Intelligent surgical navigation system and surgical navigation method based on inertial measurement unit

Abstract

The application relates to an intelligent surgery navigation system and method based on an inertial measurement unit, the surgery navigation system comprising an inertial measurement data acquisition and calibration module, a pose solution and fusion positioning module, an image space registration module, a navigation guidance and safety constraint module, and a drift compensation and quality control module. The surgery navigation method comprises zero offset estimation, installation pose calibration and time synchronization; external reference information is fused to obtain a continuous and stable six-degree-of-freedom pose of a surgical instrument; a registration relationship between a patient image coordinate system and an intraoperative patient coordinate system is established; and navigation guidance and risk early warning are output. The application can complete the acquisition and calibration of inertial measurement data at the instrument end, the continuous solution and multi-source fusion correction of the instrument pose, the real-time mapping of the instrument pose to the patient image space, and the navigation guidance and safety constraint output under conditions such as interference or intermittent failure of external positioning, so as to improve the positioning accuracy, navigation continuity and operation safety in a complex surgery scene.

Description

Technical Field

[0001] This invention belongs to the field of computer-aided surgical navigation and intelligent medical device technology, specifically an intelligent surgical navigation system and surgical navigation method based on an inertial measurement unit. Background Technology

[0002] In high-precision surgeries such as neurosurgery, orthopedics, otolaryngology, and spinal surgery, surgical navigation systems are crucial for improving positioning accuracy and reducing the risk of tissue damage. Current navigation methods largely rely on optical, electromagnetic, or vision-based positioning technologies. They acquire instrument pose through real-time tracking of instrument markers and map the instrument position onto preoperative or intraoperative imaging space to assist surgeons in path planning, target attainment, and safety boundary control. However, the complexities of actual surgical environments mean that current technologies still face the following prominent problems and challenges in clinical application: 1. Obstruction and limited field of vision lead to navigation interruption and insufficient continuity: Optical navigation usually relies on the camera's visual tracking of reflective balls or coded markers. During the operation, it is easily affected by medical staff, instrument crossing, changes in body position, and reflection of surgical lights, which can cause the marker points to be lost or the tracking to be unstable, resulting in short or long interruptions in navigation, affecting the rhythm of the operation and the safety of the operation. 2. Electromagnetic environment interference and spatial limitations affect positioning accuracy: Although electromagnetic navigation can alleviate the obstruction problem to some extent, its positioning accuracy is easily affected by environmental interference such as metal instruments, operating tables, and CT gantry; at the same time, the working space of electromagnetic fields is limited and the requirements for operating room layout are high, making it difficult to obtain high-precision pose stably in some scenarios. 3. Intraoperative dynamic changes lead to cumulative registration errors: During the operation, slight changes in patient position, soft tissue deformation, changes in exposure of bony structures, or local morphological changes caused by traction may occur, causing deviations between preoperative images and the actual intraoperative state; if the system lacks a continuous error monitoring and dynamic correction mechanism, navigation errors will accumulate over time, leading to increased target deviation and distortion of risk structure indications; 4. Existing systems are not responsive enough to high-frequency motion: Surgical instruments may require rapid fine-tuning, jitter suppression and high-frequency attitude changes during critical steps. However, external positioning such as optical / electromagnetic systems is usually affected by sampling rate, filtering delay or short-term frame loss, and is not responsive enough to high-frequency attitude changes, making it difficult to simultaneously achieve "smooth stability" and "real-time tracking". To address these challenges, existing technologies incorporate inertial measurement units (IMUs) into the device for attitude measurement, leveraging the IMU's high sampling rate and line-of-sight independence to improve navigation continuity. However, existing solutions still have shortcomings: Firstly, IMUs suffer from zero-bias drift and integration errors. Without effective calibration, online drift compensation, and external reference fusion, prolonged operation can lead to rapid accumulation of pose errors. Secondly, there are multi-level coordinate transformation relationships between the IMU coordinate system, the device coordinate system, the patient coordinate system, and the image coordinate system. Without a rigorous spatiotemporal synchronization and registration mapping mechanism, coordinate drift can easily accumulate, resulting in deviations in the final navigation display.

[0003] In summary, current technologies have not yet provided an integrated intelligent surgical navigation method that can fully leverage the advantages of high-frequency continuous IMU measurements under conditions of occlusion, interference, and intraoperative dynamic changes, and combine multi-source reference information to achieve drift suppression, real-time registration mapping, and navigation reliability assessment. Therefore, a new technical solution is urgently needed to balance navigation continuity, positioning accuracy, and clinical usability, thereby improving the level of intelligent navigation and operational safety in complex surgical scenarios. Summary of the Invention

[0004] The technical problem to be solved by this invention is to provide an intelligent surgical navigation system and surgical navigation method based on inertial measurement units. Under conditions such as intraoperative obstruction, limited field of view, electromagnetic interference, or intermittent failure of external positioning, it can automatically complete the highly reliable acquisition and calibration of inertial measurement data at the instrument end, continuous calculation and multi-source fusion correction of instrument pose, real-time mapping of instrument pose to patient image space, and navigation guidance and safety constraint output, thereby improving the positioning accuracy, navigation continuity and operational safety in complex surgical scenarios.

[0005] To address the aforementioned technical problems, this invention provides an intelligent surgical navigation system based on an inertial measurement unit (IMU), comprising: an inertial measurement data acquisition and calibration module, used to acquire in real time the acceleration, angular velocity, and attitude information of the surgical instrument end through an IMU installed on the surgical instrument end or navigation indicator, and to perform static and / or dynamic calibration on the IMU to compensate for zero bias, scale factor error, and installation error, thereby forming an inertial measurement data stream with a unified time reference; The pose calculation and fusion positioning module is used to perform attitude integration and kinematic calculation on the inertial measurement data stream, and to fuse the high-frequency pose update of the inertial measurement unit (IMU) with external reference information using extended Kalman filter (EKF) and / or unscented Kalman filter (UKF) to obtain a continuous and stable six-degree-of-freedom pose of the surgical instrument. The external reference information includes optical positioning information, electromagnetic positioning information, intraoperative visual odometry information and / or preoperative registration results. The image space registration module is used to establish a spatial mapping relationship between the surgical instrument coordinate system and the patient image coordinate system, and to map the six-degree-of-freedom pose of the surgical instrument to the patient image coordinate system, so as to realize the real-time display of the instrument in two-dimensional slices and three-dimensional models. The navigation guidance and safety constraint module is used to display the instrument position, attitude and motion trajectory in real time on the preoperative CT and / or MRI 3D model based on the mapped pose, and to provide navigation prompts and risk warnings in combination with the surgical planning path and safety boundaries. The drift compensation and quality control module is used to perform online compensation for the cumulative drift of the inertial measurement unit (IMU) based on external reference information and error constraints, and output positioning error evaluation results and / or navigation reliability prompts.

[0006] Furthermore, the inertial measurement data acquisition and calibration module includes: The zero-bias estimation submodule is used to estimate and compensate for the zero bias of the gyroscope and accelerometer in a static state. Install the pose calibration submodule to determine the fixed transformation relationship between the inertial measurement unit (IMU) coordinate system and the surgical instrument coordinate system; The time synchronization submodule is used to synchronize the sampling clock of the inertial measurement unit (IMU) with the sampling clock of the external reference information to form a data alignment result with a unified timestamp.

[0007] Furthermore, the pose calculation and fusion localization module includes: The attitude calculation unit is used to perform attitude integration based on the gyroscope angular velocity and to perform attitude correction in combination with acceleration and gravity direction constraints. The state estimation unit is used to construct a state vector containing attitude, velocity, position and sensor zero bias, and to recursively estimate the state vector using EKF and / or UKF. An external reference fusion unit is used to introduce optical positioning information, electromagnetic positioning information, intraoperative visual odometry information and / or preoperative registration results as observations into the state estimation unit to suppress drift and improve pose stability.

[0008] Furthermore, the external reference fusion unit has a failure switching strategy. When external reference information is lost or obstructed, the external reference fusion unit automatically switches to the prediction mode dominated by the inertial measurement unit (IMU) to maintain navigation continuity. When external reference information is restored, it performs relocking and error recovery to reduce accumulated errors and restore positioning accuracy.

[0009] Furthermore, the image spatial registration module includes: The preoperative image 3D reconstruction submodule is used to generate a 3D model of the patient's anatomical structure based on preoperative CT and / or MRI. The marker or anatomical feature registration submodule is used to register the patient image coordinate system with the intraoperative patient coordinate system based on intraoperatively acquired landmarks, bony structural features and / or surface point clouds; The instrument mapping submodule is used to map the surgical instrument pose to the patient image coordinate system based on the registration results and to update it in real time.

[0010] Furthermore, the navigation guidance and safety constraint module includes: The path guidance submodule is used to display the planned path, the target point, and the deviation of the current attitude of the instrument, and output direction, angle, or distance prompts. The visualization submodule is used to simultaneously display the instrument trajectory and its spatial relationship with key anatomical structures in two-dimensional slices and three-dimensional views.

[0011] The present invention also provides a surgical navigation method using the above-mentioned intelligent surgical navigation system based on an inertial measurement unit, comprising the following steps: S1: Install an inertial measurement unit (IMU) at the surgical instrument end and complete time synchronization. Perform zero bias estimation and compensation in a static or quasi-static state. Perform installation pose calibration between the IMU coordinate system and the instrument coordinate system to obtain a fixed transformation relationship installation pose calibration and obtain an inertial measurement data stream with a unified time reference. S2: Perform attitude integration and state estimation on the inertial measurement data stream, obtain external reference information, and fuse the external reference information through EKF and / or UKF to obtain a continuous and stable six-degree-of-freedom pose of the surgical instrument; S3: Establish the registration relationship between the patient image coordinate system and the intraoperative patient coordinate system, and map the six-degree-of-freedom pose of the surgical instruments to the patient image coordinate system; S4: Display the instrument position, orientation, and trajectory in real time on the preoperative CT and / or MRI 3D model, and output navigation guidance and risk warnings in combination with the planned path and safety boundary; S5: Based on external reference information and error constraints, perform online compensation for IMU drift and output navigation reliability assessment results.

[0012] Furthermore, the fusion of external reference information in step S2 includes: using the external reference information as an observation for error correction when the external reference information is available; maintaining pose continuity using the inertial measurement unit (IMU) prediction mode when the external reference information is unavailable, and performing relocking and error recovery when the external reference information is recovered.

[0013] Furthermore, the navigation reliability assessment in step S5 includes: outputting a positioning accuracy indication based on the filter residual, covariance growth trend, and / or drift estimate, and prompting recalibration, re-registration, or switching to a backup external reference information source when the accuracy is lower than a preset threshold.

[0014] Compared with the prior art, the beneficial effects of the present invention are: 1. Strong navigation continuity: Utilizing IMU high-frequency measurement and failure switching strategies, the instrument's pose can still be continuously output even when there is occlusion or short-term failure of external positioning.

[0015] 2. Multi-source fusion to suppress drift: Online correction of IMU cumulative drift is performed by fusing external reference information through EKF / UKF, which significantly improves the positioning stability and accuracy during long-term surgery.

[0016] 3. Real-time image space mapping: Establish a stable mapping relationship between instrument pose and patient image coordinate system to realize real-time navigation display and trajectory playback on two-dimensional slices and three-dimensional models.

[0017] 4. Safety Constraints and Risk Warnings: By combining the safety boundaries of the planned path and key risk structures, real-time deviation prompts and alarm mechanisms are provided to improve operational safety.

[0018] 5. Strong adaptability to complex surgical fields: It can maintain reliable navigation even under conditions such as limited field of vision, instrument crossover, and environmental interference, improving the usability of complex surgical scenarios.

[0019] 6. Integrated process facilitates deployment: It forms an integrated process of "calibration-integration-registration-guidance-evaluation", which is easy to integrate into existing navigation platforms or intelligent surgical systems for application. Attached Figure Description

[0020] Figure 1 This is a structural block diagram of the intelligent surgical navigation system based on an inertial measurement unit according to the present invention; Figure 2 This is a flowchart of the surgical navigation method of the present invention; Figure 3 This is an example of the effect of the invention (trajectory comparison illustration). Detailed Implementation

[0021] To make the above-mentioned objects, features and advantages of the present invention more apparent and understandable, the specific embodiments of the present invention will be described in detail below with reference to the accompanying drawings.

[0022] Many specific details are set forth in the following description in order to provide a full understanding of the invention. However, the invention may also be practiced in other ways different from those described herein, and those skilled in the art can make similar extensions without departing from the spirit of the invention. Therefore, the invention is not limited to the specific embodiments disclosed below.

[0023] The intelligent surgical navigation system based on an inertial measurement unit proposed in this invention is available for reference. Figure 1It includes an inertial measurement data acquisition and calibration module, a pose calculation and fusion positioning module, an image spatial registration module, a navigation guidance and safety constraint module, and a drift compensation and quality control module, and these modules are interconnected.

[0024] This invention divides the overall process into two closely coupled and interconnected core links: the inertial fusion positioning link and the image registration and navigation link.

[0025] Inertial Fusion Positioning Link: This link aims to leverage the high sampling rate and line-of-sight independence of the Inertial Measurement Unit (IMU) to obtain continuous and stable six-DOF (degrees of freedom) pose of the instrument through calibration compensation and filtering fusion. Its "high-frequency continuous drive, primarily based on the IMU," prioritizes the continuity and high-frequency response of pose output, rather than relying solely on instantaneous observations from external positioning.

[0026] Image registration and navigation link: This link aims to establish a stable mapping relationship between instrument pose and patient image coordinate system, and to achieve real-time visual guidance and safety boundary constraints on preoperative CT and / or MRI 3D models. Its "registration mapping + safety constraint" mode strives to provide interpretable and usable navigation prompts and risk warnings even under dynamic conditions during surgery.

[0027] The intelligent surgical navigation system and method of the present invention achieve the above-mentioned link coordination. Specifically, in the embodiments of the present invention: I. Inertial Measurement Unit (IMU) calibration and time synchronization, corresponding to the deepening of the inertial measurement data acquisition and calibration module.

[0028] Stable calibration and time synchronization are prerequisites for subsequent pose calculation and navigation mapping. This invention employs a strategy based on "zero bias compensation + installation calibration + unified time reference" to achieve a consistent data foundation across instruments and sensors.

[0029] Inertial data stream initialization: After the instrument-side IMU is installed before the operation begins, the calibration module first collects acceleration and angular velocity data within a time window in a stationary or quasi-stationary state to estimate the zero bias of the accelerometer and gyroscope, and writes the zero bias into the compensation parameters, thereby forming a preliminary drift-free inertial measurement data stream.

[0030] Installation pose calibration: Due to the fixed installation error between the IMU coordinate system and the instrument coordinate system, the system further performs installation pose calibration, solving for the fixed transformation matrix from the IMU coordinate system to the instrument coordinate system. This allows subsequent attitude calculations to output a six-DOF pose that can be directly used for navigation, with the instrument axis as the reference. The calibration can be achieved based on predefined calibration actions, alignment procedures based on structural constraints, or joint estimation based on external references.

[0031] Time synchronization and alignment: To ensure the consistency of IMU high-frequency data and external reference information in fusion filtering, the system timestamps the IMU sampling clock and the external reference sampling clock to establish a unified time reference for data alignment. When there are frame drops or delays in the external reference, the system can use interpolation and delay compensation strategies to ensure that observation updates and prediction updates are performed on the same time axis.

[0032] Error baseline establishment: After completing zero bias compensation, installation calibration and time synchronization, the system will output a set of traceable calibration parameters and synchronization parameters as the error baseline of the current surgical session, which will be used for subsequent drift monitoring, reliability assessment and rapid recalibration when necessary.

[0033] II. Pose calculation and multi-source fusion correction, which is a further development of the pose calculation and multi-source fusion positioning module and the drift compensation and reliability assessment module.

[0034] To obtain reliable pose output suitable for surgical navigation under conditions of occlusion, limited field of view, or intermittent failure of external positioning, this invention establishes a strongly coupled fusion mechanism between IMU high-frequency prediction and external reference observation, enabling pose calculation to serve the stability of subsequent image mapping and safety guidance from the source.

[0035] Pose calculation and error state modeling: Attitude integration and gravity constraints: Once the inertial measurement data stream is determined, the fusion positioning module first performs attitude integration on the gyroscope angular velocity to obtain high-frequency attitude updates; and combines the accelerometer gravity direction constraints to suppress attitude drift, thereby maintaining the stability and continuity of attitude calculation in a short period of time.

[0036] State vector extension and zero bias estimation: To address the issues of zero bias drift and scaling factor error in IMUs, the module further constructs an error state model that includes attitude, velocity, position, and sensor zero bias. During the filtering recursion process, the zero bias is estimated and compensated online, so that the integral error can be continuously "absorbed" and suppressed.

[0037] Kinematic consistency constraints: To avoid instability in the solution caused by rapid micro-movements or jitters of the instrument, the system can introduce kinematic constraints and smoothing constraints to distinguish high-frequency noise from real motion and improve the usability of pose output.

[0038] Multi-source observation fusion and failure switching strategy: Observation update phase: When external reference information is available, the fusion positioning module introduces optical positioning, electromagnetic positioning, intraoperative visual odometry and / or preoperative registration results as observations into the EKF / UKF filtering framework to update the IMU predicted state, thereby periodically correcting the accumulated drift and keeping the instrument pose within an acceptable error range during long-term operation.

[0039] Prediction maintenance phase: When external reference information is temporarily unavailable due to occlusion, frame loss, or interference, the system automatically switches to IMU-led prediction mode, continuously outputting continuous poses and maintaining uninterrupted navigation. This phase prioritizes continuity to ensure that the navigation display is stable and followable during the operator's operation.

[0040] Relocking and Error Recovery: When external reference information is restored and available, the system executes a relocking and error recovery strategy to match the restored observation and prediction results in a consistent manner, and absorbs short-term drift through filtering to avoid sudden jumps in pose display, thereby achieving "regressible" accuracy recovery while "uninterrupted".

[0041] Core: Applications of drift compensation and reliability assessment Drift suppression: The system continuously monitors the drift trend through the filtered residuals and the zero-bias estimate, and increases the weight of external observations or triggers short-process recalibration when the drift increases, so as to reduce the risk of error accumulation during long-term operations.

[0042] Reliability Indication: The system comprehensively evaluates the covariance growth trend, observation availability, and filter residuals, and outputs positioning accuracy indication and navigation reliability prompts; when the reliability is lower than the preset threshold, it prompts recalibration, re-registration, or switching to a backup external reference information source.

[0043] Anomaly detection and security degradation: When an external reference mutation, observation inconsistency, or abnormal noise is detected, the system can temporarily reduce the weight of the observation source or block the observation source to avoid erroneous observations from "pulling off" the pose estimation, thereby improving the robustness of fusion positioning.

[0044] Through the above-mentioned in-depth design of attitude integration, error state modeling, multi-source fusion and failure switching, this invention constructs a complete "prediction-correction-recovery" technical closed loop, ensuring that the system can not only obtain high-precision instrument pose when the external positioning is stable, but also maintain navigation continuity under occlusion and interference conditions, and quickly recover errors and output reliability assessments after the external reference is restored, thereby truly realizing the core value of this invention in intelligent surgical navigation under complex surgical field conditions.

[0045] III. The surgical navigation method of the intelligent surgical navigation system based on inertial measurement unit of the present invention includes the following steps: refer to Figure 2 Phase 1: Offline calibration and model building, used to establish the inertial fusion model and image registration benchmark at the device end.

[0046] Calibration preparation and parameter construction: This stage is the same as in the previous embodiments, but emphasizes the standardization of the calibration process and the consistency of the coordinate reference. By performing zero-bias estimation, scaling factor compensation, and installation pose calibration on the instrument-side IMU, a fixed transformation relationship from the IMU coordinate system to the instrument coordinate system is established; and the timestamps and sampling frequencies of external reference information (such as optical positioning or electromagnetic positioning) are aligned to form a data synchronization rule with a unified time reference, thereby providing a reliable input basis for subsequent fusion filtering.

[0047] Specifically, the key to the offline construction process lies in the unified design of the "error model and coordinate relationship": establishing a zero bias and noise statistical model at the sensor level to constrain filter divergence; establishing a synchronous mapping between the IMU and the external reference at the time level to reduce pseudo-errors introduced by delay; and completing the fixed transformation calibration of IMU-instrument-external reference at the spatial level to ensure that the pose calculation output can be directly used for navigation display.

[0048] The aforementioned navigation space coordinate system can be defined as: IMU coordinate system I, instrument coordinate system K, external reference coordinate system R, and image coordinate system S.

[0049] IMU coordinate system I is a local coordinate system with the inertial measurement unit itself as the reference. It is the direct source of all acceleration and angular velocity data and is used to capture the most primitive motion information from the instrument.

[0050] The instrument coordinate system K is a coordinate system established with reference to the structural axis of the surgical instrument and the key point at the end. It is used to define the orientation, tip position, and clinically significant positional output of the instrument. It obtains a fixed transformation from I to K through positional calibration.

[0051] The external reference coordinate system R is a global coordinate system that is referenced by an external positioning system (such as an optical camera coordinate system or an electromagnetic field coordinate system). It is used to provide observational correction and global constraints for IMU drift. The correspondence between K→R or I→R is obtained through a one-time system calibration.

[0052] The image coordinate system S is an image space coordinate system with reference to preoperative CT and / or MRI. It is a "display anchor point" for navigation guidance and is used to present the spatial relationship between instruments and key anatomical structures in two-dimensional slices and three-dimensional models. The mapping relationship between R and S is obtained through patient registration.

[0053] Parameter solidification and strategy storage: During system deployment, key configuration solidification and annotation steps are performed. A core field, "Navigation Configuration," is added to record IMU calibration parameters, filter initial values ​​and noise covariance settings, external reference observation weights and failure switching thresholds, as well as key parameters of the image registration process, thereby ensuring traceability and consistency when called in different surgical scenarios.

[0054] Phase Two: Online navigation, positioning, and guidance output for real-time intraoperative tracking and interaction.

[0055] Inertial data acquisition and real-time calculation: The system starts the IMU to acquire data in real time and performs attitude integration and state prediction, outputting high-frequency continuous machine pose estimation results.

[0056] Multi-source fusion and drift suppression: When external reference information is available, the system performs observation updates to correct the accumulated drift of the IMU online; when external reference information is unavailable, the system automatically switches to IMU-dominated prediction mode to maintain pose continuity, and performs relocking and error recovery after the external reference is restored to reduce pose jumps and restore accuracy.

[0057] Image registration, mapping, and monitoring: The system establishes a registration relationship between the intraoperative patient coordinate system and the preoperative image coordinate system, and maps the instrument pose to the image coordinate system S. Subsequently, it outputs the instrument position, orientation, and trajectory on the image, and performs reliability assessment and risk warning based on the planned path and safety boundaries. When an increase in covariance anomaly, observation residual anomaly, or a decrease in positioning reliability is detected, a prompt message is output to ensure the usability of the navigation results.

[0058] Specifically, this is a typical real-time mapping and navigation guidance process of "instrument pose → image space". The accompanying drawings use the synchronous display of the instrument trajectory in two-dimensional slices and three-dimensional models, the deviation from the planned path, and the safety boundary alarm when approaching a risky structure as examples to intuitively present the technical connotation of the present invention of "calibration first, then fusion, then mapping, and then guidance".

[0059] pass Figure 3 It can be seen that the planned surgical trajectory and the estimated navigation trajectory are very consistent with each other, with very small error. The surgical navigation system and method of the present invention have good practicality.

[0060] Finally, it should be noted that the above descriptions are merely preferred embodiments of the present invention and are not intended to limit the present invention. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art can still modify the technical solutions described in the foregoing embodiments or make equivalent substitutions for some of the technical features. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the protection scope of the present invention.

Claims

1. An intelligent surgical navigation system based on an inertial measurement unit, characterized in that, include: The inertial measurement data acquisition and calibration module is used to acquire the acceleration, angular velocity and attitude information of the surgical instrument end in real time through the inertial measurement unit (IMU) installed on the surgical instrument end or navigation indicator, and to perform static and / or dynamic calibration on the inertial measurement unit (IMU) to compensate for zero bias, scale factor error and installation error, and form an inertial measurement data stream with a unified time reference. The pose calculation and fusion positioning module is used to perform attitude integration and kinematic calculation on the inertial measurement data stream, and to fuse the high-frequency pose update of the inertial measurement unit (IMU) with external reference information using extended Kalman filter (EKF) and / or unscented Kalman filter (UKF) to obtain a continuous and stable six-degree-of-freedom pose of the surgical instrument. The image space registration module is used to establish a spatial mapping relationship between the surgical instrument coordinate system and the patient image coordinate system, and to map the six-degree-of-freedom pose of the surgical instrument to the patient image coordinate system; The navigation guidance and safety constraint module is used to display the instrument position, attitude and motion trajectory in real time on the preoperative CT and / or MRI 3D model based on the mapped pose, and to provide navigation prompts and risk warnings in combination with the surgical planning path and safety boundaries. The drift compensation and quality control module is used to perform online compensation for the cumulative drift of the inertial measurement unit (IMU) based on external reference information and error constraints, and output positioning error evaluation results and / or navigation reliability prompts.

2. The intelligent surgical navigation system based on an inertial measurement unit as described in claim 1, characterized in that, The inertial measurement data acquisition and calibration module includes: The zero-bias estimation submodule is used to estimate and compensate for the zero bias of the gyroscope and accelerometer in a static state. Install the pose calibration submodule to determine the fixed transformation relationship between the inertial measurement unit (IMU) coordinate system and the surgical instrument coordinate system; The time synchronization submodule is used to synchronize the sampling clock of the inertial measurement unit (IMU) with the sampling clock of the external reference information to form a data alignment result with a unified timestamp.

3. The intelligent surgical navigation system based on an inertial measurement unit as described in claim 1, characterized in that, The pose calculation and fusion localization module includes: The attitude calculation unit is used to perform attitude integration based on the gyroscope angular velocity and to perform attitude correction in combination with acceleration and gravity direction constraints. The state estimation unit is used to construct a state vector containing attitude, velocity, position and sensor zero bias, and to recursively estimate the state vector using EKF and / or UKF. An external reference fusion unit is used to introduce optical positioning information, electromagnetic positioning information, intraoperative visual odometry information and / or preoperative registration results as observations into the state estimation unit to suppress drift and improve pose stability.

4. The intelligent surgical navigation system based on an inertial measurement unit as described in claim 3, characterized in that, When external reference information is lost or obstructed, the external reference fusion unit automatically switches to a prediction mode dominated by the inertial measurement unit (IMU), and performs relocking and error recovery when external reference information is restored to ensure navigation continuity.

5. The intelligent surgical navigation system based on an inertial measurement unit as described in claim 1, characterized in that, The image spatial registration module includes: The preoperative image 3D reconstruction submodule is used to generate a 3D model of the patient's anatomical structure based on preoperative CT and / or MRI. The marker or anatomical feature registration submodule is used to register the patient image coordinate system with the intraoperative patient coordinate system based on intraoperatively acquired landmarks, bony structural features and / or surface point clouds; The instrument mapping submodule is used to map the surgical instrument pose to the patient image coordinate system based on the registration results and to update it in real time.

6. The intelligent surgical navigation system based on an inertial measurement unit as described in claim 1, characterized in that, The navigation guidance and safety constraint module includes: The path guidance submodule is used to display the planned path, the target point, and the deviation of the current attitude of the instrument, and output direction, angle, or distance prompts. The visualization submodule is used to simultaneously display the instrument trajectory and its spatial relationship with key anatomical structures in two-dimensional slices and three-dimensional views.

7. A surgical navigation method using the intelligent surgical navigation system based on an inertial measurement unit according to any one of claims 1-6, characterized in that, Includes the following steps: S1: Install an inertial measurement unit (IMU) at the surgical instrument end and complete zero-bias estimation, installation pose calibration and time synchronization to obtain an inertial measurement data stream with a unified time reference; S2: Perform attitude integration and state estimation on the inertial measurement data stream, and fuse external reference information through EKF and / or UKF to obtain a continuous and stable six-degree-of-freedom pose of the surgical instrument; S3: Establish the registration relationship between the patient image coordinate system and the intraoperative patient coordinate system, and map the six-degree-of-freedom pose of the surgical instruments to the patient image coordinate system; S4: Display the instrument position, orientation, and trajectory in real time on the preoperative CT and / or MRI 3D model, and output navigation guidance and risk warnings in combination with the planned path and safety boundary; S5: Based on external reference information and error constraints, perform online compensation for IMU drift and output navigation reliability assessment results.

8. The surgical navigation method as described in claim 7, characterized in that, Step S2, which involves fusing external reference information, includes: using external reference information as an observation for error correction when it is available; maintaining pose continuity using the inertial measurement unit (IMU) prediction mode when external reference information is unavailable, and performing relocking and error recovery when external reference information is restored.

9. The surgical navigation method as described in claim 7, characterized in that, The navigation reliability assessment in step S5 includes: outputting a positioning accuracy indication based on the filter residual, covariance growth trend and / or drift estimate, and prompting recalibration, re-registration or switching to a backup external reference information source when the accuracy is lower than a preset threshold.

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