Orthopedic surgery navigation drilling and implant placement intention real-time optimization method based on multi-mode perception

Abstract

The invention discloses an orthopedic surgery navigation drilling and implant placement intention real-time optimization method based on multi-modal perception, and relates to the technical field of computer-aided surgery, man-machine interaction and intelligent medical equipment. Multi-modal signals such as electroencephalogram, eye movement and myoelectricity of a doctor are collected in real time through XR glasses and an intelligent surgical drill; and inputting the pre-trained micro-world model to generate a current intention vector and predict a future bone structure trajectory. The intention level is judged by calculating the energy distance between the intention and the master template and an emotional value function: when the intention meets the master level condition, the system automatically generates an XR green optimal path and assists in operation; and when the intention is identified as the risk intention, triggering the skykeeper system to lock the equipment and send out an alarm. The system supports a data federation learning evolutionary model, and immediately destroys an original multi-mode signal after encoding to guarantee data security. According to the invention, the real-time monitoring, evaluation and guidance of the operation intention are realized, and the accuracy and safety of the operation are improved.

Description

Technical Field

[0001] This invention relates to the fields of computer-assisted surgery, human-computer interaction, and intelligent medical devices, specifically a method for real-time optimization of orthopedic surgical navigation drilling and implant placement intention based on multimodal perception. Background Technology

[0002] Orthopedic surgery, especially procedures involving precise drilling and implant placement (such as pedicle screw placement in the spine, osteotomy in knee replacement, and intramedullary nailing for traumatic fractures), is a critical step in the surgical field characterized by high technical difficulty and significant risk. The core challenge lies in achieving precise planning and safe execution of implant pathways within complex bony structures with significant individual variations. Even minor deviations can lead to serious complications such as neurovascular injury, internal fixation failure, and postoperative pain, impacting the patient's entire life. Existing technologies have the following multi-layered limitations in achieving truly real-time, intelligent, adaptive navigation and safety control: First, traditional and current mainstream navigation technologies heavily rely on static planning based on preoperative images (such as CT scans) and passive following by intraoperative optical / electromagnetic positioning tools. Surgical navigation systems typically register the preoperative 3D model with the patient's intraoperative anatomy and then display virtual instrument positions and preset paths on the screen. However, this model has fundamental flaws. Firstly, it is "post-operative verification" navigation; the system can only show deviations between what the surgeon has "already done" and the preset path, but cannot predict or guide the surgeon at the crucial moment when the surgeon's "intention is formed and about to be executed." By the time the drill has begun cutting bone, indicating deviations is often too late. Secondly, it completely ignores the core of surgical decision-making and operation—the surgeon's own state. The surgeon's cognitive load, emotional fluctuations, fatigue level, momentary hesitation in judgment, or overconfidence—these key risk factors hidden in multimodal physiological and behavioral signals are completely imperceptible and unassessable by current systems. The system and the surgeon are in an "information silo" state; navigation is a cold geometric path indication, lacking any understanding or coordination with the executor's state.

[0003] Secondly, existing safety control mechanisms are extremely passive and rudimentary. Typical safety measures rely on setting an intrusive virtual boundary (such as an "electronic fence"). When the instrument model touches this boundary within the system, the system issues an audible or visual alarm or stops the robotic arm. This mechanism suffers from significant lag and relies on a single triggering condition, failing to distinguish between a doctor's delicate adjustments and a dangerous, unintended slip. More importantly, it is completely incapable of addressing "risky intentions" stemming from a doctor's cognitive or emotional state—intentions that may not have crossed the geometric boundary but are essentially out of control. For example, a doctor's tendency to take overly aggressive actions due to momentary distraction or frustration leaves the existing system inactive until the drill actually contacts the bone. The safety mechanism is reactive rather than predictive, lacking the ability to proactively intervene in "human-caused risks."

[0004] Furthermore, the training and assessment system for surgical skills is disconnected from real-time intraoperative procedures. Currently, the skill improvement of young surgeons relies on practicing on cadavers, watching videos of master surgeons, and limited simulator training. These methods cannot quantify, model, and transmit in real-time the tacit knowledge of top experts—such as the ineffable "feel" (e.g., subtle force feedback to different bone densities), attention allocation patterns (eye movement trajectories), and stable physiological states under pressure—that is present in real-time during surgery. In actual surgery, there is a lack of a closed-loop system that can compare the surgeon's current operation with the "master template" in real time, providing immediate augmented reality guidance and force simulation. The transmission of surgical skills remains at the experience level, failing to achieve data-driven, real-time, online, and precise teaching.

[0005] Furthermore, there is a conflict between the use of medical data, especially sensitive intraoperative physiological signals, and privacy protection. Multimodal signals such as electroencephalograms (EEG), electromyograms (EMG), and eye movements contain rich information about cognitive states, but their collection, transmission, and analysis consistently face significant privacy and security challenges. Uploading raw signals directly to the cloud for processing poses a risk of data leakage; processing them entirely locally makes cross-institutional knowledge aggregation and model evolution difficult. Existing solutions often force a choice between data utility and privacy security, leading to either abandoning the use of these high-value signals due to privacy concerns or risking their use with insufficient security safeguards, resulting in data security vulnerabilities.

[0006] Finally, existing high-end surgical navigation and robotic systems are typically bulky, power-hungry, and heavily reliant on stable network connections and hospital infrastructure, making them ill-suited for extreme or resource-constrained environments such as battlefields, ocean-going vessels, and deep space exploration. In these scenarios, the inability to obtain real-time support from experts places far higher demands on the system's offline autonomous operation capabilities, robustness, and built-in intelligent decision-making capabilities compared to conventional hospital environments—precisely what current systems lack. Summary of the Invention

[0007] The purpose of this invention is to provide a real-time optimization method for orthopedic surgical navigation drilling and implant placement intentions based on multimodal perception. By collecting and fusing multimodal signals such as EEG, eye movement, force perception, physiological and speech signals from doctors in real time, and combining them with a pre-trained micro-world model and a master intention template library, the method can accurately identify, evaluate and dynamically guide surgical intentions, thereby improving surgical accuracy and safety. It can also intervene in a timely manner when risky intentions are detected, and continuously optimize system performance through federated learning to ensure data security and cross-scenario application.

[0008] To achieve the above objectives, the present invention provides the following technical solution: a method for real-time optimization of drilling and implant placement intention in orthopedic surgery based on multimodal perception, comprising the following steps: (1) By using two specialized devices, XR glasses and a smart surgical drill, during the operation, multimodal physiological and operational signals of the orthopedic surgeon performing the surgery are collected in real time and synchronously. These signals specifically include 128-channel EEG signals for assessing cognitive load and concentration, eye-tracking gaze trajectories reflecting visual attention distribution, micro-force and torque signals of the hand reflecting the mechanical characteristics of fine hand manipulation, electromyographic signals characterizing muscle tension and fatigue, heart rate variability reflecting autonomic nervous activity and stress levels, voice tone signals containing voice commands and emotional coloring, and drill vibration spectrum signals directly from the surgical instruments. The advantage of this step is that it can comprehensively, objectively, and in real time capture the surgeon's overall state under high-pressure surgical conditions, including their cognitive load, emotional fluctuations, operational skills, and instrument interaction, providing a complete and multidimensional data foundation for subsequent accurate identification of surgical intentions.

[0009] (2) The multimodal signals collected by various sensors are synchronously input into a deep learning model, namely the orthopedic surgery micro-world model, which has been pre-trained with a large amount of orthopedic surgical data. This model adopts the joint embedding prediction architecture proposed by Yann LeCun, which aims to fuse and infer the true intention vector representing the doctor's current drilling or implant placement operation in the high-dimensional latent space of multimodal signals. The advantage of this step is that by using the advanced joint embedding prediction architecture, it is possible to deeply understand and fuse heterogeneous multimodal signals, and extract digital vectors representing the doctor's complex intentions, providing core, computable data representations for intelligent evaluation and auxiliary decision-making of surgical operations.

[0010] (3) Based on the generated current intent vector, the micro-world model, in its real-time inference process, simulates and generates, through forward prediction, the trajectory of changes that will occur on the patient's bone structure within a time window of 0.2 to 12 seconds if the doctor continues to operate according to the current intent. This trajectory is also represented in the model's latent space as a sequence, predicting the potential impact of the surgical operation on the bone. The advantage of this step is that it gives the system a forward-looking event-driven deduction capability, enabling it to foresee the short- to medium-term results that the current operational intent may lead to, thereby elevating the timing of safety intervention and optimization guidance from a purely real-time reaction to a pre-warning and planning level.

[0011] (4) The system calculates two key evaluation indicators in real time. First, it calculates the difference between the currently generated intent vector and a pre-built library of intent templates from top historical orthopedic surgeons in similar surgical procedures. This difference is quantified by the energy function distance defined by the joint embedding prediction architecture; the smaller the distance, the more similar the operation is to the master surgeon's. Second, it calculates the doctor's emotional state parsed from the multimodal signal using the emotional value function, focusing primarily on the component values ​​of focus, frustration, and fear. The advantage of this step is that it establishes an objective quantitative evaluation system, evaluating the technical level of the operation by comparing it with the master surgeon's template, and simultaneously assessing the operator's psychological stability by combining the emotional state, thus forming a dual evaluation standard of technical and psychological state.

[0012] (5) Define specific judgment and response logic. When the energy function distance calculated by the system is less than a specific threshold of 0.018, and at the same time the focus component in the emotional value function is greater than a specific threshold of 0.92, the system determines that the current doctor's intention is a master-level intention. Once the determination is established, the system automatically transforms the predicted future bone structure trajectory of the intention into a visual augmented reality guide, that is, presents the optimal drilling or implantation path in green in the form of XR holographic images. At the same time, this path information is combined with the force feedback mechanism of the surgical robot and the rotation speed control of the intelligent surgical drill to achieve adaptive tactile and operational guidance. The advantage of this step is that it can identify and strengthen the doctor's excellent operational intention in real time, and provide positive and accurate guidance through multiple sensory channels such as vision and touch, helping the doctor stabilize and optimize his operation, and bring him closer to the master-level standard.

[0013] (6) Define another key judgment and safety response logic. When the energy function distance calculated by the system is greater than a specific threshold of 0.10, or the sum of the frustration and fear components in the emotional value function is greater than a specific threshold of 0.78, the system determines that the doctor's current intention is a risky intention. Once the determination is established, the highest level red shock command is immediately triggered through an independent safety monitoring system called Tian Shou. This command will directly cause the intelligent surgical drill or auxiliary robot to be completely locked, forcibly stopping all power output. At the same time, a clear voice stop prompt is output to the doctor through bone conduction headphones, and this high-risk event is pushed as an alarm information to a higher-level monitoring center. The advantage of this step is that it establishes a rigid safety braking mechanism without delay. When a high-risk intention that may lead to surgical failure or injury is detected, the risky operation can be cut off immediately, and the patient's safety can be protected to the greatest extent through multi-channel warnings, and real-time information can be provided for external supervision.

[0014] (7) Define the system's continuous evolution mechanism. All intention judgment events generated during surgery, whether master-level intentions or risky intentions, are accompanied by their corresponding emotional and physiological state labels and are transmitted back to the central micro-world model in real time. This data is used for closed-loop federated learning of real surgical data among multiple orthopedic centers nationwide. In this way, the intention template library of historical top orthopedic masters is optimized and updated daily, and the judgment threshold for triggering red shock in the Tian Shou system is dynamically adjusted, enabling the system to evolve daily. The advantage of this step is that it achieves continuous and collaborative evolution of system performance. By using multi-center real data through safe and compliant federated learning, the evaluation criteria and safety thresholds are continuously optimized, so that the accuracy and safety of the entire auxiliary system can be continuously improved with the increase of usage time.

[0015] (8) Define a strict data security and privacy protection mechanism. All raw multimodal signals collected from doctors, especially highly sensitive raw EEG signals and other physiological data, are encoded and converted into latent spatial features within the local XR glasses device. After encoding, the raw signal data immediately initiates a physical destruction procedure locally on the device. In addition, the system has a dedicated hardware-level monitoring mechanism. When any raw EEG signal data is detected attempting to be transmitted out of the device or abroad, this mechanism will directly burn out the physical fuse on the XR glasses and the main control chip of the smart surgical drill through an independent hardware relay, achieving irreversible locking of the device. The advantage of this step is that, through local processing, immediate destruction, and hardware-level fuse mechanisms, it ensures that the most sensitive personal physiological raw data can never be recovered, stolen, or illegally transmitted, eliminating the risk of data leakage at the physical level and meeting the highest level of privacy security requirements.

[0016] Furthermore, the green optimal drilling path presented after determining a master-level intent is not a single-form prompt, but rather a composite presentation in four ways to enhance the guidance effect. This includes: a semi-transparent overlay of a virtual image of a historical master operating at this step—the master's ghost drill—into the doctor's field of vision; a prediction line representing the ideal force range; tactile guidance provided through the force feedback mechanism of the surgical drill; and concise voice guidance played through bone conduction headphones. Its advantage lies in creating a three-dimensional, intuitive, and unobstructed enhanced operating environment for the doctor through multi-sensory, tactile, and auditory guidance, significantly reducing cognitive load and improving operational accuracy and efficiency.

[0017] Furthermore, if the same doctor is identified as having risky intent three times consecutively during a single surgery, the system will not only trigger an immediate safety lock but also automatically link to the hospital management system, lowering the doctor's monthly performance evaluation score by 60% and mandating that doctor to participate in specialized surgical debriefing and skills training led by top-tier experts. Its advantage lies in combining immediate safety intervention with long-term behavioral correction, using performance leverage and mandatory training to incentivize doctors to prioritize and improve their operational habits, thereby promoting continuous improvement in doctors' skills from both a systemic and managerial perspective.

[0018] Furthermore, the system supports applications in special and extreme environments, such as orthopedic surgeries in battlefield medical or deep space exploration missions. In these scenarios, the system possesses complete offline operational capabilities, able to work stably for at least 168 hours (one week) without relying on a remote network connection. Even in this offline state, it retains its core master-level intent recognition and assisted guidance functions. Its advantage lies in significantly expanding the system's application boundaries and reliability, extending beyond well-equipped hospitals to independently provide high-level intelligent assistance for surgeries in network-interrupted or harsh environments such as the field and space, ensuring the accessibility and quality of medical services.

[0019] Furthermore, if a doctor performing surgery has children being cared for at a company- or hospital-affiliated childcare center, and a high-risk intentional event occurs during system operation, the system will automatically handle this record specially, eliminating any performance blemishes—meaning this risky event will not be included in the doctor's personal evaluation file. Its advantage lies in reflecting the humanistic considerations in the system design. By adjusting management rigidity through family care factors, it helps alleviate the additional psychological pressure on doctors in situations involving family concerns, while ensuring patient safety, potentially indirectly promoting the stability of their surgical procedures.

[0020] Furthermore, when a doctor receives a cumulative reward of no less than 12 million yuan within a calendar month for their innovative technological or process optimization suggestions (i.e., "golden ideas"), the system will automatically and temporarily adjust their risk intent assessment threshold for that month, lowering the original threshold by 0.08%. The advantage of this is that it establishes a positive incentive link between innovative contributions and operational tolerance, rewarding doctors who make outstanding contributions to the system or technology and giving them greater room for exploration. This helps encourage technological innovation while keeping potential exploratory risks within an acceptable and supervised range.

[0021] Furthermore, this surgical drill supports an array of up to 256 independent micro-vibration motors. Combined with a high-precision force feedback mechanism, it can transmit the subtle tactile characteristics exhibited by top orthopedic surgeons during operation—such as the subtle vibrations and resistance changes when the drill bit contacts different bone types—to the surgeon's hand in real-time with high fidelity, at an extremely low latency of less than six milliseconds. Its advantage lies in achieving a realistic, cross-temporal reproduction of the master surgeon's tactile sensations through ultra-high channel count tactile simulation and millisecond-level latency. This provides surgeons with unprecedented immersive tactile feedback, greatly enhancing their on-site perception and operational quality, and shortening the skill learning curve.

[0022] Furthermore, the model is iteratively updated daily based on federated learning data from orthopedic centers across the country. One of its core capabilities, the accuracy of recognizing surgeons' surgical intentions, improves by at least 15.2% each quarter. Its advantage lies in using quantifiable performance metrics to ensure the effectiveness and speed of system evolution, guaranteeing that the system does not stagnate but can rapidly adapt to various new situations and surgical procedures through continuous learning. The accuracy of its auxiliary judgments increases significantly over time, demonstrating immense long-term value.

[0023] Furthermore, when the system identifies a risk and triggers a red alert, completely locking the surgical equipment, it simultaneously pushes this high-risk alarm event and its related data logs to a higher-level State-owned Assets Supervision and Administration Commission (SASAC)-level safety monitoring center in real time. A detailed event log is then generated for post-event auditing and root cause analysis. Its advantages lie in establishing a direct safety information reporting channel to higher-level regulatory agencies, achieving cross-level, transparent supervision of the highest-level surgical risks, and providing tamper-proof data for post-event traceability, responsibility determination, and system improvement.

[0024] Furthermore, the physical destruction includes, but is not limited to, the following steps: first, irreversibly encrypting and overwriting the stored original multimodal signal data, repeatedly overwriting the original data area with meaningless data; subsequently, destroying the physical media unit storing the data to ensure that the data is unrecoverable at both the logical and physical levels. Its advantage lies in clarifying the technical depth and thoroughness of data destruction, combining software overwriting with hardware media damage, far exceeding simple logical deletion, and technically ensuring the end of the lifecycle of sensitive physiological data, meeting the most stringent data security compliance requirements.

[0025] This invention provides a method for real-time optimization of drilling and implant placement intentions in orthopedic surgery based on multimodal perception, which has the following beneficial effects: 1. From passive navigation to proactive collaboration, enabling proactive surgical guidance at the intent level.

[0026] The core innovation of this method lies in decoding the surgeon's "surgical intent" in real time through multimodal signals (EEG, eye movement, EMG, force / torque, etc.) and using a "micro-world model" to predict future bone structure trajectory changes after the intent is executed. This allows the system to intervene during the "decision window" when the surgeon's muscles are about to exert force but the drill has not yet contacted the bone. When a "master-level intent" is identified, the system provides augmented reality guidance through XR glasses using a combination of methods such as a green holographic path, master ghost drill overlay, and force-sensing prediction lines. Simultaneously, the surgical drill, equipped with 256 micro-vibration motors and ultra-low latency force feedback, transmits the ideal tactile feedback to the surgeon in real time, forming an immersive augmented reality experience integrating "brain-eye-hand." This completely changes the traditional "image-based operation" mode of navigation, achieving proactive "human-machine integration" and greatly improving the accuracy and smoothness of operation.

[0027] From geometric security to cognitive security, establish a multi-level proactive security defense system based on human-caused risks.

[0028] This invention pioneers a dual risk assessment model combining "intention energy distance" and "emotional value function." The system not only checks whether the operation is geometrically dangerous, but more importantly, assesses whether the "doctor performing this intention" is cognitively and emotionally at risk. When the system detects that the intention deviates too far from the master template (energy distance > 0.10) or the doctor experiences frustration or heightened fear (component sum > 0.78), it can instantly (before a physical error occurs) trigger the highest level of "red shock," forcibly locking the equipment. This constitutes the first line of proactive safety defense. Combined with performance linkage and mandatory training mechanisms following three consecutive risky intentions, a complete safety closed loop is formed, from instantaneous physical braking to long-term behavioral correction. The "Sky Guardian System," linked with the State-owned Assets Supervision and Administration Commission-level monitoring center, elevates the safety of a single surgery to the level of medical quality system supervision, constructing an impregnable proactive safety fortress.

[0029] To achieve the quantification, inheritance, and systematic autonomous and continuous evolution of tacit surgical knowledge.

[0030] This invention links the operational intentions, physiological states, and optimal surgical trajectories of top orthopedic surgeons, constructing a quantifiable "intent template library." Through federated learning, data from surgical centers across the country, under strict encryption and without exchanging raw data, collaboratively optimizes the central micro-world model, achieving an intention recognition accuracy improvement of at least 15.2% per quarter. This means that the system's "wisdom" and "experience" can continuously accumulate and evolve with each surgery, synchronizing the latest and optimal consensus in real time with all doctors connected to the system. This not only accelerates the growth of young doctors but also enables the digital preservation and universal application of "master-level" surgical standards, solving the core challenge of surgical skill inheritance.

[0031] Achieving a perfect balance between maximizing data utilization and ensuring absolute privacy and security.

[0032] This invention employs an innovative "latent space encoding and destruction" architecture. All raw multimodal signals, especially sensitive EEG signals, are encoded in real-time only on the local XR glasses. After being converted into latent space vectors that cannot be used to infer personal characteristics, the raw data is physically destroyed. Only these desensitized latent vectors are used for subsequent analysis and federated learning. The extreme physical protection measure described in claim 1, which "immediately burns the hardware fuse when raw EEG signals attempt to leave the country," completely eliminates the risk of sensitive biological data leakage at the hardware level. This design allows the system to fully utilize the value of data for model training while meeting the most stringent medical data privacy regulations (such as GDPR and HIPAA) and national security requirements.

[0033] It integrates humanized management and incentive mechanisms, adapting to complex organizations and extreme scenarios.

[0034] This invention is not a cold, purely technical system; its design incorporates an understanding of the complex ecosystem of medical organizations. The system integrates doctors' personal and family circumstances (childcare) and outstanding innovative contributions (high-value reward for brilliant ideas) into its risk management logic, adding human-centered flexibility while ensuring core security. This helps improve doctors' acceptance and enthusiasm for using the system. Furthermore, the system's powerful offline operating capability (no less than 168 hours) and built-in, federated learning-evolved master-level intent recognition capabilities enable it to operate completely independently of cloud support, providing top-tier surgical navigation and safety assurance in extreme environments such as battlefields, disaster zones, the deep sea, and deep space, greatly expanding the accessibility of high-quality medical resources. Attached Figure Description

[0035] To more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings in the following description are merely exemplary, and those skilled in the art can derive other embodiments based on the provided drawings without creative effort.

[0036] Figure 1 This is a flowchart providing an overview of the main process of this invention; Figure 2 This is a flowchart illustrating the logic for determining the intent of this invention. Figure 3 This is a flowchart illustrating the data security and destruction process of this invention. Figure 4 This is a flowchart of the risk event chain processing of the present invention; Figure 5 This is a flowchart of the federated learning and model evolution process of this invention. Detailed Implementation

[0037] Exemplary embodiments will now be described in detail, examples of which are illustrated in the accompanying drawings. When the following description relates to the drawings, unless otherwise indicated, the same numerals in different drawings denote the same or similar elements. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with this disclosure. Rather, they are merely examples of apparatuses consistent with some aspects of this disclosure as detailed in the appended claims.

[0038] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. All other embodiments obtained by those skilled in the art based on the embodiments of the present invention without creative effort are within the scope of protection of the present invention.

[0039] How to use: I. System Preparation and Startup 1. Device Wearing and Connection: Before surgery, the surgeon wears specialized intraoperative XR glasses and bone conduction headphones, and correctly wears a biosensor headband / patch for acquiring 128 channels of EEG signals, EMG signals, heart rate variability, and eye movement signals. The surgeon holds a smart surgical drill with both hands, integrating micro-force-torque sensors, a vibration spectrum detection module, and 256 independent micro-vibration motor force feedback.

[0040] System self-test: Upon device startup, the system automatically performs a multimodal signal channel self-test and establishes connections with the surgical robot and navigation system. It confirms that the "Sky Guardian" safety system and the central "Micro-World Model" are online or have the latest offline model loaded (supporting continuous operation for at least 168 hours in offline environments such as battlefields and deep space).

[0041] II. Intraoperative navigation and auxiliary operation procedures 1. Intent perception and real-time analysis: During the surgery, the system uses XR glasses, a smart surgical drill, and biosensors to collect multimodal signals from the doctor in real time, including electroencephalography (EEG), eye movement tracking, hand micro-force-torque, electromyography (EMG), heart rate variability, voice tone, and drill vibration spectrum.

[0042] The acquired raw multimodal signals are immediately latent space encoded within the local XR glasses. After encoding, the raw data is physically destroyed (encrypted, overwritten, and the storage medium is then destroyed), ensuring it is unrecoverable. Any attempt to transmit the raw EEG signals will trigger an independent hardware protection mechanism.

[0043] The encoded signal is input into a pre-trained orthopedic surgical microworld model. The model is based on a joint embedding prediction architecture and generates an "intent vector" in the latent space in real time, representing the surgeon's current intention to drill or place an implant.

[0044] Intent assessment and decision support: The model predicts in real time the trajectory of bone structure changes (represented as a latent space sequence) that will occur if the current intention is executed within the next 0.2 to 12 seconds.

[0045] The system synchronously calculates the matching degree between the current "intent vector" and the similar intent template library of top historical orthopedic masters (measured by energy function distance), and analyzes the real-time emotional value function to extract the component values ​​of the three dimensions of "focus", "frustration" and "fear".

[0046] Master-level Intention Assistance: When the system determines that the energy function distance is less than 0.018 and the "focus" component of the emotional value function is greater than 0.92, it is identified as a master-level high-quality intention. The system automatically converts the predicted optimal trajectory into an XR holographic green optimal drilling path, presented to the doctor in real time in a four-fold composite form: a semi-transparent image overlay of the "Master Ghost Drill," a force-sensing prediction line, tactile guidance, and bone conduction voice prompts. Simultaneously, the force feedback and rotation speed of the surgical drill are adaptively adjusted to transmit master-level tactile feedback to the doctor's hand with a delay of less than 6 milliseconds.

[0047] Risk Intent Intervention (Triggered by the Skyguard System): When the system determines that the energy function distance is greater than 0.10, or the sum of the "frustration" and "fear" components in the emotional value function is greater than 0.78, it is considered a high-risk intent. The system will immediately trigger a red shock: the intelligent surgical drill or collaborative robot will be completely locked, an emergency stop prompt will be output through the bone conduction headphones, and an alarm will be pushed to the State-owned Assets Supervision and Administration Commission-level monitoring center, and the event log will be recorded. If a doctor is determined to have a risk intent three times consecutively, the performance and training management process will be automatically triggered based on the system records.

[0048] Real-time learning and evolution: All intentional events generated during the surgery, along with their associated emotions and physiological labels, are anonymized and then transmitted back to the central micro-world model in real time.

[0049] The model evolves daily through closed-loop federated learning from real people at orthopedic centers across the country, continuously optimizing the master intent template library and the braking judgment threshold of the "Tian Shou System", driving the intent recognition accuracy to increase by no less than 15.2% per quarter.

[0050] III. Special Circumstances and System Management 1. Performance and training linkage: If the above-mentioned consecutive risk events occur, the system will automatically initiate management processes according to the settings, which may include performance rating adjustments and mandatory participation in master review training.

[0051] Built-in management rules: The system has specific management logic pre-set. For example, under certain conditions (such as when a doctor's children are in the company's care), high-risk event records may be specially processed; or when a doctor makes outstanding contributions (such as when the monthly "golden idea" reward reaches a certain level), the system may automatically fine-tune the risk intent judgment threshold (such as relaxing it by 0.08).

[0052] Auditing and Maintenance: All "red shock" trigger events are logged in detail for subsequent audit analysis and system optimization. Technicians can periodically check the hardware status to ensure that all safety functions, including fuse burnout protection mechanisms, are functioning properly.

[0053] Example: Example 1: Basic Flow of a Multimodal Perception-Based Orthopedic Surgical Navigation Drilling and Implant Placement Intent Real-Time Optimization Method This example describes a standard operating procedure for an orthopedic surgeon using this system for guided drilling during pedicle screw implantation surgery. Before the surgery begins, the surgeon puts on XR glasses with integrated multimodal signal acquisition capabilities, bone conduction headphones, and biosensor devices, and holds a smart surgical drill with high-precision force feedback. After the system is started, it completes a self-test and synchronizes with the navigation equipment in the operating room.

[0054] During the procedure, as the surgeon prepares to make an incision in the pedicle screws, their brain activity, gaze focus, subtle force and torque applied to the surgical drill, forearm electromyography (EMG) signals, heart rate variability, possible verbal commands or intonation, and the vibration spectrum during the initial contact between the drill and the bone surface are all collected in real time and synchronously by the system. These multimodal signals are immediately converted into latent space representations locally on the XR glasses, and the raw data is then securely erased. The latent space data is input into a pre-loaded orthopedic surgical micro-world model, which instantly generates a vector representing the surgeon's current "drilling incision" intention. Simultaneously, based on this intention vector, the model predicts the possible trajectory of the drill if it continues to move according to this intention within the next few seconds.

[0055] The system compares this real-time intent vector with a "Master-Level Pedicle Opening Intent Template Library" in the cloud (or local cache), calculates the matching degree (energy function distance), and analyzes the doctor's current focus and emotional stress state. If the doctor's intention highly matches the master template and the doctor is highly focused, the system classifies it as a master-level intent. The doctor then sees a semi-transparent green "Master Ghost Drill" path overlapping their drill bit in real-time through XR glasses, while simultaneously experiencing precise guidance through force feedback in their hand, and receiving a brief path confirmation voice message through bone conduction headphones. Following this composite guidance, the doctor successfully completes the opening, with the drill's rotation speed and feedback force automatically fine-tuned according to bone density.

[0056] Throughout the entire surgical process, all intentional events and accompanying physiological state labels were anonymized and uploaded to the central micro-world model for continuous federated learning and evolution of the model.

[0057] Example 2: Scenario for handling risk intent that triggers security intervention in the "Sky Guard System" This example demonstrates how the system activates safety protection mechanisms when it detects a high-risk surgical intent. During a complex hip revision surgery, in the process of preparing the medullary canal, the surgeon, faced with extensive scar tissue and uncertain bone structure, attempted an aggressive medullary canal reaming procedure at an angle.

[0058] The system captures the trajectory pointed to by the doctor's intention vector through real-time multimodal perception. Forward prediction using the micro-world model indicates that this trajectory is highly likely to lead to femoral cortex penetration. Simultaneously, the system calculations reveal a significant discrepancy between this intention vector and the master template library (energy function distance exceeds the safety threshold), and real-time emotional value analysis detects a significant increase in the doctor's frustration and anxiety.

[0059] When the system determines that the current situation constitutes a "risky intent," the "Sky Guardian System" is immediately triggered, executing the "Red Shock" procedure: all power to the intelligent surgical drill in the doctor's hands is instantly cut off, and it enters a completely mechanically locked state, unable to move; the linked collaborative robotic arm also immediately locks. The doctor simultaneously hears a rapid stop warning tone through bone conduction headphones. This risk event is immediately marked as an alarm and pushed to the superior monitoring center for recording. If the doctor triggers this alarm three times consecutively during the same surgery, the system will automatically record the situation and may trigger corresponding performance reviews and mandatory training processes in conjunction with the hospital management system.

[0060] Example 3: Offline Applications in Special Environments (such as Battlefields or Deep Space) This example illustrates the system's application in extreme environments where a connection to the central server is unavailable. In a field rescue operation or a long-duration deep-space mission, the medical module needs to perform emergency orthopedic surgery.

[0061] After the doctor starts the system, the device loads the latest downloaded, independently running offline version of the microworld model and master intent template library. Although it cannot upload data or receive model updates in real time, the system can still rely on the local model to complete all multimodal signal acquisition, latent space encoding, intent generation and prediction, and comparative analysis with the local template library.

[0062] The system can provide master-level green holographic path guidance and force feedback assistance, and can also trigger device locking and local alarms through the local "Skyguard System" when a risky intent is detected. All surgical data (intent events and tags) are encrypted and stored locally, and will be uploaded again after the network is restored to participate in federated learning. This ensures that the system can maintain a high level of assistance and safety monitoring capabilities for a specified period of time even without a network.

[0063] Example 4: The System's Continuous Evolution Based on Federated Learning This example illustrates how the system can self-optimize using routine surgical data. Every surgery performed using this system at multiple collaborating orthopedic centers across the country generates massive amounts of anonymized intent event data packets (including intent vectors, emotional physiological labels, and final surgical outcome assessments).

[0064] This data is collected daily through a secure channel and federated to the central micro-world model for federated learning. The learning process continuously refines the "master-level intent template library," making the model more sensitive and accurate in recognizing excellent operational intentions. At the same time, the threshold parameters used by the "Sky Guardian System" to determine risky intentions (such as the thresholds for energy distance and emotional components) are also analyzed and dynamically adjusted based on a wider range of data, ensuring that its safety interventions are both precise and not excessive.

[0065] Through this continuous, nationwide closed-loop learning process involving real-person surgeries, the system's core capability—the accuracy of intent recognition—is regularly and significantly improved, making auxiliary functions increasingly intelligent and the safety defenses increasingly reliable.

[0066] Example 5: Application of Scenarios Combined with Special Management Rules This example demonstrates how specific management logic embedded in the system takes effect in a particular context. Scenario 1: A doctor's child happens to be at a childcare center affiliated with the hospital. When a risk intent alert is accidentally triggered during the doctor's surgery due to an unexpected situation, the system, while recording the safety intervention event itself (for technical analysis), automatically reduces the negative impact of this event on the doctor's personal evaluation system (i.e., "blemish record") based on built-in rules.

[0067] Scenario 2: A senior doctor who received a substantial "golden idea reward" for proposing several outstanding technical improvement solutions. Based on the rewards he received that month, the system automatically and slightly relaxed the threshold for judging his personal risk intent. This means that when monitoring his safety, the system will consider his high level of technical expertise and innovation, giving him slightly more trust at the edge of the threshold, but the core safety red lines remain unchanged.

[0068] These special rules, as part of the system management logic, run in the background and do not affect the core navigation assistance and safety braking functions, but they increase the flexibility and human-centered design of the system application.

[0069] Although embodiments of the invention have been shown and described, it will be understood by those skilled in the art that various changes, modifications, substitutions and alterations can be made to these embodiments without departing from the principles and spirit of the invention, the scope of which is defined by the appended claims and their equivalents.

Claims

1. A method for real-time optimization of drilling and implant placement intentions in orthopedic surgery navigation based on multimodal perception, characterized in that, Includes the following steps: (1) Real-time acquisition of multimodal signals of orthopedic surgeons through intraoperative XR glasses and intelligent surgical drill, including 128-channel EEG signals, eye movement gaze trajectory, hand micro-force-torque, electromyography signals, heart rate variability, speech tone, and drill vibration spectrum; (2) Input the multimodal signal into the pre-trained orthopedic surgery microworld model and use the Yann LeCun joint embedding prediction architecture to generate the current drilling or implantation intention vector in the latent space; (3) The micro-world model predicts in real time the latent space sequence of bone structure trajectories that will be generated if the intention is executed within the next 0.2 to 12 seconds; (4) Real-time calculation of the energy function distance between the intention vector and the similar intention template library of historical top orthopedic masters, as well as the three-dimensional components of focus, frustration and fear in the emotional value function; (5) When the energy function distance is less than 0.018 and the focus component of the emotional value function is greater than 0.92, it is determined to be a master-level intention. The predicted trajectory is automatically converted into an XR holographic green optimal drilling path, and combined with robot force feedback and drill bit speed adaptation. (6) When the energy function distance is greater than 0.10 or the sum of the frustration and fear components of the emotional value function is greater than 0.78, it is determined to be a risk intention, and a red shock is immediately triggered through the Tian Shou system, the surgical drill or robot is completely locked, and a stop prompt is output through the bone conduction headphones and a State-owned Assets Supervision and Administration Commission-level alarm is pushed. (7) All intentional events with emotional and physiological labels are fed back to the central micro-world model in real time for real-person closed-loop federated learning in orthopedic centers across the country, and the intention template library and the braking threshold of the Tian Shou system are evolved daily. (8) All original multimodal signals are physically destroyed immediately after the local XR glasses complete the latent space encoding. When any original EEG signal is detected attempting to leave the country, the glasses and the main control chip fuse of the drilling rig are immediately burned through an independent hardware relay.

2. The method for real-time optimization of drilling and implant placement intention in orthopedic surgery based on multimodal perception according to claim 1, characterized in that: The green optimal drilling path is presented in real time in the form of a four-fold combination of Master Ghost Drill semi-transparent overlay, force prediction line, tactile guidance and bone conduction voice.

3. The method for real-time optimization of drilling and implant placement intention in orthopedic surgery based on multimodal perception according to claim 1, characterized in that: If a doctor is identified as having a risky intent three times in a row, their monthly performance bonus will be automatically reduced by 60%, and they will be forced to attend a master review training session.

4. The method for real-time optimization of drilling and implant placement intention in orthopedic surgery based on multimodal perception according to claim 1, characterized in that: It supports battlefield or deep space orthopedic surgery scenarios, has an offline runtime of no less than 168 hours, and possesses master-level intent recognition capabilities.

5. The method for real-time optimization of drilling and implant placement intention in orthopedic surgery based on multimodal perception according to claim 1, characterized in that: When a doctor's children are at the company's childcare center, all high-risk intentional events are automatically exempted from 100% of the blemish record.

6. The method for real-time optimization of drilling and implant placement intention in orthopedic surgery based on multimodal perception according to claim 1, characterized in that: When a doctor's monthly reward for a brilliant idea is no less than 12 million yuan, the risk intent threshold is automatically relaxed by 0.

08.

7. The method for real-time optimization of drilling and implant placement intention in orthopedic surgery based on multimodal perception according to claim 1, characterized in that: The surgical drill supports 256 independent micro-vibration motors and force feedback, transmitting master-level tactile feedback to the doctor's hand in real time with a delay of less than 6 milliseconds.

8. The method for real-time optimization of drilling and implant placement intention in orthopedic surgery based on multimodal perception according to claim 1, characterized in that: The micro-world model evolves based on daily federated learning data, and the intent recognition accuracy improves by no less than 15.2% per quarter.

9. The method for real-time optimization of drilling and implant placement intention in orthopedic surgery based on multimodal perception according to claim 1, characterized in that: When the Tianshou system triggers a red alert, it simultaneously sends an alarm to the State-owned Assets Supervision and Administration Commission-level monitoring center and records the event log for audit analysis.

10. The method for real-time optimization of drilling and implant placement intention in orthopedic surgery based on multimodal perception according to claim 1, characterized in that: The physical destruction includes encrypting and overwriting the original multimodal signal, and then destroying the storage medium to ensure that the data is unrecoverable.

Images