CN111789595A - Artificial intelligence scoliosis real-time supervision early warning system based on cloud platform - Google Patents
Artificial intelligence scoliosis real-time supervision early warning system based on cloud platform Download PDFInfo
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- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- 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
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Abstract
The invention relates to an artificial intelligence scoliosis real-time monitoring and early warning system based on a cloud platform, which comprises a wearable scoliosis detection device, a wearable early warning device and an artificial intelligence cloud platform, wherein the wearable scoliosis detection device is used for detecting scoliosis; the wearable scoliosis detection device comprises a wearable part, an attitude sensor and a position sensor which are arranged in the wearable part, and a single chip microcomputer connected with the attitude sensor and the position sensor, wherein the single chip microcomputer transmits data to the artificial intelligent cloud platform. The monitoring and early warning device is portable and wearable, can realize real-time monitoring and early warning for the scoliosis patients of teenagers and children, and is simultaneously connected with medical care and patient terminals to realize remote diagnosis and rehabilitation guidance of the medical care to the patients.
Description
Technical Field
The invention relates to a scoliosis early warning system, in particular to an artificial intelligent real-time scoliosis monitoring early warning system based on a cloud platform.
Background
Scoliosis can seriously affect the external physique and the internal organ function of a patient, and even endanger life when the symptoms are serious; most people have scoliosis which begins with an incorrect posture, and stresses the spine and even the muscles and nerves around the spine, resulting in irreversible scoliosis and deformity. However, most people with incorrect sitting posture are less aware of the change of their own posture, and even if the people are consciously correcting the sitting posture, the correction effect is not obvious because the people cannot focus on the state of the spine for a long time, which is especially common among students, white-collar workers and other people who need to sit for a long time.
The key of the rehabilitation therapy of scoliosis of teenagers and children is early discovery, early diagnosis, early prevention and early treatment. The occurrence and development of the diseases can be well prevented and treated only by paying more attention to body posture in daily life and reminding correction in real time. Therefore, how to supervise and ensure the correct body posture in the learning work and prevent the occurrence of scoliosis becomes a hot spot of the common research in the fields of medical health, engineering technology, physical health and the like. The existing medical scoliosis monitor can monitor and evaluate the scoliosis state of a user, but cannot monitor the spine condition of the user in real time and perform corresponding correction reminding due to the complex structure and incapability of being worn by the user at any time; the spine is bent to the side, so that people can seek medical help after severe discomfort is caused, but forced correction is carried out after the spine is bent to the side, so that the health is harmed, the development of teenagers is influenced, and the great waste of medical resources is caused.
The traditional diagnosis method of scoliosis is that a patient carries out X-ray examination in an imaging department, takes an X-ray film after several hours, and then gives the X-ray film to a doctor for observation and diagnosis, and the doctor carries out entity measurement on the X-ray film to obtain a diagnosis result. In the conventional diagnosis method, the waiting time of the patient is extremely long, and the manual measurement of the doctor is inevitable to have certain errors. And the patient needs to go to the hospital every time of diagnosis, and the effect of remote and real-time monitoring is difficult to achieve.
Disclosure of Invention
The artificial intelligence scoliosis real-time monitoring and early warning system is convenient to carry and wearable, and can remind a user of correcting sitting postures in time.
In order to solve the above problems, the technical scheme adopted by the application is as follows: an artificial intelligence scoliosis real-time monitoring and early warning system based on a cloud platform comprises a wearable scoliosis detection device, a wearable early warning device and an artificial intelligence cloud platform; the wearable scoliosis detection device comprises a wearable part, an attitude sensor and a position sensor which are arranged in the wearable part, and a single chip microcomputer connected with the attitude sensor and the position sensor; the single chip microcomputer transmits data to the artificial intelligent cloud platform; the artificial intelligence cloud platform receives the uploaded data of at least two wearable scoliosis detection devices, analyzes and processes the received data respectively, and then feeds the result back to the corresponding wearable early warning device.
The attitude sensor integrates a three-axis acceleration sensor, a three-axis gyroscope and a three-axis magnetometer.
Furthermore, the three-axis acceleration sensor is used for acquiring acceleration data of three degrees of freedom of the carrier;
further, the three-axis gyroscope is used for acquiring data of three-degree-of-freedom arbitrary rotation attitude of the carrier;
furthermore, the three-axis magnetometer is used for measuring the magnetic field intensity around the sensor, preventing magnetic field interference and providing course angle correction information.
The system comprises an attitude sensor, a position sensor, an artificial intelligent cloud platform, a space vector analysis method, a Cobb angle and a wearable early warning device, wherein the attitude sensor and the position sensor acquire three-axis angles in the neighborhood of each fixed line length mark point on a spinal spinous process line of a human body and upload the three-axis angles to the artificial intelligent cloud platform through a single chip microcomputer, the artificial intelligent cloud platform analyzes and constructs a three-dimensional curve of a spinal vertebra form, the Cobb angle used for quantitatively evaluating the malformation degree of the spinal column is calculated through the three-dimensional curve of the spinal vertebra form and the space vector analysis method, the Cobb angle is compared with a set threshold value, and the.
The artificial intelligence cloud platform comprises an orthopedic technician evaluation terminal and a guardian monitoring terminal. The artificial intelligence cloud platform sends the three-dimensional curve of the spinal vertebra morphology and the Cobb's angle to an orthopedic assessment terminal. The artificial intelligence cloud platform evaluates the scoliosis severity and gives a correction suggestion according to the three-dimensional curve of the spine vertebra morphology and the Cobb's angle, and sends the evaluation information of the scoliosis severity and the correction suggestion to the guardian terminal.
The artificial intelligent scoliosis real-time monitoring and early warning system based on the cloud platform can be applied to all students in the same classroom or all workers in the same office area.
The monitoring and early warning device is portable and wearable, can realize real-time monitoring and early warning for the scoliosis patients of teenagers and children, and is simultaneously connected with medical care and patient terminals to realize remote diagnosis and rehabilitation guidance of the medical care to the patients.
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FIG. 1 is a schematic view of the structure of the present invention.
Detailed Description
An artificial intelligence scoliosis real-time monitoring and early warning system based on a cloud platform is applied to all students in the same classroom; the system comprises a wearable scoliosis detection device, a wearable early warning device and an artificial intelligent cloud platform; the wearable scoliosis detection device comprises a wearable part, an attitude sensor and a position sensor which are arranged in the wearable part, and a single chip microcomputer connected with the attitude sensor and the position sensor; the single chip microcomputer transmits data to the artificial intelligent cloud platform; the artificial intelligence cloud platform receive the scoliosis detection device's that the whole class classmate dresses simultaneously upload data and carry out the early warning bracelet that wears that analysis processes the back with result feedback to the whole class classmate is right to received data respectively. When the student's position of sitting is bad, the warning bracelet is reported to the police in time and is reminded.
Preferably, the attitude sensor integrates a three-axis acceleration sensor, a three-axis gyroscope and a three-axis magnetometer.
Preferably, the wearable part is made of comfortable and air-permeable materials, and the inner wall of the wearable part is provided with a strip-shaped groove which is matched with the spine; the attitude sensor and the position sensor are arranged in the strip-shaped groove.
Preferably, the wearable early warning device is a bracelet worn on the wrist of the user. Based on wearable scoliosis detection device and artificial intelligence cloud platform, when user's backbone condition is bad, or when bad posture appears in work, study, life, send the early warning through the bracelet, remind the user to correct bad posture or follow medical advice and carry out rehabilitation.
The system comprises an attitude sensor, a position sensor, an artificial intelligent cloud platform, a space vector analysis method, a Cobb angle and a wearable early warning device, wherein the attitude sensor and the position sensor acquire three-axis angles in the neighborhood of each fixed line length mark point on a spinal spinous process line of a human body and upload the three-axis angles to the artificial intelligent cloud platform through a single chip microcomputer, the artificial intelligent cloud platform analyzes and constructs a three-dimensional curve of a spinal vertebra form, the Cobb angle used for quantitatively evaluating the malformation degree of the spinal column is calculated through the three-dimensional curve of the spinal vertebra form and the space vector analysis method, the Cobb angle is compared with a set threshold value, and the.
The artificial intelligence cloud platform comprises an orthopedic technician evaluation terminal and a guardian monitoring terminal.
The artificial intelligence cloud platform sends the three-dimensional curve of the spinal vertebra morphology and the Cobb's angle to an orthopedic assessment terminal. The orthopedic teacher evaluation terminal and the guardian terminal are connected with the artificial intelligent cloud platform, so that remote diagnosis and rehabilitation guidance are realized.
The artificial intelligence cloud platform is internally stored with spine iconography data of normal persons and scoliosis patients in different age groups, cases and correction schemes of typical scoliosis patients, so that the artificial intelligence cloud platform analyzes the deviation of various parameters of the spine of the patient from normal values according to a three-dimensional curve of the spine vertebra shape and Cobb's angle, analyzes the position and the angle of the scoliosis of the patient, evaluates the scoliosis severity and gives a correction suggestion, and sends the evaluation information of the scoliosis severity and the correction suggestion to the guardian terminal. Parents of students can know the severity of scoliosis of children and know correction suggestions through the monitoring terminal.
The monitoring and early warning device is portable and wearable, can realize real-time monitoring and early warning for the scoliosis patients of teenagers and children, and is simultaneously connected with medical care and patient terminals to realize remote diagnosis and rehabilitation guidance of the medical care to the patients.
The artificial intelligent real-time monitoring and early warning system for scoliosis based on the cloud platform can monitor the scoliosis condition of a patient in real time, and realizes early discovery, early diagnosis, early prevention and early treatment.
When the spine of the patient is in poor condition or has poor postures in work, study and life, the early warning can be realized in real time, the patient is reminded to correct the poor postures in time or carry out rehabilitation treatment according to medical advice, and the rehabilitation curative effect is improved. In addition, the remote real-time diagnosis and rehabilitation guidance of the patient by medical care can be realized, and the remote real-time diagnosis and rehabilitation guidance system has important significance for guiding the rehabilitation training of the patient and the efficient rehabilitation treatment of the patient more conveniently and quickly by medical care.
Claims (9)
1. An artificial intelligence scoliosis real-time monitoring and early warning system based on a cloud platform is characterized by comprising a wearable scoliosis detection device, a wearable early warning device and an artificial intelligence cloud platform; the wearable scoliosis detection device comprises a wearable part, an attitude sensor and a position sensor which are arranged in the wearable part, and a single chip microcomputer connected with the attitude sensor and the position sensor; the single chip microcomputer transmits data to the artificial intelligent cloud platform; the artificial intelligence cloud platform receives the uploaded data of at least two wearable scoliosis detection devices, analyzes and processes the received data respectively, and then feeds the result back to the corresponding wearable early warning device.
2. The cloud platform-based artificial intelligence scoliosis real-time monitoring and early warning system of claim 1, wherein the attitude sensor integrates a three-axis acceleration sensor, a three-axis gyroscope and a three-axis magnetometer.
3. The cloud platform-based artificial intelligence scoliosis real-time monitoring and early warning system according to claim 1 or 2, wherein a strip-shaped groove is formed in the inner wall of the wearable part and is matched with a spine; the attitude sensor and the position sensor are arranged in the strip-shaped groove.
4. The cloud platform-based artificial intelligence scoliosis real-time monitoring and early-warning system of claim 2, wherein the wearable early-warning device is a bracelet worn on a wrist of a user.
5. The cloud platform-based artificial intelligence scoliosis real-time monitoring and early warning system as claimed in claim 2 or 4, wherein the attitude sensor and the position sensor acquire three-axis angles in the vicinity of each fixed line length mark point on a human spine spinous process line and upload the three-axis angles to the artificial intelligence cloud platform through the single chip microcomputer, the artificial intelligence cloud platform analyzes and constructs a three-dimensional curve of spine vertebra morphology, a Cobb's angle for quantitatively evaluating the malformation degree of the spine is calculated by the three-dimensional curve of the spine vertebra morphology and a method for analyzing a space angle by combining a space vector, the Cobb's angle is compared with a set threshold value, and the artificial intelligence cloud platform sends out early warning information through a wearable early warning device.
6. The cloud platform-based artificial intelligence scoliosis real-time monitoring and early warning system according to claim 5, wherein the artificial intelligence cloud platform comprises an orthopedic technician evaluation terminal and a guardian monitoring terminal.
7. The cloud platform-based artificial intelligence scoliosis real-time monitoring and early warning system of claim 6, wherein the artificial intelligence cloud platform sends a three-dimensional curve of spinal vertebra morphology and a Cobb's angle to an orthopedic assessment terminal.
8. The cloud platform-based artificial intelligence scoliosis real-time monitoring and early warning system of claim 6, wherein the artificial intelligence cloud platform evaluates the scoliosis severity and gives a correction suggestion according to a three-dimensional curve of a spine vertebra morphology and a Cobb's angle, and sends the evaluation information of the scoliosis severity and the correction suggestion to the guardian terminal.
9. The cloud platform-based artificial intelligence scoliosis real-time monitoring and early warning system as claimed in claim 8, wherein the system is applicable to all students in the same classroom or all staff in the same office area.
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Cited By (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN112472111A (en) * | 2020-12-14 | 2021-03-12 | 上海交通大学医学院附属新华医院 | Early self-checking and rehabilitation cloud platform for scoliosis |
| CN113100897A (en) * | 2021-04-20 | 2021-07-13 | 电子科技大学 | Intelligent external fixing clamp for monitoring spinal rehabilitation state and monitoring method |
| CN113951878A (en) * | 2021-11-03 | 2022-01-21 | 苏州高新区人民医院 | Artificial intelligence scoliosis monitoring and early warning system based on cloud platform |
| CN115381439A (en) * | 2022-08-29 | 2022-11-25 | 江苏省淮安体育运动学校 | Visual tight clothes of backbone side bending degree |
| CN115429517A (en) * | 2022-11-07 | 2022-12-06 | 北京积水潭医院 | Soft scoliosis brace system based on fuzzy PID neural network |
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Cited By (7)
| Publication number | Priority date | Publication date | Assignee | Title |
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| CN112472111A (en) * | 2020-12-14 | 2021-03-12 | 上海交通大学医学院附属新华医院 | Early self-checking and rehabilitation cloud platform for scoliosis |
| CN112472111B (en) * | 2020-12-14 | 2023-08-29 | 上海交通大学医学院附属新华医院 | Scoliosis early self-checking and Kang Fuyun platform |
| CN113100897A (en) * | 2021-04-20 | 2021-07-13 | 电子科技大学 | Intelligent external fixing clamp for monitoring spinal rehabilitation state and monitoring method |
| CN113951878A (en) * | 2021-11-03 | 2022-01-21 | 苏州高新区人民医院 | Artificial intelligence scoliosis monitoring and early warning system based on cloud platform |
| CN113951878B (en) * | 2021-11-03 | 2023-08-15 | 苏州高新区人民医院 | Cloud platform-based artificial intelligence scoliosis monitoring and early warning system |
| CN115381439A (en) * | 2022-08-29 | 2022-11-25 | 江苏省淮安体育运动学校 | Visual tight clothes of backbone side bending degree |
| CN115429517A (en) * | 2022-11-07 | 2022-12-06 | 北京积水潭医院 | Soft scoliosis brace system based on fuzzy PID neural network |
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