CN108491074B - Electronic device, exercise assisting method and related product - Google Patents
Electronic device, exercise assisting method and related product Download PDFInfo
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Abstract
The embodiment of the application relates to the technical field of mobile terminals, and discloses an electronic device, a motion assisting method and a related product. The electronic device comprises a brain wave sensor, a processor and an output device, wherein the brain wave sensor is used for acquiring brain wave signals of a user under the condition that the user performs a movement preparation action; a processor for determining a psychological state of the user according to the brain wave signal; output means for outputting instruction information in a case where a matching degree of the psychological state of the user and the target psychological state model is higher than a threshold value; the instruction information is used to instruct the user to perform the athletic movement. Therefore, by implementing the embodiment of the application, the brain wave signals can be analyzed to determine the current psychological state of the user, and the instruction information is output to instruct the user to execute the sports action when the current psychological state of the user is better, so that the user is helped to improve the sports achievement and the sports state.
Description
Technical Field
The present application relates to the field of mobile terminal technologies, and in particular, to an electronic device, a motion assistance method, and a related product.
Background
With the development of mobile terminal technology, mobile terminals have played an increasingly important role in people's lives. In life, it is increasingly convenient to use mobile terminals to perform activities such as payment and office work.
However, when a user interacts with the mobile terminal, the user often needs to input to the mobile terminal through operations such as gestures and actions, so that the user can interact with the mobile terminal. This limits the flexibility and freedom of operation of the mobile terminal by the user, and therefore how to improve the flexibility and freedom of operation of the mobile terminal by the user becomes a problem to be solved.
Disclosure of Invention
The embodiment of the application provides an electronic device, an exercise assisting method and a related product, which can help a user to improve exercise scores and competitive states.
In a first aspect, embodiments of the present application disclose an electronic device, which includes a brain wave sensor, a processor, and an output device, wherein,
the brain wave sensor is used for acquiring brain wave signals of a user under the condition that the user performs a movement preparation action;
the processor is used for determining the psychological state of the user according to the brain wave signals;
the output device is used for outputting instruction information under the condition that the matching degree of the psychological state of the user and the target psychological state model is higher than a threshold value; the instruction information is used for instructing the user to execute the motion action.
In a second aspect, an embodiment of the present application discloses a method for assisting exercise, applied to an electronic device including a brain wave sensor, a processor, and an output device, the method including:
controlling the brain wave sensor to acquire a brain wave signal of a user when the user performs a movement preparation action;
determining the psychological state of the user according to the brain wave signals;
controlling the output device to output instruction information under the condition that the matching degree of the psychological state of the user and the target psychological state model is higher than a threshold value; the instruction information is used for instructing the user to execute the motion action.
In a third aspect, embodiments of the present application disclose a movement assistance apparatus applied to an electronic apparatus including a brain wave sensor, a processor, and an output apparatus, the movement assistance apparatus including an acquisition unit, a determination unit, and an output unit, wherein,
the acquisition unit is used for controlling the brain wave sensor to acquire the brain wave signals of the user when the user performs a movement preparation action;
the determining unit is used for determining the psychological state of the user according to the brain wave signals;
the output unit is used for controlling the output device to output instruction information under the condition that the matching degree of the psychological state of the user and the target psychological state model is higher than a threshold value; the instruction information is used for instructing the user to execute the motion action.
In a fourth aspect, an embodiment of the present application provides an electronic device, including a processor, a memory, a communication interface, and one or more programs, where the one or more programs are stored in the memory and configured to be executed by the processor, and the program includes instructions for executing the steps of any of the methods in the second aspect of the embodiment of the present application.
In a fifth aspect, the present application provides a computer-readable storage medium, where the computer-readable storage medium stores a computer program for electronic data exchange, where the computer program makes a computer perform part or all of the steps described in any one of the methods in the second aspect of the present application.
In a sixth aspect, the present application provides a computer program product, wherein the computer program product includes a non-transitory computer-readable storage medium storing a computer program, and the computer program is operable to cause a computer to perform some or all of the steps described in any one of the methods of the second aspect of the present application. The computer program product may be a software installation package.
In the embodiment of the application, the electronic device comprises a brain wave sensor, a processor and an output device, wherein the brain wave sensor is used for acquiring brain wave signals of a user under the condition that the user performs a movement preparation action; a processor for determining a psychological state of the user according to the brain wave signal; output means for outputting instruction information in a case where a matching degree of the psychological state of the user and the target psychological state model is higher than a threshold value; the instruction information is used to instruct the user to perform the athletic movement. Therefore, by implementing the embodiment of the application, the brain wave signals can be analyzed to determine the current psychological state of the user, and the instruction information is output to instruct the user to execute the sports action when the current psychological state of the user is better, so that the user is helped to improve the sports achievement and the sports state.
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In order to more clearly illustrate the technical solutions in the embodiments of the present application, the drawings needed to be used in the description of the embodiments will be briefly introduced below, and it is obvious that the drawings in the following description are only some embodiments of the present application, and it is obvious for those skilled in the art to obtain other drawings based on these drawings without inventive exercise.
Fig. 1 is a schematic structural diagram of an electronic device disclosed in an embodiment of the present application;
fig. 2 is a schematic structural diagram of another electronic device disclosed in the embodiment of the present application;
fig. 3A is a schematic structural diagram of another electronic device disclosed in the embodiment of the present application;
fig. 3B is an interaction diagram of a brain wave sensor, an electronic device and a smart wearable device according to an embodiment of the disclosure;
fig. 4 is a schematic structural diagram of another electronic device disclosed in the embodiment of the present application;
FIG. 5 is a schematic illustration of an electroencephalogram disclosed in an embodiment of the present application;
fig. 6 is a schematic flow chart of an exercise assisting method disclosed in the embodiments of the present application;
FIG. 7 is a functional block diagram of an exercise assisting device according to an embodiment of the present disclosure;
fig. 8 is a schematic structural diagram of another electronic device disclosed in the embodiments of the present application;
fig. 9 is a schematic structural diagram of another electronic device disclosed in the embodiment of the present application.
Detailed Description
In order to make the objects, technical solutions and advantages of the present application clearer, the present application will be described in further detail with reference to the accompanying drawings, and it is obvious that the described embodiments are only a part of the embodiments of the present application, and not all embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present application.
The terms "first," "second," and the like in the description and claims of the present application and in the above-described drawings are used for distinguishing between different objects and not for describing a particular order. Furthermore, the terms "include" and "have," as well as any variations thereof, are intended to cover non-exclusive inclusions. For example, a process, method, system, article, or apparatus that comprises a list of steps or elements is not limited to only those steps or elements listed, but may alternatively include other steps or elements not listed, or inherent to such process, method, or apparatus.
Reference herein to "an embodiment" means that a particular feature, structure, or characteristic described in connection with the embodiment can be included in at least one embodiment of the application. The appearances of the phrase in various places in the specification are not necessarily all referring to the same embodiment, nor are separate or alternative embodiments mutually exclusive of other embodiments. It is explicitly and implicitly understood by one skilled in the art that the embodiments described herein can be combined with other embodiments.
The electronic device according to the embodiment of the present application may include various handheld devices, vehicle-mounted devices, wearable devices, computing devices or other processing devices connected to a wireless modem, and various forms of User Equipment (UE), Mobile Stations (MS), terminal devices (terminal device), and the like. For convenience of description, the above-mentioned apparatuses are collectively referred to as electronic devices.
The embodiment of the application provides an electronic device, a motion assisting method and a related product, which can analyze brain wave signals to determine the current psychological state of a user, and output instruction information to instruct the user to execute a motion action when the current psychological state of the user is better, so that the user is helped to improve the motion score and the competitive state. The following are detailed below.
Referring to fig. 1, fig. 1 is a schematic structural diagram of an electronic device 100 disclosed in an embodiment of the present application, as shown in fig. 1, the electronic device 100 includes a brain wave sensor 110, a processor 120 and an output device 130, and the brain wave sensor 110, the processor 120 and the output device 130 may be connected to each other so as to communicate with each other.
In the embodiment of the present application, the brain wave sensor 110 is configured to acquire a brain wave signal of a user when the user performs a movement preparation action;
a processor 120 for determining a psychological state of the user according to the brain wave signal;
an output means 130 for outputting instruction information in a case where a matching degree of the user's psychological state with the target psychological state model is higher than a threshold value; wherein the instruction information is used for instructing the user to perform the motion action.
In the human body, neuronal activity of the brain is conducted to the cerebral cortex by ions, thus producing weak voltage changes; therefore, in the embodiment of the present application, the brain wave sensor 110 has at least one conductive electrode that can be fixed on the scalp of the user so as to sense a weak voltage variation caused by the brain waves. In this embodiment, the conductive electrode may be a dry electrode, a wet electrode, or an invasive electrode, and specifically, which conductive electrode is adopted is not limited in this embodiment.
As an alternative embodiment, the brain wave sensor 110 further has a signal processing circuit, so that after the conductive electrodes acquire the original voltage signals, the signal processing circuit performs differential amplification on the original voltage signals, filters out interference noise introduced by the electromyographic signals, and performs analog-to-digital conversion to obtain digitized brain wave signals. The brain wave signals may be transmitted to the processor 120 for further signal processing and analysis, so as to know the fatigue level, concentration level, psychological state, and the like of the user.
In the embodiment of the present Application, the Processor 120 may be a Central Processing Unit (CPU), 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, a transistor logic device, a hardware component, or any combination thereof.
In the embodiment of the present application, the output device 130 may be a display screen, a speaker, an indicator light, or other devices capable of outputting instruction information. Accordingly, when the output device 130 is a display screen, the instruction information is video or picture information; when the output device 130 is a speaker, the instruction information is audio information.
In the embodiment of the application, the electronic device 100 may analyze the psychological state of the user when the user performs the exercise preparation action, and prompt the user to perform the exercise action when the psychological state of the user is better, so as to help the user to stabilize the psychological state during the exercise and improve the athletic performance. For example, the user may perform archery, in a case where the user performs the pantograph aiming (i.e., performs the movement preparation motion), the electronic device 100 acquires the brain wave signals of the user, analyzes the brain wave signals to determine the psychological state of the user, and outputs instruction information to instruct the user to shoot the arrow in a case where the degree of matching between the psychological state of the user and the psychological state model corresponding to the archery is higher than a threshold value.
The processor 120 may analyze the brain wave signals of the user according to the brain wave signals acquired by the brain wave sensor 110, so as to determine the current psychological state of the user; the mental state may include a plurality of dimensions, and specifically, the mental state may include concentration, fatigue, tension, excitement, and the like, and may also be a combination of one or more of the above dimensions. Wherein, the processor 120 determines a matching degree of the user's mental state with the target mental state model by comparing the multi-dimensional model of the user's mental state with the target mental state template, and in case the matching degree is higher than a threshold value, outputs instruction information to instruct the user to perform the exercise action.
Therefore, by implementing the embodiment of the application, the brain wave signals can be analyzed to determine the current psychological state of the user, and the instruction information is output to instruct the user to execute the sports action when the current psychological state of the user is better, so that the user is helped to improve the sports achievement and the sports state.
As an alternative implementation, the electronic device 100 may further include a motion capture sensor 140, please refer to fig. 2, fig. 2 is a schematic structural diagram of another electronic device disclosed in this embodiment, as shown in fig. 2, the motion capture sensor 140 may be connected to the processor 120, so that the processor 120 may invoke the motion capture sensor 140 to obtain the pose information.
Among them, the motion capture sensor 140 may be a set of cameras arranged at an angle, which determines the posture information of the user by acquiring images of the user from multiple angles; in addition, infrared optical markers may be disposed on joints, the body, and the head of the user, and the motion capture sensor 140 may be an infrared camera or an infrared camera, so as to acquire the posture information of the user.
Specifically, the motion capture sensor 140 is configured to acquire posture information of the user when performing the motion preparation motion.
In this embodiment, the processor 120 may determine whether the exercise preparation action of the user is in place (i.e., whether the exercise preparation action satisfies the preset action requirement) in addition to determining whether the matching degree between the mental state of the user and the target mental state model is higher than the threshold, and may control the output device to output the instruction information if both of the exercise preparation action and the preset action requirement are satisfied. By controlling the preparation action and the psychological state when the user executes the sports action, the sports performance of the user can be effectively improved, and the athletic score is improved.
In particular, output means 130 for: and outputting instruction information under the condition that the matching degree of the mental state of the user and the target mental state model is higher than a threshold value and the movement preparation movement meets the preset movement requirement.
In addition to this, an apparatus or device for motion capture of the user may be provided separately from the electronic device 100. As an alternative embodiment, the electronic device 100 may include a data transmission module 150 based on the embodiment shown in fig. 1. Referring to fig. 3A, fig. 3A is a schematic structural diagram of another electronic device disclosed in the embodiment of the present application. As shown in fig. 3A, the data transmission module 150 may be connected to the processor 120 so that data can be received or transmitted under the control of the processor 120.
Specifically, the data transmission module 150 is configured to receive posture information of the user performing the exercise preparation action, which is fed back by the smart wearable device. After that, the output device 130 may output the instruction information in a case that the matching degree of the user's mental state and the target mental state model is higher than the threshold value, and the exercise preparation motion satisfies the preset motion requirement.
The intelligent wearable device can be intelligent clothes, intelligent gloves and the like, a large number of sensors are distributed on the intelligent wearable device, the motion action of the body of a user can be acquired, and therefore posture information of the user is obtained through analysis.
As an alternative embodiment, the brain wave sensor 110 may also be a device or an apparatus separately disposed from the electronic device 100, please refer to fig. 3B, where fig. 3B is an interaction diagram of the brain wave sensor, the electronic device, and the smart wearable apparatus disclosed in the embodiments of the present application. As shown in fig. 3B, after the brain wave sensor 110 acquires the brain wave signals, the brain wave signals are transmitted to the electronic apparatus 100 through a network connection; after acquiring the posture information of the user during the exercise preparation action, the smart wearable device 200 transmits the posture information to the electronic device 100 through network connection; then the electronic device 100 determines the psychological state of the user according to the brain wave signal, determines whether the exercise preparation movement of the user meets the preset movement requirement according to the posture information of the user, and outputs instruction information to prompt the user to execute the exercise movement under the condition that the matching degree of the psychological state of the user and the target psychological state model is higher than a threshold value and the exercise preparation movement meets the preset movement requirement.
Referring to fig. 4, fig. 4 is a schematic structural diagram of another electronic device disclosed in the embodiment of the present application. As shown in fig. 4, the electronic device 100 may further include a memory 160 on the basis of the electronic device shown in fig. 3A, and the memory 160 may be connected to the processor 120, so that the processor 120 may store data in the memory 160 or call data from the memory 160.
In the embodiment of the present application, the memory 160 is configured to store more than one mental state model.
The processor 120 is further configured to determine a type of motion performed by the user according to the acquired gesture information; and selects a target mind state model from the more than one mind state models stored in the memory 160 according to the motion class.
In this embodiment, different motion categories correspond to different mental state models; for example, when the sport category is archery, when the user's performance is better, the corresponding mental state model should be: high concentration, low tension and low excitation; when the sport category is sprint, the corresponding mental state model should be: high concentration, low tension and high excitement. Therefore, in the embodiment, the gesture information of the user is analyzed to determine the type of exercise the user is performing, and a mental state model corresponding to the type of exercise is selected from more than one mental state models according to the type of exercise the user is engaged in as the target mental state model; and then comparing the current psychological state of the user with the target psychological state model to determine whether the user is in a better psychological state currently.
In particular, in the case where the psychological state includes three dimensions of concentration, tension, and excitement, the processor 120 is specifically configured to, in determining the psychological state of the user from the brain wave signals: determining the concentration degree, the tension degree and the excitement degree of the user according to the brain wave signals; and generating a three-dimensional data model according to the concentration degree, the tension degree and the excitement degree of the user, and determining the three-dimensional data model as the psychological state of the user.
Further, the memory 160 is also used for storing an electroencephalogram template library, which includes more than one electroencephalogram template, and the concentration, tension and excitement corresponding to each electroencephalogram template. Thus, through the electroencephalogram template library, the concentration, the tension, and the excitement of the user currently using the electronic apparatus 100 can be determined. Specifically, the method comprises the following steps: the processor 120 is configured to: generating the current electroencephalogram of the user according to the electroencephalogram signals; determining a waveform feature period in the current electroencephalogram; dividing the current electroencephalogram into a plurality of segmented electroencephalograms according to the waveform feature period; comparing each segmented electroencephalogram with an electroencephalogram template in an electroencephalogram template library to obtain an electroencephalogram template matched with each segmented electroencephalogram; determining one or more electroencephalogram templates with the highest repetition degree in a plurality of electroencephalogram templates corresponding to the plurality of segmented electroencephalograms; and determining the concentration degree, the tension degree and the excitement degree corresponding to the electroencephalogram template with the highest repetition degree as the concentration degree, the tension degree and the excitement degree of the user.
For example, please refer to fig. 5, fig. 5 is a schematic diagram of an electroencephalogram according to an embodiment of the present application; as shown in fig. 5, assuming that the electroencephalogram currently acquired by the electronic device includes 100 waveform feature periods, the current electroencephalogram can be split according to the waveform feature periods into at least 5 segmented electroencephalograms, namely, segmented electroencephalograms 1, 2, 3, 4 and 5, wherein each segmented electroencephalogram occupies 20 feature periods, specifically, segmented electroencephalograms 1 correspond to waveform feature periods 1-20, segmented electroencephalograms 2 correspond to waveform feature periods 21-40, segmented electroencephalograms 3 correspond to waveform feature periods 41-60, segmented electroencephalograms 4 correspond to waveform feature periods 61-80, segmented electroencephalograms 5 correspond to waveform feature periods 81-100, each segmented electroencephalogram is compared with an electroencephalogram template library, each segmented electroencephalogram corresponds to a highest-matching electroencephalogram template, specifically, the segmented electroencephalogram 1 corresponds to an electroencephalogram template a, the segmented electroencephalogram 2 corresponds to an electroencephalogram template a, the segmented electroencephalogram 3 corresponds to an electroencephalogram template b, the segmented electroencephalogram 4 corresponds to the electroencephalogram template a, and the segmented electroencephalogram 5 corresponds to the electroencephalogram template a, and then the electroencephalogram template a with the highest repetition degree is determined to be the electroencephalogram template corresponding to the current electroencephalogram.
As can be seen, in this example, in consideration of the volatility of the human brain, the electronic device divides the electroencephalogram into a plurality of segmented electroencephalograms based on the waveform feature period of the current electroencephalogram of the user, performs template comparison on each segmented electroencephalogram to obtain an electroencephalogram template corresponding to each segmented electroencephalogram, and then determines the electroencephalogram template with the highest template repetition degree as the electroencephalogram template corresponding to the current electroencephalogram, so that a part of the electroencephalograms corresponding to abnormal electroencephalogram signals generated due to the volatility of the human brain can be removed in time, the influence of the abnormal electroencephalograms on the matching result is avoided, the matching accuracy of the electroencephalogram templates is improved, and the detection accuracy is improved.
Referring to fig. 6, fig. 6 is a schematic flow chart illustrating a method for assisting exercise according to an embodiment of the present application. As shown in fig. 6, the method may be applied to an electronic device including a brain wave sensor, a processor, and an output device, and the exercise assisting method may include the steps of:
601. when the user performs the movement preparation motion, the brain wave sensor is controlled to acquire the brain wave signal of the user.
In the human body, neuronal activity of the brain is conducted to the cerebral cortex by ions, thus producing weak voltage changes; therefore, in the embodiment of the present application, the brain wave sensor has at least one conductive electrode that can be fixed on the scalp of the user so as to sense a weak voltage variation caused by the brain waves. In this embodiment, the conductive electrode may be a dry electrode, a wet electrode, or an invasive electrode, and specifically, which conductive electrode is adopted is not limited in this embodiment.
As an optional implementation manner, the brain wave sensor further has a signal processing circuit, so that after the conductive electrode acquires the original voltage signal, the signal processing circuit performs differential amplification on the original voltage signal, filters out interference noise introduced by the electromyographic signal, and performs analog-to-digital conversion on the interference noise to obtain a digitized brain wave signal. The brain wave signals can be transmitted to a processor for further signal processing and analysis, so that the fatigue degree, the concentration degree, the psychological state and the like of the user can be obtained.
602. And determining the psychological state of the user according to the brain wave signals.
In the case where the psychological state includes three dimensions of concentration, tension, and excitement, in determining the psychological state of the user from the brain wave signals, the electronic apparatus may: determining the concentration degree, the tension degree and the excitement degree of the user according to the brain wave signals; and generating a three-dimensional data model according to the concentration degree, the tension degree and the excitement degree of the user, and determining the three-dimensional data model as the psychological state of the user.
Specifically, the electronic device may generate a current electroencephalogram of the user from the brain wave signals of the user; determining a waveform feature period in the current electroencephalogram; dividing the current electroencephalogram into a plurality of segmented electroencephalograms according to the waveform feature period; comparing each segmented electroencephalogram with an electroencephalogram template in an electroencephalogram template library to obtain an electroencephalogram template matched with each segmented electroencephalogram; determining an electroencephalogram template with the highest repetition degree in a plurality of electroencephalogram templates corresponding to the plurality of segmented electroencephalograms; and determining the concentration degree, the tension degree and the excitement degree corresponding to the electroencephalogram template with the highest repetition degree as the concentration degree, the tension degree and the excitement degree of the user.
603. Controlling an output device to output instruction information under the condition that the matching degree of the psychological state of the user and the target psychological state model is higher than a threshold value; the instruction information is used to instruct the user to perform the athletic movement.
In this embodiment, different motion categories correspond to different mental state models; for example, when the sport category is archery, when the user's performance is better, the corresponding mental state model should be: high concentration, low tension and low excitation; when the sport category is sprint, the corresponding mental state model should be: high concentration, low tension and high excitement. Therefore, in the embodiment, the gesture information of the user is analyzed to determine the type of exercise the user is performing, and a mental state model corresponding to the type of exercise is selected from more than one mental state models according to the type of exercise the user is engaged in as the target mental state model; and then comparing the current psychological state of the user with the target psychological state model to determine whether the user is in a better psychological state currently.
Therefore, by implementing the method described in fig. 6, the electroencephalogram signal can be analyzed to determine the current psychological state of the user, and when the current psychological state of the user is better, instruction information can be output to instruct the user to perform an athletic movement, thereby helping the user to improve the athletic performance and the athletic state.
Referring to fig. 7, fig. 7 is a functional block diagram of a exercise assisting device according to an embodiment of the present disclosure. The exercise assisting device may be applied to an electronic device having a brain wave sensor, a processor, and an output device, the exercise assisting device including an acquisition unit 701, a determination unit 702, and an output unit 703, wherein,
an acquisition unit 701 for controlling the brain wave sensor to acquire a brain wave signal of a user in a case where the user performs a movement preparation action;
a determination unit 702 for determining a psychological state of the user from the brain wave signal;
an output unit 703, configured to control the output device to output instruction information when a matching degree between the mental state of the user and a target mental state model is higher than a threshold; the instruction information is used for instructing the user to execute the motion action.
It will be appreciated that the exercise assisting device, in order to achieve the above-described functions, comprises corresponding hardware structures and/or software modules for performing the respective functions. Those of skill in the art would readily appreciate that the various illustrative elements and algorithm steps described in connection with the embodiments disclosed herein may be implemented as hardware or combinations of hardware and computer software. Whether a function is performed as hardware or computer software drives hardware depends upon the particular application and design constraints imposed on the solution. Skilled artisans may implement the described functionality in varying ways for each particular application, but such implementation decisions should not be interpreted as causing a departure from the scope of the present application.
The embodiment of the present application may perform the division of the functional units for the exercise assisting device according to the above method examples, for example, each functional unit may be divided corresponding to each function, or two or more functions may be integrated into one processing unit. The integrated unit can be realized in a form of hardware, and can also be realized in a form of a software functional unit. It should be noted that the division of the unit in the embodiment of the present application is schematic, and is only a logic function division, and there may be another division manner in actual implementation.
As an alternative embodiment, the obtaining Unit 701 and the determining Unit 702 may be a Central Processing Unit (CPU), 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, a transistor logic device, a hardware component, or any combination thereof. And the output unit 703 may be a speaker, a display screen, an indicator light, and the like.
Therefore, with the exercise assisting device described in fig. 7, the electroencephalogram signal can be analyzed to determine the current psychological state of the user, and when the current psychological state of the user is better, instruction information is output to instruct the user to perform an exercise action, thereby helping the user to improve the athletic performance and the athletic state.
Referring to fig. 8, fig. 8 is a schematic structural diagram of another electronic device 800 according to an embodiment of the disclosure. The electronic device 800 comprises a processor 801, a memory 802, a communication interface 803, and one or more programs, wherein the communication interface 803 may also be referred to as a data transmission module; the electronic device 800 also includes a brain wave sensor 804, an output device 805, and a motion capture sensor 806. Wherein the one or more programs are stored in the memory 802 and configured to be executed by the processor 801, the programs including instructions for performing the steps of:
controlling the brain wave sensor to acquire a brain wave signal of a user when the user performs a movement preparation action;
determining the psychological state of the user according to the brain wave signals;
controlling the output device to output instruction information under the condition that the matching degree of the psychological state of the user and the target psychological state model is higher than a threshold value; the instruction information is used for instructing the user to execute the motion action.
As an alternative implementation, the program further includes instructions for performing the steps of:
controlling the motion capture sensor to acquire attitude information of the user during the motion preparation motion;
in controlling the output device to output the instruction information in a case where the degree of matching of the user's mind state with the target mind state model is higher than a threshold value, the program includes instructions specifically for performing the steps of:
determining whether the movement preparation action meets a preset action requirement or not according to the attitude information;
and controlling the output device to output the instruction information under the condition that the matching degree of the psychological state of the user and the target psychological state model is higher than the threshold value and the motion preparation motion meets the preset motion requirement.
As an alternative implementation, the program further includes instructions for performing the steps of:
controlling the data transmission module to receive the gesture information fed back by the intelligent wearable device when the user performs the motion preparation action.
As an alternative implementation, the program further includes instructions for performing the steps of:
determining the type of the motion performed by the user according to the posture information;
selecting the target mental state model from more than one mental state models stored in the memory according to the motion category.
As an alternative embodiment, the mental states include concentration, tension, and excitement;
in determining the psychological state of the user from the brain wave signals, the above-mentioned program includes instructions for specifically performing the steps of:
determining concentration, tension and excitement of the user according to the brain wave signals; generating a three-dimensional data model according to the concentration degree, the tension degree and the excitement degree of the user, and determining the three-dimensional data model as the psychological state of the user;
in determining the concentration, the tension and the excitement of the user from the brain wave signals, the program comprises instructions for carrying out in particular the steps of:
generating an electroencephalogram of the user from the brain wave signals;
determining a waveform characteristic period of the electroencephalogram;
dividing the electroencephalogram into a plurality of segmented electroencephalograms according to the waveform feature period;
comparing each segmented electroencephalogram of the plurality of segmented electroencephalograms with an electroencephalogram template in an electroencephalogram template library stored in the memory to obtain an electroencephalogram template matching each segmented electroencephalogram; wherein the electroencephalogram template library comprises more than one electroencephalogram template and the concentration, the tension and the excitement corresponding to each electroencephalogram template;
determining an electroencephalogram template with the highest repetition degree in a plurality of electroencephalogram templates corresponding to the plurality of segmented electroencephalograms;
and determining the concentration degree, the tension degree and the excitement degree corresponding to the electroencephalogram template with the highest repetition degree as the concentration degree, the tension degree and the excitement degree of the user.
Therefore, with the electronic device described in fig. 8, the electroencephalogram signal can be analyzed to determine the current psychological state of the user, and when the current psychological state of the user is better, instruction information is output to instruct the user to perform an athletic movement, thereby helping the user to improve the athletic performance and the athletic state.
Referring to fig. 9, fig. 9 is a schematic structural diagram of another electronic device 900 disclosed in the present embodiment. As shown in fig. 9, for convenience of explanation, only the parts related to the embodiments of the present application are shown, and details of the technology are not disclosed, please refer to the method part of the embodiments of the present application. The electronic device may be any terminal equipment including a mobile phone, a tablet computer, a PDA (Personal Digital Assistant), a POS (Point of Sales), a vehicle-mounted computer, etc., taking the electronic device as the mobile phone as an example:
fig. 9 is a block diagram illustrating a partial structure of a mobile phone related to an electronic device provided in an embodiment of the present application. Referring to fig. 9, the handset includes: memory 902, input unit 903, display unit 904, sensor 905, and processor 908. Those skilled in the art will appreciate that the handset configuration shown in fig. 9 is not intended to be limiting and may include more or fewer components than those shown, or some components may be combined, or a different arrangement of components.
The following describes each component of the mobile phone in detail with reference to fig. 9:
the memory 902 may be used to store software programs and modules, and the processor 908 executes various functional applications and data processing of the cellular phone by operating the software programs and modules stored in the memory 902. The memory 902 may mainly include a program storage area and a data storage area, wherein the program storage area may store an operating system, an application program required by at least one function (such as a sound playing function, an image playing function, etc.), and the like; the storage data area may store data (such as audio data, a phonebook, etc.) created according to the use of the cellular phone, and the like. Further, the memory 902 may include high speed random access memory, and may also include non-volatile memory, such as at least one magnetic disk storage device, flash memory device, or other volatile solid state storage device. In embodiments of the present application, memory 902 may be used for more than one mental state model; the memory 902 may also be used to store an electroencephalogram template library; wherein the electroencephalogram template library includes more than one electroencephalogram template and a concentration, an excitement, and a tension corresponding to each electroencephalogram template.
The input unit 903 may be used to receive input numeric or character information and generate key signal inputs related to user settings and function control of the cellular phone. Specifically, the input unit 903 may include a touch panel 9031. The touch panel 9031, also called a touch screen, may collect a touch operation performed by a user on or near the touch panel 9031 (e.g., an operation performed by the user on or near the touch panel 9031 by using a finger, a stylus, or any other suitable object or accessory), and drive a corresponding connection device according to a preset program. Alternatively, the touch panel 9031 may include two parts, namely, a touch detection device and a touch controller. The touch detection device detects the touch direction of a user, detects a signal brought by touch operation and transmits the signal to the touch controller; the touch controller receives touch information from the touch sensing device and converts it to touch point coordinates, which are provided to the processor 908 and can receive commands from the processor assembly 908 and execute them. In addition, the touch panel 9031 may be implemented by using various types such as a resistive type, a capacitive type, an infrared ray, and a surface acoustic wave.
The display unit 904 may be used to display information input by the user or information provided to the user and various menus of the cellular phone. The Display unit 904 may include a Display panel 9041, and optionally, the Display panel 9041 may be configured in the form of a Liquid Crystal Display (LCD), an Organic Light-Emitting Diode (OLED), or the like. Further, the touch panel 9031 may cover the display panel 9041, and when the touch panel 9031 detects a touch operation thereon or nearby, the touch panel is transmitted to the processor assembly 908 to determine the type of the touch event, and then the processor assembly 908 provides a corresponding visual output on the display panel 9041 according to the type of the touch event. Although in fig. 9, the touch panel 9031 and the display panel 9041 are two independent components to implement the input and output functions of the mobile phone, in some embodiments, the touch panel 9031 and the display panel 9041 may be integrated to implement the input and output functions of the mobile phone. In this embodiment, the display panel 9041 may be configured to output instruction information, where the instruction information is used to instruct a user to perform a motion action.
The handset may also include at least one sensor 905, such as a light sensor, motion sensor, and other sensors. Specifically, the light sensor may include an ambient light sensor and a proximity sensor, wherein the ambient light sensor may adjust the brightness of the display panel 9041 according to the brightness of ambient light, and the proximity sensor may turn off the display panel 9041 and/or the backlight when the mobile phone moves to the ear. As one of the motion sensors, the accelerometer sensor can detect the magnitude of acceleration in each direction (generally, three axes), can detect the magnitude and direction of gravity when stationary, and can be used for applications of recognizing the posture of a mobile phone (such as horizontal and vertical screen switching, related games, magnetometer posture calibration), vibration recognition related functions (such as pedometer and tapping), and the like; as for other sensors such as a gyroscope, a barometer, a hygrometer, a thermometer, and an infrared sensor, which can be configured on the mobile phone, further description is omitted here. In the embodiment of the present application, the sensor 905 includes a brain wave sensor 9051, and the brain wave sensor 9051 is configured to acquire a brain wave signal of the user.
The processor 908 is a control center of the mobile phone, and the processor 908 connects various parts of the entire mobile phone by using various interfaces and lines, and performs various functions of the mobile phone and processes data by operating or executing software programs and/or modules stored in the memory 902 and calling data stored in the memory 902, thereby performing overall monitoring of the mobile phone. Alternatively, processor 908 may include one or more processing units; preferably, the processor 908 may integrate an application processor, which primarily handles operating systems, user interfaces, applications, etc., and a modem processor, which primarily handles wireless communications. It is to be appreciated that the modem processor described above may not be integrated into processor 908. In the embodiment of the present application, the processor 908 may determine the psychological state of the user from the brain wave signals.
Although not shown, the mobile phone may further include a radio frequency circuit, a Wireless Fidelity (WiFi) module, a bluetooth module, and the like, which are not described in detail herein.
In the embodiment shown in fig. 6, the method flow of each step may be implemented based on the structure of the mobile phone.
In the embodiment shown in fig. 7, the functions of the units can be implemented based on the structure of the mobile phone.
Therefore, with the mobile phone described in fig. 9, the electroencephalogram signal can be analyzed to determine the current psychological state of the user, and when the current psychological state of the user is better, instruction information is output to instruct the user to perform an athletic movement, thereby helping the user to improve the athletic performance and the athletic state.
Embodiments of the present application also provide a computer storage medium, where the computer storage medium stores a computer program for electronic data exchange, and the computer program enables a computer to execute part or all of the steps of any one of the methods described in the above method embodiments, and the computer includes a mobile terminal.
Embodiments of the present application also provide a computer program product comprising a non-transitory computer readable storage medium storing a computer program operable to cause a computer to perform some or all of the steps of any of the methods as described in the above method embodiments. The computer program product may be a software installation package, the computer comprising a mobile terminal.
It should be noted that, for simplicity of description, the above-mentioned method embodiments are described as a series of acts or combination of acts, but those skilled in the art will recognize that the present application is not limited by the order of acts described, as some steps may occur in other orders or concurrently depending on the application. Further, those skilled in the art should also appreciate that the embodiments described in the specification are preferred embodiments and that the acts and modules referred to are not necessarily required in this application.
In the foregoing embodiments, the descriptions of the respective embodiments have respective emphasis, and for parts that are not described in detail in a certain embodiment, reference may be made to related descriptions of other embodiments.
In the embodiments provided in the present application, it should be understood that the disclosed apparatus may be implemented in other manners. For example, the above-described embodiments of the apparatus are merely illustrative, and for example, the above-described division of the units is only one type of division of logical functions, and other divisions may be realized in practice, for example, a plurality of units or components may be combined or integrated into another system, or some features may be omitted, or not executed. In addition, the shown or discussed mutual coupling or direct coupling or communication connection may be an indirect coupling or communication connection of some interfaces, devices or units, and may be an electric or other form.
The units described as separate parts may or may not be physically separate, and parts displayed as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of the embodiment.
In addition, functional units in the embodiments of the present application may be integrated into one processing unit, or each unit may exist alone physically, or two or more units are integrated into one unit. The integrated unit can be realized in a form of hardware, and can also be realized in a form of a software functional unit.
The integrated unit may be stored in a computer readable memory if it is implemented in the form of a software functional unit and sold or used as a stand-alone product. Based on such understanding, the technical solution of the present application may be substantially implemented or a part of or all or part of the technical solution contributing to the prior art may be embodied in the form of a software product stored in a memory, and including several instructions for causing a computer device (which may be a personal computer, a server, or a network device) to execute all or part of the steps of the above-mentioned method of the embodiments of the present application. And the aforementioned memory comprises: a U-disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a removable hard disk, a magnetic or optical disk, and other various media capable of storing program codes.
Those skilled in the art will appreciate that all or part of the steps in the methods of the above embodiments may be implemented by associated hardware instructed by a program, which may be stored in a computer-readable memory, which may include: flash Memory disks, Read-Only memories (ROMs), Random Access Memories (RAMs), magnetic or optical disks, and the like.
The foregoing detailed description of the embodiments of the present application has been presented to illustrate the principles and implementations of the present application, and the above description of the embodiments is only provided to help understand the method and the core concept of the present application; meanwhile, for a person skilled in the art, according to the idea of the present application, there may be variations in the specific embodiments and the application scope, and in summary, the content of the present specification should not be construed as a limitation to the present application.
Claims (9)
1. An electronic device comprising a brain wave sensor, a memory, a processor, and an output device, wherein,
the memory is used for storing more than one mental state model and storing an electroencephalogram template library; wherein the electroencephalogram template library comprises more than one electroencephalogram template and the concentration, the tension and the excitement corresponding to each electroencephalogram template;
the brain wave sensor is used for acquiring brain wave signals of a user under the condition that the user performs a movement preparation action;
the processor is used for determining the motion type of the user according to the posture information; selecting a target mental state model from the more than one mental state models according to the motion type; generating an electroencephalogram of the user from the brain wave signals; determining a waveform characteristic period of the electroencephalogram; dividing the electroencephalogram into a plurality of segmented electroencephalograms according to the waveform feature period; comparing each segmented electroencephalogram of the plurality of segmented electroencephalograms with an electroencephalogram template of the electroencephalogram template library to obtain an electroencephalogram template matching each segmented electroencephalogram; determining an electroencephalogram template with the highest repetition degree in a plurality of electroencephalogram templates corresponding to the plurality of segmented electroencephalograms; determining the concentration degree, the tension degree and the excitement degree corresponding to the electroencephalogram template with the highest repetition degree as the concentration degree, the tension degree and the excitement degree of the user; generating a three-dimensional data model according to the concentration degree, the tension degree and the excitement degree of the user, and determining the three-dimensional data model as the psychological state of the user;
the output device is used for outputting instruction information under the condition that the matching degree of the psychological state of the user and the target psychological state model is higher than a threshold value; the instruction information is used for instructing the user to execute a motion action; and the motion type and the target mental state model have a corresponding relation.
2. The electronic device of claim 1, further comprising a motion capture sensor;
the motion capture sensor is used for acquiring gesture information of the user during the motion preparation motion;
in the aspect of outputting instruction information when the matching degree between the mental state of the user and the target mental state model is higher than the threshold, the output device is specifically configured to:
determining whether the movement preparation action meets a preset action requirement or not according to the attitude information;
and outputting the instruction information under the condition that the matching degree of the psychological state of the user and the target psychological state model is higher than the threshold value and the motion preparation motion meets the preset motion requirement.
3. The electronic device of claim 1, further comprising a data transmission module;
the data transmission module is used for receiving gesture information fed back by the intelligent wearable device when the user performs the motion preparation action;
in the aspect of outputting instruction information when the matching degree between the mental state of the user and the target mental state model is higher than the threshold, the output device is specifically configured to:
determining whether the movement preparation action meets a preset action requirement or not according to the attitude information;
and outputting the instruction information under the condition that the matching degree of the psychological state of the user and the target psychological state model is higher than the threshold value and the motion preparation motion meets the preset motion requirement.
4. An exercise assisting method is applied to an electronic device comprising a brain wave sensor, a memory, a processor and an output device, wherein the memory is used for storing more than one mental state model and storing an electroencephalogram template library; wherein the electroencephalogram template library comprises more than one electroencephalogram template and the concentration, the tension and the excitement corresponding to each electroencephalogram template; the method comprises the following steps:
controlling the brain wave sensor to acquire a brain wave signal of a user when the user performs a movement preparation action;
determining the type of the motion performed by the user according to the posture information; selecting a target mental state model from the more than one mental state models according to the motion type; generating an electroencephalogram of the user from the brain wave signals; determining a waveform characteristic period of the electroencephalogram; dividing the electroencephalogram into a plurality of segmented electroencephalograms according to the waveform feature period; comparing each segmented electroencephalogram of the plurality of segmented electroencephalograms with an electroencephalogram template of the electroencephalogram template library to obtain an electroencephalogram template matching each segmented electroencephalogram; determining an electroencephalogram template with the highest repetition degree in a plurality of electroencephalogram templates corresponding to the plurality of segmented electroencephalograms; determining the concentration degree, the tension degree and the excitement degree corresponding to the electroencephalogram template with the highest repetition degree as the concentration degree, the tension degree and the excitement degree of the user; generating a three-dimensional data model according to the concentration degree, the tension degree and the excitement degree of the user, and determining the three-dimensional data model as the psychological state of the user;
controlling the output device to output instruction information under the condition that the matching degree of the psychological state of the user and the target psychological state model is higher than a threshold value; the instruction information is used for instructing the user to execute a motion action; and the motion type and the target mental state model have a corresponding relation.
5. The method of claim 4, wherein the electronic device further comprises a motion capture sensor;
the method further comprises the following steps:
controlling the motion capture sensor to acquire attitude information of the user during the motion preparation motion;
when the matching degree of the psychological state of the user and the target psychological state model is higher than a threshold value, the control of the output device to output instruction information comprises the following steps:
determining whether the movement preparation action meets a preset action requirement or not according to the attitude information;
and controlling the output device to output the instruction information under the condition that the matching degree of the psychological state of the user and the target psychological state model is higher than the threshold value and the motion preparation motion meets the preset motion requirement.
6. The method of claim 4, wherein the electronic device further comprises a data transmission module;
the method comprises the following steps:
controlling the data transmission module to receive posture information fed back by the intelligent wearable device when the user performs the motion preparation action;
when the matching degree of the psychological state of the user and the target psychological state model is higher than a threshold value, the control of the output device to output instruction information comprises the following steps:
determining whether the movement preparation action meets a preset action requirement or not according to the attitude information;
and controlling the output device to output the instruction information under the condition that the matching degree of the psychological state of the user and the target psychological state model is higher than the threshold value and the motion preparation motion meets the preset motion requirement.
7. A movement assistance apparatus characterized by being applied to an electronic apparatus including a brain wave sensor, a memory, a processor, and an output apparatus, the movement assistance apparatus including an acquisition unit, a determination unit, and an output unit, wherein,
the memory is used for storing more than one mental state model and storing an electroencephalogram template library; wherein the electroencephalogram template library comprises more than one electroencephalogram template and the concentration, the tension and the excitement corresponding to each electroencephalogram template;
the acquisition unit is used for controlling the brain wave sensor to acquire the brain wave signals of the user when the user performs a movement preparation action;
the determining unit is used for determining the motion type of the user according to the posture information; selecting a target mental state model from the more than one mental state models according to the motion type; generating an electroencephalogram of the user from the brain wave signals; determining a waveform characteristic period of the electroencephalogram; dividing the electroencephalogram into a plurality of segmented electroencephalograms according to the waveform feature period; comparing each segmented electroencephalogram of the plurality of segmented electroencephalograms with an electroencephalogram template of the electroencephalogram template library to obtain an electroencephalogram template matching each segmented electroencephalogram; determining an electroencephalogram template with the highest repetition degree in a plurality of electroencephalogram templates corresponding to the plurality of segmented electroencephalograms; determining the concentration degree, the tension degree and the excitement degree corresponding to the electroencephalogram template with the highest repetition degree as the concentration degree, the tension degree and the excitement degree of the user; generating a three-dimensional data model according to the concentration degree, the tension degree and the excitement degree of the user, and determining the three-dimensional data model as the psychological state of the user;
the output unit is used for controlling the output device to output instruction information under the condition that the matching degree of the psychological state of the user and the target psychological state model is higher than a threshold value; the instruction information is used for instructing the user to execute a motion action; and the motion type and the target mental state model have a corresponding relation.
8. An electronic device comprising a processor, a memory, a communication interface, and one or more programs stored in the memory and configured to be executed by the processor, the programs comprising instructions for performing the steps in the method of any of claims 4-6.
9. A computer-readable storage medium, characterized in that a computer program for electronic data exchange is stored, wherein the computer program causes a computer to perform the method according to any of the claims 4-6.
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