A device for detecting hemoglobin in peritoneal drainage fluid

Abstract

The present application relates to a kind of peritoneal cavity drainage liquid hemoglobin detection device;The device includes test module and connecting module:The connecting module is used to set the test module on drainage tube;The test module includes probe and processor;The probe is used to emit infrared light by emission end, after the reflection light of drainage liquid is received by receiving end, and send to the processor for hemoglobin detection;The processor is used to carry out variant component analysis based on the spectrum of the reflection light, constructs hemoglobin concentration regression model based on the light absorption contribution of the variant component, and obtains hemoglobin concentration by solving.This application solves the problem that there is no device for real-time detection of peritoneal cavity drainage liquid in the prior art, and only by observing the state of drainage liquid or the method of venous blood inspection can determine whether peritoneal cavity hemorrhage occurs.

Description

TECHNICAL FIELD

[0001] The present application belongs to the technical field of medical devices, and particularly relates to an abdominal cavity drainage liquid hemoglobin detection device. BACKGROUND

[0002] Postoperative hemorrhage is one of the most serious complications after abdominal surgery. It is a clinical focus problem because of its acute onset, rapid change and serious consequences. Postoperative hemorrhage can lead to a series of complications, including blood volume deficiency and damage to important organs such as the heart or kidney. Abdominal cavity drainage is one of the most common and important basic techniques in abdominal surgery. By monitoring the abdominal cavity drainage liquid, it can be determined whether the patient has postoperative hemorrhage, and appropriate measures can be taken in time.

[0003] At present, for patients with suspected abdominal cavity hemorrhage, the color, appearance, drainage volume, etc. of the abdominal cavity drainage liquid are observed to roughly analyze the abdominal cavity drainage liquid. However, the composition of the drainage liquid is complex, and is easily affected by various factors such as age, type and range of surgery, drainage time, etc. Therefore, it is difficult to accurately analyze the properties of the drainage liquid and quantitatively detect abdominal cavity hemorrhage. In addition, venous blood of the patient can be collected for detection at regular intervals, and the degree of change in hemoglobin of the patient can be used to determine whether there is abdominal cavity hemorrhage. However, the detection efficiency is low, the waiting time is long, and the treatment opportunity is easily delayed, which cannot meet the clinical needs.

[0004] Therefore, it is of great significance to develop a portable and reusable abdominal cavity drainage liquid hemoglobin detection device that can be monitored in real time and has precision meeting clinical standards. SUMMARY

[0005] In view of the above analysis, the present application aims to disclose an abdominal cavity drainage liquid hemoglobin detection device, which solves the problem that the abdominal cavity drainage liquid cannot be detected in real time in the prior art, and only the state of the drainage liquid or venous blood detection can be used to determine whether there is abdominal cavity hemorrhage.

[0006] The main purpose of the present application is achieved by the following technical solutions:

[0007] The present application discloses an abdominal cavity drainage liquid hemoglobin detection device, which comprises a test module and a connection module:

[0008] The connection module is used to set the test module on the drainage tube;

[0009] The test module comprises a probe and a processor. The probe is used to emit infrared light through the emitting end, receive reflected light after passing through the drainage liquid through the receiving end, and send the reflected light to the processor for hemoglobin detection.

[0010] The processor is configured to perform a variation component analysis based on the spectrum of the reflected light, construct a hemoglobin concentration regression model based on light absorption contributions of the variation components, and calculate the hemoglobin concentration.

[0011] Further, the processor constructs the hemoglobin concentration regression model by the following method:

[0012] The reflected light after calibration under the condition of no bleeding is used as the incident light, and the reflected light detected during the detection process is used as the emergent light; the optical absorbance of the drainage fluid is obtained based on the spectrum of the incident light and the emergent light;

[0013] The spectrum of the emergent light is subjected to principal component analysis to obtain light absorption contributions of m variation components;

[0014] Based on the light absorption contributions of the variation components, the optical absorbance of the drainage fluid, and the light absorption coefficient of hemoglobin, a hemoglobin concentration regression model is constructed.

[0015] Further, the hemoglobin concentration regression model is expressed as:

[0016]

[0017] Wherein, A represents the optical absorbance of the drainage fluid, C1 and C2 represent the concentrations of oxygenated hemoglobin and deoxygenated hemoglobin in the drainage fluid respectively, G represents background noise, and α1 and α2 are the light absorption coefficients of oxygenated hemoglobin and deoxygenated hemoglobin respectively; X k represents the light absorption contribution of the kth principal variation component extracted by PCA, β k represents the dynamic weight coefficient of the kth variation component.

[0018] Further, based on the hemoglobin concentration regression model, the hemoglobin concentration is obtained by the following method:

[0019] The spectrum of the emergent light is obtained continuously multiple times to obtain multiple optical absorbance detection results of the drainage fluid;

[0020] Based on the multiple optical absorbance detection results and the hemoglobin concentration regression model, an optical absorbance matrix is constructed;

[0021] Based on the optical absorbance matrix, an optical absorbance error sum of squares is obtained;

[0022] Based on the optical absorbance error sum of squares, the dynamic weight coefficients of the k principal variation components are optimized by the least square method, and the hemoglobin concentration is obtained.

[0023] Further, the optical absorbance matrix is expressed as:

[0024] A=Cα+XB+G;

[0025]

[0026] The light absorption degree error square sum is represented as:

[0027]

[0028] Further, in the process of hemoglobin detection by the processor, the background noise is dynamically modeled and calibrated by the following method:

[0029] After the machine is calibrated, a plurality of groups of light absorption data are collected in the state of no bleeding, and after the transient noise is removed by wavelet filtering, the initial mean value G0 and the standard deviation σ0 of the background noise are calculated;

[0030] In the continuous detection process, the light absorption data when there is no significant change in hemoglobin is collected every time T, a background noise dynamic calibration model is constructed, and the dynamically updated background noise is obtained based on the background noise dynamic calibration model by the sliding window method;

[0031] The light absorption degree prediction value of the drainage fluid is obtained based on the dynamically updated background noise;

[0032] If the residual error between the prediction value and the corresponding detection value is greater than a preset threshold, it is prompted that there is an unknown interference and the device is calibrated.

[0033] Further, the background noise dynamic calibration model is represented as:

[0034]

[0035] Wherein, γ is a forgetting factor, N is the number of data points in the sliding window, A i The light absorption degree data detected for the i-th time

[0036] Further, the probe is arranged on the back side of the test module; a recess is arranged on the connecting module, and the probe is detachably connected in the recess; the contact surface of the recess and the probe is made of high-transparency plastic material.

[0037] Further, the connecting module is provided with a reflective coating on the opposite side of the recess.

[0038] Further, the side of the test module away from the probe is provided with a display screen and a key; the display screen is used to display the measurement result; and the key is used to turn on and off the device and start and stop the device calibration.

[0039] The present application can at least achieve one of the following beneficial effects:

[0040] 1. This invention employs a non-invasive method to monitor changes in hemoglobin concentration in drainage fluid. By combining PCA (principal component analysis) with recursive least squares, it accurately separates and quantifies the light absorption characteristics of various interfering components in the drainage fluid, dynamically adjusts the weight coefficients of each interfering component, and through dynamic modeling and calibration of background noise, ensures that the detection results of hemoglobin concentration are not affected by complex components such as drainage tubes, bilirubin, and lipids, thereby improving the accuracy and stability of the detection.

[0041] 2. The product of this invention is a portable wearable device that can continuously monitor changes in hemoglobin levels in peritoneal drainage fluid in real time after surgery, visually displaying the hemoglobin concentration in the drainage tube to assess the patient's peritoneal bleeding status. Furthermore, this device is reusable and requires no testing reagents, thus saving costs. Attached Figure Description

[0042] The accompanying drawings are for illustrative purposes only and are not intended to limit the invention. Throughout the drawings, the same reference numerals denote the same parts.

[0043] Figure 1 This is a schematic diagram of the peritoneal drainage fluid hemoglobin detection device in an embodiment of the present invention;

[0044] Figure 2 This is a schematic diagram of the connection module structure in an embodiment of the present invention. Detailed Implementation

[0045] Preferred embodiments of the present invention will now be described in detail with reference to the accompanying drawings, which form part of this application and, together with the embodiments of the present invention, serve to illustrate the principles of the present invention.

[0046] An embodiment of the present invention discloses a device for detecting hemoglobin in abdominal drainage fluid, such as... Figure 1 As shown, the device includes a testing module and a connection module:

[0047] The connection module is used to mount the test module onto the drainage tube;

[0048] The testing module includes a probe and a processor; the probe is used to emit infrared light through the transmitting end, receive the reflected light after passing through the drainage fluid through the receiving end, and send it to the processor for hemoglobin detection;

[0049] The processor is used to perform variation component analysis based on the spectrum of the reflected light, construct a hemoglobin concentration regression model based on the light absorption contribution of the variation components, and calculate the hemoglobin concentration.

[0050] Specifically, the processor constructs a hemoglobin concentration regression model using the following method:

[0051] The reflected light after starting up and calibrating under a non-bleeding state is taken as incident light, and the reflected light detected in the detection process is taken as emergent light; the optical absorption degree of the drainage liquid is obtained based on the spectrum of the incident light and the emergent light;

[0052] The spectrum of the emergent light is subjected to principal component analysis to obtain optical absorption contribution of m variable components;

[0053] Based on the optical absorption contribution of the variable components, the optical absorption degree of the drainage liquid and the optical absorption coefficient of hemoglobin, a hemoglobin concentration regression model is constructed.

[0054] Based on the hemoglobin concentration regression model, the hemoglobin concentration is obtained by the following method:

[0055] The spectrum of the emergent light is acquired continuously for multiple times to obtain multiple optical absorption degree detection results of the drainage liquid;

[0056] Based on the multiple optical absorption degree detection results and the hemoglobin concentration regression model, an optical absorption degree matrix is constructed;

[0057] Based on the optical absorption degree matrix, an optical absorption degree error sum of squares is obtained;

[0058] Based on the optical absorption degree error sum of squares, the dynamic weight coefficient of k main variable components is optimized by the least square method, and the hemoglobin concentration is obtained.

[0059] It should be noted that the purpose of the present application is to provide a detection device which can monitor and quantitatively analyze the hemoglobin concentration in abdominal drainage liquid in real time. The device continuously detects the hemoglobin concentration in the drainage liquid in a non-contact manner and detects the reflection of specific light based on hemoglobin. The composition of the drainage liquid is different from that of blood and may contain bacteria, bilirubin crystals, lipid droplets, amylase and bile acid, etc. At the same time, the device needs to pass through the drainage tube, which is different from the conventional human tissue experimental environment. In order to solve the influence of the above factors, the present application analyzes the variable components by principal component analysis (PCA) and recursive least square method (RLS), and combines a dynamic calibration algorithm to update the background noise in real time, eliminate the interference of bilirubin, lipids and other complex components in the drainage tube and the drainage liquid on the detection result, and improve the detection robustness. The hemoglobin concentration when the device is initially started is taken as the judgment standard. When the medical staff determines that there is no bleeding in the abdominal cavity, the device is started, and the light reflection at this time is taken as the baseline value. When the hemoglobin concentration in the drainage tube increases, the device can detect the concentration change and display it synchronously, thereby assisting the medical staff in judging the bleeding situation in the abdominal cavity.

[0060] More specifically, the present application is based on the principle of photoelectric wave and uses spectral method to measure the content of human hemoglobin, realizing non-invasive and fast quantitative detection of human hemoglobin, that is, by measuring the diffuse reflection spectrum of postoperative drainage of human body, regression analysis is performed on the concentration of each substance in blood and light absorption, so as to quantitatively detect the content of hemoglobin.

[0061] When the human body drainage appears bleeding, the content of hemoglobin in blood increases, the amount of absorbed incident light increases, the light absorption increases, the outgoing light intensity at this time becomes weak, based on this principle, the reflected light during detection is taken as the outgoing light intensity Io; when the human body has no bleeding phenomenon, the content of hemoglobin is minimum, the incident light is least affected by hemoglobin, and the light absorption is minimum, the light intensity at this time is taken as the incident light intensity I.

[0062] The quantitative relationship between light absorption and each component in the solute can be described by the expression of Beer-Lambert law.

[0063]

[0064] Wherein, A is the light absorption, I o (λ) is the outgoing light intensity, I(λ) is the incident light intensity, ε iλ is the extinction coefficient of the i-th substance at wavelength λ, which is a constant representing the light absorption characteristics of the substance at a specific wavelength λ, c i represents the concentration of the i-th substance, d represents the length of the light propagation path, and G represents the background noise.

[0065] As can be seen from the above formula, the absorption of a light is affected by the accumulation of the concentrations of various substances in the transmitted part. By detecting multiple wavelengths or multiple measurements of light absorption at the same wavelength, the concentration of a specific substance can be solved by calculation.

[0066] That is, the light absorption at a certain wavelength and the concentration of each substance in the blood constitute a linear combination relationship, so the regression model can be used for analysis.

[0067] In spectral detection, non-hemoglobin components (such as bilirubin crystals, lipid droplets, amylase) in the drainage fluid and the drainage tube will also absorb light of a specific wavelength, resulting in overestimation or underestimation of the measured value of total light absorption (A). In order to further improve the background noise suppression capability, the present embodiment also performs variation component analysis by principal component analysis (PCA) method, obtains the light absorption contribution of multiple variation components, further constructs a hemoglobin concentration regression model based on the light absorption contribution of the variation components, the light absorption of the drainage fluid and the light absorption coefficient of hemoglobin, and finally optimizes the dynamic weight coefficient of the variation components by recursive least squares (RLS) method, and obtains the hemoglobin concentration.

[0068] Specifically, the analysis of variable components using principal component analysis (PCA) includes:

[0069] 1. Time series data construction: The light absorbance values ​​At (t=1,2,...,m) of multiple time windows are continuously collected at a fixed sampling frequency. The data of p time windows are combined into an m×p dimensional matrix X, with each column representing the light absorption sequence of a time window.

[0070] 2. PCA Decomposition of Interference Modes: The matrix X is centered and its covariance matrix is ​​calculated. The top k principal components of light absorption contribution X1, X2, ... X are extracted through eigenvalue decomposition. i ...X k Each X i Characterizes the light absorption contribution of an interfering substance (such as bilirubin crystals or lipid droplets) at different time windows.

[0071] 3. Dynamic weighted quantification of contribution: The light absorption contribution X is calculated... k Input the regression model and optimize the weight coefficients β in real time using recursive least squares (RLS). k . β k The absolute value is proportional to the light absorption contribution intensity of the corresponding interfering object.

[0072] This method utilizes the characteristic that the concentration of interfering substances fluctuates over time to achieve the separation and compensation of multiple interference sources at a single wavelength.

[0073] In the hemoglobin concentration regression model, light absorbance A is used as the dependent variable, and the concentrations of each substance are used as independent variables, as follows:

[0074]

[0075] Where A represents the light absorbance of the drainage fluid, C1 and C2 represent the concentrations of oxyhemoglobin and deoxyhemoglobin in the drainage fluid, respectively, G represents the background noise, α1 and α2 are the light absorption coefficients of oxyhemoglobin and deoxyhemoglobin, respectively, and X is the product of the extinction coefficients of oxyhemoglobin and deoxyhemoglobin at that wavelength and the optical path difference; k β represents the light absorption contribution of the k-th major variant component extracted by PCA. k This represents the dynamic weight coefficient of the k-th variant component.

[0076] The light absorption contributions of the k major variable components in the drainage fluid spectral data extracted by PCA include the effects of bilirubin crystals, lipid droplets, amylase, and the drainage tube on the light absorption of hemoglobin. The dynamic weighting coefficient β k The weight of each interfering agent's effect on hemoglobin light absorption in the overall model is represented. If β kThe greater the value, the more significant the influence of the interference component on light absorption. If β k The smaller the value, the weaker the influence of the interference component. The extracted X k is input into the hemoglobin concentration regression model as an independent variable, and the dynamic weight coefficient β k is optimized in real time through recursive least squares to reduce the influence of background noise interference on the estimation of C1 and C2.

[0077] In this embodiment, n sets of light absorption data are obtained through multiple measurements, and are expressed in the form of a light absorption matrix as follows:

[0078] A = Cα + Xβ + G

[0079]

[0080] The light absorption error square sum is expressed as:

[0081]

[0082] wherein X k,i represents the light absorption contribution of the kth variant component of the ith sample.

[0083] Determination of the dynamic weight coefficient β k : When new light absorption data is obtained, the current hemoglobin concentration value is first fixed: if it is in the initial non-bleeding state, C1 = C2 = 0; if it is not in the initial state, the C1 and C2 estimation values obtained in the last iteration are used as fixed parameters. Based on this parameter, the weight coefficients β k of the interference components in the drainage fluid are optimized and calculated through least squares to obtain the current optimal β k value.

[0084] After obtaining the optimized β k value, the C that minimizes Q is recalculated based on the light absorption error square sum through least squares, and is denoted as The components and C1 + C2 are the updated hemoglobin concentrations.

[0085] Whenever new light absorption data arrives, the system repeats the above process: fix the current C1 and C2 values to update β k , and then update the C1 and C2 concentrations using the new β k value. This iterative process continues to ensure that the detection results can track the dynamic changes in the hemoglobin concentration of the drainage fluid in real time.

[0086] Further, to cope with unknown component interference that may occur in the drainage fluid, the processor also includes dynamic modeling and device calibration of background noise through the following method during the hemoglobin detection process:

[0087] In the continuous detection process, a sliding window is set with a step T (5 minutes in this embodiment), and the light absorption data in the sliding window (i.e. the light absorption data when there is no significant change in hemoglobin and no alarm state) is collected;

[0088] A background noise dynamic calibration model is constructed, and a dynamically updated background noise is obtained based on the background noise dynamic calibration model and the light absorption data in the current sliding window;

[0089] A light absorption prediction value of the drainage fluid is obtained based on the dynamically updated background noise;

[0090] If the residual error between the prediction value and the corresponding detection value is greater than a preset threshold, it is prompted that there is an unknown interference and device calibration is performed.

[0091] The background noise dynamic calibration model is represented as:

[0092]

[0093] Wherein, γ is a forgetting factor, which is set to 0.8 in this embodiment, N is the number of data points in the sliding window, A i The light absorption data detected for the i-th time.

[0094] For example, the light absorption prediction value is represented as: Wherein:∑β k X k,t is a known interference component (such as bilirubin crystals, lipid droplets, amylase, drainage tube, etc.) dynamically compensated by PCA, G t is the remaining background noise (without known interference).

[0095] When the real-time detected light absorption A current exceeds the threshold 3σ predicted , the residual error of the prediction value A t (σ t is the dynamic standard deviation of the background noise, which is calculated in real time by the sliding window, and the initial value is determined by the first window data in the calibration stage), it is determined that there is an unknown interference, and the system automatically triggers a temporary calibration mode to realize abnormal detection and adaptive compensation. In actual application, medical staff can also be prompted to manually confirm the drainage fluid state to ensure accurate and safe detection of the drainage fluid state.

[0096] Further, the probe of the hemoglobin detection device in the embodiment adopts a MAX30102 module, the MAX30102 module internally integrates an infrared LED, a red light LED and a photodetector, the embodiment adopts the infrared LED as a transmitting end to emit infrared light, collects reflected light signals through the photodetector, and then sends the reflected light signals to a processor for hemoglobin concentration analysis; the probe in the embodiment adopts a reflective design, that is, the transmitting end and the photodetector are arranged on the same side of the drainage tube; as shown in Figure 2 the connecting module of the detection device is provided with a groove, the probe is arranged on the back side of the test module; the probe is detachably connected in the groove; the contact surface of the groove and the probe is made of high-transparency plastic material. And the connecting module is provided with a reflective coating on the opposite side of the groove.

[0097] The side, away from the probe, of the test module is provided with a display screen and a key; the display screen is used for displaying measurement results; and the key is used for switching on and off and starting and stopping calibration of the device.

[0098] In actual application, the abdominal drainage tube is connected with the suction ball by using a connecting pipe. The contact surface of the connecting module and the probe is designed with a groove, the probe of the test module can be wrapped, and the contact surface is made of high-transparency plastic material to increase the incidence of incident light. The bottom side of the connecting module has a reflective coating to increase the reflection of light.

[0099] The reusable detection device is fixed by clamping from the outside of the connecting module. The key is long-pressed to turn on and off, and the key is short-pressed to wake up the screen. The device is turned on when it is confirmed that the drainage fluid has no bleeding, and the calibration key is pressed when the drainage fluid passes through the detection device. At this time, the detection device automatically calibrates the reference value. After that, the device will sound an alarm when the hemoglobin content rises or falls by 10%. If it is necessary to check the current hemoglobin detection result during the detection process, the screen can be woken up by short-pressing the key to check.

[0100] In summary, the abdominal drainage fluid hemoglobin detection device provided by the application adopts a non-invasive method to monitor the change of hemoglobin concentration in the drainage fluid, combines PCA (principal component analysis) and recursive least squares method to accurately separate and quantify the light absorption characteristics of various interference components in the drainage fluid, dynamically adjusts the weight coefficients of the interference components, and dynamically models and calibrates the background noise, so that the detection result of the hemoglobin concentration is not affected by complex components such as drainage tubes, bilirubin and lipids, and the accuracy and stability of the detection are improved. The product of the application is a portable wearable device, which can continuously and real-timely monitor the change of hemoglobin content in the abdominal drainage fluid after surgery, visually display the hemoglobin concentration in the drainage tube, and judge the abdominal bleeding condition of the patient. The device can be continuously and repeatedly used without the need for reagents, which saves costs.

[0101] Those skilled in the art can understand that all or part of the processes of the methods in the above embodiments can be instructed by a computer program to relevant hardware, and the program can be stored in a computer readable storage medium. The computer readable storage medium includes a magnetic disk, an optical disk, a read-only memory, a random access memory, and the like.

[0102] The above description is merely a preferred specific embodiment of the present application, and the protection scope of the present application is not limited thereto. Any person skilled in the art can easily think of changes or replacements within the technical scope disclosed by the present application, and all such changes or replacements should be covered within the protection scope of the present application.

Claims

1. A device for detecting hemoglobin in abdominal drainage fluid, characterized in that, The device includes a testing module and a connection module: The connection module is used to mount the test module onto the drainage tube; The testing module includes a probe and a processor; the probe is used to emit infrared light through the transmitting end, receive the reflected light after passing through the drainage fluid through the receiving end, and send it to the processor for hemoglobin detection; The processor is used to perform variation component analysis based on the spectrum of the reflected light, construct a hemoglobin concentration regression model based on the light absorption contribution of the variation components, and calculate the hemoglobin concentration; the hemoglobin concentration regression model is expressed as: ； Where A represents the light absorbance of the drainage fluid, C1 and C2 represent the concentrations of oxygenated and deoxygenated hemoglobin in the drainage fluid, respectively, and G represents the background noise. and The light absorption coefficients of oxyhemoglobin and deoxyhemoglobin are respectively; X k This represents the light absorption contribution of the k-th major variant component extracted by PCA. This represents the dynamic weight coefficient of the k-th variant component; Based on the hemoglobin concentration regression model, the hemoglobin concentration is obtained by the following method: acquiring the emitted light spectrum multiple times to obtain multiple light absorbance detection results of the drainage fluid; constructing a light absorbance matrix based on the multiple light absorbance detection results and the hemoglobin concentration regression model; obtaining the sum of squared light absorbance errors based on the light absorbance matrix; and optimizing the dynamic weight coefficients of the k main variable components using the least squares method based on the sum of squared light absorbance errors to obtain the hemoglobin concentration.

2. The peritoneal drainage fluid hemoglobin detection device according to claim 1, characterized in that, The processor constructs a hemoglobin concentration regression model using the following method: The reflected light after calibration under no-bleeding conditions is used as the incident light, and the reflected light detected during the detection process is used as the output light; the light absorbance of the drainage fluid is obtained based on the spectra of the incident and output light. Principal component analysis was performed on the spectrum of the emitted light to obtain the light absorption contributions of m variable components; Based on the light absorption contribution of the variable components, the light absorbance of the drainage fluid, and the light absorption coefficient of hemoglobin, a regression model for hemoglobin concentration was constructed.

3. The peritoneal drainage fluid hemoglobin detection device according to claim 1, characterized in that, The light absorbance matrix is ​​represented as follows: ； ； The sum of squares of the light absorbance error is expressed as follows: ； This represents the absorbance of the drainage fluid in the i-th test. This represents the light absorption contribution of the k-th major variant component corresponding to the i-th detection.

4. The peritoneal drainage fluid hemoglobin detection device according to claim 1, characterized in that, During the hemoglobin detection process, the processor also includes dynamic modeling and calibration of background noise using the following method: During continuous detection, a sliding window is set with a step size T, and light absorbance data within the sliding window is collected. A dynamic background noise calibration model is constructed, and the dynamically updated background noise is obtained based on the dynamic background noise calibration model and the light absorbance data in the current sliding window; The predicted light absorbance of the drainage fluid is obtained based on the dynamically updated background noise. If the residual between the predicted value and the corresponding detected value is greater than a preset threshold, an unknown interference is detected and the device is calibrated.

5. The peritoneal drainage fluid hemoglobin detection device according to claim 4, characterized in that, The background noise dynamic calibration model is expressed as follows: ； in, Let N be the forgetting factor, and N be the number of data points within the sliding window. The light absorbance data detected for the i-th time.

6. The peritoneal drainage fluid hemoglobin detection device according to claim 1, characterized in that, The probe is disposed on the back side of the test module; the connection module is provided with a groove, and the probe is detachably connected to the groove; the contact surface between the groove and the probe is made of high-transparency plastic material.

7. The peritoneal drainage fluid hemoglobin detection device according to claim 1, characterized in that, The connecting module has a reflective coating on the opposite side of the groove.

8. The peritoneal drainage fluid hemoglobin detection device according to claim 1, characterized in that, The test module has a display screen and buttons on the side opposite to the probe; the display screen is used to display measurement results; the buttons are used to power on / off and to start and stop device calibration.

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