CN107808694B - System and method for judging walking ability of cerebral palsy child patient based on GMFCS - Google Patents
System and method for judging walking ability of cerebral palsy child patient based on GMFCS Download PDFInfo
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- CN107808694B CN107808694B CN201610808995.3A CN201610808995A CN107808694B CN 107808694 B CN107808694 B CN 107808694B CN 201610808995 A CN201610808995 A CN 201610808995A CN 107808694 B CN107808694 B CN 107808694B
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- A61B5/00—Measuring for diagnostic purposes; Identification of persons
- A61B5/103—Detecting, measuring or recording devices for testing the shape, pattern, colour, size or movement of the body or parts thereof, for diagnostic purposes
- A61B5/11—Measuring movement of the entire body or parts thereof, e.g. head or hand tremor, mobility of a limb
Abstract
The invention provides a system and a method for judging the walking ability of a cerebral palsy child patient based on GMFCS (Gaussian mixture model) and the method thereof, wherein the method comprises the steps that a computer receives and stores first hierarchical data input by a user; respectively acquiring a first sample entropy of a surface electromyogram signal of the left lower limb of the cerebral palsy child to be detected and a second sample entropy of the surface electromyogram signal of the right lower limb by using an electrophysiological acquisition device, and sending the first sample entropy and the second sample entropy to the computer; the computer displays a comparison result after comparing the magnitude of the first sample entropy with the magnitude of the second sample entropy; and the computer receives and stores second hierarchical data input by a user after the displayed comparison result is that the first sample entropy is smaller than the second sample entropy. According to the system and the method for judging the walking ability of the cerebral palsy child based on the GMFCS, the walking ability of the cerebral palsy child is graded by combining the GMFCS and the sample entropy of the surface electromyographic signals of the lower limbs of the cerebral palsy child, and the grading accuracy can be increased.
Description
Technical Field
The invention relates to the technical field of grading of the walking ability of children with cerebral palsy, in particular to a system and a method for judging the walking ability of children with cerebral palsy based on GMFCS.
Background
The Gross Motor Function Classification System (GMFCS) is used for classifying Gross Motor abilities of cerebral palsy patients in different age groups, and mainly classifies cerebral palsy patients of 0-12 years old into four age groups of 2 years old, 2-4 years old, 4-6 years old and 6-12 years old according to the ages, and the patients are classified into five grades of I, II, III, IV and V according to the walking abilities of the patients in each age group. Wherein, the I level represents that the walking can be carried out without limit and the walking is limited in finishing higher motor skills; level II indicates that walking is not required using an auxiliary instrument, but is limited outdoors and within communities; level III represents walking with an assisted mobile device, limited walking outdoors and within communities; the IV level indicates that the movement of the robot is limited and the robot needs to be transported or walk outdoors and in communities by using electric mobile instruments; the V level indicates that the movement itself is severely limited even in the case of using the auxiliary technology.
The signal sample entropy represents the complexity of the signal, and the larger the sample entropy value is, the more complex the signal is. For children with cerebral palsy, if the lower limb abnormal degree is more serious, the lower limb nerve muscles, joints and the like need to be matched with the limbs as much as possible to carry out walking movement in the walking process, an unusual movement mode can be shown, and the complexity of signals can be increased. In the current GMFCS (Gross motor function Classification System) rating scale, the walking ability of the patient is generally rated according to the Classification of walking ability without using any instrument and assisting walking, and the Classification of walking ability is relatively rough, for example, according to the GMFCS rating scale, the walking ability of the patient who walks quickly and normally without using any instrument and can walk independently is rated as the walking ability of the patient who walks slowly and without using any instrument, but the lower limb abnormal degree of the patient is often inconsistent, and the Classification of the conditions into the same grade is not favorable for the analysis and diagnosis of the patient's condition. Therefore, the classification against the GMFCS judgment standard cannot make a more accurate classification of the walking function of the infant patient.
Disclosure of Invention
In order to solve the above problems, the present invention provides a system and a method for judging the walking ability of a cerebral palsy infant based on GMFCS, which can increase the accuracy of classification.
The specific technical scheme provided by the invention is as follows: there is provided a method of assessing a child's walking ability of a cerebral palsy patient based on GMFCS, the method comprising:
the computer receives and stores first hierarchical data input by a user, wherein the first hierarchical data is obtained by grading the walking ability of a cerebral palsy child to be tested according to GMFCS by the user;
respectively acquiring a first sample entropy of a surface electromyogram signal of the left lower limb of the cerebral palsy child to be detected and a second sample entropy of the surface electromyogram signal of the right lower limb by using an electrophysiological acquisition device, and sending the first sample entropy and the second sample entropy to the computer;
the computer displays a comparison result after comparing the magnitude of the first sample entropy with the magnitude of the second sample entropy;
and the computer receives and stores second hierarchical data input by the user after the displayed comparison result is that the first sample entropy is smaller than the second sample entropy, wherein the second hierarchical data is obtained by grading the walking ability of the left lower limb of the cerebral palsy infant to be detected according to GMFCS by the user.
Further, when the displayed comparison result is that the entropy of the first sample is smaller than the entropy of the second sample, the grading data of the walking ability of the right lower limb of the cerebral palsy infant to be detected is first grading data.
Further, the computer receives and stores third grading data input by the user after the displayed comparison result shows that the first sample entropy is larger than the second sample entropy, wherein the third grading data is obtained by grading the walking ability of the right lower limb of the cerebral palsy infant to be tested according to GMFCS.
Further, when the displayed comparison result is that the entropy of the first sample is larger than the entropy of the second sample, the classification data of the walking ability of the left lower limb of the cerebral palsy infant to be detected is first classification data.
Further, the step of respectively acquiring the first sample entropy of the surface electromyogram signal of the left lower limb and the second sample entropy of the surface electromyogram signal of the right lower limb by the electrophysiological acquisition device includes:
collecting surface electromyographic signals of the left lower limb and the right lower limb of the cerebral palsy patient to be detected;
and calculating a first sample entropy of the surface electromyogram signal of the left lower limb of the cerebral palsy infant to be detected and a second sample entropy of the surface electromyogram signal of the right lower limb.
Further, the surface electromyographic signal is a gastrocnemius signal.
The invention also provides a system for judging the walking ability of the cerebral palsy infant based on the GMFCS, which comprises a computer and electrophysiological acquisition equipment, wherein the computer comprises a storage module, a comparison module and a display module; the storage module is used for receiving and storing first grading data input by a user, wherein the first grading data is obtained by grading the walking ability of a cerebral palsy infant to be tested according to GMFCS; the electrophysiological acquisition equipment is used for respectively acquiring a first sample entropy of a surface electromyogram signal of the left lower limb of the cerebral palsy infant to be detected and a second sample entropy of the surface electromyogram signal of the right lower limb, and sending the first sample entropy and the second sample entropy to the comparison module; the comparison module is used for sending a comparison result to the display module for displaying after comparing the first sample entropy with the second sample entropy; the storage module is further used for receiving and storing second hierarchical data input by a user after the displayed comparison result is that the first sample entropy is smaller than the second sample entropy, and the second hierarchical data is obtained by grading the walking ability of the left lower limb of the cerebral palsy infant to be detected according to GMFCS.
Further, the storage module is further configured to receive and store third grading data input by the user after the displayed comparison result is that the first sample entropy is larger than the second sample entropy, where the third grading data is obtained by grading, according to GMFCS, the walking ability of the right lower limb of the cerebral palsy infant to be tested.
Further, the electrophysiological acquisition device includes: the signal acquisition unit is used for acquiring surface electromyographic signals of the left lower limb and the right lower limb of the cerebral palsy infant to be detected; and the calculating unit is used for calculating a first sample entropy of the surface electromyogram signal of the left lower limb of the cerebral palsy infant to be detected and a second sample entropy of the surface electromyogram signal of the right lower limb of the cerebral palsy infant to be detected.
According to the system and the method for judging the walking ability of the cerebral palsy infant based on the GMFCS, after the walking ability of the lower limbs of the cerebral palsy infant is graded according to the GMFCS, whether a first sample entropy of a surface electromyogram signal of the left lower limb of the cerebral palsy infant is equal to a second sample entropy of a surface electromyogram signal of the right lower limb is judged, and when the first sample entropy is not equal to the second sample entropy, the walking ability of the left lower limb or the walking ability of the right lower limb of the cerebral palsy infant is graded according to the GMFCS again, so that the walking ability of the cerebral palsy infant is graded by combining the GMFCS with the sample entropy of the surface electromyogram signal of the lower limb of the cerebral palsy infant, and the grading accuracy is increased.
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The above and other aspects, features and advantages of embodiments of the present invention will become more apparent from the following description taken in conjunction with the accompanying drawings, in which:
FIG. 1 is a flow chart of a method for assessing the walking ability of a cerebral palsy patient based on GMFCS;
fig. 2 is a block diagram of a system for determining the walking ability of a cerebral palsy patient based on GMFCS.
Detailed Description
Hereinafter, embodiments of the present invention will be described in detail with reference to the accompanying drawings. This invention may, however, be embodied in many different forms and should not be construed as limited to the specific embodiments set forth herein. Rather, these embodiments are provided to explain the principles of the invention and its practical application to thereby enable others skilled in the art to understand the invention for various embodiments and with various modifications as are suited to the particular use contemplated.
Referring to fig. 1, the method for judging the walking ability of a cerebral palsy patient based on GMFCS provided in this embodiment includes:
the computer receives and stores first hierarchical data input by a user, wherein the first hierarchical data is obtained by grading the walking ability of a cerebral palsy child to be tested according to GMFCS by the user;
the method comprises the steps that electrophysiological acquisition equipment respectively acquires a first sample entropy of a surface electromyogram signal of a left lower limb of a cerebral palsy child to be detected and a second sample entropy of a surface electromyogram signal of a right lower limb, and sends the first sample entropy and the second sample entropy to a computer;
the computer displays the comparison result after comparing the first sample entropy with the second sample entropy;
and the computer receives and stores second grading data input by the user after the displayed comparison result is that the first sample entropy is smaller than the second sample entropy, and the second grading data is obtained by grading the walking ability of the left lower limb of the cerebral palsy infant to be tested according to the GMFCS by the user.
Specifically, the method for grading the walking ability of the cerebral palsy infant patient based on GMFCS provided in this embodiment includes the following steps:
s1, receiving and storing first hierarchical data input by a user through a computer, wherein the first hierarchical data is obtained by grading the walking ability of a cerebral palsy child to be tested according to GMFCS.
The step S1 specifically includes that the user divides the walking ability of the cerebral palsy infant to be tested into a grade I, a grade II, a grade III, a grade IV or a grade V according to the GMFCS within an age group corresponding to the age of the cerebral palsy infant to be tested. For example, the cerebral palsy patient to be tested can walk without limitation, and the walking ability of the cerebral palsy patient is divided into I level if the cerebral palsy patient is limited to finish higher motor skills; the cerebral palsy patient needs no auxiliary equipment for walking, but walking is limited outdoors and in communities, and the walking ability of the cerebral palsy patient is divided into II grades; the cerebral palsy patient to be detected walks by using an auxiliary mobile instrument, and the walking ability of the cerebral palsy patient is divided into III grade if the walking is limited outdoors and in communities; the cerebral palsy patient child to be detected is limited in self movement and needs to be transported or walk outdoors and in communities by using an electric moving device, and then the walking ability of the cerebral palsy patient child is divided into IV grade; the cerebral palsy patient to be tested is still severely limited in self movement even under the condition of using an auxiliary technology, and the walking ability of the cerebral palsy patient to be tested is divided into V levels. After the user obtains the level of the walking ability of the cerebral palsy child to be tested, namely the first hierarchical data, the first hierarchical data is input into the computer, and the computer receives and stores the first hierarchical data.
S2, the electrophysiological acquisition equipment respectively acquires a first sample entropy of a surface electromyogram signal of the left lower limb of the cerebral palsy infant to be detected and a second sample entropy of the surface electromyogram signal of the right lower limb, and sends the first sample entropy and the second sample entropy to a computer, wherein the S2 specifically comprises the following steps:
s21, collecting surface electromyographic signals of the left lower limb and the right lower limb of the cerebral palsy patient to be detected;
s22, calculating a first sample entropy of the surface electromyogram signal of the left lower limb of the cerebral palsy infant to be detected and a second sample entropy of the surface electromyogram signal of the right lower limb.
And S3, the computer displays a comparison result after comparing the first sample entropy with the second sample entropy.
Specifically, the comparison result may be represented by a comparison flag, for example, when the entropy of the first sample is equal to the entropy of the second sample, the comparison flag is 0, and the computer displays 0; when the first sample entropy is larger than the second sample entropy, the comparison flag bit is 1, and the computer displays 1; when the first sample entropy is smaller than the second sample entropy, the comparison flag bit is 2, the computer displays 2, and a user can know the magnitude of the first sample entropy and the magnitude of the second sample entropy according to the magnitude of data displayed by the computer.
And S4, receiving and storing second grading data input by the user after the displayed comparison result is that the first sample entropy is smaller than the second sample entropy, wherein the second grading data is obtained by grading the walking ability of the left lower limb of the cerebral palsy infant to be tested according to GMFCS.
Specifically, in step S4, if the comparison result displayed by the computer is that the first sample entropy is smaller than the second sample entropy, the user needs to re-grade the walking ability of the left lower limb of the cerebral palsy infant to be tested to obtain second grade data, the specific process is similar to that in step S1, and details are not repeated here, and the grade data of the walking ability of the right lower limb of the cerebral palsy infant to be tested is the first grade data. If the comparison result displayed by the computer is that the first sample entropy is larger than the second sample entropy, the user needs to re-grade the walking ability of the right lower limb of the cerebral palsy infant to be detected to obtain third grade data, the specific process is similar to the step S1, which is not repeated here, and the grade data of the walking ability of the left lower limb of the cerebral palsy infant to be detected is the first grade data. For example, in step S1, the first classification data is class II, and when the first sample entropy is smaller than the second sample entropy, the classification data of the walking ability of the right lower limb of the cerebral palsy infant to be tested is class II; the user reclassifies the walking ability of the left lower limb of the cerebral palsy infant to be detected according to the GMFCS; when the first sample entropy is larger than the second sample entropy, the classification data of the walking ability of the left lower limb of the cerebral palsy infant to be detected is II grade; and the user reclassifies the walking ability of the right lower limb of the cerebral palsy infant to be detected according to the GMFCS.
In addition, in step S4, if the comparison result displayed by the computer is that the first sample entropy is equal to the second sample entropy, it is not necessary to classify the walking ability of the left or right lower limb of the cerebral palsy infant to be tested again, and at this time, the classification data of the walking ability of the left or right lower limb of the cerebral palsy infant to be tested are respectively the same as the first classification data.
Referring to fig. 2, the embodiment further provides a system for judging the walking ability of a cerebral palsy child patient based on GMFCS, and the system includes a computer 1 and an electrophysiological acquisition device 2. The computer 1 comprises a memory module 11, a comparison module 12 and a display module 13.
Specifically, the storage module 11 is configured to receive and store first grading data input by a user, where the first grading data is obtained by grading, according to the GMFCS, the walking ability of a cerebral palsy infant to be tested. The electrophysiological acquisition device 2 is configured to obtain a first sample entropy of a surface electromyogram signal of a left lower limb of the cerebral palsy infant to be detected and a second sample entropy of the surface electromyogram signal of a right lower limb, and send the first sample entropy and the second sample entropy to the comparison module 12. The comparison module 12 is configured to send the comparison result to the display module 13 for display after comparing the magnitudes of the first sample entropy and the second sample entropy. The storage module 11 is further configured to receive and store second hierarchical data input by the user after the displayed comparison result is that the first sample entropy is smaller than the second sample entropy, and to receive and store third hierarchical data input by the user after the displayed comparison result is that the first sample entropy is larger than the second sample entropy, where the second hierarchical data is obtained by classifying, according to GMFCS, the walking ability of the left lower limb of the cerebral palsy infant to be detected, and the third hierarchical data is obtained by classifying, according to GMFCS, the walking ability of the right lower limb of the cerebral palsy infant to be detected.
The electrophysiological acquisition device 2 comprises a signal acquisition unit 21 and a calculation unit 22, wherein the signal acquisition unit 21 is used for acquiring a surface electromyogram signal of a left lower limb and a surface electromyogram signal of a right lower limb of a cerebral palsy infant to be detected, and the calculation unit 22 is used for calculating a first sample entropy of the surface electromyogram signal of the left lower limb and a second sample entropy of the surface electromyogram signal of the right lower limb of the cerebral palsy infant to be detected.
The foregoing is directed to embodiments of the present application and it is noted that numerous modifications and adaptations may be made by those skilled in the art without departing from the principles of the present application and are intended to be within the scope of the present application.
Claims (5)
1. A method for assessing the walking ability of a cerebral palsy patient based on GMFCS, the method comprising:
the computer receives and stores first hierarchical data input by a user, wherein the first hierarchical data is obtained by grading the walking ability of a cerebral palsy child to be tested according to GMFCS by the user;
respectively acquiring a first sample entropy of a surface electromyogram signal of the left lower limb of the cerebral palsy child to be detected and a second sample entropy of the surface electromyogram signal of the right lower limb by using an electrophysiological acquisition device, and sending the first sample entropy and the second sample entropy to the computer;
the computer displays a comparison result after comparing the magnitude of the first sample entropy with the magnitude of the second sample entropy;
the computer receives and stores second hierarchical data input by a user after the displayed comparison result is that the first sample entropy is smaller than the second sample entropy, wherein the second hierarchical data is obtained by grading the walking ability of the left lower limb of the cerebral palsy infant to be detected according to GMFCS by the user;
when the displayed comparison result is that the entropy of the first sample is smaller than the entropy of the second sample, the grading data of the walking ability of the right lower limb of the cerebral palsy infant to be detected are first grading data;
the computer receives and stores third grading data input by a user after the displayed comparison result is that the first sample entropy is larger than the second sample entropy, wherein the third grading data is obtained by grading the walking ability of the right lower limb of the cerebral palsy child to be detected according to GMFCS by the user;
and when the displayed comparison result of the computer is that the first sample entropy is larger than the second sample entropy, the grading data of the walking ability of the left lower limb of the cerebral palsy infant to be detected is first grading data.
2. The method for judging the walking ability of the cerebral palsy infant based on the GMFCS of claim 1, wherein the respectively obtaining the first sample entropy of the surface electromyographic signal of the left lower limb and the second sample entropy of the surface electromyographic signal of the right lower limb of the cerebral palsy infant to be detected by the electrophysiological collection device comprises:
collecting surface electromyographic signals of the left lower limb and the right lower limb of the cerebral palsy patient to be detected;
and calculating a first sample entropy of the surface electromyogram signal of the left lower limb of the cerebral palsy infant to be detected and a second sample entropy of the surface electromyogram signal of the right lower limb.
3. Method for judging the walking ability of a cerebral palsy infant based on GMFCS according to claim 1 or 2, characterized in that the surface electromyographic signal is the gastrocnemius signal.
4. A system for judging the walking ability of a cerebral palsy child patient based on GMFCS is characterized by comprising a computer and electrophysiological acquisition equipment, wherein the computer comprises a storage module, a comparison module and a display module;
the storage module is used for receiving and storing first grading data input by a user, wherein the first grading data is obtained by grading the walking ability of a cerebral palsy child to be tested according to GMFCS by the user;
the electrophysiological acquisition equipment is used for respectively acquiring a first sample entropy of a surface electromyogram signal of the left lower limb of the cerebral palsy infant to be detected and a second sample entropy of a surface electromyogram signal of the right lower limb of the cerebral palsy infant to be detected, and sending the first sample entropy and the second sample entropy to the comparison module;
the comparison module is used for sending a comparison result to the display module for displaying after comparing the first sample entropy with the second sample entropy;
the storage module is further used for receiving and storing second hierarchical data input by a user after the displayed comparison result is that the first sample entropy is smaller than the second sample entropy, wherein the second hierarchical data is obtained by grading the walking ability of the left lower limb of the cerebral palsy infant to be detected according to GMFCS by the user; when the displayed comparison result is that the first sample entropy is smaller than the second sample entropy, the grading data of the walking ability of the right lower limb of the cerebral palsy infant to be detected is first grading data;
the storage module is further used for receiving and storing third grading data input by a user after the displayed comparison result is that the first sample entropy is larger than the second sample entropy, wherein the third grading data is obtained by grading the walking ability of the right lower limb of the cerebral palsy infant to be detected according to GMFCS by the user; and when the displayed comparison result is that the first sample entropy is larger than the second sample entropy, the grading data of the walking ability of the left lower limb of the cerebral palsy infant to be detected is first grading data.
5. The system for assessing walking ability of a child suffering from cerebral palsy based on GMFCS of claim 4, wherein the electrophysiology collection apparatus comprises:
the signal acquisition unit is used for acquiring surface electromyographic signals of the left lower limb and the right lower limb of the cerebral palsy infant to be detected;
and the computing unit is used for computing a first sample entropy of the surface electromyogram signal of the left lower limb of the cerebral palsy infant to be tested and a second sample entropy of the surface electromyogram signal of the right lower limb.
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| CN113101134B (en) * | 2021-04-02 | 2023-11-28 | 上海交通大学医学院附属新华医院 | Child lower limb movement auxiliary rehabilitation system based on power exoskeleton |
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