一种腰椎减压手术实时跟踪与力反馈触觉检测方法及系统
By constructing a three-dimensional model of the patient's surgical area and combining it with a probe handle using piezoelectric ceramic sensing elements for real-time detection, the problems of large wound area, large spatial registration error, and insufficient tactile feedback in existing spinal surgeries have been solved. This has enabled real-time assessment of nerve root status and determination of tactile level, improving the accuracy and safety of the surgery.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Patents(China)
- Current Assignee / Owner
- FIRST HOSPITAL AFFILIATED TO GENERAL HOSPITAL OF PLA
- Filing Date
- 2025-12-15
- Publication Date
- 2026-07-17
AI Technical Summary
Current spinal surgeries and surgical navigation platforms typically employ open or relatively mature methods such as pedicle screw placement, which may result in larger wounds and slower recovery. Secondly, with the diverse forms and locations of lumbar degenerative diseases, and the frequent occurrence of multiple diseases, spatial registration errors exist between traditional image-guided navigation and intraoperative procedures. This makes it difficult to accurately identify and safely avoid complex nerve roots and surrounding soft tissues. Surgeons are forced to rely on experience to perform decompression procedures, lacking quantitative and real-time monitoring of tactile feedback, thus increasing the risk of nerve damage and postoperative complications.
By acquiring the patient's original preoperative imaging data, a three-dimensional model of the patient's surgical area is constructed, a surgical simulation path is formulated, and real-time detection is performed using a probe handle with piezoelectric ceramic sensing elements to achieve quantitative analysis of nerve root tactile sensation, establish a quantitative model of nerve root elasticity, and generate tactile levels.
It significantly improves the precision and safety of lumbar decompression surgery, reduces the risk of nerve damage, provides quantifiable and visualized auxiliary decision-making basis for minimally invasive decompression surgery, and enhances the intelligence and individualization of the surgery.
Smart Images
Figure CN121818102B_ABST