Exercise guidance method, equipment, system, storage medium and computer program product

Abstract

The invention discloses an exercise guidance method, device and system, a storage medium and a computer program product, and relates to the technical field of exercise guidance, the exercise guidance method comprises the steps that an electromyographic signal of a concerned muscle group is acquired, and the concerned muscle group is a muscle group involved in a target exercise item; according to the electromyographic signal, identifying activity state information of the concerned muscle group; and according to the activity state information, generating and outputting adjustment guidance information corresponding to the target exercise item. The problem that an existing exercise guidance method is low in refinement degree is solved.

Description

Technical Field

[0001] This application relates to the technical field of motion guidance, and particularly to a motion guidance method, device, system, storage medium, and computer program product. Background Art

[0002] With the pursuit of a healthy lifestyle by people, intelligent motion training systems are developing rapidly and becoming an important tool for improving exercise effects and health management.

[0003] Currently, although some wearable devices (such as smart patches, smart bracelets, smart watches, etc.) are used to collect users' motion information for motion guidance. However, such motion information can usually only simply identify the users' motion postures, so the refinement degree of the motion suggestions obtained by analyzing this motion information is relatively low.

[0004] The above content is only used to assist in understanding the technical solution of this application and does not represent an admission that the above content is prior art. Summary of the Invention

[0005] The main purpose of this application is to provide a motion guidance method, device, system, storage medium, and computer program product, aiming to solve the technical problem of the relatively low refinement degree of the existing motion guidance method.

[0006] To achieve the above purpose, this application proposes a motion guidance method, and the motion guidance method includes: Obtain the electromyogram signals of the concerned muscle groups, where the concerned muscle groups are the muscle groups involved in the target exercise item; According to the electromyogram signals, identify the activity state information of the concerned muscle groups; According to the activity state information, generate and output the adjustment guidance information corresponding to the target exercise item.

[0007] In one embodiment, the step of identifying the activity state information of the concerned muscle groups according to the electromyogram signals includes: According to the electromyogram signals, calculate the root mean square value and the signal attenuation slope of the concerned muscle groups; According to the root mean square value, generate the activity intensity information of the concerned muscle groups; According to the signal attenuation slope, generate the recovery speed information of the concerned muscle groups; Take the activity intensity information and the recovery speed information as the activity state information of the concerned muscle groups.

[0008] In one embodiment, the step of identifying the activity state information of the concerned muscle groups according to the electromyogram signals further includes: Perform wavelet transform on the myoelectric signal to obtain the high-frequency band energy of the myoelectric signal; After the high-frequency band energy is greater than a predetermined energy threshold, it is determined that the concerned muscle group is in a tense state as the activity state information of the concerned muscle group.

[0009] In one embodiment, the concerned muscle group includes a first limb muscle group and a second limb muscle group that cooperates with the first limb muscle group. The step of identifying the activity state information of the concerned muscle group according to the myoelectric signal further includes: Identify the first activation timing of the first limb muscle group and the second activation timing of the second limb muscle group according to the myoelectric signal; Generate the coordination information of the concerned muscle group as the activity state information of the concerned muscle group according to the activation timing difference between the first activation timing and the second activation timing.

[0010] In one embodiment, the step of generating and outputting the adjustment guidance information corresponding to the target sports event according to the activity state information includes: Obtain the target muscle group activity index of the target sports event; Compare the activity state information with the target muscle group activity index to obtain muscle group activity difference information; Generate and output corresponding adjustment guidance information according to the muscle group activity difference information.

[0011] In one embodiment, before the step of obtaining the myoelectric signal of the concerned muscle group, the sports guidance method further includes: After receiving the input target sports event, query the concerned muscle group corresponding to the target sports event; Display the position information of the concerned muscle group so that the user can paste the monitoring patch on the area where the concerned muscle group is located; Receive the myoelectric signal of the concerned muscle group fed back by the monitoring patch.

[0012] In addition, to achieve the above object, the present application also proposes a sports guidance device, which includes: a memory, a processor, and a computer program stored on the memory and executable on the processor. The computer program is configured to implement the steps of the sports guidance method as described above.

[0013] In addition, to achieve the above object, the present application also proposes a sports guidance system, which includes: A monitoring patch for collecting the myoelectric signal of the concerned muscle group and sending it to the sports guidance device; A sports guidance device communicatively connected to the monitoring patch for executing the steps of the sports guidance method as described above.

[0014] In addition, to achieve the above object, the present application further provides a storage medium, which is a computer-readable storage medium. A computer program is stored on the storage medium, and when the computer program is executed by a processor, the steps of the motion guidance method described above are implemented.

[0015] In addition, to achieve the above object, the present application further provides a computer program product, which includes a computer program. When the computer program is executed by a processor, the steps of the motion guidance method described above are implemented.

[0016] One or more technical solutions proposed by the present application have at least the following technical effects: The present application obtains the electromyographic signals of the muscles of interest, where the muscles of interest are the muscle groups involved in the target exercise item. Thus, the electromyographic signals of the muscle groups involved in the target exercise item that the user is about to perform can be obtained. Since the electromyographic signals can reflect the functional state of the muscle system, the activity state information of the muscles of interest can be identified according to the electromyographic signals. Thus, the present application can integrate the independent activity states of the individual muscle groups and the associated activity states between the muscle groups under the muscles of interest involved in the target exercise item according to the activity state information, generate the corresponding adjustment guidance information for the target exercise item and output it, so as to guide the user to adjust the activity state of the muscles of interest, and more precisely guide the user to perform exercise training, improving the refinement degree of motion guidance. Description of the Drawings

[0017] The drawings here are incorporated into the specification and form a part of the specification, showing the embodiments consistent with the present application, and are used together with the specification to explain the principles of the present application.

[0018] To more clearly illustrate the technical solutions in the embodiments of the present application or the prior art, the following will briefly introduce the drawings required for use in the description of the embodiments or the prior art. Obviously, for those of ordinary skill in the art, other drawings can be obtained according to these drawings without creative efforts.

[0019] Figure 1 It is a schematic flowchart provided for Embodiment 1 of the motion guidance method of the present application; Figure 2 It is a schematic flowchart provided for Embodiment 2 of the motion guidance method of the present application; Figure 3 It is a schematic flowchart provided for Embodiment 3 of the motion guidance method of the present application; Figure 4 It is a schematic structural diagram of the motion guidance device in the embodiment of the present application; Figure 5Schematic diagram of the system structure of the motion guidance system in the embodiments of the present application; Figure 6 Schematic diagram of the structure of the monitoring patch in the motion guidance system of the present application.

[0020] Explanation of the reference numerals in the drawings: 100, motion guidance device; 1001, processing device; 1002, read-only memory; 1003, storage device; 1004, random access memory; 1005, bus; 1006, I / O interface; 1007, input device; 1008, output device; 1009, communication device; 200, monitoring patch.

[0021] The realization of the purpose, functional features and advantages of the present application will be further described in conjunction with the embodiments with reference to the accompanying drawings. Specific embodiments

[0022] It should be understood that the specific embodiments described herein are only used to explain the technical solutions of the present application and are not used to limit the present application.

[0023] In order to better understand the technical solutions of the present application, the following will be described in detail in conjunction with the drawings of the specification and specific embodiments.

[0024] The main solution of the embodiments of the present application is: acquiring the electromyographic signals of the concerned muscle groups, where the concerned muscle groups are the muscle groups involved in the target sports event; identifying the activity state information of the concerned muscle groups according to the electromyographic signals; generating and outputting the adjustment guidance information corresponding to the target sports event according to the activity state information.

[0025] Although the prior art collects the motion information of users with the help of some wearable devices (such as smart patches, smart bracelets, smart watches, etc.) to provide motion guidance for users. However, such motion information can usually only simply identify the motion postures of users, so the fineness of the motion suggestions obtained by analyzing this motion information is relatively low.

[0026] This application provides a solution. By obtaining the electromyographic signals of the concerned muscle groups, the electromyographic signals of the muscle groups involved in the target exercise item that the user is about to perform are obtained. Since the electromyographic signals can reflect the functional state of the muscle system, the activity state information of the concerned muscle groups can be identified according to the electromyographic signals. Thus, this application can integrate the independent activity states of each muscle group under the concerned muscle groups involved in the target exercise item and the associated activity states between the muscle groups according to the activity state information, generate the corresponding adjustment guidance information for the target exercise item and output it, so as to guide the user to adjust the activity state of the concerned muscle groups, more precisely guide the user to perform exercise training, and improve the precision of exercise guidance.

[0027] Based on this, an embodiment of this application provides an exercise guidance method. Refer to Figure 1 , Figure 1 which is a schematic flowchart of the first embodiment of the exercise guidance method of this application.

[0028] In this embodiment, the exercise guidance method includes steps S10 to S40: Step S10, obtain the electromyographic signals of the concerned muscle groups, where the concerned muscle groups are the muscle groups involved in the target exercise item; It should be noted that the concerned muscle groups are the muscle groups involved in the target exercise item, and the target exercise item is the exercise item for which the user expects exercise guidance, such as yoga, push-ups, rehabilitation training, etc.

[0029] In this embodiment, communication can be carried out with a wearable device (such as a smart patch) worn or pasted on the area where the concerned muscle groups are located to receive the electromyographic signals of the concerned muscle groups collected by the wearable device.

[0030] Step S20, identify the activity state information of the concerned muscle groups according to the electromyographic signals; It should be noted that the activity state information includes real-time indicators for describing the activity state of the concerned muscle groups, such as activity intensity, recovery speed, activity frequency, coordination, etc.

[0031] Exemplarily, in this embodiment, the root mean square value of the muscle group of interest can be calculated based on the myoelectric signal, and the root mean square value is the root mean square value of the intensity of the myoelectric signal. Since when the muscle contracts with a greater intensity (i.e., the activity intensity increases), the generated electrical activity also increases, resulting in an increase in the root mean square value. Therefore, the root mean square value can be used to characterize the activity intensity of the muscle group of interest, and further, the signal root mean square value and / or its derivative value can be used as the activity intensity information. The derivative value is a real-time index for characterizing the activity intensity derived from the root mean square value. For example, the derivative value can be to divide corresponding intensity levels according to the range where the root mean square value is located; or to count the number of times the root mean square value is greater than a predetermined intensity threshold within a predetermined first time period to obtain real-time indexes such as the number of times the intensity meets the standard.

[0032] Exemplarily, in this embodiment, the signal attenuation slope of the muscle group of interest can also be calculated based on the myoelectric signal, and the signal attenuation slope is the rate at which the intensity of the myoelectric signal weakens over time. The signal attenuation slope reflects the speed at which the muscle returns to the resting state after activity. A faster signal attenuation slope may indicate that the muscle recovers faster, while a slower signal attenuation slope may indicate that the muscle takes longer to recover. Therefore, the signal attenuation slope can be used to characterize the recovery speed of the muscle group of interest, and further, the signal attenuation slope and / or its derivative value can be used as the recovery speed information. The derivative value is a real-time index for characterizing the recovery speed derived from the signal attenuation slope. For example, the derivative value can be to divide corresponding recovery force levels according to the range where the signal attenuation slope is located; or to count the number of times the slope reduction of the signal attenuation slope is greater than a predetermined reduction threshold within a predetermined first time period to obtain real-time indexes such as the degree of fatigue.

[0033] Exemplarily, in this embodiment, the myoelectric signal can also be subjected to wavelet transform to obtain the high-frequency band energy of the myoelectric signal. The high-frequency band energy generally refers to the energy in the frequency band of 150 - 400 Hz. The high-frequency band energy is usually related to the rapid activation and deactivation of the muscle. Therefore, the high-frequency band energy obtained after wavelet transform can reflect the rapid changes in muscle activity, such as muscle tremors or subtle adjustment activities. However, there are usually certain limits to the subjective muscle adjustment activities of the user. Therefore, after the high-frequency band energy is greater than a predetermined energy threshold, this embodiment can determine that the muscle group of interest is in a tense state (such as muscle tension) as the activity state information of the muscle group of interest.

[0034] Exemplarily, the muscle groups of interest include the first limb muscle group and the second limb muscle group that cooperates with the first limb muscle group. In this embodiment, the first activation timing of the first limb muscle group and the second activation timing of the second limb muscle group can also be identified based on the myoelectric signals. Furthermore, in this embodiment, the time difference between the activations (i.e., muscle force exertion) of the first limb muscle group and the second limb muscle group can be determined according to the activation timing difference between the first activation timing and the second activation timing. Thus, the activation timing difference can be compared with a predetermined timing range to generate the coordination information of the muscle groups of interest as the activity state information of the muscle groups of interest.

[0035] Furthermore, in this embodiment, at least one of the above activity intensity information, recovery speed information, tension state, and coordination information can be used as the activity state information of the muscle groups of interest.

[0036] In a feasible implementation manner, step S20 may include steps S21 to S24: Step S21, calculate the root mean square value and the signal attenuation slope of the muscle groups of interest according to the myoelectric signals; Step S22, generate the activity intensity information of the muscle groups of interest according to the root mean square value; Step S23, generate the recovery speed information of the muscle groups of interest according to the signal attenuation slope; Step S24, use the activity intensity information and the recovery speed information as the activity state information of the muscle groups of interest.

[0037] It should be noted that the root mean square value is the root mean square value of the intensity of the myoelectric signals, and the signal attenuation slope is the rate at which the intensity of the myoelectric signals weakens over time.

[0038] In this embodiment, the root mean square value of the muscle group of interest can be calculated based on the myoelectric signal, and the root mean square value is the root mean square of the intensity of the myoelectric signal. Since when the muscle contracts with a greater intensity (i.e., the activity intensity increases), the generated electrical activity also increases, resulting in an increase in the root mean square value. Therefore, the root mean square value can be used to characterize the activity intensity of the muscle group of interest, and then the signal root mean square value and / or its derivative value can be used as the activity intensity information. The derivative value is a real-time index for characterizing the activity intensity derived from the root mean square value. For example, the derivative value can be to divide the corresponding intensity levels according to the range where the root mean square value is located; or to count the number of times the root mean square value is greater than a predetermined intensity threshold within a predetermined first time period to obtain real-time indexes such as the number of times of meeting the intensity standard. In addition, in this embodiment, the signal attenuation slope of the muscle group of interest can also be calculated based on the myoelectric signal, and the signal attenuation slope is the rate at which the intensity of the myoelectric signal weakens over time. The signal attenuation slope reflects the speed at which the muscle returns to the resting state after activity. A faster signal attenuation slope may indicate that the muscle recovers faster, while a slow signal attenuation slope may indicate that the muscle takes longer to recover. Therefore, the signal attenuation slope can be used to characterize the recovery speed of the muscle group of interest, and then the signal attenuation slope and / or its derivative value can be used as the recovery speed information. The derivative value is a real-time index for characterizing the recovery speed derived from the signal attenuation slope. For example, the derivative value can be to divide the corresponding recovery force levels according to the range where the signal attenuation slope is located; or to count the number of times the slope reduction of the signal attenuation slope is greater than a predetermined reduction threshold within a predetermined first time period to obtain real-time indexes such as the degree of fatigue.

[0039] In a feasible implementation manner, step S20 may further include steps S25 to S26: Step S25, perform wavelet transform on the myoelectric signal to obtain the high-frequency band energy of the myoelectric signal; Step S26, after the high-frequency band energy is greater than a predetermined energy threshold, it is determined that the muscle group of interest is in a tense state as the activity state information of the muscle group of interest.

[0040] It should be noted that wavelet transform is a time-frequency domain operation that performs scale and translation operations on a signal to obtain information about the signal in the time domain and frequency domain. The predetermined energy threshold is a threshold set in advance to characterize muscle tension.

[0041] In this embodiment, the electromyogram signal can also be subjected to wavelet transform to obtain the high-frequency band energy of the electromyogram signal. The high-frequency band energy generally refers to the energy in the frequency band of 150 - 400 Hz. The high-frequency band energy is usually related to the rapid activation and deactivation of muscles. Therefore, the high-frequency band energy obtained after wavelet transform can reflect the rapid changes in muscle activity, such as muscle tremors or subtle adjustment activities. However, there are usually certain limits to the subjective muscle adjustment activities of users. Therefore, after the high-frequency band energy is greater than a predetermined energy threshold, this embodiment can determine that the concerned muscle group is in a tense state (i.e., muscle tightness) as the activity state information of the concerned muscle group. Since different sports events have different requirements for muscle states, some muscle groups need to be relaxed.

[0042] Step S30, generate and output adjustment guidance information corresponding to the target sports event according to the activity state information.

[0043] It should be noted that the adjustment guidance information is to guide the training of the concerned muscle group to the expected activity state that the concerned muscle group is to reach.

[0044] This embodiment can compare the activity state information with the expected activity state that the target sports event requires the concerned muscle group to reach, to obtain muscle group activity difference information. Then, based on the muscle group activity difference information, generate corresponding adjustment guidance information, and output the adjustment guidance information in at least one form such as text, image, and voice. It can be understood that the expected exercise state can be the exercise state set by the user himself, or the target muscle group activity index of the target sports event. The target muscle group activity index is the activity state that the target sports event presets that the concerned muscle group needs to achieve.

[0045] In a feasible implementation manner, step S30 may further include steps S31 - S33: Step S31, obtain the target muscle group activity index of the target sports event; Step S32, compare the activity state information with the target muscle group activity index to obtain muscle group activity difference information; Step S33, generate and output corresponding adjustment guidance information according to the muscle group activity difference information.

[0046] It should be noted that the target muscle group activity index is the activity state that the target sports event presets that the concerned muscle group needs to achieve. For example, the activation time difference is less than a predetermined time difference value (such as 100 ms, 120 ms), the root mean square value of a certain concerned muscle group is greater than a predetermined root mean square value, the number of muscle tension times of a certain concerned muscle group is less than a predetermined number threshold, etc.

[0047] This embodiment can obtain the target muscle group activity index of the target sports item, and then compare the activity state information with the target muscle group activity index to obtain muscle group activity difference information, that is, the activity state information does not meet the description information of the target muscle group activity index. Then, the corresponding adjustment guidance information can be generated according to the muscle group activity difference information. Exemplarily, if the activation timing difference is not less than the predetermined timing difference, it means that the movement of the concerned muscle group is not coordinated. Then, the limb muscle group with delayed force can be determined according to the activation timing difference, and the corresponding adjustment guidance information can be generated, such as the prompt "the left leg force is delayed, adjust the center of gravity to the right heel". Or if the number of muscle tensions of a certain concerned muscle group is greater than the predetermined number threshold, it means that the muscles of this concerned muscle group are tight, then the action of relaxing this concerned muscle group can be used as adjustment guidance information. For example, if the shoulder muscles are in a state of muscle tension, the "cat-cow" action can be added as a compensatory training to relieve shoulder pressure. Or the number of times the slope of the signal attenuation slope decreases within a predetermined first time length (such as 20s, 30s) is greater than a predetermined decrease threshold, indicates that the muscle recovery speed is reduced and the concerned muscle group is relatively fatigued. In this case, adjustment methods such as actions that do not require the concerned muscle group to exert force, suggesting rest or massaging the concerned muscle group can be used as adjustment guidance information.

[0048] The first embodiment of the present application provides a method of sports guidance, by acquiring the electromyographic signal of a muscle group of interest, wherein the muscle group of interest is a muscle group involved in a target sports project, thereby obtaining the electromyographic signal of the muscle group involved in the target sports project that the user is about to perform. Since the electromyographic signal can reflect the functional state of the muscle system, the activity state information of the muscle group of interest can be identified based on the electromyographic signal. Therefore, this embodiment can integrate the independent activity states of each muscle group under the muscle group of interest involved in the target sports project, as well as the associated activity states between muscle groups, based on the activity state information, generate and output the adjustment guidance information corresponding to the target sports project, thereby guiding the user to adjust the activity state of the muscle group of interest, so as to be more refined to guide the user to perform sports training, and improve the refinement of sports guidance.

[0049] Based on the first embodiment of the present application, in the second embodiment of the present application, the same or similar contents as those in the above-mentioned embodiment 1 can be referred to the above introduction, and will not be repeated in the following. Figure 2 , the concerned muscle group includes a first limb muscle group and a second limb muscle group cooperating with the first limb muscle group, step S20 further includes steps A10 to A20: Step A10, identifying a first activation timing of the first limb muscle group and a second activation timing of the second limb muscle group according to the electromyographic signal; Step A20: Generate the coordination information of the target muscle groups as the activity status information of the target muscle groups according to the activation timing difference between the first activation timing and the second activation timing.

[0050] It should be noted that the target muscle groups include the first limb muscle groups and the second limb muscle groups that cooperate with the first limb muscle groups. The first limb muscle groups and the second limb muscle groups are respectively the muscle groups on the first limb and the second limb that need to move coordinately in the target sports event. For example, the muscle groups on the left leg and the right leg (such as the rectus femoris), the muscle groups on the left arm and the right arm (such as the biceps brachii), the muscle groups on the left arm and the right leg, the muscle groups on the left arm and the left leg, the muscle groups on the right arm and the right leg, etc. The first activation timing includes the moment when the first limb muscle groups are activated, and the second activation timing includes the moment when the second limb muscle groups are activated. The coordination information of the target muscle groups is the information describing the coordination between the first limb to which the first limb muscle groups belong and the second limb to which the second limb muscle groups belong, such as the lag of the first limb or the second limb, and the specific lag duration, etc.

[0051] Since the activation and deactivation of muscles (i.e., muscle contraction and relaxation) will cause changes in the electromyographic signals, in this embodiment, the first activation timing of the first limb muscle groups and the second activation timing of the second limb muscle groups can be identified according to the electromyographic signals. Furthermore, the coordination information of the target muscle groups can be generated as the activity status information of the target muscle groups according to the activation timing difference between the first activation timing and the second activation timing. Exemplarily, the activation timing difference is the difference between the first activation timing and the second activation timing, which characterizes the movement coordination between the first limb muscle groups and the second limb muscle groups. Taking the first limb muscle groups as the left leg and the second limb muscle groups as the right leg as an example, the activation timing difference can be directly used as the coordination information of the target muscle groups, or after the activation timing difference is greater than a predetermined timing threshold (i.e., the timing difference characterizing the incoordination of the first limb and the second limb), the fact that the left leg exerts force with a lag can be used as the coordination information of the target muscle groups.

[0052] In the second embodiment of the present application, the first activation timing of the first limb muscle groups and the second activation timing of the second limb muscle groups are identified according to the electromyographic signals; the coordination information of the target muscle groups is generated as the activity status information of the target muscle groups according to the activation timing difference between the first activation timing and the second activation timing. Thus, in this embodiment, the coordination ability of different limbs is identified through the activation timing difference between the limb muscle groups of different limbs, which is beneficial to giving more refined training guidance information.

[0053] Based on the first embodiment of the present application, in the third embodiment of the present application, the same or similar content as in the above-mentioned first embodiment can be referred to the above introduction and will not be repeated hereinafter. On this basis, please refer to Figure 3 , before step S10, the movement guidance method further includes steps S01 to S03: Step S01, after receiving the input target movement item, query the concerned muscle groups corresponding to the target movement item; Step S02, display the position information of the concerned muscle groups so that the user can paste the monitoring patch on the area where the concerned muscle groups are located; Step S03, receive the electromyographic signals of the concerned muscle groups fed back by the monitoring patch.

[0054] In this embodiment, a mapping relationship between the movement item and the concerned muscle groups can be constructed in advance. Then, after receiving the input target movement item, this embodiment queries the concerned muscle groups corresponding to the target movement item based on this mapping relationship. Exemplarily, the user selects the target movement item of "Yoga - Boat Pose Training", and then invokes the pre - stored movement - muscle group mapping relationship to query the concerned muscle groups corresponding to the target movement item of "Yoga - Boat Pose Training": rectus abdominis, rectus femoris of the left and right legs, and deltoid muscles. Then, the position information of the concerned muscle groups can be displayed. It can be understood that the display method of the position information can be at least one of image, text, voice, etc. Exemplarily, this embodiment can display a 3D human model, highlight the muscle areas of the concerned muscle groups (i.e., the abdomen corresponding to the rectus abdominis, the front side of the thigh corresponding to the rectus femoris, and the shoulder corresponding to the deltoid muscle), and prompt "Please paste the monitoring patch according to the highlighted area" so that the user can paste the monitoring patch on the area where the concerned muscle groups are located. It can be understood that different identifiers (such as colors, shapes, etc.) can be set for the monitoring patch in this embodiment. Then, when displaying the position information of the concerned muscle groups, the user can be guided to paste the monitoring patches with different identifiers on the areas where the concerned muscle groups are located, realizing the association between the electromyographic signals of different monitoring patches and different concerned muscle groups. This embodiment can also guide the user to paste the monitoring patches on the areas where the concerned muscle groups are located in sequence when displaying the position information of the concerned muscle groups, and realize the association between the electromyographic signals of different monitoring patches and different concerned muscle groups through the pasting order of multiple monitoring patches. Further, this embodiment can also detect the connection status between each monitoring patch, and output a prompt message after the connection status of the monitoring patch is disconnected to prompt the user. Thus, after the user pastes the monitoring patch on the area where the concerned muscle groups are located, this embodiment can receive the electromyographic signals of the concerned muscle groups fed back by the monitoring patch.

[0055] In the third embodiment of this application, after receiving the input target sports event, the attention muscle groups corresponding to the target sports event are queried, and the position information of the attention muscle groups is displayed, so that the user can paste the monitoring patch on the area where the attention muscle groups are located, and thus the electromyographic signals of the attention muscle groups fed back by the monitoring patch can be received. Therefore, this embodiment can guide the user to adaptively paste on the area where the attention muscle groups corresponding to the target sports event are located. Compared with the patch method at a fixed position, this embodiment effectively improves the applicable range of sports guidance.

[0056] It should be noted that the above examples are only for understanding this application and do not constitute a limitation on the sports guidance method of this application. Based on this technical concept, more forms of simple transformation are within the protection scope of this application.

[0057] This application provides a sports guidance device, which includes: at least one processor; and a memory communicatively connected to the at least one processor; wherein, the memory stores instructions executable by the at least one processor, and the instructions are executed by the at least one processor to enable the at least one processor to execute the sports guidance method in the first embodiment above.

[0058] Next, refer to Figure 4 , which shows a schematic structural diagram of a sports guidance device suitable for implementing the embodiments of this application. The sports guidance device in the embodiments of this application may include, but is not limited to, terminal devices such as smart phones, laptop computers, PDAs (Personal Digital Assistants), PADs (Portable Application Descriptions), and smart wearable devices (such as smart watches, virtual reality helmets, and augmented reality glasses). Figure 4 The sports guidance device shown is only an example and should not bring any limitations to the functions and usage scope of the embodiments of this application.

[0059] As Figure 4As shown, the motion guidance device may include a processing device 1001 (such as a central processing unit, a graphics processing unit, etc.), which can perform various appropriate actions and processes according to a program stored in a read-only memory (ROM: Read Only Memory) 1002 or a program loaded from a storage device 1003 into a random access memory (RAM: Random Access Memory) 1004. In the random access memory 1004, various programs and data required for the operation of the motion guidance device are also stored. The processing device 1001, the read-only memory 1002, and the random access memory 1004 are connected to each other through a bus 1005. An I / O (input / output) interface 1006 is also connected to the bus. Generally, the following systems may be connected to the I / O interface 1006: an input device 1007 including, for example, a touch screen, a touchpad, a keyboard, a mouse, an image sensor, a microphone, an accelerometer, a gyroscope, etc.; an output device 1008 including, for example, a liquid crystal display (LCD: Liquid Crystal Display), a speaker, a vibrator, etc.; a storage device 1003 including, for example, a magnetic tape, a hard disk, etc.; and a communication device 1009. The communication device 1009 can allow the motion guidance device to communicate with other devices wirelessly or wiredly to exchange data. Although the figure shows a motion guidance device with various systems, it should be understood that it is not required to implement or have all the systems shown. Instead, more or fewer systems may be implemented or had.

[0060] In particular, according to the embodiments disclosed in the present application, the processes described above with reference to the flowcharts can be implemented as computer software programs. For example, the embodiments disclosed in the present application include a computer program product, which includes a computer program carried on a computer-readable medium, and the computer program contains program codes for performing the methods shown in the flowcharts. In such an embodiment, the computer program can be downloaded and installed from a network through the communication device, or installed from the storage device 1003, or installed from the read-only memory 1002. When the computer program is executed by the processing device 1001, the above functions defined in the methods of the embodiments disclosed in the present application are executed.

[0061] The motion guidance device provided by the present application adopts the motion guidance method in the above embodiments and can solve the technical problem of the low refinement degree of the existing motion guidance methods. Compared with the prior art, the beneficial effects of the motion guidance device provided by the present application are the same as those of the motion guidance method provided by the above embodiments, and the other technical features in the motion guidance device are the same as those disclosed in the method of the previous embodiment and will not be elaborated here.

[0062] It should be understood that each part disclosed in this application can be implemented by hardware, software, firmware, or a combination thereof. In the description of the above embodiments, specific features, structures, materials, or characteristics can be combined in a suitable manner in any one or more embodiments or examples.

[0063] As described above, the above is only the specific implementation manner of this application, but the protection scope of this application is not limited thereto. Any person skilled in the art can easily think of changes or substitutions within the technical scope disclosed in this application, and all should be covered within the protection scope of this application. Therefore, the protection scope of this application should be subject to the protection scope of the claims.

[0064] This application also provides a motion guidance system. Please refer to Figure 5 , the motion guidance system includes: A monitoring patch 200, configured to collect the electromyographic signals of the concerned muscle groups and send them to the motion guidance device; A motion guidance device 100 communicatively connected to the monitoring patch, configured to execute the steps of the motion guidance method in the above embodiments.

[0065] See Figure 6 , Figure 6 is a schematic structural diagram of the monitoring patch 200. The monitoring patch 200 includes an electrode patch and an electromyographic processing device connected to the electrode patch. The electromyographic processing device includes an electromyographic sensor, a processing unit, a communication unit, a power supply unit, etc. In addition, the electromyographic processing device may further include components such as an inertial detection unit and a lighting unit.

[0066] The motion guidance system provided by this application adopts the motion guidance method in the above embodiments, and can solve the technical problem of the low refinement degree of the existing motion guidance methods. Compared with the prior art, the beneficial effects of the motion guidance system provided by this application are the same as those of the motion guidance method provided by the above embodiments, and other technical features in the motion guidance system are the same as the features disclosed in the method of the above embodiments, and will not be elaborated here.

[0067] This application provides a computer-readable storage medium, having computer-readable program instructions (i.e., computer programs) stored thereon, and the computer-readable program instructions are used to execute the motion guidance method in the above embodiments.

[0068] The computer-readable storage medium provided by the present application may be, for example, a USB flash drive, but is not limited to electrical, magnetic, optical, electromagnetic, infrared, or semiconductor systems or devices, or any combination of the above. More specific examples of computer-readable storage media may include, but are not limited to: electrical connections with one or more wires, portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM) or flash memory, optical fibers, portable compact disk read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination of the above. In this embodiment, the computer-readable storage medium may be any tangible medium that contains or stores a program, and the program can be used by or in combination with an instruction execution system or device. The program code contained on the computer-readable storage medium can be transmitted by any appropriate medium, including but not limited to: wires, optical cables, RF (Radio Frequency), etc., or any suitable combination of the above.

[0069] The above computer-readable storage medium may be included in a motion guidance device; or may exist separately without being assembled into the motion guidance device.

[0070] The above computer-readable storage medium carries one or more programs. When the one or more programs are executed by a motion guidance device, the motion guidance device is caused to: acquire the electromyographic signals of the muscle groups of interest, where the muscle groups of interest are the muscle groups involved in the target motion project; identify the activity state information of the muscle groups of interest according to the electromyographic signals; generate and output adjustment guidance information corresponding to the target motion project according to the activity state information.

[0071] Computer program code for performing the operations of this application can be written in one or more programming languages or combinations thereof. The above-mentioned programming languages include object-oriented programming languages such as Java, Smalltalk, C++, and also include conventional procedural programming languages such as the "C" language or similar programming languages. The program code can be executed entirely on the user's computer, partially on the user's computer, executed as an independent software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In the case of a remote computer, the remote computer can be connected to the user's computer through any kind of network, including a local area network (LAN: Local Area Network) or a wide area network (WAN: Wide Area Network), or it can be connected to an external computer (for example, by using an Internet service provider to connect through the Internet).

[0072] The flowcharts and block diagrams in the accompanying drawings illustrate the possible architectures, functions, and operations of systems, methods, and computer program products according to various embodiments of this application. In this regard, each block in the flowchart or block diagram may represent a module, a program segment, or a part of code that contains one or more executable instructions for implementing the specified logical function. It should also be noted that in some alternative implementations, the functions marked in the blocks may occur in a different order than that marked in the accompanying drawings. For example, two consecutive blocks shown may actually be executed substantially in parallel, and they may sometimes be executed in the reverse order, depending on the functions involved. It should also be noted that each block in the block diagram and / or flowchart, and the combination of blocks in the block diagram and / or flowchart, can be implemented by a dedicated hardware-based system for performing the specified functions or operations, or can be implemented by a combination of dedicated hardware and computer instructions.

[0073] The modules described in the embodiments of this application can be implemented in software or in hardware. Among them, the name of the module does not constitute a limitation on the unit itself in some cases.

[0074] The readable storage medium provided in this application is a computer-readable storage medium. The computer-readable storage medium stores computer-readable program instructions (i.e., computer programs) for performing the above-mentioned motion guidance method, and can solve the technical problem of the low refinement degree of the existing motion guidance method. Compared with the prior art, the beneficial effects of the computer-readable storage medium provided in this application are the same as those of the motion guidance method provided in the above embodiments, and will not be elaborated here.

[0075] The present application also provides a computer program product, including a computer program which, when executed by a processor, implements the steps of the motion guidance method as described above.

[0076] The computer program product provided by the present application can solve the technical problem of the low refinement degree of the existing motion guidance method. Compared with the prior art, the beneficial effects of the computer program product provided by the present application are the same as those of the motion guidance method provided by the above embodiments, and will not be elaborated herein.

[0077] The above are only partial embodiments of the present application, and thus do not limit the patent scope of the present application. Any equivalent structural transformation made under the technical concept of the present application by using the content of the specification and drawings of the present application, or direct / indirect application in other related technical fields, is included in the patent protection scope of the present application.

Claims

1. A sports guidance method, characterized in that, The described motion guidance method includes: Obtaining the electromyography signals of the concerned muscle groups, where the concerned muscle groups are the muscle groups involved in the target motion project; Identifying the activity status information of the concerned muscle groups according to the electromyography signals; Generating and outputting the adjustment guidance information corresponding to the target motion project according to the activity status information.

2. The exercise guidance method according to claim 1, characterized in that The step of identifying the activity status information of the concerned muscle groups according to the electromyography signals includes: Calculating the root mean square value and the signal attenuation slope of the concerned muscle groups according to the electromyography signals; Generating the activity intensity information of the concerned muscle groups according to the root mean square value; Generating the recovery speed information of the concerned muscle groups according to the signal attenuation slope; Taking the activity intensity information and the recovery speed information as the activity status information of the concerned muscle groups.

3. The exercise guidance method according to claim 2, wherein The step of identifying the activity status information of the concerned muscle groups according to the electromyography signals further includes: Performing wavelet transform on the electromyography signals to obtain the high-frequency band energy of the electromyography signals; After the high-frequency band energy is greater than a predetermined energy threshold, it is determined that the concerned muscle groups are in a tense state as the activity status information of the concerned muscle groups.

4. The exercise guidance method according to claim 1, characterized in that, The concerned muscle groups include the first limb muscle groups and the second limb muscle groups that cooperate with the first limb muscle groups. The step of identifying the activity status information of the concerned muscle groups according to the electromyography signals further includes: Identifying the first activation timing of the first limb muscle groups and the second activation timing of the second limb muscle groups according to the electromyography signals; Generating the coordination information of the concerned muscle groups as the activity status information of the concerned muscle groups according to the activation timing difference between the first activation timing and the second activation timing.

5. The exercise guidance method according to claim 1, wherein The step of generating and outputting the adjustment guidance information corresponding to the target motion project according to the activity status information includes: Obtaining the target muscle group activity index of the target motion project; Comparing the activity status information with the target muscle group activity index to obtain the muscle group activity difference information; Generating and outputting the corresponding adjustment guidance information according to the muscle group activity difference information.

6. The exercise guidance method according to any one of claims 1 to 5, characterized in that, Before the step of obtaining the electromyography signals of the concerned muscle groups, the motion guidance method further includes: After receiving the input target motion project, querying the concerned muscle groups corresponding to the target motion project; Displaying the position information of the concerned muscle groups so that the user can paste the monitoring patch on the area where the concerned muscle groups are located; Receiving the electromyography signals of the concerned muscle groups fed back by the monitoring patch.

7. A sports guidance device, characterized in that, The device includes: a memory, a processor, and a computer program stored on the memory and executable on the processor. The computer program is configured to implement the steps of the motion guidance method according to any one of claims 1 to 6.

8. A motion guidance system, characterized in that, The motion guidance system includes: A monitoring patch for collecting the electromyography signals of the concerned muscle groups and sending them to the motion guidance device; A motion guidance device communicatively connected to the monitoring patch for executing the steps of the motion guidance method according to any one of claims 1 to 6.

9. A storage medium, characterized in that, The storage medium is a computer-readable storage medium, and a computer program is stored on the storage medium. When the computer program is executed by a processor, the steps of the motion guidance method according to any one of claims 1 to 6 are implemented.

10. A computer program product, characterized in that, The computer program product includes a computer program. When the computer program is executed by a processor, the steps of the motion guidance method according to any one of claims 1 to 6 are implemented.

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