Motion monitoring method and device, electronic equipment and storage medium

Abstract

The invention discloses a motion monitoring method and device, electronic equipment and a storage medium, and the method comprises the steps: determining at least two monitoring parameters in a current motion process, and carrying out the safety event monitoring based on each monitoring parameter; wherein the safety event comprises at least one of fall monitoring, excess motion monitoring and emergency monitoring; if it is determined that the current motion process is ended, determining a motion score of the current motion process; and determining an exercise effect evaluation value according to the exercise score of the current exercise process, and performing exercise reward exchange and / or exercise ranking based on the exercise effect evaluation value. According to the method, the accuracy of multi-dimensional monitoring in the motion process can be improved, the safety of the motion process is improved, and the accurate evaluation of the motion process is realized.

Description

Technical Field

[0001] The present invention relates to the field of data processing technology, and in particular to a motion monitoring method, device, electronic equipment and storage medium. Background Art

[0002] With the development of science and technology and the improvement of living standards, there are more and more types of smart wearable devices. Among them, smart watches and smart bracelets have been widely used. An important function of smart watches and smart bracelets is motion monitoring.

[0003] However, the exercise monitoring functions of existing smart wearable devices are generally limited to statistics on exercise type, exercise time, exercise volume, and heart rate monitoring. They lack safety protection mechanisms during exercise and post-exercise evaluation. Safety protection mechanisms during exercise monitoring and post-exercise evaluation are particularly important for smart wearable devices for children. Summary of the Invention

[0004] The present invention provides a motion monitoring method, device, electronic device and storage medium to improve the accuracy of multi-dimensional monitoring during motion, improve the safety of the motion process, and achieve accurate evaluation of the motion process.

[0005] In a first aspect, an embodiment of the present invention provides a motion monitoring method, the method comprising:

[0006] Determine at least two monitoring parameters during the current exercise process, and perform safety event monitoring based on each monitoring parameter;

[0007] Among them, safety events include at least one of fall monitoring, excessive exercise monitoring, and emergency event monitoring;

[0008] If it is determined that the current exercise process is finished, then the exercise score of the current exercise process is determined;

[0009] Determine the exercise effect evaluation value based on the exercise score of the current exercise process, and perform exercise reward exchange and / or exercise ranking based on the exercise effect evaluation value

[0010] In a second aspect, an embodiment of the present invention further provides a motion monitoring device, the device comprising:

[0011] A safety event monitoring module is used to determine at least two monitoring parameters during the current exercise process and perform safety event monitoring based on the monitoring parameters;

[0012] Among them, safety events include at least one of fall monitoring, excessive exercise monitoring, and emergency event monitoring;

[0013] an exercise score determination module, configured to determine an exercise score for the current exercise process if it is determined that the current exercise process is finished;

[0014] The exercise effect evaluation value determination module is used to determine the exercise effect evaluation value according to the exercise score of the current exercise process, so as to perform exercise reward exchange and / or exercise ranking based on the exercise effect evaluation value.

[0015] In a third aspect, an embodiment of the present invention further provides an electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein when the processor executes the program, the motion monitoring method as described in any one of the embodiments of the present invention is implemented.

[0016] In a fourth aspect, an embodiment of the present invention further provides a storage medium storing computer-executable instructions, wherein the computer-executable instructions, when executed by a computer processor, are used to execute the motion monitoring method as described in any one of the embodiments of the present invention.

[0017] The technical solution of the embodiment of the present invention continuously monitors the parameters of the current exercise process and monitors security events based on the various monitoring parameters. After the current exercise process ends, the exercise score of the current exercise process is determined, and the exercise effect evaluation value is determined based on the exercise score. Subsequently, exercise reward redemption and / or exercise ranking are performed based on the exercise effect evaluation value. This solves the problem of the lack of security protection mechanisms and post-exercise evaluation mechanisms in smart wearable devices in the prior art. Through multi-dimensional detection, the accuracy of exercise process monitoring is improved, the safety of the exercise process is improved, and accurate evaluation of the exercise process is achieved.

[0018] It should be understood that the content described in this section is not intended to identify the key or important features of the embodiments of the present invention, nor is it intended to limit the scope of the present invention. Other features of the present invention will become readily understood through the following description. BRIEF DESCRIPTION OF THE DRAWINGS

[0019] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following briefly introduces the drawings required for use in the description of the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0020] Figure 1 is a flow chart of a motion monitoring method provided by Example 1 of the present invention;

[0021] Figure 2 is a flow chart of a motion monitoring method provided by Embodiment 2 of the present invention;

[0022] Figure 3 is a structural diagram of a motion monitoring device provided by Embodiment 3 of the present invention;

[0023] Figure 4 This is a structural diagram of an electronic device provided in Example 4 of the present invention. DETAILED DESCRIPTION

[0024] In order to enable those skilled in the art to better understand the solutions of the present invention, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the embodiments described are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts should fall within the scope of protection of the present invention.

[0025] It should be noted that the terms "first", "second", etc. in the specification and claims of the present invention and the above-mentioned drawings are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that the data used in this way can be interchangeable where appropriate, so that the embodiments of the present invention described herein can be implemented in an order other than those illustrated or described herein. In addition, the terms "including" and "having" and any variations thereof are intended to cover non-exclusive inclusions. For example, a process, method, system, product or device that includes a series of steps or units is not necessarily limited to those steps or units clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices. In the embodiments of the present application, certain software, components, models and other existing solutions in the industry may be mentioned, and they should be considered as exemplary. Their purpose is merely to illustrate the feasibility of the implementation of the technical solution of the present application, but it does not mean that the applicant has or will necessarily use the solution.

[0026] The acquisition, transmission, storage, use, and processing of data in the technical solution of this application comply with the relevant provisions of national laws and regulations.

[0027] Example 1

[0028] Figure 1 A flowchart of a motion monitoring method is provided for the first embodiment of the present invention. This embodiment is applicable to situations where safety monitoring of the exercise process and effect evaluation after exercise are performed. The method can be performed by a motion monitoring device, which can be implemented in the form of hardware and / or software. The motion monitoring device can be configured in a smart wearable device, such as a smart watch, a smart bracelet, etc.

[0029] like Figure 1 As shown, the method includes:

[0030] S110: Determine at least two monitoring parameters during the current exercise process, and perform safety event monitoring based on the monitoring parameters.

[0031] Among them, the current exercise process can be started in response to the setting of the exercise monitoring object through the user interaction interface of the smart wearable device. Exemplarily, the exercise monitoring object can set the exercise type through the user interaction interface of the smart wearable device and click the start button to start the current exercise process. It can also be determined that the current exercise process is in progress based on the monitoring parameters by continuously monitoring various monitoring parameters. Specifically, if it is monitored that the speed remains within the running speed range for a period of time and the three-axis acceleration shows a periodic change pattern, it can be determined that the current state is in the running exercise process.

[0032] The types of monitored parameters may include speed, three-axis acceleration, angular velocity, position, heart rate, temperature, light intensity, etc. This embodiment does not limit the types of monitored parameters. For example, three-axis acceleration can be monitored by an acceleration sensor, angular velocity can be monitored by a gyroscope, position can be monitored by a positioning system, speed can be obtained by combining position, acceleration, and angular velocity through multi-dimensional information fusion, heart rate can be monitored by PPG (photoplethysmography) technology, and temperature and light intensity can be monitored by a temperature sensor and a light intensity sensor, respectively.

[0033] Safety events include at least one of fall monitoring, excessive exercise monitoring, and emergency event monitoring. Fall monitoring is the process of determining whether the subject has fallen; excessive exercise monitoring is the process of determining whether the subject's exercise volume exceeds a safe range; and emergency event monitoring is the process of determining whether the subject is in a situation requiring emergency assistance.

[0034] In this embodiment, multi-dimensional sensors are integrated into smart wearable devices to achieve multi-dimensional parameter monitoring, so that quantitative judgment of security events can be made based on multi-dimensional monitoring parameters, thereby improving the accuracy of security event monitoring.

[0035] Furthermore, at least two monitoring parameters during the current exercise process are determined, and fall monitoring is performed based on the monitoring parameters, including:

[0036] A1. Determine the three-axis acceleration, angular velocity, and heart rate during the current exercise;

[0037] A2. If at least one of the following conditions is met: the rate of change of the three-axis acceleration is greater than or equal to the preset acceleration rate of change threshold, the rate of change of the angular velocity is greater than or equal to the preset angular velocity rate of change threshold, and the difference in heart rate within the preset time period is greater than or equal to the preset difference threshold, then it is determined that the current state is a fall.

[0038] This embodiment provides a specific implementation method for fall monitoring by combining three-axis acceleration, angular velocity, and heart rate.

[0039] Among them, if the rate of change of the three-axis acceleration is greater than or equal to the preset acceleration rate threshold, it means that the instantaneous change of the three-axis acceleration is large, the degree of motion mutation is large, and the possibility of falling is high. If the rate of change of the angular velocity is greater than or equal to the preset angular velocity rate threshold, it means that the rotation state of the motion monitoring object has changed more dramatically. The difference in heart rate within a preset time period is greater than or equal to the preset difference threshold. For example, the difference in heart rate within 5 seconds can be greater than 20, or the ratio of the difference in heart rate within 5 seconds to the heart rate 5 seconds ago is greater than or equal to 30%.

[0040] Specifically, this embodiment can flexibly adjust the specific method of determining a fall state based on the above three judgment conditions according to the actual needs of motion monitoring. For example, it can be set so that when all three conditions are met at the same time, it is determined that the current state is a fall. It is also possible to select at least one judgment condition for fall monitoring based on the age of the subject being monitored, the type of exercise, etc. For example, if the subject is relatively young, it can be set so that a fall state is determined when any one of the three judgment conditions is met. It is also possible to set weights for the three monitoring parameters based on the age of the subject being monitored, the type of exercise, etc., and perform a weighted sum of the ratio of the difference between the axial acceleration change rate and the acceleration change rate threshold divided by the acceleration change rate threshold, the ratio of the difference between the angular velocity change rate and the angular velocity change rate threshold divided by the angular velocity change rate threshold, and the ratio of the heart rate difference to the heart rate before a preset time. The resulting value is then compared with a preset threshold to determine whether a fall state has occurred.

[0041] In this embodiment, by combining three-axis acceleration, angular velocity and heart rate, quantitative judgment of the fall state can be achieved, greatly reducing the fall misjudgment rate.

[0042] Furthermore, when it is determined that the current state is a fall, a fall alarm reminder can be issued through voice, or a fall reminder can be sent to the client bound to the smart wearable device, so that the motion monitoring object in the fall state can receive timely attention.

[0043] Furthermore, in addition to fall monitoring, this embodiment can also implement running state monitoring and stationary state monitoring. Specifically, the acceleration during the current motion process is determined, and the acceleration is converted into an acceleration frequency spectrum. In addition, the gait cycle is determined based on the acceleration, where the gait cycle refers to the complete cycle from the heel of one side of the motion monitoring subject touching the ground to the heel of the same side touching the ground again. If it is determined that the acceleration frequency spectrum is within a preset range, such as 2-4Hz, and the gait cycle standard deviation is less than a preset standard deviation threshold, such as 0.2, then it is determined that the current state is running.

[0044] Specifically, the acceleration and position during the current motion process are determined, and the acceleration variance and displacement within a preset time interval are determined. If the variance is less than or equal to a preset variance threshold, such as 0.1, and the displacement is less than or equal to a displacement threshold, such as 10m, then it is determined that the current state is static.

[0045] In this embodiment, accurate monitoring of the motion state is achieved through the fusion of multi-dimensional monitoring parameters.

[0046] Furthermore, at least two monitoring parameters during the current exercise process are determined, and based on each monitoring parameter, excessive exercise monitoring is performed, including:

[0047] B1. Determine the amount of exercise, safety threshold, and heart rate during the current exercise process;

[0048] B2. If it is determined that the amount of exercise is greater than or equal to the safety threshold, and / or the duration of the heart rate being greater than or equal to the preset heart rate threshold is greater than or equal to the preset time threshold, it is determined that the current state is excessive exercise.

[0049] Among them, the amount of exercise can be calculated based on data such as exercise mode, exercise time, heart rate, acceleration and angular velocity. The safety threshold is used to evaluate whether the amount of exercise exceeds the safety range. It can be a pre-set value. Specifically, it can be set according to the exercise mode, the age of the exercise monitoring object, etc.; it can also be a dynamically adjusted value.

[0050] The duration of the heart rate being greater than or equal to a preset heart rate threshold is greater than or equal to a preset time threshold. For example, the heart rate threshold can be calculated by (220-age of the exercise monitoring subject)×0.9, and the time threshold can be set to 5 minutes.

[0051] In this embodiment, the determination criteria of exercise intensity and heart rate can be set to either meet or not, or only meet both criteria to determine excessive exercise. Similarly, the setting can be flexible according to the actual needs of exercise monitoring, the age of the exercise monitoring subject, etc.

[0052] Furthermore, the safety threshold during the current movement is determined, including:

[0053] Determine the safety threshold during the current motion process according to the following formula: Wherein, T represents the safety threshold, BMR represents the basal metabolic rate of the exercise detection subject, HRV represents the heart rate variability, age represents the age of the exercise detection subject, and R represents the heart rate of the exercise detection subject.

[0054] Among them, BMR (Basal Metabolic Rate) can be calculated according to the Basal Metabolic Rate equation. HRV (Heart Rate Variability) refers to the degree of time variation between successive heartbeat cycles. The pulse wave signal can be collected by a PPG sensor, and the time intervals between adjacent peaks of the pulse wave signal can be converted into millisecond-level data to form an RR interval sequence. The HRV index can be calculated through time domain, frequency domain or nonlinear analysis methods.

[0055] In this embodiment, since HRV and heart rate are both dynamically changing data, and since the safety threshold is also a dynamically changing value, the use of a dynamic safety threshold can provide more accurate overexertion alerts and can be personalized to suit the different physical conditions and athletic abilities of exercisers, thereby improving safety. Furthermore, incorporating heart rate monitoring into overexertion monitoring enables timely detection and rapid response to heart rate anomalies.

[0056] Furthermore, when it is determined that the current state is excessive exercise, an excessive exercise reminder can be given through voice, or an excessive exercise reminder can be sent to the client bound to the smart wearable device, so that the exercise monitoring object who is not suitable to continue exercising can receive timely intervention.

[0057] Furthermore, at least two monitoring parameters during the current exercise process are determined, and emergency event monitoring is performed based on each monitoring parameter, including:

[0058] C1. Determine the acceleration, position, heart rate, and ambient light intensity during the current exercise;

[0059] C2. If it is determined that the acceleration variance within the preset time period is less than or equal to the preset variance threshold, the displacement between positions within the preset time period is less than or equal to the preset displacement threshold, the heart rate fluctuation within the preset time period is less than or equal to the preset fluctuation threshold, and the ambient light intensity difference within the preset time period is greater than or equal to the preset light intensity difference threshold, then it is determined that the current state is an emergency.

[0060] This embodiment implements a four-dimensional trigger mechanism for emergency status. Specifically, an emergency is identified only when acceleration, position, heart rate, and ambient light intensity simultaneously meet these four conditions. This configuration effectively avoids misjudgments caused by a single trigger mechanism and significantly improves the accuracy of emergency status detection.

[0061] Furthermore, when it is determined that the current state is an emergency, an emergency state prompt can be sent to the client bound to the smart wearable device so that the motion monitoring object can get help in time.

[0062] S120: If it is determined that the current exercise process is finished, determine the exercise score of the current exercise process.

[0063] Correspondingly, the end of the current exercise process can also be determined in response to the exercise monitoring subject setting it through the user interface of the smart wearable device. For example, the exercise monitoring subject can click the exercise end button through the user interface of the smart wearable device to end the current exercise process. Alternatively, the end of the current exercise process can be determined based on the monitoring parameters by continuously monitoring the various monitoring parameters.

[0064] The exercise score can be determined based on the exercise mode or exercise type of the current exercise process and the actual exercise situation. Specifically, if the exercise type is set to running, the exercise score of the current exercise process can be evaluated based on the exercise time, average exercise speed, average heart rate, and mileage of the current exercise process. It can also be determined based on pre-set evaluation criteria and the actual exercise situation of the current exercise process. Specifically, if the current exercise process is an 800m running test in a physical test process, the exercise score can be determined based on the pre-set correspondence between time and score and the actual time of the current exercise process.

[0065] In this embodiment, the exercise score is used to accurately reflect the objective exercise situation of the current exercise process.

[0066] S130. Determine an exercise effect evaluation value according to the exercise score of the current exercise process, and perform exercise reward exchange and / or exercise ranking based on the exercise effect evaluation value.

[0067] Among them, the exercise effect evaluation value is used to evaluate the exercise effect of the current exercise process in the entire exercise process, and can reflect the exercise progress level of the exercise monitoring object.

[0068] Specifically, if the current exercise process is the first time that the subject is monitored for exercise using a smart wearable device, the exercise score can be directly used as the exercise effect evaluation value. Alternatively, a correspondence between different exercise score intervals and exercise effect evaluation values ​​can be pre-set, and the exercise effect evaluation value can be determined based on the exercise score. Alternatively, a basic evaluation value can be set and used as the exercise effect evaluation value.

[0069] When a non-exercise monitoring subject is subjected to exercise monitoring for the first time through a smart wearable device during the current exercise process, the exercise score of the current exercise process and the exercise score of at least one historical exercise process can be combined to determine the exercise effect evaluation value. For example, the difference between the exercise score of the current exercise process and the average of the exercise scores of the current exercise process and the historical exercise process can be calculated, and the exercise effect evaluation value can be calculated based on the difference. The larger the difference, the higher the level of exercise progress, and the greater the exercise effect evaluation value.

[0070] Sports reward redemption can be to redeem sports effect evaluation values ​​for virtual goods or physical goods. Sports ranking refers to using sports scores or sports effect evaluation values ​​as indicators to determine the sports scores or sports effect evaluation values ​​of other smart wearable devices that are connected to communicate with the smart wearable device, sort them and generate a ranking table.

[0071] In this embodiment, the exercise effect evaluation value can be used to accurately judge the exercise progress level of the exercise monitoring subject, motivate the exercise monitoring subject, and improve the exercise enthusiasm of the exercise monitoring subject.

[0072] The technical solution of the embodiment of the present invention continuously monitors the parameters of the current exercise process and monitors security events based on the various monitoring parameters. After the current exercise process ends, the exercise score of the current exercise process is determined, and the exercise effect evaluation value is determined based on the exercise score. Subsequently, exercise reward redemption and / or exercise ranking are performed based on the exercise effect evaluation value. This solves the problem of the lack of security protection mechanisms and post-exercise evaluation mechanisms in smart wearable devices in the prior art. Through multi-dimensional detection, the accuracy of exercise process monitoring is improved, the safety of the exercise process is improved, and accurate evaluation of the exercise process is achieved.

[0073] Example 2

[0074] Figure 2 This is a flowchart of a motion monitoring method provided in the second embodiment of the present invention. Based on the above embodiments, this embodiment of the present invention further specifies the determination of the motion effect evaluation value and adds a verification process to the motion reward exchange and / or motion ranking.

[0075] like Figure 2 As shown, the method includes:

[0076] S210: Determine at least two monitoring parameters during the current exercise process, and perform safety event monitoring based on the monitoring parameters.

[0077] S220: If it is determined that the current exercise process is finished, determine the exercise score of the current exercise process.

[0078] S230: Determine an exercise effect evaluation value according to the exercise score of the current exercise process.

[0079] This embodiment provides a specific implementation method for determining an exercise effect evaluation value based on an exercise score.

[0080] Furthermore, S230 may include:

[0081] S231. Determine the exercise effect evaluation value according to the following formula: Among them, V represents the exercise effect evaluation value, S represents the exercise score of the current exercise process, and S Z represents the standard movement score, V B represents the basic evaluation value, represents the average value of the historical movement score during the historical movement process, and λ represents the progress coefficient;

[0082] S232, wherein the progress coefficient can be expressed by the following formula: in, The variance of the historical movement score representing the historical movement process.

[0083] The standard exercise score may refer to a full score or a passing score, and the progress coefficient is used to indicate the degree of exercise progress of the current exercise process compared to the historical exercise process.

[0084] In this embodiment, the above-mentioned dynamic progress coefficient algorithm based on historical exercise score variance and the exercise effect evaluation value algorithm based on the progress coefficient make the calculation of the exercise effect evaluation value more scientific, accurate and reasonable, and can better reflect the actual level of exercise progress.

[0085] S240. If it is determined that the interruption rate of each monitoring parameter during the exercise process is less than or equal to the preset interruption rate threshold, and the matching degree between each monitoring parameter and the exercise pattern is greater than or equal to the preset matching degree threshold, then exercise reward redemption and / or exercise ranking are performed based on the exercise effect evaluation value.

[0086] Before performing exercise reward redemption and / or exercise ranking based on the exercise effect evaluation value, this embodiment also provides a verification method.

[0087] Specifically, the interruption rate of each monitoring parameter during exercise can be calculated based on the ratio of the monitoring parameter pause monitoring time to the total exercise time of the current exercise process. The interruption rate can be calculated for each monitoring parameter separately, and then the interruption rate is weighted and summed according to the weight of each monitoring parameter. If the interruption rate of each monitoring parameter during exercise is less than or equal to the preset interruption rate threshold, it means that the monitoring data during exercise is relatively continuous. For example, the interruption rate threshold can be set to 5%.

[0088] The degree of matching between the monitoring parameters and the motion mode can be calculated based on the standard monitoring parameter intervals corresponding to the monitoring parameters and the motion mode. For example, when the motion mode is running, the acceleration, speed, heart rate and other monitoring parameters are set to corresponding standard intervals, and the actual monitoring parameters are compared with the standard intervals to determine the matching degree. Similarly, the matching degree can be calculated for each monitoring parameter separately, and then the matching degree is weighted and summed according to the weight of each monitoring parameter. For example, the matching degree threshold can be set to 90%.

[0089] In this embodiment, by verifying the interruption rate of the monitoring parameters and the matching degree with the exercise pattern, the authenticity and validity of the exercise score and the exercise effect evaluation value can be further guaranteed, and cheating behavior can be effectively blocked.

[0090] Furthermore, this embodiment provides a specific implementation for ranking exercise based on exercise scores. Specifically, the ranking weight can be calculated using the following formula: S × 70% + λ × 30%. The ranking weights of the exercise scores of other smart wearable devices that have established communication connections with the current smart wearable device are then sorted from largest to smallest to obtain the exercise ranking.

[0091] Furthermore, the motion monitoring algorithm in this embodiment is deployed locally on the smart wearable device. This ensures minimal delay in responding to early warning alerts after security event detection, improving safety. Furthermore, the motion monitoring algorithm in this embodiment supports remote updates from the server, allowing it to adapt to dynamic changes in the motion monitored object without requiring hardware replacement.

[0092] The technical solution of the embodiment of the present invention improves the safety of the exercise process by continuously monitoring the monitoring parameters of the current exercise process, and monitoring safety events such as falls, excessive exercise, and emergency events based on various monitoring parameters. After the current exercise process ends, the exercise score of the current exercise process is determined, the dynamic progress coefficient is calculated based on the variance of the historical exercise scores, and the exercise effect evaluation value is calculated based on the progress coefficient, which improves the scientificity, accuracy and rationality of the exercise effect evaluation value and better reflects the real level of exercise progress. Subsequently, the continuity and matching degree of the monitoring parameters are verified. After the verification is passed, the exercise reward exchange and / or exercise ranking are carried out according to the exercise effect evaluation value, which can effectively block cheating behavior and improve the exercise enthusiasm of the exercise monitoring object.

[0093] Example 3

[0094] Figure 3 This is a schematic diagram of the structure of a motion monitoring device provided by the third embodiment of the present invention. Figure 3 As shown, the device includes:

[0095] The safety event monitoring module 310 is used to determine at least two monitoring parameters during the current exercise process and perform safety event monitoring based on the monitoring parameters;

[0096] Among them, safety events include at least one of fall monitoring, excessive exercise monitoring, and emergency event monitoring;

[0097] The exercise score determination module 320 is configured to determine an exercise score for the current exercise process if it is determined that the current exercise process has ended.

[0098] The exercise effect evaluation value determination module 330 is used to determine the exercise effect evaluation value according to the exercise score of the current exercise process, so as to perform exercise reward exchange and / or exercise ranking based on the exercise effect evaluation value.

[0099] The technical solution of the embodiment of the present invention continuously monitors the parameters of the current exercise process and monitors security events based on the various monitoring parameters. After the current exercise process ends, the exercise score of the current exercise process is determined, and the exercise effect evaluation value is determined based on the exercise score. Subsequently, exercise reward redemption and / or exercise ranking are performed based on the exercise effect evaluation value. This solves the problem of the lack of security protection mechanisms and post-exercise evaluation mechanisms in smart wearable devices in the prior art. Through multi-dimensional detection, the accuracy of exercise process monitoring is improved, the safety of the exercise process is improved, and accurate evaluation of the exercise process is achieved.

[0100] Based on the above embodiment, optionally, the security event monitoring module 310 includes:

[0101] A first monitoring parameter determination unit is used to determine the three-axis acceleration, angular velocity and heart rate during the current exercise process;

[0102] The fall monitoring unit is used to determine that the current state is a fall if at least one of the following is met: the three-axis acceleration change rate is greater than or equal to a preset acceleration change rate threshold, the angular velocity change rate is greater than or equal to a preset angular velocity change rate threshold, and the difference in heart rate within a preset time period is greater than or equal to a preset difference threshold.

[0103] Based on the above embodiment, optionally, the security event monitoring module 310 includes:

[0104] A second monitoring parameter determination unit is used to determine the amount of exercise, safety threshold and heart rate during the current exercise process;

[0105] The excessive exercise monitoring unit is used to determine that the current state is excessive exercise if it is determined that the amount of exercise is greater than or equal to the safety threshold, and / or the duration of the heart rate is greater than or equal to the preset heart rate threshold, and is greater than or equal to the preset time threshold.

[0106] Based on the above embodiment, optionally, the second monitoring parameter determination unit is specifically configured to:

[0107] Determine the safety threshold during the current motion process according to the following formula: Wherein, T represents the safety threshold, BMR represents the basal metabolic rate of the exercise detection subject, HRV represents the heart rate variability, age represents the age of the exercise detection subject, and R represents the heart rate of the exercise detection subject.

[0108] Based on the above embodiment, optionally, the security event monitoring module 310 includes:

[0109] a third monitoring parameter determination unit, configured to determine acceleration, position, heart rate, and ambient light intensity during the current exercise process;

[0110] An emergency event monitoring unit is used to determine that the current state is an emergency if it is determined that the acceleration variance within a preset time period is less than or equal to a preset variance threshold, the displacement between positions within a preset time period is less than or equal to a preset displacement threshold, the heart rate fluctuation within a preset time period is less than or equal to a preset fluctuation threshold, and the ambient light intensity difference within the preset time period is greater than or equal to a preset light intensity difference threshold.

[0111] Based on the above embodiment, optionally, the exercise effect evaluation value determination module 330 includes:

[0112] The exercise effect evaluation value determination unit is used to determine the exercise effect evaluation value according to the following formula: Among them, V represents the exercise effect evaluation value, S represents the exercise score of the current exercise process, and S Z represents the standard movement score, V B represents the basic evaluation value, represents the average value of the historical movement score during the historical movement process, and λ represents the progress coefficient;

[0113] Among them, the progress coefficient can be expressed by the following formula: in, The variance of the historical movement score representing the historical movement process.

[0114] Based on the above embodiment, optionally, the exercise effect evaluation value determination module 330 includes:

[0115] The sports reward redemption unit is used to redeem sports rewards based on the sports effect evaluation value if it is determined that the interruption rate of each monitoring parameter during the exercise process is less than or equal to the preset interruption rate threshold, and the matching degree between each monitoring parameter and the exercise mode is greater than or equal to the preset matching degree threshold.

[0116] The motion monitoring device provided in the embodiment of the present invention can execute the motion monitoring method provided in any embodiment of the present invention, and has the corresponding functional modules and beneficial effects of the execution method.

[0117] Example 4

[0118] Figure 4 A schematic diagram of the structure of an electronic device 10 that can be used to implement an embodiment of the present invention is shown. The electronic device is intended to represent various forms of digital computers, such as laptop computers, desktop computers, workstations, personal digital assistants, servers, blade servers, mainframe computers, and other suitable computers. The electronic device can also represent various forms of mobile devices, such as personal digital processing, cellular phones, smart phones, wearable devices (such as helmets, glasses, watches, etc.) and other similar computing devices. The components shown herein, their connections and relationships, and their functions are merely examples and are not intended to limit the implementation of the present invention described and / or claimed herein.

[0119] like Figure 4As shown, the electronic device 10 includes at least one processor 11 and a memory, such as a read-only memory (ROM) 12, a random access memory (RAM) 13, etc., which is communicatively connected to the at least one processor 11. The memory stores a computer program that can be executed by the at least one processor. The processor 11 can perform various appropriate actions and processes according to the computer program stored in the read-only memory (ROM) 12 or the computer program loaded from the storage unit 18 into the random access memory (RAM) 13. Various programs and data required for the operation of the electronic device 10 can also be stored in the RAM 13. The processor 11, ROM 12, and RAM 13 are connected to each other via a bus 14. An input / output (I / O) interface 15 is also connected to the bus 14.

[0120] Multiple components in the electronic device 10 are connected to the I / O interface 15, including an input unit 16, such as a keyboard, a mouse, etc.; an output unit 17, such as various types of displays, speakers, etc.; a storage unit 18, such as a magnetic disk, an optical disk, etc.; and a communication unit 19, such as a network card, a modem, a wireless communication transceiver, etc. The communication unit 19 allows the electronic device 10 to exchange information / data with other devices via a computer network such as the Internet and / or various telecommunication networks.

[0121] The processor 11 may be any general-purpose and / or specialized processing component with processing and computing capabilities. Some examples of the processor 11 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various specialized artificial intelligence (AI) computing chips, various processors running machine learning model algorithms, a digital signal processor (DSP), and any appropriate processor, controller, microcontroller, etc. The processor 11 executes the various methods and processes described above, such as the motion monitoring method.

[0122] In some embodiments, the motion monitoring method can be implemented as a computer program that is tangibly contained in a computer-readable storage medium, such as storage unit 18. In some embodiments, part or all of the computer program can be loaded and / or installed on electronic device 10 via ROM 12 and / or communication unit 19. When the computer program is loaded into RAM 13 and executed by processor 11, one or more steps of the motion monitoring method described above can be performed. Alternatively, in other embodiments, processor 11 can be configured to perform the motion monitoring method in any other suitable manner (e.g., by means of firmware).

[0123] Various embodiments of the systems and techniques described herein can be implemented in digital electronic circuit systems, integrated circuit systems, field programmable gate arrays (FPGAs), application specific integrated circuits (ASICs), application specific standard products (ASSPs), system-on-chip systems (SOCs), programmable logic devices (CPLDs), computer hardware, firmware, software, and / or combinations thereof. These various embodiments can include being implemented in one or more computer programs that are executable and / or interpreted on a programmable system that includes at least one programmable processor, which can be a special purpose or general purpose programmable processor that can receive data and instructions from a storage system, at least one input device, and at least one output device, and transmit data and instructions to the storage system, the at least one input device, and the at least one output device.

[0124] Computer programs for implementing the methods of the present invention can be written in any combination of one or more programming languages. These computer programs can be provided to a processor of a general-purpose computer, a special-purpose computer, or other programmable motion monitoring device, so that when the computer program is executed by the processor, the functions / operations specified in the flowcharts and / or block diagrams are implemented. The computer program can be executed entirely on the machine, partially on the machine, as a stand-alone software package, partially on the machine and partially on a remote machine, or entirely on a remote machine or server.

[0125] In the context of the present invention, computer-readable storage media can be tangible media that can contain or store a computer program for use with an instruction execution system, device or equipment or used in combination with an instruction execution system, device or equipment. Computer-readable storage media can include but are not limited to electronic, magnetic, optical, electromagnetic, infrared or semiconductor systems, devices or equipment, or any suitable combination of the foregoing. Alternatively, computer-readable storage media can be machine-readable signal media. More specific examples of machine-readable storage media can include electrical connections based on one or more lines, portable computer disks, hard disks, random access memories (RAM), read-only memories (ROM), erasable programmable read-only memories (EPROM or flash memory), optical fibers, portable compact disk read-only memories (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination of the foregoing.

[0126] To provide interaction with a user, the systems and techniques described herein can be implemented on an electronic device having: a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to the user; and a keyboard and pointing device (e.g., a mouse or trackball) through which the user can provide input to the electronic device. Other types of devices can also be used to provide interaction with the user; for example, the feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user can be received in any form (including acoustic input, voice input, or tactile input).

[0127] The systems and techniques described herein can be implemented in a computing system that includes back-end components (e.g., as a data server), or a computing system that includes middleware components (e.g., an application server), or a computing system that includes front-end components (e.g., a user computer with a graphical user interface or web browser through which a user can interact with implementations of the systems and techniques described herein), or a computing system that includes any combination of such back-end components, middleware components, or front-end components. The components of the system can be interconnected by any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include: a local area network (LAN), a wide area network (WAN), a blockchain network, and the Internet.

[0128] A computing system may include clients and servers. The clients and servers are typically remote from each other and typically interact via a communication network. This client-server relationship arises through computer programs running on the respective computers, creating a client-server relationship. The server may be a cloud server, also known as a cloud computing server or cloud host. This server is a hosting product within the cloud computing service ecosystem that addresses the management difficulties and limited scalability of traditional physical hosting and VPS services.

[0129] It should be understood that the various forms of the processes shown above can be used to reorder, add, or delete steps. For example, the steps described in the present invention can be performed in parallel, sequentially, or in a different order, as long as the desired results of the technical solution of the present invention can be achieved. This is not limited herein.

[0130] The above specific embodiments do not limit the scope of protection of the present invention. Those skilled in the art will appreciate that various modifications, combinations, sub-combinations, and substitutions may be made based on design requirements and other factors. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of the present invention are intended to be included within the scope of protection of the present invention.

Claims

1. A motion monitoring method, characterized in that: include: Determine at least two monitoring parameters during the current exercise process, and perform safety event monitoring based on each monitoring parameter; Among them, safety events include at least one of fall monitoring, excessive exercise monitoring, and emergency event monitoring; If it is determined that the current exercise process is finished, then the exercise score of the current exercise process is determined; According to the exercise score of the current exercise process, an exercise effect evaluation value is determined, so as to perform exercise reward redemption and / or exercise ranking based on the exercise effect evaluation value.

2. The method according to claim 1, characterized in that Determine at least two monitoring parameters during the current exercise process, and perform fall detection based on each monitoring parameter, including: Determine the three-axis acceleration, angular velocity, and heart rate during the current exercise; If it is determined that at least one of the following is met: the three-axis acceleration change rate is greater than or equal to the preset acceleration change rate threshold, the angular velocity change rate is greater than or equal to the preset angular velocity change rate threshold, and the difference in heart rate within the preset time period is greater than or equal to the preset difference threshold, then it is determined that the current state is a fall.

3. The method according to claim 1, characterized in that Determine at least two monitoring parameters during the current exercise process, and perform exercise overload monitoring based on each monitoring parameter, including: Determine the amount of exercise, safety threshold, and heart rate during the current exercise process; If it is determined that the amount of exercise is greater than or equal to the safety threshold, and / or the duration of the heart rate being greater than or equal to the preset heart rate threshold is greater than or equal to the preset time threshold, it is determined that the current state is excessive exercise.

4. The method according to claim 3, characterized in that Determine the safety threshold during the current exercise, including: Determine the safety threshold during the current motion process according to the following formula: Wherein, T represents the safety threshold, BMR represents the basal metabolic rate of the exercise detection subject, HRV represents the heart rate variability, age represents the age of the exercise detection subject, and R represents the heart rate of the exercise detection subject.

5. The method according to claim 1, wherein Determine at least two monitoring parameters during the current movement process, and perform emergency event monitoring based on each monitoring parameter, including: Determine acceleration, position, heart rate, and ambient light intensity during the current movement; If it is determined that the acceleration variance within the preset time period is less than or equal to the preset variance threshold, the displacement between positions within the preset time period is less than or equal to the preset displacement threshold, the heart rate fluctuation within the preset time period is less than or equal to the preset fluctuation threshold, and the ambient light intensity difference within the preset time period is greater than or equal to the preset light intensity difference threshold, then it is determined that the current state is an emergency.

6. The method according to claim 1, characterized in that Determine the exercise effect evaluation value based on the exercise score of the current exercise process, including: The exercise effect evaluation value is determined according to the following formula: Among them, V represents the exercise effect evaluation value, S represents the exercise score of the current exercise process, and S Z represents the standard movement score, V B represents the basic evaluation value, represents the average value of the historical movement score during the historical movement process, and λ represents the progress coefficient; Among them, the progress coefficient can be expressed by the following formula: in, The variance of the historical movement score representing the historical movement process.

7. The method according to claim 1, characterized in that Performing exercise reward redemption and / or exercise ranking based on the exercise effect evaluation value includes: If it is determined that the interruption rate of each monitoring parameter during exercise is less than or equal to the preset interruption rate threshold, and the matching degree of each monitoring parameter with the exercise mode is greater than or equal to the preset matching degree threshold, exercise reward redemption and / or exercise ranking will be performed based on the exercise effect evaluation value.

8. A motion monitoring device, characterized in that: include: A safety event monitoring module is used to determine at least two monitoring parameters during the current exercise process and perform safety event monitoring based on the monitoring parameters; Among them, safety events include at least one of fall monitoring, excessive exercise monitoring, and emergency event monitoring; an exercise score determination module, configured to determine an exercise score for the current exercise process if it is determined that the current exercise process is finished; The exercise effect evaluation value determination module is used to determine the exercise effect evaluation value according to the exercise score of the current exercise process, so as to perform exercise reward exchange and / or exercise ranking based on the exercise effect evaluation value.

9. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein: When the processor executes the program, the motion monitoring method according to any one of claims 1 to 7 is implemented.

10. A storage medium storing computer executable instructions, characterized in that: When the computer executable instructions are executed by a computer processor, they are used to perform the motion monitoring method according to any one of claims 1 to 7.

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