CN117084646A - Training injury monitoring and early warning method and system based on electronic sensing - Google Patents
Training injury monitoring and early warning method and system based on electronic sensing Download PDFInfo
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Abstract
The invention provides a training injury monitoring and early warning method and system based on electronic sensing, which relate to the technical field of data processing, and are characterized in that a real-time exercise heart rate set of a user is obtained based on an exercise heart rate monitoring instruction, and an exercise heart rate warning instruction is generated by traversing and comparing the real-time exercise heart rate set; and obtaining a peak exercise heart rate set of the user based on the recovery heart rate monitoring instruction, and comparing the peak exercise heart rate set with the exercise recovery heart rate set for multiple times to generate a recovery heart rate alarm instruction. The technical problems that training injury and even sudden death accident easily occur due to the fact that physical training scheme establishment in the prior art depends on manual experience and has the physical function of an unadapted participant are solved. The physical performance of the user is known from the exercise heart rate monitoring dimension and the exercise recovery heart rate monitoring dimension, and references are provided for timely and effectively adjusting the training intensity and the training quantity in an adaptive manner, so that the occurrence of training injury caused by training is effectively avoided, the exercise sudden death probability of the user is reduced, and the physical and mental health of the user is guaranteed.
Description
Technical Field
The application relates to the technical field of data processing, in particular to a training injury monitoring and early warning method and system based on electronic sensing.
Background
With the vigorous development of the sports and body-building industry, people have increasingly high demands for more personalized, efficient and scientific physical training. However, the formulation of most physical training schemes still depends on manual experience, and a certain problem of the physical functions of the inadaptation and training users exists.
Because each person's physiological characteristics are different, the same training program may have different effects on different users. However, the conventional manual training plan making method is difficult to fully consider the individual difference factors, which easily causes the mismatching of the training plan with the physical functions of the participant, and further causes the occurrence of training injury or more serious sudden death accident.
In the prior art, the physical training scheme is formulated by relying on manual experience, and the technical problem that training injury and even sudden death accident easily occur due to the fact that the physical function of a user is not adapted to the training is existed.
Disclosure of Invention
The application provides a training injury monitoring and early warning method and system based on electronic sensing, which are used for solving the technical problems that in the prior art, physical training schemes are formulated to depend on manual experience, and the physical functions of a participant are not adapted to cause easy occurrence of training injury and even sudden death of sports.
In view of the above problems, the application provides a training injury monitoring and early warning method and system based on electronic sensing.
In a first aspect of the application, there is provided an electronic sensing-based training injury monitoring and early warning method, the method comprising: presetting a motion monitoring instruction, wherein the motion monitoring instruction comprises a motion heart rate monitoring instruction and a recovery heart rate monitoring instruction; based on the exercise heart rate monitoring instruction interaction intelligent wearable device, a real-time exercise heart rate set of a target monitoring user is obtained; the highest heart rate reference value of the target monitoring user is obtained through interaction, the highest heart rate reference value is traversed and compared with the real-time exercise heart rate set, and an exercise heart rate warning instruction is generated; interacting the intelligent wearable device based on the recovery heart rate monitoring instruction to obtain a peak exercise heart rate set of the target monitoring user; the exercise recovery heart rate set of the target monitoring user is obtained through interaction, and the peak exercise heart rate set and the exercise recovery heart rate set are compared for a plurality of times to generate a recovery heart rate alarm instruction; and the exercise heart rate warning instruction and the recovery heart rate warning instruction form training injury monitoring early warning reminding of the target monitoring user.
In a second aspect of the present application, there is provided an electronic sensing-based training injury monitoring and early warning system, the system comprising: the monitoring instruction presetting module is used for presetting movement monitoring instructions, wherein the movement monitoring instructions comprise movement heart rate monitoring instructions and recovery heart rate monitoring instructions; the exercise heart rate interaction module is used for interacting the intelligent wearable device based on the exercise heart rate monitoring instruction to obtain a real-time exercise heart rate set of the target monitoring user; the alarm instruction generation module is used for interactively obtaining the highest heart rate reference value of the target monitoring user, traversing and comparing the highest heart rate reference value with the real-time exercise heart rate set, and generating an exercise heart rate alarm instruction; the peak heart rate acquisition module is used for interacting the intelligent wearable device based on the recovery heart rate monitoring instruction to obtain a peak exercise heart rate set of the target monitoring user; the alarm instruction output module is used for interactively obtaining a motion recovery heart rate set of the target monitoring user, comparing the peak motion heart rate set with the motion recovery heart rate set for a plurality of times and generating a recovery heart rate alarm instruction; and the early warning reminding generation module is used for forming training injury monitoring early warning reminding of the target monitoring user by the exercise heart rate warning instruction and the recovery heart rate warning instruction.
One or more technical schemes provided by the application have at least the following technical effects or advantages:
the method provided by the embodiment of the application comprises the steps of presetting exercise monitoring instructions, wherein the exercise monitoring instructions comprise an exercise heart rate monitoring instruction, a heart rate recovery monitoring instruction and an exercise body temperature monitoring instruction; based on the exercise heart rate monitoring instruction interaction intelligent wearable device, a real-time exercise heart rate set of a target monitoring user is obtained; the highest heart rate reference value of the target monitoring user is obtained through interaction, the highest heart rate reference value is traversed and compared with the real-time exercise heart rate set, and an exercise heart rate warning instruction is generated; interacting the intelligent wearable device based on the recovery heart rate monitoring instruction to obtain a peak exercise heart rate set of the target monitoring user; the exercise recovery heart rate set of the target monitoring user is obtained through interaction, and the peak exercise heart rate set and the exercise recovery heart rate set are compared for a plurality of times to generate a recovery heart rate alarm instruction; and the exercise heart rate warning instruction and the recovery heart rate warning instruction form training injury monitoring early warning reminding of the target monitoring user. The physical performance of the user is known from the exercise heart rate monitoring dimension and the exercise recovery heart rate monitoring dimension, and references are provided for timely and effectively adjusting the training intensity and the training quantity in an adaptive manner, so that the occurrence of training injury caused by training is effectively avoided, the exercise sudden death probability of the user is reduced, and the physical and mental health technical effect of the user is guaranteed.
Drawings
FIG. 1 is a schematic flow chart of a training injury monitoring and early warning method based on electronic sensing;
FIG. 2 is a schematic flow chart of an exercise heart rate warning command generated in the training injury monitoring and early warning method based on electronic sensing;
FIG. 3 is a schematic flow chart of a heart rate recovery warning command generated in the training injury monitoring and early warning method based on electronic sensing;
fig. 4 is a schematic structural diagram of a training injury monitoring and early warning system based on electronic sensing.
Reference numerals illustrate: the system comprises a monitoring instruction presetting module 1, an exercise heart rate interaction module 2, an alarm instruction generating module 3, a peak heart rate acquisition module 4, an alarm instruction output module 5 and an early warning reminding generating module 6.
Detailed Description
The application provides a training injury monitoring and early warning method and system based on electronic sensing, which are used for solving the technical problems that in the prior art, physical training schemes are formulated depending on manual experience, and the physical functions of a participant training user are not adapted, so that training injury and even sudden death of sports are easy to happen. The physical performance of the user is known from the exercise heart rate monitoring dimension and the exercise recovery heart rate monitoring dimension, and references are provided for timely and effectively adjusting the training intensity and the training quantity in an adaptive manner, so that the occurrence of training injury caused by training is effectively avoided, the exercise sudden death probability of the user is reduced, and the physical and mental health technical effect of the user is guaranteed.
The technical scheme of the application accords with related regulations on data acquisition, storage, use, processing and the like.
In the following, the technical solutions of the present application will be clearly and completely described with reference to the accompanying drawings, and it should be understood that the described embodiments are only some embodiments of the present application, but not all embodiments of the present application, and that the present application is not limited by the exemplary embodiments described herein. All other embodiments, which can be made by those skilled in the art based on the embodiments of the application without making any inventive effort, are intended to be within the scope of the application. It should be further noted that, for convenience of description, only some, but not all of the drawings related to the present application are shown.
Example 1
As shown in fig. 1, the application provides a training injury monitoring and early warning method based on electronic sensing, which comprises the following steps:
s100, presetting a motion monitoring instruction, wherein the motion monitoring instruction comprises a motion heart rate monitoring instruction and a recovery heart rate monitoring instruction;
specifically, in this embodiment, a training injury monitoring and early warning method based on electronic sensing is applied to a training injury monitoring and early warning system based on electronic sensing. The target monitoring user is a non-specific training participant who wears intelligent wearing equipment to participate in physical training, the intelligent wearing equipment is multifunctional equipment integrating a heart rate sensor, a temperature sensor, a 3D acceleration sensor and a data transmission module, the intelligent wearing equipment realizes heart rate monitoring function, body temperature data acquisition function and heart rate variability monitoring function based on the multifunctional sensor, and meanwhile the intelligent wearing equipment has a data storage function and a data receiving and transmitting function.
The exercise heart rate refers to heart rate data of a target monitoring user in a training exercise state acquired based on the intelligent wearing equipment, the recovery heart rate refers to heart rate data acquired by the target monitoring user in an exercise-rest process acquired based on the intelligent wearing equipment, and the exercise body temperature is data acquired by acquiring body temperature data of the whole exercise training process of the target monitoring user based on the intelligent wearing equipment.
The exercise monitoring instructions are preset in this embodiment, and include an exercise heart rate monitoring instruction and a recovery heart rate monitoring instruction.
The intelligent wearable equipment receives the motion monitoring instruction, performs multiple dimension data acquisition on the target monitoring user, feeds back the data to a training injury monitoring and early warning system based on electronic sensing, and performs motion training sign monitoring, analysis and early warning on the acquired data of the target monitoring user based on the system.
S200, based on the exercise heart rate monitoring instruction, the intelligent wearable device is interacted with to obtain a real-time exercise heart rate set of a target monitoring user;
specifically, in the present embodiment, the formulation of the exercise intensity and the training amount of the target monitoring user and the supervision guidance of the overall process of the exercise training of the target monitoring user are performed based on the instructor.
After the training instruction is issued to the target monitoring user by the instructor, the target monitoring user starts sports behaviors, meanwhile, the instructor sends the sports heart rate monitoring instruction to the intelligent wearing equipment of the target monitoring user based on the intelligent wearing equipment, and the sports heart rate monitoring instruction comprises a monitoring start time node, a monitoring end time node and a monitoring period node.
The intelligent wearable device worn by the target monitoring user receives the exercise heart rate monitoring instruction, and invokes a heart rate sensor to collect the real-time heart rate of the target monitoring user based on the monitoring start time node until the monitoring end time node stops, so as to obtain the real-time exercise heart rate set, wherein the real-time exercise heart rate set comprises real-time exercise heart rates of a plurality of interval monitoring period nodes. For example, the real-time exercise heart rate set is 10:00-10: 10am monitoring start time node-monitoring end time node, a set of real-time heart rate data acquired once every 1 second.
S300, interactively obtaining the highest heart rate reference value of the target monitoring user, traversing and comparing the highest heart rate reference value with the real-time exercise heart rate set, and generating an exercise heart rate warning instruction;
In one embodiment, as shown in fig. 2, the method step S300 provided by the present application further includes:
s310, interactively acquiring a target age parameter of the target monitoring user;
s320, inputting the target age parameter into a pre-constructed maximum heart rate estimation formula to obtain the maximum heart rate reference value;
s330, presetting an exercise heart rate deviation index;
s340, interacting the intelligent wearable equipment based on the exercise heart rate monitoring instruction to obtain the real-time exercise heart rate set;
s350, calculating and obtaining an exercise heart rate deviation index set based on the real-time exercise heart rate set and the highest heart rate reference value;
s360, judging whether the exercise heart rate deviation index set completely meets the exercise heart rate deviation index;
and S370, if any one of the exercise heart rate deviation indexes does not meet the exercise heart rate deviation index, generating the exercise heart rate warning instruction.
In particular, it should be understood that the highest heart rate refers to the heart rate value that the principal achieves at the maximum heart rate load, as calculated by the maximum heart rate estimation formula: maximum heart rate = 220-age, with a more accurate estimate.
Therefore, in the embodiment, personal information of the target monitoring user is input in advance based on the intelligent wearable device, and the intelligent wearable device is interacted to directly acquire the target age parameter of the target monitoring user. And inputting the target age parameter into a maximum heart rate estimation formula to obtain the highest heart rate reference value, wherein the highest heart rate reference value is the heart rate maximum value of a theoretical target monitoring user in a health state.
An exercise heart rate deviation index, i.e. a percentage of the target monitoring user's actual maximum heart rate allowed to exceed the maximum heart rate reference value in a healthy state, is preset, e.g. the exercise heart rate deviation index is 90% higher than the maximum heart rate reference value.
Based on the exercise heart rate monitoring instruction interaction the intelligent wearable device obtains the real-time exercise heart rate set, a plurality of real-time heart rate data in the real-time exercise heart rate set are used as the subtracted numbers, the highest heart rate reference value is the most subtracted number, heart rate deviation calculation is carried out one by one, the exercise heart rate deviation index set is obtained, and a plurality of exercise heart rate deviation indexes in the exercise heart rate deviation index set have a mapping relation with a plurality of real-time heart rate data.
Judging whether all the exercise heart rate deviation indexes of the exercise heart rate deviation index set meet the exercise heart rate deviation index, if any one of the exercise heart rate deviation indexes does not meet the exercise heart rate deviation index, indicating that the current exercise intensity and training amount exceed the load amount of the target monitoring user, and generating the exercise heart rate warning instruction.
And the exercise heart rate warning instruction is synchronously sent to intelligent wearing equipment of the instructor and the target monitoring user so as to prompt the two parties to reduce the training intensity and the training amount.
According to the method, the device and the system, the target monitoring user can acquire heart rate data of the target monitoring user in a motion state in multiple cycles and compare the highest heart rate reference value, so that whether the current training quantity and the motion intensity are matched with the target monitoring user or not is accurately known, the training intensity and the training quantity are timely adjusted through intervention, and the training injury accident is effectively avoided.
S400, interacting the intelligent wearable equipment based on the heart rate recovery monitoring instruction to obtain a peak exercise heart rate set of the target monitoring user;
specifically, in this embodiment, the purpose of the recovery heart rate monitoring is to obtain the highest heart rate value of the user when the exercise reaches the highest heart rate, and stop the exercise for one minute to perform heart rate difference calculation, so as to determine whether the formulated training intensity and training amount are suitable for the physical condition of the target monitoring user.
Specifically, when giving a heart rate recovery test instruction to the target monitoring user, the instructor sends the heart rate recovery test instruction to the intelligent wearing equipment of the target monitoring user based on the intelligent wearing equipment.
And the target monitoring user receives a heart rate recovery test instruction, selects any exercise mode based on personal preference to enable the exercise heart rate of the target monitoring user to be improved to the peak exercise heart rate, and receives the heart rate recovery test instruction by intelligent wearable equipment worn by the target monitoring user, acquires heart rate data of the target monitoring user, and obtains the peak exercise heart rate set.
S500, interactively obtaining a motion recovery heart rate set of the target monitoring user, and comparing the peak motion heart rate set with the motion recovery heart rate set for a plurality of times to generate a recovery heart rate alarm instruction;
in one embodiment, as shown in fig. 3, the method step S500 provided by the present application further includes:
s510, presetting a peak exercise execution frequency and a heart rate deviation threshold;
S520, performing operation heart rate lifting by the target monitoring user based on the peak exercise execution frequency, and generating the peak exercise heart rate set and the exercise recovery heart rate set, wherein the peak exercise heart rate set and the exercise recovery heart rate set are temporarily stored in the intelligent wearable device;
s530, interacting the intelligent wearable device based on the recovery heart rate monitoring instruction, and calling the peak exercise heart rate set and the exercise recovery heart rate set;
s540, comparing the peak exercise heart rate set and the exercise recovery heart rate set for multiple times to obtain a heart rate deviation set;
s550, judging whether the heart rate deviation sets all meet the heart rate deviation threshold value;
and S560, if the heart rate deviation sets all meet the heart rate deviation threshold value, generating the heart rate recovery alarm instruction.
Specifically, in this embodiment, the peak exercise execution frequency is the number of times that the target is required to monitor the user to raise his exercise heart rate to the peak exercise heart rate. The exercise recovery heart rate is that the target monitors the real-time heart rate value after the user stops exercising for one minute.
And presetting peak exercise execution frequency by the instructor, and generating the recovery heart rate monitoring instruction based on the peak exercise execution frequency and peak exercise execution time and peak exercise interval time.
And prompting the target monitoring user to start and stop movement based on the peak movement execution time in the heart rate recovery monitoring instruction by the intelligent wearable device, and recording the highest heart rate of the target monitoring user as the peak movement heart rate in the peak movement execution time.
After the target monitoring user stops moving based on the intelligent wearing equipment, the intelligent wearing equipment counts 1 minute, and the exercise recovery heart rate of the round peak exercise is acquired. And temporarily storing the peak exercise heart rate-exercise recovery heart rate record of the round to the intelligent wearable device.
And carrying out peak exercise heart rate-exercise recovery heart rate testing and recording for multiple rounds based on the peak exercise execution frequency by adopting the same method for obtaining the peak exercise heart rate-exercise recovery heart rate for a single round, and obtaining the peak exercise heart rate set and the exercise recovery heart rate set.
And interacting the intelligent wearable equipment based on the recovery heart rate monitoring instruction, calling the peak exercise heart rate set and the exercise recovery heart rate set, and comparing the peak exercise heart rate set and the exercise recovery heart rate set for a plurality of times based on a round mapping relation to obtain a heart rate deviation set, wherein the heart rate deviation set is a plurality of heart rate deviation data mapped to the peak exercise heart rate-exercise recovery heart rate for a plurality of times.
And presetting a heart rate deviation threshold, for example, 25 times/min, judging whether all the heart rate deviation data in the heart rate deviation set meet the heart rate deviation threshold, if the heart rate deviation set meets the heart rate deviation threshold, indicating that the body function of the current target monitoring user is weaker and the heart rate stability is not high, and generating the heart rate recovery alarm instruction to prompt an instructor to adjust the training method and the training amount so as to avoid the sports injury event of the target monitoring user.
The embodiment realizes that whether the current training quantity and the exercise intensity are matched with the target monitoring user or not is obtained based on the heart rate peak value and the heart rate recovery value test, so that the training intensity and the training quantity are adjusted by intervention in time, and the occurrence of training injury accidents is effectively avoided.
And S600, the exercise heart rate warning instruction and the recovery heart rate warning instruction form a training injury monitoring early warning prompt of the target monitoring user.
Specifically, in this embodiment, the exercise heart rate warning instruction and the recovery heart rate warning instruction are integrated in information to form a training injury monitoring early warning prompt for the target monitoring user, and the instructor and the target monitoring user can learn the physical performance of the target monitoring user from the exercise heart rate long-term monitoring dimension and the exercise recovery heart rate monitoring dimension based on the training injury monitoring early warning prompt.
The embodiment achieves the technical effects of knowing the physical condition of the user from the exercise heart rate monitoring dimension and the exercise recovery heart rate monitoring dimension, providing references for timely and effectively adjusting the training intensity and the training quantity, effectively avoiding the occurrence of training injury caused by training, reducing the exercise sudden death probability of the user and guaranteeing the physical and mental health of the training staff.
In one embodiment, the method steps provided by the application further comprise:
s710, presetting a thermal-jet disease monitoring window, a body temperature early-warning threshold value and a heart rate early-warning threshold value;
s720, monitoring the body temperature of the target monitoring user based on the thermal-jet disease monitoring window to obtain real-time body temperature data;
s730, when the real-time body temperature data meets the body temperature early warning threshold value, acquiring a data acquisition node of the real-time body temperature data;
s740, acquiring a temperature rise interval threshold value, and acquiring historical body temperature data based on the data acquisition node and the temperature rise interval threshold value;
s750, interactively obtaining a target normal body temperature parameter and a target real-time heart rate of the target monitoring user;
s760, judging whether the historical body temperature data meets the target normothermic parameters or not;
s770, judging whether the target real-time heart rate meets the heart rate early warning threshold value;
S780, if the historical body temperature data meets the target normal body temperature parameters and the target real-time heart rate meets the heart rate early warning threshold, generating a heat-radiation disease early warning instruction.
Specifically, in this embodiment, in the whole process that the target monitoring user completes exercise heart rate monitoring and recovery heart rate monitoring one by one, when the instructor issues an exercise heart rate monitoring instruction, the heat-shooting disease monitoring window starts to operate until the recovery heart rate monitoring instruction is executed, and the heat-shooting disease monitoring window stops operating.
The thermal-jet disease monitoring window is used for calling a heart rate sensor and a temperature sensor in intelligent wearable equipment of a target monitoring user to operate, body temperature monitoring is carried out on the target monitoring user, real-time body temperature data are obtained, and when the real-time body temperature data meet the body temperature early-warning threshold value, a data acquisition node of the real-time body temperature data is obtained.
A temperature rise interval threshold is obtained, wherein the temperature rise interval threshold refers to a time span from the body temperature of the target monitoring user to the body temperature early warning threshold, for example, 30min. And acquiring historical body temperature data based on the data acquisition node and the temperature rise interval threshold, wherein the historical body temperature data is a real-time body temperature value of a target monitoring user before 30 minutes.
And the interaction internet obtains the normal human body temperature as a target normal body temperature parameter of the target monitoring user, and simultaneously the intelligent wearable equipment is interacted to obtain the target real-time heart rate of heart rate data of the target monitoring user at the data acquisition time node.
Judging whether the historical body temperature data is smaller than or equal to the target normal body temperature parameter; and judging that the target real-time heart rate is larger than or equal to the heart rate early warning threshold value (120 times/minute). If the historical body temperature data meets the target normal body temperature parameters and the target real-time heart rate meets the heart rate early warning threshold, the fact that the real-time body temperature, the temperature rising condition and the real-time heart rate of the current target monitoring user meet the characteristics of the heat shooting disease precursor is indicated, so that a heat shooting disease early warning instruction is generated, and the heat shooting disease early warning instruction is sent to intelligent wearable equipment of the target monitoring user.
After the intelligent wearing equipment of the target monitoring user receives the heat-shooting disease early warning instruction, the vibration motor continuously vibrates, meanwhile, the screen of the intelligent wearing equipment prompts the target monitoring user to touch a corresponding button to close vibration, if the target monitoring user does not complete touch operation within one minute, the electronic sensing-based training injury monitoring early warning system judges that the target monitoring user may be in coma or extremely weak symptoms, and the electronic sensing-based training injury monitoring early warning system immediately sends the heat-shooting disease early warning prompt to the intelligent wearing equipment of the instructor so as to ensure that the target monitoring user in a dangerous state is timely rescued. The method and the device achieve the technical effects of ensuring that vital signs of the target monitoring user are monitored in the whole training process, ensuring the life safety of the target monitoring user and ensuring the physical and mental health of the training personnel.
In one embodiment, before the motion monitoring command is preset, the method step S100 provided in the present application further includes:
s110, interactively obtaining a reference resting heart rate and a real-time resting heart rate of a target monitoring user;
s120, comparing whether the real-time resting heart rate meets the reference resting heart rate or not, and generating first early warning information;
s130, interactively obtaining a reference adjacent heartbeat interval and an adjacent heartbeat interval set of the target monitoring user;
s140, comparing whether the adjacent heartbeat interval set meets the reference adjacent heartbeat interval or not, and generating second early warning information;
s150, the first early warning information and the second early warning information form training load early warning reminding of the target monitoring user.
In one embodiment, comparing whether the real-time resting heart rate meets the reference resting heart rate, generating first pre-warning information, the method provided in the application further comprises the following step S120:
s121, presetting a resting heart rate acquisition period and a resting heart rate deviation threshold;
s122, interacting the intelligent wearable equipment based on the resting heart rate acquisition period to obtain a historical resting heart rate sequence of the target monitoring user;
s123, carrying out averaging treatment on the historical resting heart rate sequence to obtain the reference resting heart rate;
S124, calculating and obtaining a real-time heart rate deviation value based on the reference resting heart rate and the real-time resting heart rate;
s125, judging whether the real-time heart rate deviation value meets the resting heart rate deviation threshold value;
and S126, if the real-time heart rate deviation value does not meet the resting heart rate deviation threshold value, generating the first early warning information.
In one embodiment, comparing whether the set of adjacent heartbeat intervals meets the reference adjacent heartbeat interval, generating second early warning information, the method provided in step S140 of the present application further includes:
s141, presetting a heart rate variability monitoring period;
s142, interacting the intelligent wearable equipment based on the heart rate variability monitoring period to obtain the adjacent heart beat interval set;
s143, judging whether the adjacent heartbeat interval set meets the reference adjacent heartbeat interval;
s144, if the adjacent heartbeat interval set does not meet the reference adjacent heartbeat interval, generating the second early warning information.
Specifically, in the present embodiment, before the physical function substance test of the target monitoring user is performed based on the preset motion monitoring instruction, the present embodiment predicts the physical function of the target monitoring user based on the history data to provide a reference for the instructor to preliminarily generate the training intensity and training scheme.
Specifically, in this embodiment, after the target monitor wakes up in the morning, the target monitor does not speak and does not perform any movement, and the target monitor is lying for 1 minute to finish measurement by selecting the resting heart rate measurement button of the intelligent wearable device, so as to obtain the real-time resting heart rate.
In order to ensure the collection credibility of real-time resting heart rate, this embodiment judges whether target monitoring personnel satisfy resting heart rate measurement condition (for example, measure the acceleration variation of the 3D acceleration transducer of intelligent wearing equipment in the first half hour) based on the data of 3D acceleration transducer in the first half hour of real-time resting heart rate collection time node, when target monitoring user does not satisfy resting heart rate measurement condition, intelligent wearing equipment reminds target monitoring user based on the display screen and does not record the real-time resting heart rate of measurement.
The resting heart rate acquisition period is preset, and is a time span for acquiring the historical resting heart rate of the target monitoring user, for example, acquiring resting heart rate data measured in the last two weeks. And based on the resting heart rate acquisition period, the intelligent wearable device is interacted to obtain a historical resting heart rate sequence of the target monitoring user, wherein the historical resting heart rate sequence is the resting heart rate data of the past 14 days with time sequence. And carrying out averaging treatment on the historical resting heart rate sequence to obtain the reference resting heart rate.
And taking the reference resting heart rate as a reduction number, taking the real-time resting heart rate as a reduced number, calculating to obtain a real-time heart rate deviation value, and presetting a resting heart rate deviation threshold value, for example, the reference resting heart rate is smaller than or equal to 5 times/second.
Judging whether the real-time heart rate deviation value is smaller than or equal to the resting heart rate deviation threshold value, if the real-time heart rate deviation value is not smaller than or equal to the resting heart rate deviation threshold value, generating first early warning information, wherein the first early warning information is used for being sent to intelligent wearing equipment of a instructor to prompt the instructor to reduce training intensity and training amount of a target monitoring user.
In addition to conducting the real-time heart rate deviation test on the day the target monitoring user is ready to conduct training, the present embodiment also conducts the heart rate variability test on the day the target monitoring user is ready to conduct training.
Specifically, a heart rate variability monitoring period is preset, where the heart rate variability monitoring period is a time span for continuously monitoring adjacent heart beat intervals of the target monitoring user, for example, 3 consecutive days. And based on the heart rate variability monitoring period, the intelligent wearable device is interacted to obtain the adjacent heart beat interval set, wherein the adjacent heart beat interval set is a plurality of adjacent heart beat interval data of the target monitoring user for three continuous days in the past.
Presetting a reference adjacent heartbeat interval, for example, 50ms, and judging whether the adjacent heartbeat interval set meets the reference adjacent heartbeat interval; if the adjacent heartbeat interval set does not meet the reference adjacent heartbeat interval, the fact that the long-term heartbeat interval time of the target monitoring user is shorter than that of a healthy person is indicated, and therefore second early warning information is generated and used for being sent to intelligent wearing equipment of the instructor, and the instructor is prompted to reduce training intensity and training quantity for the target monitoring user. The first early warning information and the second early warning information form training load early warning reminding of the target monitoring user so as to prompt the instructor to reduce training intensity and training quantity of the target monitoring user.
According to the embodiment, the body function preliminary prediction of the target monitoring user is carried out based on the historical data before the body function test of the target monitoring user is formally executed, so that the technical effect of providing effective reference for the establishment of training intensity and training quantity of a teacher in the subsequent actual execution of the body skill test of the target monitoring user is achieved.
Example two
Based on the same inventive concept as the training injury monitoring and early warning method based on electronic sensing in the foregoing embodiment, as shown in fig. 4, the present application provides a training injury monitoring and early warning system based on electronic sensing, where the system includes:
The monitoring instruction presetting module 1 is used for presetting movement monitoring instructions, wherein the movement monitoring instructions comprise movement heart rate monitoring instructions and recovery heart rate monitoring instructions;
the exercise heart rate interaction module 2 is used for interacting the intelligent wearable device based on the exercise heart rate monitoring instruction to obtain a real-time exercise heart rate set of the target monitoring user;
the alarm instruction generation module 3 is used for interactively obtaining the highest heart rate reference value of the target monitoring user, traversing and comparing the highest heart rate reference value with the real-time exercise heart rate set, and generating an exercise heart rate alarm instruction;
the peak heart rate acquisition module 4 is used for interacting the intelligent wearable device based on the recovery heart rate monitoring instruction to obtain a peak exercise heart rate set of the target monitoring user;
the alarm instruction output module 5 is used for interactively obtaining a motion recovery heart rate set of the target monitoring user, comparing the peak motion heart rate set with the motion recovery heart rate set for a plurality of times, and generating a recovery heart rate alarm instruction;
and the early warning reminding generation module 6 is used for forming training injury monitoring early warning reminding of the target monitoring user by the exercise heart rate warning instruction and the recovery heart rate warning instruction.
In one embodiment, the system further comprises:
the resting heart rate interaction unit is used for interactively obtaining a reference resting heart rate and a real-time resting heart rate of the target monitoring user;
the early warning information generation unit is used for comparing whether the real-time resting heart rate meets the reference resting heart rate or not to generate first early warning information;
the heartbeat interval interaction unit is used for interactively obtaining a reference adjacent heartbeat interval and an adjacent heartbeat interval set of the target monitoring user;
the early warning information output unit is used for comparing whether the adjacent heartbeat interval set meets the reference adjacent heartbeat interval or not and generating second early warning information;
and the early warning reminding integrated unit is used for forming training load early warning reminding of the target monitoring user by the first early warning information and the second early warning information.
In one embodiment, the system further comprises:
the comparison data presetting unit is used for presetting a resting heart rate acquisition period and a resting heart rate deviation threshold value;
the historical data interaction unit is used for interacting the intelligent wearable device based on the resting heart rate acquisition period to obtain a historical resting heart rate sequence of the target monitoring user;
the reference data calculation unit is used for carrying out averaging processing on the historical resting heart rate sequence to obtain the reference resting heart rate;
The deviation data calculation unit is used for calculating and obtaining a real-time heart rate deviation value based on the reference resting heart rate and the real-time resting heart rate;
the deviation data judging unit is used for judging whether the real-time heart rate deviation value meets the resting heart rate deviation threshold value or not;
and the early warning information generation unit is used for generating the first early warning information if the real-time heart rate deviation value does not meet the resting heart rate deviation threshold value.
In one embodiment, the system further comprises:
the detection period presetting unit is used for presetting a heart rate variability monitoring period;
a heartbeat interval obtaining unit, configured to interact with the smart wearable device based on the heart rate variability monitoring period, to obtain the adjacent heartbeat interval set;
a heartbeat interval judging unit, configured to judge whether the adjacent heartbeat interval set meets the reference adjacent heartbeat interval;
and the early warning information output unit is used for generating the second early warning information if the adjacent heartbeat interval set does not meet the reference adjacent heartbeat interval.
In one embodiment, the system further comprises:
the age parameter interaction unit is used for interactively acquiring the target age parameter of the target monitoring user;
The reference heart rate obtaining unit is used for inputting the target age parameter into a pre-constructed maximum heart rate estimation formula to obtain the maximum heart rate reference value;
the heart rate deviation preset unit is used for presetting exercise heart rate deviation indexes;
the real-time heart rate acquisition unit is used for interacting the intelligent wearable device based on the exercise heart rate monitoring instruction to acquire the real-time exercise heart rate set;
a deviation index calculation unit for calculating and obtaining a heart rate deviation index set based on the real-time exercise heart rate set and the highest heart rate reference value;
the deviation index comparison unit is used for judging whether the exercise heart rate deviation index set completely meets the exercise heart rate deviation index;
and the alarm instruction forming unit is used for generating the exercise heart rate alarm instruction if any one of the exercise heart rate deviation index sets does not meet the exercise heart rate deviation index.
In one embodiment, the system further comprises:
the data preset executing unit is used for presetting the peak exercise executing frequency and the heart rate deviation threshold value;
the change data elucidation unit is used for improving the running heart rate of the target monitoring user based on the peak exercise execution frequency, and generating the peak exercise heart rate set and the exercise recovery heart rate set, wherein the peak exercise heart rate set and the exercise recovery heart rate set are temporarily stored in the intelligent wearable device;
The data calling execution unit is used for interacting the intelligent wearable device based on the recovery heart rate monitoring instruction and calling the peak exercise heart rate set and the exercise recovery heart rate set;
the multi-round comparison execution unit is used for carrying out multi-round comparison on the peak exercise heart rate set and the exercise recovery heart rate set to obtain a heart rate deviation set;
the data judging and processing unit is used for judging whether the heart rate deviation set completely meets the heart rate deviation threshold value;
and the alarm information generation unit is used for generating the heart rate recovery alarm instruction if the heart rate deviation set completely meets the heart rate deviation threshold value.
In one embodiment, the system further comprises:
the preset information generation unit is used for presetting a thermal-jet disease monitoring window, a body temperature early-warning threshold value and a heart rate early-warning threshold value;
the body temperature monitoring execution unit is used for monitoring the body temperature of the target monitoring user based on the thermal-jet disease monitoring window to obtain real-time body temperature data;
the acquisition node obtaining unit is used for obtaining the data acquisition node of the real-time body temperature data when the real-time body temperature data meet the body temperature early warning threshold value;
The temperature rise threshold interaction unit is used for obtaining a temperature rise interval threshold and obtaining historical body temperature data based on the data acquisition node and the temperature rise interval threshold;
the data interaction acquisition unit is used for interactively acquiring the target normal body temperature parameter and the target real-time heart rate of the target monitoring user;
the body temperature value comparison unit is used for judging whether the historical body temperature data meets the target normal body temperature parameters or not;
the heartbeat data comparison unit is used for judging whether the target real-time heart rate meets the heart rate early warning threshold value;
and the heat radiation disease early warning instruction generation unit is used for generating a heat radiation disease early warning instruction if the historical body temperature data meets the target normal body temperature parameter and the target real-time heart rate meets the heart rate early warning threshold.
Any of the methods or steps described above may be stored as computer instructions or programs in various non-limiting types of computer memories, and identified by various non-limiting types of computer processors, thereby implementing any of the methods or steps described above.
Based on the above-mentioned embodiments of the present invention, any improvements and modifications to the present invention without departing from the principles of the present invention should fall within the scope of the present invention.
Claims (8)
1. The training injury monitoring and early warning method based on electronic sensing is characterized by comprising the following steps of:
presetting a motion monitoring instruction, wherein the motion monitoring instruction comprises a motion heart rate monitoring instruction and a recovery heart rate monitoring instruction;
based on the exercise heart rate monitoring instruction interaction intelligent wearable device, a real-time exercise heart rate set of a target monitoring user is obtained;
the highest heart rate reference value of the target monitoring user is obtained through interaction, the highest heart rate reference value is traversed and compared with the real-time exercise heart rate set, and an exercise heart rate warning instruction is generated;
interacting the intelligent wearable device based on the recovery heart rate monitoring instruction to obtain a peak exercise heart rate set of the target monitoring user;
the exercise recovery heart rate set of the target monitoring user is obtained through interaction, and the peak exercise heart rate set and the exercise recovery heart rate set are compared for a plurality of times to generate a recovery heart rate alarm instruction;
and the exercise heart rate warning instruction and the recovery heart rate warning instruction form training injury monitoring early warning reminding of the target monitoring user.
2. The method of claim 1, wherein prior to presetting the motion monitoring instructions, the method further comprises:
Interactively obtaining a reference resting heart rate and a real-time resting heart rate of a target monitoring user;
comparing whether the real-time resting heart rate meets the reference resting heart rate or not, and generating first early warning information;
interactively obtaining a reference adjacent heartbeat interval and an adjacent heartbeat interval set of the target monitoring user;
comparing whether the adjacent heartbeat interval set meets the reference adjacent heartbeat interval or not, and generating second early warning information;
the first early warning information and the second early warning information form training load early warning reminding of the target monitoring user.
3. The method of claim 2, wherein comparing whether the real-time resting heart rate meets the baseline resting heart rate generates first pre-warning information, the method further comprising:
presetting a resting heart rate acquisition period and a resting heart rate deviation threshold;
the intelligent wearable device is interacted based on the resting heart rate acquisition period to obtain a historical resting heart rate sequence of the target monitoring user;
performing averaging treatment on the historical resting heart rate sequence to obtain the reference resting heart rate;
calculating a real-time heart rate deviation value based on the reference resting heart rate and the real-time resting heart rate;
Judging whether the real-time heart rate deviation value meets the resting heart rate deviation threshold value or not;
and if the real-time heart rate deviation value does not meet the resting heart rate deviation threshold value, generating the first early warning information.
4. The method of claim 2, wherein a comparison is made of whether the set of adjacent heartbeat intervals meets the reference adjacent heartbeat interval to generate second pre-warning information, the method further comprising:
presetting a heart rate variability monitoring period;
interacting the intelligent wearable device based on the heart rate variability monitoring period to obtain the adjacent heart beat interval set;
judging whether the adjacent heartbeat interval set meets the reference adjacent heartbeat interval or not;
and if the adjacent heartbeat interval set does not meet the reference adjacent heartbeat interval, generating the second early warning information.
5. The method of claim 1, wherein the interaction obtains a highest heart rate reference value for the target monitoring user and compares the highest heart rate reference value traversal to the real-time athletic heart rate set, generating an athletic heart rate alert instruction, the method further comprising:
interactively acquiring a target age parameter of the target monitoring user;
Inputting the target age parameter into a pre-constructed maximum heart rate estimation formula to obtain the highest heart rate reference value;
presetting an exercise heart rate deviation index;
interacting the intelligent wearable device based on the exercise heart rate monitoring instruction to obtain the real-time exercise heart rate set;
calculating and obtaining an exercise heart rate deviation index set based on the real-time exercise heart rate set and the highest heart rate reference value;
judging whether the exercise heart rate deviation index set completely meets the exercise heart rate deviation index;
and if any one of the exercise heart rate deviation index sets does not meet the exercise heart rate deviation index, generating the exercise heart rate warning instruction.
6. The method of claim 1, wherein the interaction obtains a set of exercise recovery heart rates for the target monitoring user and compares the set of peak exercise heart rates and the set of exercise recovery heart rates a plurality of times to generate a recovery heart rate alert instruction, the method further comprising:
presetting a peak exercise execution frequency and a heart rate deviation threshold;
the target monitoring user performs operation heart rate lifting based on the peak exercise execution frequency, and generates the peak exercise heart rate set and the exercise recovery heart rate set, wherein the peak exercise heart rate set and the exercise recovery heart rate set are temporarily stored in the intelligent wearable device;
Interacting the intelligent wearable device based on the recovery heart rate monitoring instruction, invoking the peak exercise heart rate set and the exercise recovery heart rate set;
performing multiple rounds of comparison on the peak exercise heart rate set and the exercise recovery heart rate set to obtain a heart rate deviation set;
judging whether the heart rate deviation set completely meets the heart rate deviation threshold value or not;
and if the heart rate deviation sets all meet the heart rate deviation threshold value, generating the heart rate recovery alarm instruction.
7. The method of claim 1, wherein the method further comprises:
presetting a thermal-jet disease monitoring window, a body temperature early-warning threshold value and a heart rate early-warning threshold value;
based on the thermal-jet disease monitoring window, body temperature monitoring is carried out on the target monitoring user, and real-time body temperature data are obtained;
when the real-time body temperature data meets the body temperature early warning threshold value, a data acquisition node of the real-time body temperature data is obtained;
acquiring a temperature rise interval threshold value, and acquiring historical body temperature data based on the data acquisition node and the temperature rise interval threshold value;
interactively obtaining a target normothermic parameter and a target real-time heart rate of the target monitoring user;
Judging whether the historical body temperature data meets the target normothermia parameter or not;
judging whether the target real-time heart rate meets the heart rate early warning threshold value or not;
and if the historical body temperature data meets the target normal body temperature parameter and the target real-time heart rate meets the heart rate early warning threshold, generating a thermal disease early warning instruction.
8. An electronic sensing-based training injury monitoring and early warning system, comprising:
the monitoring instruction presetting module is used for presetting movement monitoring instructions, wherein the movement monitoring instructions comprise movement heart rate monitoring instructions and recovery heart rate monitoring instructions;
the exercise heart rate interaction module is used for interacting the intelligent wearable device based on the exercise heart rate monitoring instruction to obtain a real-time exercise heart rate set of the target monitoring user;
the alarm instruction generation module is used for interactively obtaining the highest heart rate reference value of the target monitoring user, traversing and comparing the highest heart rate reference value with the real-time exercise heart rate set, and generating an exercise heart rate alarm instruction;
the peak heart rate acquisition module is used for interacting the intelligent wearable device based on the recovery heart rate monitoring instruction to obtain a peak exercise heart rate set of the target monitoring user;
The alarm instruction output module is used for interactively obtaining a motion recovery heart rate set of the target monitoring user, comparing the peak motion heart rate set with the motion recovery heart rate set for a plurality of times and generating a recovery heart rate alarm instruction;
and the early warning reminding generation module is used for forming training injury monitoring early warning reminding of the target monitoring user by the exercise heart rate warning instruction and the recovery heart rate warning instruction.
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