Method and system for monitoring state of personnel in movement process

Abstract

The invention relates to a method and system for monitoring the state of a person in the exercise process, and relates to the field of exercise monitoring, and the method comprises the steps: obtaining body fat data of a user before exercise, image information of the user during exercise, and a heart rate change diagram and a blood pressure value of the user during exercise, and determining a body type score of the user based on the body fat data and the image information, and performing feature recognition on the image information to obtain a motion posture of the user, determining a motion score of the user based on the body type score, the motion posture, the heart rate change diagram and the blood pressure value, and when the motion score is lower than a preset score threshold, outputting alarm information and stopping continuous motion. The method and the device have the effect of timely and accurately predicting fatigue or accidents of the hypertension user in the running process.

Description

Technical Field

[0001] This application relates to the field of motion monitoring, and in particular to a method and system for monitoring the status of personnel during exercise. Background Art

[0002] With the development of society and the improvement of living standards, people's diet has been significantly improved. However, excessive energy intake has led to the problem of overnutrition, which has become a risk factor for hypertension. Blood pressure is a key indicator for measuring the heart's pumping blood and vascular health. The cardiovascular risk of hypertensive patients increases with the increase in blood pressure. The key to preventing hypertension lies in controlling diet and moderate exercise. Some hypertensive patients choose to run to strengthen their physique, but they need to avoid overloading exercise to prevent blood pressure from rising and endangering their lives.

[0003] Due to the instability of blood pressure or the relatively high blood pressure level of hypertensive patients during running, the probability of accidents occurring to hypertensive patients during running is higher than that of normal people. In the prior art, only real-time monitoring of heart rate or blood pressure can be achieved during the running process of hypertensive patients, and it is difficult to predict the situation of exhaustion or accidents occurring to hypertensive patients during the running process. Summary of the Invention

[0004] In order to timely and accurately predict the situation of exhaustion or accidents occurring to hypertensive users during the running process, this application provides a method and system for monitoring the status of personnel during exercise.

[0005] In the first aspect, this application provides a method for monitoring the status of personnel during exercise, adopting the following technical solution: A method for monitoring the status of personnel during exercise includes: Obtaining the body fat data of the user before exercise, the image information of the user during exercise, the heart rate change graph of the user during exercise, and the blood pressure value; Determining the body type score of the user based on the body fat data and the image information; Performing feature recognition on the image information to obtain the exercise posture of the user; Determining the exercise score of the user based on the body type score, the exercise posture, the heart rate change graph, and the blood pressure value; When the exercise score is lower than the preset score threshold, outputting an alarm message and stopping further exercise.

[0006] By adopting the above technical solution, the body fat data of the user before exercise, the image information of the user during exercise, the heart rate change graph and blood pressure value of the user during exercise are obtained. The state of hypertensive people during exercise needs to be particularly concerned about to ensure the safety and effectiveness of exercise. Therefore, before exercise, the user will be measured by a body fat scale. Based on the body fat data and image information, the body type score of the user is determined. The body type score represents the level of the user's exercise quality. Feature recognition is performed on the image information to obtain the user's exercise posture. The greater the difference between the user's movement during exercise and the standard degree, the greater the impact on the user's exercise time and physical condition. People with different physiques have different conditions after exercise. Some users may have knee pain, some users may have too fast heart rate or blood pressure, or some users may have non-standard exercise postures, all of which may lead to a shorter exercise time. Therefore, based on the body type score, exercise posture, heart rate change graph and blood pressure value, the exercise score of the user is determined. The lower the exercise score, the greater the possibility that the user will become fatigued or have an accident. When the exercise score is lower than the preset score threshold, an alarm message is output and the exercise is stopped, which can timely and accurately predict the situation of fatigue or accident during the running of hypertensive users.

[0007] In another possible implementation manner, the determining the body type score of the user based on the body fat data and the image information includes: Determine the preset interval where the body fat data is located, and determine the first body type corresponding to the preset interval; Perform human feature recognition on the image information to determine the height and contour of the user; Determine the corresponding second body type based on the height and contour; Determine the lowest score corresponding to the first body type and the second body type as the body type score of the user, and each body type corresponds to a different preset score.

[0008] In another possible implementation manner, the determining the exercise score of the user based on the body type score, exercise posture, heart rate change graph and blood pressure value includes: Determine the initial heart rate and maximum heart rate of the user in the heart rate change graph, and the required duration for the first appearance of the maximum heart rate; Determine the highest blood pressure value in the blood pressure value; Determine the heart rate growth rate of the user based on the initial heart rate, maximum heart rate and required duration; Determine the supplementary score of the user based on the exercise posture; Determine the exercise score of the user based on the body type score, supplementary score, heart rate growth rate, highest blood pressure value and their respective first coefficients.

[0009] In another possible implementation manner, the method further includes: Determine a target person from a historical database based on the body fat data, height, and profile. The historical database contains data of other hypertensive users participating in this exercise. The target person is a person whose target similarity to the user's physical condition reaches a preset similarity threshold; Obtain the historical exercise duration of each target person; Determine the first preset duration interval in which each historical exercise duration is located from multiple preset duration intervals; Determine the number of target persons corresponding to each first preset duration interval; Determine the first preset duration interval with the largest number as the target preset duration interval of the user.

[0010] In another possible implementation manner, the determining of the target person from the historical database based on the body fat data, height, and profile includes: Determine a preset height deviation range of the height, and determine the first persons within the preset height deviation range from the historical database; Determine the first similarity between the profile and the profile of the first persons, and determine the second similarity between the body fat data and the body fat data of the first persons; Determine a target similarity based on the first similarity, the second similarity, and their respective second coefficients; Determine the persons whose target similarity reaches the preset similarity threshold as target persons.

[0011] In another possible implementation manner, the method further includes: Obtain the start time and end time of the user's exercise; Determine the exercise duration of the user based on the start time and end time; Determine the heart rate recovery time of the user based on the exercise duration, body type score, and their respective third coefficients; After the heart rate recovery time has passed, obtain the user's current heart rate; Determine whether the current heart rate is within a preset heart rate interval; If not, control the sports bracelet to vibrate and prompt the staff.

[0012] In another possible implementation manner, the method further includes: When the user turns on the fitness equipment, obtain the diet time, diet amount, and current time before the user's exercise; Determine the post - meal interval of the user based on the diet time and the current time; Judge whether the user can start exercising based on the post - meal interval and the diet amount; If not, control the fitness equipment to turn off and remind the user to take a rest.

[0013] In a second aspect, the present application provides a system for monitoring the state of a person during exercise, adopting the following technical solutions: A system for monitoring the state of a person during exercise, comprising: A first acquisition module, configured to acquire the body fat data of the user before exercise, the image information of the user during exercise, the heart rate change graph of the user during exercise, and the blood pressure value; A body type score determination module, configured to determine the body type score of the user based on the body fat data and the image information; An identification module, configured to perform feature identification on the image information to obtain the exercise posture of the user; A motion score determination module, configured to determine the motion score of the user based on the body type score, the motion posture, the heart rate change graph, and the blood pressure value; An output module, configured to output an alarm message and stop further exercise when the motion score is lower than a preset score threshold.

[0014] By adopting the above technical solutions, the first acquisition module acquires the body fat data of the user before exercise, the image information of the user during exercise, the heart rate change graph of the user during exercise, and the blood pressure value. The state of hypertensive patients during exercise needs to be particularly concerned about to ensure the safety and effectiveness of exercise. Therefore, the user will be measured by a body fat scale before exercise. The body type score determination module determines the body type score of the user based on the body fat data and the image information. The body type score characterizes the level of the user's exercise quality. The identification module performs feature identification on the image information to obtain the exercise posture of the user. The greater the difference between the user's actions during exercise and the standard, the greater the impact on the user's exercise time and physical condition. The conditions of different physical constitutions after exercise are different. Some users may have knee pain, some users may have too fast heart rate or blood pressure, or some users may have non-standard exercise postures, all of which may lead to a shorter exercise time. Therefore, the motion score determination module determines the motion score of the user based on the body type score, the motion posture, the heart rate change graph, and the blood pressure value. The lower the motion score, the greater the possibility of the user getting tired or having an accident. When the motion score is lower than the preset score threshold, the output module outputs an alarm message and stops further exercise, which can timely and accurately predict the situation of hypertensive users getting tired or having an accident during running.

[0015] In another possible implementation manner, when the body type score determination module determines the body type score of the user based on the body fat data and the image information, it is specifically configured to: Determine the preset interval where the body fat data is located, and determine the first body type corresponding to the preset interval; Perform human feature identification on the image information to determine the height and contour of the user; Determine the corresponding second body type based on the height and contour; Determine the lowest score corresponding to the first body type and the second body type among them as the user's body type score, and each body type corresponds to a different preset score.

[0016] In another possible implementation, when the exercise score determination module determines the user's exercise score based on the body type score, exercise posture, heart rate change graph, and blood pressure value, it is specifically used for: Determine the user's initial heart rate and maximum heart rate in the heart rate change graph, as well as the required duration for the first appearance of the maximum heart rate; Determine the highest blood pressure value in the blood pressure value; Determine the heart rate growth rate of the user based on the initial heart rate, maximum heart rate, and required duration; Determine the supplementary score of the user based on the exercise posture; Determine the user's exercise score based on the body type score, supplementary score, heart rate growth rate, highest blood pressure value, and their respective first coefficients.

[0017] In another possible implementation, the system further includes: A target person determination module, configured to determine a target person from the historical database based on the body fat data, height, and profile. The historical database is the data of other hypertensive users participating in this exercise, and the target person is a person whose target similarity with the user's physical condition reaches a preset similarity threshold; A second acquisition module, configured to acquire the historical exercise duration of each target person; A first determination module, configured to determine the first preset duration interval in which each historical exercise duration is located from multiple preset duration intervals; A quantity determination module, configured to determine the quantity of target persons corresponding to each first preset duration interval; A second determination module, configured to determine the first preset duration interval with the largest quantity as the target preset duration interval of the user.

[0018] In another possible implementation, when the target person determination module determines a target person from the historical database based on the body fat data, height, and profile, it is specifically used for: Determine the preset height deviation range of the height, and determine the first person belonging to the preset height deviation range from the historical database; Determine the first similarity between the profile and the profile of the first person, and determine the second similarity between the body fat data and the body fat data of the first person; Determine the target similarity based on the first similarity, second similarity, and their respective second coefficients; Identify the person whose target similarity reaches the preset similarity threshold as the target person.

[0019] In another possible implementation, the system further includes: A third acquisition module, configured to acquire the start time and end time of the user's movement; A third determination module, configured to determine the movement duration of the user based on the start time and the end time; A fourth determination module, configured to determine the heart rate recovery time of the user based on the movement duration, the body type score, and their respective third coefficients; A fourth acquisition module, configured to acquire the user's current heart rate after the heart rate recovery time has passed; A first judgment module, configured to judge whether the current heart rate is within a preset heart rate range; A first control module, configured to, if not, control the sports bracelet to vibrate and prompt the staff.

[0020] In another possible implementation, the system further includes: A fifth acquisition module, configured to acquire the diet time, diet amount, and current time before the user's movement when the user turns on the fitness device; A fifth determination module, configured to determine the post-meal interval of the user based on the diet time and the current time; A second judgment module, configured to judge whether the user can start exercising based on the post-meal interval and the diet amount; A second control module, configured to, if not, control the fitness device to turn off and remind the user to take a rest.

[0021] In a third aspect, the present application provides an electronic device, adopting the following technical solution: An electronic device, the electronic device includes: At least one processor; A memory; At least one application program, where at least one application program is stored in the memory and is configured to be executed by at least one processor, and at least one configuration is for: executing a method for monitoring the status of a person during a movement process as shown in any possible implementation manner of the first aspect.

[0022] In a fourth aspect, the present application provides a computer-readable storage medium, adopting the following technical solution: A computer-readable storage medium, when the computer program is executed on a computer, causing the computer to execute a method for monitoring the status of a person during a movement process as described in any item of the first aspect.

[0023] In summary, the present application includes at least one of the following beneficial technical effects: Obtain the body fat data of the user before exercise, the image information of the user during exercise, the heart rate change graph and blood pressure value of the user during exercise. The state of hypertensive patients during exercise needs to be particularly concerned about to ensure the safety and effectiveness of exercise. Therefore, the user will be measured by a body fat scale before exercise. Based on the body fat data and image information, determine the body type score of the user. The body type score characterizes the level of the user's exercise quality. Perform feature recognition on the image information to obtain the user's exercise posture. The greater the difference between the user's movement during exercise and the standard degree, the greater the impact on the user's exercise time and physical condition. People with different physiques have different conditions after exercise. Some users may have knee pain, some users may have too fast heart rate or blood pressure, or some users may have non-standard exercise postures, all of which may lead to a shorter exercise time. Therefore, based on the body type score, exercise posture, heart rate change graph and blood pressure value, determine the exercise score of the user. The lower the exercise score, the greater the possibility that the user will become fatigued or have an accident. When the exercise score is lower than the preset score threshold, output an alarm message and stop continuing the exercise, which can timely and accurately predict the situation that hypertensive users become fatigued or have an accident during running. Brief Description of the Drawings

[0024] Figure 1 It is a schematic flow chart of a method for monitoring the state of personnel during exercise according to an embodiment of the present application.

[0025] Figure 2 It is a schematic structural diagram of a system for monitoring the state of personnel during exercise according to an embodiment of the present application.

[0026] Figure 3 It is a schematic structural diagram of an electronic device according to an embodiment of the present application. Detailed Embodiment

[0027] The following further describes the present application in detail with reference to the accompanying drawings.

[0028] Those skilled in the art can make modifications to this embodiment without creative contributions according to needs after reading this specification, but as long as it is within the scope of the claims of the present application, it is protected by the Patent Law.

[0029] To make the objectives, technical solutions, and advantages of the embodiments of the present application clearer, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present application. Obviously, the described embodiments are some, but not all, of the embodiments of the present application. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present application without creative efforts belong to the scope of protection of the present application.

[0030] In addition, the term "and / or" in this article is only a description of the association relationship of associated objects, indicating that there can be three relationships. For example, A and / or B can represent: A exists alone, A and B exist at the same time, and B exists alone. In addition, the character " / " in this article, unless otherwise specified, generally means that the associated objects before and after are in an "or" relationship.

[0031] The embodiments of the present application are further described in detail below in conjunction with the drawings in the specification.

[0032] The embodiment of the present application provides a method for monitoring the status of a person during exercise, which is performed by an electronic device, which can be a server or a terminal device, wherein the server can be an independent physical server, a server cluster or a distributed system composed of multiple physical servers, or a cloud server that provides cloud computing services. The terminal device can be a smart phone, a tablet computer, a laptop computer, a desktop computer, etc., but is not limited thereto. The terminal device and the server can be directly or indirectly connected via wired or wireless communication, which is not limited in the embodiment of the present application. Figure 1 As shown, the method includes step S101, step S102, step S103, step S104 and step S105, wherein: S101, obtaining body fat data of the user before exercise, image information of the user during exercise, and a heart rate variation graph and blood pressure value of the user during exercise.

[0033] With respect to the embodiments of the present application, special attention needs to be paid to the state of people with hypertension during exercise to ensure the safety and effectiveness of the exercise. However, due to unstable blood pressure or high blood pressure levels, users with hypertension are more likely to have accidents when running than normal people. Therefore, users will be measured by a body fat scale before exercise to collect body fat data. The body fat scale is wirelessly connected to an electronic device, which records the user's physical condition before each exercise, and then the electronic device obtains the user's body fat data before exercise. Users may exercise in places such as gyms or fitness plazas. The age group corresponding to gyms may be young and middle-aged people, and fitness plazas are more inclined to middle-aged and elderly people. Gyms, fitness plazas and other places are all equipped with camera devices that can monitor users during exercise. The camera devices are connected to the electronic device by wire or wirelessly, and then the electronic device can obtain image information of the user during exercise.

[0034] When exercising, users can wear sports bracelets or other measuring devices that can collect heart rate and blood pressure data. Users with hypertension may have too fast a heart rate or too high a blood pressure when exercising. The measuring devices are also wirelessly connected to electronic devices, which obtain and generate a graph of the user's heart rate changes and blood pressure values ​​during exercise.

[0035] S102. Determine the body type score of the user based on the body fat data and image information.

[0036] For the embodiments of the present application, the body type of each user can reflect a part of the physical condition. The electronic device determines the body type score of the user based on the body fat data and image information, and the body type score characterizes the level of the user's sports quality.

[0037] S103. Perform feature recognition on the image information to obtain the user's motion posture.

[0038] For the embodiments of the present application, the electronic device inputs the image information into a trained network model for feature recognition to obtain the user's motion posture. The greater the difference between the user's motion actions and the standard degree during exercise, the greater the impact on the user's exercise time and physical condition.

[0039] S104. Determine the exercise score of the user based on the body type score, motion posture, heart rate change graph, and blood pressure value.

[0040] For the embodiments of the present application, the conditions of different people with different physiques after exercise are different. Some users may have knee pain, some users may have too fast heart rate or blood pressure, or some users may have non-standard motion postures, all of which may lead to a shorter exercise time. Therefore, the body type score, motion posture, heart rate change graph, and blood pressure value are all important factors affecting the user's exercise score. Therefore, the electronic device determines the user's exercise score based on the body type score, motion posture, heart rate change graph, and blood pressure value. The lower the exercise score, the greater the adverse reaction of the user to this exercise, and the greater the possibility of the user getting tired or having an accident.

[0041] S105. When the exercise score is lower than the preset score threshold, output an alarm message and stop continuing the exercise.

[0042] For the embodiments of the present application, when the electronic device monitors that the exercise score is lower than the preset score threshold, it means that the user may be about to get tired at this time, and the physical condition is no longer suitable for continuing the exercise. And continuing the exercise may lead to an accident. Therefore, the electronic device outputs an alarm message and stops continuing the exercise. The alarm message can be a voice prompt of the exercise device or a text message prompt sent to the terminal device of the staff. The image information of the user during exercise reflects the user's motion posture. The body type score of the user is determined through the body fat data before the user exercises and the image information during exercise. The exercise score of the user is determined based on the body type score, motion posture, heart rate change graph, and blood pressure value. When the exercise score is lower than the preset score threshold, an alarm message is output and the continuation of the exercise is stopped, which can timely and accurately predict the situation of hypertensive users getting tired or having an accident during running.

[0043] In a possible implementation of the embodiment of the present application, in step S102, determining the body type score of the user based on the body fat data and the image information specifically includes step S1021 (not shown in the figure), step S1022 (not shown in the figure), step S1023 (not shown in the figure), and step S1024 (not shown in the figure), where Step S1021, determining the preset interval where the body fat data is located, and determining the first body type corresponding to the preset interval.

[0044] For the embodiment of the present application, the body fat data may include body fat percentage, BMI (Body Mass Index), muscle mass, water percentage, etc. Each type of data is divided into a preset interval, and each body type corresponds to its own matching preset interval. Therefore, the electronic device determines the preset interval corresponding to the body fat data and determines the first body type corresponding to the preset interval.

[0045] Step S1022, performing human feature recognition on the image information to determine the height and contour of the user.

[0046] For the embodiment of the present application, the electronic device performs human feature recognition on the image information to determine the height and contour of the user. Different heights or contours will result in different effective exercise durations.

[0047] Step S1023, determining the corresponding second body type based on the height and contour.

[0048] For the embodiment of the present application, each body type also corresponds to its own height interval and contour interval. Therefore, the electronic device determines the corresponding second body type based on the height and contour.

[0049] Step S1024, determining the lowest score corresponding to the first body type and the second body type as the body type score of the user. Each body type corresponds to a different preset score.

[0050] For the embodiment of the present application, each body type corresponds to a different preset score, and the electronic device determines the lowest score corresponding to the first body type and the second body type as the body type score of the user.

[0051] In a possible implementation of the embodiment of the present application, in step S104, determining the exercise score of the user based on the body type score, exercise posture, heart rate change graph, and blood pressure value specifically includes step S1041 (not shown in the figure), step S1042 (not shown in the figure), step S1043 (not shown in the figure), step S1044 (not shown in the figure), and step S1045 (not shown in the figure), where Step S1041, determining the initial heart rate and maximum heart rate of the user in the heart rate change graph, and the required duration for the maximum heart rate to appear for the first time.

[0052] For the embodiments of the present application, the electronic device determines the user's initial heart rate, maximum heart rate, and the required duration for the first appearance of the maximum heart rate based on the user's heart rate variation graph. The shorter the required duration, the faster the user's heart rate increases, which may lead to accidents for the user.

[0053] Step S1042: Determine the highest blood pressure value among the blood pressure values.

[0054] For the embodiments of the present application, the electronic device determines the highest blood pressure value among the blood pressure values.

[0055] Step S1043: Determine the user's heart rate growth rate based on the initial heart rate, maximum heart rate, and required duration.

[0056] For the embodiments of the present application, the electronic device determines the heart rate difference between the initial heart rate and the maximum heart rate, and determines the ratio between the heart rate difference and the required duration, which is the user's heart rate growth rate.

[0057] Step S1044: Determine the user's supplementary score based on the exercise posture.

[0058] For the embodiments of the present application, when the user exercises, they have their own exercise postures. Different exercise postures reflect different degrees of standardization of the user's postures. Therefore, the electronic device can determine the similarity between each exercise posture and the corresponding standard posture, and determine the average value of all similarities to determine the user's supplementary score.

[0059] Step S1045: Determine the user's exercise score based on the body type score, supplementary score, heart rate growth rate, highest blood pressure value, and their respective first coefficients.

[0060] For the embodiments of the present application, the electronic device determines the user's exercise score based on the body type score, supplementary score, heart rate growth rate, highest blood pressure value, and their respective first coefficients. The lower the body type score and the supplementary score, the lower the user's exercise score. In the case of a faster heart rate growth rate or a higher highest blood pressure value, the user's exercise score will also be lower.

[0061] A possible implementation manner of the embodiments of the present application, the method further includes Step One, Step Two, Step Three, Step Four, and Step Five, where Step One: Determine the target person from the historical database based on the body fat data, height, and profile.

[0062] Among them, the historical database is the data of other hypertensive users participating in this exercise, and the target person is the person whose target similarity to the user's physical condition reaches the preset similarity threshold.

[0063] For the embodiments of this application, when each hypertensive user participates in this exercise, the exercise device will store all the data of each user and the information of each user. The electronic device determines, based on the body fat data, height, and profile, target persons from the historical database whose target similarity to the user's physical condition reaches a preset similarity threshold.

[0064] Step 2: Obtain the historical exercise duration of each target person.

[0065] For the embodiments of this application, for persons with similar physical conditions, their exercise data may also be similar when exercising. Therefore, the electronic device obtains the historical exercise duration of each target person.

[0066] Step 3: Determine the first preset duration interval where each historical exercise duration is located from multiple preset duration intervals.

[0067] For the embodiments of this application, the electronic device determines the first preset duration interval where each historical exercise duration is located from multiple preset duration intervals.

[0068] Step 4: Determine the number of target persons corresponding to each first preset duration interval.

[0069] For the embodiments of this application, the electronic device determines the number of target persons corresponding to each first preset duration interval.

[0070] Step 5: Determine the first preset duration interval with the largest number as the target preset duration interval for the user.

[0071] For the embodiments of this application, among all the target persons, filter out the target persons with overly high or low physical fitness. The exercise duration corresponding to the remaining target persons is very likely to be the maximum duration that the user can achieve. Therefore, the electronic device determines the first preset duration interval with the largest number as the target preset duration interval for the user.

[0072] A possible implementation manner of the embodiments of this application is that in Step 1, the target persons are determined from the historical database based on the body fat data, height, and profile. The historical database is the data of other hypertensive users participating in this exercise, and the target persons are those whose target similarity to the user's physical condition reaches the preset similarity threshold. Specifically, it includes Step S1 (not shown in the figure), Step S2 (not shown in the figure), Step S3 (not shown in the figure), and Step S4 (not shown in the figure). Among them, Step S1: Determine the preset height deviation range of the height, and determine the first persons within the preset height deviation range from the historical database.

[0073] For the embodiments of the present application, the electronic device determines a preset height deviation range of the user's height, and determines a first person within the preset height deviation range from the historical database. For example, when the user's height is 173 cm, the preset height deviation range can be determined to be 171 cm - 175 cm, including 171 cm and 175 cm.

[0074] Step S2, determine a first similarity between the profile and the profile of the first person, and determine a second similarity between the body fat data and the body fat data of the first person.

[0075] For the embodiments of the present application, for hypertensive users with a height similar to that of the user, the profile and body fat data are also important factors for screening out a person with a more similar physique to the user. Therefore, the electronic device determines a first similarity between the profile of the user and the profile of the first person, and determines a second similarity between the body fat data of the user and the body fat data of the first person.

[0076] Step S3, determine a target similarity based on the first similarity, the second similarity, and their respective second coefficients.

[0077] For the embodiments of the present application, the electronic device determines a target similarity based on the first similarity, the second similarity, and their respective second coefficients.

[0078] Step S4, determine the person whose target similarity reaches the preset similarity threshold as the target person.

[0079] For the embodiments of the present application, the exercise situation of the target person with a height similar to that of the user and a highly matched physical condition is used to more accurately represent the exercise situation of the user. That is, the electronic device determines the person whose target similarity reaches the preset similarity threshold as the target person.

[0080] In a possible implementation manner of the embodiments of the present application, the method further includes step Sa, step Sb, step Sc, step Sd, step Se, and step Sf, where Step Sa, obtain the start time and end time of the user's exercise.

[0081] For the embodiments of the present application, the user's exercise time can be recorded by the user himself / herself using a sports bracelet or sports device, and the electronic device obtains the start time and end time of the user's exercise.

[0082] Step Sb, determine the exercise duration of the user based on the start time and end time.

[0083] For the embodiments of the present application, the electronic device determines the difference between the start time and the end time, which is the exercise duration of the user.

[0084] Step Sc, determine the user's heart rate recovery time based on the exercise duration, body type score, and their respective third coefficients.

[0085] For the embodiments of this application, the heart rate recovery of hypertensive users may be slower after exercise. The longer the exercise duration, the longer the required recovery time, and the lower the body type score, the longer the required recovery time. Therefore, the electronic device determines the user's heart rate recovery time based on the exercise duration, body type score, and their respective third coefficients.

[0086] Step Sd, when the heart rate recovery time has passed, obtain the user's current heart rate.

[0087] For the embodiments of this application, when the electronic device monitors that the heart rate recovery time has passed, obtain the user's current heart rate.

[0088] Step Se, determine whether the current heart rate is within a preset heart rate range.

[0089] For the embodiments of this application, after the heart rate recovery time has passed, the user's heart rate should return to the preset heart rate range for normal conditions. Therefore, the electronic device determines whether the current heart rate is within the preset heart rate range.

[0090] Step Sf, if it is not within the range, control the sports bracelet to vibrate and prompt the staff.

[0091] For the embodiments of this application, if it is not within the range, it indicates that there may be an abnormality in the user's physical condition. Then the electronic device controls the sports bracelet to vibrate and prompt the staff to observe the user's subsequent status in a timely manner.

[0092] A possible implementation of the embodiments of this application, the method further includes Step Six, Step Seven, Step Eight, and Step Nine, where Step Six, when the user turns on the fitness device, obtain the user's pre-exercise diet time, diet amount, and current time.

[0093] For the embodiments of this application, if the user exercises immediately after a meal, it may cause harm to the body and may lead to unexpected situations. Therefore, when the electronic device monitors that the user turns on the fitness device, obtain the user's pre-exercise diet time, diet amount, and current time.

[0094] Step Seven, determine the post-meal interval of the user based on the diet time and the current time.

[0095] For the embodiments of this application, the electronic device determines the user's post-meal interval based on the difference between the diet time and the current time. The shorter the post-meal interval, the greater the harm caused by exercise.

[0096] Step Eight, determine whether the user can start exercising based on the post-meal interval and the diet amount.

[0097] For the embodiments of the present application, the electronic device sets different post - meal intervals for different diet amounts. Therefore, the electronic device determines whether the user can start exercising based on the post - meal interval and the diet amount.

[0098] Step Nine, if not, control the fitness device to turn off and remind the user to take a rest.

[0099] For the embodiments of the present application, if not, the electronic device controls the fitness device to turn off and reminds the user to take a rest.

[0100] The above embodiments introduce a method for monitoring the state of personnel during exercise from the perspective of the method process. The following embodiments introduce a system for monitoring the state of personnel during exercise from the perspective of virtual modules or virtual units. For details, see the following embodiments.

[0101] The embodiments of the present application provide a system 20 for monitoring the state of personnel during exercise, as Figure 2 shown. The system 20 for monitoring the state of personnel during exercise may specifically include: A first acquisition module 201, configured to acquire the body fat data of the user before exercise, the image information of the user during exercise, the heart rate change graph of the user during exercise, and the blood pressure value; A body type score determination module 202, configured to determine the body type score of the user based on the body fat data and the image information; An identification module 203, configured to perform feature recognition on the image information to obtain the exercise posture of the user; A motion score determination module 204, configured to determine the motion score of the user based on the body type score, the exercise posture, the heart rate change graph, and the blood pressure value; An output module 205, configured to output an alarm message and stop further exercise when the motion score is lower than a preset score threshold.

[0102] The embodiment of the present application discloses a system 20 for monitoring the state of a person during exercise. Among them, the first acquisition module 201 acquires the body fat data of the user before exercise, the image information of the user during exercise, the heart rate change graph and blood pressure value of the user during exercise. The state of hypertensive people during exercise needs to be particularly concerned about to ensure the safety and effectiveness of exercise. Therefore, the user will be measured by a body fat scale before exercise. The body type score determination module 202 determines the body type score of the user based on the body fat data and image information. The body type score characterizes the level of the user's exercise quality. The recognition module 203 performs feature recognition on the image information to obtain the exercise posture of the user. The greater the difference between the actions of the user during exercise and the standard degree, the greater the impact on the user's exercise time and physical condition. The post-exercise conditions of people with different physiques are different. Some users may have knee pain, some users may have too fast heart rate or blood pressure, or some users may have non-standard exercise postures, all of which may lead to a shorter exercise time. Therefore, the exercise score determination module 204 determines the exercise score of the user based on the body type score, exercise posture, heart rate change graph and blood pressure value. The lower the exercise score, the greater the possibility that the user will become tired or have an accident. When the exercise score is lower than the preset score threshold, the output module 205 outputs an alarm message and stops continuing the exercise, which can predict in a timely and accurate manner the situation where a hypertensive user becomes tired or has an accident during running.

[0103] In a possible implementation manner of the embodiment of the present application, when the body type score determination module 202 determines the body type score of the user based on the body fat data and image information, it is specifically used for: Determine the preset interval where the body fat data is located, and determine the first body type corresponding to the preset interval; Perform human feature recognition on the image information to determine the height and contour of the user; Determine the corresponding second body type based on the height and contour; Determine the lowest score corresponding to the first body type and the second body type as the body type score of the user. Each body type corresponds to a different preset score.

[0104] In a possible implementation manner of the embodiment of the present application, when the exercise score determination module 204 determines the exercise score of the user based on the body type score, exercise posture, heart rate change graph and blood pressure value, it is specifically used for: Determine the initial heart rate and maximum heart rate of the user in the heart rate change graph, and the required duration for the first appearance of the maximum heart rate; Determine the highest blood pressure value in the blood pressure value; Determine the heart rate growth rate of the user based on the initial heart rate, maximum heart rate and required duration; Determine the supplementary score of the user based on the exercise posture; Determine the exercise score of the user based on the body type score, supplementary score, heart rate growth rate, highest blood pressure value and their respective first coefficients.

[0105] A possible implementation manner of the embodiment of the present application, the system 20 further includes: A target person determination module, configured to determine a target person from a historical database based on body fat data, height, and profile. The historical database is the data of other hypertensive users participating in this exercise, and the target person is a person whose target similarity to the user's physical condition reaches a preset similarity threshold; A second acquisition module, configured to acquire the historical exercise duration of each target person; A first determination module, configured to determine the first preset duration interval where each historical exercise duration is located from multiple preset duration intervals; A quantity determination module, configured to determine the quantity of target persons corresponding to each first preset duration interval; A second determination module, configured to determine the first preset duration interval with the largest quantity as the target preset duration interval of the user.

[0106] A possible implementation manner of the embodiment of the present application, when the target person determination module determines a target person from the historical database based on body fat data, height, and profile, it is specifically configured to: Determine a preset height deviation range of the height, and determine the first persons belonging to the preset height deviation range from the historical database; Determine the first similarity between the profile and the profile of the first person, and determine the second similarity between the body fat data and the body fat data of the first person; Determine the target similarity based on the first similarity, the second similarity, and their respective second coefficients; Determine the persons whose target similarity reaches the preset similarity threshold as the target persons.

[0107] A possible implementation manner of the embodiment of the present application, the system 20 further includes: A third acquisition module, configured to acquire the start time and end time of the user's exercise; A third determination module, configured to determine the exercise duration of the user based on the start time and end time; A fourth determination module, configured to determine the heart rate recovery time of the user based on the exercise duration, body type score, and their respective third coefficients; A fourth acquisition module, configured to acquire the current heart rate of the user after the heart rate recovery time; A first judgment module, configured to judge whether the current heart rate is within a preset heart rate interval; A first control module, configured to, if not, control the sports bracelet to vibrate and prompt the staff.

[0108] A possible implementation manner of the embodiment of the present application, the system 20 further includes: A fifth acquisition module, configured to obtain the user's pre-exercise eating time, eating amount, and the current time when the user turns on the fitness device; A fifth determination module, configured to determine the post-meal interval of the user based on the eating time and the current time; A second judgment module, configured to judge whether the user can start exercising based on the post-meal interval and the eating amount; A second control module, configured to, if not, control the fitness device to turn off and remind the user to take a rest.

[0109] In an embodiment of the present application, an electronic device is provided, as Figure 3 shown, Figure 3 The electronic device 30 shown includes a processor 301 and a memory 303. Among them, the processor 301 and the memory 303 are connected, such as connected through a bus 302. Optionally, the electronic device 30 may further include a transceiver 304. It should be noted that in practical applications, the transceiver 304 is not limited to one, and the structure of the electronic device 30 does not constitute a limitation to the embodiment of the present application.

[0110] The processor 301 may be a CPU (Central Processing Unit), a general-purpose processor, a DSP (Digital Signal Processor), an ASIC (Application Specific Integrated Circuit), an FPGA (Field Programmable Gate Array), or other programmable logic devices, transistor logic devices, hardware components, or any combination thereof. It can implement or execute various exemplary logical blocks, modules, and circuits described in combination with the disclosure of the present application. The processor 301 may also be a combination for implementing computing functions, such as a combination including one or more microprocessors, a combination of a DSP and a microprocessor, etc.

[0111] The bus 302 may include a path for transmitting information between the above components. The bus 302 may be a PCI (Peripheral Component Interconnect) bus or an EISA (Extended Industry Standard Architecture) bus, etc. The bus 302 may be divided into an address bus, a data bus, a control bus, etc. For the sake of representation, Figure 3 only a thick line is used to represent it in the figure, but it does not mean that there is only one bus or one type of bus.

[0112] The memory 303 can be a ROM (Read Only Memory), or other types of static storage devices that can store static information and instructions, a RAM (Random Access Memory), or other types of dynamic storage devices that can store information and instructions. It can also be an EEPROM (Electrically Erasable Programmable Read Only Memory), a CD-ROM (Compact Disc Read Only Memory), or other optical disc storage, optical disc storage (including compact discs, laser discs, optical discs, digital versatile discs, Blu-ray discs, etc.), magnetic disk storage media, or other magnetic storage devices, or any other medium that can be used to carry or store the desired program code in the form of instructions or data structures and can be accessed by a computer, but is not limited thereto.

[0113] The memory 303 is used to store the application program code for executing the solution of this application, and is controlled by the processor 301 for execution. The processor 301 is used to execute the application program code stored in the memory 303 to implement the content shown in the foregoing method embodiments.

[0114] Among them, the electronic device includes but is not limited to: mobile terminals such as mobile phones, laptop computers, digital broadcast receivers, PDAs (Personal Digital Assistants), PADs (Tablet Computers), PMPs (Portable Multimedia Players), in-vehicle terminals (such as in-vehicle navigation terminals), etc., and fixed terminals such as digital TVs, desktop computers, etc. It can also be a server, etc. Figure 3 The shown electronic device is only an example and should not impose any limitations on the functions and usage scope of the embodiments of this application.

[0115] An embodiment of the present application provides a computer-readable storage medium, on which a computer program is stored. When it runs on a computer, the computer can execute the corresponding content in the foregoing method embodiment. Compared with the related art, in the embodiment of the present application, body fat data before user movement, image information during user movement, heart rate change graph and blood pressure value during user movement are obtained. The state of hypertensive people during exercise needs to be particularly concerned about to ensure the safety and effectiveness of exercise. Therefore, before exercise, users will be measured by a body fat scale. Based on the body fat data and image information, a body type score of the user is determined. The body type score characterizes the level of the user's exercise quality. Feature recognition is performed on the image information to obtain the user's exercise posture. The greater the difference between the user's movement during exercise and the standard degree, the greater the impact on the user's exercise time and physical condition. People with different physiques have different conditions after exercise. Some users may have knee pain, some users may have too fast heart rate or blood pressure, or some users' exercise postures are not standard, all of which may lead to a shorter exercise time. Therefore, based on the body type score, exercise posture, heart rate change graph and blood pressure value, the exercise score of the user is determined. The lower the exercise score, the greater the possibility that the user will become fatigued or have an accident. When the exercise score is lower than the preset score threshold, an alarm message is output and the exercise is stopped, which can timely and accurately predict the situation that hypertensive users become fatigued or have an accident during running.

[0116] It should be understood that although the steps in the flowchart of the accompanying drawings are shown in sequence according to the indication of the arrows, these steps are not necessarily executed in the order indicated by the arrows. Unless there is a clear description in this article, the execution of these steps has no strict order limitation, and they can be executed in other orders. Moreover, at least a part of the steps in the flowchart of the accompanying drawings may include multiple sub-steps or multiple stages. These sub-steps or stages are not necessarily executed at the same time, but can be executed at different times. Their execution order is not necessarily sequential, but can be executed alternately or alternately with at least a part of other steps or sub-steps or stages of other steps.

[0117] The above are only some embodiments of the present application. It should be noted that for those of ordinary skill in the art, without departing from the principle of the present application, several improvements and refinements can be made, and these improvements and refinements should also be regarded as the protection scope of the present application.

Claims

1. A method for monitoring the status of personnel during exercise, characterized in that: include: Obtain the user's body fat data before exercise, image information during exercise, and heart rate change graph and blood pressure value during exercise; Determine a body shape score of the user based on the body fat data and the image information; Performing feature recognition on the image information to obtain the user's motion posture; Determine the user's exercise score based on the body shape score, exercise posture, heart rate variation graph and blood pressure value; When the exercise score is lower than a preset score threshold, an alarm message is output and the exercise is stopped.

2. A method for monitoring the status of a person in a sports process according to claim 1, characterized in that: The determining the user's body shape score based on the body fat data and the image information includes: Determine a preset interval in which the body fat data is located, and determine a first body type corresponding to the preset interval; Performing personal feature recognition on the image information to determine the height and outline of the user; Determining a corresponding second body type based on the height and outline; The lowest score corresponding to the first body type and the second body type is determined as the body type score of the user, and each body type corresponds to a different preset score.

3. A method for monitoring the status of a person in a sports process according to claim 1, characterized in that: The determining of the user's exercise score based on the body shape score, exercise posture, heart rate variation graph and blood pressure value includes: Determine the initial heart rate and maximum heart rate of the user in the heart rate variation graph, and the time required for the maximum heart rate to appear for the first time; determining the highest blood pressure value among the blood pressure values; Determine the user's heart rate growth rate based on the initial heart rate, maximum heart rate, and required time; determining a supplemental score for the user based on the motion gesture; The user's exercise score is determined based on the body shape score, the supplement score, the heart rate growth rate, the highest blood pressure value and the respective first coefficients.

4. A method for monitoring the status of a person in a sports process according to claim 2, characterized in that: The method further comprises: Determine a target person from a historical database based on the body fat data, height and outline, wherein the historical database is various data of other hypertensive users participating in the exercise, and the target person is a person whose target similarity with the user's physical condition reaches a preset similarity threshold; Get the historical movement duration of each target person; Determine a first preset duration interval in which each of the historical exercise durations is located from a plurality of preset duration intervals; Determine the number of target personnel corresponding to each first preset time interval; The first preset time interval with the largest number is determined as the target preset time interval of the user.

5. A method for monitoring the status of a person in a sports process according to claim 4, characterized in that: The step of determining a target person from a historical database based on the body fat data, height and outline includes: Determining a preset height deviation range of the height, and determining a first person within the preset height deviation range from a historical database; determining a first similarity between the outline and the outline of the first person, and determining a second similarity between the body fat data and the body fat data of the first person; Determine a target similarity based on the first similarity, the second similarity and respective second coefficients; Determine the person whose target similarity reaches a preset similarity threshold as the target person.

6. A method for monitoring the status of a person in a sports process according to claim 1, characterized in that: The method further comprises: Get the start and end time of the user's exercise; Determine the user's exercise duration based on the start time and end time; Determine the user's heart rate recovery time based on the exercise duration, the body shape score, and respective third coefficients; After the heart rate recovery time has passed, obtaining the user's current heart rate; Determining whether the current heart rate is within a preset heart rate range; If not, the sports bracelet is controlled to vibrate and prompt the staff.

7. A method for monitoring the status of a person in a sports process according to claim 1, characterized in that: The method further comprises: When the user turns on the fitness equipment, obtain the user's meal time before exercise, meal amount and current time; determining a user's post-meal interval based on the eating time and current time; Determining whether the user can start exercising based on the post-meal interval and the food intake; If not, the fitness equipment is controlled to shut down and the user is reminded to take a rest.

8. A system for monitoring the status of people in a movement process, characterized in that: include: The first acquisition module is used to acquire the body fat data of the user before exercise, the image information of the user during exercise, and the heart rate change graph and blood pressure value of the user during exercise; A body shape score determination module, used to determine the body shape score of the user based on the body fat data and the image information; A recognition module, used to perform feature recognition on the image information to obtain the user's motion posture; An exercise score determination module, used to determine the user's exercise score based on the body shape score, exercise posture, heart rate variation graph and blood pressure value; The output module is used to output an alarm message and stop exercising when the exercise score is lower than a preset score threshold.

9. An electronic device, characterized in that: It includes: at least one processor; Memory; At least one application, wherein the at least one application is stored in the memory and is configured to be executed by the at least one processor, and the at least one application is used to execute a method for monitoring the status of a person in a motion process according to any one of claims 1 to 7.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed in a computer, the computer is caused to execute the method for monitoring the status of a person in a movement process as described in any one of claims 1 to 7.

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