Intelligent urinary surgery postoperative care equipment and system

Abstract

The embodiment of the invention discloses an intelligent urinary surgery postoperative nursing device and system, and the nursing device comprises a nursing device body which is used for providing a postoperative rest environment for a patient; the fixing part is arranged on the nursing equipment body and used for fixing a urine bag of a patient; the image acquisition equipment is arranged near the fixing part and is used for acquiring an image of the urine bag; the physical sign acquisition equipment is arranged on the equipment body and is used for acquiring vital sign parameters of a patient; the analysis equipment is used for obtaining urine sediment, urine color and urine volume data according to the urine bag image and determining posture parameters of the nursing equipment body according to the urine sediment, the urine color, the urine volume data and the vital sign parameters; the adjusting component is used for adjusting the posture of the nursing equipment body according to the posture parameters of the nursing equipment body.

Description

Technical Field

[0001] The present invention relates to the field of medical technology, and in particular, to an intelligent postoperative nursing device and system for urology surgery. Background Art

[0002] Postoperative nursing in urology is a crucial link in the patient's rehabilitation process, which is of great significance for promoting the recovery of the patient's physical function, preventing complications, and reducing the readmission rate. The postoperative nursing device is a medical device specially designed to assist patients in recovering after surgery. By providing comfortable support and adjustable postures, it helps patients maintain the correct posture, promotes blood circulation, relieves pain, and improves the efficiency of postoperative recovery.

[0003] Although the existing postoperative nursing devices have made certain progress in design and function, there are still some problems and deficiencies: Most of the existing nursing devices have relatively single functions and lack intelligent adjustment and monitoring functions; Many nursing devices require manual adjustment of the angles of the backrest and leg support, which may be very difficult for patients with limited mobility; Moreover, there is a lack of customized design for different types of urology surgeries and cannot meet the special needs of different patient groups.

[0004] Therefore, designing an intelligent postoperative nursing device for urology surgery is an urgent problem to be solved by those skilled in the art. Summary of the Invention

[0005] In view of this, an embodiment of the present invention provides an intelligent postoperative nursing device and system for urology surgery, which intelligently adjusts the posture of the nursing device by monitoring the urine data and vital sign data of the patient, thereby promoting the postoperative recovery of the patient.

[0006] To achieve the purpose of the present invention, the following technical solutions are adopted:

[0007] In a first aspect, an intelligent postoperative nursing device for urology surgery, characterized by comprising:

[0008] A nursing device body for providing a postoperative rest environment for the patient;

[0009] A fixing component provided on the nursing device body for fixing the patient's urine bag;

[0010] An image acquisition device provided near the fixing component for acquiring an image of the urine bag;

[0011] A vital sign acquisition device provided on the device body for acquiring the vital sign parameters of the patient;

[0012] An analysis device, including an image analysis module and a posture analysis module, wherein the image analysis module is used to obtain urine sediment, urine color and urine volume data based on the urine bag image, and the posture analysis module is used to determine the posture parameter of the nursing device body according to the urine sediment, the urine color, the urine volume data, the vital sign parameters and the posture parameter of the current nursing device body;

[0013] An adjustment component, used to adjust the posture of the nursing device body according to the posture parameter of the nursing device body.

[0014] Optionally, the nursing device body is a recovery chair.

[0015] Optionally, the image acquisition module includes a camera, the camera corresponds to the urine bag and is used to acquire the urine bag image, and the camera sends the acquired urine bag image to the analysis device.

[0016] Optionally, the sign acquisition module includes a temperature sensor, a sphygmomanometer and a heart rate monitor, which are respectively used to acquire the body temperature, blood pressure and heart rate data of the patient.

[0017] Optionally, the image analysis module is a YOLO-based model. The image analysis module includes a backbone network, a neck network and a head network. The head network includes a urine bag scale detection branch, a liquid level detection branch, a color detection branch and a sediment detection branch. The urine bag scale detection branch, the liquid level detection branch, the color detection branch and the sediment detection branch share the features of the neck network, and the head network outputs the urine bag scale, the urine sediment, the urine color and the liquid level position.

[0018] Optionally, the neck network includes a feature extraction module and a feature fusion module. The feature extraction module includes a plurality of context anchor modules, and the plurality of context anchor modules are used to extract features from the feature maps of different layers of the backbone network. The feature fusion module includes a feature refinement module and a feature enhancement module. The feature refinement module fuses the high-level features processed by the feature extraction module with the low-level features, and the feature enhancement module fuses the high-level features processed by the feature extraction module with the features fused by the feature refinement module. The features fused by the feature refinement module and the feature enhancement module are input to each branch of the head network.

[0019] Optionally, the urine volume data is determined according to the urine bag scale and the liquid level position. If the liquid level position is at the scale line, the scale line is directly used as the urine volume data. If the liquid level position is between two adjacent scale lines, the urine volume data is determined by proportional calculation according to the distance between the liquid level position and the two scale lines.

[0020] Optionally, the attitude parameters of the nursing device body include the backrest angle, the leg support height, and the headrest position.

[0021] Optionally, the attitude analysis module includes an input layer, an LSTM layer, a feature fusion layer, a fully connected layer, and an output layer. The input features of the input layer include the urine sediment, the urine color, the urine volume data, the vital sign parameters, and the attitude parameters of the current nursing device body. The LSTM layer processes the vital sign parameters to obtain extracted features. The feature fusion layer fuses the extracted features with the urine sediment, the urine color, the urine volume data, and the attitude parameters of the current nursing device body to obtain fused features. The fully connected layer extracts features from the fused features to obtain output features. The output layer obtains the attitude parameters of the nursing device body according to the output features.

[0022] Optionally, the adjustment component includes a controller and a power component. The controller receives the attitude parameters of the nursing device body to generate a control signal. The power component drives a motor or a hydraulic rod according to the control signal to adjust the attitude of the nursing device body.

[0023] In a second aspect, an intelligent postoperative nursing system for urology is characterized by comprising:

[0024] The device according to the first aspect;

[0025] An information transmission module for transmitting urine sediment, urine color, urine volume data, and vital sign parameters to a host;

[0026] A host for storing and monitoring the urine sediment, the urine color, the urine volume data, and the vital sign parameters, generating a reminder signal when the data parameters meet preset conditions, and sending the reminder signal to a reminder module;

[0027] A reminder module for generating light or sound information according to the reminder signal to remind patients and medical staff to handle it.

[0028] Compared with the prior art, the present invention has the following beneficial effects:

[0029] The intelligent postoperative nursing equipment and system provided by the present invention can intelligently adjust the posture of the nursing equipment according to the urine bag image and vital sign data of the patient, promoting the postoperative recovery of the patient; the designed image analysis module can obtain the urine information of the patient by detecting the urine bag of the patient, reducing the complexity of urine detection, and adjusting the nursing equipment in combination with the urine information of the patient to better meet the special needs of the patient group undergoing urological surgery; the designed posture analysis module can accurately predict the posture more beneficial to the patient's recovery by integrating the urine information and vital sign data of the patient, so as to adjust the recovery equipment and help the patient maintain the correct posture.

[0030] The technical solution of the present invention will be further described in detail below with reference to the accompanying drawings and embodiments. BRIEF DESCRIPTION OF THE DRAWINGS

[0031] By describing the embodiments of the present invention in more detail in conjunction with the accompanying drawings, the above and other objects, features, and advantages of the present invention will become more apparent. The accompanying drawings are used to provide a further understanding of the embodiments of the present invention, and constitute a part of the specification, and are used to explain the present invention together with the embodiments of the present invention, and do not constitute a limitation to the present invention. In the accompanying drawings, the same reference numerals generally represent the same components or steps.

[0032] Figure 1 It is a schematic structural diagram of an intelligent postoperative nursing equipment for urology provided by an exemplary embodiment of the present invention.

[0033] Figure 2 It is a schematic structural diagram of an intelligent postoperative nursing system for urology provided by an exemplary embodiment of the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0034] Next, exemplary embodiments of the present invention will be described in detail with reference to the accompanying drawings. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments of the present invention. It should be understood that the present invention is not limited by the exemplary embodiments described herein.

[0035] It should be noted that: unless otherwise specifically stated, the relative arrangement of components and steps, numerical expressions, and numerical values set forth in these embodiments do not limit the scope of the present invention.

[0036] Those skilled in the art can understand that terms such as "first" and "second" in the embodiments of the present invention are only used to distinguish different steps, devices, or modules, etc., and do not represent any specific technical meaning, nor do they indicate an inevitable logical order between them.

[0037] It should also be understood that in the embodiments of the present invention, "a plurality" may refer to two or more, and "at least one" may refer to one, two, or more.

[0038] It should also be understood that for any component, data, or structure mentioned in the embodiments of the present invention, without clear limitation or contrary indication in the context, it is generally understood as one or more.

[0039] Embodiment 1

[0040] As Figure 1 shown, this embodiment provides an intelligent postoperative nursing device 10 for urology. To achieve the above objectives, the present invention is realized through the following technical solutions:

[0041] A nursing device body 100 for providing a postoperative rest environment for patients;

[0042] A fixing component 110 provided on the nursing device body for fixing the patient's urine bag;

[0043] An image acquisition device 120 provided near the fixing component for acquiring the urine bag image;

[0044] A vital sign acquisition device 130 provided on the device body for acquiring the vital sign parameters of the patient;

[0045] An analysis device 140 includes an image analysis module 141 and a posture analysis module 142. The image analysis module is used to obtain urine sediment, urine color, and urine volume data based on the urine bag image. The posture analysis module is used to determine the posture parameters of the nursing device body according to the urine sediment, the urine color, the urine volume data, the vital sign parameters, and the current posture parameters of the nursing device body;

[0046] An adjustment component 150 for adjusting the posture of the nursing device body according to the posture parameters of the nursing device body.

[0047] In this embodiment, the nursing device body 100 is a recovery chair. A recovery chair is a rehabilitation assistance device specifically designed for postoperative patients, mainly used to help patients rest, recover, and perform early activities better during the postoperative recovery period. It can adjust the angle to help patients perform limb activities or joint training, promoting blood circulation and muscle recovery.

[0048] The fixing component 110 can be a hook provided on the nursing device body 100. When the patient rests on the nursing device body 100, the urine bag is fixed on the fixing component 110. Among them, after urological surgery, the patient may be unable to urinate independently due to reasons such as anesthesia, surgical trauma, or physical weakness. The urine bag can effectively drain urine, avoid overfilling of the bladder. By draining urine through the urine bag, the retention time of urine in the bladder can be reduced, and the risk of infection can be lowered. Moreover, after some urological surgeries, such as bladder surgery or ureteral surgery, the urine bag can reduce the irritation of urine to the wound and promote wound healing. Therefore, the patient needs to wear the urine bag at all times after surgery. Setting the fixing component 110 on the nursing device body 100 can meet the needs of urological surgery patients.

[0049] The image acquisition device 120 includes a camera. The camera is corresponding to the urine bag to ensure that the entire urine bag is within the acquisition range of the image acquisition device 120. The camera sends the acquired urine bag image data to the analysis device 140.

[0050] The vital sign acquisition module 130 includes a body temperature sensor, a sphygmomanometer, and a heart rate monitor, which are respectively used to acquire the body temperature, blood pressure, and heart rate data of the patient. Among them, after urological surgery, the speed of the heart rate reflects the patient's wound pain, anxiety, blood loss, arrhythmia, or abnormal heart function. The blood pressure reflects the postoperative states such as blood loss, insufficient blood volume, and uncomfortable posture. And the body temperature reflects the body's response to surgical trauma and inflammatory response. Therefore, the vital sign parameters of the patient are closely related to the physical condition and recovery status of the postoperative patient.

[0051] The image analysis module 141 in the analysis device 140 is a YOLO-based model. YOLO (You Only Look Once) is a real-time object detection model based on deep learning. The core idea of YOLO is to regard the object detection task as a single regression problem, and complete the localization and classification of the object through a single forward propagation, thus achieving extremely high detection speed and playing an important role in many practical applications such as autonomous driving, security monitoring, and medical imaging. Using the YOLO model as the basis of the image analysis module 141 to detect urine from the image aspect can improve the convenience of detection.

[0052] To match the analysis scenario of a patient's urine and more accurately detect urine information, in this embodiment, the standard YOLO model is improved. Specifically, the image analysis module 141 includes a backbone network, a neck network, and a head network. The head network includes a urine bag scale detection branch, a liquid level detection branch, a color detection branch, and a sediment detection branch. The urine bag scale detection branch, the liquid level detection branch, the color detection branch, and the sediment detection branch share the features of the neck network. The head network outputs the urine bag scale, the urine sediment, the urine color, and the liquid level position.

[0053] Among them, the backbone network is the basic part of the YOLO model and is used to extract multi-scale feature maps. In this embodiment, the backbone network extracts low-scale feature maps, medium-scale feature maps, and high-scale feature maps through the P3 layer, P4 layer, and P5 layer respectively, so as to provide rich feature information for the detection tasks of the neck network.

[0054] The neck network includes a feature extraction module and a feature fusion module. The feature extraction module includes multiple context anchor modules. The multiple context anchor modules are used to extract features from the feature maps of different layers of the backbone network. After the feature maps output by the P3 layer, P4 layer, and P5 layer of the backbone network are extracted by the context anchor modules respectively, they can capture long-range context information and enhance the central features, thereby improving the detection accuracy.

[0055] Among them, the context anchor module is an attention mechanism module. The core idea is to capture long-range context information through strip convolution and is suitable for detecting small targets because the features of these targets are usually distributed in local areas of the feature map and stronger context information is required to improve the detection accuracy. Then, in this embodiment, since the sediments in urine are usually tiny particles or flocs and the scale of the detected objects is small, the context anchor module can be used to better detect the sediments in urine.

[0056] The feature fusion module includes a feature refinement module and a feature enhancement module. The feature refinement module includes a dynamic sampling module and a selective feature fusion module. The feature refinement module uses the dynamic sampling module and the selective feature fusion module to fuse the high-level features and low-level features processed by the feature extraction module. The feature enhancement module includes a two-dimensional convolution module and a selective feature fusion module. The feature enhancement module uses the two-dimensional convolution module and the selective feature fusion module to fuse the low-level features and high-level features processed by the feature extraction module. The features fused by the feature refinement module and the feature enhancement module are input to each branch of the head network.

[0057] The feature fusion module includes two feature refinement modules and two feature enhancement modules. One feature refinement module fuses the feature map of the P5 layer and the feature map of the P4 layer processed by the feature extraction module, and the other feature refinement module fuses the feature map of the P5 layer and the feature map of the P3 layer processed by the feature extraction module. One feature enhancement module fuses the feature map of the P5 layer processed by the feature extraction module with the feature fused by one feature refinement module, and the other feature enhancement module fuses the feature map of the P5 layer processed by the feature extraction module with the feature fused by the other feature refinement module. Finally, the features fused by the two feature refinement modules and the two feature enhancement modules are respectively input into the four branches of the head network.

[0058] After the head network outputs the urine bag scale and the liquid level position, the urine volume data is determined according to the urine bag scale and the liquid level position. If the liquid level position is at the scale line, the scale line is directly used as the urine volume data. If the liquid level position is between two adjacent scale lines, the urine volume data is determined by proportional calculation according to the distances between the liquid level position and the two scale lines. For example, assume that the liquid level is between the scales "100ml" and "200ml" and is at 1 / 3 of the distance from the "100ml" scale. Then the urine volume is: 100ml + 1 / 3×(200ml - 100ml) = 133.3ml.

[0059] In this embodiment, the urine information and physical sign information of the patient on the nursing device body can reflect whether the patient's posture is appropriate. For example, if there is a large amount of urine sediment or abnormal urine color, the nursing device is adjusted to a semi-recumbent position or a sitting position to slightly incline the patient's body, which helps the excretion of urine. If the patient's body temperature rises, the nursing device is adjusted to a more comfortable supine position with the head slightly elevated to facilitate heat dissipation. For patients with abnormal blood pressure and heart rate, it is adjusted to a semi-recumbent position or a sitting position to reduce the burden on the heart; and so on. Therefore, the posture analysis module analyzes the appropriate posture based on the patient's urine information, physical sign information and current posture to promote the patient's recovery.

[0060] The posture analysis module includes an input layer, an LSTM layer, a feature fusion layer, a fully connected layer and an output layer. The input features of the input layer include urine sediment, the urine color, the urine volume data, the vital sign parameters and the posture parameters of the current nursing device body. Preprocessing is performed before the urine sediment, urine color, urine volume data, vital sign parameters and the posture parameters of the current nursing device body are input into the input layer. The urine sediment, urine color and urine volume data are converted into numerical features, and the heart rate, blood pressure and body temperature data are standardized. The heart rate, blood pressure and body temperature data are organized into sequences at a fixed time step (such as per minute).

[0061] Among them, LSTM is a special recurrent neural network architecture specifically designed to address the vanishing gradient and exploding gradient problems encountered by traditional RNNs when processing long sequence data. LSTM can handle sequence data of various lengths and is applicable to multiple tasks such as time series prediction.

[0062] The LSTM layer processes the vital sign parameters to obtain extracted features, and uses the time series characteristics of the vital sign parameters. Since the heart rate, blood pressure, and body temperature data have time series characteristics, that is, there are temporal dependencies between data points, the change trends of the heart rate, blood pressure, and body temperature data can reflect the patient's physical condition, and LSTM can capture the long-term dependencies in these time series data, thus more accurately predicting and analyzing the patient's health status.

[0063] Since the vital sign parameters belong to time series data, and the urine sediment, urine color, urine volume data, and the attitude parameters of the current nursing device body belong to static data, therefore, the feature fusion layer fuses the output features of the LSTM layer with the urine sediment, urine color, urine volume data, and the attitude parameters of the current nursing device body to obtain fused features, and extracts higher-level feature representations; the fully connected layer performs feature extraction on the fused features to obtain output features, and the output layer obtains the attitude parameters of the nursing device body according to the output features.

[0064] The attitude parameters of the nursing device body include the backrest angle, the leg support height, and the headrest position.

[0065] The adjustment component includes a controller and a power component. The controller receives the attitude parameters of the nursing device body to generate a control signal, and the power component drives a motor or a hydraulic rod to adjust the attitude of the nursing device body according to the control signal.

[0066] Embodiment 2

[0067] This embodiment provides an intelligent postoperative urological nursing system, as Figure 2 shown, the system includes:

[0068] The device 10 described in Embodiment 1;

[0069] An information transmission module 11 for transmitting urine sediment, urine color, urine volume data, and vital sign parameters to the host;

[0070] A host 12 for storing and monitoring the urine sediment, the urine color, the urine volume data, and the vital sign parameters, generating a reminder signal when the data parameters meet the preset conditions, and sending the reminder signal to the reminder module;

[0071] A reminder module 13 for generating optical or acoustic information according to the reminder signal to remind the patient and medical staff to take action.

[0072] In this embodiment, the information transmission module 11 can use a wired communication method with RS-232, RS-485 or USB interfaces, or use Wi-Fi, Bluetooth or ZigBee wireless communication technologies.

[0073] The host 12 receives data from the care device and stores it in a local database or cloud storage. When the data parameters meet the preset conditions, the host 12 generates a reminder signal. For example, when the urine volume is greater than the preset value, it indicates that the urine bag is about to be full, and at this time, the patient or medical staff should be reminded to empty the urine bag. When the heart rate, body temperature or blood pressure is higher than the preset value, it indicates that the patient's physical condition has suddenly deteriorated, and at this time, the medical staff needs to be reminded to take corresponding emergency measures.

[0074] The reminder module 13 uses an LED lamp or a display screen to display reminder information, or uses a speaker to play reminder sounds to remind the patient and medical staff to take corresponding actions.

[0075] The basic principles of the present disclosure have been described above in conjunction with specific embodiments. However, it should be noted that the advantages, benefits, effects, etc. mentioned in the present disclosure are only examples and not limitations, and it cannot be considered that these advantages, benefits, effects, etc. are essential for each embodiment of the present disclosure. In addition, the above-mentioned specific details are only for the purposes of illustration and easy understanding, and are not limitations. The above details do not limit the present disclosure to necessarily adopt the above specific details to implement.

[0076] Each embodiment in this specification is described in a progressive manner. The key point of each embodiment is to illustrate the differences from other embodiments. The same or similar parts between each embodiment can be referred to each other. For system embodiments, since they basically correspond to method embodiments, the description is relatively simple, and the relevant parts can refer to the partial description of the method embodiments.

[0077] The block diagrams of the devices, apparatuses, equipment, and systems involved in the present disclosure are only illustrative examples and do not intend to require or imply that they must be connected, arranged, and configured in the manner shown in the block diagrams. As those skilled in the art will recognize, these devices, apparatuses, equipment, and systems can be connected, arranged, and configured in any manner. Words such as "including", "comprising", "having", etc. are open-ended words, meaning "including but not limited to", and can be used interchangeably with each other. The words "or" and "and" used here refer to the word "and / or", and can be used interchangeably with each other, unless the context clearly indicates otherwise. The word "such as" used here refers to the phrase "such as but not limited to", and can be used interchangeably with each other.

[0078] The methods and apparatuses of the present disclosure can be implemented in many ways. For example, the methods and apparatuses of the present disclosure can be implemented by software, hardware, firmware, or any combination of software, hardware, and firmware. The above order of the steps for the methods is for illustrative purposes only. The steps of the methods of the present disclosure are not limited to the specific order described above, unless otherwise specifically stated. In addition, in some embodiments, the present disclosure can also be implemented as a program recorded in a recording medium, and these programs include machine-readable instructions for implementing the methods according to the present disclosure. Thus, the present disclosure also covers a recording medium storing a program for executing the methods according to the present disclosure.

[0079] It should also be noted that in the apparatuses, devices, and methods of the present disclosure, each component or each step can be decomposed and / or recombined. These decompositions and / or recombinations should be regarded as equivalent solutions of the present disclosure. The above description of the disclosed aspects is provided to enable any person skilled in the art to make or use the present disclosure. Various modifications to these aspects are very obvious to those skilled in the art, and the general principles defined herein can be applied to other aspects without departing from the scope of the present disclosure. Therefore, the present disclosure is not intended to be limited to the aspects shown herein, but rather to the broadest scope consistent with the principles and novel features disclosed herein.

[0080] The above description has been given for purposes of illustration and description. In addition, this description is not intended to limit the embodiments of the present disclosure to the forms disclosed herein. Although multiple example aspects and embodiments have been discussed above, those skilled in the art will recognize certain variations, modifications, alterations, additions, and sub-combinations thereof.

Claims

1. An intelligent urology postoperative care device, characterized in that: include: The nursing equipment body is used to provide a postoperative rest environment for patients; A fixing component, arranged on the nursing device body, for fixing the patient's urine bag; An image acquisition device, disposed near the fixed component, for acquiring an image of the urine bag; A vital sign collection device, arranged on the device body, for collecting vital sign parameters of the patient; An analysis device, comprising an image analysis module and a posture analysis module, wherein the image analysis module is used to obtain urine sediment, urine color and urine volume data according to the urine bag image, and the posture analysis module is used to determine the posture parameters of the nursing device body according to the urine sediment, the urine color, the urine volume data, the vital sign parameters and the posture parameters of the current nursing device body; An adjusting component is used to adjust the posture of the nursing device body according to the posture parameters of the nursing device body.

2. The device according to claim 1, characterized in that The nursing equipment body is a recovery chair.

3. The device according to claim 1, characterized in that The image acquisition module includes a camera, which corresponds to the urine bag and is used to acquire an image of the urine bag. The camera sends the acquired image of the urine bag to the analysis device.

4. The device according to claim 1, characterized in that The vital sign collection module includes a body temperature sensor, a sphygmomanometer and a heart rate monitor, which are used to collect the patient's body temperature, blood pressure and heart rate data respectively.

5. The device according to claim 1, characterized in that The image analysis module is a YOLO-based model, comprising a backbone network, a neck network and a head network, wherein the head network comprises a urine bag scale detection branch, a liquid level detection branch, a color detection branch and a sediment detection branch, wherein the urine bag scale detection branch, the liquid level detection branch, the color detection branch and the sediment detection branch share features of the neck network, and the head network outputs the urine bag scale, the urine sediment, the urine color and the liquid level position.

6. The device according to claim 5, characterized in that The neck network includes a feature extraction module and a feature fusion module. The feature extraction module includes multiple context anchor modules. The multiple context anchor modules are used to extract features from feature maps of different layers of the backbone network. The feature fusion module includes a feature refinement module and a feature enhancement module. The feature refinement module fuses high-level features processed by the feature extraction module with low-level features. The feature enhancement module fuses high-level features processed by the feature extraction module with features fused by the feature refinement module. The features fused by the feature refinement module and the feature enhancement module are input into each branch of the head network.

7. The device according to claim 5, characterized in that The urine volume data is determined according to the urine bag scale and the liquid level position. If the liquid level position is at the scale line, the scale line is directly used as the urine volume data. If the liquid level position is between two adjacent scale lines, the urine volume data is determined by proportional calculation based on the distance between the liquid level position and the two scale lines.

8. The device according to claim 1, characterized in that The posture parameters of the nursing device body include seat back angle, leg support height, and headrest position.

9. The device according to claim 1, characterized in that The posture analysis module includes an input layer, an LSTM layer, a feature fusion layer, a fully connected layer and an output layer. The input features of the input layer include the urine sediment, the urine color, the urine volume data, the vital sign parameters and the posture parameters of the current nursing device body. The LSTM layer processes the vital sign parameters to obtain extracted features. The feature fusion layer fuses the extracted features with the urine sediment, the urine color, the urine volume data and the posture parameters of the current nursing device body to obtain fused features. The fully connected layer extracts features from the fused features to obtain output features. The output layer obtains the posture parameters of the nursing device body according to the output features.

10. The device according to claim 1, characterized in that The adjustment component includes a controller and a power component. The controller receives the posture parameter of the nursing device body to generate a control signal. The power component drives a motor or a hydraulic rod to adjust the posture of the nursing device body according to the control signal.

11. An intelligent urology postoperative care system, characterized in that: include: The device according to any one of claims 1 to 10; An information transmission module, used to transmit urine sediment, urine color, urine volume data and vital sign parameters to a host computer; A host, used for storing and monitoring the urine sediment, the urine color, the urine volume data and the vital sign parameters, generating a reminder signal when the data parameters meet preset conditions, and sending the reminder signal to a reminder module; The reminder module is used to generate light or sound information according to the reminder signal to remind patients and medical staff to take action.

Images