2426 results about "Spinal column" patented technology

The invention provides a seat comfort optimization calculation method based on a sensor and AI modeling, and the method comprises the steps: collecting the pressure distribution data of the sitting posture of a passenger and a spine contact area in real time through an attitude sensor and a pressure sensor which are disposed on a seat; a seat supporting area is divided into a cervical vertebra area, a thoracic vertebra area, a lumbar vertebra area and a sacrococcygeal area, and a pressure distribution prediction model of each area is established; constructing an input vector based on the average pressure, the maximum pressure, the pressure gravity center, the body type parameter and the pathological weight factor, and outputting a target support pressure value, a pressure avoiding curve and a neighbor cell migration proportion of each partition by using an artificial intelligence model; dynamic adjustment is achieved through the partitioned air bag and the driving unit, and secondary fine adjustment and protection are achieved in combination with feedback monitoring. The system comprises a posture sensing module, a pressure sensing module, a data processing module, a model building module, a regulation and control execution module and a feedback monitoring module, and self-adaptive regulation and control of different areas of the spine of a passenger can be achieved.

A clinical vertebra image segmentation method for assisting pedicle screw placement surgery, said method comprising: constructing a VerseDiff-UNet end-to-end framework, the framework being integrated with a denoising diffusion probabilistic model (DDPM); combining a noise-added image with a marked mask by using the VerseDiff-UNet framework, and guiding a diffusion direction toward a target region; and introducing a shape priors module on the basis of the DDPM, and extracting structural semantic information from an input spine image. In order to capture specific anatomical prior information in a medical image, the shape priors module is combined and the module effectively extracts the structural semantic information from the input spine image, thereby enabling more accurate anatomical structure segmentation, and facilitating accurate diagnosis and treatment of spinal disorders.

The embodiment of the invention discloses a spinal metastatic tumor treatment scheme generation system. According to one specific embodiment, the system comprises a data processing server, an information fusion server and a scheme generation server which are in communication connection with one another, and the data processing server is used for preprocessing multi-source patient data to obtain standard multi-source patient data; the information fusion server is used for executing the following steps: performing feature code fusion on standard multi-source patient data to obtain a multi-source patient feature vector; performing feature enhancement on the multi-source patient feature vector to obtain a joint patient characterization vector; generating an initial therapeutic schedule result based on the joint patient characterization vector; and the scheme generation server is used for performing feature decision processing on the initial treatment scheme result to obtain a final treatment report. According to the embodiment, waste of computing resources can be reduced, and system response time can be shortened.

The invention discloses a multi-axis dynamic scoliosis direction correcting device, which belongs to the technical field of medical instruments and comprises an upper flitch plate, a lower flitch plate, a spine plate, a movable connecting piece, a tension sensor, a hydraulic adjusting mechanism, a positioning and supporting mechanism and a control system, an upper arc-shaped plate surrounding the armpit is arranged on the outer side of the upper flitch, a lower arc-shaped plate surrounding the lower portion of the spine is arranged on the outer side of the lower flitch, and fixing mechanisms are arranged between the upper flitch and the upper arc-shaped plate and between the lower flitch and the lower arc-shaped plate. The movable connecting piece composed of the first ball seat and the first ball bead between the spine plates can achieve accurate attachment and flexible adaptation according to the natural trend of the spine, it is ensured that the device can accurately lock the deformity segment of scoliosis, a foundation is laid for subsequent targeted correction, and meanwhile the spine plates can be used for accurately locking the deformity segment of scoliosis. The tension sensors on the two sides of the spine plate can continuously monitor the pressure of the malformation section, and real-time data support is provided for correction force regulation and control.

The embodiment of the invention provides a spine image recognition method and related equipment. The spine image recognition comprises the following steps: acquiring a spine image to be detected, and preprocessing the spine image to be detected to obtain a target spine image; the target spine image is input into a key point recognition model, position information output by the key point recognition model for each section of vertebral body in the target spine image is obtained, and the position information is marked on the target spine image and at least comprises positioning frame information, a vertebral body name and angular point coordinates; the key point identification model comprises a CBAM module; correcting and adjusting the position information to obtain corrected position information; and performing intervertebral disc positioning and vertebra identification according to the corrected position information. According to the technical scheme, the improved key point recognition model is adopted, the positioning frame, the cone name and the angular point coordinates are directly output without depending on a segmentation model, the process is simplified, and the detection speed and robustness are improved.

The invention relates to the technical field of rehabilitation medical treatment, and discloses a muscle group stress analysis method and device, a terminal and a storage medium, and the method comprises the steps: respectively obtaining motion data collected by inertial measurement units arranged on the body of a user, and recognizing gait events based on the motion data corresponding to the inertial measurement units of the lower limbs, dividing the continuous motion data into a plurality of gait cycles according to the gait event; fusing the motion data acquired by each inertial measurement unit to obtain a three-dimensional posture of each preset segment of the body, and constructing a three-dimensional motion track of the spine area of the user in combination with a human kinematics chain model; processing the three-dimensional motion track and the known muscle group stress data by adopting a singular value decomposition embedding regression method to obtain a preliminary target muscle group stress curve of each gait cycle; and correcting the initial target muscle group stress curve based on a human body multi-rigid-body dynamic model in combination with a control cost function to obtain a final target muscle group stress curve.

The invention discloses an angle-adjustable spine blood coagulation electrode which comprises a tool bit assembly, a fixed body and a movable wire clamp. The tool bit assembly comprises an insulating rod, an inner tube and an outer tube, two electrodes which are insulated and separated are arranged at one end of the insulating rod, each electrode is connected with a conductive wire, and each conductive wire penetrates through the other end of the insulating rod and is connected with a cable; a first cavity and a second cavity which are communicated are formed in the fixing body, a steel pipe chuck and a screw cap are fixed to the other end of the first cavity, and a first handle and a second handle are arranged outside the fixing body. A reset spring is arranged in the first cavity; the movable wire clamp comprises a small-diameter section and a large-diameter section, and a third handle is arranged outside the movable wire clamp. The scalpel head can axially stretch out and draw back and circumferentially rotate to adjust the angle of the scalpel head through a single hand, the operation range is small, the scalpel head rotates more gently, use is more convenient, and the requirement for multi-angle blood coagulation in a spinal operation can be met.

The invention discloses a machine learning-based intra-operative bleeding risk prediction method and device for spinal surgery. The machine learning-based intraoperative bleeding risk prediction method for spinal surgery comprises the following steps: acquiring information of a patient to be predicted; obtaining a trained hemorrhage risk prediction model; and inputting the information of the patient to be predicted into the trained massive hemorrhage risk prediction model so as to obtain a prediction result. According to the method, the high-precision prediction model is trained through large-scale patient data (including basic information, operation parameters, blood indexes and the like), so that the accuracy and the stability of intraoperative SBL risk prediction are improved. And a Cell Saver use suggestion based on a risk threshold is provided, and blood resource allocation is optimized. Clinical decision-making efficiency is improved through an automatic tool, blood transfusion related complications (such as infection and immune response) are reduced, and patient prognosis is improved.

The invention provides a cortical bone screw automatic planning method and device based on a statistical morphology model. The method comprises the following steps: acquiring CT image data of any object; based on the CT image data, segmenting point cloud information of a vertebral body to be subjected to screw placement; acquiring a statistical shape model and cortical bone screw planning information corresponding to the serial number; and registering the statistical shape model to the point cloud information, and determining a cortical bone screw plan of the vertebral body to be subjected to screw placement. In the application, the preset screw placement planning of the cortical bone screw is performed through the statistical shape model, and the preset screw placement planning is mapped to the current spinal column three-dimensional model through registration, so that the preset screw placement planning only needs to be performed on the statistical shape model, and a screw placement model is not needed, thereby solving the problem that a large number of cases need to be collected to realize the screw placement model; therefore, the problem of nail placement of the cortical bone can be solved.

The invention provides a massage robot personalized physiotherapy method and system based on a cloud platform, and relates to the technical field of massage robots, and the method comprises the steps: carrying out the static posture scanning and dynamic posture capturing of a user; carrying out posture structure modeling based on a multi-modal fusion algorithm; calculating a security boundary, and marking a risk area; a massage path is planned through an improved RRT algorithm, and a personalized massage track is output; executing user massage, and monitoring massage pressure and spine displacement data in real time; abnormal values of massage pressure and spine displacement data are judged in real time, and personalized massage tracks are adjusted according to abnormal conditions. According to the method, an exclusive biomechanical digital twinborn model is established by adopting static and dynamic posture capture starting from individualization and fusing multi-dimensional data, and a safety constraint posture model is constructed through precisely quantified safety boundary calculation and risk area labeling, so that a unique massage path is planned; the individual difference requirements from the structure to the physiological tolerance are met.

The invention discloses a spine image key point detection algorithm based on multi-task learning. The algorithm comprises the following steps: constructing a multi-task deep learning network model comprising a segmentation branch and a key point positioning branch; a feature aggregation module based on multi-scale cavity convolution is embedded in the segmented branches, and the multi-scale cone feature extraction capability of the model is enhanced through splicing fusion of multiple cavity rate convolution branches and global pooling branches; a cross-task attention fusion module is introduced between the two branches, and bidirectional dynamic interaction and complementation between segmentation features and key point features are realized by generating and fusing first-order and second-order context attention maps; semantic alignment loss is designed in a training stage, collaborative optimization of two tasks is promoted by constraining the consistency of segmentation masks and key point heat maps in a high-level feature space, global information of segmentation and local information of key point detection are fully utilized, and the accuracy and stability of spine centrum key point positioning and the accuracy of a segmentation result are improved.

The invention discloses a self-adaptive sensing anti-shake regulation and control method and system for a spinal surgery auxiliary mechanical arm, and relates to the technical field of spinal surgery, and the method comprises the steps: collecting multi-dimensional data of a mechanical arm tail end actuator through a multi-dimensional sensor group, and transmitting the multi-dimensional data to an AeroStead space-level stability calculation platform; the platform carries out filtering processing on the data, and vibration of the mechanical arm and disturbance components caused by external interference are separated; constructing a spine mechanical arm rigid-flexible coupling dynamic disturbance observation and compensation model by using the disturbance component to observe disturbance and generate a compensation amount; calling a spinal operation area three-dimensional reconstruction and dynamic obstacle avoidance mixed density network model, and fusing different images to generate an operation area three-dimensional dynamic model and an obstacle avoidance adjustment signal; a mechanical arm motion control instruction is generated through a force sense position cooperation self-adaptive control algorithm; and the mechanical arm is driven to move for closed-loop regulation and control. According to the method, through fusion of multiple models and algorithms, the disturbance compensation precision, the operation area modeling accuracy and the control collaboration are improved, and the operation safety is guaranteed.

The invention provides a spine centrum compression fracture recognition method and system based on artificial intelligence, and the method comprises the steps: receiving original spine CT sequence data, and outputting a preprocessed standardized image; inputting the preprocessed image into a three-dimensional U-Net + + network to obtain a centrum segmentation probability graph; outputting the segmented centrum set and the position code thereof; for each segmented centrum, extracting a corresponding area based on a centrum mask, and splicing all features to form a comprehensive feature vector of each centrum; inputting the three-dimensional image block of each vertebral body into an image flow network to extract visual semantic features; and automatically generating a structured PDF report. According to the spine centrum compression fracture recognition method and system based on artificial intelligence, the problem of image quality difference caused by different CT devices and scanning parameters is effectively solved through the multi-scale residual enhancement technology and self-adaptive window level adjustment, and standardized processing of images is achieved.

The invention relates to the technical field of artificial intelligence, and discloses a spinal surgery mechanical arm precise regulation and control system integrating deep learning and dynamic calibration, and the system comprises a digital twinborn body construction module which is used for constructing a dynamic spinal digital twinborn body of a target object; the motion path analysis module is used for generating a planned motion path of the mechanical arm; the coarse regulation and control module is used for calculating a translation vector and a rotation vector of the mechanical arm and executing coarse regulation and control of the mechanical arm when the path error is not smaller than a preset first threshold value; the fine regulation and control module is used for calculating the rigidity coefficient of the mechanical arm and executing fine regulation and control of the mechanical arm when the path error is smaller than a first threshold value and not smaller than a preset second threshold value; and the micron-order regulation and control module is used for calculating pulse voltage required by the micro-motion platform and executing micron-order regulation and control of the mechanical arm when the path error is smaller than a second threshold value and not smaller than a preset safety threshold value. The control precision and safety of the spine surgery mechanical arm can be improved.

The invention discloses a rod end pedicle screw connector and a spine stabilizing device, and the connector comprises a first maintaining part which is provided with a cylindrical cavity, a main accommodating groove and an extrusion cavity; the second retaining part is arranged in the columnar cavity and is fixed with the rod-shaped part; the main gland is screwed with the upper cavity wall of the columnar cavity; a first sub-gland for pressing the second holding member; the wrapping part is arranged in the extrusion cavity and used for clamping the ball head of the screw; a force transmission part is arranged between the wrapping part and the main gland and used for transmitting pressure applied by the main gland to the wrapping part. An elastic component is arranged in the columnar cavity and is provided with a first combining end and a second combining end, and the two combining ends are allowed to be close to or far away from each other and the first combining end is allowed to swing in any direction relative to the second combining end through elastic deformation; the first combination end is fixedly connected to the second holding part, and the second combination end is fixedly connected to the first holding part or the force transmission part.

The invention discloses a deep learning algorithm-based spinal MRI precise synthesis CT image processing system and method for central axis type spinal arthritis, and the system comprises a data obtaining unit which is used for obtaining a three-dimensional T1 weighted multi-gradient echo sequence, a T2 weighted sequence and a water-fat separation sequence which are obtained through the magnetic resonance imaging of the spinal column of a target user; the spatial registration unit is used for inputting the multi-sequence data into a deformable registration network so as to carry out spatial registration on the multi-modal features; the feature processing unit is used for carrying out feature fusion on the registered multi-modal features and carrying out double-domain splitting based on an anatomical attention gating mechanism to obtain skeleton features and soft tissue features; and the image fusion unit is used for synthesizing a synthesized CT image with an HU value corresponding to the spine of the target user based on the skeleton features and the soft tissue features, so that radiation-free high-precision CT image acquisition is realized, the diagnosis grading requirement on the axis type spine joint in the spine can be met, and the influence of radiation on the target user can be reduced.

A system for correcting a lateral curvature of a spine that can include a plurality of screws configured to be implanted in a plurality of vertebrae, and a plurality of extensions configured to be removably coupled with the plurality of screws. Some embodiments of the plurality of extensions can be curved, bent, angled, and / or offset along at least a portion thereof and can be removably coupled with a screw head of each of the plurality of screws. The system can include a connecting element or rod that is configured to be coupled with the plurality of screw heads. Some embodiments of the system can be configured such that the rod can be guided along the plurality of extensions from the proximal toward the distal end portions of the extensions and into engagement with the plurality of screws to cause the plurality of vertebrae to move laterally.

Disclosed methods, devices, and systems are suitable for performing minimally-invasive procedures for accessing the intervertebral space along an oblique pathway with an insertion instrument that holds a disc implant, and reorienting the angular relationship between instrument and implant while the implant is inside the body (for example at or within the disc space).

The invention relates to the technical field of spine health, solves the problems that in the prior art, a spine posture abnormity screening mode is single, a screening process lacks grading progressive performance and a correction strategy lacks individuation, and provides a spine posture abnormity three-level screening and correction system and method. The system comprises a data acquisition module used for acquiring first original data, second original data and third original data; the primary screening module is used for obtaining a primary screening result; the secondary screening module is used for obtaining a secondary screening result according to the second original data; the third-stage screening module is used for obtaining a third-stage screening result according to the third original data; the comprehensive evaluation module is used for obtaining a comprehensive evaluation result; the correction management module is used for generating a personalized correction strategy; and the control module is used for managing the working process of each module. The invention provides a spine posture abnormity screening and correction system capable of generating a personalized spine correction strategy.

The present technology includes patient-specific spinal fusion devices, which may include an interbody implant that is designed to be positioned within a disc space between two vertebral bodies and one or more fixation elements that can anchor the interbody implant to the vertebral bodies. The fusion devices include one or more retention mechanisms for retaining the fixation elements within corresponding lumens or bore holes extending through the interbody implant. Methods for designing and manufacturing patient-specific spinal fusion devices are also described herein.

Methods of generating a surgical operative note for a surgical procedure, such as a spinal surgical procedure, and associated systems and devices are disclosed herein. In some embodiments, a representative method includes capturing surgical procedure data of the surgical procedure with a sensor array positioned to view the surgical procedure, and identifying features in the surgical procedure data relevant to the surgical procedure. The method can further comprise processing the identified features to provide contextual information about the surgical procedure, and utilizing an artificial intelligence (AI) application to generate the operative note based on the identified features and the contextual information. The operative note can include a natural language, structured, and coherent description of the surgical procedure that summarizes the surgical procedure, including the type of surgery performed, specific surgical techniques used, intraoperative findings, and / or postoperative care instructions.

The invention discloses a health early warning management system and method based on physical examination information, and particularly relates to the field of skeleton structure recognition, and the method comprises the steps: constructing a structural posture imaging data set based on a physical examination posture image of a student, extracting three-dimensional structure coordinates of parts, such as a scapula, a spine and a pelvis; and uniformly mapping to a skeleton reference system to calculate a body inclination index, a spine offset rate and a pelvic inclination index. Then, constructing a time sequence of posture structure parameters, and generating a trend feature vector sequence according to academic difference and gradient extraction; and further constructing a posture structure evolution trajectory diagram by taking the structure parameters as nodes and the trend vectors as edge attributes, and capturing a cross-year posture change path of the students. On the basis, all paths are aligned according to ages, the sudden change trend is extracted, the posture deviation high-incidence risk of a specific age group is recognized, and accurate student posture early warning management is achieved.

The invention relates to an early screening method and system for abnormal spinal curvature based on multi-modal data fusion, and the method comprises the steps: carrying out the fusion of space-time sequence features based on obtained multi-modal data, and carrying out the three-dimensional biomechanical modeling, and obtaining a spine-pelvis-lower limb dynamic coupling network; carrying out weighted calculation on the key mechanical transmission path through a graph attention mechanism based on a dynamic coupling network to obtain a path strengthening feature vector; performing multi-modal risk quantitative modeling based on the path strengthening feature vector to obtain a multi-dimensional risk index; and based on multi-dimensional risk indexes, carrying out grading early warning decision making through threshold value comparison and dynamic risk layering so as to realize early screening of spinal curvature abnormity. By implementing the scheme, the early screening accuracy of the abnormal spinal curvature can be improved.

A bellows shaped spinal implant, comprising an upper plate, a lower plate and a bellows shaped shell extending between and joining the upper and lower plates. The bellows shaped shell is formed of titanium or an alloy comprising titanium and includes a wall extending therearound that defines a hollow interior. The wall has a thickness in the range of 0.5 mm to 1.0 mm to provide for radiographic imaging through the wall. The wall is angled or curved inwardly or outwardly between the upper and lower plates to provide stiffness mimicking the stiffness properties of a similarly sized polyetheretherketone (PEEK) implant. The upper and lower plates each comprise porous contact regions including a three-dimensional gyroid lattice structure defined by a plurality of struts and pores in communication with the hollow interior. The outer surfaces of at least a portion of the struts may comprise a laser ablated textured surface.

Expandable spinal implants, systems and methods are disclosed. An expandable spinal implant may include a first endplate, a second endplate, and a moving mechanism that is operably coupled to the first and second endplates. The moving mechanism may include a wedge, a first sliding frame and a second sliding frame disposed on opposite sides of the wedge, a screw guide housing a rotatable first set screw and a rotatable second set screw opposite the first set screw. The first set screw may be operably coupled to the second sliding frame and the second set screw may be operably coupled to the wedge. The moving mechanism may operably adjust a spacing between the first and second endplates upon simultaneous rotation of the first and second set screws and operably adjust an angle of inclination between the first and second endplates upon translating the first set screw or second set screw.

A multi-axial spine testing system includes a physiological motion unit (PMU); a uni-axial test frame having an input; and a fixture configured to be attached to the test frame and facilitates a plurality of primary motions of one or more of the PMU and the fixture. The plurality of primary motions includes a linear motion of the input and a rotational movement of an output. The fixture has an upper assembly directly or indirectly coupled to the input. The upper assembly transfers the linear motion (Tz) of the actuator to the rotational movement (Rx) of the output. The upper assembly and lower assembly apply a bending moment (MX) and an axial compression (Fz) to the PMU. An external transducer collects data related to or generated by at least the plurality of primary motions. The fixture simultaneously provides the bending motion and axial compression to the PMU.

A stackable burial tower configured to store cremated remains is provided. The stackable burial tower includes a base member and a plurality of intermediate blocks. Each of the plurality of intermediate blocks is configured to stack on the base member or on each other thereby, in combination with the base member, forming a tower. A spinal structure extends from the base member through the plurality of intermediate blocks and a plurality of chamber vessels are configured to store cremated remains, each of the plurality of chamber vessels positioned within one of the plurality of intermediate blocks.

A surgical instrument kit for spinal fusion. The instrument kit includes a curved trocar (10), a flexible cannula (30) for positioning over the curved trocar, a flexible rasp device (70), and a bone graft delivery container (90).

A device for spinal correction includes a stabilizer assembly including a hinge including a first rod-bearing leaf; a second rod-bearing leaf rotatably coupled to the first rod-bearing leaf to provide coronal or sagittal freedom of movement, or both, of the stabilizer assembly; a locking mechanism to lock the first and second rod-bearing leaves at a desired angle; a first stabilizing rod coupled to the first rod-bearing leaf; a second stabilizing rod coupled to the second rod-bearing leaf; and a plurality of monoaxial or polyaxial links, wherein each monoaxial or polyaxial link is movably coupled to the first or second stabilizing rod and is movably couplable to a first spinal rod or a second spinal rod fixed to the spine; wherein the stabilizer assembly is couplable to the first or second spinal rod to stabilize the spine to prevent compression, distraction, or translation of the spinal cord during a spinal correction.

The invention relates to the field of biomedicine, and discloses a spine implant design method and system using the self-sensing characteristic of a piezoelectric material, and the method comprises the steps: collecting spine three-dimensional image data and clinical diagnosis information, recognizing the spine lesion characteristic and the spine implantation part of a target patient, and determining the basic structure size of a spine implant; setting a perception sensitivity level of the spine implant in the body of the target patient to generate perception performance judgment conditions of the spine implant; analyzing the biocompatibility requirement of the spine implantation part, and identifying the biological adaptation mode of the piezoelectric material in the body of the target patient; and embedding a piezoelectric signal processing module in the spine implant, and executing parameter optimization processing of the spine implant in combination with the biological adaptation mode and the perception performance judgment condition to obtain a target spine implant. According to the invention, the working state of the postoperative implant and the rehabilitation progress of the spine can be accurately evaluated.