Spectroscopic analysis method and device for negative pressure drainage bottle

Abstract

The application relates to the technical field of drainage liquid analysis, and particularly provides a spectrum analysis method and device for a negative pressure drainage bottle, the method comprising the following steps: obtaining first spectrum data and second spectrum data when spectrum analysis of drainage liquid is needed; obtaining spectrum data deviation information according to the second spectrum data and calibration spectrum data, wherein the calibration spectrum data is spectrum data corresponding to an optical path which does not pass through drainage liquid in the negative pressure drainage bottle in a calibration position; querying a mapping relationship table about spectrum data deviation and correction coefficients which is constructed in advance according to the spectrum data deviation information to obtain a spectrum correction coefficient; obtaining corrected spectrum data according to the spectrum data and the spectrum correction coefficient; and obtaining drainage liquid parameter information based on the corrected spectrum data analysis; the method can effectively solve the problem that spectrum data deviates and has errors due to the change of an optical path when a position of the negative pressure drainage bottle changes, and the change amount of the optical path is a dynamic value.

Description

Technical Field

[0001] This application relates to the field of drainage fluid analysis technology, and more specifically, to a spectral analysis method and apparatus for a negative pressure drainage bottle. Background Technology

[0002] During or after surgery, current technology typically uses negative pressure drainage bottles to collect exudates and blood from the patient's body. Existing technology can obtain drainage fluid parameters (such as hemoglobin concentration and bilirubin concentration) by using spectral analysis technology to analyze the drainage fluid. This allows medical staff to understand the patient's bleeding status, postoperative recovery status, and timely detection of potential complications based on the drainage fluid parameters.

[0003] Existing technologies utilize spectral analysis equipment positioned near the negative pressure drainage bottle to acquire spectral data of the drainage fluid. However, the negative pressure drainage bottle is not stationary during use (e.g., the patient's spontaneous activities or nursing procedures by medical staff may cause changes in the bottle's orientation). These changes in orientation cause variations in the optical path length of the spectral analysis equipment. Since the optical path length is a key factor affecting the accuracy of spectral data, existing technologies suffer from drift and error in spectral data due to the dynamic nature of the change in optical path length caused by variations in the negative pressure drainage bottle's orientation. This results in poor spectral analysis performance and low accuracy of drainage fluid parameters.

[0004] Currently, there is no effective technical solution to the above-mentioned problems. It should be noted that the information disclosed in this section is only for understanding the background of the present invention and therefore may include information that does not constitute prior art. Summary of the Invention

[0005] The purpose of this application is to provide a spectral analysis method and apparatus for a negative pressure drainage bottle, which can effectively solve the problem of drift and error in spectral data caused by the change of optical path length when the position of the negative pressure drainage bottle changes and the change of optical path length is a dynamic value.

[0006] In a first aspect, this application provides a spectral analysis method for a negative pressure drainage bottle, used to perform spectral analysis on the drainage fluid inside the negative pressure drainage bottle. The spectral analysis method for the negative pressure drainage bottle includes the following steps:

[0007] S1. When it is necessary to perform spectral analysis on the drainage fluid, acquire first spectral data and second spectral data. The first spectral data is the spectral data corresponding to the light path passing through the drainage fluid in the negative pressure drainage bottle, and the second spectral data is the spectral data corresponding to the light path not passing through the drainage fluid in the negative pressure drainage bottle.

[0008] S2. Obtain spectral data deviation information based on the second spectral data and the calibration spectral data. The calibration spectral data is the spectral data corresponding to the optical path that does not pass through the drainage fluid in the negative pressure drainage bottle in the calibration posture.

[0009] S3. Based on the spectral data deviation information, query the pre-built mapping table between spectral data deviation and correction coefficient to obtain the spectral correction coefficient;

[0010] S4. Obtain corrected spectral data based on spectral data and spectral correction coefficients;

[0011] S5. Obtain drainage fluid parameter information based on corrected spectral data analysis.

[0012] This application provides a spectral analysis method for a negative pressure drainage bottle. First, spectral data deviation information is obtained based on second spectral data and calibration spectral data. Then, a spectral correction coefficient is obtained based on the spectral data deviation information, and the first spectral data is corrected based on the spectral correction coefficient to obtain corrected spectral data. Finally, drainage fluid parameter information is obtained based on the corrected spectral data. Since the spectral data deviation information reflects the magnitude of optical path change caused by the pose change of the negative pressure drainage bottle, and the spectral correction coefficient is obtained based on the spectral data deviation information, this application can correct the offset and error of the first spectral data caused by the pose change of the negative pressure drainage bottle. In other words, this application can effectively solve the problem of spectral data drift and error caused by the change in optical path when the pose of the negative pressure drainage bottle changes, and the change in optical path is a dynamic value. This effectively improves the spectral analysis effect and the accuracy of the drainage fluid parameters.

[0013] Optionally, the first spectral data includes multiple sets of spectral wavelengths and their corresponding spectral intensities, and step S4 includes:

[0014] S41. Based on the spectral wavelength, query the pre-built mapping table of wavelength and adjustment coefficient to obtain multiple first spectral adjustment coefficients, each spectral wavelength corresponding to a first spectral adjustment coefficient;

[0015] S42. Obtain the corrected spectral intensity corresponding to each spectral wavelength based on the spectral correction coefficient, the spectral intensity corresponding to each spectral wavelength, and the first spectral adjustment coefficient. The corrected spectral data is the set of all corrected spectral intensities.

[0016] Since the drainage fluid contains multiple components, and different components absorb and scatter light of different wavelengths to varying degrees, this technical solution first obtains the first spectral adjustment coefficient corresponding to different spectral wavelengths, and then adjusts the corresponding spectral intensity based on the first spectral adjustment coefficient. Therefore, this technical solution is equivalent to using different correction strategies when correcting the spectral intensity corresponding to different spectral wavelengths. Thus, this technical solution can effectively improve the accuracy of the corrected spectral data, thereby effectively improving the accuracy of the final obtained drainage fluid parameter information.

[0017] Optionally, step S4 may further include steps performed between steps S41 and S42:

[0018] S43. Use the image acquisition component to acquire the image information of the negative pressure drainage bottle, and analyze whether there are air bubbles in the drainage fluid based on the image information of the negative pressure drainage bottle. If yes, proceed to step S44; otherwise, proceed to step S42.

[0019] S44. Based on the image information of the negative pressure drainage bottle, obtain bubble parameter information. Then, based on the bubble parameter information, query the pre-constructed mapping relationship table between bubble parameters and adjustment coefficient set to obtain the adjustment coefficient set. The adjustment coefficient set includes the second spectral adjustment coefficient corresponding to different spectral wavelengths. The bubble parameter information includes the number of bubbles and the average size of bubbles.

[0020] When air bubbles are detected in the drainage fluid, step S42 includes:

[0021] S421. Obtain the corrected spectral intensity corresponding to each spectral wavelength based on the spectral correction coefficient, the spectral intensity corresponding to each spectral wavelength, the first spectral adjustment coefficient, and the second spectral adjustment coefficient.

[0022] When air bubbles are present in the drainage fluid, they scatter, reflect, or refract light. These scattering, reflection, and refraction all lead to a decrease in the accuracy of spectral intensity. Furthermore, the degree of scattering, reflection, and refraction of light by air bubbles may vary for different wavelengths. The adjustment coefficient set obtained by this technical solution includes second spectral adjustment coefficients corresponding to different spectral wavelengths. Therefore, this technical solution is equivalent to adaptively adjusting the spectral intensity based on the specific parameters of the air bubbles when they are present in the drainage fluid. The degree of adaptive adjustment of the spectral intensity varies for different spectral wavelengths. Thus, this technical solution can further improve the accuracy of spectral intensity, thereby further improving the accuracy of the corrected spectral data.

[0023] Optionally, step S43 includes:

[0024] S431. Use the image acquisition component to acquire image information of the negative pressure drainage bottle;

[0025] S432. Preprocess the image information of the negative pressure drainage bottle. The preprocessing includes grayscale processing, contrast enhancement and noise reduction.

[0026] S433. Use an edge detection algorithm to perform edge detection on the preprocessed negative pressure drainage bottle image information to obtain the drainage fluid area;

[0027] S434. Use the Holf circle transformation algorithm to identify air bubbles in the drainage fluid area to analyze whether there are air bubbles in the drainage fluid. If yes, proceed to step S44; otherwise, proceed to step S42.

[0028] This technical solution is equivalent to performing grayscale processing, contrast enhancement, and noise reduction on the negative pressure drainage bottle image information before analyzing whether there are air bubbles in the drainage fluid. Grayscale processing can simplify image data and reduce the complexity of subsequent processing, contrast enhancement can make the boundaries in the image clearer, and noise reduction can improve the image quality. Therefore, this technical solution can effectively improve the accuracy of air bubble identification.

[0029] Optionally, the edge detection algorithm is the Canny edge detection algorithm.

[0030] Optionally, step S1 includes:

[0031] S11. When it is necessary to perform spectral analysis on the drainage fluid, acquire the first spectral data and the second spectral data;

[0032] S12. Perform smoothing filtering on the first and second spectral data to reduce noise interference.

[0033] Since this technical solution can effectively reduce random noise and improve the signal-to-noise ratio of the first and second spectral data by smoothing and filtering the first and second spectral data, this example can effectively improve the accuracy and reliability of the first and second spectral data, so as to provide more accurate and reliable spectral data for subsequent processing steps, thereby further improving the spectral analysis effect and the accuracy of the drainage fluid parameters.

[0034] Optionally, the spectral analysis method for negative pressure drainage bottles may further include the following steps:

[0035] S6. Obtain the height of the drainage fluid, and generate an alarm message when the difference between the height of the drainage fluid and the height of the optical path that does not pass through the drainage fluid in the negative pressure drainage bottle is less than the height threshold.

[0036] Since the difference between the height of the drainage fluid level and the height of the optical path that does not pass through the drainage fluid in the negative pressure drainage bottle is less than the height threshold, it indicates that the drainage fluid level is too high. There is a risk that the optical path corresponding to the second spectral data may pass through the drainage fluid. If the optical path corresponding to the second spectral data passes through the drainage fluid, the difference between the second spectral data and the calibration spectral data will not be solely related to the positional difference of the negative pressure drainage bottle. Therefore, this technical solution can avoid the situation where the difference between the second spectral data and the calibration spectral data is not solely related to the positional difference of the negative pressure drainage bottle due to the drainage fluid level being too high, resulting in unreliable spectral analysis results and drainage fluid parameters.

[0037] Optionally, the height threshold is determined based on the actual pose of the negative pressure drainage bottle.

[0038] Since the height threshold of this technical solution is determined based on the actual position of the negative pressure drainage bottle, meaning that the height threshold of this technical solution is always adapted to the actual position of the negative pressure drainage bottle, this technical solution can effectively reduce the occurrence of missed alarms or false alarms, thereby effectively improving the reliability of alarm information.

[0039] Optionally, the drainage fluid parameters include hemoglobin concentration and bilirubin concentration.

[0040] Secondly, this application also provides a spectroscopic analysis device for a negative pressure drainage bottle, used for spectroscopic analysis of the drainage fluid inside the negative pressure drainage bottle. The spectroscopic analysis device for the negative pressure drainage bottle includes:

[0041] The spectral data acquisition module is used to acquire first spectral data and second spectral data when spectral analysis of the drainage fluid is required. The first spectral data is the spectral data corresponding to the light path passing through the drainage fluid in the negative pressure drainage bottle, and the second spectral data is the spectral data corresponding to the light path not passing through the drainage fluid in the negative pressure drainage bottle.

[0042] The spectral data deviation acquisition module is used to acquire spectral data deviation information based on the second spectral data and the calibration spectral data. The calibration spectral data is the spectral data corresponding to the optical path that does not pass through the drainage fluid in the negative pressure drainage bottle in the calibration posture.

[0043] The spectral correction coefficient acquisition module is used to query a pre-built mapping table of spectral data deviation and correction coefficient based on spectral data deviation information to obtain the spectral correction coefficient.

[0044] The spectral data correction module is used to obtain corrected spectral data based on the spectral data and spectral correction coefficients.

[0045] The drainage fluid parameter acquisition module is used to obtain drainage fluid parameter information based on the analysis of corrected spectral data.

[0046] This application provides a spectral analysis device for a negative pressure drainage bottle. First, spectral data deviation information is obtained based on second spectral data and calibration spectral data. Then, a spectral correction coefficient is obtained based on the spectral data deviation information, and the first spectral data is corrected based on the spectral correction coefficient to obtain corrected spectral data. Finally, drainage fluid parameter information is obtained based on the corrected spectral data analysis. Since the spectral data deviation information reflects the magnitude of the optical path change caused by the change in the posture of the negative pressure drainage bottle, and the spectral correction coefficient is obtained based on the spectral data deviation information, this application can correct the offset and error of the first spectral data caused by the change in the posture of the negative pressure drainage bottle. In other words, this application can effectively solve the problem of spectral data drift and error caused by the change in optical path when the posture of the negative pressure drainage bottle changes, and the change in optical path is a dynamic value. This effectively improves the spectral analysis effect and the accuracy of the drainage fluid parameters.

[0047] As can be seen from the above, the spectral analysis method and apparatus for a negative pressure drainage bottle provided in this application first obtains spectral data deviation information based on the second spectral data and the calibration spectral data, then obtains a spectral correction coefficient based on the spectral data deviation information, and corrects the first spectral data based on the spectral correction coefficient to obtain corrected spectral data. Finally, the drainage fluid parameter information is obtained based on the corrected spectral data analysis. Since the spectral data deviation information can reflect the magnitude of the optical path change caused by the change in the posture of the negative pressure drainage bottle, and the spectral correction coefficient is obtained based on the spectral data deviation information, this application can correct the offset and error of the first spectral data caused by the change in the posture of the negative pressure drainage bottle. That is, this application can effectively solve the problem of spectral data drift and error caused by the change in optical path when the posture of the negative pressure drainage bottle changes, and the change in optical path is a dynamic value, thereby effectively improving the spectral analysis effect and the accuracy of the drainage fluid parameters. Attached Figure Description

[0048] Figure 1 A flowchart of a spectral analysis method for a negative pressure drainage bottle provided in this application embodiment.

[0049] Figure 2 This is a schematic diagram of the structure of a spectral analysis device for a negative pressure drainage bottle provided in an embodiment of this application.

[0050] Attached reference numerals: 1. Spectral data acquisition module; 2. Spectral data deviation acquisition module; 3. Spectral correction coefficient acquisition module; 4. Spectral data correction module; 5. Drainage fluid parameter acquisition module. Detailed Implementation

[0051] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, and not all embodiments. The components of the embodiments of this application described and shown in the accompanying drawings can be arranged and designed in various different configurations. Therefore, the following detailed description of the embodiments of this application provided in the accompanying drawings is not intended to limit the scope of the claimed application, but merely represents selected embodiments of this application. All other embodiments obtained by those skilled in the art based on the embodiments of this application without inventive effort are within the scope of protection of this application.

[0052] It should be noted that similar reference numerals and letters in the following figures indicate similar items; therefore, once an item is defined in one figure, it does not need to be further defined and explained in subsequent figures. Furthermore, in the description of this application, terms such as "first," "second," etc., are used only to distinguish descriptions and should not be construed as indicating or implying relative importance.

[0053] Firstly, such as Figure 1 As shown, this application provides a spectral analysis method for a negative pressure drainage bottle, used to perform spectral analysis on the drainage fluid inside the negative pressure drainage bottle. The spectral analysis method for the negative pressure drainage bottle includes the following steps:

[0054] S1. When it is necessary to perform spectral analysis on the drainage fluid, acquire first spectral data and second spectral data. The first spectral data is the spectral data corresponding to the light path passing through the drainage fluid in the negative pressure drainage bottle, and the second spectral data is the spectral data corresponding to the light path not passing through the drainage fluid in the negative pressure drainage bottle.

[0055] S2. Obtain spectral data deviation information based on the second spectral data and the calibration spectral data. The calibration spectral data is the spectral data corresponding to the optical path that does not pass through the drainage fluid in the negative pressure drainage bottle in the calibration posture.

[0056] S3. Based on the spectral data deviation information, query the pre-built mapping table between spectral data deviation and correction coefficient to obtain the spectral correction coefficient;

[0057] S4. Obtain corrected spectral data based on spectral data and spectral correction coefficients;

[0058] S5. Obtain drainage fluid parameter information based on corrected spectral data analysis.

[0059] Step S1 can utilize existing light sources and spectrometers to acquire first and second spectral data. Specifically, the spectrometer splits the light beam emitted by the light source into two beams, one of which passes through the drainage fluid in the negative pressure drainage bottle, while the other beam avoids the drainage fluid (does not pass through the drainage fluid in the negative pressure drainage bottle). Step S2 can also utilize two existing light sources to acquire the first and second spectral data. Specifically, the two light sources have the same operating parameters, with the light beam emitted by one light source passing through the drainage fluid in the negative pressure drainage bottle, and the light beam emitted by the other light source not passing through the drainage fluid in the negative pressure drainage bottle. It should be understood that, due to gravity, the drainage fluid accumulates at the bottom of the negative pressure drainage bottle; therefore, this embodiment requires the height of the light beam to be greater than the liquid level of the drainage fluid in order to prevent the light beam from passing through the drainage fluid in the negative pressure drainage bottle. It should also be understood that, since the first spectral data is the spectral data corresponding to the light path passing through the drainage fluid in the negative pressure drainage bottle, and the second spectral data is the spectral data corresponding to the light path not passing through the drainage fluid in the negative pressure drainage bottle, the first spectral data can reflect the spectral characteristics of the light beam passing through the drainage fluid, and the second spectral data can reflect the spectral characteristics of the light beam not passing through the drainage fluid.

[0060] Step S2 can obtain spectral data deviation information by subtracting the second spectral data from the calibrated spectral data. The formula for calculating the spectral data deviation information is: Spectral data deviation information = Calibrated spectral data - Second spectral data. The calibrated spectral data in step S2 is obtained through pre-calibration. Specifically, the process of obtaining the calibrated spectral data can be as follows: adjusting the actual pose of the negative pressure drainage bottle to the calibrated pose; fixing the negative pressure drainage bottle to ensure that its pose does not change; ensuring that the light beam emitted by the light source does not pass through the drainage fluid inside the negative pressure drainage bottle; and then using the spectral data at this point as the calibrated spectral data. It should be understood that the calibrated pose of this embodiment can be designed by those skilled in the art based on experience or actual needs. It should also be understood that, since both the second spectral data and the calibration spectral data are spectral data corresponding to the optical path that does not pass through the drainage fluid inside the negative pressure drainage bottle, the difference between the second spectral data and the calibration spectral data is caused by the difference between the actual pose and the calibration pose of the negative pressure drainage bottle. In other words, the difference between the second spectral data and the calibration spectral data is only related to the pose difference of the negative pressure drainage bottle. Therefore, the spectral data deviation information obtained in step S2 can reflect the magnitude of the optical path change caused by the pose change of the negative pressure drainage bottle. That is, this embodiment is equivalent to using the spectral data deviation information to quantify the optical path change.

[0061] The mapping table between spectral data deviation and correction coefficient in step S3 stores multiple sets of spectral data deviations and their corresponding correction coefficients. The data source for this mapping table can be experimental data or simulation data. It should be understood that, since the spectral data deviation information in this embodiment can reflect the magnitude of the optical path change caused by the change in the pose of the negative pressure drainage bottle, and under the same conditions, the amount of optical path change is related to the amount of correction of the spectral data passing through the drainage, step S3 can obtain the spectral correction coefficient based on the spectral data deviation information, so as to use the spectral correction coefficient to correct the first spectral data in subsequent processes. This spectral correction coefficient can reflect the degree of correction of the first spectral data.

[0062] Step S4 corrects the first spectral data by multiplying it by a spectral correction coefficient to obtain corrected spectral data, i.e., the corrected spectral data is the corrected first spectral data. It should be understood that since the spectral correction coefficient in this embodiment is based on spectral data deviation information, and this deviation information reflects the magnitude of the optical path change caused by the change in the orientation of the negative pressure drainage bottle, step S4 can correct the offset and error of the first spectral data caused by the change in the orientation of the negative pressure drainage bottle. In other words, this application can effectively improve the accuracy of the spectral data corresponding to the optical path passing through the drainage fluid through steps S1-S4, so that the spectral data corresponding to the optical path passing through the drainage fluid can more accurately reflect the true spectral characteristics of the drainage fluid.

[0063] Step S5 can obtain drainage fluid parameter information based on existing drainage fluid parameter analysis models or drainage fluid parameter analysis algorithms by analyzing corrected spectral data. Preferably, step S5 obtains drainage fluid parameter information by inputting corrected spectral data into a pre-trained drainage fluid parameter analysis model. Taking the calculation of hemoglobin concentration in drainage fluid as an example, the drainage fluid parameter analysis model is established based on the standard spectral characteristics of hemoglobin. The drainage fluid parameter analysis model calculates the hemoglobin concentration value by analyzing the absorbance value of a specific wavelength in the corrected spectral data and combining it with the model algorithm.

[0064] This application provides a spectral analysis method for a negative pressure drainage bottle. First, spectral data deviation information is obtained based on second spectral data and calibration spectral data. Then, a spectral correction coefficient is obtained based on the spectral data deviation information, and the first spectral data is corrected based on the spectral correction coefficient to obtain corrected spectral data. Finally, drainage fluid parameter information is obtained based on the corrected spectral data. Since the spectral data deviation information reflects the magnitude of optical path change caused by the pose change of the negative pressure drainage bottle, and the spectral correction coefficient is obtained based on the spectral data deviation information, this application can correct the offset and error of the first spectral data caused by the pose change of the negative pressure drainage bottle. In other words, this application can effectively solve the problem of spectral data drift and error caused by the change in optical path when the pose of the negative pressure drainage bottle changes, and the change in optical path is a dynamic value. This effectively improves the spectral analysis effect and the accuracy of the drainage fluid parameters.

[0065] In some preferred embodiments, the first spectral data includes multiple sets of spectral wavelengths and their corresponding spectral intensities, and step S4 includes:

[0066] S41. Based on the spectral wavelength, query the pre-built mapping table of wavelength and adjustment coefficient to obtain multiple first spectral adjustment coefficients, each spectral wavelength corresponding to a first spectral adjustment coefficient;

[0067] S42. Obtain the corrected spectral intensity corresponding to each spectral wavelength based on the spectral correction coefficient, the spectral intensity corresponding to each spectral wavelength, and the first spectral adjustment coefficient. The corrected spectral data is the set of all corrected spectral intensities.

[0068] The mapping table between wavelength and adjustment coefficient in step S41 can be a data table stored in memory or a cloud server. This mapping table records multiple sets of wavelengths and their corresponding adjustment coefficients. Therefore, step S41 can determine the first spectral adjustment coefficient corresponding to each spectral wavelength by querying this mapping table according to the spectral wavelength. For example, the mapping table can be set as follows: the adjustment coefficient for wavelengths less than or equal to 380 nm is 0.65, the adjustment coefficient for wavelengths greater than 380 nm and less than or equal to 450 nm is 0.85, the adjustment coefficient for wavelengths greater than 450 nm and less than or equal to 580 nm is 1.1, and the adjustment coefficient for wavelengths greater than 580 nm is 0.8. If the spectral wavelength is 270 nm, then its corresponding first spectral adjustment coefficient is 0.65. Step S42 can obtain the corrected spectral intensity corresponding to the spectral wavelength by multiplying the spectral coefficient corresponding to the spectral wavelength, the first spectral adjustment coefficient, and the spectral correction coefficient. That is, the formula for calculating the corrected spectral intensity is: Corrected spectral intensity of the i-th spectral wavelength = spectral intensity corresponding to the i-th spectral wavelength × first spectral adjustment coefficient corresponding to the i-th spectral wavelength × spectral correction coefficient. Since the drainage fluid contains multiple components, and different components have different absorption and scattering degrees for different wavelengths of light, this embodiment first obtains the first spectral adjustment coefficient corresponding to different spectral wavelengths, and then adjusts the corresponding spectral intensity based on the first spectral adjustment coefficient. Therefore, this embodiment is equivalent to using different correction strategies when correcting the spectral intensity corresponding to different spectral wavelengths. Thus, this embodiment can effectively improve the accuracy of the corrected spectral data, thereby effectively improving the accuracy of the final obtained drainage fluid parameter information.

[0069] In some preferred embodiments, step S4 further includes steps performed between steps S41 and S42:

[0070] S43. Use the image acquisition component to acquire the image information of the negative pressure drainage bottle, and analyze whether there are air bubbles in the drainage fluid based on the image information of the negative pressure drainage bottle. If yes, proceed to step S44; otherwise, proceed to step S42.

[0071] S44. Based on the image information of the negative pressure drainage bottle, obtain bubble parameter information. Then, based on the bubble parameter information, query the pre-constructed mapping relationship table between bubble parameters and adjustment coefficient set to obtain the adjustment coefficient set. The adjustment coefficient set includes the second spectral adjustment coefficient corresponding to different spectral wavelengths. The bubble parameter information includes the number of bubbles and the average size of bubbles.

[0072] When air bubbles are detected in the drainage fluid, step S42 includes:

[0073] S421. Obtain the corrected spectral intensity corresponding to each spectral wavelength based on the spectral correction coefficient, the spectral intensity corresponding to each spectral wavelength, the first spectral adjustment coefficient, and the second spectral adjustment coefficient.

[0074] In this embodiment, the image acquisition component can be an existing camera. Step S43 can utilize existing image recognition technology to identify air bubbles (equivalent to the target object of image recognition technology) within the negative pressure drainage bottle image information to analyze whether air bubbles exist in the drainage fluid. When air bubbles are detected in the drainage fluid, step S43 can utilize existing image recognition and image analysis technologies to analyze and obtain air bubble parameter information based on the negative pressure drainage bottle image information. This air bubble parameter information includes the number of air bubbles and the average size of the air bubbles. The number of air bubbles is the total number of air bubbles in the drainage fluid, and the average size of the air bubbles is the average size of all air bubbles in the drainage fluid. The mapping relationship table between air bubble parameters and adjustment coefficient sets in step S44 stores multiple sets of air bubble parameters and their corresponding adjustment coefficient sets. Each adjustment coefficient set includes second spectral adjustment coefficients for different spectral wavelengths. Therefore, the adjustment coefficient set obtained in step S43 includes second spectral adjustment coefficients corresponding to different spectral wavelengths. When air bubbles are detected in the drainage fluid, this embodiment obtains the corrected spectral intensity for each wavelength based on the spectral correction coefficient, the spectral intensity corresponding to each wavelength, the first spectral adjustment coefficient, and the second spectral adjustment coefficient. Conversely, when no air bubbles are detected in the drainage fluid, this embodiment obtains the corrected spectral intensity for each wavelength based on the spectral correction coefficient, the spectral intensity corresponding to each wavelength, and the first spectral adjustment coefficient. Since the presence of air bubbles in the drainage fluid causes light scattering, reflection, or refraction, these processes all reduce the accuracy of the spectral intensity. Furthermore, the degree of scattering, reflection, and refraction by the bubbles may differ for different wavelengths. This embodiment obtains a set of adjustment coefficients including the second spectral adjustment coefficients corresponding to different wavelengths. Therefore, this embodiment is equivalent to adaptively adjusting the spectral intensity based on the specific parameters of the air bubbles when they are present in the drainage fluid, with different degrees of adaptive adjustment for different wavelengths. Thus, this embodiment can further improve the accuracy of the spectral intensity, thereby further improving the accuracy of the corrected spectral data. It should be understood that this embodiment is equivalent to using a spectral correction coefficient to correct the spectral deviation caused by the change in the position of the negative pressure drainage bottle, using a first spectral adjustment coefficient to correct the spectral differences at different wavelengths, and using a second spectral adjustment coefficient to correct the spectral error introduced by the bubble, so as to improve the accuracy and reliability of the corrected spectral data.

[0075] In some preferred embodiments, step S43 includes:

[0076] S431. Use the image acquisition component to acquire image information of the negative pressure drainage bottle;

[0077] S432. Preprocess the image information of the negative pressure drainage bottle. The preprocessing includes grayscale processing, contrast enhancement and noise reduction.

[0078] S433. Use an edge detection algorithm to perform edge detection on the preprocessed negative pressure drainage bottle image information to obtain the drainage fluid area;

[0079] S434. Use the Holf circle transformation algorithm to identify air bubbles in the drainage fluid area to analyze whether there are air bubbles in the drainage fluid. If yes, proceed to step S44; otherwise, proceed to step S42.

[0080] The grayscale conversion process in step S432 converts the negative pressure drainage bottle image information from a color image to a grayscale image, simplifying the image data and reducing the complexity of subsequent processing. The contrast enhancement process in step S432 makes the boundaries between bubbles and drainage fluid, as well as between drainage fluid and the negative pressure drainage bottle, clearer in the grayscale image. The noise reduction process in step S432 reduces noise in the grayscale image, improving its quality. Step S432 can employ existing Gaussian filtering or median filtering methods for noise reduction. The edge detection algorithm in step S433 can be an existing algorithm. This edge detection algorithm can locate the boundary of the drainage fluid by analyzing the pixel gradient changes in the preprocessed negative pressure drainage bottle image information, thereby obtaining the drainage fluid region. The Holf circle transformation algorithm in step S434 is a mature algorithm capable of searching for a set of pixels in an image that conforms to circular features. Since the cross-sectional shape of bubbles in the drainage fluid is usually circular or approximately circular, and the Holf circle transformation algorithm can search for a set of pixels in the image that conforms to circular features, if the Holf circle transformation algorithm detects circular features within the drainage fluid area, it indicates the presence of bubbles in the drainage fluid; conversely, if the Holf circle transformation algorithm does not detect circular features within the drainage fluid area, it indicates the absence of bubbles in the drainage fluid. This embodiment is equivalent to performing grayscale processing, contrast enhancement, and noise reduction on the negative pressure drainage bottle image information before analyzing whether bubbles exist in the drainage fluid. Grayscale processing simplifies image data and reduces the complexity of subsequent processing; contrast enhancement makes the boundaries in the image clearer; and noise reduction improves image quality. Therefore, this embodiment can effectively improve the accuracy of bubble recognition.

[0081] In some preferred embodiments, the edge detection algorithm is the Canny edge detection algorithm. This embodiment utilizes the Canny edge detection algorithm to perform edge detection on the preprocessed negative pressure drainage bottle image information. Since the Canny edge detection algorithm can effectively suppress noise interference and accurately locate edges in the image through multi-level filtering and gradient calculation, this embodiment can effectively improve the accuracy of the drainage fluid area, providing a more accurate target area for bubble identification. This effectively avoids situations where some bubbles are not correctly identified due to the obtained drainage fluid area being smaller than the actual drainage fluid area, or drainage fluid containing bubbles being misjudged as not containing bubbles. In other words, this embodiment can effectively improve the accuracy of bubble identification.

[0082] In some preferred embodiments, step S1 includes:

[0083] S11. When it is necessary to perform spectral analysis on the drainage fluid, acquire the first spectral data and the second spectral data;

[0084] S12. Perform smoothing filtering on the first and second spectral data to reduce noise interference.

[0085] The smoothing filtering process in step S12 can be an existing signal processing technique. Because the acquisition of spectral data is affected by factors such as ambient light fluctuations and electronic device noise, the acquired first and second spectral data will inevitably contain noise. This noise reduces the signal-to-noise ratio of the first and second spectral data and affects their quality. Since step S12 can effectively reduce random noise and improve the signal-to-noise ratio of the first and second spectral data by performing smoothing filtering, this example can effectively improve the accuracy and reliability of the first and second spectral data, providing more accurate and reliable spectral data for subsequent processing steps, thereby further improving the spectral analysis effect and the accuracy of the drainage fluid parameters.

[0086] In some preferred embodiments, the spectral analysis method for the negative pressure drainage bottle further includes the following steps:

[0087] S6. Obtain the height of the drainage fluid, and generate an alarm message when the difference between the height of the drainage fluid and the height of the optical path that does not pass through the drainage fluid in the negative pressure drainage bottle is less than the height threshold.

[0088] Step S6 can acquire the drainage fluid level height using existing liquid level monitoring components (e.g., liquid level sensor). The height threshold in this embodiment can be a value set by those skilled in the art based on experience or actual needs. The alarm information in this embodiment is used to remind medical staff that the drainage fluid level is too high, enabling them to take appropriate measures. This alarm information can take the form of an audible alarm, a visual alarm, or text prompts on a display screen. Since a difference between the drainage fluid level height and the height of the optical path that does not pass through the drainage fluid in the negative pressure drainage bottle is less than the height threshold, it indicates that the drainage fluid level is too high. The optical path corresponding to the second spectral data may have the risk of passing through the drainage fluid. If the optical path corresponding to the second spectral data passes through the drainage fluid, the difference between the second spectral data and the calibrated spectral data will not be solely related to the pose difference of the negative pressure drainage bottle. Therefore, this embodiment can minimize the possibility that the difference between the second spectral data and the calibrated spectral data will not be solely related to the pose difference of the negative pressure drainage bottle due to the excessively high drainage fluid level, resulting in unreliable spectral analysis results and drainage fluid parameters.

[0089] In some preferred embodiments, the height threshold is determined based on the actual pose of the negative pressure drainage bottle. This embodiment determines the height threshold based on the actual pose of the negative pressure drainage bottle, meaning it is equivalent to making the height threshold a dynamically determined value based on the actual pose of the bottle, rather than a fixed value. This embodiment obtains the actual pose of the negative pressure drainage bottle by using a pose sensor to monitor its tilt angle and orientation. It can then query a pre-built mapping table between the bottle's pose and the height threshold, which records the height threshold corresponding to different poses. Therefore, this embodiment can quickly determine the height threshold matching the current actual pose of the negative pressure drainage bottle by querying this mapping table based on the bottle's actual pose. Since the height threshold in this embodiment is determined based on the actual pose of the negative pressure drainage bottle, meaning it always adapts to the bottle's actual pose, this embodiment effectively reduces the occurrence of missed or false alarms, thereby effectively improving the reliability of alarm information.

[0090] In some preferred embodiments, the drainage fluid parameters include hemoglobin concentration and bilirubin concentration. In this embodiment, the hemoglobin concentration reflects postoperative bleeding, and the bilirubin concentration reflects the liver and gallbladder recovery status.

[0091] As can be seen from the above, the spectral analysis method for a negative pressure drainage bottle provided in this application first obtains spectral data deviation information based on the second spectral data and the calibration spectral data, then obtains a spectral correction coefficient based on the spectral data deviation information, and corrects the first spectral data based on the spectral correction coefficient to obtain corrected spectral data. Finally, the drainage fluid parameter information is obtained based on the analysis of the corrected spectral data. Since the spectral data deviation information can reflect the magnitude of the optical path change caused by the change in the pose of the negative pressure drainage bottle, and the spectral correction coefficient is obtained based on the spectral data deviation information, this application can correct the offset and error of the first spectral data caused by the change in the pose of the negative pressure drainage bottle. That is, this application can effectively solve the problem of spectral data drift and error caused by the change in optical path when the pose of the negative pressure drainage bottle changes, and the change in optical path is a dynamic value, thereby effectively improving the spectral analysis effect and the accuracy of the drainage fluid parameters.

[0092] Secondly, such as Figure 2 As shown, this application also provides a spectroscopic analysis device for a negative pressure drainage bottle, used for spectroscopic analysis of the drainage fluid inside the negative pressure drainage bottle. The spectroscopic analysis device for the negative pressure drainage bottle includes:

[0093] The spectral data acquisition module 1 is used to acquire first spectral data and second spectral data when spectral analysis of the drainage fluid is required. The first spectral data is the spectral data corresponding to the light path passing through the drainage fluid in the negative pressure drainage bottle, and the second spectral data is the spectral data corresponding to the light path not passing through the drainage fluid in the negative pressure drainage bottle.

[0094] The spectral data deviation acquisition module 2 is used to acquire spectral data deviation information based on the second spectral data and the calibration spectral data. The calibration spectral data is the spectral data corresponding to the optical path that does not pass through the drainage fluid in the negative pressure drainage bottle in the calibration posture.

[0095] The spectral correction coefficient acquisition module 3 is used to query a pre-built mapping table of spectral data deviation and correction coefficient based on the spectral data deviation information to obtain the spectral correction coefficient.

[0096] Spectral data correction module 4 is used to obtain corrected spectral data based on spectral data and spectral correction coefficients;

[0097] The drainage fluid parameter acquisition module 5 is used to acquire drainage fluid parameter information based on the analysis of corrected spectral data.

[0098] This application provides a spectral analysis device for a negative pressure drainage bottle, comprising a spectral data acquisition module 1, a spectral data deviation acquisition module 2, a spectral correction coefficient acquisition module 3, a spectral data correction module 4, and a drainage fluid parameter acquisition module 5. This embodiment of the spectral analysis device for a negative pressure drainage bottle is used to perform the steps in the spectral analysis method for a negative pressure drainage bottle provided in the first aspect above. The principle of this embodiment of the spectral analysis device for a negative pressure drainage bottle is the same as the principle of the spectral analysis method for a negative pressure drainage bottle provided in the first aspect above, and will not be discussed in detail here.

[0099] As can be seen from the above, the spectral analysis method and apparatus for a negative pressure drainage bottle provided in this application first obtains spectral data deviation information based on the second spectral data and the calibration spectral data, then obtains a spectral correction coefficient based on the spectral data deviation information, and corrects the first spectral data based on the spectral correction coefficient to obtain corrected spectral data. Finally, the drainage fluid parameter information is obtained based on the corrected spectral data analysis. Since the spectral data deviation information can reflect the magnitude of the optical path change caused by the change in the posture of the negative pressure drainage bottle, and the spectral correction coefficient is obtained based on the spectral data deviation information, this application can correct the offset and error of the first spectral data caused by the change in the posture of the negative pressure drainage bottle. That is, this application can effectively solve the problem of spectral data drift and error caused by the change in optical path when the posture of the negative pressure drainage bottle changes, and the change in optical path is a dynamic value, thereby effectively improving the spectral analysis effect and the accuracy of the drainage fluid parameters.

[0100] In the embodiments provided in this application, it should be understood that the disclosed apparatus and method can be implemented in other ways. The apparatus embodiments described above are merely illustrative. For example, the division of the above units is only a logical functional division, and there may be other division methods in actual implementation. Furthermore, multiple units or components may be combined or integrated into another robot, or some features may be ignored or not executed. Additionally, the coupling or direct coupling or communication connection shown or discussed may be through some communication interface; the indirect coupling or communication connection between devices or units may be electrical, mechanical, or other forms.

[0101] In addition, the functional modules in the various embodiments of this application can be integrated together to form an independent part, or each module can exist independently, or two or more modules can be integrated to form an independent part.

[0102] In this document, relational terms such as first and second are used only to distinguish one entity or operation from another entity or operation, without necessarily requiring or implying any such actual relationship or order between these entities or operations.

[0103] The above description is merely an embodiment of this application and is not intended to limit the scope of protection of this application. Various modifications and variations can be made to this application by those skilled in the art. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of this application should be included within the scope of protection of this application.

Claims

1. A spectral analysis method for a negative pressure drainage bottle, used for spectral analysis of the drainage fluid inside the negative pressure drainage bottle, characterized in that, The spectral analysis method for the negative pressure drainage bottle includes the following steps: S1. When it is necessary to perform spectral analysis on the drainage fluid, first spectral data and second spectral data are obtained. The first spectral data is the spectral data corresponding to the light path passing through the drainage fluid in the negative pressure drainage bottle, and the second spectral data is the spectral data corresponding to the light path not passing through the drainage fluid in the negative pressure drainage bottle. S2. Obtain spectral data deviation information based on the second spectral data and the calibration spectral data, wherein the calibration spectral data is the spectral data corresponding to the optical path that does not pass through the drainage fluid in the negative pressure drainage bottle in the calibration posture. S3. Based on the spectral data deviation information, query the pre-constructed mapping table of spectral data deviation and correction coefficient to obtain the spectral correction coefficient; S4. Obtain corrected spectral data based on the spectral data and the spectral correction coefficient; S5. Obtain drainage fluid parameter information based on the corrected spectral data analysis.

2. The spectral analysis method for the negative pressure drainage bottle according to claim 1, characterized in that, The first spectral data includes multiple sets of spectral wavelengths and their corresponding spectral intensities. Step S4 includes: S41. Based on the spectral wavelength, query the pre-constructed mapping table of wavelength and adjustment coefficient to obtain multiple first spectral adjustment coefficients, each of the spectral wavelengths corresponding to one first spectral adjustment coefficient; S42. Obtain the corrected spectral intensity corresponding to each spectral wavelength based on the spectral correction coefficient, the spectral intensity corresponding to each spectral wavelength, and the first spectral adjustment coefficient. The corrected spectral data is a set of all the corrected spectral intensities.

3. The spectral analysis method for the negative pressure drainage bottle according to claim 2, characterized in that, Step S4 also includes steps performed between steps S41 and S42: S43. Use the image acquisition component to acquire the image information of the negative pressure drainage bottle, and analyze whether there are air bubbles in the drainage fluid based on the image information of the negative pressure drainage bottle. If yes, proceed to step S44; otherwise, proceed to step S42. S44. Based on the image information of the negative pressure drainage bottle, bubble parameter information is obtained. Then, based on the bubble parameter information, a pre-constructed mapping table of bubble parameters and adjustment coefficient set is queried to obtain the adjustment coefficient set. The adjustment coefficient set includes the second spectral adjustment coefficients corresponding to different spectral wavelengths. The bubble parameter information includes the number of bubbles and the average size of bubbles. When air bubbles are detected in the drainage fluid, step S42 includes: S421. Obtain the corrected spectral intensity corresponding to each spectral wavelength based on the spectral correction coefficient, the spectral intensity corresponding to each spectral wavelength, the first spectral adjustment coefficient, and the second spectral adjustment coefficient.

4. The spectral analysis method for the negative pressure drainage bottle according to claim 3, characterized in that, Step S43 includes: S431. Use the image acquisition component to acquire image information of the negative pressure drainage bottle; S432. Preprocess the image information of the negative pressure drainage bottle, the preprocessing including grayscale processing, contrast enhancement and noise reduction processing; S433. Use an edge detection algorithm to perform edge detection on the preprocessed negative pressure drainage bottle image information to obtain the drainage fluid area; S434. Use the Holf circle transformation algorithm to identify air bubbles in the drainage fluid area to analyze whether there are air bubbles in the drainage fluid. If yes, proceed to step S44; otherwise, proceed to step S42.

5. The spectral analysis method for the negative pressure drainage bottle according to claim 4, characterized in that, The edge detection algorithm is the Canny edge detection algorithm.

6. The spectral analysis method for the negative pressure drainage bottle according to claim 1, characterized in that, Step S1 includes: S11. When it is necessary to perform spectral analysis on the drainage fluid, acquire the first spectral data and the second spectral data; S12. Perform smoothing filtering on the first spectral data and the second spectral data to reduce noise interference.

7. The spectral analysis method for the negative pressure drainage bottle according to claim 1, characterized in that, The spectral analysis method for the negative pressure drainage bottle also includes the following steps: S6. Obtain the height of the drainage fluid, and generate an alarm message when the difference between the height of the drainage fluid and the height of the optical path that does not pass through the drainage fluid in the negative pressure drainage bottle is less than a height threshold.

8. The spectral analysis method for the negative pressure drainage bottle according to claim 7, characterized in that, The height threshold is determined based on the actual position of the negative pressure drainage bottle.

9. The spectral analysis method for the negative pressure drainage bottle according to claim 1, characterized in that, The drainage fluid parameters include hemoglobin concentration and bilirubin concentration.

10. A spectroscopic analysis device for a negative pressure drainage bottle, used for spectroscopic analysis of the drainage fluid inside the negative pressure drainage bottle, characterized in that, The spectral analysis device for the negative pressure drainage bottle includes: The spectral data acquisition module is used to acquire first spectral data and second spectral data when it is necessary to perform spectral analysis on the drainage fluid. The first spectral data is the spectral data corresponding to the light path passing through the drainage fluid in the negative pressure drainage bottle, and the second spectral data is the spectral data corresponding to the light path not passing through the drainage fluid in the negative pressure drainage bottle. The spectral data deviation acquisition module is used to acquire spectral data deviation information based on the second spectral data and the calibration spectral data, wherein the calibration spectral data is the spectral data corresponding to the optical path that does not pass through the drainage fluid in the negative pressure drainage bottle in the calibration orientation; The spectral correction coefficient acquisition module is used to query a pre-built mapping table of spectral data deviation and correction coefficient based on the spectral data deviation information to obtain the spectral correction coefficient. A spectral data correction module is used to obtain corrected spectral data based on the spectral data and the spectral correction coefficients; The drainage fluid parameter acquisition module is used to obtain drainage fluid parameter information based on the corrected spectral data analysis.

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