Exercise program reactivity prediction model and modeling method, electronic equipment
An exercise plan and prediction model technology, applied in the field of exercise plan responsiveness prediction model and modeling, can solve problems such as uncontrollable exercise plan effect, poor patient improvement effect, extensive exercise plan, etc., to improve the effect of exercise intervention.
Active Publication Date: 2021-12-07
北京动亮健康科技有限公司
View PDF5 Cites 0 Cited by
- Summary
- Abstract
- Description
- Claims
- Application Information
AI Technical Summary
Problems solved by technology
[0003] (1) The effect of the exercise program is uncontrollable. Before prescribing the exercise program, the doctor only knows that the exercise program can improve the patient's metabolic condition, but it is not clear to what extent the exercise program can improve
[0004] (2) The current exercise program cannot be targeted. For patients with the same disease, the exercise program prescribed by the doctor may be the same, but due to the differences in other conditions of the individual, the actual effect is different. Therefore, for patients with the same disease The same exercise program, some patients have a good improvement effect, and some patients have a poor improvement effect
[0005] (3) The exercise program is too extensive. The doctor prescribes the user’s exercise intensity, exercise time, exercise frequency, and exercise type according to the guidelines, and fails to quantify the patient’s more exercise information, such as the choice of exercise time and excessive exercise. Time, ineffective exercise time, exercise efficiency and the impact of evaluating these exercise information on the intervention effect
Method used
the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
View moreImage
Smart Image Click on the blue labels to locate them in the text.
Smart ImageViewing Examples
Examples
Experimental program
Comparison scheme
Effect test
Embodiment Construction
[0051] Example embodiments will now be described more fully with reference to the accompanying drawings. Example embodiments may, however, be embodied in many forms and should not be construed as limited to the examples set forth herein; rather, these embodiments are provided so that the description of the invention will be thorough and complete and will fully convey the concept of example embodiments. communicated to those skilled in the art. The drawings are merely schematic illustrations of the invention and are not necessarily drawn to scale.
[0052] Furthermore, the described features, structures, or characteristics may be combined in any suitable manner in one or more embodiments. In the following description, numerous specific details are provided in order to give a thorough understanding of embodiments of the invention. However, those skilled in the art will appreciate that one or more of the specific details may be omitted in practicing the technical solution of th...
the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to View More PUM
Login to View More Abstract
The invention discloses a sports program reactivity prediction model, a modeling method, and an electronic device. The modeling method of the sports program reactivity prediction model includes the following steps: S101: collect training data and perform preprocessing, and the collection training data The method of data preprocessing includes: collecting the indicators and exercise information data of patients with metabolic diseases; obtaining the effect of exercise programs by evaluating the indicators of patients with metabolic diseases; and screening out significant influencing factors by analyzing the effects of exercise programs; S102: Setting XGBoost training Parameters; S103: Take the significant influencing factors and motion information data as the input of the model, take the effect of the motion plan as the output of the model, and use the ten-fold cross-validation method to train the model based on the XGBoost algorithm; S104: Use the trained model in step S103 Make predictions. The predictive model established by the invention can assist doctors to form more effective exercise schemes and improve the effect of exercise intervention.
Description
technical field [0001] The invention relates to the fields of biomedical engineering technology and sports health, in particular to a predictive model and a modeling method for the reactivity of a sports program. Background technique [0002] The role of exercise in the prevention and treatment of metabolic diseases cannot be ignored. Studies have shown that moderate exercise can improve blood sugar, blood pressure and blood lipids in metabolic diseases. However, the current exercise programs prescribed by doctors have the following problems: [0003] (1) The effect of the exercise program is uncontrollable. Before prescribing the exercise program, the doctor only knows that the exercise program can improve the patient's metabolic condition, but it is not clear to what extent the exercise program can be improved. [0004] (2) The current exercise program cannot be targeted. For patients with the same disease, the exercise program prescribed by the doctor may be the same, bu...
Claims
the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to View More Application Information
Patent Timeline
Login to View More Patent Type & Authority Patents(China)
IPC IPC(8): G16H20/30G16H50/30G16H50/50G16H50/70G06N20/00G06K9/62
CPCG16H20/30G16H50/70G16H50/50G16H50/30G06N20/00G06F18/214
Inventor 张永亮叶骏陈娟
Owner 北京动亮健康科技有限公司