Artificial intelligence-based minimally invasive spinal fusion system

CN121512698BActive Publication Date: 2026-06-26联科医疗器械(安徽)有限公司
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Patent Information

Authority / Receiving Office
CN · China
Patent Type
Patents(China)
Current Assignee / Owner
联科医疗器械(安徽)有限公司
Filing Date
2025-11-17
Publication Date
2026-06-26

AI Technical Summary

Technical Problem

Existing technologies struggle to achieve real-time, high-precision monitoring and dynamic path optimization of surgical instrument trajectories in spinal surgery, especially in complex surgical environments where instrument trajectories are susceptible to vibration, tissue deformation, and equipment vibration. This makes it difficult to accurately quantify and correct trajectory deviations in real time, and real-time synchronization of image data and navigation models is challenging, affecting the accuracy of deviation warnings and the stability of path planning.

Method used

The minimally invasive spinal fusion system based on artificial intelligence collects surgical instrument movement trajectories and intraoperative imaging data in real time. It combines machine learning algorithms to build a predictive model, identify deviation trends and generate compensation parameters, dynamically adjust vibration intensity and frequency, update the three-dimensional navigation model, trigger deviation warnings, optimize the trajectory through smoothing filtering, generate navigation command sequences, and iteratively update multimodal data to correct instrument vibration deviations and ensure path stability.

Benefits of technology

It enables precise surgical navigation in complex surgical environments, significantly improving the surgical operation experience and consistency, and ensuring the stability and reliability of the surgical path.

✦ Generated by Eureka AI based on patent content.

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Abstract

The application discloses a minimally invasive spinal fusion system based on artificial intelligence, which comprises the following steps: after the deviation warning signal is obtained, the instrument trajectory data is subjected to smoothing filtering processing, the filtered trajectory sequence is obtained, and the filtered trajectory sequence is matched with the updated model grid; the dynamic path adjustment parameter is determined and is built into the surgical robot to adjust the vibration frequency parameter and improve the control experience level; the subsequent image data is processed by using the iterated model version, the temporary deviation caused by the instrument shaking is determined, and the temporary deviation is corrected through the path planning algorithm; the corrected navigation instruction sequence is generated, and the real-time feedback mechanism is applied to transfer the intuitive deviation information; the surgical instrument is driven to adjust the movement through the navigation instruction sequence, the adjusted trajectory data is obtained, and the deviation of the optimized path is compared and optimized in a cycle; if the deviation continuously falls below the threshold value, the current model is maintained, and the final navigation model is output to ensure reliable consistency.
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