tube (7) of the sample. The BP neural network is used to establish a mapping relationship between the total amount of particles in each liquid layer of the urine test tube (7), the ratio of the amount of particles in each liquid layer of the urine test tube (7), and the retention time.

4. The urine testing device based on medical testing according to claim 3, characterized in that: The BP neural network is trained based on the total amount of particles in each liquid layer of the urine test tube (7) collected at different retention times under the same sample, the ratio of the amount of particles in each liquid layer of the urine test tube (7), and the urine test results. The BP neural network is used to output the deviation value of the urine test result caused by different retention times.

5. The urine testing device based on medical testing according to claim 4, characterized in that: The controller is used to obtain the test result of the automatic urine testing machine (1), and inversely calculate the test result when the urine test tube (7) is not retained according to the retention time and deviation value output by the BP neural network.

6. The urine testing device based on medical testing according to claim 5, characterized in that: The controller signal is connected to an alarm (6), and the controller is used to control the alarm (6) to sound an alarm when the retention time output by the BP neural network is greater than 2 hours.

7. The urine testing device based on medical testing according to claim 6, characterized in that: The controller is also used to obtain the current time node. A standard collection period is preset in the controller. The controller obtains the urine collection time by subtracting the retention time output by the BP neural network from the current time node. When the urine collection time exceeds the standard collection period, the control alarm (6) sounds an alarm.

8. The urine testing device based on medical testing according to claim 7, characterized in that: The controller is preset with a standard particle amount range value. When the particle amount detected by the light beam receiver (4) exceeds the standard particle amount range value, the controller controls the alarm (6) to sound an alarm.

9. The urine testing device based on medical testing according to claim 8, characterized in that: The number of the light beam emitters (3) and the light beam receivers (4) is at least 2, and the light beam emitters (3) and the light beam receivers (4) are both slidably connected to the light shielding box (5).

10. The urine testing device based on medical testing according to claim 9, characterized in that: The alarm (6) is one or more of a buzzer, an LED light and a vibration motor.

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