Rehabilitation medical training management system

Abstract

The invention relates to the technical field of medical management, and discloses a rehabilitation medical training management system which comprises a medical acquisition module and an intelligent evaluation module. According to the rehabilitation medical training management system, management data and rehabilitation data of all patients and monitoring data of training environments where the patients are located are obtained through the medical collection module and classified to form a data set, and the intelligent evaluation module divides resistance groups and susceptible groups according to the ages of the patients and determines rehabilitation difficulty. Analyzing the severity of the physiological disorder of each patient, generating a disorder coefficient, setting a monitoring period, analyzing the fluctuation rate of the disorder coefficient of each patient and the variable quantity of each physiological parameter of the patient, generating a monitoring data set, analyzing the load coefficient during rehabilitation training, and comprehensively analyzing the training suitability of the patient; the intelligent evaluation module judges whether the patient has the physical state of rehabilitation training or not and whether the exercise intensity in the rehabilitation training process is overloaded or not and outputs corresponding training suggestions, and the rehabilitation effect is dynamically adjusted to be better.

Description

Technical Field

[0001] The present invention relates to the technical field of medical management, and in particular to a rehabilitation medical training management system. Background Art

[0002] Rehabilitation medicine is a treatment process for patients to restore their functions after illness, injury or surgery, aiming to improve their quality of life, reduce disability and restore independence. Rehabilitation medicine is usually carried out by a multidisciplinary team of professional rehabilitation physicians, physical therapists, occupational therapists, speech therapists and psychotherapists, covering a variety of methods such as physical therapy, exercise therapy, speech therapy, occupational therapy and psychological counseling. Rehabilitation medicine has a wide range of subjects, including patients with neurological diseases, bone and joint diseases, chronic diseases, cardiopulmonary diseases and the elderly. The main purpose of rehabilitation medicine is to reduce the functional impairment caused by disease, injury or aging, and help patients restore their impaired physiological, psychological and social functions. The rehabilitation medical training management system can automatically generate personalized rehabilitation treatment plans according to the specific conditions of the patients, and auxiliary therapists can dynamically adjust the treatment plans according to the feedback and progress of the patients. For patients, the system records and analyzes daily training performance, and also provides precise rehabilitation goals to help them better understand their rehabilitation progress, enhance their confidence in treatment, and make medical services more efficient and of better quality.

[0003] At present, traditional rehabilitation medical training management systems ignore the stability of patients' conditions and the adaptability of the training environment, resulting in poor rehabilitation effects for patients. In addition, the lack of intelligent dynamic monitoring and adjustment mechanisms makes it difficult to meet individual needs, and patients are prone to accidental injuries during training. Summary of the invention

[0004] 1. Technical issues to be resolved In view of the shortcomings of the existing technology, the present invention provides a rehabilitation medical training management system, which has the advantages of comprehensively analyzing the patient's training adaptability and dynamically adjusting the rehabilitation effect for better results. It solves the problem that the traditional rehabilitation medical training management system ignores the stability of the patient's condition and the adaptability of the training environment and lacks a dynamic adjustment mechanism.

[0005] (II) Technical solution To achieve the above-mentioned object, the present invention provides the following technical solutions: a rehabilitation medical training management system, comprising a medical collection module and an intelligent evaluation module; The medical acquisition module is composed of a patient data unit, a rehabilitation data unit and a real-time data unit. The patient data unit is connected to a database through a network to collect a patient data set, and the patient data set includes management data of all patients. The rehabilitation data unit is connected to a remote monitoring device through a network to collect a rehabilitation data set, and the rehabilitation data set includes rehabilitation data of all patients. The real-time data unit is connected to a remote monitoring device through a network to collect a real-time data set, and the real-time data set includes monitoring data of the patient's training environment. The intelligent assessment module consists of a disease analysis unit, a training assessment unit and a rehabilitation management unit. The disease analysis unit divides the patient data set into resistant groups and susceptible groups according to the age of each patient, analyzes the severity of each patient's physiological disorder, and generates a corresponding disorder coefficient. The condition analysis unit is provided with a monitoring cycle of fixed duration. , analyze the barrier coefficient of each patient The changing trend of The training evaluation unit counts the monitoring period according to the rehabilitation data set and the real-time data set. The changes in the patient's physiological parameters generate corresponding monitoring data sets. , and analyze the load factor of each patient during rehabilitation training The rehabilitation management unit is set with a fixed range of resistance barrier thresholds , Susceptibility threshold , Fluctuation Threshold , Heart rate threshold , blood oxygen saturation threshold , blood pressure threshold , temperature threshold and load threshold , combined with the barrier coefficient , Volatility , Monitoring Data Group and load factor , determine whether the patient has the physical condition to undergo rehabilitation training, whether the exercise intensity during rehabilitation training is overloaded, and output corresponding training suggestions.

[0006] Preferably, the expression of the patient data set is , to First to Second Management data of patients, including APACHE II score, SOFA score, NYHA functional class, CPSS score and CCI score. Indicates the age of each patient.

[0007] Preferably, the expression of the rehabilitation data set is , to First to Second The rehabilitation data of patients, the rehabilitation data is the treatment planning duration, Indicates the length of time each patient has completed rehabilitation training.

[0008] Preferably, the expression of the real-time data set is , to First to Second The monitoring data of patients during rehabilitation training included WBGT index, heart rate, blood oxygen saturation, blood pressure, body temperature, movement amplitude and movement acceleration. Indicates the specific time for obtaining the monitoring data of each patient.

[0009] Preferably, the obstacle coefficient The calculation process is as follows: Extract the patient data set The administrative data of the patients and The APACHE II score of the patients was , will The SOFA scores of patients were marked as , will The NYHA functional class of the patients was , will The CPSS scores of the patients were marked as , will The CCI scores of the patients are marked as , will The age of the patients is marked as ; like , divided into resistant groups; ; In the formula, represents the evaluation weight for APACHE II score, represents the evaluation weight for SOFA score, represents the assessment weight for NYHA functional class, Represents the evaluation weight for CPSS score, represents the evaluation weight for CCI score, represents the evaluation weight for the patient's age, , Indicates according to , , , , and Weight, calculate the Disability coefficient of patients ; like or , divided into susceptible groups; ; In the formula, represents the evaluation weight for APACHE II score, represents the evaluation weight for SOFA score, represents the assessment weight for NYHA functional class, Represents the evaluation weight for CPSS score, represents the evaluation weight for CCI score, represents the evaluation weight for the patient's age, , represents the amplification factor, Indicates according to , , , , and Weight, calculate the Disability coefficient of patients .

[0010] Preferably, the volatility The calculation process is as follows: Statistical monitoring cycle within, no. Disability coefficient of patients , and marked as , to Respectively Patients from the first time point to the Obstacle coefficient at each time point; ; ; In the formula, Indicates monitoring cycle within, no. The average value of the disability coefficient of the patients, Indicates Patients in The obstacle coefficient at each time point is According to the variance formula, the first Fluctuation rate of the disorder coefficient for each patient .

[0011] Preferably, the monitoring data set The calculation process is as follows: According to the real-time data set, extract the The monitoring data of patients will be The heart rates of the patients are marked as , will The blood oxygen saturation of patients is marked as , will The blood pressure of patients is marked as , will The patient's temperature is marked as ; ; In the formula, Indicates Patients at time point Heart rate during rehabilitation training, Indicates Patients at time point Heart rate during rehabilitation training, Represents the change in heart rate between two time points. Indicates Patients at time point Blood oxygen saturation during rehabilitation training, Indicates Patients at time point Blood oxygen saturation during rehabilitation training, Indicates the change in blood oxygen saturation between two time points. Indicates Patients at time point Blood pressure during rehabilitation training, Indicates Patients at time point Blood pressure during rehabilitation training, Represents the change in blood pressure between two time points. Indicates Patients at time point Body temperature during rehabilitation training, Indicates Patients at time point Body temperature during rehabilitation training, represents the change in body temperature between two time points. represents the monitoring data set of the e-th patient.

[0012] Preferably, the load factor The calculation process is as follows: According to the rehabilitation data set, The treatment planning duration of patients is marked as , will The duration of rehabilitation training completed by patients is marked as ; According to the real-time data set, The WBGT index of the training environment for the patients is marked as , will The range of motion of the patients during rehabilitation training was marked as , will The movement acceleration of the patients during rehabilitation training is marked as ; ; ; In the formula, It represents the percentage of training time to treatment planning time, which is Completion progress of rehabilitation training for patients , represents the evaluation weight of the completion progress of rehabilitation training, Represents the evaluation weight of the WBGT index for the training environment, represents the evaluation weight for the motion amplitude, Represents the evaluation weight for motion acceleration, , Indicates according to , , and Weight, calculate the The load factor of the patients undergoing rehabilitation training .

[0013] Preferably, the barrier coefficient of patients in the resistant population is Exceeding the resistance barrier threshold , indicating that the patient does not have the physical condition to undergo rehabilitation training, and it is recommended that the patient continue to receive drug treatment. The obstacle coefficient of the patient in the resistance group Included in resistance barrier threshold , and volatility Included in volatility threshold , indicating that the patient has the physical condition to undergo rehabilitation training, and it is recommended that the patient choose a light functional training program. The obstacle coefficient of the patient in the susceptible group is Exceeding the threshold of susceptible disorder , indicating that the patient does not have the physical condition to undergo rehabilitation training, and it is recommended that the patient continue to receive drug treatment. The disability coefficient of the patient in the susceptible group Included in the Susceptibility Threshold , and volatility Included in volatility threshold , it means that the patient has the physical condition to undergo rehabilitation training, and it is recommended that the patient choose a light functional training program.

[0014] Preferably, the monitoring data set The heart rate change exceeds the heart rate threshold , The change in blood oxygen saturation exceeds the blood oxygen saturation threshold , Blood pressure change exceeds the blood pressure threshold , the temperature change exceeds the temperature threshold or load factor Exceeding load threshold It means that the patient's exercise intensity during rehabilitation training has been overloaded. It is recommended that the patient slowly stop exercising and get enough rest.

[0015] Compared with the prior art, the present invention provides a rehabilitation medical training management system, which has the following beneficial effects: 1. The present invention connects the database and the remote monitoring device through the medical acquisition module network to obtain the management data, rehabilitation data of all patients, and the monitoring data of the patient's training environment, and classifies them into patient data sets, rehabilitation data sets and real-time data sets. The intelligent evaluation module divides the patient data sets into resistance groups and susceptible groups according to the age of each patient to determine the patient's rehabilitation difficulty, and then analyzes the severity of each patient's physiological disorder and generates a corresponding disorder coefficient. , which helps medical staff judge the patient's recovery potential, provide personalized training suggestions, reduce training risks, and set a fixed-duration monitoring cycle for the intelligent assessment module , analyze the barrier coefficient of each patient Volatility , the changes in various physiological parameters of the patient, and generate monitoring data sets , and analyze the load factor of each patient during rehabilitation training , identify potential risk signals, promptly discover sudden changes in patients' conditions, excessive physical exertion, etc., comprehensively analyze patients' training adaptability, and specifically evaluate each patient's carrying capacity to avoid patients undergoing overly strenuous training under inappropriate conditions.

[0016] 2. The present invention sets a fixed range of resistance barrier thresholds through an intelligent evaluation module , Susceptibility threshold , Fluctuation Threshold , heart rate threshold , blood oxygen saturation threshold , blood pressure threshold , temperature threshold and load threshold , combined with the barrier coefficient , Volatility , Monitoring Data Group and load factor , determine whether the patient has the physical condition to undergo rehabilitation training, and whether the exercise intensity during rehabilitation training is overloaded, and output corresponding training suggestions to dynamically adjust the rehabilitation effect for better results. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] Figure 1 It is a schematic diagram of the system flow of the present invention. DETAILED DESCRIPTION

[0018] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0019] The traditional rehabilitation medical training management system ignores the stability of the patient's condition and the adaptability of the training environment, which leads to poor patient rehabilitation results. In addition, the lack of intelligent dynamic monitoring and adjustment mechanism makes it difficult to meet individual needs. At the same time, patients are prone to accidental injuries during training. Therefore, a rehabilitation medical training management system is provided. Please refer to Figure 1 , a rehabilitation medical training management system, including a medical collection module and an intelligent evaluation module; The medical collection module consists of patient data unit, rehabilitation data unit and real-time data unit, which is used to grasp the health status and clinical indicators of each patient, help determine the direction and intensity of rehabilitation, and provide a scientific basis for subsequent training plans. The patient data unit collects patient data sets through a network connection database. The patient data set includes the management data of all patients. The expression of the patient data set is , to First to Second Management data of patients, including APACHE II score, SOFA score, NYHA functional class, CPSS score and CCI score. Indicates the age of each patient. The APACHE II score takes into account multiple physiological parameters. The higher the score, the higher the estimated risk of death. The SOFA score takes into account the functional indicators of the six systems of respiration, circulation, coagulation, liver, kidney and nerves. The higher the score, the more severe the degree of organ failure. The NYHA functional grade is used to assess the functional status of patients with heart failure. Grade I means that the patient is asymptomatic and daily activities are not affected. Grade IV means that the patient has severe symptoms and cannot perform any physical activities. The CPSS score is used to assess whether the patient has a stroke reaction. The higher the score, the more severe the patient's limb movement disorder. The CCI score is accumulated according to different comorbidities. The higher the score, the worse the patient's health condition and the higher the risk of death. The rehabilitation data unit collects the rehabilitation data set through the network connection remote monitoring device. The rehabilitation data set includes the rehabilitation data of all patients. The expression of the rehabilitation data set is: , to First to Second The rehabilitation data of patients, the rehabilitation data is the treatment planning duration, Indicates the length of time each patient has completed rehabilitation training, which helps track the patient's rehabilitation progress and ensure the feasibility and effectiveness of the treatment plan; The real-time data unit collects real-time data sets through a network connection to a remote monitoring device. The real-time data sets include monitoring data of the patient's training environment. The expression of the real-time data set is: , to First to Second The monitoring data of patients during rehabilitation training included WBGT index, heart rate, blood oxygen saturation, blood pressure, body temperature, movement amplitude and movement acceleration. Indicates the specific time of obtaining monitoring data for each patient, and monitors the adaptability of environmental factors and changes in physiological parameters during the patient's rehabilitation training in real time, providing an important basis for doctors to evaluate the performance and load of patients in rehabilitation training; The intelligent assessment module consists of a disease analysis unit, a training assessment unit, and a rehabilitation management unit. The disease analysis unit divides the patient data set into resistant groups and susceptible groups according to the age of each patient to determine the patient's rehabilitation difficulty, and then analyzes the severity of each patient's physiological disorder and generates a corresponding disorder coefficient. , the calculation process is as follows: Extract the patient data set The administrative data of the patients and The APACHE II score of the patients was , will The SOFA scores of patients were marked as , will The NYHA functional class of the patients was , will The CPSS scores of the patients were marked as , will The CCI scores of the patients are marked as , will The age of the patients is marked as ; like , divided into resistant groups, the resistant group is mostly young people, with strong immune system resistance and good training load capacity; ; In the formula, represents the evaluation weight for APACHE II score, represents the evaluation weight for SOFA score, represents the assessment weight for NYHA functional class, Represents the evaluation weight for CPSS score, represents the evaluation weight for CCI score, represents the evaluation weight for the patient's age, , Indicates according to , , , , and Weight, calculate the Disability coefficient of patients ; like or , divided into susceptible groups, mostly children and elderly patients. Children's immune function is not yet mature, and the elderly's physiological function is weak. Both children and elderly patients find it difficult to bear high-intensity rehabilitation training content; ; In the formula, represents the evaluation weight for APACHE II score, represents the evaluation weight for SOFA score, represents the assessment weight for NYHA functional class, Represents the evaluation weight for CPSS score, represents the evaluation weight for CCI score, represents the evaluation weight for the patient's age, , represents the amplification factor, Indicates according to , , , , and Weight, calculate the Disability coefficient of patients , which helps medical staff judge the patient's recovery potential, provide personalized training suggestions, and reduce training risks; The condition analysis unit is set with a fixed-duration monitoring cycle , analyze the barrier coefficient of each patient The changing trend of , the calculation process is as follows: Statistical monitoring cycle within, no. Disability coefficient of patients , and marked as , to Respectively Patients from the first time point to the Obstacle coefficient at each time point; ; ; In the formula, Indicates monitoring cycle within, no. The average value of the disability coefficient of the patients, Indicates Patients in The obstacle coefficient at each time point is According to the variance formula, the first Fluctuation rate of the disorder coefficient for each patient , identify potential risk signals and promptly detect sudden changes in the patient's condition, excessive physical exhaustion, etc.; The training evaluation unit counts the monitoring cycle based on the rehabilitation data set and the real-time data set. The changes in the patient's physiological parameters generate corresponding monitoring data sets. , and analyze the load factor of each patient during rehabilitation training ; Monitoring data set The calculation process is as follows: According to the real-time data set, extract the The monitoring data of patients will be The heart rates of the patients were marked as , will The blood oxygen saturation of patients is marked as , will The blood pressure of patients is marked as , will The patient's temperature is marked as ; ; In the formula, Indicates Patients at time point Heart rate during rehabilitation training, Indicates Patients at time point Heart rate during rehabilitation training, Represents the change in heart rate between two time points. Indicates Patients at time point Blood oxygen saturation during rehabilitation training, Indicates Patients at time point Blood oxygen saturation during rehabilitation training, Indicates the change in blood oxygen saturation between two time points. Indicates Patients at time point Blood pressure during rehabilitation training, Indicates Patients at time point Blood pressure during rehabilitation training, Represents the change in blood pressure between two time points. Indicates Patients at time point Body temperature during rehabilitation training, Indicates Patients at time point Body temperature during rehabilitation training, represents the change in body temperature between two time points. represents the monitoring data set of the e-th patient, ensuring that all physiological parameters of the patient are within the safe range during the training process; Load Factor The calculation process is as follows: According to the rehabilitation data set, The treatment planning duration of patients is marked as , will The duration of rehabilitation training completed by patients is marked as ; According to the real-time data set, The WBGT index of the training environment for the patients is marked as , will The range of motion of the patients during rehabilitation training was marked as , will The movement acceleration of the patients during rehabilitation training is marked as ; ; ; In the formula, It represents the percentage of training time to treatment planning time, which is Completion progress of rehabilitation training for patients , represents the evaluation weight of the completion progress of rehabilitation training, Represents the evaluation weight of the WBGT index for the training environment, represents the evaluation weight for the motion amplitude, Represents the evaluation weight for motion acceleration, , Indicates according to , , and Weight, calculate the The load factor of the patients undergoing rehabilitation training , comprehensively analyze the patient's training suitability, and specifically evaluate each patient's carrying capacity to prevent the patient from undergoing overly intense training in an unsuitable state; The rehabilitation management unit has a fixed range of resistance barrier thresholds. , Susceptibility threshold , Fluctuation Threshold , Heart rate threshold , blood oxygen saturation threshold , blood pressure threshold , temperature threshold and load threshold , combined with the barrier coefficient , Volatility , Monitoring Data Group and load factor , to determine whether the patient has the physical condition to undergo rehabilitation training, whether the exercise intensity during rehabilitation training is overloaded, and the obstacle coefficient of patients in the resistance group Exceeding the resistance barrier threshold , indicating that the patient does not have the physical condition for rehabilitation training, and it is recommended that the patient continue to receive drug treatment. The obstacle coefficient of patients in the resistance group Included in resistance barrier threshold , and volatility Included in volatility threshold When , it means that the patient has the physical condition to undergo rehabilitation training. It is recommended that the patient choose a light functional training program. The obstacle coefficient of patients in the susceptible group is Exceeding the threshold of susceptible disorder , indicating that the patient does not have the physical condition for rehabilitation training, and it is recommended that the patient continue to receive drug treatment. The disability coefficient of patients in the susceptible group Included in the Susceptibility Threshold , and volatility Included in volatility threshold When the patient is in good physical condition for rehabilitation training, it is recommended that the patient choose a light functional training program. The heart rate change exceeds the heart rate threshold , The change in blood oxygen saturation exceeds the blood oxygen saturation threshold , Blood pressure change exceeds the blood pressure threshold , the temperature change exceeds the temperature threshold or load factor Exceeding load threshold It means that the patient's exercise intensity during rehabilitation training has been overloaded. It is recommended that the patient slowly stop exercising, get enough rest, and dynamically adjust the training load, so that the patient's rehabilitation effect will be better.

[0020] Example 1: In this experiment, a 25-year-old patient was selected as the experimental subject. After judgment, the patient was divided into the resistance group. At the current time point, the patient's APACHE II score was 20 points, SOFA score was 15 points, NYHA functional grade was III, CPSS score was 8 points, CCI score was 5 points, and the patient's disability coefficient was The calculation formula is as follows: ; In the formula, represents the evaluation weight for APACHE II score, represents the evaluation weight for SOFA score, represents the assessment weight for NYHA functional class, Represents the evaluation weight for CPSS score, represents the evaluation weight for CCI score, represents the evaluation weight for the patient's age, ,according to , , , , and Weight, the obstacle coefficient of the patient is calculated as .

[0021] Example 2: In this experiment, a patient with cardiovascular disease was selected as the experimental subject. After testing, at the current time point, the patient's heart rate was 75bpm, blood oxygen saturation was 95%, blood pressure was 93.33mmHg, and body temperature was 36.5℃. At the next time point, the patient's heart rate was 85bpm, blood oxygen saturation was 92%, blood pressure was 100mmHg, and body temperature was 36.8℃. The patient's monitoring data set The calculation formula is as follows: ; In the formula, Represents the change in heart rate between two time points. % represents the change in blood oxygen saturation between two time points. Indicates Patients at time point Blood pressure during rehabilitation training, mmHg represents the change in blood pressure between two time points. ℃ represents the change in body temperature between two time points.

[0022] Although embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that various changes, modifications, substitutions and variations may be made to the embodiments without departing from the principles and spirit of the present invention, and that the scope of the present invention is defined by the appended claims and their equivalents.

Claims

1. A rehabilitation medical training management system, characterized in that: Including medical collection module and intelligent evaluation module; The medical acquisition module is composed of a patient data unit, a rehabilitation data unit and a real-time data unit. The patient data unit is connected to a database through a network to collect a patient data set, and the patient data set includes management data of all patients. The rehabilitation data unit is connected to a remote monitoring device through a network to collect a rehabilitation data set, and the rehabilitation data set includes rehabilitation data of all patients. The real-time data unit is connected to a remote monitoring device through a network to collect a real-time data set, and the real-time data set includes monitoring data of the patient's training environment. The intelligent assessment module consists of a disease analysis unit, a training assessment unit and a rehabilitation management unit. The disease analysis unit divides the patient data set into resistant groups and susceptible groups according to the age of each patient, analyzes the severity of each patient's physiological disorder, and generates a corresponding disorder coefficient. The condition analysis unit is provided with a monitoring cycle of fixed duration. , analyze the barrier coefficient of each patient The changing trend of The training evaluation unit counts the monitoring period according to the rehabilitation data set and the real-time data set. The changes in the patient's physiological parameters generate corresponding monitoring data sets. , and analyze the load factor of each patient during rehabilitation training The rehabilitation management unit is set with a fixed range of resistance barrier thresholds , Susceptibility threshold , Fluctuation threshold , Heart rate threshold , blood oxygen saturation threshold , blood pressure threshold , temperature threshold and load threshold , combined with the barrier coefficient , Volatility , Monitoring Data Group and load factor , determine whether the patient has the physical condition to undergo rehabilitation training, whether the exercise intensity during rehabilitation training is overloaded, and output corresponding training suggestions.

2. A rehabilitation medical training management system according to claim 1, characterized in that: The expression of the patient dataset is , to First to Second Management data of patients, including APACHE II score, SOFA score, NYHA functional class, CPSS score and CCI score. Indicates the age of each patient.

3. A rehabilitation medical training management system according to claim 2, characterized in that: The expression of the rehabilitation data set is: , to First to Second The rehabilitation data of patients, the rehabilitation data is the treatment planning duration, Indicates the length of time each patient has completed rehabilitation training.

4. A rehabilitation medical training management system according to claim 3, characterized in that: The expression of the real-time data set is: , to First to Second The monitoring data of patients during rehabilitation training included WBGT index, heart rate, blood oxygen saturation, blood pressure, body temperature, movement amplitude and movement acceleration. Indicates the specific time for obtaining the monitoring data of each patient.

5. A rehabilitation medical training management system according to claim 4, characterized in that: The obstacle coefficient The calculation process is as follows: Extract the patient data set The administrative data of the patients and The APACHE II score of the patients was , will The SOFA scores of patients were marked as , will The NYHA functional class of the patients was , will The CPSS scores of the patients were marked as , will The CCI scores of the patients are marked as , will The age of the patients is marked as ; like , divided into resistant groups; ； In the formula, represents the evaluation weight for APACHE II score, represents the evaluation weight for SOFA score, represents the assessment weight for NYHA functional class, Represents the evaluation weight for CPSS score, represents the evaluation weight for CCI score, represents the evaluation weight for the patient's age, , Indicates according to , , , , and Weight, calculate the Disability coefficient of patients ; like or , divided into susceptible groups; ； In the formula, represents the evaluation weight for APACHE II score, represents the evaluation weight for SOFA score, represents the assessment weight for NYHA functional class, Represents the evaluation weight for CPSS score, represents the evaluation weight for CCI score, represents the evaluation weight for the patient's age, , represents the amplification factor, Indicates according to , , , , and Weight, calculate the Disability coefficient of patients .

6. A rehabilitation medical training management system according to claim 5, characterized in that: The volatility The calculation process is as follows: Statistical monitoring cycle within, no. Disability coefficient of patients , and marked as , to Respectively Patients from the first time point to the Obstacle coefficient at each time point; ； ； In the formula, Indicates monitoring cycle within, no. The average value of the disability coefficient of the patients, Indicates Patients in The obstacle coefficient at each time point is According to the variance formula, the first Fluctuation rate of the disorder coefficient for each patient .

7. A rehabilitation medical training management system according to claim 6, characterized in that: The monitoring data set The calculation process is as follows: According to the real-time data set, extract the The monitoring data of patients will be The heart rates of the patients were marked as , will The blood oxygen saturation of patients is marked as , will The blood pressure of patients is marked as , will The patient's temperature is marked as ; ； In the formula, Indicates Patients at time point Heart rate during rehabilitation training, Indicates Patients at time point Heart rate during rehabilitation training, Represents the change in heart rate between two time points. Indicates Patients at time point Blood oxygen saturation during rehabilitation training, Indicates Patients at time point Blood oxygen saturation during rehabilitation training, Indicates the change in blood oxygen saturation between two time points. Indicates Patients at time point Blood pressure during rehabilitation training, Indicates Patients at time point Blood pressure during rehabilitation training, Represents the change in blood pressure between two time points. Indicates Patients at time point Body temperature during rehabilitation training, Indicates Patients at time point Body temperature during rehabilitation training, represents the change in body temperature between two time points. represents the monitoring data set of the e-th patient.

8. A rehabilitation medical training management system according to claim 7, characterized in that: The load factor The calculation process is as follows: According to the rehabilitation data set, The treatment planning duration of patients is marked as , will The duration of rehabilitation training completed by patients is marked as ; According to the real-time data set, The WBGT index of the training environment for the patients is marked as , will The range of motion of the patients during rehabilitation training was marked as , will The movement acceleration of the patients during rehabilitation training is marked as ; ； ； In the formula, It represents the percentage of training time to treatment planning time, which is Completion progress of rehabilitation training for patients , represents the evaluation weight of the completion progress of rehabilitation training, Represents the evaluation weight of the WBGT index for the training environment, represents the evaluation weight for the motion amplitude, Represents the evaluation weight for motion acceleration, , Indicates according to , , and Weight, calculate the The load factor of the patients undergoing rehabilitation training .

9. A rehabilitation medical training management system according to claim 8, characterized in that: The barrier coefficient of patients in the resistant population Exceeding the resistance barrier threshold , indicating that the patient does not have the physical condition to undergo rehabilitation training, and it is recommended that the patient continue to receive drug treatment. The obstacle coefficient of the patient in the resistance group Included in resistance barrier threshold , and volatility Included in volatility threshold , indicating that the patient has the physical condition to undergo rehabilitation training, and it is recommended that the patient choose a light functional training program. The obstacle coefficient of the patient in the susceptible group is Exceeding the threshold of susceptible disorder , indicating that the patient does not have the physical condition to undergo rehabilitation training, and it is recommended that the patient continue to receive drug treatment. The disability coefficient of the patient in the susceptible group Included in the Susceptibility Threshold , and volatility Included in volatility threshold , it means that the patient has the physical condition to undergo rehabilitation training, and it is recommended that the patient choose a light functional training program.

10. A rehabilitation medical training management system according to claim 9, characterized in that: The monitoring data set The heart rate change exceeds the heart rate threshold , The change in blood oxygen saturation exceeds the blood oxygen saturation threshold , Blood pressure change exceeds the blood pressure threshold , the temperature change exceeds the temperature threshold or load factor Exceeding load threshold It means that the patient's exercise intensity during rehabilitation training has been overloaded. It is recommended that the patient slowly stop exercising and get enough rest.

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