Visualized acupotomy treatment auxiliary control system for cervical spondylosis rehabilitation

Abstract

The application relates to the technical field of rehabilitation medicine, and discloses a visual needle-knife treatment auxiliary control system for cervical spondylosis rehabilitation, which comprises an image acquisition and reconstruction module, a spatial data acquisition module, an intelligent evaluation module and an interaction module. The application acquires target region and dangerous region point position data of a cervical vertebra model of a cervical spondylosis patient and motion data of a needle-knife in a treatment process in real time, calculates a danger coefficient, a resistance deviation coefficient, an operation evaluation coefficient and a target distance based on the acquired data, and then carries out real-time early warning on the treatment condition of the patient, and judges whether the needle-knife has reached the target region, and if so, the doctor is reminded.

Description

Technical Field

[0001] This invention relates to the field of rehabilitation medicine technology, specifically to a visual acupuncture knife therapy auxiliary control system for cervical spondylosis rehabilitation. Background Technology

[0002] As a representative minimally invasive technique combining traditional Chinese and Western medicine, needle knife therapy has unique value in the treatment of cervical spondylosis. However, the core operation of this technique has long relied heavily on the practitioner's personal experience and spatial imagination. With the development of medical technology towards precision and digitalization, the inherent defects of traditional needle knife therapy have become increasingly prominent, limiting its further improvement in safety and effectiveness and its standardized promotion.

[0003] Traditional techniques mostly rely on two-dimensional cross-sectional images provided by ultrasound to achieve visualization of cervical spine treatment. However, this technique requires doctors to integrate multiple two-dimensional planes into three-dimensional anatomical relationships in their minds, which requires a high level of spatial thinking ability and is prone to misjudgment. Furthermore, traditional techniques only provide visual assistance and lack synchronous perception of mechanical information that is crucial to the operation process, such as tissue resistance, leading to a disconnect between visual information and tactile sensation during treatment. Summary of the Invention

[0004] To address the shortcomings of existing technologies, this invention provides a visual needle knife therapy auxiliary control system for cervical spondylosis rehabilitation. This system connects to a visualization device to collect target and danger zone data from a patient's cervical spine model, as well as needle knife movement data during treatment. It then calculates the risk factor, resistance deviation factor, operation evaluation factor, and target distance in real time, providing real-time warnings about the patient's treatment progress. Furthermore, it alerts the doctor based on the target distance to confirm whether the target area has been reached. This invention solves the aforementioned technical problems.

[0005] To achieve the above objectives, the present invention provides the following technical solution: including an image acquisition and reconstruction module, a spatial data acquisition module, an intelligent evaluation module, and an interaction module; The image acquisition and reconstruction module is used to acquire the patient's cervical spine medical image data and construct a cervical spine pathological model; The spatial data acquisition module is connected to the visualization device. Based on the iterative nearest point algorithm, it fuses the pre-built cervical spine pathological model with the actual cervical spine model during patient treatment to obtain the fused actual cervical spine model. It also collects the point data of the target area and danger area of ​​the fused actual cervical spine model, as well as the motion dataset of the needle knife tip entering the patient's body. The intelligent assessment module includes a hazard identification unit, a target determination unit, and an operation assessment unit. The hazard identification unit obtains the hazard coefficient and resistance deviation coefficient based on the location data and motion dataset of the hazard area. The target determination unit obtains the target distance based on the location data and motion dataset of the target area. The operation assessment unit obtains the operation assessment coefficient based on the motion dataset. The interaction module executes guidance commands based on the risk factor, resistance deviation factor, operation evaluation factor, and target distance.

[0006] As a preferred technical solution of the present invention, the cervical spine pathological model includes multiple target areas and danger areas. The target areas are the lesion sites in the patient's cervical spine region, and the danger areas are the vascular structures, nerve structures, and skeletal structures in the patient's cervical spine region.

[0007] As a preferred embodiment of the present invention, the expression for the location data of the target area is: ,in, to They represent The outline of the target region, where the first... The expression for the contour of each target region is: ,in, to They represent the first The contours of the target regions in the fused actual cervical spine model Points.

[0008] As a preferred embodiment of the present invention, the expression for the location data of the hazardous area is: ,in, to They represent The outline of the danger zone, of which, the first The expression for the contour of a danger zone is: ,in, to They represent the first The contours of the danger zones in the fused actual cervical spine model Points.

[0009] As a preferred embodiment of the present invention, the expression for the motion dataset is: ,in, to This indicates that the tip of the needle knife has entered the patient's body. Motion data at a given moment, including the position of the needle tip, speed, resistance encountered, vibration frequency, and swing amplitude.

[0010] As a preferred embodiment of the present invention, the calculation process of the risk factor is as follows: Step A1: Calculate the Euclidean distance from the tip of the needle knife to all points along the contour of the danger zone, thus creating a dataset. ,in, Indicates the distance from the tip of the needle knife to the first Real-time Euclidean distance dataset of the contours of danger zones to These represent the distances from the tip of the needle knife to the first... Outline of a danger zone Real-time Euclidean distance of each point; Step A2: Based on the dataset obtained in Step A1 The hazard factor is calculated using the following expression: in, Indicates the risk factor; Indicates the distance from the tip of the needle knife to the first Real-time Euclidean distance dataset of the contours of several danger zones; This indicates taking the minimum value; This indicates the minimum Euclidean distance between the tip of the needle knife and the outline of the danger zone. Indicates the time at which the tip of the needle knife is... speed; This indicates the set buffer time for the needle tip to reach the danger zone; and These are the weighting coefficients. .

[0011] As a preferred embodiment of the present invention, the expression for the resistance deviation coefficient is as follows: in, Indicates the resistance deviation coefficient; This indicates that the tip of the needle knife enters the patient's body at a certain time. The resistance encountered; This represents the average resistance experienced by the tip of the needle knife at all times since it entered the patient's body; This represents the standard deviation of the resistance experienced by the tip of the needle knife at all moments since it entered the patient's body. It represents the absolute value.

[0012] As a preferred embodiment of the present invention, the calculation process of the target distance is as follows: Step B1: Calculate the Euclidean distance from the tip of the needle knife to all points on the target area contour, forming a dataset. ,in, Indicates the distance from the tip of the needle knife to the first Real-time Euclidean distance dataset of target region contours to These represent the distances from the tip of the needle knife to the first... Outline of each target area Real-time Euclidean distance of each point; Step B2: Select Dataset The shortest distance in As the target distance .

[0013] As a preferred embodiment of the present invention, the expression for the operation evaluation coefficient is as follows: in, Indicates the operational evaluation coefficient; Indicates the time at which the tip of the needle knife is... The frequency of the jitter; This indicates the vibration frequency set at the tip of the needle knife; Indicates the time at which the tip of the needle knife is... The amplitude of the swing; This indicates the set swing amplitude of the needle tip; and These are the weighting coefficients. .

[0014] As a preferred embodiment of the present invention, the guiding instruction specifically comprises: When the risk factor Resistance deviation coefficient and operational evaluation coefficient An alert is issued when any coefficient is greater than or equal to its respective set threshold; when the risk coefficient is... Resistance deviation coefficient and operational evaluation coefficient No warning will be issued if all thresholds are less than their respective set thresholds. When the target distance When the needle tip has entered the target area, it alerts the doctor; when the target distance is... At that time, no reminder is issued.

[0015] Compared with existing technologies, this invention provides a visual needle knife therapy auxiliary control system for cervical spondylosis rehabilitation, which has the following beneficial effects: This invention reconstructs and fuses 3D models based on CT 3D reconstruction technology and the Iterative Closest Point (ICP) algorithm by connecting to a visualization device. It collects target and danger zone location data of the cervical spine model of cervical spine patients, as well as needle knife movement data during treatment. Based on the collected data, it calculates the danger coefficient, resistance deviation coefficient, operation evaluation coefficient, and target distance, thereby providing real-time early warning of the patient's treatment status and determining whether the needle knife has reached the target area. If it has, it alerts the doctor. Attached Figure Description

[0016] Figure 1 This is a schematic diagram of the system framework of the present invention. Detailed Implementation

[0017] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0018] Please see Figure 1 A visual needle knife therapy auxiliary control system for cervical spondylosis rehabilitation, including an image acquisition and reconstruction module, a spatial data acquisition module, an intelligent assessment module, and an interaction module; The image acquisition and reconstruction module is used to acquire the patient's cervical spine medical imaging data and construct a cervical spine pathological model; The cervical spine pathology model includes multiple target areas and danger areas. The target area is the lesion site in the patient's cervical spine region, and the danger area is the vascular structure, nerve structure and bone structure in the patient's cervical spine region. The cervical spine pathology model is generated by three-dimensional reconstruction based on the patient's cervical spine CT scan data using CT three-dimensional reconstruction technology. The target area and danger area are jointly determined by doctors and experts. The spatial data acquisition module is connected to the visualization device. Based on the Iterative Closest Point (ICP) algorithm, the pre-built cervical spine pathological model is fused with the actual cervical spine model during patient treatment to obtain the fused actual cervical spine model. The module also collects the point data of the target area and danger area of ​​the fused actual cervical spine model, as well as the motion dataset of the needle knife tip entering the patient's body. During treatment, doctors use the ultrasound probe of an ultrasound diagnostic instrument to obtain a cervical spine model of the patient during treatment. After fusing it with a pre-constructed cervical spine pathology model, they use the region annotation function of 3D model software and optical positioning technology to collect point data and motion data of the needle knife tip. The expression for the point data of the target area is: ,in, to They represent The outline of the target region, where the first... The expression for the contour of each target region is: ,in, to They represent the first The contours of the target regions in the fused actual cervical spine model One point; The expression for the location data of the danger zone is: ,in, to They represent The outline of the danger zone, of which, the first The expression for the contour of a danger zone is: ,in, to They represent the first The contours of the danger zones in the fused actual cervical spine model One point; The expression for the motion dataset is: ,in, to This indicates that the tip of the needle knife has entered the patient's body. Motion data at any given moment, including the position of the needle tip, speed, resistance encountered, vibration frequency, and swing amplitude; The intelligent assessment module includes a hazard identification unit, a target determination unit, and an operation assessment unit. The hazard identification unit obtains the hazard coefficient and resistance deviation coefficient based on the location data and motion dataset of the hazard area. The target determination unit obtains the target distance based on the location data and motion dataset of the target area. The operation assessment unit obtains the operation assessment coefficient based on the motion dataset. The calculation process for the risk factor is as follows: Step A1: Calculate the Euclidean distance from the tip of the needle knife to all points along the contour of the danger zone, thus creating a dataset. ,in, Indicates the distance from the tip of the needle knife to the first Real-time Euclidean distance dataset of the contours of danger zones to These represent the distances from the tip of the needle knife to the first... Outline of a danger zone The real-time Euclidean distance of each point is given by the following expression: in, , and These represent the time intervals at the tip of the needle knife. The coordinates of the point along the horizontal, vertical, and axial directions; , and They represent the first The outline of the danger zone The coordinates of each point along the horizontal, vertical, and axial directions; Step A2: Based on the dataset obtained in Step A1 The hazard factor is calculated using the following expression: in, Indicates the risk factor; Indicates the distance from the tip of the needle knife to the first Real-time Euclidean distance dataset of the contours of several danger zones; This indicates taking the minimum value; This indicates the minimum Euclidean distance between the tip of the needle knife and the outline of the danger zone. Indicates the time at which the tip of the needle knife is... speed; This indicates the set buffer time for the needle tip to reach the danger zone; and These are the weighting coefficients. ; Risk factor The real-time shortest Euclidean distance between the tip of the needle knife and the danger zone There is a negative correlation; the closer the needle knife tip is to the danger zone, the higher the risk factor. The larger the value; The expression for the resistance deviation coefficient is as follows: in, Indicates the resistance deviation coefficient; This indicates that the tip of the needle knife enters the patient's body at a certain time. The resistance encountered; This represents the average resistance experienced by the tip of the needle knife at all times since it entered the patient's body; This represents the standard deviation of the resistance experienced by the tip of the needle knife at all moments since it entered the patient's body. Represents absolute value; Resistance deviation coefficient The range is It can reflect the real-time resistance experienced by the tip of the needle knife. Significant changes occur, such as the difference in resistance encountered by the tip of the needle when it touches bones and blood vessels compared to when it touches muscle tissue, and the exponential function can amplify this difference; The calculation process for the target distance is as follows: Step B1: Calculate the Euclidean distance from the tip of the needle knife to all points on the target area contour, forming a dataset. ,in, Indicates the distance from the tip of the needle knife to the first Real-time Euclidean distance dataset of target region contours to These represent the distances from the tip of the needle knife to the first... Outline of each target area The real-time Euclidean distance between each point is given by the following expression: in, , and They represent the first The outline of the target region The coordinates of each point along the horizontal, vertical, and axial directions; Step B2: Select Dataset The shortest distance in As the target distance ; The expression for the operational evaluation coefficient is as follows: in, Indicates the operational evaluation coefficient; Indicates the time at which the tip of the needle knife is... The frequency of the jitter; This indicates the vibration frequency set at the tip of the needle knife; Indicates the time at which the tip of the needle knife is... The amplitude of the swing; This indicates the set swing amplitude of the needle tip; and These are the weighting coefficients. ; Operational evaluation coefficient Real-time vibration frequency of the needle knife tip and real-time swing amplitude There is a positive correlation when the real-time jitter frequency Real-time swing amplitude The greater the difference between the actual value and the set value, the higher the operational evaluation coefficient. The larger the value; The interaction module executes guidance instructions based on the risk factor, drag deviation factor, operational evaluation factor, and target distance. The specific guidance instructions are as follows: When the risk factor Resistance deviation coefficient and operational evaluation coefficient An alert is issued when any coefficient is greater than or equal to its respective set threshold; when the risk coefficient is... Resistance deviation coefficient and operational evaluation coefficient No warning will be issued if all thresholds are less than their respective set thresholds. When the target distance When the needle tip has entered the target area, it alerts the doctor; when the target distance is... At that time, no reminder is issued.

[0019] 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 visual needle knife therapy auxiliary control system for cervical spondylosis rehabilitation, characterized in that: It includes an image acquisition and reconstruction module, a spatial data acquisition module, an intelligent evaluation module, and an interaction module; The image acquisition and reconstruction module is used to acquire the patient's cervical spine medical image data and construct a cervical spine pathological model; The spatial data acquisition module is connected to the visualization device. Based on the iterative nearest point algorithm, it fuses the pre-built cervical spine pathological model with the actual cervical spine model during patient treatment to obtain the fused actual cervical spine model. It also collects the point data of the target area and danger area of ​​the fused actual cervical spine model, as well as the motion dataset of the needle knife tip entering the patient's body. The intelligent assessment module includes a hazard identification unit, a target determination unit, and an operation assessment unit. The hazard identification unit obtains the hazard coefficient and resistance deviation coefficient based on the location data and motion dataset of the hazard area. The target determination unit obtains the target distance based on the location data and motion dataset of the target area. The operation assessment unit obtains the operation assessment coefficient based on the motion dataset. The interaction module executes guidance commands based on the risk factor, resistance deviation factor, operation evaluation factor, and target distance.

2. The visualized needle knife therapy auxiliary control system for cervical spondylosis rehabilitation according to claim 1, characterized in that: The cervical spine pathological model includes multiple target areas and danger areas. The target areas are the lesion sites in the patient's cervical spine region, and the danger areas are the vascular, neural, and skeletal structures in the patient's cervical spine region.

3. The visualized needle knife therapy auxiliary control system for cervical spondylosis rehabilitation according to claim 2, characterized in that: The expression for the location data of the target area is: ,in, to They represent The outline of the target region, where the first... The expression for the contour of each target region is: ,in, to They represent the first The contours of the target regions in the fused actual cervical spine model Points.

4. The visualized needle knife therapy auxiliary control system for cervical spondylosis rehabilitation according to claim 3, characterized in that: The expression for the location data of the hazardous area is: ,in, to They represent The outline of the danger zone, of which, the first The expression for the contour of a danger zone is: ,in, to They represent the first The contours of the danger zones in the fused actual cervical spine model Points.

5. The visualized needle knife therapy auxiliary control system for cervical spondylosis rehabilitation according to claim 4, characterized in that: The expression for the motion dataset is: ,in, to This indicates that the tip of the needle knife has entered the patient's body. Motion data at a given moment, including the position of the needle tip, speed, resistance encountered, vibration frequency, and swing amplitude.

6. The visualized needle knife therapy auxiliary control system for cervical spondylosis rehabilitation according to claim 5, characterized in that: The calculation process for the risk factor is as follows: Step A1: Calculate the Euclidean distance from the tip of the needle knife to all points along the contour of the danger zone, thus creating a dataset. ,in, Indicates the distance from the tip of the needle knife to the first Real-time Euclidean distance dataset of the contours of danger zones to These represent the distances from the tip of the needle knife to the first... Outline of a danger zone Real-time Euclidean distance of each point; Step A2: Based on the dataset obtained in Step A1 The hazard factor is calculated using the following expression: in, Indicates the risk factor; Indicates the distance from the tip of the needle knife to the first Real-time Euclidean distance dataset of the contours of several danger zones; This indicates taking the minimum value; This indicates the minimum Euclidean distance between the tip of the needle knife and the outline of the danger zone. Indicates the time at which the tip of the needle knife is... speed; This indicates the set buffer time for the needle tip to reach the danger zone; and These are the weighting coefficients. .

7. The visual needle knife therapy auxiliary control system for cervical spondylosis rehabilitation according to claim 6, characterized in that: The expression for the resistance deviation coefficient is as follows: in, Indicates the resistance deviation coefficient; This indicates that the tip of the needle knife enters the patient's body at a certain time. The resistance encountered; This represents the average resistance experienced by the tip of the needle knife at all times since it entered the patient's body; This represents the standard deviation of the resistance experienced by the tip of the needle knife at all moments since it entered the patient's body. It represents the absolute value.

8. The visual needle knife therapy auxiliary control system for cervical spondylosis rehabilitation according to claim 7, characterized in that: The calculation process for the target distance is as follows: Step B1: Calculate the Euclidean distance from the tip of the needle knife to all points on the target area contour, forming a dataset. ,in, Indicates the distance from the tip of the needle knife to the first Real-time Euclidean distance dataset of target region contours to These represent the distances from the tip of the needle knife to the first... Outline of the target area Real-time Euclidean distance of each point; Step B2: Select Dataset The shortest distance in As the target distance .

9. The visualized needle knife therapy auxiliary control system for cervical spondylosis rehabilitation according to claim 8, characterized in that: The expression for the operation evaluation coefficient is as follows: in, Indicates the operational evaluation coefficient; Indicates the time at which the tip of the needle knife is... The frequency of the jitter; This indicates the vibration frequency set at the tip of the needle knife; Indicates the time at which the tip of the needle knife is... The amplitude of the swing; This indicates the set swing amplitude of the needle tip; and These are the weighting coefficients. .

10. The visualized needle knife therapy auxiliary control system for cervical spondylosis rehabilitation according to claim 9, characterized in that: The specific boot instructions are: When the risk factor Resistance deviation coefficient and operational evaluation coefficient An alert is issued when any coefficient is greater than or equal to its respective set threshold; when the risk coefficient is... Resistance deviation coefficient and operational evaluation coefficient No warning will be issued if all thresholds are less than their respective set thresholds. When the target distance When the needle tip has entered the target area, it alerts the doctor; when the target distance is... At that time, no reminder is issued.

Images