Method for analyzing scoliosis

Abstract

The application discloses a kind of scoliosis analysis auxiliary methods, comprising the following steps: 1) the CT data of patient spine is imported into fusion ultrasound, and the segment of patient spinous process is positioned using ultrasound and is marked;2) under the fusion of CT data, the ultrasound measurement of patient muscle form is carried out, and the three-dimensional skeletal muscle digital model of patient is established and is displayed through screen;3) the surface electromyogram of patient is collected, and the analysis and judgment result of surface electromyogram is superimposed and displayed to the three-dimensional skeletal muscle model that has been established;4) collection is completed, and display analysis report.The scoliosis analysis auxiliary method of the application can provide assistance when doctor carries out scoliosis analysis diagnosis, display the three-dimensional skeletal muscle digital model of patient to doctor, superimposed and display the analysis and judgment result of surface electromyogram collected when patient is tested in multiple positions, and display analysis report, which can improve the accuracy and efficiency of doctor scoliosis analysis diagnosis.

Description

TECHNICAL FIELD

[0001] The present application relates to a scoliosis analysis auxiliary method. BACKGROUND

[0002] Scoliosis, also known as scoliosis, is a primary or secondary disease with three-dimensional changes in the skeletal structure of the spine. The spine of a scoliosis patient will show three-dimensional changes of lateral bending, rotation, and anterior-posterior convexity of each segment. Scoliosis is divided into different types according to the early or late onset of the disease, the cause of the disease, and the characteristics of the spinal structural changes. Primary or secondary neuromuscular diseases, primary and lower limb skeletal deformities, may all have scoliosis symptoms. The most common one is adolescent idiopathic scoliosis (AIS), which usually occurs before puberty, and the cause is unknown. Current research suggests that the involvement of the spine in this disease may be related to neuromuscular control. Secondary scoliosis includes skeletal deformities, Parkinson's disease, cerebral palsy, etc.; in these diseases, the nerves, muscles, or bones that maintain the stability of the spine have undergone certain pathological changes, ultimately leading to spinal deformation. Therefore, whether it is primary scoliosis or secondary scoliosis, analyzing neuromuscular problems is the need for functional assessment and precise treatment of such patients.

[0003] If an auxiliary can be provided when a doctor analyzes and diagnoses scoliosis, a three-dimensional skeletal muscle digital model of the patient is displayed to the doctor, the analysis and judgment results of the surface electromyography signals collected by the patient in multiple body positions are superimposed and displayed, and an analysis report is displayed, the accuracy and efficiency of the doctor's scoliosis analysis and diagnosis can be improved. SUMMARY

[0004] In order to assist doctors in analyzing and diagnosing scoliosis, the present application provides a scoliosis analysis auxiliary method, comprising the following steps:

[0005] 1) Import the CT data of the patient's spine into the fusion ultrasound, use ultrasound to locate the patient's spinous process segment and mark it;

[0006] 2) Under the fusion of CT data, perform ultrasound measurement of the patient's muscle morphology, establish a three-dimensional skeletal muscle digital model of the patient and display it on the screen;

[0007] 3) Collect the surface electromyography signals of the patient:

[0008] The collection points include: 2cm away from the midline on both sides of the T2 spinous process plane, 2cm and 4cm away from the midline on both sides of the T7 spinous process plane, 2cm and 4cm away from the midline on both sides of the T12 spinous process plane, 2cm and 4cm away from the midline on both sides of the L3 spinous process plane, and the midpoint of the vertical distance between the anterior superior iliac spine and the rib;

[0009] Make the patient in multiple body positions for test collection: first, when the patient is in a static prone position, a left flexion prone position, and a right flexion prone position, collect the surface electromyogram of the patient in a relaxed state; then, when the patient is in a prone position, collect the surface electromyogram of the patient in a prone position, collect the surface electromyogram of the patient in a prone position, and collect the surface electromyogram of the patient in a prone position;

[0010] The collected surface electromyogram is analyzed by a neural network calculation to determine the surface electromyogram connection, signal strength, data quality, and number of repeated measurements; the analysis result of the surface electromyogram is dynamically and real-time superimposed on the established three-dimensional skeletal muscle model by color depth, and can be adjusted to observe stereoscopically;

[0011] 4) After the collection is completed, the analysis report is displayed:

[0012] The analysis report includes the following contents obtained by neural network calculation: real-time information of the electromyogram during the test collection, electromyogram network analysis report after the test collection, two or more difference analysis reports, and responsibility muscle tracing report of scoliosis.

[0013] Preferably, in step 3), the collection points further include: 2cm and 5cm from the midline of the T1 to L3 spinous process plane.

[0014] Preferably, the surface electromyogram of the patient is collected by a wireless surface electromyogram sensor.

[0015] Preferably, the wireless surface electromyogram sensor is pre-set on the electromyogram collection vest, and the patient wears the electromyogram collection vest to collect the surface electromyogram.

[0016] Preferably, before collecting the surface electromyogram of the patient, the skin at the collection point of the patient is first coated with a scrub cream and cleaned with anhydrous alcohol.

[0017] The advantages and beneficial effects of the present application are that a scoliosis analysis auxiliary method is provided, which can assist doctors in scoliosis analysis and diagnosis, display a three-dimensional skeletal muscle digital model of the patient to the doctor, superimpose the analysis and judgment results of the collected surface electromyogram of the patient in multiple body positions for testing, and display the analysis report, which can improve the accuracy and efficiency of the doctor's scoliosis analysis and diagnosis. BRIEF DESCRIPTION OF DRAWINGS

[0018] Figure 1 is a schematic diagram of the patient in multiple body positions for test collection; Figure 1 In the figure, 1 represents the first collection position, i.e. a static prone position, the upper body of which can be inclined to the left, centered, or right, and the position of the head has a breathing port; 2 represents the second collection position, i.e. a prone position like a flying swallow; 3 represents the third collection position, i.e. a semi-recumbent position for abdominal curling;

[0019] Figure 2 It is an indicator and algorithm for tracing the responsible muscles in scoliosis. Detailed Implementation

[0020] The specific embodiments of the present invention will be further described below with reference to the accompanying drawings and examples. The following examples are only used to more clearly illustrate the technical solutions of the present invention and should not be construed as limiting the scope of protection of the present invention.

[0021] This invention provides an auxiliary method for scoliosis analysis, comprising the following steps:

[0022] 1) Import the patient's spinal CT data into fusion ultrasound, and use ultrasound to locate and mark the patient's spinous process segments;

[0023] 2) With CT data fusion, perform ultrasound measurements of the patient's muscle morphology, establish a three-dimensional skeletal muscle digital model of the patient, and display it on the screen;

[0024] 3) Collect surface electromyography signals from the patient:

[0025] The patient's surface electromyography (EMG) signals were collected using a wireless surface EMG sensor. The collection points included: 2 cm to the sides of the midline of the T2 spinous process plane, 2 cm and 4 cm to the sides of the midline of the T7 spinous process plane, 2 cm and 4 cm to the sides of the midline of the T12 spinous process plane, 2 cm and 4 cm to the sides of the midline of the L3 spinous process plane, the midpoint of the vertical distance between the anterior superior iliac spine and the rib, and 2 cm and 5 cm to the sides of the midline of the T1 to L3 spinous process planes.

[0026] Before collection, apply a scrub to the patient's skin at the collection point and clean it with anhydrous alcohol;

[0027] like Figure 1 As shown, the patient was placed in multiple positions for testing and data collection: first, when the patient was in a static prone position, a left flexed prone position, and a right flexed prone position, electromyographic signals were collected from the patient at a quiet and relaxed position; then, when the patient was in a prone position with head up and a supine position with abdominal crunches, surface electromyographic signals were collected from the patient's abdominal muscles and back at the collection points, respectively.

[0028] The collected surface electromyography (EMG) signals are analyzed using neural network calculations to determine the surface EMG connectivity, signal strength, data quality, and number of repeated measurements. The analysis results of the surface EMG signals are dynamically and in real-time superimposed onto the established three-dimensional skeletal muscle model using color depth, and the viewing angle can be adjusted for stereoscopic observation.

[0029] 4) Data collection complete, analysis report displayed:

[0030] The analysis report includes the following contents obtained by neural network calculation analysis: real-time information of the electromyogram during the test acquisition process, the electromyogram network analysis report after the test acquisition is completed, the twice or more difference analysis report, and the scoliosis responsible muscle tracing report;

[0031] The index and algorithm of the scoliosis responsible muscle tracing are shown in the following table. Figure 2

[0032] The present application can provide assistance to doctors when performing scoliosis analysis and diagnosis, display a three-dimensional skeletal muscle digital model of the patient to the doctor, superimpose the analysis and judgment results of the surface electromyogram signals collected when the patient is tested in multiple body positions, and display the analysis report, which can improve the accuracy and efficiency of the doctor's scoliosis analysis and diagnosis.

[0033] More specifically, the present application also provides a method for collecting electromyogram signals of paravertebral muscles on both sides of the spine, which uses a horizontal bar with a wireless surface electromyogram sensor and a vest with a horizontal bar.

[0034] The vest includes a front part and a back part, and the back part is provided with a hollow area that can expose the spine area of the patient's back, and the hollow area is a vertically arranged rectangle.

[0035] The middle part of the horizontal bar is provided with a hollow positioning point for aligning with the spine segment of the patient, and the hollow positioning point is circular.

[0036] The front surface of the horizontal bar is provided with two magic tape heads at both ends, respectively.

[0037] The front surface of the horizontal bar is provided with two magic tape heads at both ends, respectively.

[0038] The method for collecting electromyogram signals of paravertebral muscles on both sides of the spine includes the following steps:

[0039] ​The number of the transverse strips to be used is determined according to the number of the spine segments to be collected, and one transverse strip is used for each spine segment; the symmetrical mounting positions on the transverse strip are selected according to the examination positions of the paravertebral muscles on both sides of the spine segment, that is, a pair of symmetrical mounting positions with a distance of 2 cm from the hollow positioning points are selected, or a pair of symmetrical mounting positions with a distance of 4 cm from the hollow positioning points are selected; then the wireless surface electromyography sensors are respectively fixed and mounted on the symmetrical mounting positions on both sides of the hollow positioning points;

[0040] Then, the transverse strips are sequentially mounted from top to bottom or from bottom to top according to the upper and lower positions of the spine segments to be collected; before the transverse strips are mounted, the skin on the back of the patient is first coated with a scrub cream and cleaned with anhydrous alcohol; when the transverse strips are mounted: the transverse strip is placed horizontally, the front surface of the transverse strip faces the back of the patient, and the hollow positioning points of the transverse strip are aligned with the corresponding spine segments; then the magic tape heads on both ends of the transverse strip are respectively adhered and fixed on the magic tape pieces on the outer side of the back of the vest; at this time, the wireless surface electromyography sensors on the symmetrical mounting positions of the transverse strip are respectively attached to the back of the patient, and the wireless surface electromyography sensors on the symmetrical mounting positions correspond to the paravertebral muscles on both sides of the corresponding spine segments one by one;

[0041] Then, the electromyography signals of the corresponding paravertebral muscles are collected through the wireless surface electromyography sensors;

[0042] After the electromyography signals are collected, the transverse strip is removed from the outer side of the back of the vest, the lower extension strip on the back of the vest is disengaged from the outer side of the front of the vest, and the vest is removed from the patient.

[0043] The collection method of the electromyography signals of the paravertebral muscles on both sides of the spine provided by the application adopts the transverse strip on which the wireless surface electromyography sensors can be mounted and the vest on which the transverse strip can be positioned, so that the wireless surface electromyography sensors can be easily mounted and positioned, and the electromyography signals of the paravertebral muscles on both sides of the spine of the patient can be easily collected.

[0044] The above only describes the preferred embodiments of the application, and it should be noted that those skilled in the art can make some improvements and refinements without departing from the technical principles of the application, and these improvements and refinements should also be considered as the protection scope of the application.

Claims

1. An auxiliary method for scoliosis analysis, characterized in that, Includes the following steps: 1) Import the patient's spinal CT data into fusion ultrasound, and use ultrasound to locate and mark the patient's spinous process segments; 2) With CT data fusion, perform ultrasound measurements of the patient's muscle morphology, establish a three-dimensional skeletal muscle digital model of the patient, and display it on the screen; 3) Collect surface electromyography signals from the patient: The patient's surface electromyography (EMG) signals were collected using a wireless surface EMG sensor. The collection points included: 2 cm to the sides of the midline of the T2 spinous process plane, 2 cm and 4 cm to the sides of the midline of the T7 spinous process plane, 2 cm and 4 cm to the sides of the midline of the T12 spinous process plane, 2 cm and 4 cm to the sides of the midline of the L3 spinous process plane, the midpoint of the vertical distance between the anterior superior iliac spine and the rib, and 2 cm and 5 cm to the sides of the midline of the T1 to L3 spinous process planes. The patient was placed in multiple positions for testing and data collection: first, when the patient was in a static prone position, a left flexed prone position, and a right flexed prone position, electromyographic signals were collected from the patient at a quiet and relaxed position; then, when the patient was in a prone position with head up and a supine position with abdominal crunches, surface electromyographic signals were collected from the patient's abdominal muscles and back at the collection points, respectively. The collected surface electromyography (EMG) signals are analyzed using neural network calculations to determine the surface EMG connectivity, signal strength, data quality, and number of repeated measurements. The analysis results of the surface EMG signals are dynamically and in real-time superimposed onto the established three-dimensional skeletal muscle model using color depth, and the viewing angle can be adjusted for stereoscopic observation. 4) Data collection complete, analysis report displayed: The analysis report includes the following information obtained through neural network calculation and analysis: real-time electromyography information during the test acquisition process, electromyography network analysis report after the test acquisition is completed, difference analysis report of two or more tests, and tracing report of the responsible muscle for scoliosis. Specifically, in step 3): Data collection is performed using a strip and a vest on which a wireless surface electromyography (SEMG) sensor can be installed. The back of the vest has a hollowed-out area that exposes the patient's spine. The hollowed-out area is a vertical rectangle. The middle of the strip has a hollowed-out positioning point for alignment with the patient's spinal segment. The hollowed-out positioning point is circular. On the front of the strip, there are mounting positions for installing the wireless SEMG sensor on both sides of the hollowed-out positioning point. The outer side of the back of the vest is covered with Velcro patches that can be attached to the Velcro heads at both ends of the front of the strip.

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