CN112932445A - Child cerebral palsy and cranial nerve injury assessment instrument based on big data and use method thereof - Google Patents
Child cerebral palsy and cranial nerve injury assessment instrument based on big data and use method thereof Download PDFInfo
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Abstract
The invention discloses a child cerebral palsy cranial nerve injury assessment instrument based on big data, which comprises special earphones worn on two ears of a child suffering from cerebral palsy, wherein each special earphone comprises a transmitter and a receiver, the special earphones are electrically connected with a processor, and the processor is connected with a medical analysis system and a big data system. The method is simple, can stimulate the neurons to generate chemical electric signals, the chemical electric signals are transmitted to organ tissue cells of the whole body through the neurons to cause resonance, and the disease state and degree of the human body cell level are judged after analysis, so that the method has a better monitoring effect on the cerebral nerve injury of children with cerebral palsy.
Description
Technical Field
The invention relates to the technical field of medical equipment, in particular to a child cerebral palsy and cranial nerve injury assessment instrument based on big data and a using method thereof.
Background
The infantile cerebral palsy is also called infantile cerebral palsy, commonly called cerebral palsy. It is a syndrome in which the brain development is not yet in a mature stage within one month after birth, and various motor dysfunctions in different postures are mainly caused by non-progressive brain injury. Is the common central nervous system disorder syndrome in children, the pathological changes are in the brain and affect the four limbs, and the symptoms of intellectual deficit, epilepsy, abnormal behaviors, mental disorder, visual disturbance, auditory disturbance, language disturbance and the like are often accompanied.
The existing assessment instrument for treating children cerebral palsy is complex in equipment composition and expensive in price, and meanwhile, the existing diagnosis instrument is not obvious in effect and high in cost for analyzing, predicting and discovering the children cerebral palsy symptoms.
Disclosure of Invention
The invention aims to solve the defects in the prior art, and provides a child cerebral palsy cranial nerve injury assessment instrument based on big data and a using method thereof.
In order to achieve the purpose, the invention adopts the following technical scheme:
the child cerebral palsy cranial nerve injury assessment instrument based on big data and the use method thereof comprise a special earphone worn on the ears of a child suffering from cerebral palsy, wherein the special earphone comprises a transmitter and a receiver;
the special earphone is electrically connected with the processor;
the processor is connected with a medical analysis system and a big data system;
the big data system comprises a cerebral palsy infant data collection module, a cerebral palsy infant database establishment module and a cerebral palsy infant database processing module;
the monitor also includes a memory.
Preferably, the processor executes an analysis program stored in the memory, comprising the steps of:
a. establishing a cerebral palsy infant pathological model, and acquiring various physiological signals of an infant through an analyzer, wherein the physiological signals comprise height, weight, body temperature, in-vivo hormone level, diet level of the infant, body activity of the infant and response time to various stimuli to obtain input parameters;
b. the model comprises four factors for inducing cerebral palsy of children, wherein the first factor is a prenatal factor; the second is a perinatal factor; the third is a factor in the neonatal period; the fourth is a genetic factor;
c. inputting parameters based on a child cerebral palsy pathological model, uploading the parameters to a unified server, performing initial state evaluation on the full-automatic biochemical analyzer by utilizing unilateral characteristic quantity, judging whether the full-automatic biochemical analyzer fails or normally operates, establishing a characteristic density estimation model by utilizing an anomaly detection algorithm, and testing whether the characteristic probability density distribution of equipment is abnormal;
d. establishing a mental model of cerebral palsy of children, analyzing the collected pathologic models of cerebral palsy children and dividing the pathologic models into 5 types according to different degrees of severity: spastic cerebral palsy, bradycerebral palsy, mixed cerebral palsy, ataxia cerebral palsy, and ankylosing cerebral palsy.
Preferably, the spastic cerebral palsy refers to movement and posture disorder caused by non-progressive injury due to incomplete development of the immature brain due to various causes;
the bradykinesia type cerebral palsy refers to dyskinesia or dyskinesia caused by injury in a brain-based region;
the mixed cerebral palsy refers to a syndrome which is mainly caused by various motor dysfunctions in postures due to non-progressive brain injury in a brain immature stage in postnatal one month;
the ataxia cerebral palsy refers to a type of damaged cerebellum accompanied by repeated lesions of the pyramidal system, extrapyramidal system and deep sensory system;
the strong and straight cerebral palsy refers to cerebral palsy caused by injury of an extrapyramidal system.
The invention also provides a child cerebral palsy cranial nerve injury assessment instrument based on big data and a using method thereof, wherein the assessment instrument comprises the following steps:
s1, when in detection, a patient to be detected wears a special earphone, electromagnetic waves are emitted by the left earmuff and reach the cerebral cortex, an external magnetic field is generated through electromagnetic resonance, the magnetic field acts on neurons, the neurons are stimulated to generate chemical electric signals, the chemical electric signals are transmitted to organ tissue cells of the whole body through the neurons to cause resonance, the electromagnetic field formed by the cell resonance generates electromagnetic signals, and the signals are captured by the right earmuff in diffusion amplification;
s2, separating and decoding the captured cell resonance electromagnetic signals through a processor, converting the separated and decoded cell resonance electromagnetic signals into frequency spectrums, comparing the detected cell frequency spectrums with reference frequency spectrums, wherein the reference frequency spectrums are derived from a standard cell database of fifteen million people, analyzing the state and the variation trend by comparing the similarity of the frequency spectrums and the frequency spectrum combination, converting the frequency spectrum difference values into statistical values, making clinical definition aiming at the disease state and the pathological change trend according to the statistical analysis result, and automatically completing signal translation and clinical definition through the processor and matched software, thereby improving the efficiency to the maximum extent and reducing the information loss and errors;
s3, networking the detection terminal and the central database, synchronously updating the detected cell molecular spectrum data and the case data obtained by statistical analysis in real time, storing information and performing cooperative operation through intelligent software along with case accumulation and database expansion, continuously correcting judgment parameters, and continuously optimizing and perfecting a mathematical model to realize more accurate diagnosis and prediction.
The invention has the beneficial effects that:
1. in the data acquisition process, the infant to be detected does not need to have an empty stomach, does not need drug intervention, does not have any radiation, and can finish the data acquisition only in 5 to 10 minutes.
2. Based on big data, the organism physiological data of different cerebral palsy children are collected and processed to be converted into data which can be mined, the collected data are judged by the illness state severity of the children through the logical operation of the mathematical model, and pathological monitoring is made according to the development track of cells in the mathematical model, so that important reference is provided for the subsequent treatment of the cerebral palsy, the monitoring and understanding of the screening conditions of a large number of cerebral palsy children are facilitated, and the whole treatment scheme of the cerebral palsy related diseases of the children is made in time.
3. Electromagnetic waves emitted by a special earphone reach the cerebral cortex, an external magnetic field is generated through electromagnetic resonance, the magnetic field acts on neurons, the neurons are stimulated to generate chemical electric signals, the chemical electric signals are transmitted to organ tissue cells of the whole body through the neurons to cause resonance, the electromagnetic field formed by cell resonance generates electromagnetic signals, the signals are captured by a right earmuff in diffusion amplification, and the disease state and degree of a human body cell layer are judged after analysis so as to count significance and predict the significance of clinical features.
5. The deep induction and summary are carried out, the data of the cerebral palsy infant are collected, a cerebral palsy infant database is established, the database of the cerebral palsy infant is subjected to big data analysis and statistics, the relation data of different pathogenic factors and cerebral palsy is obtained, scientific reference basis is provided for screening the cerebral palsy infant at the early stage, scientific basis is provided for making relevant diagnosis and maintenance strategies, the diagnosis is facilitated for operators, the manpower maintenance cost can be effectively reduced, and the application prospect is good.
Drawings
FIG. 1 is a system block diagram of a child cerebral palsy cranial nerve injury assessment instrument based on big data according to the present invention;
FIG. 2 is a medical logic progression diagram of cerebral palsy of a child;
fig. 3 is a working flow chart of the child cerebral palsy cranial nerve injury assessment instrument based on big data according to the present invention.
Detailed Description
The technical scheme of the invention is further explained by the specific implementation mode in combination with the attached drawings.
As shown in fig. 1, the child cerebral palsy cranial nerve injury assessment instrument based on big data comprises special earphones worn on two ears of a cerebral palsy child, wherein each special earphone comprises a transmitter and a receiver, the special earphones are electrically connected with a processor, the processor is connected with a medical analysis system and a big data system, the big data system comprises a cerebral palsy child data collection module, a cerebral palsy child database establishment module and a cerebral palsy child database processing module, the monitor further comprises a memory, and the processor executes an analysis program stored in the memory.
As shown in fig. 2, it is a medical logic progression diagram of children cerebral palsy, and thousands of children cerebral palsy cases use statistical software to perform correlation analysis on each index data, and the research of children cerebral palsy medicine is integrated to obtain the research of children cerebral palsy: the research finds that four factors are mainly used for inducing the cerebral palsy of children, wherein the first factor is a prenatal factor, the second factor is a perinatal factor, the third factor is a neonatal factor, and the fourth factor is a genetic factor; the first prenatal factor, the quality of the pregnant embryo is easily affected when the mother is pregnant, the embryo quality is affected by smoking and drinking of parents before and after the pregnancy, the parents can damage germ cell sperms and ova when drinking the alcohol, once the sperm and the ova which are damaged by the alcohol are combined for pregnancy, the infant who is born is often dementia or brain hypoplasia, and the fetal alcoholism syndrome has the following characteristics: at birth, the weight is lower than that of a normal newborn; the central nervous system is usually dysplastic, usually microcephaly, with inward contraction of the upper lip, and often malformation of the heart and limbs. The occurrence of the deformity is related to the drinking time and the drinking capacity of the pregnant women, generally speaking, the more the drinking capacity is larger in the early gestation period, the more obvious and serious the deformity is, and the risk of the deformity is more than 2 times higher than that of the women who do not drink the wine when the infants who are born by intemperance women are counted by people; the mother smokes or absorbs second-hand smoke during pregnancy, which is harmful to fetal development, and the tobacco contains more than 400 kinds of harmful substances, such as carbon monoxide, nicotine, cyanide, etc. When the pregnant woman smokes, nicotine is absorbed into blood, so that the blood vessels of the uterus and the placenta are promoted to contract, the supply of oxygen and nutrition of the fetus is reduced, and the fetal dysplasia is caused.
Second perinatal factors such as preterm birth, birth injury, and hypoxia; premature babies have difficulty in feeding, have multiple pathological conditions such as malnutrition and the like, lead to slow development of the body and intelligence of a fetus, lead to irregular breathing and oxygen deficiency, are easy to combine cerebral palsy, are in urgent labor, induced labor and clamp labor, possibly cause birth injury and further cause intracranial hemorrhage and further cause cerebral palsy, lead to cerebral anoxia of the fetus due to factors such as umbilical cord winding, meconium inhalation, placenta dysfunction and the like caused by overlong delivery time, lead to oxygen deficiency in uterus and oxygen deficiency ischemic encephalopathy caused by asphyxia during labor, lead to cerebral hemorrhage and the like which are serious pathogenic factors of the cerebral palsy, and 40 percent of patients with the cerebral palsy are caused by asphyxia birth injury.
The third factor in the neonatal period, cerebral palsy can be caused by various infections, severe asphyxia, brain trauma, intracranial hemorrhage caused by neonatal hemorrhage, and the like.
The fourth genetic factor, some children with cerebral palsy may have familial genetic history, and if the children with epilepsy, cerebral palsy or dysnoesia are close to each other, the probability of cerebral palsy is increased.
As shown in fig. 3, a mental-paralysis model of the child is generated by relying on the upper cerebral-paralysis model, and the collected pathological data of the cerebral palsy of the child is analyzed and divided into 5 types according to different degrees of severity: spastic cerebral palsy, bradycerebral palsy, mixed cerebral palsy, ataxia cerebral palsy, and ankylosing cerebral palsy.
Spastic cerebral palsy refers to movement and posture disorder caused by non-progressive injury due to incomplete development of immature brain due to various causes, and spasticity can not only hinder the normal movement development of children, but also cause complications such as contracture, malformation, pain, etc.
The bradykinesia type cerebral palsy refers to dyskinesia or dyskinesia caused by injury in the basal brain region, which is manifested as involuntary movement difficult to control with will, the bradykinesia type cerebral palsy occupies about 15% of the cerebral palsy, the lesion part is in the extrapyramidal system of the basal part of the brain, and the damage of the upper limb is usually heavier than that of the lower limb
The mixed cerebral palsy refers to a syndrome which is mainly caused by various motor dysfunctions in postures within one month after birth and is not in a mature stage of brain development and non-progressive brain injury, is a common central nervous system disorder syndrome in the period of children, has a diseased part in the brain and affected limbs, and is often accompanied by symptoms such as intellectual defects, epilepsy, behavioral abnormality, mental disorder, visual, auditory and language disorders, and the like.
Ataxia type cerebral palsy refers to the type of damaged cerebellum accompanied by repeated lesions of the pyramidal system, extrapyramidal system and deep sensory system, which accounts for 4% of the number of patients with cerebral palsy, and is characterized by the inability of continuous posture control, coordinated movement disorder, loss of position sense of joints, decreased muscle tension, easy fatigue, accompanied by distance measuring disorder, tremor of eyes and limbs, and possibly mental retardation.
The strong and direct cerebral palsy refers to cerebral palsy caused by injury of an extrapyramidal system, the simple tonic cerebral palsy is rare, the pure tonic cerebral palsy exists in a mixed way with spastic cerebral palsy, and the biggest characteristic of the tonic cerebral palsy is that passive movement is resisted.
The invention also provides a child cerebral palsy cranial nerve injury assessment instrument based on big data and a using method thereof, wherein the assessment instrument comprises the following steps:
s1, when in detection, a patient to be detected wears a special earphone, electromagnetic waves are emitted by the left earmuff and reach the cerebral cortex, an external magnetic field is generated through electromagnetic resonance, the magnetic field acts on neurons, the neurons are stimulated to generate chemical electric signals, the chemical electric signals are transmitted to organ tissue cells of the whole body through the neurons to cause resonance, the electromagnetic field formed by the cell resonance generates electromagnetic signals, and the signals are captured by the right earmuff in diffusion amplification;
s2, separating and decoding the captured cell resonance electromagnetic signals through a processor, converting the separated and decoded cell resonance electromagnetic signals into frequency spectrums, comparing the detected cell frequency spectrums with reference frequency spectrums, wherein the reference frequency spectrums are derived from a standard cell database of fifteen million people, analyzing the state and the variation trend by comparing the similarity of the frequency spectrums and the frequency spectrum combination, converting the frequency spectrum difference values into statistical values, making clinical definition aiming at the disease state and the pathological change trend according to the statistical analysis result, and automatically completing signal translation and clinical definition through the processor and matched software, thereby improving the efficiency to the maximum extent and reducing the information loss and errors;
s3, networking the detection terminal and the central database, synchronously updating the detected cell molecular spectrum data and the case data obtained by statistical analysis in real time, storing information and performing cooperative operation through intelligent software along with case accumulation and database expansion, continuously correcting judgment parameters, and continuously optimizing and perfecting a mathematical model to realize more accurate diagnosis and prediction.
The above-mentioned embodiments are only used for illustrating the technical solutions of the present invention, and not for limiting the same; although the present invention has been described in detail with reference to the foregoing embodiments, it will be understood by those of ordinary skill in the art that: the technical solutions described in the foregoing embodiments may still be modified, or some technical features may be equivalently replaced; and such modifications or substitutions do not depart from the spirit and scope of the corresponding technical solutions of the embodiments of the present invention.
Claims (4)
1. The child cerebral palsy cranial nerve injury assessment instrument based on big data is characterized by comprising a special earphone worn on two ears of a cerebral palsy child, wherein the special earphone comprises a transmitter and a receiver;
the special earphone is electrically connected with the processor;
the processor is connected with a medical analysis system and a big data system;
the big data system comprises a cerebral palsy infant data collection module, a cerebral palsy infant database establishment module and a cerebral palsy infant database processing module;
the monitor also includes a memory.
2. The apparatus and method for assessing cerebral palsy and cranial nerve damage of children according to claim 1, wherein the processor executes the analysis program stored in the memory, comprising the steps of:
a. establishing a cerebral palsy infant pathological model, and acquiring various physiological signals of an infant through an analyzer, wherein the physiological signals comprise height, weight, body temperature, in-vivo hormone level, diet level of the infant, body activity of the infant and response time to various stimuli to obtain input parameters;
b. the model comprises four factors for inducing cerebral palsy of children, wherein the first factor is a prenatal factor; the second is a perinatal factor; the third is a factor in the neonatal period; the fourth is a genetic factor;
c. inputting parameters based on a child cerebral palsy pathological model, uploading the parameters to a unified server, performing initial state evaluation on the full-automatic biochemical analyzer by utilizing unilateral characteristic quantity, judging whether the full-automatic biochemical analyzer fails or normally operates, establishing a characteristic density estimation model by utilizing an anomaly detection algorithm, and testing whether the characteristic probability density distribution of equipment is abnormal;
d. establishing a mental model of cerebral palsy of children, analyzing the collected pathologic models of cerebral palsy children and dividing the pathologic models into 5 types according to different degrees of severity: spastic cerebral palsy, bradycerebral palsy, mixed cerebral palsy, ataxia cerebral palsy, and ankylosing cerebral palsy.
3. The apparatus and method for assessing cerebral nerve injury of cerebral palsy of children according to claim 2, wherein the spastic cerebral palsy is disorder of movement and posture caused by non-progressive injury due to incomplete development of immature brain under various causes;
the bradykinesia type cerebral palsy refers to dyskinesia or dyskinesia caused by injury in a brain-based region;
the mixed cerebral palsy refers to a syndrome which is mainly caused by various motor dysfunctions in postures due to non-progressive brain injury in a brain immature stage in postnatal one month;
the ataxia cerebral palsy refers to a type of damaged cerebellum accompanied by repeated lesions of the pyramidal system, extrapyramidal system and deep sensory system;
the strong and straight cerebral palsy refers to cerebral palsy caused by injury of an extrapyramidal system.
4. The child cerebral palsy cranial nerve injury assessment instrument based on big data and the use method thereof are characterized by comprising the following steps:
s1, when in detection, a patient to be detected wears a special earphone, electromagnetic waves are emitted by the left earmuff and reach the cerebral cortex, an external magnetic field is generated through electromagnetic resonance, the magnetic field acts on neurons, the neurons are stimulated to generate chemical electric signals, the chemical electric signals are transmitted to organ tissue cells of the whole body through the neurons to cause resonance, the electromagnetic field formed by the cell resonance generates electromagnetic signals, and the signals are captured by the right earmuff in diffusion amplification;
s2, separating and decoding the captured cell resonance electromagnetic signals through a processor, converting the separated and decoded cell resonance electromagnetic signals into frequency spectrums, comparing the detected cell frequency spectrums with reference frequency spectrums, wherein the reference frequency spectrums are derived from a standard cell database of fifteen million people, analyzing the state and the variation trend by comparing the similarity of the frequency spectrums and the frequency spectrum combination, converting the frequency spectrum difference values into statistical values, making clinical definition aiming at the disease state and the pathological change trend according to the statistical analysis result, and automatically completing signal translation and clinical definition through the processor and matched software, thereby improving the efficiency to the maximum extent and reducing the information loss and errors;
s3, networking the detection terminal and the central database, synchronously updating the detected cell molecular spectrum data and the case data obtained by statistical analysis in real time, storing information and performing cooperative operation through intelligent software along with case accumulation and database expansion, continuously correcting judgment parameters, and continuously optimizing and perfecting a mathematical model to realize more accurate diagnosis and prediction.
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Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN113545766A (en) * | 2021-06-18 | 2021-10-26 | 遵义医科大学附属医院 | Method for predicting gross motor function of spastic cerebral palsy children based on MRI nomogram |
| CN114999648A (en) * | 2022-05-27 | 2022-09-02 | 浙江大学医学院附属儿童医院 | Early screening system, equipment and storage medium for cerebral palsy based on baby dynamic posture estimation |
-
2021
- 2021-01-26 CN CN202110103086.0A patent/CN112932445A/en not_active Withdrawn
Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN113545766A (en) * | 2021-06-18 | 2021-10-26 | 遵义医科大学附属医院 | Method for predicting gross motor function of spastic cerebral palsy children based on MRI nomogram |
| CN114999648A (en) * | 2022-05-27 | 2022-09-02 | 浙江大学医学院附属儿童医院 | Early screening system, equipment and storage medium for cerebral palsy based on baby dynamic posture estimation |
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