Surgical assistance methods, apparatuses, devices, and media

Abstract

The present application relates to the medical technical field, specifically relates to a kind of surgical auxiliary method, device, equipment and medium, method includes: obtaining the sign information of patient in operation, wound information, surgical progress information and surgical environment information;The sign information, wound information, surgical progress information, surgical environment information and the historical case and surgical plan of the patient are input into the first risk prediction model of pre-set to carry out sudden risk prediction, and the first risk prediction model is used to predict whether patient exists sudden risk;The first risk prediction model outputs first risk prompt.The present application can accurately predict the sudden risk that patient can appear in operation, and timely risk prompt is sent to surgeon, so that doctor can take measures in advance according to prompt to reduce or avoid risk, and then improve surgical safety and surgical efficiency.

Description

Technical Field

[0001] This invention relates to the field of medical technology, specifically to a surgical assistance method, device, equipment, and medium. Background Technology

[0002] Surgery, as a crucial means of modern medical treatment, is a highly specialized and complex procedure. During surgery, various unforeseen circumstances frequently arise due to factors such as individual patient differences, organ and tissue variations, and instrument manipulation. These unforeseen circumstances include, but are not limited to, massive bleeding, organ damage, and anesthetic accidents, and are characterized by significant unpredictability and suddenness. Currently, the medical community generally recognizes that unforeseen circumstances during surgery are a key factor affecting surgical safety and success rates, and also a significant and challenging issue in clinical medical research.

[0003] Current technologies for handling surgical emergencies primarily rely on the medical team's on-site judgment and emergency response capabilities. This approach has significant limitations: firstly, due to the unpredictability of emergencies, the medical team is often in a reactive state; secondly, the lack of an effective early warning mechanism makes it difficult to provide the surgical team with sufficient reaction time; and thirdly, complete reliance on human judgment is susceptible to subjective factors, potentially leading to untimely or inaccurate responses. Furthermore, existing surgical assistance systems largely focus on recording and imaging the surgical process, lacking the ability to predict potential risks. These technological deficiencies directly impact the safety and success rate of surgery, increasing the patient's medical risks. Summary of the Invention

[0004] Based on the aforementioned technical problems, surgical assistance systems lack proactive early warning and predictive capabilities, relying excessively on the on-site judgment of the medical team. This leads to passive, delayed, and inaccurate responses to emergencies, directly increasing surgical risks. Therefore, this invention provides a surgical assistance method, device, equipment, and medium. This invention primarily utilizes a risk prediction model to predict sudden risks during surgery, enabling doctors to take proactive measures to reduce or avoid risks, thereby improving surgical safety and efficiency.

[0005] The technical means employed in this invention are as follows:

[0006] In a first aspect, the present invention includes a surgical assistance method, comprising the following steps: Obtain patient vital signs, wound information, surgical progress information, and surgical environment information during surgery; The vital signs information, wound information, surgical progress information, surgical environment information, as well as the patient's historical medical records and surgical plan, are input into a preset first risk prediction model to predict sudden risks. The first risk prediction model is used to predict whether the patient has a sudden risk. The first risk prediction model outputs a first risk warning.

[0007] Furthermore, the vital signs information includes body temperature, heart rate, blood pressure, perspiration, eye movement frequency, blood glucose, electroencephalogram (EEG) and blood oxygen saturation; the wound information includes wound location, wound size and bleeding amount; and the surgical environment information includes ambient temperature, ambient humidity, oxygen content, light intensity in the surgical area and surgical instruments.

[0008] Furthermore, the acquisition of the patient's vital signs, wound information, surgical progress information, and surgical environment information during the operation includes: The patient's vital signs information is collected based on sensors installed on the patient's body; Wound information is obtained by identifying wound images captured by the imaging device; Based on the wound image and the surgical plan, the surgical progress information is determined. Surgical environment information is collected based on sensors installed in the surgical environment.

[0009] Furthermore, the method also includes: The information on the sudden risk and the patient's historical medical records are input into a preset analysis model to obtain a prevention plan for the sudden risk. The information on the sudden risk includes the name, classification, and risk description of the sudden risk. The prevention plan was presented to the surgeon.

[0010] Furthermore, the method also includes: Based on the wound information, the surgical progress information, and the surgical plan, surgical guidance information is generated; The surgical guidance information is displayed to the surgeon. The surgical guidance information includes voice guidance information and image guidance information. The image guidance information is used to guide the surgical location and display the target surgical parameters, including the incision depth and length.

[0011] Furthermore, the method also includes: Obtain the surgeon's vital signs during the operation; The surgeon's vital signs during the operation, the operation progress information, the surgical environment information, and the surgical plan are input into a preset second risk prediction model for risk prediction. In response to the prediction of an emergency risk to the surgeon, a second risk warning is issued.

[0012] Furthermore, the method also includes: The surgical progress information is sent to a display screen outside the operating room for display.

[0013] Secondly, the present invention also includes a surgical assistance device for implementing the above-described surgical assistance method, comprising: The first acquisition module is used to acquire the patient's vital signs, wound information, surgical progress information, and surgical environment information during the operation. The first prediction module is used to input the vital signs information, wound information, surgical progress information, surgical environment information, as well as the patient's historical medical records and surgical plan into a preset first risk prediction model to predict sudden risks. The first alert module is used to issue a first risk alert in response to the prediction that the patient has a sudden risk.

[0014] Thirdly, the present invention also includes a surgical aid device, comprising: The communication component is used to receive patient vital signs, wound information, surgical progress information, and surgical environment information collected by the acquisition device during the operation. Memory, used to store computer programs; A processor for invoking the computer program, wherein when the computer program is invoked by the processor, the processor executes the surgical assistance method as described in any one of claims 1-7.

[0015] Fourthly, the present invention also includes a computer-readable storage medium storing a computer program that, when executed, implements the surgical assistance method as described in any one of claims 1-7.

[0016] Compared with the prior art, the present invention has the following advantages: This invention acquires the patient's intraoperative vital signs, wound information, surgical progress information, and surgical environment information. This information, along with the patient's historical medical records and surgical plan, is then input into a pre-set first risk prediction model for risk prediction. This model can accurately predict potential sudden risks that may occur during surgery (such as shock, cardiac arrest, sudden spasm, etc., but not limited to those listed here), and promptly alerts the surgeon. This allows the surgeon to take preventative measures to reduce or avoid risks, thereby improving surgical safety and efficiency.

[0017] Based on the above reasons, this invention can be widely applied in fields such as medicine. Attached Figure Description

[0018] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0019] Figure 1 This is a schematic diagram of a surgical assistance system provided in an embodiment of the present invention; Figure 2 This is a flowchart of a surgical assistance method provided in an embodiment of the present invention; Figure 3 This is a flowchart of another surgical assistance method provided in an embodiment of the present invention; Figure 4 This is a flowchart of another surgical assistance method provided in an embodiment of the present invention; Figure 5 This is a flowchart of another surgical assistance method provided in an embodiment of the present invention; Figure 6 This is a schematic diagram of the structure of a surgical aid device provided in an embodiment of the present invention; Figure 7 This is a schematic diagram of the structure of a surgical aid device according to an embodiment of the present invention. Detailed Implementation

[0020] To enable those skilled in the art to better understand the present invention, the technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings of the embodiments of the present invention. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort should fall within the scope of protection of the present invention.

[0021] It should be noted that the terms "first," "second," etc., in the specification, claims, and accompanying drawings of this invention are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that the embodiments of the invention described herein can be implemented in orders other than those illustrated or described herein. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover a non-exclusive inclusion; for example, a process, method, system, product, or apparatus that comprises a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or apparatus.

[0022] To address potential risks during surgery, this embodiment provides a surgical assistance solution. The purpose of this solution is to predict and alert patients to potential risks during surgery based on real-time surgical data (such as patient vital signs, wound information, surgical progress, and surgical environment information), as well as the patient's medical history and surgical plan. This aims to reduce surgical risks and improve surgical safety and efficiency.

[0023] The surgical assistance scheme provided in this embodiment is applied to a surgical assistance system. For example, Figure 1 This is a schematic diagram of a surgical assistance system provided in this embodiment, as shown below. Figure 1 As shown. The system may include at least a sensor 11 for detecting patient vital signs, a sensor 12 for acquiring wound information, a sensor 13 for acquiring surgical environment information, a data processing device 14, a gateway 15, a server 16, and a notification device 17.

[0024] The sensor 11 for measuring vital signs can be one or more. For example, in one embodiment, the sensor 11 for measuring vital signs may include a sensor for measuring body temperature, a sensor for measuring heart rate, a sensor for measuring blood pressure, a sensor for measuring perspiration, a sensor for measuring eye movement frequency, a sensor for measuring blood glucose, a sensor for measuring brain waves, and a sensor for measuring blood oxygen content, etc.

[0025] The sensor 12 for acquiring wound information can be, for example, a monocular or binocular camera, and the number of cameras can be one or more. The corresponding wound information can be understood as at least one of the following: wound images captured by the camera, wound location identified based on the wound images, wound size, and bleeding volume. It should be noted that in some embodiments, the type and quantity of tissue contained in the wound can also be identified based on the wound images captured by the camera, and then, in conjunction with a pre-defined surgical plan, the current surgical progress can be determined, such as the removal status of the target resection object.

[0026] The sensor 13 for acquiring surgical environment information can be one or more. For example, in one embodiment, the sensor 13 for acquiring surgical environment information may include a temperature sensor, a humidity sensor, an oxygen content sensor, a brightness sensor, an image sensor (i.e., an imaging device), etc. The image sensor can be used to acquire images of the surgical environment. These images can be used, for example, to identify the types and quantities of surgical instruments in the surgical environment.

[0027] The data collected by sensors 11, 12, and 13 are transmitted to data processing device 14 for processing via a preset protocol. Data processing device 14 performs preset processing on the data collected by the sensors. This preset processing may include, for example, determining surgical progress and wound information through image analysis and recognition, and packaging and encrypting the processed data.

[0028] Data processed by data processing device 14 is sent to server 16 via gateway 15. Server 16 inputs the received vital signs information, wound information, surgical progress information, surgical environment information, and pre-obtained patient history and surgical plan information into a preset first risk prediction model for risk prediction, and obtains the prediction result. The first risk prediction model is a model with the ability to predict sudden risks, trained using a model training method. Training samples may include the patient's vital signs information, wound information, surgical progress information, surgical environment information, patient history and surgical plan, and the sample labels are the risks that occur during the patient's surgery. The naming of the first risk prediction model is only used to distinguish different models and has no other meaning.

[0029] If server 16 predicts a sudden risk to the patient, it sends a notification message to notification device 17 via gateway 15 to alert the surgeon. Notification device 17 may be, for example, augmented reality (AR) glasses and / or an audio playback device worn by the surgeon, but is not limited to AR glasses and audio playback devices.

[0030] It should be noted that Figure 1 The provided auxiliary system is merely an example and not the only limitation of this embodiment. In fact, in other embodiments, the identification of wound information and surgical progress can also be performed by the server. The execution method and data processing equipment are similar and will not be described in detail here.

[0031] The embodiment acquires the patient's intraoperative vital signs, wound information, surgical progress information, and surgical environment information, and inputs the acquired vital signs, wound information, surgical progress information, surgical environment information, as well as the patient's historical medical records and surgical plan into a preset first risk prediction model for risk prediction. It can accurately predict the sudden risks that the patient may encounter during the operation (such as shock, cardiac arrest, sudden spasm, etc., but not limited to the sudden risks listed here), and issue timely risk warnings, so that doctors can take measures in advance to reduce or avoid risks based on the warnings, thereby improving surgical safety and surgical efficiency.

[0032] Figure 2This is a flowchart of a surgical assistance method provided in this embodiment. The method can be performed by a surgical assistance device. This surgical assistance device can be exemplarily understood as... Figure 1 The servers in the system. For example... Figure 2 As shown, in one embodiment of this example, the surgical assistance method provided in this example may include steps 201-203.

[0033] Step 201: Obtain the patient's vital signs, wound information, surgical progress information, and surgical environment information during the operation.

[0034] Specifically, the patient's vital signs during surgery may include, but are not limited to, at least one of the following: body temperature, heart rate, blood pressure, perspiration, eye movement frequency, blood glucose, electroencephalogram (EEG), and blood oxygen saturation. These vital signs can be collected by corresponding sensors mounted on the patient. The data collected by the sensors is transmitted directly or indirectly to the surgical aids via a pre-defined transmission protocol.

[0035] The patient's surgical wound information includes, but is not limited to, at least one of the following: wound image, wound location, size, and bleeding volume. The wound location, size, and bleeding volume can be identified from the wound image based on a preset image recognition algorithm or image recognition model. For example, in one feasible implementation, multiple cameras can be used to capture images of the patient's wound from multiple angles. Then, a three-dimensional model of the wound can be created based on the images captured from multiple angles to obtain information such as the wound's location and size. By identifying the bleeding location, multiple consecutive images of the bleeding location are input into a preset bleeding volume recognition model to identify the amount of bleeding. It should be noted that the wound information in this embodiment can be identified by the surgical aid device mentioned in this embodiment, or by other devices (e.g., surgical aids). Figure 1 The data processing device in the middle identifies the bleeding volume and transmits it to the surgical auxiliary device referred to in this embodiment. The bleeding volume recognition model can be trained using existing model training methods, and the training samples can be images of the bleeding location, with the bleeding volume as the sample label.

[0036] In this embodiment, there are multiple ways to acquire surgical progress information. For example, in one feasible implementation, it can be obtained from the voice information emitted by the surgeon during the operation. For instance, after locating the target resection object, the surgeon can output the voice information "Target resection object located, preparing for resection." After acquiring this voice information, the acquisition device sends it to the surgical auxiliary equipment or other preset processing equipment (e.g., Figure 1The data processing device in the middle performs speech recognition processing to obtain surgical progress information. Alternatively, in another feasible implementation, surgical progress information can also be obtained by comprehensively judging the wound image and surgical plan. For example, in one example, the type and quantity of tissue contained in the wound can be identified from the wound image based on a preset image recognition model. At the same time, based on the information of the target excision object (including type and quantity) recorded in the surgical plan, the removal status of the remaining target excision object in the current wound is determined, thereby obtaining surgical progress information.

[0037] As an embodiment of the present invention, after obtaining the surgical progress information, the surgical progress information can also be sent to a display screen outside the operating room for display, so that the patient's family can keep track of the surgical progress in real time and alleviate the family's anxiety.

[0038] Of course, the two methods for obtaining surgical progress information described above are merely two exemplary methods, not the only ones. In fact, any other solution capable of obtaining surgical progress information can be applied to the technical solution of this embodiment to achieve the inventive objective of this embodiment.

[0039] Surgical environment information may include at least one of the following: ambient temperature, ambient humidity, oxygen content, light intensity in the surgical area, and the type and quantity of surgical instruments. This information can be collected by sensors installed within the surgical environment. For example, ambient temperature, humidity, oxygen content, and light intensity in the surgical area can be collected by devices such as temperature sensors, humidity sensors, oxygen content sensors, and light sensors. Information such as the type and quantity of surgical instruments can be obtained through image recognition based on images acquired by image acquisition sensors. The surgical environment information collected by these sensors can be transmitted directly or indirectly to the surgical aid device of this embodiment via a preset communication protocol.

[0040] Step 202: Input the vital signs information, wound information, surgical progress information, surgical environment information, as well as the patient's historical medical records and surgical plan into the preset first risk prediction model to predict sudden risks. The first risk prediction model is used to predict whether the patient has sudden risks.

[0041] Patient history and surgical plans can be stored in the surgical aids before surgery. Alternatively, image recognition technology can identify the patient entering the operating room and then automatically retrieve the patient's history and surgical plans from the patient database based on that identification. For example, after the patient enters the operating room, a pre-set image acquisition device captures the patient's image. This image is then transmitted to the surgical aids. Upon receiving the patient's image, the surgical aids perform facial recognition to obtain the patient's identity information. Based on this identity information, it then retrieves the corresponding history and surgical plans from the patient database. This is merely an example of how history and surgical plans can be obtained, and not the only possible method.

[0042] The first risk prediction model referred to in this embodiment is a model trained using a model training method, possessing the ability to predict sudden risks. This model can be, for example, a machine learning model, a neural network model, or a language model, but is not limited to the models listed here. The first risk prediction model in this embodiment takes the patient's intraoperative vital signs, wound information, surgical progress information, surgical environment information, as well as the patient's historical medical records and surgical plan as input, and outputs the sudden risk prediction result. The sudden risk prediction result can be divided into two categories: no risk and sudden risk. In the case of sudden risk, the sudden risk prediction result can include information such as the type of sudden risk, descriptive information about the sudden risk, and the probability of occurrence.

[0043] Step 203: The first risk prediction model outputs the first risk warning.

[0044] The first risk warning in this embodiment may include voice prompts and / or visual prompts. The warning content may include information such as the type of the sudden risk, its probability of occurrence, and a detailed description of the risk. For example, in one example, the first risk warning generated based on the prediction result may include voice prompts and video prompts. The video prompts may include a preset warning animation and detailed information about the sudden risk (including images and text). The voice prompts are transmitted to a preset playback device (such as a player on AR glasses worn by a doctor) for playback, and the video prompts are transmitted to a preset display device (such as AR glasses) for display.

[0045] In this embodiment, by acquiring the patient's intraoperative vital signs, wound information, surgical progress information, and surgical environment information, and inputting the acquired vital signs, wound information, surgical progress information, surgical environment information, as well as the patient's historical medical records and surgical plan, into a preset first risk prediction model for risk prediction, it can accurately predict the sudden risks that the patient may encounter during surgery (such as shock, cardiac arrest, sudden spasm, etc., but not limited to the sudden risks listed here), and promptly issue risk warnings to the surgeon, so that the doctor can take measures in advance to reduce or avoid risks based on the warnings, thereby improving surgical safety and surgical efficiency.

[0046] Figure 3 This is a flowchart of another surgical assistance method provided in this embodiment. For example... Figure 3 As shown, in some embodiments of this example, after predicting that a patient has a sudden risk, the execution plan of steps 301-302 may also be included.

[0047] Step 301: In response to the prediction of a sudden risk to the patient, the information of the sudden risk and the patient's historical medical records are input into a preset analysis model to obtain a prevention plan for the sudden risk. The information of the sudden risk includes the name, classification and risk description of the sudden risk.

[0048] In this embodiment, the preset analysis model can be a model trained using a model training method, possessing risk analysis capabilities and outputting prevention plans. This model and the first risk prediction model can be models with the same architecture or models with different architectures. The training samples of the model can be information on sudden risks encountered by patients during surgery and the patient's historical medical records, and the learning objective is the prevention plan. The training method of this model can be found in related technologies and will not be elaborated here.

[0049] In this embodiment, the pre-set analysis model takes information about sudden risks and the patient's historical medical records as input, and outputs a prevention plan for the sudden risks. The prevention plan may include specific medical measures, such as blood transfusion type, transfusion volume, electric shock intensity, oxygen supply, and adjustment of incision depth and / or width. Of course, this is merely an example and not the only limitation on any specific prevention plan.

[0050] Step 302: Show the prevention plan to the surgeon.

[0051] For example, in one embodiment of this invention, corresponding voice broadcast information and corresponding visual information can be generated based on the prevention plan. The visual information may include icons and text descriptions corresponding to various prevention measures. The voice broadcast information can be transmitted to a preset playback device (such as a player on AR glasses worn by a doctor) for playback, and the visual information can be transmitted to a preset display device (such as AR glasses) for display.

[0052] By predicting potential risks during surgery and generating corresponding prevention plans when such risks are predicted, it is possible to effectively avoid or reduce these risks and improve surgical safety and efficiency.

[0053] Figure 4 This is a flowchart of another surgical assistance method provided in this embodiment. For example... Figure 4 As shown, in some other embodiments of this example, intelligent guidance of surgery can also be achieved based on the scheme of steps 401-402.

[0054] Step 401: Generate surgical guidance information based on wound information, surgical progress information, and surgical plan.

[0055] In this embodiment, the surgical plan can be semantically analyzed based on a preset semantic analysis model to obtain the surgical content. Then, the wound information and surgical progress information are compared with the surgical content to determine the completed surgical content and the next stage of the surgical procedure. Based on this, surgical guidance information is generated. For example, if the current surgery has completed the incision at the target location and exposed the target resection object, the next stage of the surgical procedure is the resection of the target object. When generating surgical guidance information, the surgical aid device identifies the target resection object based on the wound image. Then, the information of the target resection object and the wound image are input into the preset surgical guidance model. This model determines the optimal resection plan and generates surgical guidance information based on the optimal plan, such as the resection order, the depth and length of the incision at each location, etc. The surgical guidance model is trained using a model training method, the training method of which can be found in related technologies and will not be elaborated here.

[0056] Step 402: Display the surgical guidance information to the surgeon. The surgical guidance information includes voice guidance information and / or image guidance information. The image guidance information is used to guide the surgical location and display the target surgical parameters, including the incision depth and length.

[0057] Among these, voice guidance information is the broadcast of surgical guidance information via voice. Image guidance information is the guidance of surgical location, surgical parameters, etc., using visual images. For example, in one implementation, the image guidance information in this embodiment can be understood as AR guidance information. This information is applied to the target surgical location through the field of view in front of AR glasses, and displays target surgical parameters, such as incision depth and length, around the target surgical location.

[0058] In this embodiment, surgical guidance information is generated by using wound information, surgical progress information, and surgical plan, and then displayed to the surgeon. This allows the surgeon to quickly and accurately locate the surgical position and parameters, thereby improving the accuracy and efficiency of the surgery.

[0059] Figure 5 This is a flowchart of another surgical assistance method provided in this embodiment. For example... Figure 5 As shown, in some other embodiments of this example, the prediction of sudden risks to surgeons can also be achieved based on the scheme of steps 501-503.

[0060] Step 501: Obtain the surgeon's vital signs during the operation.

[0061] Step 502: Input the surgeon's vital signs, surgical progress, surgical environment, and surgical plan into the preset second risk prediction model for risk prediction.

[0062] The second risk prediction model can be understood as a model with risk prediction capabilities trained through model training methods. The training samples of the model can include the surgeon's vital signs during the operation, the progress of the operation, the surgical environment, and the surgical plan. The sample labels include the risks that occurred to the surgeon during the operation. This model can be of the same architecture as the first risk prediction model, or it can be a model with a different architecture.

[0063] Step 503: In response to the prediction of an emergency risk to the surgeon, issue a second risk warning.

[0064] The execution method of steps 501-503 is similar to that of steps 201-203, and will not be described again here.

[0065] Since surgeons are key participants in surgical procedures, any unexpected risks they encounter can impact the safety and efficiency of the operation. Predicting potential risks for surgeons can help identify these risks promptly, thereby improving surgical safety and efficiency.

[0066] Figure 6This is a schematic diagram of a surgical assistance device provided in this embodiment. This surgical assistance device can be understood, by way of example, as the surgical assistance equipment or some functional modules of the surgical assistance equipment in the above embodiments. For example... Figure 6 As shown, in this embodiment, the surgical assistance device 60 may include: The first acquisition module 61 is used to acquire the patient's vital signs, wound information, surgical progress information and surgical environment information during the operation; The first prediction module 62 is used to input vital signs information, wound information, surgical progress information, surgical environment information, as well as the patient's historical medical records and surgical plans into a preset first risk prediction model to predict sudden risks. The first alert module 63 is used to issue a first risk alert to the surgeon in response to the prediction that the patient has a sudden risk.

[0067] Vital signs information includes at least one of the following: Body temperature, heart rate, blood pressure, perspiration, eye movement frequency, blood glucose, brain waves, and blood oxygen levels; Wound information includes at least one of the following: wound location, wound size, and amount of bleeding; Surgical environment information includes at least one of the following: ambient temperature, ambient humidity, oxygen content, light intensity in the surgical area, and the type and quantity of surgical instruments.

[0068] The first acquisition module 61 is specifically used for: The patient's vital signs information is collected based on sensors installed on the patient's body; Wound information is obtained by identifying wound images captured by the imaging device; Based on the wound images and surgical plan, the surgical progress information was determined. Surgical environment information is collected based on sensors installed in the surgical environment.

[0069] Surgical aid device 60 may also include: The first generation module is used to respond to the prediction that a patient has a sudden risk. It inputs the information of the sudden risk and the patient's historical medical records into a preset analysis model to obtain a prevention plan for the sudden risk. The information of the sudden risk includes the name, classification and risk description of the sudden risk. The first presentation module is used to show the prevention plan to the surgeon.

[0070] Surgical aid device 60 may also include: The second generation module is used to generate surgical guidance information based on wound information, surgical progress information, and surgical plan. The second display module is used to display surgical guidance information to the surgeon. The surgical guidance information includes voice guidance information and / or image guidance information. The image guidance information is used to guide the surgical location and display the target surgical parameters, including the incision depth and length.

[0071] Surgical aid device 60 may also include: The second acquisition module is used to acquire the surgeon's vital signs information during the operation; The second prediction module is used to input the surgeon's vital signs, surgical progress, surgical environment, and surgical plan into a preset second risk prediction model for risk prediction. The second alert module is used to issue a second risk alert to the surgeon in response to a predicted sudden risk.

[0072] Surgical aid device 60 may also include: The sending module is used to send surgical progress information to a display screen outside the operating room for display.

[0073] The apparatus provided in this embodiment can execute the methods of any of the above method embodiments, and its execution mode and beneficial effects are similar, so they will not be described again here.

[0074] This embodiment also provides a surgical aid device, which includes: The communication component is used to receive patient vital signs, wound information, surgical progress information, and surgical environment information collected by the acquisition device during the operation. Memory, used to store computer programs; A processor is used to invoke a computer program. When the computer program is invoked by the processor, the processor executes the method of any of the above method embodiments.

[0075] Example, Figure 7 This is a schematic diagram of a surgical aid device in this embodiment. See below for details. Figure 7 The diagram illustrates a structural schematic suitable for implementing the surgical aid device 1400 in this embodiment. The surgical aid device 1400 in this embodiment may include, but is not limited to, devices with computing and processing capabilities such as laptops, tablets, desktop computers, and servers. Figure 7 The surgical aids shown are merely an example and should not be construed as limiting the functionality and scope of use of this embodiment.

[0076] like Figure 7As shown, the surgical aid device 1400 may include a processing unit (e.g., a central processing unit, a graphics processor, etc.) 1401, which can perform various appropriate actions and processes according to a program stored in a read-only memory (ROM) 1402 or a program loaded from a storage device 1408 into a random access memory (RAM) 1403. The RAM 1403 also stores various programs and data required for the operation of the surgical aid device 1400. The processing unit 1401, ROM 1402, and RAM 1403 are interconnected via a bus 1404. An input / output (I / O) interface 1405 is also connected to the bus 1404.

[0077] Typically, the following devices can be connected to I / O interface 1405: input devices 1406 including, for example, a touchscreen, touchpad, keyboard, mouse, camera, microphone, accelerometer, gyroscope, etc.; output devices 1407 including, for example, a liquid crystal display (LCD), speaker, vibrator, etc.; storage devices 1408 including, for example, magnetic tape, hard disk, etc.; and communication devices 1409. Communication device 1409 allows surgical aids 1400 to communicate wirelessly or wiredly with other devices to exchange data. Although Figure 7 A surgical aid device 1400 with various devices is shown; however, it should be understood that implementation or possession of all the devices shown is not required. More or fewer devices may be implemented or possessed alternatively.

[0078] According to embodiments of this disclosure, the processes described above with reference to the flowcharts can be implemented as computer software programs. For example, this embodiment includes a computer program product comprising a computer program carried on a non-transitory computer-readable medium, the computer program containing program code for performing the methods shown in the flowcharts. In such an embodiment, the computer program can be downloaded and installed from a network via communication device 1409, or installed from storage device 1408, or installed from ROM 1402. When the computer program is executed by processing device 1401, it performs the functions defined in the methods of this embodiment.

[0079] It should be noted that the aforementioned computer-readable medium can be a computer-readable signal medium or a computer-readable storage medium, or any combination thereof. A computer-readable storage medium can be, for example,—but not limited to—an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination thereof. More specific examples of a computer-readable storage medium may include, but are not limited to: an electrical connection having one or more wires, a portable computer disk, a hard disk, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fiber, portable compact disk read-only memory (CD-ROM), optical storage device, magnetic storage device, or any suitable combination thereof. In this disclosure, a computer-readable storage medium can be any tangible medium containing or storing a program that can be used by or in conjunction with an instruction execution system, apparatus, or device. A computer-readable signal medium can include a data signal propagated in baseband or as part of a carrier wave, carrying computer-readable program code. Such propagated data signals can take various forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination thereof. A computer-readable signal medium can be any computer-readable medium other than a computer-readable storage medium, which can send, propagate, or transmit a program for use by or in connection with an instruction execution system, apparatus, or device. The program code contained on the computer-readable medium can be transmitted using any suitable medium, including but not limited to: wires, optical fibers, RF (radio frequency), etc., or any suitable combination thereof.

[0080] The aforementioned computer-readable medium may be included in the aforementioned surgical aid device; or it may exist independently and not assembled into the surgical aid device.

[0081] The aforementioned computer-readable medium carries one or more programs, which, when executed by a processing device, enable the processing device to: acquire the patient's vital signs, wound information, surgical progress information, and surgical environment information during the operation; input the vital signs, wound information, surgical progress information, surgical environment information, as well as the patient's historical medical records and surgical plan into a preset first risk prediction model to predict sudden risks; and, in response to the prediction that the patient has a sudden risk, issue a first risk warning to the surgeon.

[0082] Computer program code for performing the operations of this disclosure can be written in one or more programming languages ​​or a combination thereof, including but not limited to object-oriented programming languages ​​such as Java, Smalltalk, and C++, as well as conventional procedural programming languages ​​such as the "C" language or similar programming languages. The program code can be executed entirely on the user's computer, partially on the user's computer, as a standalone software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In cases involving remote computers, the remote computer can be connected to the user's computer via any type of network—including a local area network (LAN) or a wide area network (WAN)—or can be connected to an external computer (e.g., via the Internet using an Internet service provider).

[0083] The flowcharts and block diagrams in the accompanying drawings illustrate the architecture, functionality, and operation of possible implementations of systems, methods, and computer program products according to various embodiments of this disclosure. In this regard, each block in a flowchart or block diagram may represent a module, segment, or portion of code containing one or more executable instructions for implementing a specified logical function. It should also be noted that in some alternative implementations, the functions indicated in the blocks may occur in a different order than those indicated in the drawings. For example, two consecutively indicated blocks may actually be executed substantially in parallel, and they may sometimes be executed in reverse order, depending on the functions involved. It should also be noted that each block in the block diagrams and / or flowcharts, and combinations of blocks in the block diagrams and / or flowcharts, can be implemented using a dedicated hardware-based system that performs the specified function or operation, or using a combination of dedicated hardware and computer instructions.

[0084] The units described in this embodiment can be implemented in software or hardware. The names of the units are not, in some cases, limiting the scope of the unit itself.

[0085] The functions described above in this embodiment can be performed at least in part by one or more hardware logic components. For example, without limitation, exemplary types of hardware logic components that can be used include: Field Programmable Gate Arrays (FPGAs), Application-Specific Integrated Circuits (ASICs), Application Standard Products (ASSPs), System-on-Chip (SoCs), Complex Programmable Logic Devices (CPLDs), and so on.

[0086] In the context of this disclosure, if the integrated unit is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, in essence, or the part that contributes to the prior art, or all or part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of the present invention. The aforementioned storage medium includes various media capable of storing program code, such as a USB flash drive, read-only memory (ROM), random access memory (RAM), portable hard drive, magnetic disk, or optical disk.

[0087] This embodiment also provides a computer-readable storage medium storing a computer program, which, when executed by a processor, can perform the above-described functions. Figures 2-7 The methods in any of the embodiments are similar in execution and beneficial effects, and will not be described again here.

[0088] This embodiment also provides a computer program product, which is stored in a storage medium. When the program product is run, it can achieve... Figures 2-7 The methods in any of the embodiments are similar in execution and beneficial effects, and will not be described again here.

[0089] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, and not to limit them; although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some or all of the technical features; and these modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of the present invention.

Claims

1. A surgical assistance method, characterized in that, Includes the following steps: Obtain patient vital signs, wound information, surgical progress information, and surgical environment information during surgery; The vital signs information, wound information, surgical progress information, surgical environment information, as well as the patient's historical medical records and surgical plan, are input into a preset first risk prediction model to predict sudden risks. The first risk prediction model is used to predict whether the patient has a sudden risk. The first risk prediction model outputs a first risk warning.

2. The surgical assistance method according to claim 1, characterized in that, The vital signs information includes body temperature, heart rate, blood pressure, perspiration, eye movement frequency, blood glucose, electroencephalogram (EEG), and blood oxygen saturation. The wound information includes wound location, wound size, and amount of bleeding. The surgical environment information includes ambient temperature, ambient humidity, oxygen content, light intensity in the surgical area, and surgical instruments.

3. The surgical assistance method according to claim 1, characterized in that, The acquisition of patient vital signs, wound information, surgical progress information, and surgical environment information during surgery includes: The patient's vital signs information is collected based on sensors installed on the patient's body; Wound information is obtained by identifying wound images captured by the imaging device; Based on the wound image and the surgical plan, the surgical progress information is determined. Surgical environment information is collected based on sensors installed in the surgical environment.

4. The surgical assistance method according to claim 1, characterized in that, The method further includes: The information on the sudden risk and the patient's historical medical records are input into a preset analysis model to obtain a prevention plan for the sudden risk. The information on the sudden risk includes the name, classification, and risk description of the sudden risk. The prevention plan was presented to the surgeon.

5. The surgical assistance method according to claim 1, characterized in that, The method further includes: Based on the wound information, the surgical progress information, and the surgical plan, surgical guidance information is generated; The surgical guidance information is displayed to the surgeon. The surgical guidance information includes voice guidance information and image guidance information. The image guidance information is used to guide the surgical location and display the target surgical parameters, including the incision depth and length.

6. The surgical assistance method according to claim 1, characterized in that, The method further includes: Obtain the surgeon's vital signs during the operation; The surgeon's vital signs during the operation, the operation progress information, the surgical environment information, and the surgical plan are input into a preset second risk prediction model for risk prediction. In response to the prediction of an emergency risk to the surgeon, a second risk warning is issued.

7. The surgical assistance method according to claim 1, characterized in that, The method further includes: The surgical progress information is sent to a display screen outside the operating room for display.

8. A surgical assistance device for implementing the surgical assistance method according to any one of claims 1-7, characterized in that, include: The first acquisition module is used to acquire the patient's vital signs, wound information, surgical progress information, and surgical environment information during the operation. The first prediction module is used to input the vital signs information, wound information, surgical progress information, surgical environment information, as well as the patient's historical medical records and surgical plan into a preset first risk prediction model to predict sudden risks. The first alert module is used to issue a first risk alert in response to the prediction that the patient has a sudden risk.

9. A surgical aid device, characterized in that, include: The communication component is used to receive patient vital signs, wound information, surgical progress information, and surgical environment information collected by the acquisition device during the operation. Memory, used to store computer programs; A processor for invoking the computer program, wherein when the computer program is invoked by the processor, the processor executes the surgical assistance method as described in any one of claims 1-7.

10. A computer-readable storage medium, characterized in that, The storage medium stores a computer program, which, when executed, implements the surgical assistance method as described in any one of claims 1-7.

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