General-purpose distributed networked control system architecture for interventional medical surgical robot, and interventional surgical robot

Abstract

Disclosed are a general-purpose distributed networked control system architecture for an interventional medical surgical robot, and an interventional surgical robot. The core, i.e., a Remind middleware layer, in the architecture comprises a Remind interface module and a Remind service module; the interface module comprises a message communication interface, a hardware node registration interface, an anomaly uploading interface, and an anomaly processing interface; the service module comprises a local storage service, a message distribution service, and a communication service. Detected anomaly information is uploaded to the communication service by means of the anomaly uploading interface, the service sends the anomaly to all online hardware nodes by means of the message distribution service, and middleware of the hardware nodes promptly calls an anomaly processing function registered by means of the hardware node registration interface. Unified application layer development interfaces and services supporting a whole process from data storage to complex algorithm computation are used to provide different types of robot systems with mechanisms for establishing complex communication network topologies and anomaly interception mechanisms.

Description

General distributed network control system architecture for interventional medical surgical robots and interventional surgical robots Technical Field

[0001] The present invention relates to the field of interventional medicine, and in particular to a universal distributed network control system architecture for an interventional medical surgical robot and an interventional surgical robot. Background Art

[0002] Interventional therapy is a technology that uses minimally invasive methods under image guidance to achieve precise disease treatment. How to standardize the operation of modern interventional surgery while ensuring the efficiency and precision of the operation is a common problem faced by doctors. Therefore, driven by this problem, interventional surgical robots have emerged like mushrooms after rain and quickly covered multiple clinical procedures in the field of interventional therapy, including percutaneous interventional surgery, vascular interventional surgery, and bronchoscopic interventional surgery. The introduction of interventional surgical robots can not only standardize the intraoperative operation process of interventional surgery, provide doctors with a safe and comfortable operating environment, and provide patients with personalized treatment plans, but can even provide precise control and decision-making for complex intraoperative scenarios through artificial intelligence and Internet of Things technologies.

[0003] According to regulations from various countries' Food and Drug Administrations, surgical robots must be developed specifically for a specific type of surgery performed on a specific part of the human body. However, the development of surgical robots is a lengthy process, and coupled with the wide variety of interventional clinical procedures, the field of interventional surgery faces even greater challenges in achieving full roboticization.

[0004] The general paradigm adopted by existing interventional surgical robots has the following main problems:

[0005] 1. Poor reuse of components and modules: Due to the wide variety of interventional clinical procedures, there will be interventional surgical robots for different procedures in the future. If the system components or modules of different interventional surgical robots are not reusable, it means that the operating room needs to have multiple sets of robot systems. The cost of this incremental approach is huge, and the space in the operating room is limited, and multiple sets of robot systems are difficult to deploy at the same time. In other words, the reuse of the main modules of the interventional surgical robot can shorten the development time of the entire machine and save R&D and deployment costs. Based on this, the interventional operating room can implement the execution of multiple clinical procedures. For example, the same CT room will complete puncture surgeries in multiple parts, such as lung nodule puncture intervention, liver solid tumor puncture intervention, and interventional treatment in the pain department. Therefore, how to reuse the component modules of the interventional surgical robot system is one of the key issues in the field of interventional surgical robots moving towards full robotization.

[0006] 2. Lack of a unified communication architecture: With the development of modern interventional operating rooms and the diversification of medical devices, the number of message types in transmission protocols has increased, and complex network systems have increasingly stringent requirements for stable information transmission. Currently, there are a small number of low-level communication management plug-ins in the field of interventional surgical robots. For example, OpenIGTLink unifies the transmission protocol for image-guided surgical systems using three message formats: tracking, imaging, and control. For interventional surgical robots, OpenIGTLink provides a limited number of message types and only includes a unified medical image encoding format and network protocol for data exchange, lacking consideration for communication quality and security. In radiotherapy, there are significant differences in the type of information required, as well as the time and frequency of information acquisition. To address this issue, some scholars have adopted Dicom-RT for real-time image transmission based on the original DICOM protocol. However, this only unifies the medical image transmission portion. Therefore, the development of a communication protocol that unifies information transmission within and between interventional surgical robots to ensure interoperability is another key issue.

[0007] 3. Inadequate reliability mechanisms: In medical surgery, every tiny movement and decision directly impacts the patient's life and surgical outcome. Because interventional surgical robots involve highly precise manipulation and complex human-machine interaction, their reliability is paramount. Any hardware failure, software defect, or operational error can lead to irreversible medical consequences or even threaten the patient's life. Therefore, ensuring the reliability of surgical robots is not only a key step in advancing technological maturity but also a crucial component in ensuring patient safety and medical quality.

[0008] Currently, ROS is the most widely used underlying robotics development system in industry. As a robotics ecosystem, ROS provides many foundational functional modules (such as messaging, log collection, security, and simulation) and a comprehensive architecture (such as event-driven and loosely coupled). However, developing interventional surgical robots based on ROS still requires custom communication protocols and data classes. Furthermore, ROS's wide applicability has increased the cost of developing robots in specific areas.

[0009] The disclosure of the above background technology content is only used to assist in understanding the inventive concept and technical solution of the present invention. It does not necessarily belong to the prior art of this patent application, nor does it necessarily provide technical guidance. In the absence of clear evidence that the above content has been disclosed before the filing date of this patent application, the above background technology should not be used to evaluate the novelty and creativity of this application. Summary of the Invention

[0010] The purpose of this invention is to provide a general paradigm for robotics in interventional surgery while integrating a stable distributed communication architecture and robust reliability mechanisms.

[0011] In order to achieve the above object, the technical solution adopted by the present invention is as follows:

[0012] A general distributed network control system architecture for an interventional medical surgical robot includes an interventional surgical robot application software layer, an operating system layer, and a Remind middleware layer for connecting the two. The Remind middleware layer includes a Remind interface module and a Remind service module, wherein:

[0013] The Remind interface module has multiple interfaces that match the interventional surgery robot application software layer, including a hardware node registration interface and an abnormality upload interface;

[0014] The Remind service module has multiple services required to support the operation of the operating system layer, including message distribution service and communication service;

[0015] The two nodes to be communicated in the interventional surgery robot application software layer register an inter-node cooperation relationship through the hardware node registration interface, and the Remind middleware layer automatically establishes a communication channel through the registered cooperation relationship;

[0016] If the node business code of the interventional surgical robot application software layer detects an exception, the detected exception information is uploaded to the communication service through the exception upload interface, and the communication service sends the exception to each hardware node of the surgical robot through the message distribution service. After receiving the exception, the middleware on the hardware node promptly calls the exception handling function registered by the hardware node registration interface.

[0017] Furthermore, based on any one of the above technical solutions or a combination of multiple technical solutions, the Remind interface module further includes an exception handling interface, which is configured with a method for registering a processing function for predefined exceptions;

[0018] The node business code of the interventional surgery robot application software layer uses the processing function registration method of the exception handling interface to set the logic for handling exceptions to handle detected exceptions.

[0019] Furthermore, based on any one of the technical solutions or a combination of multiple technical solutions mentioned above, the Remind interface module also includes a message communication interface, and multiple nodes of the interventional surgery robot application software layer exchange information according to business processes through the message communication interface.

[0020] Further, based on any one of the above technical solutions or a combination of multiple technical solutions, the Remind interface module further includes an algorithm calling interface, and the services provided by the Remind service module further include algorithm services;

[0021] In response to the computing power demand of the node business of the interventional surgery robot application software layer, the interventional surgery robot application software layer calls the algorithm service through the algorithm calling interface.

[0022] Furthermore, based on any one of the above technical solutions or a combination of multiple technical solutions, the services provided by the Remind service module also include local storage services;

[0023] The node business code of the interventional surgery robot application software layer is supplemented with data that needs to be solidified through the local storage service.

[0024] Furthermore, based on any one of the technical solutions or a combination of multiple technical solutions described above, the local storage service supports the storage of multiple data types, including medical imaging data files, structured data, medical diagnostic text data files, and information interaction data of the entire surgical process.

[0025] Furthermore, based on any one of the technical solutions or a combination of multiple technical solutions described above, the high availability solution for the local database function provided by the local storage service includes a master-slave replication mode, a master-slave mode and / or a cluster mode.

[0026] Furthermore, based on any one of the above technical solutions or a combination of multiple technical solutions, the communication service is integrated with a node status synchronization service program, and the service type of the node status synchronization service program is a scheduled task, and its purpose is to scan the node information in the current registration table and kick inactive nodes out of the registration information;

[0027] If the node status synchronization service program scans and finds that the business node fails to report the status to the interventional brain central processing module of the interventional surgical robot system in a timely manner, the node registration information is updated according to the abnormal information found so that other nodes can perceive the abnormal information found.

[0028] Furthermore, based on any one of the technical solutions or a combination of multiple technical solutions mentioned above, the communication service integrates a communication quality adjustment service program, whose service type is a timed task, and its purpose is to monitor the communication transmission quality between the current surgical nodes. If the transmission rate of one or more nodes is monitored to exceed the preset rate range, the communication quality adjustment service program will make downgrade or upgrade adjustments according to the pre-configured transmission scheme.

[0029] Furthermore, based on any one of the technical solutions or a combination of multiple technical solutions described above, the communication service is integrated with an exception service program, and the exception upload interface uploads the detected exception information to the exception service program of the communication service. The service type of the exception service program is Restful API, which is configured to collect and record the service exceptions of the node.

[0030] Furthermore, based on any one of the technical solutions or a combination of multiple technical solutions described above, the communication service also integrates a discovery service program, which is configured to provide services based on the Restful API. Other nodes need to configure the connection information of the discovery service program and periodically register the node's own status to the discovery service program.

[0031] Furthermore, based on any one of the aforementioned technical solutions or a combination of multiple technical solutions, the message distribution service provides message queue middleware support, and its high availability solution includes active-standby mode and / or cluster mode.

[0032] Furthermore, based on any one of the above technical solutions or a combination of multiple technical solutions, the general distributed network control system architecture for interventional medical surgical robots further includes a cloud computing center layer and a hardware device layer, wherein the cloud computing center layer includes infrastructure as a service, platform as a service, and software as a service;

[0033] The hardware device layer and the operating system layer respectively correspond to the computer hardware devices required for the operation of the interventional surgical robot and the computer operating system for scheduling and using these hardware devices and the driver software contained therein.

[0034] Furthermore, based on any one of the above technical solutions or a combination of multiple technical solutions, the surgical robot system includes an interventional brain central processing module, a preoperative plan information generation module, an immersive navigation and control module, an interventional instrument perception module, and an interventional behavior execution module, and the interventional brain central processing module interacts with the preoperative plan information generation module to complete the generation of the interventional plan information set;

[0035] Receiving planning information from the preoperative planning information generation module, and initiating or terminating the surgical action through the immersive navigation and control module;

[0036] The interventional device perception module collects the perception of the intraoperative behavioral process and its results, and sends the perception information to the immersive navigation and control module for immersive experience display of the perception information;

[0037] After the intervention brain central processing module calculates the control instructions for the perception information, the intervention behavior execution module cooperates with the operator to complete the action response and perception feedback.

[0038] Furthermore, based on any one of the technical solutions or a combination of multiple technical solutions described above, the types of interventional surgical robots that can be connected include puncture interventional surgical robots, vascular interventional surgical robots, and bronchoscope-based interventional robots.

[0039] According to another aspect of the present invention, an interventional surgical robot is provided, which adopts the universal distributed network control system architecture as described above.

[0040] The functional modules of the interventional surgery robot system, divided according to the process of performing interventional surgery, include an interventional brain central processing module, a preoperative plan information generation module, an immersive navigation and control module, an interventional instrument perception module, and an interventional behavior execution module. The interventional physician cloud computing module interacts with the preoperative plan information generation module to complete the generation of the interventional plan information set.

[0041] Receiving planning information from the preoperative planning information generation module, and initiating or terminating the surgical action through the immersive navigation and control module;

[0042] The interventional device perception module collects the perception of the intraoperative behavioral process and its results, and sends the perception information to the immersive navigation and control module for immersive experience display of the perception information;

[0043] After the intervention brain central processing module calculates the control instructions for the perception information, the intervention behavior execution module cooperates with the operator to complete the action response and perception feedback.

[0044] The types of interventional surgical robots include puncture interventional surgical robots, vascular interventional surgical robots, and bronchoscope-based interventional robots.

[0045] The beneficial effects brought about by the technical solution provided by the present invention are as follows:

[0046] 1) The core distributed Remind middleware is built into the general paradigm of interventional robotics. Leveraging a unified application layer development interface and services that support the entire process from data storage to complex algorithm calculations, it provides mechanisms for establishing complex communication network topologies and capturing exceptions for different types of robotic systems.

[0047] 2) Applicable to various types of interventional surgical robots, such as puncture interventional surgical robots, vascular interventional surgical robots, bronchoscope-based interventional robots, etc.

[0048] BRIEF DESCRIPTION OF THE DRAWINGS

[0049] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are only some embodiments recorded in this application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0050] FIG1 is a schematic block diagram of a general distributed network control system architecture for an interventional medical surgical robot provided by an exemplary embodiment of the present invention. DETAILED DESCRIPTION

[0051] In order to enable those skilled in the art to better understand the solutions of the present invention, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the embodiments described are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts should fall within the scope of protection of the present invention.

[0052] It should be noted that the terms "first", "second", etc. in the description and claims of the present invention and the above-mentioned drawings are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that the numbers used in this way can be interchanged where appropriate, so that the embodiments of the present invention described herein can be implemented in an order other than those illustrated or described herein. In addition, the terms "including" and "having" and any variations thereof are intended to cover non-exclusive inclusions. For example, a process, method, apparatus, product or device that includes a series of steps or units is not necessarily limited to those steps or units clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices.

[0053] To address key issues such as component module reuse, the lack of a unified communication architecture, and insufficient reliability mechanisms, a universal paradigm for interventional surgery robots is needed. Therefore, this paper proposes a new underlying universal paradigm for interventional surgery robots to meet the needs of interventional surgery robots.

[0054] In one embodiment of the present invention, a general distributed network control system architecture for interventional medical surgical robots is provided to propose a general paradigm for interventional surgical robots, whose main features include: a stable distributed communication architecture; a unified message protocol; a reliable abnormal situation response mechanism, etc.

[0055] The general paradigm of robots includes three basic functional modules: a sensing module, an intelligent module, and an execution module. The sensing module serves as the interventional physician's "eyes" and "hands," providing the robot with visual and tactile feedback to obtain external information. The intelligent module serves as the interventional physician's "brain," providing the robot with the ability to think, that is, after receiving external information, the robot begins to think about subsequent actions. The execution module serves as the interventional physician's "arm," providing the robot with the ability to act and complete the actions after thinking. Therefore, the surgical robot system can be divided into the following modules:

[0056] Interventional Brain Central Processing Module (IBCCM): Similar to the interventional physician's brain, it needs to store and distribute intraoperative control, sensing, and other information, integrate all core algorithm modules, and have self-learning and evolutionary capabilities;

[0057] Preoperative Planning Information Generation Module (IPGM): During the interventional procedure, doctors can interact with the IBCCM through it to generate the interventional planning information set;

[0058] Immersive Navigation and Control Module (ICNM): Receives planning information from the IPGM and allows interventional physicians to initiate or terminate each surgical action.

[0059] Interventional Device Perception Module (ITSM): collects the perception of all intraoperative behaviors and their results, and sends them to the ICNM for an immersive experience display of the perception information;

[0060] Interventional Behavior Execution Module (ITEM): After the IBCCM module calculates the control instructions based on the perception information, this module can cooperate with the physician to complete the response and perception feedback of each set of actions.

[0061] As shown in Figure 1, the general distributed network control system architecture consists of five layers:

[0062] The first layer is the Cloud Computing Center, which supports multiple cloud service models, including Infrastructure as a Service, Platform as a Service, and Software as a Service, providing users with flexible and efficient IT solutions.

[0063] The second layer is the interventional robot application software layer (Interventional Robot Application Software), which refers to the application software developed for different robots based on different functional requirements;

[0064] The third layer is the Remind Middleware layer, which includes the Remind interface module and the Remind service module. The Remind interface module has a unified application layer development interface, including development tools for C++ and Python. The Remind service module is deployed on the IBCCM (Interventional Brain Central Processing Module) and supports the services required for the operation of the interventional surgical robot.

[0065] The fourth layer is the operating system layer, which interacts with the interventional surgery robot application software layer through the Remind middleware layer;

[0066] The fifth layer is the hardware device layer. The hardware device layer and the operating system layer correspond to the computer hardware devices required for the operation of the interventional surgical robot and the computer operating system for scheduling and using these hardware devices and the driver software contained therein.

[0067] The combination of the first to third layers can provide a variety of mechanisms for different types of robotic systems, including mechanisms for establishing complex communication network topologies, mechanisms for capturing exceptions, and mechanisms for self-recovery of network layer exceptions.

[0068] The third layer, the Remind Middleware, is the core layer of this embodiment. By unifying the communication and interaction mechanisms between modules, the Remind Middleware layer not only significantly reduces dependence on specific equipment manufacturers but also enables the reuse of core functional modules and the rapid replacement of individual modules. Specifically, the various functions required for robot development are encapsulated into a distributed middleware software within the REMIND architecture. This distributed middleware plays a key role in the REMIND framework. Its core goal is to enable pluggable and independently upgradeable modules, reduce the operator learning curve, lower the development cost of interventional surgical robots, and accelerate robot development. All developers or robots participating in the REMIND ecosystem can develop and execute specific services using the REMIND middleware software.

[0069] To address challenges such as system heterogeneity, node open / closed principles, and independent replaceability within interventional surgical robot systems, the Remind middleware layer utilizes a universal, unified interface layer—the REMIND Interface—that interacts with the interventional surgical robot's application software layer, as shown in Figure 1. This layer addresses the specific needs of interventional surgical robots in highly complex clinical environments, including but not limited to precise surgical navigation, real-time medical image processing, and rapid response in emergency situations. It encapsulates the programming interfaces required by the REMIND ecosystem to support programmatic calls, including the Message Interface, the Device Registration Interface, the Exception Uploading Interface, the Exception Handling Interface, and the Advance Function Interface. These interfaces provide the communication, hardware node registration, exception uploading, exception resolution, and algorithm call functions required for interventional surgical robot development. These interfaces are described below:

[0070] The message communication interface is a key interface for communication between nodes in the interventional surgical robot system. It not only provides message transmission and exchange, but also integrates performance monitoring and fault recovery functions to ensure the stable transmission and reliability of key information during interventional surgery.

[0071] The hardware node registration interface is used to register hardware nodes. It provides developers with a unified hardware device registration and access function, achieving high customizability and scalability to meet different interventional surgery requirements.

[0072] The exception upload interface provides developers with the ability to upload these exceptions to the exception service program (described below), which is crucial for maintaining the continuity and safety of the interventional procedure;

[0073] The exception handling interface is an interface for resolving exceptions. It provides developers with the ability to automatically handle pre-defined exceptions, allowing the interventional surgical robot to quickly recover when encountering specific problems, reducing the risk of surgical interruption.

[0074] The algorithm calling interface provides developers with efficient and flexible algorithm calling functions, such as precise positioning and navigation algorithms under image guidance, or high-precision motion control algorithms.

[0075] To unify the hardware-level node interaction interface, the REMIND middleware layer uses wired or wireless networks as inter-node communication channels, thereby resolving interoperability issues arising from different operating systems and programming languages. For different robot nodes, the access provider implements the Message Interface according to their specific needs during development. This interface is then configured using the REMIND Interface methods to take effect. Configuration information includes the robot node IP address, robot node name, IBCCM IP address, and topology. After configuring the interventional surgical robot's topology, the REMIND middleware layer automatically registers with the IBCCM based on the configuration and establishes communication channels between the relevant nodes according to the topology requirements. Once the connection between the relevant nodes is established, the communicating parties negotiate a communication data key to ensure the validity and security of communication information during the surgery. To address exceptions, the REMIND middleware layer provides two solutions: exception uploading and exception handling. This flexible exception handling mechanism is key to the high reliability of the interventional surgical robot system, ensuring stable operation and patient safety even in the most complex surgical scenarios.

[0076] In addition to the universal unified interface layer, the REMIND middleware layer also uses the Remind service module. In interventional medicine, the middleware layer is the infrastructure that supports the key functions of interventional surgical robotic systems. These services must not only demonstrate high efficiency and stability during routine operations, but also maintain these performance levels under the high-pressure environments of surgery. These services include: On-Premise Storage Service, Message Distribution Service, Communication Service, and Computing Intensive Services. These services support the entire process from data storage to complex algorithm calculations. The following is a description of each of these services:

[0077] The local storage service provides local database functionality for the large amount of medical data generated during interventional surgery. Depending on the database type, its high availability solutions may include master-slave replication, master-slave mode, or cluster mode, which are key to ensuring data reliability and real-time backup during interventional surgery. The service defines a data storage structure for interventional surgery scenarios, which is divided into: intraoperative temporary status storage, medical image file storage, and structured data storage for the entire surgical process. The structured data storage for the entire surgical process is divided into three categories: preoperative, intraoperative, and postoperative. Preoperatively, it records all preoperative medical imaging information and its access index, preoperative diagnostic information corresponding to the surgery, patient identification information, etc.; intraoperatively, it records all information interacting between the robot's distributed nodes and marks them with synchronized timestamps to form a data logic relationship that conforms to the actual surgical situation; and postoperatively, it records the actual results of the surgery and its confirmation information.

[0078] The message distribution service provides message queue middleware support, ensuring the reliable transmission of real-time data streams and control commands from surgical robots to physician workstations during interventional procedures. High-availability solutions, such as active-standby and cluster modes, ensure the continuity of the message transmission system during critical surgical moments. The message distribution service not only supports real-time data transmission but also, in application scenarios like interventional surgery, supports large file transfers, eliminating the need for robotics developers to waste development effort on complex and diverse data communication scenarios.

[0079] The communication service integrates the Discovery service, the Service Discovery Cron Job, the QoS Coordinator Service, and the Exception Service. These services are crucial in interventional surgery. For example, real-time updates of the surgical robot's status and location, as well as ensuring the quality of image and data streams, are key factors for successful interventional surgery. These services are decoupled and independently deployed. The Discovery service provides a RESTful API-based service. All other nodes must configure connection information to the Discovery Service and periodically register their status with it. To achieve high availability, load balancing can be configured to route requests to the intranet DNS and thus to multiple deployed nodes. Note that implementing load balancing also requires a high availability solution. The Service Discovery Cron Job is a scheduled task that scans the node information in the current registry. Inactive nodes are removed from the registry. When deploying a high-availability solution, only one instance can execute each task. The QoS Coordinator Service is also a scheduled task. Its purpose is to monitor the communication transmission quality between the current surgical nodes. If one or more nodes are found to have low (or high) transmission rates, QoS will be downgraded (or upgraded) based on the configured transmission plan. For high-availability solution deployment, refer to the Service Discovery Cron Job. The Exception Service is a RESTful API. Its purpose is to collect and record service exceptions from other nodes. For high-availability solutions, refer to the Discovery service.

[0080] The algorithm service provides services such as image processing, navigation algorithms, and machine learning. These services often require significant computing resources. This service provides algorithmic support for specific modules and uses a RESTful API. For high-availability solutions, refer to the Discovery service. During surgery, any computational delay can impact surgical outcomes, so the high availability of the algorithm service is crucial to ensuring smooth operations.

[0081] In interventional surgery, high availability not only means continuous service availability in the event of failures but also high-speed responsiveness in data processing and algorithmic computation. To address any unexpected situations, such as equipment failure or network outages, comprehensive high-availability solutions for these services must be implemented to minimize the risk of surgical interruptions. This includes, but is not limited to, redundant deployments, failover mechanisms, and real-time data backup and recovery strategies. Implementing these strategies ensures the stability and reliability of interventional surgical robotic systems during interventional procedures, ultimately guaranteeing patient safety and optimizing surgical outcomes.

[0082] The collaboration between the Remind interface module and the Remind service module is as follows:

[0083] In the context of interventional medicine, the business organization of robot nodes needs to take into account the requirements for high precision and real-time performance during surgery. The following is how the business code of interventional surgery robots is organized:

[0084] a) IBCCM:

[0085] IBCCM allows for textual definition of the robotic system's topology and automatically establishes a communication channel when both communicating nodes are online. Specifically, the communicating nodes register their inter-node collaboration relationship via the hardware node registration interface, and the Remind middleware layer automatically establishes the communication channel based on this registered collaboration relationship. This relies on the Message Distribution Service, and the configurable heartbeat service provided by the Communication Service ensures that each node has real-time information about the communicating party's status, which is crucial for real-time decision-making and coordinated operations during interventional surgery.

[0086] b) Node registration:

[0087] Each node first registers its information with the IBCCM through the Device Registration Interface. Because the IBCCM is the central node, each node can access real-time information about other nodes and the system's topology through this API, which is crucial for maintaining device coordination and information flow during interventional procedures.

[0088] c) Establish a connection:

[0089] Connection establishment is initiated by the Interventional Cloud Network Management (ICNM) based on the topology stored in the IBCCM. Once the connection is established, nodes exchange information through the Message Interface according to business processes. All data is recorded in the IBCCM database using a unified protocol format, ensuring the integrity and traceability of interventional procedures. The On-Premise Storage Service provides data persistence, allowing node business code to supplement persistent data as needed.

[0090] d) High computing power requirements:

[0091] If a node's business requires high computing power, the node code can call Computing Intensive Services through the Advance Function Interface. In interventional surgery, this may involve computationally intensive tasks such as image processing and data analysis.

[0092] When an abnormal situation occurs, there are two types of response measures:

[0093] I. Abnormal reporting:

[0094] If a node's business code detects an anomaly, it is sent to the Communication Service via the Exception Uploading Interface. The Communication Service then notifies all online nodes of the anomaly by updating the node's registration information. This is crucial in interventional procedures because it ensures that any potential problems are quickly identified and widely communicated.

[0095] II. Abnormal findings:

[0096] If a service node fails to report its status to IBCCM in a timely manner, the Service Discovery Cron Job in the Communication Service will detect the anomaly and update the node's registration information so that other nodes can be notified promptly. In interventional surgical robotic systems, this automated fault detection is crucial for maintaining continuous system operation and reducing surgical interventions.

[0097] Once an exception is detected, the Exception Handling Interface becomes the entry point for resolving the issue. Node code must pre-configure the handling logic using the exception handling function registration method within the Exception Handling Interface. Given the diverse handling methods, the registration mechanism provides necessary flexibility. The middleware passes detected exceptions to the pre-set handling function via interface parameters and calls it promptly for appropriate exception handling. This is crucial in interventional surgery, ensuring that any issues are addressed promptly and appropriately, protecting patient safety and maintaining a smooth surgical process.

[0098] As described above, the universal distributed network control system architecture of this embodiment can provide different types of robotic systems with a mechanism for establishing complex communication network topologies, a mechanism for capturing exceptions, and a mechanism for self-recovery of network-layer exceptions. The types of interventional surgical robots that can be adapted include puncture interventional surgical robots, vascular interventional surgical robots, and bronchoscope-based interventional robots.

[0099] The Preoperative Planning Module (IPGM) of a puncture interventional surgical robot is responsible for collecting preoperative 3D medical images of the patient, such as CT and MRI, and generating surgical planning information, such as the planned path during puncture intervention, through algorithmic calculations. The Immersive Navigation Control Module (ICNM) presents multi-dimensional intraoperative sensor information to the physician and uses it to make critical clinical decisions, such as confirming the implant path, making emergency pauses, and identifying the patient's breathing. The first two modules can be considered the brains of the interventional surgical robot. The Intuitive Sensor Module (ITSM) collects and transmits multi-dimensional intraoperative sensor information to intelligent units within it, such as near-infrared optical sensors and magnetic positioning sensors, acting like the robot's eyes. Regarding behavior, the Interventional Behavior Execution Module (ITEM) executes certain clinical actions, such as positioning the distal end of an interventional instrument using a six-degree-of-freedom collaborative robot. Currently, interventional surgical robots in this field are generally built using the collaboration of these three modules. Hardware homogeneity is particularly evident in the field of puncture interventional surgical robots.

[0100] Vascular interventional surgical robots: Within the framework of this type of robot, the preoperative planning module (IPGM), serving as the robot's entry point, collects preoperative 3D medical images from the patient, such as CT and MRI. By calculating the vascular structure, it generates the corresponding surgical plan information, including the interventional pathway, potential errant branches, complex branching areas, and the location of stenosis. After receiving this planning information, the immersive navigation control module (ICNM) presents the physician with real-time intraoperative multi-sensor information, such as X-ray images and the positioning of the guidewire tip within the 3D vascular structure. This module facilitates critical clinical decision-making. The IPGM and ICNM can be characterized as the brain-computer interface between the interventional surgical robot and the interventional physician. Regarding perception, the sensor module (ITSM) collects multi-sensor information from the patient during the procedure and provides timely feedback to the intelligent unit within the robot. This module is divided into two categories: real-time X-ray imaging and force and torque measurement information. These two types of information constitute the eyes and tactile nerves of the vascular interventional surgical robot. In terms of behavior, the interventional-related instrument execution module (ITEM) is used to perform some interventional clinical actions, such as the rotational propulsion and delivery of interventional instruments such as guidewires and catheters, and the quantitative control of contrast agent injection modules.

[0101] Bronchoscope-based interventional robots: Within the framework of this type of robot, the preoperative planning module (IPGM) is responsible for collecting preoperative 3D medical images of the patient, such as CT and MRI, and generating corresponding surgical plan information through algorithmic calculations, such as the interventional path for hilar lesions. The immersive navigation control module (ICNM) presents multi-dimensional intraoperative sensor information to the physician, enabling key clinical decisions, such as scene perception at branch points and identifying complex conditions such as the patient's breathing. The first two modules can be considered the brains of the interventional surgical robot. The sensor module (ITSM) is responsible for timely collecting and transmitting multi-dimensional intraoperative sensor information to intelligent units within the robot, such as near-infrared optical sensor modules and magnetic positioning sensor modules, acting like the robot's eyes. Regarding behavior, the interventional instrument behavior module (ITEM) is responsible for executing some clinical actions, such as rotational propulsion delivery using a linear guidewire and positioning the end of the interventional instrument using a six-degree-of-freedom collaborative robot.

[0102] It should be noted that, in this document, relational terms such as first and second, etc., are used only to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply the existence of any such actual relationship or order between these entities or operations. Moreover, the terms "comprises," "comprising," or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article, or device comprising a series of elements includes not only those elements, but also other elements not explicitly listed, or elements inherent to such process, method, article, or device. In the absence of further limitations, an element defined by the phrase "comprising a ..." does not exclude the presence of other identical elements in the process, method, article, or device comprising the element.

[0103] The above is only a specific implementation method of the present application. It should be pointed out that for ordinary technicians in this technical field, several improvements and modifications can be made without departing from the principles of the present application. These improvements and modifications should also be regarded as the scope of protection of the present application.

Claims

1. [Corrected 17.12.2024 according to Rule 91] A general distributed network control system architecture for interventional medical surgical robots, characterized in that: It includes an interventional surgery robot application software layer, an operating system layer, and a Remind middleware layer for connecting the two. The Remind middleware layer includes a Remind interface module and a Remind service module, wherein: The Remind interface module has multiple interfaces that match the interventional surgery robot application software layer, including a hardware node registration interface and an abnormality upload interface; The Remind service module has multiple services required to support the operation of the operating system layer, including message distribution service and communication service; The two nodes to be communicated in the interventional surgery robot application software layer register an inter-node cooperation relationship through the hardware node registration interface, and the Remind middleware layer automatically establishes a communication channel through the registered cooperation relationship; If the node business code of the interventional surgical robot application software layer detects an exception, the detected exception information is uploaded to the communication service through the exception upload interface, and the communication service sends the exception to each hardware node of the surgical robot through the message distribution service. After receiving the exception, the middleware on the hardware node promptly calls the exception handling function registered by the hardware node registration interface.

2. [Corrected 17.12.2024 according to Rule 91] The universal distributed network control system architecture for interventional medical surgical robots according to claim 1, characterized in that: The Remind interface module also includes an exception handling interface, which is configured with a method for registering a processing function for predefined exceptions; The node business code of the interventional surgery robot application software layer uses the processing function registration method of the exception handling interface to set the logic for handling exceptions to handle detected exceptions.

3. [Corrected 17.12.2024 according to Rule 91] The universal distributed network control system architecture for interventional medical surgical robots according to claim 1, characterized in that: The Remind interface module also includes a message communication interface, through which multiple nodes of the interventional surgery robot application software layer exchange information according to business processes.

4. [Corrected 17.12.2024 according to Rule 91] The universal distributed network control system architecture for interventional medical surgical robots according to claim 1, characterized in that: The Remind interface module also includes an algorithm calling interface, and the services provided by the Remind service module also include algorithm services; In response to the computing power demand of the node business of the interventional surgery robot application software layer, the interventional surgery robot application software layer calls the algorithm service through the algorithm calling interface.

5. [Corrected 17.12.2024 according to Rule 91] The universal distributed network control system architecture for interventional medical surgical robots according to claim 1, characterized in that: The services provided by the Remind service module also include local storage services; The node business code of the interventional surgery robot application software layer is supplemented with data that needs to be solidified through the local storage service.

6. [Corrected 17.12.2024 according to Rule 91] The universal distributed network control system architecture for interventional medical surgical robots according to claim 5, characterized in that: The local storage service supports storage of multiple data types, including medical imaging data files, structured data, medical diagnosis text data files, and information interaction data of the entire surgical process.

7. [Corrected 17.12.2024 according to Rule 91] The universal distributed network control system architecture for interventional medical surgical robots according to claim 5, characterized in that: The local storage service provides a high availability solution for local database functions including a master-slave replication mode, a master-slave mode and / or a cluster mode.

8. [Corrected 17.12.2024 according to Rule 91] The universal distributed network control system architecture for interventional medical surgical robots according to claim 1, characterized in that: The communication service is integrated with a node status synchronization service program. The service type of the node status synchronization service program is a scheduled task. Its purpose is to scan the node information in the current registration table and kick inactive nodes out of the registration information. If the node status synchronization service program scans and finds that the business node fails to report the status to the interventional brain central processing module of the interventional surgical robot system in a timely manner, the node registration information is updated according to the abnormal information found so that other nodes can perceive the abnormal information found.

9. [Corrected 17.12.2024 according to Rule 91] The universal distributed network control system architecture for interventional medical surgical robots according to claim 1, characterized in that: The communication service is integrated with a communication quality adjustment service program, whose service type is a timed task. Its purpose is to monitor the communication transmission quality between the current surgical nodes. If the transmission rate of one or more nodes is monitored to exceed the preset rate range, the communication quality adjustment service program will make downgrade or upgrade adjustments according to the pre-configured transmission plan.

10. [Corrected 17.12.2024 according to Rule 91] The universal distributed network control system architecture for interventional medical surgical robots according to claim 1, characterized in that: The communication service is integrated with an exception service program. The exception upload interface uploads the detected exception information to the exception service program of the communication service. The service type of the exception service program is Restful API, which is configured to collect and record service exceptions of nodes.

11. [Corrected 17.12.2024 according to Rule 91] The universal distributed network control system architecture for interventional medical surgical robots according to claim 10, characterized in that: The communication service is also integrated with a discovery service program, which is configured to provide services based on the Restful API. Other nodes need to configure the connection information of the discovery service program and periodically register the node's own status to the discovery service program.

12. [Corrected 17.12.2024 according to Rule 91] The universal distributed network control system architecture for interventional medical surgical robots according to claim 1, characterized in that: The message distribution service provides message queue middleware support, and its high availability solutions include active-standby mode and / or cluster mode.

13. [Corrected 17.12.2024 according to Rule 91] A general distributed network control system architecture for an interventional medical surgical robot according to any one of claims 1 to 12, characterized in that: It also includes a hardware device layer, wherein the hardware device layer and the operating system layer respectively correspond to the computer hardware devices required for the operation of the interventional surgical robot and the computer operating system for scheduling and using these hardware devices and the driver software contained therein.

14. [Corrected 17.12.2024 according to Rule 91] The universal distributed network control system architecture for interventional medical surgical robots according to claim 13, characterized in that: It also includes a cloud computing center layer, which includes infrastructure as a service, platform as a service and software as a service.

15. [Corrected 17.12.2024 according to Rule 91] A general distributed network control system architecture for an interventional medical surgical robot according to any one of claims 1 to 12 or claim 14, characterized in that: The surgical robot system includes an interventional brain central processing module, a preoperative plan information generation module, an immersive navigation and control module, an interventional instrument perception module, and an interventional behavior execution module. The interventional physician cloud computing module interacts with the preoperative plan information generation module to complete the generation of the interventional plan information set. Receiving planning information from the preoperative planning information generation module, and initiating or terminating the surgical action through the immersive navigation and control module; The interventional device perception module collects the perception of the intraoperative behavioral process and its results, and sends the perception information to the immersive navigation and control module for immersive experience display of the perception information; After the intervention brain central processing module calculates the control instructions for the perception information, the intervention behavior execution module cooperates with the operator to complete the action response and perception feedback.

16. [Corrected as of 17.12.2024 in accordance with Rule 91] The universal distributed network control system architecture for interventional medical surgical robots according to any one of claims 1 to 12 or claim 14, wherein the types of interventional surgical robots that can be docked include puncture interventional surgical robots, vascular interventional surgical robots, and bronchoscope-based interventional robots.

17. [Corrected 17.12.2024 according to Rule 91] An interventional surgical robot, characterized in that A universal distributed network control system architecture as claimed in any one of claims 1 to 16 is adopted.

18. [Corrected 17.12.2024 according to Rule 91] The interventional surgical robot according to claim 17, characterized in that It includes an interventional brain central processing module, a preoperative plan information generation module, an immersive navigation and control module, an interventional instrument perception module, and an interventional behavior execution module. The interventional physician cloud computing module interacts with the preoperative plan information generation module to complete the generation of the interventional plan information set. Receiving planning information from the preoperative planning information generation module, and initiating or terminating the surgical action through the immersive navigation and control module; The interventional device perception module collects the perception of the intraoperative behavioral process and its results, and sends the perception information to the immersive navigation and control module for immersive experience display of the perception information; After the intervention brain central processing module calculates the control instructions for the perception information, the intervention behavior execution module cooperates with the operator to complete the action response and perception feedback.

19. [Corrected 17.12.2024 according to Rule 91] The interventional surgical robot according to claim 17 or 18, characterized in that The types of interventional surgical robots include puncture interventional surgical robots, vascular interventional surgical robots, and bronchoscope-based interventional robots.

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