CN116564469A - Intelligent athlete physical ability monitoring system and method based on Internet of things - Google Patents
Intelligent athlete physical ability monitoring system and method based on Internet of things Download PDFInfo
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Abstract
The invention provides an intelligent athlete physical ability monitoring system and method based on the Internet of things, comprising the following steps: setting and adjusting parameters of a preset first model according to physique and health information of a user, movement environment and position information and movement item types, monitoring and early warning physical stamina by using the obtained model, generating corresponding suggestions and strategies, updating and replacing the model based on related data information in a movement process, and monitoring the physical stamina of the user based on the updated and replaced model; the initial exercise plan is formulated according to the physique and health information of the user, and the exercise plan is adjusted wholly and locally based on feedback of the exercise plan, objective data information and individual physical ability increase and decrease conditions of the user in the exercise process, collected after the exercise is finished, so that the exercise effect is improved, and the training confidence of athletes is helped.
Description
Technical Field
The invention relates to the field of physical ability monitoring, in particular to an athlete physical ability intelligent monitoring system and method based on the Internet of things.
Background
In recent years, people's attention to health has been increasingly focused, and enthusiasm for promoting health by physical exercise has been increasingly increased. However, the physical exercise is a double-edged sword, which helps us improve health and physical quality and can cause problems such as shortness of breath, palpitation, chest distress, irregular heartbeat and the like. Investigation shows that with age, the risk of chest distress, chest pain, dyspnea and other problems in exercise is multiplied. Therefore, in the process of exercise, the physical ability of people is intelligently monitored, so that the exercise safety is improved.
The existing physical ability monitoring system mainly has the following problems: firstly, the external environment and the geographic position are different in the movement process, the corresponding physiological parameter threshold levels are different, for example, the corresponding body temperature and heartbeat threshold levels are higher than those in the lower temperature environment when the user moves in the higher temperature environment, and the threshold level of the respiratory frequency is higher than that in the lower elevation environment when the user moves at the higher elevation; secondly, the physique level and the health condition of each person are unique, and as the number of sports increases, the physical energy level is continuously improved, and the corresponding physiological parameter threshold level is unique and time-varying; in addition, in order to improve the exercise effect of the user, a proper exercise plan is often required to be formulated, so that automatic recommendation of the exercise plan and subsequent automatic adjustment of the exercise plan are important, and can effectively help athletes to find physical superiority and weaknesses and cultivate confidence.
Disclosure of Invention
The invention aims to provide an intelligent athlete physical ability monitoring system and method based on the Internet of things, which are used for solving the technical problems in the background technology.
In order to achieve the above purpose, the specific technical scheme adopted by the invention is as follows:
an athlete physical ability intelligent monitoring method based on the Internet of things comprises the following steps:
s1: collecting physique and health information, exercise environment and position information and exercise item types of a user, and setting and adjusting parameters of a preset first model;
s2: monitoring and early warning the physical state by using the obtained model, and generating corresponding suggestions and strategies;
s3: updating and replacing the model based on the related data information in the movement process;
s4: monitoring the physical performance state of the user based on the updated and replaced model;
s5: making an initial exercise plan according to physique and health information of a user;
s6: and (3) carrying out overall and local adjustment on the exercise plan based on feedback of the user on the exercise plan, objective data information in the exercise process and the increase and decrease of the physical stamina, which are collected after the exercise is finished.
The user physique information may be: height, weight, sex, age, body fat rate, vital capacity; the health information may be: whether suffering from heart disease, lung disease, arthritis, hypertension, hypotension, cardiovascular and cerebrovascular diseases, and whether having undergone surgery; the movement environment information may be: temperature, humidity, altitude, wind speed, air pressure; the movement position information may be: longitude and latitude; the sports categories may be: swimming, diving, climbing mountain, riding and running;
the first model is an SPC control chart model, and parameters of the first model comprise: center line, upper control limit, lower control limit;
the S1: collecting physique and health information, exercise environment and position information and exercise item types of a user, setting and adjusting parameters of a preset first model, and comprising the following steps:
the control module sends the acquired physique and health information, the exercise environment and position information and the exercise item type of the user to the cloud server, and the cloud server sets and adjusts parameters of the first model based on the information and sends the set and adjusted model to the control module;
the S2: monitoring and early warning the physical state by using the obtained model, and generating corresponding suggestions and strategies; comprising the following steps:
the method comprises the steps of sending collected environment, position, physiological information and motion information in a motion process to a control module, extracting and processing various data information by the control module based on a sliding time window algorithm, inputting the obtained data to an SPC control chart model, detecting whether overrun conditions exist in various parameters, comprehensively weighting and calculating the overrun conditions of the various parameters, and carrying out early warning of different grades and generating corresponding suggestions and strategies based on the obtained values;
the physiological information includes: heart rate, blood oxygen concentration, respiratory rate, blood pressure, and body temperature; the motion information includes: speed, acceleration;
the step of carrying out early warning of different grades and generating corresponding suggestions and strategies based on the obtained values comprises the following steps: when the value is smaller, prompting the type and proportion of the overrun of the physiological parameter of the user on a display; when the value is in the middle, corresponding advice is given on the display; when the value is larger, an emergency rescue signal is sent to the cloud server, and the safety equipment is started;
the method further comprises the steps of: detecting whether an intelligent physical ability monitoring terminal exists nearby, and simultaneously transmitting emergency rescue information to the intelligent physical ability monitoring terminal nearby and a cloud server when the intelligent physical ability monitoring terminal exists nearby;
the rescue information comprises user positions, information and abnormal types;
the S3: updating and replacing the model based on the related data information in the movement process; comprising the following steps:
the control module acquires environment, position, physiological information and motion information in the motion process in real time, uploads the data information to the cloud server after the motion is finished, and a physical ability evaluation model updating module on the cloud server extracts and analyzes related parameters to generate a central line, an upper control limit and a lower control limit parameter of a new SPC control chart model and sends new parameter information to the control module;
the S5: making an initial exercise plan according to physique and health information of a user; comprising the following steps:
the control module sends the acquired physique and health information of the user to the cloud server, and the exercise plan making module in the cloud server makes an initial exercise plan based on the information;
the S6: based on feedback of the user on the exercise plan, objective data information and individual physical ability increase and decrease conditions in the exercise process, which are collected after the exercise is finished, the exercise plan is wholly and locally adjusted; comprising the following steps:
after the exercise is finished, subjective feedback information of the user on the exercise plan is collected by using a display and an interaction module; the subjective feedback information is sent to a cloud server, and a motion plan adjusting module in the cloud server adjusts corresponding feedback grades on the whole based on the subjective feedback information;
the cloud server analyzes physiological and motion information in the motion process and locally adjusts a motion plan based on an analysis result; after the monitoring terminal monitors and reminds that the speed, the acceleration or the physiological parameter exceeds the limit, the user still keeps higher-level speed, acceleration or physiological parameter in a plurality of time ranges, which indicates that the movement plan intensity in the time range needs to be further increased, and corresponding adjustment amplitude is calculated based on the overrun proportion; the monitoring terminal monitors and reminds that the speed and the acceleration are too low, and then the user keeps keeping the speed and the acceleration at a lower level, which indicates that the intensity of the movement plan in the time range needs to be regulated down; for the time range of the speed, the acceleration or the parameters in a reasonable range, the exercise planning intensity is proportionally increased based on the increase and decrease of the physical ability of the person;
the motion plan intensity can be a motion speed and/or acceleration and/or motion frequency and/or motion amplitude weighted calculated value;
after the exercise is finished, weighting calculation is carried out based on the obtained SPC control chart center line size, exercise duration, consumed calories and exercise distance of the corresponding parameters of each physiological and exercise information, corresponding physical ability scores are given, and the increase and decrease conditions of the physical ability of the individual are calculated based on the difference value of the scores of the two exercise processes.
According to another aspect of the invention, the invention also provides an athlete physical ability intelligent monitoring system based on the Internet of things, which comprises a monitoring terminal, a safety device and a cloud server, wherein the monitoring terminal comprises an information acquisition module, a control module, an interaction module, a display and a storage module, and the information acquisition module comprises a temperature sensor, a humidity sensor, a height sensor, a position sensor, an anemometer, a barometer, a respiratory rate sensor, a heart rate sensor, a sphygmomanometer, an oximetry meter, a thermometer, a speed sensor and an acceleration sensor;
the interaction module can be voice or touch control;
the storage module is used for storing the SPC control chart model and related parameter information;
the display is used for displaying a recommendation curve and a real-time curve of related parameter information, prompting corresponding overrun early warning information, displaying corresponding suggestions and strategies, selecting a sport item category by a user, and collecting feedback of the user for a sport plan after the sport is finished;
before exercise, the information acquisition module acquires physique and health information, exercise environment and position information and exercise item types of a user, and sets and adjusts parameters of a preset first model; comprising the following steps:
collecting physique and health information, exercise environment and position information of a user and exercise item types, sending the collected data information to a cloud server by a control module, setting and adjusting parameters of a first model by the cloud server, and sending the set and adjusted model to the control module;
the cloud server stores the mapping relation between the physique and health information of the user, the movement environment and position information and the movement item type and the parameters of the first model, and realizes the adjustment of the parameters of the first model based on the mapping relation;
during movement, the control module monitors and pre-warns the physical state by using the obtained model and generates corresponding suggestions and strategies; comprising the following steps:
the acquired environment, position, physiological information and motion information are sent to a control module, the control module extracts and processes various data information based on a sliding time window algorithm, the obtained data are input to an SPC control chart model, whether various parameters have overrun conditions or not is detected, comprehensive weighting calculation is carried out on the overrun conditions of the various parameters, and early warning of different grades and corresponding suggestion and strategy generation are carried out based on the obtained values;
the step of carrying out early warning of different grades and generating corresponding suggestions and strategies based on the obtained values comprises the following steps: when the value is smaller, prompting the type and proportion of the overrun of the physiological parameter of the user on a display; when the numerical value is in the middle, corresponding advice is given on the display, and the stride can be reduced and the stride frequency can be reduced; when the value is larger, an emergency rescue signal is sent to the cloud server, and safety equipment is started, so that an airbag can be popped up to float out of the water, riding resistance is reduced, and oxygen supply rate is increased;
during movement, the recommendation curve and the real-time curve of the environment, the position, the physiological information and the movement information in the movement process are displayed on a display in real time, corresponding overrun early warning information is prompted on the display, and corresponding suggestions and strategies are displayed;
detecting whether an intelligent physical ability monitoring terminal exists nearby when an emergency occurs, and simultaneously transmitting emergency rescue information to the intelligent physical ability monitoring terminal nearby and a cloud server when the emergency exists, wherein the rescue information comprises user positions, information and abnormal types;
after the movement, updating and replacing the model based on the related data information in the movement process; comprising the following steps:
the control module uploads environmental, position, physiological information and motion information in a real-time acquisition motion process to the cloud server, the physical ability evaluation model updating module on the cloud server extracts and analyzes related parameters, generates a central line, an upper control limit and a lower control limit parameter of a new SPC control chart model, and sends new parameter information to the control module to update and replace model parameters;
the cloud server can also make an initial exercise plan according to the physique and health information of the user, and can carry out overall and local adjustment on the exercise plan based on feedback of the exercise plan, objective data information and individual physical ability increase and decrease conditions of the user in the exercise process, which are collected after the exercise is finished;
the initial exercise plan is formulated according to the physique and health information of the user; comprising the following steps:
the control module sends the acquired physique and health information of the user to the cloud server, and the exercise plan making module in the cloud server makes an initial exercise plan based on the information;
the overall and local adjustment is carried out on the exercise plan based on feedback of the user on the exercise plan, objective data information in the exercise process and the increase and decrease of the physical stamina, which are collected after the exercise is finished; comprising the following steps:
after the exercise is finished, subjective feedback information of the user on the exercise plan is collected by utilizing a display and an interaction module, wherein the subjective feedback information can be the evaluation grade set by the user on the exercise duration, the exercise intensity and the rest interval; the subjective feedback information is sent to a cloud server, and a movement plan adjusting module in the cloud server adjusts the movement plan to the grade on the basis of the evaluation grade;
the cloud server analyzes physiological and motion information in the motion process and locally adjusts a motion plan based on an analysis result; after the monitoring terminal monitors and reminds that the speed, the acceleration or the physiological parameter exceeds the limit, the user still keeps higher-level speed, acceleration or physiological parameter in a plurality of time ranges, which indicates that the movement plan intensity in the time range needs to be further increased, and corresponding adjustment amplitude is calculated based on the overrun proportion; the monitoring terminal monitors and reminds that the speed and the acceleration are too low, and then the user keeps keeping the speed and the acceleration at a lower level, which indicates that the intensity of the movement plan in the time range needs to be regulated down; for the time range of the speed, the acceleration or the parameters in a reasonable range, the exercise planning intensity is proportionally increased based on the increase and decrease of the physical ability of the person;
after the exercise is finished, weighting calculation is carried out on the basis of the obtained SPC control chart center line size, exercise duration, consumed calories and exercise distance of the corresponding parameters of each piece of physiological and exercise information, corresponding physical ability scores are given, and the increase and decrease conditions of the physical ability of the individual are calculated on the basis of the difference value of the scores of the two successive exercise processes;
the monitoring terminal can be an intelligent watch and glasses, and also can be a mobile terminal fixed on a bicycle.
The invention provides an intelligent athlete physical ability monitoring system and method based on the Internet of things, comprising the following steps: setting and adjusting parameters of a preset first model according to physique and health information of a user, movement environment and position information and movement item types, monitoring and early warning physical stamina by using the obtained model, generating corresponding suggestions and strategies, updating and replacing the model based on related data information in a movement process, and monitoring the physical stamina of the user based on the updated and replaced model; the method is characterized in that an initial exercise plan is formulated according to physique and health information of a user, and the exercise plan is adjusted wholly and locally based on feedback of the exercise plan, objective data information and individual physical ability increase and decrease conditions of the user in the exercise process, which are collected after the exercise is finished, so that the exercise plan is formulated and adjusted automatically, physical ability advantages and weak links are found by athletes, and confidence is cultivated.
Drawings
Fig. 1 is a schematic structural diagram of an intelligent athlete physical ability monitoring system based on the internet of things;
FIG. 2 is a flow chart of an intelligent athlete physical ability monitoring method based on the Internet of things;
fig. 3 is a schematic information interaction diagram of a plurality of monitoring terminals and a cloud server.
Detailed Description
The present invention will be described in further detail with reference to the drawings and examples, in order to make the objects, technical solutions and advantages of the present invention more apparent. The specific embodiments described herein are to be considered in an illustrative sense only and are not intended to limit the invention. In addition, the technical features of the embodiments of the invention described below can be combined with one another as long as they do not conflict with one another.
An athlete physical ability intelligent monitoring method based on the Internet of things comprises the following steps:
s1: collecting physique and health information, exercise environment and position information and exercise item types of a user, and setting and adjusting parameters of a preset first model;
s2: monitoring and early warning the physical state by using the obtained model, and generating corresponding suggestions and strategies;
s3: updating and replacing the model based on the related data information in the movement process;
s4: monitoring the physical performance state of the user based on the updated and replaced model;
s5: making an initial exercise plan according to physique and health information of a user;
s6: and (3) carrying out overall and local adjustment on the exercise plan based on feedback of the user on the exercise plan, objective data information in the exercise process and the increase and decrease of the physical stamina, which are collected after the exercise is finished.
The user physique information may be: height, weight, sex, age, body fat rate, vital capacity; the health information may be: whether suffering from heart disease, lung disease, arthritis, hypertension, hypotension, cardiovascular and cerebrovascular diseases, and whether having undergone surgery; the movement environment information may be: temperature, humidity, altitude, wind speed, air pressure; the movement position information may be: longitude and latitude; the sports categories may be: swimming, diving, climbing mountain, riding and running;
the information and the types of the sports items can be acquired based on a sensor, and can also be input by a user through an interaction module; in an embodiment, the location information may be obtained based on a GPS or IP address;
the first model is an SPC control chart model, and parameters of the first model comprise: center line, upper control limit, lower control limit;
the SPC control chart is a functional chart for distinguishing normal fluctuation and abnormal fluctuation, is commonly applied to statistics of field quality management, can be used for distinguishing whether a process has obvious change or abnormal events by using a limit, has higher recognition accuracy on fluctuation conditions of time-varying signals due to the existence of the upper limit and the lower limit, and can intuitively and accurately display abnormal information of physical stamina related parameters for people;
the S1: collecting physique and health information, exercise environment and position information and exercise item types of a user, setting and adjusting parameters of a preset first model, and comprising the following steps:
the control module sends the acquired physique and health information, the exercise environment and position information and the exercise item type of the user to the cloud server, and the cloud server sets and adjusts parameters of the first model based on the information and sends the set and adjusted model to the control module;
the first model is an initial model which is obtained based on the exercise and physiological parameter data training of a plurality of people;
the cloud server stores the mapping relation between the physique and health information of the user, the movement environment and position information and the movement item type and the parameters of the first model, and realizes the adjustment of the parameters of the first model based on the mapping relation; the mapping relationship may be linear or nonlinear, and may be in a form of a list or a machine learning model, or may be in other forms, which is not limited herein;
the S2: monitoring and early warning the physical state by using the obtained model, and generating corresponding suggestions and strategies; comprising the following steps:
the method comprises the steps of sending collected environment, position, physiological information and motion information in a motion process to a control module, extracting and processing various data information by the control module based on a sliding time window algorithm, inputting the obtained data to an SPC control chart model, detecting whether various parameters have overrun conditions, realizing real-time monitoring of physical energy states of users, comprehensively weighting and calculating overrun conditions of the various parameters, and carrying out early warning of different grades and generating corresponding suggestions and strategies based on the obtained values;
the overrun condition includes being above an upper control limit or below a lower control limit;
the physiological information includes: heart rate, blood oxygen concentration, respiratory rate, blood pressure, and body temperature; the motion information includes: speed, acceleration;
the step of carrying out early warning of different grades and generating corresponding suggestions and strategies based on the obtained values comprises the following steps: when the value is smaller, prompting the type and proportion of the overrun of the physiological parameter of the user on a display; when the numerical value is in the middle, corresponding advice is given on the display, and the stride can be reduced and the stride frequency can be reduced; when the value is larger, an emergency rescue signal is sent to the cloud server, and safety equipment is started, so that an airbag can be popped up to float out of the water, riding resistance is reduced, and oxygen supply rate is increased;
the method further comprises the steps of: during exercise, the recommendation curve and the real-time curve of the environment, the position, the physiological information and the exercise information in the exercise process are displayed on the display in real time, corresponding overrun early warning information is prompted on the display, corresponding suggestions and strategies are displayed, and people can conveniently view and master exercise related information in real time;
the method further comprises the steps of: detecting whether an intelligent physical ability monitoring terminal exists nearby, and simultaneously transmitting emergency rescue information to the intelligent physical ability monitoring terminal nearby and a cloud server when the intelligent physical ability monitoring terminal exists nearby, wherein the rescue information comprises user positions, information and abnormal types, so that people can catch up with rescue as soon as possible;
the S3: updating and replacing the model based on the related data information in the movement process; comprising the following steps:
in the movement process, the control module acquires environment, position, physiological information and movement information in the movement process in real time and stores the acquired data information into the storage module; after the movement is finished, uploading the data information to a cloud server, extracting and analyzing related parameters by a physical ability evaluation model updating module on the cloud server, generating a central line, an upper control limit and a lower control limit parameter of a new SPC control chart model, and sending new parameter information to a control module to update and replace model parameters;
the S5: making an initial exercise plan according to physique and health information of a user; comprising the following steps:
the control module sends the acquired physique and health information of the user to the cloud server, and the exercise plan making module in the cloud server makes an initial exercise plan based on the information;
the S6: based on feedback of the user on the exercise plan, objective data information and individual physical ability increase and decrease conditions in the exercise process, which are collected after the exercise is finished, the exercise plan is wholly and locally adjusted; comprising the following steps:
after the exercise is finished, subjective feedback information of the user on the exercise plan is collected by utilizing a display and an interaction module, wherein the subjective feedback information can be the evaluation grade set by the user on the exercise duration, the exercise intensity and the rest interval; for example, each item may be set to 6 levels; the subjective feedback information is sent to a cloud server, and a motion plan adjusting module in the cloud server adjusts the motion plan to the grade on the whole based on the evaluation grade, for example, the motion strength of the grade corresponding proportion can be increased/decreased, the motion duration of the grade corresponding proportion can be shortened/prolonged, the rest interval of the grade corresponding proportion can be increased/decreased, or the rest interval can be kept unchanged;
the cloud server analyzes physiological and motion information in the motion process and locally adjusts a motion plan based on an analysis result; after the monitoring terminal monitors and reminds that the speed, the acceleration or the physiological parameter exceeds the limit, the user still keeps higher-level speed, acceleration or physiological parameter in a plurality of time ranges, which indicates that the movement plan intensity in the time range needs to be further increased, and corresponding adjustment amplitude is calculated based on the overrun proportion; the monitoring terminal monitors and reminds that the speed and the acceleration are too low, and then the user keeps keeping the speed and the acceleration at a lower level, which indicates that the intensity of the movement plan in the time range needs to be regulated down; for the time range of the speed, the acceleration or the parameters in a reasonable range, the exercise planning intensity is proportionally increased based on the increase and decrease of the physical ability of the person;
the motion plan intensity can be a motion speed and/or acceleration and/or motion frequency and/or motion amplitude weighted calculated value;
in addition, after the exercise is finished, weighting calculation is carried out on the basis of the obtained SPC control chart center line size, exercise duration, consumed calories and exercise distance of the corresponding parameters of the physiological and exercise information, corresponding physical ability scores are given, and the increase and decrease conditions of the physical ability of the individual are calculated on the basis of the difference value of the scores of the two exercise processes;
the method further comprises the steps of: the cloud server establishes a sports file and a physical stamina image according to the collected sports related data information, so that the follow-up inquiry of the sports data is facilitated, and the physical superiority and weak links of individuals are checked;
it is expected that after the overall and local adjustment of the exercise program is performed based on the feedback of the user on the exercise program, the objective data information in the exercise process and the physical stamina increase and decrease condition collected after the exercise is finished, the central line, the upper control limit and the lower control limit parameters of the SPC control chart model can be correspondingly and automatically adjusted.
According to another aspect of the invention, as shown in fig. 1, the system comprises a monitoring terminal, a safety device and a cloud server, wherein the monitoring terminal comprises an information acquisition module, a control module, an interaction module, a display and a storage module, and the information acquisition module comprises a temperature sensor, a humidity sensor, a height sensor, a position sensor, an anemometer, a barometer, a respiratory rate sensor, a heart rate sensor, a sphygmomanometer, an oximeter, a thermometer, a speed sensor and an acceleration sensor;
the interaction module can be voice or touch control;
the storage module is used for storing the SPC control chart model and related parameter information;
the display is used for displaying a recommendation curve and a real-time curve of related parameter information, prompting corresponding overrun early warning information, displaying corresponding suggestions and strategies, selecting a sport item category by a user, and collecting feedback of the user for a sport plan after the sport is finished;
as shown in fig. 2, before exercise, the information acquisition module acquires physique and health information, exercise environment and position information and exercise item types of a user, and sets and adjusts parameters of a preset first model; comprising the following steps:
collecting physique and health information, exercise environment and position information of a user and exercise item types, sending the collected data information to a cloud server by a control module, setting and adjusting parameters of a first model by the cloud server, and sending the set and adjusted model to the control module;
the user physique information may be: height, weight, sex, age, body fat rate, vital capacity; the health information may be: whether suffering from heart disease, lung disease, arthritis, hypertension, hypotension, cardiovascular and cerebrovascular diseases, and whether having undergone surgery; the movement environment information may be: temperature, humidity, altitude, wind speed, air pressure; the movement position information may be: longitude and latitude; the sports categories may be: swimming, diving, climbing mountain, riding and running;
the location information may be obtained based on a GPS or IP address;
the first model is an SPC control chart model, and parameters of the first model comprise: center line, upper control limit, lower control limit;
the first model is an initial model which is obtained based on the exercise and physiological parameter data training of a plurality of people;
the cloud server stores the mapping relation between the physique and health information of the user, the movement environment and position information and the movement item type and the parameters of the first model, and realizes the adjustment of the parameters of the first model based on the mapping relation;
during movement, the control module monitors and pre-warns the physical state by using the obtained model and generates corresponding suggestions and strategies; comprising the following steps:
the acquired environment, position, physiological information and motion information are sent to a control module, the control module extracts and processes various data information based on a sliding time window algorithm, the obtained data are input to an SPC control chart model, whether various parameters have overrun conditions or not is detected, real-time monitoring of physical energy states of users is achieved, comprehensive weighting calculation of overrun conditions of the various parameters is achieved, and early warning of different levels and corresponding advice and strategy generation are carried out based on the obtained values;
the overrun condition includes being above an upper control limit or below a lower control limit;
the physiological information includes: heart rate, blood oxygen concentration, respiratory rate, blood pressure, and body temperature; the motion information includes: speed, acceleration;
the step of carrying out early warning of different grades and generating corresponding suggestions and strategies based on the obtained values comprises the following steps: when the value is smaller, prompting the type and proportion of the overrun of the physiological parameter of the user on a display; when the numerical value is in the middle, corresponding advice is given on the display, and the stride can be reduced and the stride frequency can be reduced; when the value is larger, an emergency rescue signal is sent to the cloud server, and safety equipment is started, so that an airbag can be popped up to float out of the water, riding resistance is reduced, and oxygen supply rate is increased;
during exercise, the recommendation curve and the real-time curve of the environment, the position, the physiological information and the exercise information in the exercise process are displayed on the display in real time, corresponding overrun early warning information is prompted on the display, corresponding suggestions and strategies are displayed, and people can conveniently view and master exercise related information in real time;
as shown in fig. 3, the plurality of monitoring terminals and the cloud server can communicate with each other, when an emergency occurs, whether the intelligent physical fitness monitoring terminals exist nearby is detected, emergency rescue information is simultaneously sent to the intelligent physical fitness monitoring terminals nearby and the cloud server when the intelligent physical fitness monitoring terminals exist, the rescue information comprises user positions, information and abnormal types, and people can conveniently and quickly drive away rescue;
after the movement, updating and replacing the model based on the related data information in the movement process; comprising the following steps:
the control module uploads environmental, position, physiological information and motion information in a real-time acquisition motion process to the cloud server, the physical ability evaluation model updating module on the cloud server extracts and analyzes related parameters, generates a central line, an upper control limit and a lower control limit parameter of a new SPC control chart model, and sends new parameter information to the control module to update and replace model parameters;
the cloud server can also make an initial exercise plan according to the physique and health information of the user, and can carry out overall and local adjustment on the exercise plan based on feedback of the exercise plan, objective data information and individual physical ability increase and decrease conditions of the user in the exercise process, which are collected after the exercise is finished;
the initial exercise plan is formulated according to the physique and health information of the user; comprising the following steps:
the control module sends the acquired physique and health information of the user to the cloud server, and the exercise plan making module in the cloud server makes an initial exercise plan based on the information;
the overall and local adjustment is carried out on the exercise plan based on feedback of the user on the exercise plan, objective data information in the exercise process and the increase and decrease of the physical stamina, which are collected after the exercise is finished; comprising the following steps:
after the exercise is finished, subjective feedback information of the user on the exercise plan is collected by utilizing a display and an interaction module, wherein the subjective feedback information can be the evaluation grade set by the user on the exercise duration, the exercise intensity and the rest interval; for example, each item may be set to 6 levels; the subjective feedback information is sent to a cloud server, and a motion plan adjusting module in the cloud server adjusts the motion plan to the grade on the whole based on the evaluation grade, for example, the motion strength of the grade corresponding proportion can be increased/decreased, the motion duration of the grade corresponding proportion can be shortened/prolonged, the rest interval of the grade corresponding proportion can be increased/decreased, or the rest interval can be kept unchanged;
the cloud server analyzes physiological and motion information in the motion process and locally adjusts a motion plan based on an analysis result; after the monitoring terminal monitors and reminds that the speed, the acceleration or the physiological parameter exceeds the limit, the user still keeps higher-level speed, acceleration or physiological parameter in a plurality of time ranges, which indicates that the movement plan intensity in the time range needs to be further increased, and corresponding adjustment amplitude is calculated based on the overrun proportion; the monitoring terminal monitors and reminds that the speed and the acceleration are too low, and then the user keeps keeping the speed and the acceleration at a lower level, which indicates that the intensity of the movement plan in the time range needs to be regulated down; for the time range of the speed, the acceleration or the parameters in a reasonable range, the exercise planning intensity is proportionally increased based on the increase and decrease of the physical ability of the person;
the motion plan intensity can be a motion speed and/or acceleration and/or motion frequency and/or motion amplitude weighted calculated value;
in addition, after the exercise is finished, weighting calculation is carried out on the basis of the obtained SPC control chart center line size, exercise duration, consumed calories and exercise distance of the corresponding parameters of the physiological and exercise information, corresponding physical ability scores are given, and the increase and decrease conditions of the physical ability of the individual are calculated on the basis of the difference value of the scores of the two exercise processes;
the cloud server establishes a sports file and a physical stamina image according to the collected sports related data information, so that the follow-up inquiry of the sports data is facilitated, and the physical superiority and weak links of individuals are checked;
it is expected that after the overall and local adjustment of the exercise plan is performed based on feedback of the exercise plan, objective data information in the exercise process and the physical energy increase and decrease condition of the individual, collected after the exercise is finished, the central line, the upper control limit and the lower control limit parameters of the SPC control chart model are also subjected to corresponding automatic adjustment;
the monitoring terminal can be an intelligent watch and glasses, and also can be a mobile terminal fixed on a bicycle.
The invention provides an intelligent athlete physical ability monitoring system and method based on the Internet of things, comprising the following steps: setting and adjusting parameters of a preset first model according to physique and health information of a user, movement environment and position information and movement item types, monitoring and early warning physical stamina by using the obtained model, generating corresponding suggestions and strategies, updating and replacing the model based on related data information in a movement process, and monitoring the physical stamina of the user based on the updated and replaced model; the initial exercise plan is formulated according to the physique and health information of the user, and the exercise plan is regulated wholly and locally based on feedback of the exercise plan, objective data information and individual physical ability increase and decrease conditions of the user in the exercise process, collected after the exercise is finished, so that the exercise plan is formulated and regulated automatically.
The above is only a technical idea of the present invention, and the protection scope of the present invention is not limited by the above, and any modification made on the basis of the technical scheme according to the technical idea of the present invention falls within the protection scope of the claims of the present invention.
Claims (10)
1. An intelligent athlete physical ability monitoring method based on the Internet of things is characterized by comprising the following steps:
s1: collecting physique and health information, exercise environment and position information and exercise item types of a user, and setting and adjusting parameters of a preset first model;
s2: monitoring and early warning the physical state by using the obtained model, and generating corresponding suggestions and strategies;
s3: updating and replacing the model based on the related data information in the movement process;
s4: monitoring the physical performance state of the user based on the updated and replaced model;
s5: making an initial exercise plan according to physique and health information of a user;
s6: and (3) carrying out overall and local adjustment on the exercise plan based on feedback of the user on the exercise plan, objective data information in the exercise process and the increase and decrease of the physical stamina, which are collected after the exercise is finished.
2. The method of claim 1, wherein the first model is an SPC control chart model, and wherein the parameters of the first model include: center line, upper control limit, lower control limit.
3. The method according to claim 2, wherein said S3: updating and replacing the model based on the related data information in the movement process; comprising the following steps:
the control module acquires environment, position, physiological information and motion information in the motion process in real time, uploads the data information to the cloud server after the motion is finished, and a physical ability evaluation model updating module on the cloud server extracts and analyzes related parameters to generate a central line, an upper control limit and a lower control limit parameter of a new SPC control chart model and sends new parameter information to the control module.
4. The method according to claim 2, wherein the method further comprises: after the exercise is finished, weighting calculation is carried out based on the obtained SPC control chart center line size, exercise duration, consumed calories and exercise distance of the corresponding parameters of each physiological and exercise information, corresponding physical ability scores are given, and the physical ability increase and decrease condition of the individual is calculated based on the difference value of the scores of the two exercise processes.
5. The method according to claim 4, wherein said S6: based on feedback of the user on the exercise plan, objective data information and individual physical ability increase and decrease conditions in the exercise process, which are collected after the exercise is finished, the exercise plan is wholly and locally adjusted; comprising the following steps:
after the exercise is finished, subjective feedback information of the user on the exercise plan is collected by using a display and an interaction module; the subjective feedback information is sent to a cloud server, and a motion plan adjusting module in the cloud server adjusts corresponding feedback grades on the whole based on the subjective feedback information; and the cloud server analyzes physiological and movement information in the movement process and locally adjusts the movement plan based on the analysis result.
6. An intelligent monitoring system for physical performance of an athlete based on the internet of things based on the method of any one of claims 1-5, comprising: the monitoring terminal comprises an information acquisition module, a control module, an interaction module, a display and a storage module, wherein the information acquisition module comprises a temperature sensor, a humidity sensor, a height sensor, a position sensor, an anemometer, a barometer, a respiratory rate sensor, a heart rate sensor, a sphygmomanometer, an oximeter, a thermometer, a speed sensor and an acceleration sensor;
before sports, collecting physique and health information, sports environment, position information and sports item types of a user, sending the collected data information to a cloud server by a control module, setting and adjusting parameters of a first model by the cloud server, and sending the set and adjusted model to the control module; during movement, the control module monitors and pre-warns the physical state by using the obtained model and generates corresponding suggestions and strategies; after the movement, the model is updated and replaced based on the related data information in the movement process.
7. The system of claim 6, wherein the cloud server is further capable of creating an initial exercise program based on physical and health information of the user, and performing overall and local adjustment of the exercise program based on feedback of the user on the exercise program collected after the exercise, objective data information during the exercise, and physical stamina increase and decrease of the individual.
8. The system of claim 6, wherein in the event of an emergency, detecting the presence of a physical fitness intelligent monitoring terminal nearby, and if so, transmitting emergency rescue information to the physical fitness intelligent monitoring terminal nearby and the cloud server simultaneously, the emergency rescue information including user location, information, and anomaly type.
9. The system of claim 8, wherein the monitoring terminal is a smart watch or glasses, or a mobile terminal fixed on a bicycle.
10. The system of claim 9, wherein during exercise, a recommended curve and a real-time curve of the environment, the location, the physiological information and the exercise information during exercise are displayed on the display in real time, and corresponding overrun warning information is prompted on the display to display corresponding advice and strategies.
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| CN117787731A (en) * | 2023-09-14 | 2024-03-29 | 西安交通大学城市学院 | Real-time rest decision method based on Actor-Critic network in sports wireless teaching |
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