system

Abstract

The system according to this embodiment aims to assist surgeons in making quick and accurate decisions during surgery. [Solution] The system according to the embodiment comprises an analysis unit, a projection unit, and an advice unit. The analysis unit performs real-time video analysis of the operating room situation. The projection unit projects the information analyzed by the analysis unit onto a glasses-type device. The advice unit provides advice to the surgeon based on the information projected by the projection unit.

Description

Technical Field

[0001] The technology of the present disclosure relates to a system.

Background Art

[0002] Patent Document 1 discloses a method for controlling a persona chatbot, which is performed by at least one processor, including steps of receiving a user utterance, adding the user utterance to a prompt including an instruction sentence related to an explanation of a chatbot character, encoding the prompt, and inputting the encoded prompt into a language model to generate a chatbot utterance in response to the user utterance.

Prior Art Documents

Patent Documents

[0003]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0004] In the conventional technology, there is not enough support for surgeons to make quick and accurate judgments during surgery, and there is room for improvement.

[0005] The system according to the embodiment aims to assist surgeons in making quick and accurate judgments during surgery.

Means for Solving the Problems

[0006] The system according to the embodiment includes an analysis unit, a projection unit, and an advice unit. The analysis unit analyzes the situation in the operating room in real time by video analysis. The projection unit projects the information analyzed by the analysis unit onto a glasses-type device. The advice unit provides advice to the surgeon based on the information projected by the projection unit.

Effects of the Invention

[0007] The system according to this embodiment can help surgeons make quick and accurate decisions during surgery. [Brief explanation of the drawing]

[0008] [Figure 1] This is a conceptual diagram showing an example of the configuration of a data processing system according to the first embodiment. [Figure 2] This is a conceptual diagram showing an example of the essential functions of a data processing device and a smart device according to the first embodiment. [Figure 3] This is a conceptual diagram showing an example of the configuration of a data processing system according to the second embodiment. [Figure 4] This is a conceptual diagram showing an example of the main functions of a data processing device and smart glasses according to the second embodiment. [Figure 5] This is a conceptual diagram showing an example of the configuration of a data processing system according to the third embodiment. [Figure 6] This is a conceptual diagram showing an example of the main functions of a data processing device and a headset-type terminal according to the third embodiment. [Figure 7] This is a conceptual diagram showing an example of the configuration of a data processing system according to the fourth embodiment. [Figure 8] This is a conceptual diagram showing an example of the main functions of a data processing device and a robot according to the fourth embodiment. [Figure 9] This shows an emotion map where multiple emotions are mapped. [Figure 10] This shows an emotion map where multiple emotions are mapped. [Modes for carrying out the invention]

[0009] Hereinafter, an example of an embodiment of the system relating to the technology of this disclosure will be described with reference to the attached drawings.

[0010] First, let's explain the terminology used in the following explanation.

[0011] In the following embodiments, the signed processor (hereinafter simply referred to as "processor") may be a single arithmetic unit or a combination of multiple arithmetic units. Furthermore, the processor may be a single type of arithmetic unit or a combination of multiple types of arithmetic units. Examples of arithmetic units include CPU (Central Processing Unit), GPU (Graphics Processing Unit), GPGPU (General-Purpose computing on Graphics Processing Units), APU (Accelerated Processing Unit), or TPU (Tensor Processing Unit).

[0012] In the following embodiments, signed RAM (Random Access Memory) is a memory that temporarily stores information and is used as work memory by the processor.

[0013] In the following embodiments, the signed storage is one or more non-volatile storage devices that store various programs and various parameters. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), or magnetic tapes.

[0014] In the following embodiments, the signed communication interface (I / F) is an interface that includes a communication processor and an antenna. The communication interface manages communication between multiple computers. Examples of communication standards applicable to the communication interface include wireless communication standards such as 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), or Bluetooth (registered trademark).

[0015] In the following embodiments, "A and / or B" is synonymous with "at least one of A and B". That is, "A and / or B" means that it may be only A, only B, or a combination of A and B. Also, in this specification, when expressing three or more matters connected by "and / or", the same concept as "A and / or B" is applied.

[0016] [First Embodiment] FIG. 1 shows an example of the configuration of a data processing system 10 according to the first embodiment.

[0017] As shown in FIG. 1, the data processing system 10 includes a data processing device 12 and a smart device 14. An example of the data processing device 12 is a server.

[0018] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. Also, the database 24 and the communication I / F 26 are connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0019] The smart device 14 includes a computer 36, a reception device 38, an output device 40, a camera 42, and a communication I / F 44. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. Also, the reception device 38, the output device 40, and the camera 42 are connected to the bus 52.

[0020] The reception device 38 is equipped with a touch panel 38A and a microphone 38B, and accepts user input. The touch panel 38A accepts user input via touch by detecting contact with an object (e.g., a pen or finger). The microphone 38B accepts user input via voice by detecting the user's voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and microphone 38B to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 (see Figure 2) acquires the data indicating the user input.

[0021] The output device 40 includes a display 40A and a speaker 40B, and presents data to the user by outputting the data in a form perceptible to the user (e.g., audio and / or text). The display 40A displays visible information such as text and images according to instructions from the processor 46. The speaker 40B outputs audio according to instructions from the processor 46. The camera 42 is a small digital camera equipped with an optical system such as a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor.

[0022] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various types of information between processor 46 and processor 28 via network 54.

[0023] Figure 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0024] As shown in Figure 2, in the data processing device 12, a specific processing is performed by the processor 28. A specific processing program 56 is stored in the storage 32. The specific processing program 56 is an example of a "program" related to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 according to the specific processing program 56 executed on the RAM 30.

[0025] Storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290. The identification processing unit 290 can estimate the user's emotions using the emotion identification model 59 and perform identification processing using the user's emotions. The emotion estimation function (emotion identification function) using the emotion identification model 59 performs various estimations and predictions regarding the user's emotions, including but not limited to these examples. Furthermore, emotion estimation and prediction also include, for example, emotion analysis.

[0026] In the smart device 14, specific processing is performed by the processor 46. The storage 50 stores a specific processing program 60. The specific processing program 60 is used in conjunction with the specific processing program 56 by the data processing system 10. The processor 46 reads the specific processing program 60 from the storage 50 and executes the read specific processing program 60 on the RAM 48. The specific processing is realized by the processor 46 operating as a control unit 46A according to the specific processing program 60 executed on the RAM 48. The smart device 14 also has a data generation model 58 and an emotion identification model 59, similar to the data generation model and emotion identification model 59, and can perform processing similar to that of the specific processing unit 290 using these models.

[0027] Furthermore, other devices besides the data processing device 12 may also have the data generation model 58. For example, a server device (e.g., a generation server) may have the data generation model 58. In this case, the data processing device 12 obtains processing results (such as prediction results) using the data generation model 58 by communicating with the server device having the data generation model 58. The data processing device 12 may also be a server device or a terminal device owned by a user (e.g., a mobile phone, robot, home appliance, etc.). Next, an example of processing by the data processing system 10 according to the first embodiment will be described.

[0028] (Example of form 1) An embodiment of the present invention provides a smart surgical agent, a glasses-type device that assists surgeons in making accurate and rapid decisions during surgery. This device analyzes the operating room situation in real time and projects important biometric information and surgical procedures visually onto the glasses. It also provides advice and warnings from a generating AI via a bone conduction speaker, enhancing the surgeon's concentration. This improves the success rate of surgery and ensures patient safety. For example, cameras and sensors are placed in the operating room to analyze the situation in real time. These devices collect the progress of the surgery and the patient's biometric information and transmit it to the generating AI. The generating AI analyzes this data and extracts important information, such as the patient's heart rate, blood pressure, and the progress of the surgery. The generated AI then projects the extracted information onto the glasses-type device. The glasses-type device is designed so that the surgeon can view the information without moving their eyes. This allows the surgeon to view necessary information in real time during surgery. For example, the progress of the surgery and the patient's biometric information are displayed on the glasses' screen. Furthermore, the generating AI provides advice and warnings to the surgeon according to the progress of the surgery. These pieces of advice and cautionary notes are communicated to the surgeon via bone conduction speakers. For example, they include the next steps in the surgery and points to be aware of. This allows the surgeon to maintain focus and perform more precise surgery. This system improves surgical success rates and ensures patient safety. Because surgeons can access necessary information in real time during surgery, they can make quick and accurate decisions. Furthermore, advice and cautionary notes from the generated AI improve surgical precision and reduce the burden on the doctor. This improves the quality of medical care and provides patients with safer and more effective treatment. Thus, smart surgical agents can help surgeons make accurate and rapid decisions during surgery, improving surgical success rates and patient safety.

[0029] The smart surgical agent according to this embodiment comprises an analysis unit, a projection unit, and an advice unit. The analysis unit performs real-time video analysis of the operating room environment. For example, the analysis unit analyzes video and biological information obtained from cameras and sensors in the operating room in real time. The analysis unit can analyze the progress of the surgery and the patient's biological information using generative AI. For example, the analysis unit can analyze biological information such as the patient's heart rate, blood pressure, and oxygen saturation in real time. The analysis unit can also analyze the progress of the surgery in real time and grasp the stage of the surgery and the duration of the surgery. The projection unit projects the information analyzed by the analysis unit onto a glasses-type device. For example, the projection unit can project information extracted by generative AI onto the glasses-type device. The projection unit is designed so that the surgeon can check the information without moving their gaze. For example, the projection unit can display the progress of the surgery and the patient's biological information on the glasses' display. The projection unit can project the progress of the surgery and the patient's biological information in real time using generative AI. The advice unit provides advice to the surgeon based on the information projected by the projection unit. The advice unit can, for example, use a generating AI to provide the surgeon with advice and points to note according to the progress of the surgery. The advice unit can also provide advice and points to note to the surgeon through a bone conduction speaker. For example, the advice unit can communicate the next steps in the surgery and points to pay attention to to the surgeon. The advice unit can use a generating AI to provide advice and points to note to the surgeon according to the progress of the surgery. As a result, the smart surgical agent according to the embodiment can help the surgeon make accurate and rapid decisions during surgery, thereby improving the success rate of the surgery and the safety of the patient.

[0030] The analysis unit performs real-time video analysis of the operating room situation. For example, the analysis unit analyzes video and biological information obtained from cameras and sensors in the operating room in real time. Specifically, high-resolution cameras installed in the operating room capture the surgery and transmit the video data to the analysis unit. The analysis unit can use generative AI to analyze the progress of the surgery and the patient's biological information. The generative AI analyzes the video data, identifies each stage of the surgery, and understands the progress of the surgery. For example, the generative AI recognizes the movement and position of surgical instruments and analyzes the progress of the surgery in real time. It can also analyze biological information such as the patient's heart rate, blood pressure, and oxygen saturation in real time. As a result, the analysis unit can constantly monitor the patient's condition during surgery and immediately detect any abnormalities. Furthermore, the analysis unit can analyze the progress of the surgery in real time and understand the stage of the surgery and the duration of the surgery. For example, it measures the time from the start to the end of the surgery and records the time taken for each stage of the surgery. This allows for evaluation of the efficiency of the surgery and identification of areas for improvement. The analysis department centrally manages this information and can collaborate with other systems and departments as needed. For example, the analyzed data is stored on a cloud server, making it accessible to other medical staff and systems. This allows the analysis department to understand the situation in the operating room in real time and improve surgical success rates and patient safety.

[0031] The projection unit projects information analyzed by the analysis unit onto a glasses-type device. For example, the projection unit can project information extracted by a generative AI onto the glasses-type device. Specifically, the projection unit displays information on a display built into the glasses-type device worn by the surgeon. The glasses-type device is designed to allow the surgeon to view information without moving their eyes. For example, the projection unit can display the progress of surgery and the patient's vital signs on the glasses' display. The progress of surgery includes each stage of the surgery, the position of surgical instruments, and the duration of the surgery. The patient's vital signs, such as heart rate, blood pressure, and oxygen saturation, are displayed in real time. This allows the surgeon to instantly check necessary information during surgery, improving the efficiency and accuracy of the operation. Furthermore, the projection unit can use generative AI to project the progress of surgery and the patient's vital signs in real time. The generative AI analyzes the progress of surgery and the patient's vital signs, extracts important information, and projects it onto the glasses-type device. For example, if an abnormality occurs during surgery, the generative AI immediately detects this information and displays a warning to the surgeon. This allows the surgeon to respond quickly without missing important information during surgery. The projection unit can update this information in real time, always providing the latest information. This allows the projection unit to help surgeons make accurate and rapid decisions during surgery, improving surgical success rates and patient safety.

[0032] The advice unit provides advice to the surgeon based on the information projected by the projection unit. For example, the advice unit's generating AI can provide the surgeon with advice and points to note according to the progress of the surgery. Specifically, the advice unit presents points to pay attention to and the next steps for the surgeon at each stage of the surgery. For example, as the surgery progresses, it informs the surgeon of the next surgical instruments to be used and the procedure. Also, if an abnormality occurs during the surgery, the advice unit provides the surgeon with the cause and how to deal with it. The advice unit can also provide advice and points to note to the surgeon through a bone conduction speaker. Because the bone conduction speaker can transmit sound directly to the surgeon's ear, it can reliably convey important information without being interfered with by noise or other sounds during the surgery. For example, the advice unit can inform the surgeon of the next steps in the surgery and points to pay attention to. The generating AI analyzes the progress of the surgery and the patient's biological information, and extracts and provides the most important information for the surgeon. This allows the surgeon to immediately obtain the information they need during the surgery, improving the efficiency and accuracy of the surgery. Furthermore, the advice unit can collect feedback from the surgeon and continuously improve the accuracy and effectiveness of the advice. For example, based on feedback from surgeons, the advice department can review its content and delivery methods to provide more effective advice. This allows the advice department to support surgeons in making accurate and rapid decisions during surgery, thereby improving surgical success rates and patient safety.

[0033] The analysis unit can analyze video and biological information obtained from cameras and sensors in the operating room in real time. For example, the analysis unit can analyze video and biological information obtained from cameras and sensors in the operating room in real time. The analysis unit can use generative AI to analyze the progress of the surgery and the patient's biological information. For example, the analysis unit can analyze biological information such as the patient's heart rate, blood pressure, and oxygen saturation in real time. In addition, the analysis unit can analyze the progress of the surgery in real time and grasp the stage of the surgery and the duration of the surgery. This allows for the rapid provision of necessary information to surgeons by analyzing the situation in the operating room in real time. Some or all of the above processing in the analysis unit may be performed using generative AI, or it may be performed without generative AI. For example, the analysis unit can input video and biological information obtained from cameras and sensors in the operating room into the generative AI, and the generative AI can analyze this data and extract important information.

[0034] The projection unit can project information extracted by the generating AI onto a glasses-type device. For example, the projection unit projects information extracted by the generating AI onto the glasses-type device. The projection unit is designed to allow surgeons to view information without moving their eyes. For example, the projection unit can display the progress of surgery and the patient's vital signs on the glasses' display. The projection unit can project the progress of surgery and the patient's vital signs in real time using the generating AI. This allows surgeons to view information without moving their eyes by projecting the information extracted by the generating AI onto the glasses-type device. Some or all of the above processing in the projection unit may be performed using the generating AI or not. For example, when the projection unit projects information extracted by the generating AI onto the glasses-type device, the generating AI can determine the priority of the information and prioritize the projection of important information.

[0035] The advice unit can use a generating AI to provide the surgeon with advice and points to note according to the progress of the surgery. The advice unit can provide advice and points to note to the surgeon via a bone conduction speaker. For example, the advice unit can communicate the next steps in the surgery and points to pay attention to to the surgeon. The advice unit can use a generating AI to provide advice and points to note to the surgeon according to the progress of the surgery. This enhances the surgeon's concentration and improves the accuracy of the surgery by having the generating AI provide advice and points to note according to the progress of the surgery. Some or all of the above processing in the advice unit may be performed using a generating AI or not. For example, when the generating AI provides advice and points to note according to the progress of the surgery, the advice unit can have the generating AI estimate the surgeon's emotions and adjust the content and timing of the advice according to the surgeon's emotions.

[0036] The advice unit can provide advice and points of caution to the surgeon through a bone conduction speaker. The advice unit can provide advice and points of caution to the surgeon through a bone conduction speaker, for example. The advice unit can use generative AI to provide advice and points of caution to the surgeon according to the progress of the surgery. For example, the advice unit can tell the surgeon the next steps in the surgery and points to pay attention to. The advice unit can use generative AI to provide advice and points of caution to the surgeon according to the progress of the surgery. This allows the surgeon to maintain concentration during surgery by providing advice and points of caution through a bone conduction speaker. Some or all of the above processing in the advice unit may be performed using generative AI or not. For example, when the generative AI provides advice and points of caution according to the progress of the surgery, the generative AI can estimate the surgeon's emotions and adjust the content and timing of the advice according to the surgeon's emotions.

[0037] The analysis unit can analyze environmental information such as temperature and humidity in the operating room and identify factors that affect the progress of surgery. For example, if the temperature in the operating room is too high, the generating AI can suggest adjusting the cooling system. If the humidity in the operating room is too low, the generating AI can suggest using a humidifier. If the lighting in the operating room is inappropriate, the generating AI can suggest adjusting the lighting. In this way, by analyzing environmental information in the operating room, factors that affect the progress of surgery can be identified and appropriate countermeasures can be proposed. Some or all of the above processing in the analysis unit may be performed using the generating AI, or it may be performed without using the generating AI. For example, the analysis unit can input environmental information such as temperature and humidity in the operating room into the generating AI, and the generating AI can analyze this data to identify factors that affect the progress of surgery and propose appropriate countermeasures.

[0038] The analysis unit can analyze a patient's past surgical history and medical history to identify risk factors related to the current surgery. For example, the analysis unit can identify the risk of complications related to the current surgery from the patient's past surgical history. The analysis unit can identify diseases that may affect the current surgery from the patient's medical history. The analysis unit can comprehensively analyze the patient's past surgical history and medical history to identify risk factors in the current surgery. In this way, by analyzing the patient's past surgical history and medical history, risk factors related to the current surgery can be identified, thereby improving the safety of the surgery. Some or all of the above processing in the analysis unit may be performed using a generation AI, or it may be performed without a generation AI. For example, the analysis unit can input the patient's past surgical history and medical history into a generation AI, and the generation AI can analyze this data to identify risk factors related to the current surgery.

[0039] The analysis unit can analyze audio information from within the operating room to understand the communication status of the surgical team. For example, the analysis unit can analyze whether communication among the surgical team is proceeding smoothly from the audio information within the operating room. The analysis unit can analyze the stress level of the surgical team from the audio information within the operating room. The analysis unit can analyze the level of cooperation among the surgical team from the audio information within the operating room. In this way, by analyzing the audio information within the operating room, the communication status of the surgical team can be understood, and the progress of the surgery can be made smoother. Some or all of the above processing in the analysis unit may be performed using a generation AI, or it may be performed without a generation AI. For example, the analysis unit can input audio information from within the operating room into a generation AI, and the generation AI can analyze this data to understand the communication status of the surgical team.

[0040] The analysis unit can analyze the lighting conditions in the operating room and propose optimal lighting conditions. For example, if the lighting in the operating room is too dim, the generation AI can suggest adjusting the brightness of the lighting. If the lighting in the operating room is too bright, the generation AI can suggest adjusting the brightness of the lighting. If the color temperature of the lighting in the operating room is inappropriate, the generation AI can suggest adjusting the color temperature of the lighting. In this way, by analyzing the lighting conditions in the operating room, the optimal lighting conditions are proposed, improving the visibility of the surgery. Some or all of the above processing in the analysis unit may be performed using the generation AI, or it may be performed without the generation AI. For example, the analysis unit can input the lighting conditions in the operating room into the generation AI, and the generation AI can analyze this data and propose optimal lighting conditions.

[0041] The projection unit can customize the font size and color of the projected information according to the surgeon's eyesight and preferences. For example, the projection unit can adjust the font size according to the surgeon's eyesight. The projection unit can adjust the font color according to the surgeon's preferences. The projection unit can comprehensively customize the font size and color according to the surgeon's eyesight and preferences. This makes it easier for the surgeon to read the information by customizing the font size and color of the projected information. Some or all of the above processing in the projection unit may be performed using a generative AI, or it may be performed without a generative AI. For example, the projection unit can input data about the surgeon's eyesight and preferences into a generative AI, and the generative AI can analyze this data to customize the font size and color of the projected information.

[0042] The projection unit can add animations to the projected information that correspond to the progress of the surgery, making it easier to understand visually. For example, the projection unit can highlight important information with animations according to the progress of the surgery. The projection unit can display surgical procedures with animations according to the progress of the surgery. The projection unit can display the patient's biological information with animations according to the progress of the surgery. This makes it easier for surgeons to visually understand the information by adding animations according to the progress of the surgery. Some or all of the above processing in the projection unit may be performed using a generative AI, or it may be performed without a generative AI. For example, the projection unit can input data about the progress of the surgery into a generative AI, and the generative AI can analyze this data and add animations to the projected information.

[0043] The projection unit can integrate and display data from other medical devices in the operating room with the information it projects. For example, the projection unit can integrate and display biological information from monitors in the operating room. The projection unit can integrate and display video from cameras in the operating room. The projection unit can integrate and display data from sensors in the operating room. This allows surgeons to centrally check the information they need by integrating and displaying data from other medical devices in the operating room. Some or all of the above processing in the projection unit may be performed using a generation AI, or it may be performed without a generation AI. For example, the projection unit can input data from other medical devices in the operating room into a generation AI, which can then analyze and integrate this data and display it as projected information.

[0044] The projection unit can add a video guide of the surgical procedure to the projected information, making it accessible to the surgeon. For example, the projection unit can project a video guide of the surgical procedure for the surgeon to refer to. The projection unit can adjust the playback of the video guide according to the progress of the surgery. The projection unit can play the video guide at the time the surgeon needs it. This makes it easier for the surgeon to review the surgical procedure by adding a video guide of the surgical procedure. Some or all of the above processing in the projection unit may be performed using or without a generative AI. For example, the projection unit can input a video guide of the surgical procedure into a generative AI, which can then analyze this data and display it as projected information.

[0045] The advice unit can include specific procedures based on past surgical data and successful cases in its advice. For example, the advice unit can include specific procedures in its advice based on past surgical data. The advice unit can include specific procedures in its advice based on successful cases. The advice unit can comprehensively analyze past surgical data and successful cases and include specific procedures in its advice. This allows surgeons to receive more specific advice by including specific procedures based on past surgical data and successful cases. Some or all of the above processing in the advice unit may be performed using a generative AI, or it may be performed without a generative AI. For example, the advice unit can input past surgical data and successful cases into a generative AI, which can then analyze this data and include specific procedures in its advice.

[0046] The advice unit can add surgical risk factors and precautions to the advice in real time. For example, the advice unit can analyze surgical risk factors in real time and add them to the advice. The advice unit can analyze surgical precautions in real time and add them to the advice. The advice unit can comprehensively analyze surgical risk factors and precautions and add them to the advice. This allows surgeons to receive necessary information immediately during surgery by adding surgical risk factors and precautions in real time. Some or all of the above processing in the advice unit may be performed using a generation AI, or it may be performed without a generation AI. For example, the advice unit can input surgical risk factors and precautions into a generation AI, which can then analyze this data and add it to the advice.

[0047] The advisory department can incorporate the opinions and suggestions of other medical staff in the operating room into its advice. For example, the advisory department can collect the opinions of other medical staff in the operating room and incorporate them into its advice. The advisory department can collect the suggestions of other medical staff in the operating room and incorporate them into its advice. The advisory department can comprehensively analyze the opinions and suggestions of other medical staff in the operating room and incorporate them into its advice. This allows surgeons to receive advice from a more multifaceted perspective by incorporating the opinions and suggestions of other medical staff in the operating room. Some or all of the above processing in the advisory department may be performed using a generative AI, or not. For example, the advisory department can input the opinions and suggestions of other medical staff in the operating room into a generative AI, which can then analyze this data and incorporate it into the advice.

[0048] The advice unit can include suggestions for postoperative care and follow-up in its advice. For example, the advice unit can include suggestions regarding postoperative care in its advice. The advice unit can also include suggestions regarding postoperative follow-up in its advice. The advice unit can comprehensively analyze suggestions regarding postoperative care and follow-up and include them in its advice. This allows surgeons to receive specific advice regarding postoperative patient care by including suggestions for postoperative care and follow-up. Some or all of the above processing in the advice unit may be performed using or without a generative AI. For example, the advice unit can input data regarding postoperative care and follow-up into a generative AI, which can then analyze this data and reflect it in the advice.

[0049] The system according to the embodiment is not limited to the example described above, and various modifications are possible, for example, as follows.

[0050] The analysis unit can analyze the surgeon's movements in real time during surgery and evaluate the accuracy and efficiency of those movements. For example, it can analyze the surgeon's hand movements and evaluate whether the surgical instruments are being used appropriately. The analysis unit can analyze the speed and accuracy of the surgeon's movements and provide feedback according to the progress of the surgery. Furthermore, the analysis unit can record the surgeon's movements and use them later for review and training. This can improve the accuracy and efficiency of the surgeon's movements and increase the success rate of surgery.

[0051] The projection unit can provide surgeons with necessary information via voice during surgery. For example, it can communicate the progress of the surgery and the patient's vital signs to the surgeon via voice. The projection unit can provide important information via voice so that surgeons can confirm the information without moving their eyes. Furthermore, the projection unit can communicate the next steps and points to note to the surgeon via voice as the surgery progresses. This allows surgeons to confirm information via voice in addition to visual information, improving the accuracy and efficiency of the surgery.

[0052] The analysis unit can analyze the surgeon's posture during surgery and provide feedback to help maintain proper posture. For example, it can analyze the surgeon's spinal angle and shoulder position to evaluate whether their posture is appropriate. If the surgeon is in an inappropriate posture, the analysis unit can provide specific advice on how to correct it. Furthermore, the analysis unit can record the surgeon's posture, which can be used later for review and training. This can help improve the surgeon's posture and reduce fatigue during surgery.

[0053] The projection unit can visually highlight information that surgeons need during surgery. For example, it can highlight important information with color or animation. By visually highlighting important information according to the progress of the surgery, the projection unit helps surgeons avoid missing important details. Furthermore, the projection unit can track the surgeon's gaze and provide visual highlighting if their gaze is not directed towards important information. This allows surgeons to quickly access the information they need, improving the accuracy and efficiency of the surgery.

[0054] The analysis unit can analyze the surgeon's hand movements during surgery and evaluate the accuracy and efficiency of those movements. For example, it can analyze the surgeon's hand movements in real time and evaluate whether the surgical instruments are being used appropriately. The analysis unit can analyze the speed and accuracy of the surgeon's hand movements and provide feedback according to the progress of the surgery. Furthermore, the analysis unit can record the surgeon's hand movements, which can then be used for review and training. This can improve the accuracy and efficiency of the surgeon's hand movements and increase the success rate of surgery.

[0055] The projection unit can visually highlight information that surgeons need during surgery. For example, it can highlight important information with color or animation. By visually highlighting important information according to the progress of the surgery, the projection unit helps surgeons avoid missing important details. Furthermore, the projection unit can track the surgeon's gaze and provide visual highlighting if their gaze is not directed towards important information. This allows surgeons to quickly access the information they need, improving the accuracy and efficiency of the surgery.

[0056] The analysis unit can analyze the surgeon's posture during surgery and provide feedback to help maintain proper posture. For example, it can analyze the surgeon's spinal angle and shoulder position to evaluate whether their posture is appropriate. If the surgeon is in an inappropriate posture, the analysis unit can provide specific advice on how to correct it. Furthermore, the analysis unit can record the surgeon's posture, which can be used later for review and training. This can help improve the surgeon's posture and reduce fatigue during surgery.

[0057] The following briefly describes the processing flow for example form 1.

[0058] Step 1: The analysis unit performs real-time video analysis of the operating room situation. The analysis unit analyzes video and biological information obtained from cameras and sensors in the operating room in real time, and uses generated AI to analyze the progress of the surgery and the patient's biological information. For example, it analyzes biological information such as the patient's heart rate, blood pressure, and oxygen saturation in real time to understand the stage of the surgery and the duration of the surgery. Step 2: The projection unit projects the information analyzed by the analysis unit onto the glasses-type device. The projection unit is designed to project the information extracted by the generating AI onto the glasses-type device, allowing surgeons to view the information without moving their eyes. For example, it can display the progress of surgery and the patient's vital signs on the glasses' display in real time. Step 3: The advice unit provides advice to the surgeon based on the information projected by the projection unit. The advice unit's generating AI provides advice and points to note to the surgeon according to the progress of the surgery, and communicates this to the surgeon through a bone conduction speaker. For example, it communicates the next steps in the surgery and points to be careful of to the surgeon.

[0059] (Example of form 2) An embodiment of the present invention provides a smart surgical agent, a glasses-type device that assists surgeons in making accurate and rapid decisions during surgery. This device analyzes the operating room situation in real time and projects important biometric information and surgical procedures visually onto the glasses. It also provides advice and warnings from a generating AI via a bone conduction speaker, enhancing the surgeon's concentration. This improves the success rate of surgery and ensures patient safety. For example, cameras and sensors are placed in the operating room to analyze the situation in real time. These devices collect the progress of the surgery and the patient's biometric information and transmit it to the generating AI. The generating AI analyzes this data and extracts important information, such as the patient's heart rate, blood pressure, and the progress of the surgery. The generated AI then projects the extracted information onto the glasses-type device. The glasses-type device is designed so that the surgeon can view the information without moving their eyes. This allows the surgeon to view necessary information in real time during surgery. For example, the progress of the surgery and the patient's biometric information are displayed on the glasses' screen. Furthermore, the generating AI provides advice and warnings to the surgeon according to the progress of the surgery. These pieces of advice and cautionary notes are communicated to the surgeon via bone conduction speakers. For example, they include the next steps in the surgery and points to be aware of. This allows the surgeon to maintain focus and perform more precise surgery. This system improves surgical success rates and ensures patient safety. Because surgeons can access necessary information in real time during surgery, they can make quick and accurate decisions. Furthermore, advice and cautionary notes from the generated AI improve surgical precision and reduce the burden on the doctor. This improves the quality of medical care and provides patients with safer and more effective treatment. Thus, smart surgical agents can help surgeons make accurate and rapid decisions during surgery, improving surgical success rates and patient safety.

[0060] The smart surgical agent according to this embodiment comprises an analysis unit, a projection unit, and an advice unit. The analysis unit performs real-time video analysis of the operating room environment. For example, the analysis unit analyzes video and biological information obtained from cameras and sensors in the operating room in real time. The analysis unit can analyze the progress of the surgery and the patient's biological information using generative AI. For example, the analysis unit can analyze biological information such as the patient's heart rate, blood pressure, and oxygen saturation in real time. The analysis unit can also analyze the progress of the surgery in real time and grasp the stage of the surgery and the duration of the surgery. The projection unit projects the information analyzed by the analysis unit onto a glasses-type device. For example, the projection unit can project information extracted by generative AI onto the glasses-type device. The projection unit is designed so that the surgeon can check the information without moving their gaze. For example, the projection unit can display the progress of the surgery and the patient's biological information on the glasses' display. The projection unit can project the progress of the surgery and the patient's biological information in real time using generative AI. The advice unit provides advice to the surgeon based on the information projected by the projection unit. The advice unit can, for example, use a generating AI to provide the surgeon with advice and points to note according to the progress of the surgery. The advice unit can also provide advice and points to note to the surgeon through a bone conduction speaker. For example, the advice unit can communicate the next steps in the surgery and points to pay attention to to the surgeon. The advice unit can use a generating AI to provide advice and points to note to the surgeon according to the progress of the surgery. As a result, the smart surgical agent according to the embodiment can help the surgeon make accurate and rapid decisions during surgery, thereby improving the success rate of the surgery and the safety of the patient.

[0061] The analysis unit performs real-time video analysis of the operating room situation. For example, the analysis unit analyzes video and biological information obtained from cameras and sensors in the operating room in real time. Specifically, high-resolution cameras installed in the operating room capture the surgery and transmit the video data to the analysis unit. The analysis unit can use generative AI to analyze the progress of the surgery and the patient's biological information. The generative AI analyzes the video data, identifies each stage of the surgery, and understands the progress of the surgery. For example, the generative AI recognizes the movement and position of surgical instruments and analyzes the progress of the surgery in real time. It can also analyze biological information such as the patient's heart rate, blood pressure, and oxygen saturation in real time. As a result, the analysis unit can constantly monitor the patient's condition during surgery and immediately detect any abnormalities. Furthermore, the analysis unit can analyze the progress of the surgery in real time and understand the stage of the surgery and the duration of the surgery. For example, it measures the time from the start to the end of the surgery and records the time taken for each stage of the surgery. This allows for evaluation of the efficiency of the surgery and identification of areas for improvement. The analysis department centrally manages this information and can collaborate with other systems and departments as needed. For example, the analyzed data is stored on a cloud server, making it accessible to other medical staff and systems. This allows the analysis department to understand the situation in the operating room in real time and improve surgical success rates and patient safety.

[0062] The projection unit projects information analyzed by the analysis unit onto a glasses-type device. For example, the projection unit can project information extracted by a generative AI onto the glasses-type device. Specifically, the projection unit displays information on a display built into the glasses-type device worn by the surgeon. The glasses-type device is designed to allow the surgeon to view information without moving their eyes. For example, the projection unit can display the progress of surgery and the patient's vital signs on the glasses' display. The progress of surgery includes each stage of the surgery, the position of surgical instruments, and the duration of the surgery. The patient's vital signs, such as heart rate, blood pressure, and oxygen saturation, are displayed in real time. This allows the surgeon to instantly check necessary information during surgery, improving the efficiency and accuracy of the operation. Furthermore, the projection unit can use generative AI to project the progress of surgery and the patient's vital signs in real time. The generative AI analyzes the progress of surgery and the patient's vital signs, extracts important information, and projects it onto the glasses-type device. For example, if an abnormality occurs during surgery, the generative AI immediately detects this information and displays a warning to the surgeon. This allows the surgeon to respond quickly without missing important information during surgery. The projection unit can update this information in real time, always providing the latest information. This allows the projection unit to help surgeons make accurate and rapid decisions during surgery, improving surgical success rates and patient safety.

[0063] The advice unit provides advice to the surgeon based on the information projected by the projection unit. For example, the advice unit's generating AI can provide the surgeon with advice and points to note according to the progress of the surgery. Specifically, the advice unit presents points to pay attention to and the next steps for the surgeon at each stage of the surgery. For example, as the surgery progresses, it informs the surgeon of the next surgical instruments to be used and the procedure. Also, if an abnormality occurs during the surgery, the advice unit provides the surgeon with the cause and how to deal with it. The advice unit can also provide advice and points to note to the surgeon through a bone conduction speaker. Because the bone conduction speaker can transmit sound directly to the surgeon's ear, it can reliably convey important information without being interfered with by noise or other sounds during the surgery. For example, the advice unit can inform the surgeon of the next steps in the surgery and points to pay attention to. The generating AI analyzes the progress of the surgery and the patient's biological information, and extracts and provides the most important information for the surgeon. This allows the surgeon to immediately obtain the information they need during the surgery, improving the efficiency and accuracy of the surgery. Furthermore, the advice unit can collect feedback from the surgeon and continuously improve the accuracy and effectiveness of the advice. For example, based on feedback from surgeons, the advice department can review its content and delivery methods to provide more effective advice. This allows the advice department to support surgeons in making accurate and rapid decisions during surgery, thereby improving surgical success rates and patient safety.

[0064] The analysis unit can analyze video and biological information obtained from cameras and sensors in the operating room in real time. For example, the analysis unit can analyze video and biological information obtained from cameras and sensors in the operating room in real time. The analysis unit can use generative AI to analyze the progress of the surgery and the patient's biological information. For example, the analysis unit can analyze biological information such as the patient's heart rate, blood pressure, and oxygen saturation in real time. In addition, the analysis unit can analyze the progress of the surgery in real time and grasp the stage of the surgery and the duration of the surgery. This allows for the rapid provision of necessary information to surgeons by analyzing the situation in the operating room in real time. Some or all of the above processing in the analysis unit may be performed using generative AI, or it may be performed without generative AI. For example, the analysis unit can input video and biological information obtained from cameras and sensors in the operating room into the generative AI, and the generative AI can analyze this data and extract important information.

[0065] The projection unit can project information extracted by the generating AI onto a glasses-type device. For example, the projection unit projects information extracted by the generating AI onto the glasses-type device. The projection unit is designed to allow surgeons to view information without moving their eyes. For example, the projection unit can display the progress of surgery and the patient's vital signs on the glasses' display. The projection unit can project the progress of surgery and the patient's vital signs in real time using the generating AI. This allows surgeons to view information without moving their eyes by projecting the information extracted by the generating AI onto the glasses-type device. Some or all of the above processing in the projection unit may be performed using the generating AI or not. For example, when the projection unit projects information extracted by the generating AI onto the glasses-type device, the generating AI can determine the priority of the information and prioritize the projection of important information.

[0066] The advice unit can use a generating AI to provide the surgeon with advice and points to note according to the progress of the surgery. The advice unit can provide advice and points to note to the surgeon via a bone conduction speaker. For example, the advice unit can communicate the next steps in the surgery and points to pay attention to to the surgeon. The advice unit can use a generating AI to provide advice and points to note to the surgeon according to the progress of the surgery. This enhances the surgeon's concentration and improves the accuracy of the surgery by having the generating AI provide advice and points to note according to the progress of the surgery. Some or all of the above processing in the advice unit may be performed using a generating AI or not. For example, when the generating AI provides advice and points to note according to the progress of the surgery, the advice unit can have the generating AI estimate the surgeon's emotions and adjust the content and timing of the advice according to the surgeon's emotions.

[0067] The advice unit can provide advice and points of caution to the surgeon through a bone conduction speaker. The advice unit can provide advice and points of caution to the surgeon through a bone conduction speaker, for example. The advice unit can use generative AI to provide advice and points of caution to the surgeon according to the progress of the surgery. For example, the advice unit can tell the surgeon the next steps in the surgery and points to pay attention to. The advice unit can use generative AI to provide advice and points of caution to the surgeon according to the progress of the surgery. This allows the surgeon to maintain concentration during surgery by providing advice and points of caution through a bone conduction speaker. Some or all of the above processing in the advice unit may be performed using generative AI or not. For example, when the generative AI provides advice and points of caution according to the progress of the surgery, the generative AI can estimate the surgeon's emotions and adjust the content and timing of the advice according to the surgeon's emotions.

[0068] The analysis unit can estimate the surgeon's emotions and adjust the analysis priority based on the estimated emotions. For example, if the surgeon is tense, the generation AI can prioritize analyzing important information related to the progress of the surgery. If the surgeon is relaxed, the generation AI can analyze detailed biometric information to provide information useful for the progress of the surgery. If the surgeon is tired, the generation AI can prioritize analyzing concise information related to the progress of the surgery. This allows for the appropriate provision of information necessary for the progress of the surgery by adjusting the analysis priority according to the surgeon's emotions. Emotion estimation is achieved using an emotion estimation function, such as an emotion engine or generation AI. The generation AI is, but is not limited to, text generation AI (e.g., LLM) or multimodal generation AI. Some or all of the above processing in the analysis unit may be performed using or without the generation AI. For example, the analysis unit can input the surgeon's facial expression data into the generation AI, which can estimate the surgeon's emotions and adjust the analysis priority based on those emotions.

[0069] The analysis unit can analyze environmental information such as temperature and humidity in the operating room and identify factors that affect the progress of surgery. For example, if the temperature in the operating room is too high, the generating AI can suggest adjusting the cooling system. If the humidity in the operating room is too low, the generating AI can suggest using a humidifier. If the lighting in the operating room is inappropriate, the generating AI can suggest adjusting the lighting. In this way, by analyzing environmental information in the operating room, factors that affect the progress of surgery can be identified and appropriate countermeasures can be proposed. Some or all of the above processing in the analysis unit may be performed using the generating AI, or it may be performed without using the generating AI. For example, the analysis unit can input environmental information such as temperature and humidity in the operating room into the generating AI, and the generating AI can analyze this data to identify factors that affect the progress of surgery and propose appropriate countermeasures.

[0070] The analysis unit can analyze a patient's past surgical history and medical history to identify risk factors related to the current surgery. For example, the analysis unit can identify the risk of complications related to the current surgery from the patient's past surgical history. The analysis unit can identify diseases that may affect the current surgery from the patient's medical history. The analysis unit can comprehensively analyze the patient's past surgical history and medical history to identify risk factors in the current surgery. In this way, by analyzing the patient's past surgical history and medical history, risk factors related to the current surgery can be identified, thereby improving the safety of the surgery. Some or all of the above processing in the analysis unit may be performed using a generation AI, or it may be performed without a generation AI. For example, the analysis unit can input the patient's past surgical history and medical history into a generation AI, and the generation AI can analyze this data to identify risk factors related to the current surgery.

[0071] The analysis unit can estimate the surgeon's emotions and adjust the display method of the analysis results based on the estimated emotions. For example, if the surgeon is tense, the generation AI can provide a simple and easy-to-read display method. If the surgeon is relaxed, the generation AI can provide a display method that includes detailed information. If the surgeon is tired, the generation AI can provide a display method that gets straight to the point. By adjusting the display method of the analysis results according to the surgeon's emotions, the information becomes easier for the surgeon to understand. Emotion estimation is achieved using an emotion estimation function, such as an emotion engine or generation AI. The generation AI is, but is not limited to, text generation AI (e.g., LLM) or multimodal generation AI. Some or all of the above processing in the analysis unit may be performed using the generation AI or not. For example, the analysis unit can input the surgeon's facial expression data into the generation AI, the generation AI can estimate the surgeon's emotions, and adjust the display method of the analysis results based on those emotions.

[0072] The analysis unit can analyze audio information from within the operating room to understand the communication status of the surgical team. For example, the analysis unit can analyze whether communication among the surgical team is proceeding smoothly from the audio information within the operating room. The analysis unit can analyze the stress level of the surgical team from the audio information within the operating room. The analysis unit can analyze the level of cooperation among the surgical team from the audio information within the operating room. In this way, by analyzing the audio information within the operating room, the communication status of the surgical team can be understood, and the progress of the surgery can be made smoother. Some or all of the above processing in the analysis unit may be performed using a generation AI, or it may be performed without a generation AI. For example, the analysis unit can input audio information from within the operating room into a generation AI, and the generation AI can analyze this data to understand the communication status of the surgical team.

[0073] The analysis unit can analyze the lighting conditions in the operating room and propose optimal lighting conditions. For example, if the lighting in the operating room is too dim, the generation AI can suggest adjusting the brightness of the lighting. If the lighting in the operating room is too bright, the generation AI can suggest adjusting the brightness of the lighting. If the color temperature of the lighting in the operating room is inappropriate, the generation AI can suggest adjusting the color temperature of the lighting. In this way, by analyzing the lighting conditions in the operating room, the optimal lighting conditions are proposed, improving the visibility of the surgery. Some or all of the above processing in the analysis unit may be performed using the generation AI, or it may be performed without the generation AI. For example, the analysis unit can input the lighting conditions in the operating room into the generation AI, and the generation AI can analyze this data and propose optimal lighting conditions.

[0074] The projection unit can estimate the surgeon's emotions and adjust the priority of the information projected based on the estimated emotions. For example, if the surgeon is tense, the generation AI can prioritize projecting important information regarding the progress of the surgery. If the surgeon is relaxed, the generation AI can project detailed biometric information. If the surgeon is tired, the generation AI can prioritize projecting concise information regarding the progress of the surgery. This allows for the appropriate provision of information necessary for the progress of the surgery by adjusting the priority of the information projected according to the surgeon's emotions. Emotion estimation is achieved using an emotion estimation function, such as an emotion engine or generation AI. The generation AI is, but is not limited to, text generation AI (e.g., LLM) or multimodal generation AI. Some or all of the above processing in the projection unit may be performed using or without the generation AI. For example, the projection unit can input the surgeon's facial expression data into the generation AI, which can estimate the surgeon's emotions and adjust the priority of the information projected based on those emotions.

[0075] The projection unit can customize the font size and color of the projected information according to the surgeon's eyesight and preferences. For example, the projection unit can adjust the font size according to the surgeon's eyesight. The projection unit can adjust the font color according to the surgeon's preferences. The projection unit can comprehensively customize the font size and color according to the surgeon's eyesight and preferences. This makes it easier for the surgeon to read the information by customizing the font size and color of the projected information. Some or all of the above processing in the projection unit may be performed using a generative AI, or it may be performed without a generative AI. For example, the projection unit can input data about the surgeon's eyesight and preferences into a generative AI, and the generative AI can analyze this data to customize the font size and color of the projected information.

[0076] The projection unit can add animations to the projected information that correspond to the progress of the surgery, making it easier to understand visually. For example, the projection unit can highlight important information with animations according to the progress of the surgery. The projection unit can display surgical procedures with animations according to the progress of the surgery. The projection unit can display the patient's biological information with animations according to the progress of the surgery. This makes it easier for surgeons to visually understand the information by adding animations according to the progress of the surgery. Some or all of the above processing in the projection unit may be performed using a generative AI, or it may be performed without a generative AI. For example, the projection unit can input data about the progress of the surgery into a generative AI, and the generative AI can analyze this data and add animations to the projected information.

[0077] The projection unit can estimate the surgeon's emotions and adjust the display time of the projected information based on the estimated emotions. For example, if the surgeon is tense, the generation AI can display important information for a longer period. If the surgeon is relaxed, the generation AI can set the display time of the information to normal. If the surgeon is tired, the generation AI can display important information for a shorter period. This allows the surgeon to properly review the information by adjusting the display time of the projected information according to their emotions. Emotion estimation is achieved using an emotion estimation function, such as an emotion engine or generation AI. The generation AI is, but is not limited to, text generation AI (e.g., LLM) or multimodal generation AI. Some or all of the above processing in the projection unit may be performed using or without the generation AI. For example, the projection unit can input the surgeon's facial expression data into the generation AI, which can estimate the surgeon's emotions and adjust the display time of the projected information based on those emotions.

[0078] The projection unit can integrate and display data from other medical devices in the operating room with the information it projects. For example, the projection unit can integrate and display biological information from monitors in the operating room. The projection unit can integrate and display video from cameras in the operating room. The projection unit can integrate and display data from sensors in the operating room. This allows surgeons to centrally check the information they need by integrating and displaying data from other medical devices in the operating room. Some or all of the above processing in the projection unit may be performed using a generation AI, or it may be performed without a generation AI. For example, the projection unit can input data from other medical devices in the operating room into a generation AI, which can then analyze and integrate this data and display it as projected information.

[0079] The projection unit can add a video guide of the surgical procedure to the projected information, making it accessible to the surgeon. For example, the projection unit can project a video guide of the surgical procedure for the surgeon to refer to. The projection unit can adjust the playback of the video guide according to the progress of the surgery. The projection unit can play the video guide at the time the surgeon needs it. This makes it easier for the surgeon to review the surgical procedure by adding a video guide of the surgical procedure. Some or all of the above processing in the projection unit may be performed using or without a generative AI. For example, the projection unit can input a video guide of the surgical procedure into a generative AI, which can then analyze this data and display it as projected information.

[0080] The advice unit can estimate the surgeon's emotions and adjust the content and timing of advice based on the estimated emotions. For example, if the surgeon is nervous, the generative AI can provide concise and to-the-point advice. If the surgeon is relaxed, the generative AI can provide detailed advice. If the surgeon is tired, the generative AI can provide advice at the appropriate time. This allows the surgeon to receive the necessary advice at the right time by adjusting the content and timing of advice according to their emotions. Emotion estimation is achieved using an emotion estimation function, such as an emotion engine or generative AI. The generative AI is, but is not limited to, text generation AI (e.g., LLM) or multimodal generation AI. Some or all of the above processing in the advice unit may be performed using or without the generative AI. For example, the advice unit can input the surgeon's facial expression data into the generative AI, which can estimate the surgeon's emotions and adjust the content and timing of advice based on those emotions.

[0081] The advice unit can include specific procedures based on past surgical data and successful cases in its advice. For example, the advice unit can include specific procedures in its advice based on past surgical data. The advice unit can include specific procedures in its advice based on successful cases. The advice unit can comprehensively analyze past surgical data and successful cases and include specific procedures in its advice. This allows surgeons to receive more specific advice by including specific procedures based on past surgical data and successful cases. Some or all of the above processing in the advice unit may be performed using a generative AI, or it may be performed without a generative AI. For example, the advice unit can input past surgical data and successful cases into a generative AI, which can then analyze this data and include specific procedures in its advice.

[0082] The advice unit can add surgical risk factors and precautions to the advice in real time. For example, the advice unit can analyze surgical risk factors in real time and add them to the advice. The advice unit can analyze surgical precautions in real time and add them to the advice. The advice unit can comprehensively analyze surgical risk factors and precautions and add them to the advice. This allows surgeons to receive necessary information immediately during surgery by adding surgical risk factors and precautions in real time. Some or all of the above processing in the advice unit may be performed using a generation AI, or it may be performed without a generation AI. For example, the advice unit can input surgical risk factors and precautions into a generation AI, which can then analyze this data and add it to the advice.

[0083] The advice unit can estimate the surgeon's emotions and adjust the tone and expression of the advice based on the estimated emotions. For example, if the surgeon is nervous, the generating AI can provide advice in a calm tone. If the surgeon is relaxed, the generating AI can provide advice in a cheerful tone. If the surgeon is tired, the generating AI can provide advice in a concise and easy-to-understand manner. By adjusting the tone and expression of the advice according to the surgeon's emotions, the surgeon can receive advice that is easier to understand. Emotion estimation is achieved using an emotion estimation function, such as an emotion engine or a generating AI. The generating AI is, but is not limited to, a text generation AI (e.g., LLM) or a multimodal generation AI. Some or all of the above processing in the advice unit may be performed using or without a generating AI. For example, the advice unit can input the surgeon's facial expression data into a generating AI, which can estimate the surgeon's emotions and adjust the tone and expression of the advice based on those emotions.

[0084] The advisory department can incorporate the opinions and suggestions of other medical staff in the operating room into its advice. For example, the advisory department can collect the opinions of other medical staff in the operating room and incorporate them into its advice. The advisory department can collect the suggestions of other medical staff in the operating room and incorporate them into its advice. The advisory department can comprehensively analyze the opinions and suggestions of other medical staff in the operating room and incorporate them into its advice. This allows surgeons to receive advice from a more multifaceted perspective by incorporating the opinions and suggestions of other medical staff in the operating room. Some or all of the above processing in the advisory department may be performed using a generative AI, or not. For example, the advisory department can input the opinions and suggestions of other medical staff in the operating room into a generative AI, which can then analyze this data and incorporate it into the advice.

[0085] The advice unit can include suggestions for postoperative care and follow-up in its advice. For example, the advice unit can include suggestions regarding postoperative care in its advice. The advice unit can also include suggestions regarding postoperative follow-up in its advice. The advice unit can comprehensively analyze suggestions regarding postoperative care and follow-up and include them in its advice. This allows surgeons to receive specific advice regarding postoperative patient care by including suggestions for postoperative care and follow-up. Some or all of the above processing in the advice unit may be performed using or without a generative AI. For example, the advice unit can input data regarding postoperative care and follow-up into a generative AI, which can then analyze this data and reflect it in the advice.

[0086] The system according to the embodiment is not limited to the example described above, and various modifications are possible, for example, as follows.

[0087] The analysis unit can analyze the surgeon's movements in real time during surgery and evaluate the accuracy and efficiency of those movements. For example, it can analyze the surgeon's hand movements and evaluate whether the surgical instruments are being used appropriately. The analysis unit can analyze the speed and accuracy of the surgeon's movements and provide feedback according to the progress of the surgery. Furthermore, the analysis unit can record the surgeon's movements and use them later for review and training. This can improve the accuracy and efficiency of the surgeon's movements and increase the success rate of surgery.

[0088] The projection unit can provide surgeons with necessary information via voice during surgery. For example, it can communicate the progress of the surgery and the patient's vital signs to the surgeon via voice. The projection unit can provide important information via voice so that surgeons can confirm the information without moving their eyes. Furthermore, the projection unit can communicate the next steps and points to note to the surgeon via voice as the surgery progresses. This allows surgeons to confirm information via voice in addition to visual information, improving the accuracy and efficiency of the surgery.

[0089] The advisory department can monitor the surgeon's stress level during surgery and provide advice to reduce stress. For example, it can analyze the surgeon's heart rate and skin electrical activity to assess their stress level. If the surgeon is experiencing high stress levels, the advisory department can suggest breathing exercises or short breaks to help them relax. Furthermore, the advisory department can provide specific advice to support the progress of the surgery, depending on the surgeon's stress level. This can reduce the surgeon's stress and improve the success rate of the surgery.

[0090] The analysis unit can analyze the surgeon's posture during surgery and provide feedback to help maintain proper posture. For example, it can analyze the surgeon's spinal angle and shoulder position to evaluate whether their posture is appropriate. If the surgeon is in an inappropriate posture, the analysis unit can provide specific advice on how to correct it. Furthermore, the analysis unit can record the surgeon's posture, which can be used later for review and training. This can help improve the surgeon's posture and reduce fatigue during surgery.

[0091] The projection unit can visually highlight information that surgeons need during surgery. For example, it can highlight important information with color or animation. By visually highlighting important information according to the progress of the surgery, the projection unit helps surgeons avoid missing important details. Furthermore, the projection unit can track the surgeon's gaze and provide visual highlighting if their gaze is not directed towards important information. This allows surgeons to quickly access the information they need, improving the accuracy and efficiency of the surgery.

[0092] The advisory unit can estimate the surgeon's emotions during surgery and provide advice tailored to those emotions. For example, if the surgeon is tense, it can provide advice to help them relax. If the surgeon is relaxed, the advisory unit can provide detailed advice regarding the progress of the surgery. Furthermore, if the surgeon is tired, the advisory unit can provide concise advice regarding the progress of the surgery. By providing advice tailored to the surgeon's emotions, the success rate of surgery can be improved.

[0093] The analysis unit can analyze the surgeon's hand movements during surgery and evaluate the accuracy and efficiency of those movements. For example, it can analyze the surgeon's hand movements in real time and evaluate whether the surgical instruments are being used appropriately. The analysis unit can analyze the speed and accuracy of the surgeon's hand movements and provide feedback according to the progress of the surgery. Furthermore, the analysis unit can record the surgeon's hand movements, which can then be used for review and training. This can improve the accuracy and efficiency of the surgeon's hand movements and increase the success rate of surgery.

[0094] The projection unit can visually highlight information that surgeons need during surgery. For example, it can highlight important information with color or animation. By visually highlighting important information according to the progress of the surgery, the projection unit helps surgeons avoid missing important details. Furthermore, the projection unit can track the surgeon's gaze and provide visual highlighting if their gaze is not directed towards important information. This allows surgeons to quickly access the information they need, improving the accuracy and efficiency of the surgery.

[0095] The advisory unit can estimate the surgeon's emotions during surgery and provide advice tailored to those emotions. For example, if the surgeon is tense, it can provide advice to help them relax. If the surgeon is relaxed, the advisory unit can provide detailed advice regarding the progress of the surgery. Furthermore, if the surgeon is tired, the advisory unit can provide concise advice regarding the progress of the surgery. By providing advice tailored to the surgeon's emotions, the success rate of surgery can be improved.

[0096] The analysis unit can analyze the surgeon's posture during surgery and provide feedback to help maintain proper posture. For example, it can analyze the surgeon's spinal angle and shoulder position to evaluate whether their posture is appropriate. If the surgeon is in an inappropriate posture, the analysis unit can provide specific advice on how to correct it. Furthermore, the analysis unit can record the surgeon's posture, which can be used later for review and training. This can help improve the surgeon's posture and reduce fatigue during surgery.

[0097] The following briefly describes the processing flow for example form 2.

[0098] Step 1: The analysis unit performs real-time video analysis of the operating room situation. The analysis unit analyzes video and biological information obtained from cameras and sensors in the operating room in real time, and uses generated AI to analyze the progress of the surgery and the patient's biological information. For example, it analyzes biological information such as the patient's heart rate, blood pressure, and oxygen saturation in real time to understand the stage of the surgery and the duration of the surgery. Step 2: The projection unit projects the information analyzed by the analysis unit onto the glasses-type device. The projection unit is designed to project the information extracted by the generating AI onto the glasses-type device, allowing surgeons to view the information without moving their eyes. For example, it can display the progress of surgery and the patient's vital signs on the glasses' display in real time. Step 3: The advice unit provides advice to the surgeon based on the information projected by the projection unit. The advice unit's generating AI provides advice and points to note to the surgeon according to the progress of the surgery, and communicates this to the surgeon through a bone conduction speaker. For example, it communicates the next steps in the surgery and points to be careful of to the surgeon.

[0099] The specific processing unit 290 transmits the result of the specific processing to the smart device 14. In the smart device 14, the control unit 46A causes the output device 40 to output the result of the specific processing. The microphone 38B acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0100] Data generation model 58 is a form of so-called generative AI (Artificial Intelligence). An example of data generation model 58 is ChatGPT (registered trademark) (Internet search).<URL: https: / / openai.com / blog / chatgpt> Examples of generative AI include text generation AI, image generation AI, and multimodal generation AI. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images (e.g., still image data or video data). The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference result in one or more data formats from audio data, text data, and image data. The data generation model 58 includes, for example, text generation AI, image generation AI, and multimodal generation AI. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization. The specific processing unit 290 performs the specific processing described above using the data generation model 58. The data generation model 58 may be a fine-tuned model that outputs inference results from prompts that do not contain instructions, in which case the data generation model 58 can output inference results from prompts that do not contain instructions. In the data processing device 12, etc., there are multiple types of data generation models 58, and the data generation model 58 includes AI other than generative AI. AI other than generative AI includes, for example, linear regression, logistic regression, decision trees, random forests, support vector machines (SVMs), k-means clustering, convolutional neural networks (CNNs), recurrent neural networks (RNNs), generative adversarial networks (GANs), or naive Bayes, and can perform various processes, but is not limited to these examples. Also, the AI ​​may be an AI agent. Furthermore, when the processing of each of the above parts is performed by the AI, the processing may be performed by the AI ​​in part or in whole, but is not limited to this example.Furthermore, processing performed by AI, including generative AI, may be replaced with rule-based processing, and rule-based processing may be replaced with processing performed by AI, including generative AI.

[0101] Furthermore, the processing performed by the data processing system 10 described above is carried out by the specific processing unit 290 of the data processing device 12 or the control unit 46A of the smart device 14, but it may also be carried out by the specific processing unit 290 of the data processing device 12 and the control unit 46A of the smart device 14. In addition, the specific processing unit 290 of the data processing device 12 acquires or collects information necessary for processing from the smart device 14 or an external device, and the smart device 14 acquires or collects information necessary for processing from the data processing device 12 or an external device.

[0102] Each of the multiple elements described above, including the analysis unit, projection unit, and advice unit, is implemented in at least one of the smart device 14 and the data processing unit 12. For example, the analysis unit uses the camera 42 and sensors of the smart device 14 to perform real-time video analysis of the operating room situation. The projection unit projects the analyzed information onto a glasses-type device using the display 40A of the smart device 14. The advice unit, for example, uses the specific processing unit 290 of the data processing unit 12 to generate AI that provides advice and points of caution to the surgeon according to the progress of the surgery, and transmits this to the surgeon via a bone conduction speaker. The correspondence between each unit and the device or control unit is not limited to the example described above, and various modifications are possible.

[0103] [Second Embodiment] Figure 3 shows an example of the configuration of the data processing system 210 according to the second embodiment.

[0104] As shown in Figure 3, the data processing system 210 includes a data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server.

[0105] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN and / or LAN.

[0106] The smart glasses 214 include a computer 36, a microphone 238, a speaker 240, a camera 42, and a communication interface 44. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, and camera 42 are also connected to the bus 52.

[0107] The microphone 238 receives voice signals from the user and accepts instructions from the user. The microphone 238 captures the voice signals from the user, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0108] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, which captures images of the area around the user (for example, an imaging range defined by a field of view equivalent to the field of vision of a typical healthy person).

[0109] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0110] Figure 4 shows an example of the main functions of the data processing device 12 and the smart glasses 214. As shown in Figure 4, the data processing device 12 performs specific processing by the processor 28. The storage 32 stores the specific processing program 56.

[0111] The processor 28 reads a specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 acting as a specific processing unit 290 according to the specific processing program 56 executed on the RAM 30.

[0112] Storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290. The identification processing unit 290 can estimate the user's emotions using the emotion identification model 59 and perform identification processing using the user's emotions. The emotion estimation function (emotion identification function) using the emotion identification model 59 performs various estimations and predictions regarding the user's emotions, including but not limited to these examples. Furthermore, emotion estimation and prediction also include, for example, emotion analysis.

[0113] In the smart glasses 214, specific processing is performed by the processor 46. The storage 50 stores a specific processing program 60. The processor 46 reads the specific processing program 60 from the storage 50 and executes the read specific processing program 60 on the RAM 48. The specific processing is realized by the processor 46 acting as a control unit 46A according to the specific processing program 60 executed on the RAM 48. The smart glasses 214 also have a data generation model 58 and an emotion identification model 59, similar to the data generation model and emotion identification model 59, and can perform processing similar to that of the specific processing unit 290 using these models.

[0114] Furthermore, other devices besides the data processing device 12 may also have the data generation model 58. For example, a server device may have the data generation model 58. In this case, the data processing device 12 obtains processing results (such as prediction results) using the data generation model 58 by communicating with the server device that has the data generation model 58. Also, the data processing device 12 may be a server device or a terminal device owned by the user (for example, a mobile phone, robot, home appliance, etc.).

[0115] The specific processing unit 290 transmits the result of the specific processing to the smart glasses 214. In the smart glasses 214, the control unit 46A causes the speaker 240 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0116] The data generation model 58 is a so-called generative AI. An example of a data generation model 58 is a generative AI such as ChatGPT. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and inference data such as audio data representing speech, text data representing text, and image data representing images (e.g., still image data or video data). The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference result in one or more data formats such as audio data, text data, and image data. The data generation model 58 includes, for example, text generation AI, image generation AI, and multimodal generation AI. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization. The specific processing unit 290 performs the specific processing described above using the data generation model 58. The data generation model 58 may be a fine-tuned model that outputs inference results from prompts that do not contain instructions, in which case the data generation model 58 can output inference results from prompts that do not contain instructions. In the data processing device 12, etc., there are multiple types of data generation models 58, and the data generation model 58 includes AI other than generative AI. AI other than generative AI includes, for example, linear regression, logistic regression, decision trees, random forests, support vector machines (SVM), k-means clustering, convolutional neural networks (CNN), recurrent neural networks (RNN), generative adversarial networks (GAN), or naive Bayes, and can perform various processes, but is not limited to these examples. Also, the AI ​​may be an AI agent. Furthermore, when the processing of each part described above is performed by the AI, the processing may be performed by the AI ​​in part or in whole, but is not limited to this example. Also, processing performed by an AI including a generative AI may be replaced by rule-based processing, and rule-based processing may be replaced by processing performed by an AI including a generative AI.

[0117] The data processing system 210 according to the second embodiment performs the same processing as the data processing system 10 according to the first embodiment. The processing by the data processing system 210 is performed by the specific processing unit 290 of the data processing device 12 or the control unit 46A of the smart glasses 214, but it may also be performed by the specific processing unit 290 of the data processing device 12 and the control unit 46A of the smart glasses 214. In addition, the specific processing unit 290 of the data processing device 12 acquires or collects information necessary for processing from the smart glasses 214 or an external device, and the smart glasses 214 acquires or collects information necessary for processing from the data processing device 12 or an external device.

[0118] Each of the multiple elements described above, including the analysis unit, projection unit, and advice unit, is implemented, for example, in at least one of the smart glasses 214 and the data processing unit 12. For example, the analysis unit uses the camera 42 and sensors of the smart glasses 214 to perform real-time video analysis of the operating room situation. The projection unit projects the analyzed information onto the glasses-type device using the display of the smart glasses 214. The advice unit, for example, uses the specific processing unit 290 of the data processing unit 12 to generate AI that provides advice and points of caution to the surgeon according to the progress of the surgery, and transmits this to the surgeon via a bone conduction speaker. The correspondence between each unit and the device or control unit is not limited to the example described above, and various modifications are possible.

[0119] [Third Embodiment] Figure 5 shows an example of the configuration of the data processing system 310 according to the third embodiment.

[0120] As shown in Figure 5, the data processing system 310 includes a data processing device 12 and a headset terminal 314. An example of the data processing device 12 is a server.

[0121] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN and / or LAN.

[0122] The headset terminal 314 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication interface 44, and a display 343. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, camera 42, and display 343 are also connected to the bus 52.

[0123] The microphone 238 receives voice signals from the user and accepts instructions from the user. The microphone 238 captures the voice signals from the user, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0124] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, which captures images of the area around the user (for example, an imaging range defined by a field of view equivalent to the field of vision of a typical healthy person).

[0125] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0126] Figure 6 shows an example of the main functions of the data processing device 12 and the headset terminal 314. As shown in Figure 6, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0127] The processor 28 reads a specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 acting as a specific processing unit 290 according to the specific processing program 56 executed on the RAM 30.

[0128] Storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290. The identification processing unit 290 can estimate the user's emotions using the emotion identification model 59 and perform identification processing using the user's emotions. The emotion estimation function (emotion identification function) using the emotion identification model 59 performs various estimations and predictions regarding the user's emotions, including but not limited to these examples. Furthermore, emotion estimation and prediction also include, for example, emotion analysis.

[0129] In the headset terminal 314, specific processing is performed by the processor 46. The storage 50 stores a specific program 60. The processor 46 reads the specific program 60 from the storage 50 and executes the read specific program 60 on the RAM 48. The specific processing is realized by the processor 46 acting as a control unit 46A according to the specific program 60 executed on the RAM 48. The headset terminal 314 also has a data generation model 58 and an emotion identification model 59, similar to the data generation model and emotion identification model 59, and can perform processing similar to that of the specific processing unit 290 using these models.

[0130] Furthermore, other devices besides the data processing device 12 may also have the data generation model 58. For example, a server device may have the data generation model 58. In this case, the data processing device 12 obtains processing results (such as prediction results) using the data generation model 58 by communicating with the server device that has the data generation model 58. Also, the data processing device 12 may be a server device or a terminal device owned by the user (for example, a mobile phone, robot, home appliance, etc.).

[0131] The specific processing unit 290 transmits the result of the specific processing to the headset terminal 314. In the headset terminal 314, the control unit 46A causes the speaker 240 and display 343 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0132] The data generation model 58 is a so-called generative AI. An example of a data generation model 58 is a generative AI such as ChatGPT. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and inference data such as audio data representing speech, text data representing text, and image data representing images (e.g., still image data or video data). The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference result in one or more data formats such as audio data, text data, and image data. The data generation model 58 includes, for example, text generation AI, image generation AI, and multimodal generation AI. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization. The specific processing unit 290 performs the specific processing described above using the data generation model 58. The data generation model 58 may be a fine-tuned model that outputs inference results from prompts that do not contain instructions, in which case the data generation model 58 can output inference results from prompts that do not contain instructions. In the data processing device 12, etc., there are multiple types of data generation models 58, and the data generation model 58 includes AI other than generative AI. AI other than generative AI includes, for example, linear regression, logistic regression, decision trees, random forests, support vector machines (SVM), k-means clustering, convolutional neural networks (CNN), recurrent neural networks (RNN), generative adversarial networks (GAN), or naive Bayes, and can perform various processes, but is not limited to these examples. Also, the AI ​​may be an AI agent. Furthermore, when the processing of each part described above is performed by the AI, the processing may be performed by the AI ​​in part or in whole, but is not limited to this example. Also, processing performed by an AI including a generative AI may be replaced by rule-based processing, and rule-based processing may be replaced by processing performed by an AI including a generative AI.

[0133] The data processing system 310 according to the third embodiment performs the same processing as the data processing system 10 according to the first embodiment. The processing by the data processing system 310 is performed by the specific processing unit 290 of the data processing device 12 or the control unit 46A of the headset terminal 314, but may also be performed by the specific processing unit 290 of the data processing device 12 and the control unit 46A of the headset terminal 314. In addition, the specific processing unit 290 of the data processing device 12 acquires or collects information necessary for processing from the headset terminal 314 or an external device, and the headset terminal 314 acquires or collects information necessary for processing from the data processing device 12 or an external device.

[0134] Each of the multiple elements described above, including the analysis unit, projection unit, and advice unit, is implemented in at least one of the headset terminal 314 and the data processing unit 12. For example, the analysis unit uses the camera 42 and sensors of the headset terminal 314 to perform real-time video analysis of the operating room situation. The projection unit uses the display 343 of the headset terminal 314 to project the analyzed information onto a glasses-type device. The advice unit uses the specific processing unit 290 of the data processing unit 12 to generate AI that provides advice and points of caution to the surgeon according to the progress of the surgery, and transmits this information to the surgeon via a bone conduction speaker. The correspondence between each unit and the device or control unit is not limited to the example described above and can be modified in various ways.

[0135] [Fourth Embodiment] Figure 7 shows an example of the configuration of the data processing system 410 according to the fourth embodiment.

[0136] As shown in Figure 7, the data processing system 410 includes a data processing device 12 and a robot 414. An example of the data processing device 12 is a server.

[0137] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN and / or LAN.

[0138] The robot 414 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication interface 44, and a controlled object 443. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, camera 42, and controlled object 443 are also connected to the bus 52.

[0139] The microphone 238 receives voice signals from the user and accepts instructions from the user. The microphone 238 captures the voice signals from the user, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0140] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS image sensor or CCD image sensor, which captures images of the area around the user (for example, an imaging range defined by a field of view equivalent to the field of vision of a typical healthy person).

[0141] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0142] The controlled object 443 includes a display device, LEDs in the eyes, and motors that drive the arms, hands, and feet. The posture and gestures of the robot 414 are controlled by controlling the motors of the arms, hands, and feet. Some of the robot 414's emotions can be expressed by controlling these motors. The robot 414's facial expressions can also be expressed by controlling the illumination state of the LEDs in its eyes.

[0143] Figure 8 shows an example of the main functions of the data processing device 12 and the robot 414. As shown in Figure 8, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0144] The processor 28 reads a specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 acting as a specific processing unit 290 according to the specific processing program 56 executed on the RAM 30.

[0145] Storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290. The identification processing unit 290 can estimate the user's emotions using the emotion identification model 59 and perform identification processing using the user's emotions. The emotion estimation function (emotion identification function) using the emotion identification model 59 performs various estimations and predictions regarding the user's emotions, including but not limited to these examples. Furthermore, emotion estimation and prediction also include, for example, emotion analysis.

[0146] In robot 414, specific processing is performed by processor 46. A specific program 60 is stored in storage 50. Processor 46 reads the specific program 60 from storage 50 and executes it on RAM 48. The specific processing is achieved by processor 46 acting as a control unit 46A according to the specific program 60 executed on RAM 48. Robot 414 also has data generation model 58 and emotion identification model 59, similar to those of the robot, and can perform processing similar to that of the specific processing unit 290 using these models.

[0147] Furthermore, other devices besides the data processing device 12 may also have the data generation model 58. For example, a server device may have the data generation model 58. In this case, the data processing device 12 obtains processing results (such as prediction results) using the data generation model 58 by communicating with the server device that has the data generation model 58. Also, the data processing device 12 may be a server device or a terminal device owned by the user (for example, a mobile phone, robot, home appliance, etc.).

[0148] The specific processing unit 290 transmits the result of the specific processing to the robot 414. In the robot 414, the control unit 46A causes the speaker 240 and the controlled object 443 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0149] The data generation model 58 is a so-called generative AI. An example of a data generation model 58 is a generative AI such as ChatGPT. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and inference data such as audio data representing speech, text data representing text, and image data representing images (e.g., still image data or video data). The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference result in one or more data formats such as audio data, text data, and image data. The data generation model 58 includes, for example, text generation AI, image generation AI, and multimodal generation AI. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization. The specific processing unit 290 performs the specific processing described above using the data generation model 58. The data generation model 58 may be a fine-tuned model that outputs inference results from prompts that do not contain instructions, in which case the data generation model 58 can output inference results from prompts that do not contain instructions. In the data processing device 12, etc., there are multiple types of data generation models 58, and the data generation model 58 includes AI other than generative AI. AI other than generative AI includes, for example, linear regression, logistic regression, decision trees, random forests, support vector machines (SVM), k-means clustering, convolutional neural networks (CNN), recurrent neural networks (RNN), generative adversarial networks (GAN), or naive Bayes, and can perform various processes, but is not limited to these examples. Also, the AI ​​may be an AI agent. Furthermore, when the processing of each part described above is performed by the AI, the processing may be performed by the AI ​​in part or in whole, but is not limited to this example. Also, processing performed by an AI including a generative AI may be replaced by rule-based processing, and rule-based processing may be replaced by processing performed by an AI including a generative AI.

[0150] The data processing system 410 according to the fourth embodiment performs the same processing as the data processing system 10 according to the first embodiment. The processing by the data processing system 410 is performed by the specific processing unit 290 of the data processing device 12 or the control unit 46A of the robot 414, but it may also be performed by the specific processing unit 290 of the data processing device 12 and the control unit 46A of the robot 414. In addition, the specific processing unit 290 of the data processing device 12 acquires or collects information necessary for processing from the robot 414 or an external device, and the robot 414 acquires or collects information necessary for processing from the data processing device 12 or an external device.

[0151] Each of the multiple elements described above, including the analysis unit, projection unit, and advice unit, is implemented in, for example, at least one of the robot 414 and the data processing unit 12. For example, the analysis unit uses the camera 42 and sensors of the robot 414 to perform real-time video analysis of the operating room situation. The projection unit projects the analyzed information onto a glasses-type device using the display of the robot 414. The advice unit, for example, uses the specific processing unit 290 of the data processing unit 12 to generate AI that provides advice and points of caution to the surgeon according to the progress of the surgery, and transmits this to the surgeon through a bone conduction speaker. The correspondence between each unit and the device or control unit is not limited to the example described above, and various modifications are possible.

[0152] Furthermore, the emotion identification model 59, acting as an emotion engine, may determine the user's emotion according to a specific mapping. Specifically, the emotion identification model 59 may determine the user's emotion according to a specific mapping, which is an emotion map (see Figure 9). Similarly, the emotion identification model 59 may also determine the robot's emotion, and the identification processing unit 290 may perform identification processing using the robot's emotion.

[0153] Figure 9 shows the emotion map 400, in which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. The closer to the center of the concentric circles, the more primitive the emotions are located. Further out of the concentric circles, emotions representing states and actions arising from mental states are located. Emotion is a concept that includes feelings and mental states. On the left side of the concentric circles, emotions that are generally generated from reactions occurring in the brain are located. On the right side of the concentric circles, emotions that are generally induced by situational judgment are located. Above and below the concentric circles, emotions that are generally generated from reactions occurring in the brain and induced by situational judgment are located. In addition, the emotion of "pleasure" is located on the upper side of the concentric circles, and the emotion of "displeasure" is located on the lower side. Thus, in the emotion map 400, multiple emotions are mapped based on the structure in which emotions arise, and emotions that are likely to occur simultaneously are mapped close together.

[0154] These emotions are distributed at the 3 o'clock position on the Emotion Map 400, and usually fluctuate between feelings of security and anxiety. In the right half of the Emotion Map 400, situational awareness takes precedence over internal feelings, resulting in a calm impression.

[0155] The inside of the Emotion Map 400 represents inner thoughts, while the outside represents actions. Therefore, the further you go from the outside of the Emotion Map 400, the more visible (expressed in actions) your emotions become.

[0156] Here, human emotions are based on various balances, such as posture and blood sugar levels. When these balances deviate from the ideal, it results in discomfort, and when they approach the ideal, it results in pleasure. Similarly, in robots, cars, and motorcycles, emotions can be created based on various balances, such as posture and battery level. When these balances deviate from the ideal, it results in discomfort, and when they approach the ideal, it results in pleasure. The emotion map can be generated based, for example, on Dr. Mitsuyoshi's emotion map (Research on a system for analyzing brain physiological signals of speech emotion recognition and emotion, Tokushima University, doctoral dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). The left half of the emotion map contains emotions belonging to a region called "response," where sensation is dominant. The right half of the emotion map contains emotions belonging to a region called "situation," where situational awareness is dominant.

[0157] The emotion map defines two emotions that promote learning. One is the emotion around the middle of the negative "repentance" and "reflection" on the situation side. In other words, it is when the robot experiences negative emotions such as "I never want to feel this way again" or "I don't want to be scolded again." The other is the emotion around the positive "desire" on the reaction side. In other words, it is when the robot has positive feelings such as "I want more" or "I want to know more."

[0158] The emotion identification model 59 inputs user input into a pre-trained neural network, obtains emotion values ​​representing each emotion shown in the emotion map 400, and determines the user's emotion. This neural network is pre-trained based on multiple training data sets, which are combinations of user input and emotion values ​​representing each emotion shown in the emotion map 400. Furthermore, this neural network is trained so that emotions located close together have similar values, as shown in the emotion map 900 in Figure 10. Figure 10 shows an example where multiple emotions such as "reassured," "calm," and "confident" have similar emotion values.

[0159] In the above embodiment, an example was given in which a specific process is performed by a single computer 22. However, the technology of this disclosure is not limited thereto, and a distributed processing method for the specific process may be used, which includes computer 22 and multiple other computers.

[0160] In the above embodiment, an example was given in which the specific processing program 56 is stored in the storage 32, but the technology of this disclosure is not limited thereto. For example, the specific processing program 56 may be stored in a portable, computer-readable, non-temporary storage medium such as a USB (Universal Serial Bus) memory. The specific processing program 56 stored in the non-temporary storage medium is installed in the computer 22 of the data processing device 12. The processor 28 executes specific processing according to the specific processing program 56.

[0161] Alternatively, the specific processing program 56 may be stored in a storage device such as a server connected to the data processing device 12 via the network 54, and the specific processing program 56 may be downloaded and installed on the computer 22 in response to a request from the data processing device 12.

[0162] Furthermore, it is not necessary to store the entirety of the specific processing program 56 in a storage device such as a server connected to the data processing device 12 via the network 54, or to store the entirety of the specific processing program 56 in the storage 32; it is acceptable to store only a portion of the specific processing program 56.

[0163] The following types of processors can be used as hardware resources to perform specific processing. Examples of processors include a CPU, a general-purpose processor that functions as a hardware resource to perform specific processing by executing software, i.e., a program. Other examples of processors include dedicated electrical circuits, such as FPGAs (Field-Programmable Gate Arrays), PLDs (Programmable Logic Devices), or ASICs (Application Specific Integrated Circuits), which have circuit configurations specifically designed to perform specific processing. All of these processors have built-in or connected memory, and all of them perform specific processing by using memory.

[0164] The hardware resource that performs a specific process may consist of one of these various processors, or it may consist of a combination of two or more processors of the same or different types (for example, a combination of multiple FPGAs, or a combination of a CPU and an FPGA). Alternatively, the hardware resource that performs a specific process may consist of a single processor.

[0165] Examples of configurations using a single processor include, firstly, a configuration in which one or more CPUs and software are combined to form a single processor, and this processor functions as a hardware resource that performs a specific process. Secondly, there is a configuration using a processor that realizes the functions of the entire system, including multiple hardware resources that perform a specific process, on a single IC chip, as exemplified by SoCs (System-on-a-chip). In this way, a specific process is realized using one or more of the above types of processors as hardware resources.

[0166] Furthermore, the hardware structure of these various processors can more specifically utilize electrical circuits that combine circuit elements such as semiconductor devices. Also, the specific processing described above is merely an example. Therefore, it goes without saying that unnecessary steps can be deleted, new steps added, or the processing order rearranged, as long as it does not deviate from the main purpose.

[0167] Furthermore, although the above-described examples were divided into four embodiments, some or all of these embodiments may be combined. Also, the smart device 14, smart glasses 214, headset terminal 314, and robot 414 are just examples, and they may be combined, or other devices may be used. Also, although the above-described examples were divided into two embodiments, Embodiment 1 and Embodiment 2, these may be combined.

[0168] The descriptions and illustrations presented above are detailed explanations of the technical aspects of this disclosure and are merely examples of the technical aspects. For example, the above descriptions of the structure, function, operation, and effect are examples of the structure, function, operation, and effect of the technical aspects of this disclosure. Therefore, it goes without saying that you may delete unnecessary parts, add new elements, or replace elements in the descriptions and illustrations presented above, as long as you do not deviate from the essence of the technical aspects of this disclosure. Furthermore, in order to avoid confusion and facilitate understanding of the technical aspects of this disclosure, explanations of common technical knowledge and other things that do not require special explanation to enable the implementation of the technical aspects of this disclosure have been omitted from the descriptions and illustrations presented above.

[0169] All documents, patent applications, and technical standards described herein are incorporated by reference to the same extent as if each individual document, patent application, and technical standard were specifically and individually noted to be incorporated by reference.

[0170] (Note 1) The analysis unit analyzes the situation in the operating room in real time, A projection unit that projects the information analyzed by the analysis unit onto a glasses-type device, The system includes an advice unit that provides advice to a surgeon based on the information projected by the projection unit. A system characterized by the following features. (Note 2) The aforementioned analysis unit, The system analyzes images and biological information obtained from cameras and sensors in the operating room in real time. The system described in Appendix 1, characterized by the features described herein. (Note 3) The projection unit is The generated AI projects extracted information onto a glasses-type device. The system described in Appendix 1, characterized by the features described herein. (Note 4) The aforementioned advice section, The AI ​​generates messages that provide surgeons with advice and warnings based on the progress of the surgery. The system described in Appendix 1, characterized by the features described herein. (Note 5) The aforementioned advice section, Providing advice and precautions to surgeons via bone conduction speakers. The system described in Appendix 1, characterized by the features described herein. (Note 6) The aforementioned analysis unit, The system estimates the surgeon's emotions and adjusts the analysis priorities based on the estimated emotions of the surgeon. The system described in Appendix 1, characterized by the features described herein. (Note 7) The aforementioned analysis unit, We analyze environmental information such as temperature and humidity inside the operating room to identify factors that affect the progress of surgery. The system described in Appendix 1, characterized by the features described herein. (Note 8) The aforementioned analysis unit, Analyze the patient's past surgical history and medical history to identify risk factors related to the current surgery. The system described in Appendix 1, characterized by the features described herein. (Note 9) The aforementioned analysis unit, The system estimates the surgeon's emotions and adjusts how the analysis results are displayed based on the estimated emotions. The system described in Appendix 1, characterized by the features described herein. (Note 10) The aforementioned analysis unit, Analyze audio information from within the operating room to understand the communication status of the surgical team. The system described in Appendix 1, characterized by the features described herein. (Note 11) The aforementioned analysis unit, We analyze the lighting conditions in the operating room and propose optimal lighting conditions. The system described in Appendix 1, characterized by the features described herein. (Note 12) The projection unit is The system estimates the surgeon's emotions and adjusts the priority of the information projected based on those estimated emotions. The system described in Appendix 1, characterized by the features described herein. (Note 13) The projection unit is The font size and color of the projected information can be customized according to the surgeon's eyesight and preferences. The system described in Appendix 1, characterized by the features described herein. (Note 14) The projection unit is The projected information will be enhanced with animations that reflect the progress of the surgery, making it easier to understand visually. The system described in Appendix 1, characterized by the features described herein. (Note 15) The projection unit is It estimates the surgeon's emotions and adjusts the display time of the projected information based on the estimated emotions of the surgeon. The system described in Appendix 1, characterized by the features described herein. (Note 16) The projection unit is The projected information integrates and displays data from other medical devices in the operating room. The system described in Appendix 1, characterized by the features described herein. (Note 17) The projection unit is The projected information will include video guides of surgical procedures for surgeons to refer to. The system described in Appendix 1, characterized by the features described herein. (Note 18) The aforementioned advice section, The system estimates the surgeon's emotions and adjusts the content and timing of advice based on those estimated emotions. The system described in Appendix 1, characterized by the features described herein. (Note 19) The aforementioned advice section, The advice should include specific procedures based on past surgical data and successful cases. The system described in Appendix 1, characterized by the features described herein. (Note 20) The aforementioned advice section, The advice will be updated in real time with information on risk factors and precautions during surgery. The system described in Appendix 1, characterized by the features described herein. (Note 21) The aforementioned advice section, The system estimates the surgeon's emotions and adjusts the tone and expression of advice based on those estimated emotions. The system described in Appendix 1, characterized by the features described herein. (Note 22) The aforementioned advice section, The advice should reflect the opinions and suggestions of other medical staff in the operating room. The system described in Appendix 1, characterized by the features described herein. (Note 23) The aforementioned advice section, The advice should include suggestions for post-operative care and follow-up. The system described in Appendix 1, characterized by the features described herein. [Explanation of symbols]

[0171] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Devices 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robots

Claims

1. The analysis unit analyzes the situation in the operating room in real time, A projection unit that projects the information analyzed by the analysis unit onto a glasses-type device, The system includes an advice unit that provides advice to a surgeon based on the information projected by the projection unit. A system characterized by the following features.

2. The aforementioned analysis unit, The system analyzes images and biological information obtained from cameras and sensors in the operating room in real time. The system according to feature 1.

3. The projection unit is The generated AI projects the extracted information onto a glasses-type device. The system according to feature 1.

4. The aforementioned advice section, The AI ​​generates and provides surgeons with advice and points to note based on the progress of the surgery. The system according to feature 1.

5. The aforementioned advice section, Providing advice and precautions to surgeons via bone conduction speakers. The system according to feature 1.

6. The aforementioned analysis unit, The system estimates the surgeon's emotions and adjusts the analysis priorities based on the estimated emotions of the surgeon. The system according to feature 1.

7. The aforementioned analysis unit, We analyze environmental information such as temperature and humidity inside the operating room to identify factors that affect the progress of surgery. The system according to feature 1.

8. The aforementioned analysis unit, Analyze the patient's past surgical history and medical history to identify risk factors related to the current surgery. The system according to feature 1.

9. The aforementioned analysis unit, The system estimates the surgeon's emotions and adjusts how the analysis results are displayed based on the estimated emotions. The system according to feature 1.

10. The aforementioned analysis unit, Analyze audio information from within the operating room to understand the communication status of the surgical team. The system according to feature 1.

Images