Muscle fatigue early warning method and device, storage medium and electronic equipment

Abstract

The invention relates to a muscle fatigue early warning method and device, a storage medium and electronic equipment, and relates to the technical field of muscle fatigue monitoring, and the method comprises the steps: obtaining the fitness plan information of a target user at this time; determining at least one muscle part to be monitored from the muscle parts of the target user according to the planned fitness actions and the corresponding planned times; actual electromyographic signals of all the to-be-monitored muscle parts are obtained, if the actual electromyographic signals are abnormal, the corresponding to-be-monitored muscle parts are determined as abnormal muscle parts, and according to actual fitness actions currently completed by the target user and the corresponding actual times, the abnormal muscle parts are determined to be abnormal muscle parts; determining whether the abnormal muscle part has a muscle fatigue risk or not; if it is determined that the abnormal muscle part has the muscle fatigue risk, a muscle fatigue early warning is given out for the abnormal muscle part. The method has the effect of improving the accuracy of muscle fatigue early warning.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of muscle fatigue monitoring, and in particular to a muscle fatigue early warning method and device, a storage medium and an electronic device. BACKGROUND

[0002] Muscle fatigue refers to the phenomenon that muscle cannot maintain normal contraction strength or speed after continuous contraction or repeated movement, resulting in decreased motor ability. It is a state of temporary decline in muscle function, usually related to factors such as energy metabolism, neural control and muscle fiber damage. Muscle fatigue early warning refers to giving a prompt through physical signals, physiological indicators or technical means before the muscle enters a state of fatigue, reminding timely adjustment of exercise intensity, rest or taking intervention measures to avoid excessive fatigue and injury. It is an important strategy to prevent sports injuries and optimize training results. Muscle fatigue early warning is also widely used in the field of fitness.

[0003] Currently, the way commonly used for muscle fatigue early warning of fitness personnel is to collect the electromyographic signals of the fitness personnel, analyze the signal characteristics of the electromyographic signals, and determine whether there is a risk of muscle fatigue through a pre-set fixed threshold. However, the electromyographic signals are prone to deviation due to poor electrode contact and other factors during collection, and the determination accuracy of muscle fatigue risk is disturbed by the fixed threshold determination method, resulting in poor accuracy of muscle fatigue early warning. SUMMARY

[0004] In order to improve the accuracy of muscle fatigue early warning, the present application provides a muscle fatigue early warning method, device, storage medium and electronic device.

[0005] In a first aspect of the present application, a muscle fatigue early warning method is provided, which specifically comprises: obtaining the fitness plan information of the target user this time, the fitness plan information including at least one planned fitness action and the corresponding planned number of times; determining at least one muscle part to be monitored from each muscle part of the target user according to each planned fitness action and the corresponding planned number of times; obtaining the actual electromyographic signals of each muscle part to be monitored, and if the actual electromyographic signals are abnormal, determining the corresponding muscle part to be monitored as an abnormal muscle part, and determining whether the abnormal muscle part has a risk of muscle fatigue according to the actual fitness action completed by the target user currently and the corresponding actual number of times; if it is determined that the abnormal muscle part has a risk of muscle fatigue, issuing a muscle fatigue early warning for the abnormal muscle part.

[0006] By adopting the technical scheme, after the planned exercise action and the corresponding planned number of times of the target user for this time of exercise are acquired, the possible occurrence of muscle fatigue of each muscle part is analyzed based on the planned exercise action and the corresponding planned number of times, and then the muscle part to be monitored is determined, so that the targeted detection of muscle fatigue of the target user is realized based on the exercise plan information. Further, if the actual electromyographic signal is abnormal, it indicates that the abnormal muscle part may have a muscle fatigue risk, and the existence of the muscle fatigue risk needs to be further verified. Then, according to the actual exercise action and the corresponding actual number of times completed by the target user, the possibility of muscle fatigue of the abnormal muscle part under the premise of the completed exercise content is analyzed, and then it is determined whether the abnormal muscle part has a muscle fatigue risk. If the muscle fatigue risk exists, in order to intervene in muscle fatigue in advance, a muscle fatigue warning is issued for the abnormal muscle part, so as to improve the accuracy of the muscle fatigue warning.

[0007] In an embodiment, the at least one muscle part to be monitored is determined from each muscle part of the target user according to each planned exercise action and the corresponding planned number of times, specifically comprising: According to a plurality of historical muscle parts that have muscle fatigue under a single exercise action, at least one target muscle part is determined, the target muscle part being a historical muscle part prone to inducing muscle fatigue; According to a number of times range of the number of times of completion of the single exercise action when a historical user has muscle fatigue in a single target muscle part, at least one corresponding target number of times range is determined, the target number of times range being a number of times range prone to inducing muscle fatigue, the historical user being consistent with the target user in exercise action and user portrait; A first weight value of each target muscle part is determined, and a second weight value of the corresponding target number of times range of each target muscle part is determined, the first weight value representing the possibility of muscle fatigue of the target muscle part, and the second weight value representing the possibility of muscle fatigue when the number of times of completion of the single exercise action is in the target number of times range; The at least one muscle part to be monitored is determined from each muscle part of the target user according to the first weight value and the second weight value corresponding to the single health action, each planned exercise action and the corresponding planned number of times.

[0008] In an embodiment, the at least one muscle part to be monitored is determined from each muscle part of the target user according to the first weight value and the second weight value corresponding to the single health action, each planned exercise action and the corresponding planned number of times, specifically comprising: For a single planned exercise action, if there is a corresponding planned number of times in the target number of times range corresponding to the target muscle part, the corresponding target muscle part is determined as a key muscle part, and the corresponding target number of times range is determined as a key number of times range; A first product of a first weight value of each of the key muscle parts and a second weight value of the corresponding target number of times range is calculated, and a first summation result corresponding to the first product of the same key muscle part is obtained by summing the first product of each of the planned exercise actions; The first summation result is compared with a preset first threshold value, and if the first summation result exceeds the first threshold value, the corresponding key muscle part is determined as a muscle part to be monitored.

[0009] In an embodiment, the method further comprises: For a single actual exercise action completed by the target user, if there is a corresponding actual number of times in the target number of times range corresponding to the target muscle part, the corresponding target muscle part is determined as a reference muscle part, and the corresponding target number of times range is determined as a reference number of times range; A second product of a first weight value of each of the reference muscle parts and a second weight value of the corresponding reference number of times range is calculated, and a second summation result is obtained by summing the second product of all actual exercise actions; If the second summation result is greater than a preset second threshold value, a third summation result corresponding to the second product of the same reference muscle part of all actual exercise actions is obtained by summing the second product of the same reference muscle part of all actual exercise actions; If the third summation result exceeds the preset first threshold value, the corresponding reference muscle part is determined as a risk muscle part, and it is determined that the abnormal muscle part has a muscle fatigue risk when the abnormal muscle part is the risk muscle part; It is determined that the abnormal muscle part does not have a muscle fatigue risk when the abnormal muscle part is not the risk muscle part.

[0010] In an embodiment, the method further comprises: If the abnormal muscle part is the reference muscle part when the abnormal muscle part does not have a muscle fatigue risk, a fourth summation result corresponding to the second product of the same abnormal muscle part of all actual exercise actions is obtained by summing the second product of the same abnormal muscle part of all actual exercise actions; A difference value of the first threshold value minus the fourth summation result is calculated, and if the difference value does not exceed a preset difference value threshold value, a planned exercise action that has not started is determined as a remaining action; if the abnormal muscle part exists in each target muscle part corresponding to the residual action, determining the corresponding residual action as an action to be adjusted, and calculating a third product of a first weight of the abnormal muscle part and a second weight of each target frequency range corresponding to the single action to be adjusted; selecting a minimum third product from each third product, summing the fourth sum result and the minimum third product corresponding to each action to be adjusted to obtain a final sum result; if the final sum result does not exceed the first threshold value, determining a suitable frequency of the corresponding action to be adjusted based on the target frequency range corresponding to the minimum third product, and sending each suitable frequency to the terminal of the target user.

[0011] In an embodiment, the method further comprises: if it is determined that the abnormal muscle part does not have a muscle fatigue risk, determining at least one part to be concerned according to a muscle part with poor electrode contact that has occurred to a historical user during fitness, the part to be concerned being a muscle part prone to poor electrode contact during monitoring of electromyographic signals; determining at least one action to be concerned according to a historical fitness action that causes poor electrode contact at the single part to be concerned, the action to be concerned being a historical fitness action prone to causing poor electrode contact; determining a first weight of each part to be concerned, and determining a second weight of the action to be concerned corresponding to each part to be concerned; verifying that the abnormal muscle part does not have a muscle fatigue risk according to the first weight, the second weight, and each actual fitness action.

[0012] In an embodiment, the verification that the abnormal muscle part does not have a muscle fatigue risk according to the first weight, the second weight, and each actual fitness action specifically comprises: if at least one actual fitness action exists in each action to be concerned corresponding to the part to be concerned, determining the corresponding part to be concerned as a part to be focused on, and calculating a fourth product of the first weight of the abnormal muscle part and the second weight of each actual fitness action when the abnormal muscle part is the part to be focused on; summing each fourth product to obtain a fifth sum result corresponding to the abnormal muscle part; comparing the fifth sum result with a preset third threshold value, and if the fifth sum result exceeds the third threshold value, determining that the verification that the abnormal muscle part does not have a muscle fatigue risk is passed.

[0013] A muscle fatigue warning device is provided in a second aspect of the present application, and specifically comprises: an information obtaining module, configured to obtain fitness plan information of a target user, the fitness plan information comprising at least one planned fitness action and a corresponding planned number of times; a part determining module, configured to determine at least one muscle part to be monitored from each muscle part of the target user according to each planned fitness action and the corresponding planned number of times; a risk determining module, configured to obtain an actual electromyography signal of each muscle part to be monitored, and if the actual electromyography signal is abnormal, determine the corresponding muscle part to be monitored as an abnormal muscle part, and determine whether the abnormal muscle part has a muscle fatigue risk according to an actual fitness action completed by the target user currently and a corresponding actual number of times; a fatigue warning module, configured to issue a muscle fatigue warning for the abnormal muscle part if it is determined that the abnormal muscle part has a muscle fatigue risk.

[0014] By using the above technical solution, the information obtaining module obtains the fitness plan information of the target user, then the part determining module determines at least one muscle part to be monitored according to the planned fitness action and the corresponding planned number of times, then the risk determining module determines whether the abnormal muscle part has a muscle fatigue risk according to the actual fitness action completed by the target user currently and the corresponding actual number of times, and finally, the fatigue warning module issues a muscle fatigue warning for the abnormal muscle part if it is determined that the abnormal muscle part has a muscle fatigue risk.

[0015] In a third aspect of the present application, a computer readable storage medium is provided, and the computer readable storage medium stores a computer program. When the computer program is loaded and executed by a processor, the method steps of any one of the first aspect are executed.

[0016] In a fourth aspect of the present application, an electronic device is provided, and specifically comprises: a processor, a memory, and a computer program stored in the memory and capable of running on the processor, the processor being configured to load and execute the computer program stored in the memory, so that the electronic device executes the method of any one of the first aspect.

[0017] In summary, the present application comprises at least one of the following beneficial technical effects: after obtaining the planned exercise actions and corresponding planned times of the target user for this time, the possible occurrence of muscle fatigue of each muscle part is analyzed based on the planned exercise actions and corresponding planned times, and then the muscle part to be monitored is determined, so as to realize the targeted detection of muscle fatigue of the target user based on the exercise plan information. Further, if the actual electromyographic signal is abnormal, it indicates that the abnormal muscle part may have a muscle fatigue risk, and the existence of the muscle fatigue risk needs to be further verified. Then, according to the actual exercise actions and corresponding actual times completed by the target user, the possibility of muscle fatigue of the abnormal muscle part under the premise of the completed exercise content is analyzed, and then it is determined whether the abnormal muscle part has a muscle fatigue risk. If there is a muscle fatigue risk, in order to intervene in muscle fatigue in advance, a muscle fatigue warning is issued for the abnormal muscle part, thereby improving the accuracy of the muscle fatigue warning. BRIEF DESCRIPTION OF DRAWINGS

[0018] Figure 1 is a flow diagram of a muscle fatigue warning method provided by an embodiment of the present application; Figure 2 is a structural diagram of a muscle fatigue warning device provided by an embodiment of the present application; Figure 3 is a structural diagram of another muscle fatigue warning device provided by an embodiment of the present application.

[0019] Legend: 11, information acquisition module; 12, part determination module; 13, risk determination module; 14, fatigue warning module; 15, exercise reminding module; 16, risk verification module. DETAILED DESCRIPTION

[0020] In order for those skilled in the art to better understand the technical solutions in the present specification, the technical solutions in the present specification will be described clearly and completely in conjunction with the drawings in the embodiments of the present specification. Obviously, the described embodiments are only some of the embodiments of the present application, not all the embodiments.

[0021] In the description of the embodiments of the present application, the words "exemplarily", "for example", or "for instance" are used to mean as an example, illustration or description. Any embodiment or design scheme described as "exemplarily", "for example", or "for instance" in the embodiments of the present application should not be interpreted as more preferred or more advantageous than other embodiments or design schemes. Rather, the words "exemplarily", "for example", or "for instance" are intended to present the relevant concept in a specific manner.

[0022] In the description of the embodiments of the present application, the term "and / or", is only to describe the association relationship of the associated objects, which means that there can be three relationships, for example, A and / or B, which can represent three cases of A alone, B alone, and A and B together. In addition, unless otherwise specified, the term "multiple" means two or more. For example, multiple systems refer to two or more systems, and multiple screen terminals refer to two or more screen terminals. In addition, the terms "first", "second" are only for descriptive purposes, and cannot be understood as indicating or implying relative importance or implicitly indicating the indicated technical features. Therefore, the features defined with "first", "second" can explicitly or implicitly include one or more features. The terms "include", "contain", "have" and their variants mean "include but not limited to", unless otherwise specifically emphasized.

[0023] Referring to Figure 1 The embodiments of the present application disclose a flowchart of a muscle fatigue warning method, which can be realized by relying on a computer program and can also run on a muscle fatigue warning device based on the von Neumann system. The computer program can be integrated in an application or run as an independent tool application. Specifically, the method comprises the following steps: S101: Obtain the fitness plan information of the target user this time, and the fitness plan information comprises at least one planned fitness action and a corresponding planned number.

[0024] Specifically, in the embodiments of the present application, the target user is a user who performs muscle fatigue monitoring during this time fitness. The fitness plan information is the training plan information of the target user this time fitness. The fitness plan information comprises at least one planned fitness action and a corresponding planned number, wherein the planned fitness action can be understood as a training action or project that the target user plans to complete in this time fitness. The planned number corresponding to the planned fitness action can be understood as the number of times that the target user plans to complete the corresponding planned fitness action. For example, the planned fitness action is deep squat, and the corresponding planned number is 40 times; the planned fitness action is pull-up, and the corresponding planned number is 20 times.

[0025] Further, the muscle fatigue early warning method disclosed in the embodiments of the present application is executed by a server, the server is wirelessly connected with a terminal, the terminal is a smart phone or a personal computer of a target user, the terminal is installed with a client related to muscle fatigue early warning, the server is a background server of the client, and specifically can be an independent physical server or a cluster composed of multiple physical servers. The server is also wirelessly connected with a wearable electromyography detection device worn by the target user. The wearable electromyography detection device can monitor the electromyography signal of the target user's body through electrodes. The wearable electromyography detection device can be an arm ring / leg ring or smart fitness clothes. The target user wears at least one wearable electromyography detection device during this time of fitness. An implementation scenario is that when the target user starts fitness according to fitness plan information, the terminal sends an opening instruction to the server through the client, the server opens the instruction, obtains the electromyography signal of the target user's body during fitness through the wearable electromyography detection device, and performs muscle fatigue early warning based on the electromyography signal. In addition, a feasible way to obtain fitness plan information is that the target user sends the fitness plan information of this time of fitness to the server through the terminal, and the server finally obtains the fitness plan information.

[0026] S102: Determine at least one muscle part to be monitored from each muscle part of the target user according to each planned fitness action and the corresponding planned number of times.

[0027] Specifically, after each planned fitness action and the corresponding planned number of times are determined, at least one muscle part to be monitored is determined from each muscle part of the target user's body according to the planned fitness action and the corresponding planned number of times, so as to realize targeted muscle fatigue early warning. One implementable implementation is that based on the first historical record of muscle fatigue early warning, a plurality of historical muscle parts that appear muscle fatigue when a past fitness user performs a single fitness action are obtained, the number of occurrences of a single historical muscle part in all historical muscle parts is counted, and if the number of occurrences exceeds a corresponding number threshold, the corresponding historical muscle part is determined as a target muscle part, that is, a historical muscle part prone to fatigue caused by a single fitness action. The first historical record includes but is not limited to historical muscle parts that appear muscle fatigue under a single fitness action.

[0028] Further, based on the second historical record of muscle fatigue warning, a range of the number of times of completing the single fitness action when the historical user is experiencing muscle fatigue at the single target muscle part is obtained, the frequency of occurrence of each range of the number of times in all ranges of the number of times is counted, and if the frequency of occurrence exceeds a corresponding frequency threshold, the corresponding range of the number of times is determined as the target range of the number of times corresponding to the target muscle part, that is, the range of the number of times that is prone to induce muscle fatigue of the target muscle part. Wherein the historical user is consistent with the target user in the fitness action and the user portrait. That is, all the fitness actions completed by the historical user are the same as all the planned fitness actions of the target user. In addition, the user portrait is a virtual user model abstracted based on the basic information of the user. The basic information includes but is not limited to the age, gender and other information of the user. The second historical record includes but is not limited to the range of the number of times of completing each fitness action when the historical user experiences muscle fatigue.

[0029] The first weight value of each target muscle part is determined, and the second weight value of the target range of the number of times corresponding to each target muscle part is determined, to obtain the first weight value and the second weight value corresponding to the single fitness action. Wherein the first weight value is the ratio of the number of occurrences of each target muscle part to the sum of the number of occurrences of all target muscle parts. The second weight value is the ratio of the frequency of occurrence of the single target range of the number of times corresponding to the target muscle part to the sum of the frequency of occurrence of all target ranges of the number of times. Finally, according to the first weight value, the second weight value corresponding to the single fitness action, each planned fitness action and the corresponding planned number of times, the muscle part to be monitored is determined. In the embodiments of the present application, a feasible determination method is: For a single planned exercise action, if the target number range corresponding to the target muscle part of the planned exercise action exists in the planned number range of the planned exercise action, the corresponding target muscle part is determined as a key muscle part, and the corresponding target number range is determined as a key number range. The first product of the first weight value of each key muscle part and the second weight value of the corresponding target number range is calculated, and at least one first product corresponding to the single planned exercise action is obtained. The greater the first product, the greater the possibility of causing muscle fatigue of the key muscle part when the number of the planned exercise action in the fitness reaches the corresponding planned number. Then, the first products corresponding to the same key muscle part in the first products corresponding to all planned exercise actions are summed to obtain a first summation result corresponding to the key muscle part. The greater the first summation result, the greater the overall possibility of muscle fatigue of the corresponding key muscle part when the target user exercises according to the fitness plan information in this fitness. Further, the first summation result is compared with a preset first threshold value. If the first summation result exceeds the first threshold value, it indicates that the overall possibility of muscle fatigue of the corresponding key muscle part is greater when the target user exercises according to the fitness plan information in this fitness, and the corresponding key muscle part needs to be monitored specifically. Then, the corresponding key muscle part is determined as a muscle part to be monitored.

[0030] S103: Obtain the actual electromyographic signal of each muscle part to be monitored. If the actual electromyographic signal is abnormal, the corresponding muscle part to be monitored is determined as an abnormal muscle part, and whether the abnormal muscle part has a muscle fatigue risk is determined according to the actual exercise action and the corresponding actual number of the target user currently completed.

[0031] Specifically, after each muscle part to be monitored is determined, the current actual electromyographic signal of the muscle part to be monitored is collected through the electrode of the wearable electromyographic detection device on the muscle part to be monitored. Then, it is judged whether the actual electromyographic signal is abnormal. A feasible judgment method is that the actual electromyographic signal is preprocessed, and the preprocessing includes filtering processing (removing high-frequency noise), amplification processing (enhancing signal strength) and rectification processing. Then, the characteristic parameter is calculated based on the result after preprocessing. If the characteristic parameter is not in the corresponding threshold range, it is determined that the actual electromyographic signal is abnormal, and the corresponding muscle part to be monitored may have a muscle fatigue risk, which needs to be further verified for the existence of the muscle fatigue risk. Then, the corresponding muscle part to be monitored is determined as an abnormal muscle part. The characteristic parameter can be a median frequency (MF) or a root mean square (RMS). Both of the two characteristic parameters are used to evaluate the activity state and fatigue degree of the muscle. This is prior art, and will not be described here.

[0032] Further, according to the actual fitness actions completed by the target user currently and the corresponding actual times, it is determined whether the abnormal muscle part has a muscle fatigue risk. An implementable embodiment is as follows: for a single actual fitness action, if there is a corresponding actual time in the target time range corresponding to the target muscle part of the target user, the corresponding target muscle part is determined as a reference muscle part, and the corresponding target time range is determined as a reference time range. Then, a second product of a first weight value of each reference muscle part and a second weight value of the corresponding reference time range is calculated, and the second products corresponding to all actual fitness actions are summed to obtain a second summation result. The greater the second summation result is, the greater the overall possibility of muscle fatigue of the target user at the current time of the current fitness is. Then, the second summation result is compared with a preset second threshold value. If the second summation result is greater than the second threshold value, it indicates that the overall possibility of muscle fatigue of the target user currently is greater. On this basis, the second products corresponding to the same reference muscle part in the second products corresponding to all actual fitness actions are summed to obtain a third summation result of the corresponding reference muscle part. Finally, if the third summation result exceeds a first threshold value, it indicates that the possibility of muscle fatigue of the corresponding reference muscle part at the current time of the current fitness is greater, and the corresponding reference muscle part is determined as a risk muscle part. If the abnormal muscle part is the risk muscle part, it is determined that the abnormal muscle part indeed has a muscle fatigue risk; otherwise, it is determined that the abnormal muscle part does not have a muscle fatigue risk. It should be noted that the second threshold value is greater than the first threshold value.

[0033] In an embodiment, when the abnormal muscle part is not at risk of muscle fatigue, if the abnormal muscle part is the reference muscle part, the second products of the same abnormal muscle part corresponding to all actual fitness actions are summed to obtain a corresponding fourth summation result, and the greater the fourth summation result, the greater the possibility of muscle fatigue of the abnormal muscle part of the target user. The difference between the first threshold value and the fourth summation result is calculated, and if the difference does not exceed the preset difference threshold value, it indicates that the fourth summation result is smaller than the first threshold value, but the gap is small, and the abnormal muscle part is still prone to muscle fatigue when the target user performs the subsequent fitness action. Therefore, the planned fitness action that has not yet started to be performed is determined as a remaining action. Further, if there is an abnormal muscle part in each target muscle part corresponding to the remaining action, the corresponding remaining action is determined as an adjusted action. For a single adjusted action, the third product of the first weight value of the abnormal muscle part and the second weight value of the corresponding target number range is calculated, and the greater the third product, the more likely the abnormal muscle part is to appear muscle fatigue when the number of times of completing the adjusted action is in the corresponding target number range. The minimum third product is selected from each third product, and the fourth summation result and the minimum third product corresponding to each adjusted action are summed to obtain a final summation result, and the greater the final summation result, the greater the possibility of muscle fatigue of the abnormal muscle part when the remaining action in this fitness is completed. If the final summation result does not exceed the first threshold value, it indicates that the possibility of muscle fatigue of the abnormal muscle part is small when the corresponding remaining action is completed according to the target number range corresponding to the minimum third product. In order to avoid muscle fatigue of the abnormal muscle part in the subsequent fitness of the target user, the appropriate number of times of the corresponding adjusted action is determined based on the target number range corresponding to the single minimum third product, which can specifically determine the maximum value in the target number range as the appropriate number of times, and finally the appropriate number of times of each adjusted action is sent to the terminal of the target user, so that the target user can change the number of times of completing each adjusted action in time in the next fitness.

[0034] In other embodiments, the target user's current target fitness action is obtained, the first weight value of each target muscle part and the second weight value of the corresponding respective target number range are calculated for the target fitness action, the respective weight products are summed to obtain a summation result corresponding to the target fitness action, if the summation result is greater than a preset threshold, it indicates that the overall possibility of muscle fatigue is greater when performing the target fitness action, and special attention is needed for the problem of posture standard, then the actual posture of the target user performing the target fitness action is obtained, and the similarity between the actual posture and the standard posture of the target fitness action is calculated, if the similarity is not greater than a preset similarity threshold, it indicates that the posture of the target user performing the target fitness action is not standard, which is easy to accelerate the occurrence of muscle fatigue, then the terminal of the target user is sent a reminder information of non-standard posture. Wherein, the similarity threshold is determined from the preset threshold matching table according to the summation result, the greater the summation result, the greater the similarity threshold, and the higher the requirement for the standard of the target fitness action. The threshold matching table includes different summation result ranges and corresponding similarity thresholds, which are all set based on human experience, for example, the threshold matching table includes a summation result range of 0.6-1, and the corresponding similarity threshold is 0.8; the summation result range is 1-1.4, and the corresponding similarity threshold is 0.9, if the summation result is in the range of 0.6-1, then the similarity threshold is 0.8. It should be noted that the actual posture of performing the target fitness action is obtained in real time by the preset infrared sensor. In addition, a feasible way to calculate the similarity is to map the actual posture and the standard posture to a high-dimensional vector space to obtain the corresponding vectors, and then calculate the cosine similarity between the two vectors.

[0035] S104: If it is determined that the abnormal muscle part has a muscle fatigue risk, a muscle fatigue warning is sent for the abnormal muscle part.

[0036] Specifically, if it is determined that the abnormal muscle part has a muscle fatigue risk, it indicates that the abnormal muscle part has a greater possibility of muscle fatigue, and a muscle fatigue warning is sent to the terminal of the target user for the abnormal muscle part, so as to remind the target user to intervene in time to avoid muscle fatigue or even muscle damage.

[0037] In other embodiments, if it is determined that the abnormal muscle part does not have a muscle fatigue risk, based on the historical record of electrode contact failure, the muscle parts where the electrode contact failure occurred during the historical user's workouts are obtained, the first frequency of repeated occurrence of a single muscle part among all muscle parts is counted, and if the first frequency exceeds the corresponding frequency threshold, the corresponding muscle part is determined as a part to be concerned, i.e., the muscle part where the electrode is prone to contact failure during the monitoring of the electromyographic signal. Then, based on the historical record, the historical workouts that cause the electrode contact failure at the single part to be concerned are obtained, the second frequency of repeated occurrence of a single historical workout among all historical workouts is counted, and if the second frequency exceeds the corresponding frequency threshold, the corresponding historical workout is determined as the workout to be concerned corresponding to the part to be concerned, i.e., the historical workout that is prone to cause the electrode contact failure. The historical record includes but is not limited to the muscle parts where the electrode contact failure occurred and the corresponding workouts, etc.

[0038] The first weight of each part to be concerned is determined, and the second weight of the workout to be concerned corresponding to each part to be concerned is determined. The first weight is the ratio of the first frequency of each part to be concerned to the sum of the first frequencies of all parts to be concerned. The second weight is the ratio of the second frequency of a single workout to be concerned corresponding to the part to be concerned to the sum of the second frequencies of all workouts to be concerned corresponding to the part to be concerned. Finally, according to the first weight, the second weight, and the actual workout, the muscle fatigue risk of the abnormal muscle part is verified. One implementable embodiment is as follows: If there is at least one actual workout in the workouts to be concerned corresponding to the part to be concerned, the corresponding part to be concerned is determined as the part to be focused on. When the abnormal muscle part is the part to be focused on, the fourth product of the first weight of the abnormal muscle part and the second weight of the actual workout is calculated. The larger the fourth product is, the more likely the actual workout causes the electrode contact failure of the abnormal muscle part. The fourth products are summed to obtain a fifth sum result. The larger the fifth sum result is, the more likely the electrode contact failure of the abnormal muscle part of the current target user is. Finally, if the fifth sum result is greater than a preset third threshold, it indicates that the electrode contact failure of the abnormal muscle part of the current target user is more likely, and the corresponding actual electromyographic signal is more likely to have an error, thereby indicating that the actual electromyographic signal of the abnormal muscle part does not truly exist an abnormality, and it is deduced that the abnormal muscle part does not have a muscle fatigue risk. Therefore, the verification of the muscle fatigue risk of the abnormal muscle part is passed, so that the accuracy of the muscle fatigue warning is higher.

[0039] The implementation principle of the muscle fatigue early warning method in the embodiment of the present application is as follows: after the planned exercise action and the corresponding planned number of times of the target user in this exercise are acquired, the possible occurrence of muscle fatigue of each muscle part is analyzed based on the planned exercise action and the corresponding planned number of times, and then the muscle part to be monitored is determined, so that the targeted detection of muscle fatigue of the target user is realized based on the exercise plan information. Further, if the actual electromyographic signal is abnormal, it indicates that the abnormal muscle part may have a muscle fatigue risk, and the existence of the muscle fatigue risk needs to be further verified. Then, according to the actual exercise action and the corresponding actual number of times completed by the target user, the possibility of muscle fatigue of the abnormal muscle part under the premise of the completed exercise content is analyzed, and then it is determined whether the abnormal muscle part has a muscle fatigue risk. If the muscle fatigue risk exists, in order to intervene in muscle fatigue in advance, a muscle fatigue early warning is issued for the abnormal muscle part, so as to improve the accuracy of the muscle fatigue early warning.

[0040] The following is an apparatus embodiment of the present application, which can be used to execute the method embodiments of the present application. For details not disclosed in the apparatus embodiments of the present application, refer to the method embodiments of the present application.

[0041] Please refer to Figure 2 The structure schematic diagram of the muscle fatigue early warning device provided in the embodiment of the present application. The muscle fatigue early warning device can be realized by software, hardware or a combination of both to become all or part of the device. The device includes an information acquisition module 11, a part determination module 12, a risk determination module 13 and a fatigue early warning module 14.

[0042] The information acquisition module 11 is configured to acquire the exercise plan information of the target user in this exercise, and the exercise plan information includes at least one planned exercise action and the corresponding planned number of times. The part determination module 12 is configured to determine at least one muscle part to be monitored from each muscle part of the target user according to each planned exercise action and the corresponding planned number of times. The risk determination module 13 is configured to acquire the actual electromyographic signal of each muscle part to be monitored. If the actual electromyographic signal is abnormal, the corresponding muscle part to be monitored is determined as an abnormal muscle part, and whether the abnormal muscle part has a muscle fatigue risk is determined according to the actual exercise action and the corresponding actual number of times completed by the target user. The fatigue early warning module 14 is configured to issue a muscle fatigue early warning for the abnormal muscle part if it is determined that the abnormal muscle part has a muscle fatigue risk.

[0043] Optionally, the part determination module 12 is specifically configured to: determine at least one target muscle part according to multiple historical muscle parts that have muscle fatigue under a single fitness action, the target muscle part being a historical muscle part that is prone to induce muscle fatigue; determine at least one target frequency range corresponding to the single fitness action according to a frequency range in which the historical user has muscle fatigue at the single target muscle part, the target frequency range being a frequency range that is prone to induce muscle fatigue, the historical user being consistent with the target user in the fitness action and the user portrait; determine a first weight value of each target muscle part and a second weight value of the target frequency range corresponding to each target muscle part, the first weight value representing a possibility of muscle fatigue of the target muscle part, and the second weight value representing a possibility of muscle fatigue when the single fitness action is completed in the target frequency range; determine at least one muscle part to be monitored from the muscle parts of the target user according to the first weight value, the second weight value, each planned fitness action and the corresponding planned frequency.

[0044] Optionally, the part determination module 12 is specifically configured to: for a single planned fitness action, if there is a corresponding planned frequency in the target frequency range corresponding to the target muscle part, the corresponding target muscle part is determined as a key muscle part, and the corresponding target frequency range is determined as a key frequency range; calculate a first product of the first weight value of each key muscle part and the second weight value of the target frequency range corresponding to each key muscle part, and sum the first products corresponding to the same key muscle part based on the first products corresponding to each planned fitness action to obtain a corresponding first summation result; compare the first summation result with a preset first threshold value, and if the first summation result exceeds the first threshold value, the corresponding key muscle part is determined as the muscle part to be monitored.

[0045] Optionally, the risk determination module 13 is specifically configured to: for a single actual fitness action that has been completed by the target user, if there is a corresponding actual frequency in the target frequency range corresponding to the target muscle part, the corresponding target muscle part is determined as a reference muscle part, and the corresponding target frequency range is determined as a reference frequency range; calculate a second product of the first weight value of each reference muscle part and the second weight value of the reference frequency range corresponding to each reference muscle part, and sum the second products corresponding to all actual fitness actions to obtain a second summation result; if the second summation result is greater than a preset second threshold value, sum the second products of the same reference muscle part in the second products corresponding to all actual fitness actions to obtain a corresponding third summation result; If the third summation result exceeds the preset first threshold value, the corresponding reference muscle part is determined as a risk muscle part, and when the abnormal muscle part is the risk muscle part, it is determined that the abnormal muscle part has a muscle fatigue risk; When the abnormal muscle part is not the risk muscle part, it is determined that the abnormal muscle part does not have a muscle fatigue risk.

[0046] Optionally, as shown in Figure 3 The device further includes a fitness reminding module 15, which is specifically used for: When the abnormal muscle part does not have a muscle fatigue risk, if the abnormal muscle part is a reference muscle part, the second products of the same abnormal muscle part corresponding to all actual fitness actions are summed to obtain a corresponding fourth summation result; A difference value between the first threshold value and the fourth summation result is calculated, and if the difference value does not exceed a preset difference threshold value, the planned fitness action that has not started is determined as a remaining action; If there is an abnormal muscle part in each target muscle part corresponding to the remaining action, the corresponding remaining action is determined as an adjusted action, and for a single adjusted action, a third product of a first weight value of the abnormal muscle part and a second weight value of each target number range corresponding to the abnormal muscle part is calculated; The minimum third product is selected from the third products, the fourth summation result and the minimum third product corresponding to each adjusted action are summed to obtain a final summation result; If the final summation result does not exceed the first threshold value, the appropriate number of the corresponding adjusted action is determined based on the target number range corresponding to the single minimum third product, and each appropriate number is sent to the terminal of the target user.

[0047] Optionally, the device further includes a risk checking module 16, which is specifically used for: If it is determined that the abnormal muscle part does not have a muscle fatigue risk, at least one part to be concerned is determined according to the muscle parts with poor electrode contact of the historical user during fitness, and the part to be concerned is a muscle part in which the electrode is prone to poor contact during monitoring of the electromyographic signal; At least one action to be concerned is determined according to the historical fitness action that causes the electrode to have poor contact at the single part to be concerned, and the action to be concerned is a historical fitness action that is prone to cause the electrode to have poor contact; A first weight of each part to be concerned is determined, and a second weight of the action to be concerned corresponding to each part to be concerned is determined; The first weight, the second weight and each actual fitness action are used to check whether the abnormal muscle part does not have a muscle fatigue risk.

[0048] Optionally, the risk checking module 16 is specifically used for: If there is at least one actual fitness action in each to-be-observed action corresponding to the to-be-observed part, the corresponding to-be-observed part is determined as a key to-be-observed part, and when the abnormal muscle part is the key to-be-observed part, a fourth product of the first weight of the abnormal muscle part and the second weight of each actual fitness action corresponding to the abnormal muscle part is calculated; The fourth products are summed to obtain a fifth summation result corresponding to the abnormal muscle part; The fifth summation result is compared with a third threshold value, and if the fifth summation result exceeds the third threshold value, it is determined that the muscle fatigue risk check on the abnormal muscle part fails.

[0049] It should be noted that the muscle fatigue early warning device provided in the above embodiment is used to execute the muscle fatigue early warning method, and only the division of the above functional modules is used as an example for illustration. In actual application, the above functions can be distributed to different functional modules according to needs, that is, the internal structure of the device is divided into different functional modules to complete all or part of the functions described above. In addition, the muscle fatigue early warning device and the muscle fatigue early warning method provided in the above embodiment belong to the same concept, and the implementation process is detailed in the method embodiment, which will not be described here.

[0050] The embodiment of the present application also discloses a computer readable storage medium, and the computer readable storage medium stores a computer program, wherein the computer program is executed by a processor to realize the muscle fatigue early warning method of the above embodiment.

[0051] The computer program can be stored in the computer readable medium, and the computer program includes computer program code, which can be in the form of source code, object code, executable file or some middleware form, etc. The computer readable medium includes any entity or device, recording medium, U disk, mobile hard disk, magnetic disk, optical disk, computer memory, read-only memory (ROM), random access memory (RAM), electric carrier signal, telecommunication signal and software distribution medium, etc. that can carry computer program code. It should be noted that the computer readable medium includes but is not limited to the above components.

[0052] The computer readable storage medium stores the muscle fatigue early warning method of the above embodiment in the computer readable storage medium, and is loaded and executed on the processor to facilitate the storage and application of the method.

[0053] The embodiment of the present application also discloses an electronic device, and the computer readable storage medium stores a computer program, which is loaded and executed by the processor to realize the muscle fatigue early warning method.

[0054] The electronic device can be a desktop computer, a notebook computer, or a cloud server, and the electronic device includes a processor and a memory, but is not limited thereto.

[0055] The processor can be a central processing unit (CPU), and can also be a general-purpose processor, a digital signal processor (DSP), an application-specific integrated circuit (ASIC), a field programmable gate array (FPGA), or other programmable logic device, discrete gate or transistor logic, discrete hardware components, or the like. The general-purpose processor can be a microprocessor or any conventional processor, and the present application is not limited thereto.

[0056] The memory can be an internal storage unit of the electronic device, such as a hard disk or a memory, or an external storage device of the electronic device, such as a plug-in hard disk, a smart media card (SMC), a secure digital card (SD), or a flash card (FC), or a combination thereof. The memory is used to store computer programs and other programs and data required by the electronic device, and can also be used to temporarily store data that has been output or will be output, and the present application is not limited thereto.

[0057] The muscle fatigue warning method of the above embodiments is stored in the memory of the electronic device, and is loaded and executed on the processor of the electronic device, which is convenient for use.

[0058] The above description is only exemplary embodiments of the present disclosure, and cannot limit the scope of the present disclosure. Any equivalent changes and modifications made in accordance with the teachings of the present disclosure are still within the scope of the present disclosure. The present application is intended to cover any variations, uses, or adaptive changes of the present disclosure that follow the general principles of the present disclosure and include common knowledge or conventional technical means in the technical field not described in the present disclosure. The scope and spirit of the present disclosure are defined by the claims.

Claims

1. A method for early warning of muscle fatigue, characterized in that, The method includes: Obtain the target user's current fitness plan information, which includes at least one planned fitness exercise and the corresponding number of repetitions. Based on each of the planned fitness movements and the corresponding number of repetitions, at least one muscle group to be monitored is determined from each muscle group of the target user; The actual electromyographic signals of each of the muscle sites to be monitored are obtained. If the actual electromyographic signals are abnormal, the corresponding muscle site to be monitored is identified as an abnormal muscle site. Based on the actual fitness movements and corresponding number of repetitions completed by the target user, it is determined whether the abnormal muscle site is at risk of muscle fatigue. If it is determined that the abnormal muscle area is at risk of muscle fatigue, a muscle fatigue warning is issued for the abnormal muscle area.

2. The muscle fatigue early warning method according to claim 1, characterized in that, The step of determining at least one muscle group to be monitored from various muscle groups of the target user based on each of the planned fitness movements and the corresponding planned repetitions specifically includes: Based on multiple historical muscle sites that have experienced muscle fatigue during a single fitness exercise, at least one target muscle site is identified, wherein the target muscle site is a historical muscle site that is prone to inducing muscle fatigue. Based on the range of number of times a single fitness exercise was completed when a historical user experienced muscle fatigue in a single target muscle area, at least one target number range is determined. The target number range is the range of number of times that easily induces muscle fatigue. The historical user and the target user are consistent in terms of fitness exercise and user profile. A first weight is determined for each target muscle group, and a second weight is determined for the target number range corresponding to each target muscle group. The first weight represents the probability of muscle fatigue occurring in the target muscle group, and the second weight represents the probability of muscle fatigue occurring when the number of times a single fitness movement is completed is within the target number range. Based on the first weight, second weight, planned fitness movements, and corresponding number of repetitions for each individual health movement, at least one muscle group to be monitored is determined from the muscle groups of the target user.

3. The muscle fatigue early warning method according to claim 2, characterized in that, The step of determining at least one muscle group to be monitored from each muscle group of the target user based on the first weight, second weight, each planned fitness movement, and the corresponding planned number of repetitions for a single health movement specifically includes: For a single planned fitness exercise, if there is a corresponding planned number of repetitions within the target repetition range corresponding to the target muscle group, then the corresponding target muscle group is identified as the key muscle group, and the corresponding target repetition range is identified as the key repetition range. Calculate the first product of the first weight of each key muscle group and the second weight of the corresponding target repetition range, and sum the first products corresponding to the same key muscle group based on the first products corresponding to each of the planned fitness movements to obtain the corresponding first summation result; The first summation result is compared with a preset first threshold. If the first summation result exceeds the first threshold, the corresponding key muscle area is identified as the muscle area to be monitored.

4. The muscle fatigue early warning method according to claim 2, characterized in that, The step of determining whether the abnormal muscle area is at risk of muscle fatigue based on the actual fitness movements and corresponding repetitions completed by the target user specifically includes: For a single actual fitness movement that the target user has completed, if there is a corresponding actual number of repetitions within the target number of repetitions for the target muscle part, then the corresponding target muscle part is determined as the reference muscle part, and the corresponding target number of repetitions is determined as the reference number of repetitions range. Calculate the second product of the first weight of each reference muscle part and the second weight of the corresponding reference number range, and sum the second products corresponding to all actual fitness movements to obtain the second summation result; If the second summation result is greater than the preset second threshold, then the second products of the same reference muscle part in the second products corresponding to all actual fitness movements are summed to obtain the corresponding third summation result; If the third summation result exceeds the preset first threshold, the corresponding reference muscle part is determined as a risk muscle part. When the abnormal muscle part is the risk muscle part, it is determined that the abnormal muscle part has a risk of muscle fatigue. When the abnormal muscle site is not a risky muscle site, it is determined that the abnormal muscle site does not pose a risk of muscle fatigue.

5. The muscle fatigue early warning method according to claim 4, characterized in that, The method further includes: When there is no risk of muscle fatigue at the abnormal muscle site, if the abnormal muscle site is the reference muscle site, then the second product of the same abnormal muscle site in all actual fitness movements is summed to obtain the corresponding fourth summation result. Calculate the difference between the first threshold and the fourth summation result. If the difference does not exceed the preset difference threshold, then the planned fitness movements that have not yet started are identified as remaining movements. If there is an abnormal muscle part among the target muscle parts corresponding to the remaining movements, the corresponding remaining movements are determined as movements to be adjusted, and for a single movement to be adjusted, the third product of the first weight of the abnormal muscle part and the second weight of the corresponding target number range is calculated. Select the smallest third product from each of the third products, and sum the fourth summation result with the smallest third product corresponding to each of the actions to be adjusted to obtain the final summation result; If the final summation result does not exceed the first threshold, then based on the target number range corresponding to the single minimum third product, the appropriate number of the corresponding adjustment action is determined, and each appropriate number is sent to the target user's terminal.

6. The muscle fatigue early warning method according to claim 1, characterized in that, The method further includes: If it is determined that there is no risk of muscle fatigue in the abnormal muscle area, then at least one area of ​​concern is identified based on the muscle areas where poor electrode contact has occurred in the past by users during exercise. The area of ​​concern is the muscle area where poor electrode contact is likely to occur when monitoring electromyographic signals. Based on the historical fitness movements that caused poor electrode contact at a single site of concern, at least one corresponding movement of concern is determined, wherein the movement of concern is a historical fitness movement that is likely to cause poor electrode contact. A first weight is determined for each of the parts to be concerned, and a second weight is determined for the action to be concerned corresponding to each part to be concerned; Based on the first weight, the second weight, and each of the actual fitness movements, it is verified that there is no risk of muscle fatigue in the abnormal muscle areas.

7. The muscle fatigue early warning method according to claim 6, characterized in that, The step of verifying whether the abnormal muscle area has a risk of muscle fatigue based on the first weight, the second weight, and each of the actual fitness movements specifically includes: If there is at least one actual fitness movement among the movements corresponding to the area to be focused on, then the corresponding area to be focused on is determined as the key area to be focused on. When the abnormal muscle area is the key area to be focused on, the fourth product of the first weight of the abnormal muscle area and the second weight of the corresponding actual fitness movement is calculated. Summing each of the fourth products yields the fifth summation result corresponding to the abnormal muscle region. The fifth summation result is compared with the preset third threshold. If the fifth summation result exceeds the third threshold, it is determined that the verification of no muscle fatigue risk for the abnormal muscle area has passed.

8. A muscle fatigue early warning device, characterized in that, include: The information acquisition module (11) is used to acquire the fitness plan information of the target user for this time. The fitness plan information includes at least one planned fitness movement and the corresponding number of planned movements. The part determination module (12) is used to determine at least one muscle part to be monitored from each muscle part of the target user according to each of the planned fitness movements and the corresponding planned number of times; The risk assessment module (13) is used to acquire the actual electromyographic signals of each of the muscle sites to be monitored. If the actual electromyographic signals are abnormal, the corresponding muscle site to be monitored is identified as an abnormal muscle site. Based on the actual fitness movements and the corresponding number of times that the target user has completed, the module determines whether the abnormal muscle site is at risk of muscle fatigue. The fatigue warning module (14) is used to issue a muscle fatigue warning for the abnormal muscle area if it is determined that there is a risk of muscle fatigue in the abnormal muscle area.

9. A computer-readable storage medium storing a computer program, characterized in that, When the computer program is loaded and executed by the processor, it implements the method of any one of claims 1-7.

10. An electronic device comprising a memory, a processor, and a computer program stored in the memory and capable of running on the processor, characterized in that, When the processor loads and executes the computer program, it implements the method of any one of claims 1-7.

Images