WO2022100597A1 - 动作自适应评价方法、电子设备和存储介质 - Google Patents

动作自适应评价方法、电子设备和存储介质 Download PDF

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Publication number
WO2022100597A1
WO2022100597A1 PCT/CN2021/129715 CN2021129715W WO2022100597A1 WO 2022100597 A1 WO2022100597 A1 WO 2022100597A1 CN 2021129715 W CN2021129715 W CN 2021129715W WO 2022100597 A1 WO2022100597 A1 WO 2022100597A1
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Prior art keywords
evaluation
user
action
parameters
electronic device
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PCT/CN2021/129715
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English (en)
French (fr)
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严家兵
刘航
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华为技术有限公司
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Priority to US18/252,632 priority Critical patent/US20230402150A1/en
Priority to EP21891117.0A priority patent/EP4224485A4/en
Publication of WO2022100597A1 publication Critical patent/WO2022100597A1/zh

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    • G—PHYSICS
    • G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
    • G16H—HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
    • G16H20/00—ICT specially adapted for therapies or health-improving plans, e.g. for handling prescriptions, for steering therapy or for monitoring patient compliance
    • G16H20/30—ICT specially adapted for therapies or health-improving plans, e.g. for handling prescriptions, for steering therapy or for monitoring patient compliance relating to physical therapies or activities, e.g. physiotherapy, acupressure or exercising
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
    • G06F16/20—Information retrieval; Database structures therefor; File system structures therefor of structured data, e.g. relational data
    • G06F16/27—Replication, distribution or synchronisation of data between databases or within a distributed database system; Distributed database system architectures therefor
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
    • G06V40/00—Recognition of biometric, human-related or animal-related patterns in image or video data
    • G06V40/20—Movements or behaviour, e.g. gesture recognition
    • G06V40/23—Recognition of whole body movements, e.g. for sport training
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
    • H04N23/00—Cameras or camera modules comprising electronic image sensors; Control thereof
    • H04N23/60—Control of cameras or camera modules
    • H04N23/64—Computer-aided capture of images, e.g. transfer from script file into camera, check of taken image quality, advice or proposal for image composition or decision on when to take image
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
    • H04N23/00—Cameras or camera modules comprising electronic image sensors; Control thereof
    • H04N23/90—Arrangement of cameras or camera modules, e.g. multiple cameras in TV studios or sports stadiums
    • G—PHYSICS
    • G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
    • G16H—HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
    • G16H40/00—ICT specially adapted for the management or administration of healthcare resources or facilities; ICT specially adapted for the management or operation of medical equipment or devices
    • G16H40/60—ICT specially adapted for the management or administration of healthcare resources or facilities; ICT specially adapted for the management or operation of medical equipment or devices for the operation of medical equipment or devices
    • G16H40/63—ICT specially adapted for the management or administration of healthcare resources or facilities; ICT specially adapted for the management or operation of medical equipment or devices for the operation of medical equipment or devices for local operation
    • G—PHYSICS
    • G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
    • G16H—HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
    • G16H40/00—ICT specially adapted for the management or administration of healthcare resources or facilities; ICT specially adapted for the management or operation of medical equipment or devices
    • G16H40/60—ICT specially adapted for the management or administration of healthcare resources or facilities; ICT specially adapted for the management or operation of medical equipment or devices for the operation of medical equipment or devices
    • G16H40/67—ICT specially adapted for the management or administration of healthcare resources or facilities; ICT specially adapted for the management or operation of medical equipment or devices for the operation of medical equipment or devices for remote operation
    • G—PHYSICS
    • G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
    • G16H—HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
    • G16H50/00—ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics
    • G16H50/20—ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for computer-aided diagnosis, e.g. based on medical expert systems
    • G—PHYSICS
    • G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
    • G16H—HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
    • G16H50/00—ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics
    • G16H50/30—ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for calculating health indices; for individual health risk assessment

Definitions

  • the present application relates to the field of sports health, and in particular, to a motion adaptive evaluation method, electronic device and storage medium.
  • the embodiments of the present application provide an action-adaptive evaluation method, an electronic device, and a storage medium, so as to solve the problem that the current intelligent motion cannot guide the user's motion in a targeted manner.
  • an embodiment of the present application provides an action-adaptive evaluation method.
  • a first evaluation threshold with a preliminary reference to the user's physical condition is obtained by using the basic information parameters of the user, so as to target the physical conditions of different users.
  • Set different evaluation thresholds to initially distinguish the user's action evaluation; then, it will also reflect the user's current exercise specific conditions in real time according to the user's key evaluation parameters during the current exercise (such as the key angle of action completion, duration, etc.) , and make an evaluation, and adjust the first evaluation threshold in real time according to the evaluation result, so that the first evaluation threshold can be adjusted in real time according to the completion of user actions, so as to achieve a more targeted user guidance effect.
  • the basic information parameters mentioned above may specifically include the user's basic physical parameters, exercise purpose and previous training experience, or parameters obtained by the user through physical fitness evaluation. Understandably, the basic information parameter reflects the basic information of the user, and by understanding the basic information, important evaluation criteria can be provided for setting the first evaluation threshold, and evaluation thresholds of different users can be preliminarily distinguished.
  • the user may also include a warm-up phase before the actual exercise.
  • the user's physical condition may be further understood to pre-adjust the first evaluation threshold.
  • warm-up actions can be set in a targeted manner to determine how well the user has completed these warm-up actions, and the higher the level, the better the physical condition of the user. Understandably, the evaluation of the quality of the warm-up action can be determined by the evaluation parameters of the warm-up action (such as the completion angle and duration of the warm-up action), etc. Adjustment.
  • the pre-adjustment step of the first evaluation threshold value in the warm-up phase can more accurately distinguish the difference between users, and can more specifically designate the user's scientific exercise.
  • the basic parameter information input by the user can be acquired through the parameter input area preset on the TV interface. Understandably, that is, the user can input the basic information parameters of the user to the TV in an active input manner.
  • the user can also use a cloud server or electronic device (such as a weight scale for measuring body fat rate, a smart bracelet for measuring heart rate, etc.)
  • the method of initiating an invocation request of basic information parameters is to receive the basic information parameters sent by the cloud or electronic device of the associated account. Compared with the method of user's active input, the method of obtaining basic parameter information by using the cloud server or electronic device associated with other accounts is more efficient, and its accuracy is also guaranteed.
  • the first evaluation threshold is calculated according to the basic information parameters, and is used to provide evaluation criteria.
  • the first evaluation threshold may be calculated by using a preset algorithm.
  • an optional implementation is to first classify the basic information parameters according to preset parameter classification standards, such as basic physical parameters, exercise purposes and previous training experience;
  • the basic information parameters are given the first weight, and the evaluation result of the category is obtained by weighted calculation according to the basic information parameters in the same category.
  • the basic body parameters can be divided into multiple parameters, and each parameter in the same category is given the first weight, The evaluation result of the basic body parameter type can be obtained through weighted calculation; finally, a second weight is assigned to the basic information parameters of different categories, and the first evaluation threshold is obtained by weighting according to the evaluation results of different categories.
  • a second weight is assigned to the basic information parameters of different categories, and the first evaluation threshold can be obtained by weighted calculation.
  • a corresponding monitoring module can be activated according to the type of the key evaluation parameters of the user's current exercise action, and the monitoring module can be used to obtain the key evaluation parameters of the current user action.
  • the TV will judge the type of the key evaluation parameter of the current action; if the type of the key evaluation parameter is the action angle, start the camera module, and use the camera module to obtain the action angle of the current action ; If the type of the key evaluation parameter is duration, start the camera module and the timing module, and use the camera module and the timing module to obtain the duration of the current action.
  • the user's action is determined to complete the evaluation.
  • the evaluation of the action can be completed by using a preset evaluation table.
  • the classification type of the basic information parameter the basic information stored in the evaluation table is used.
  • the mapping information between the parameter and the action completion evaluation, and the first evaluation threshold, determine the user's action completion evaluation.
  • the user can adjust the first evaluation threshold in real time according to the action completion evaluation in the exercise stage, and specifically, the preset threshold adjustment conditions can be used for judgment. If the threshold adjustment condition is reached, the first evaluation threshold is adjusted according to the threshold adjustment condition. Understandably, with the progress of the user's movement, the user's actions may become more and more standard, or the opposite is possible. Targeted guidance of users to exercise.
  • embodiments of the present application provide an electronic device with a screen, including a memory, a processor, and a computer program stored in the memory and executable on the processor, where the processor executes the The computer program implements the following steps:
  • the basic information parameters mentioned above may specifically include the user's basic physical parameters, exercise purpose and previous training experience, or parameters obtained by the user through physical fitness evaluation. Understandably, the basic information parameter reflects the basic information of the user, and by understanding the basic information, important evaluation criteria can be provided for setting the first evaluation threshold, and evaluation thresholds of different users can be preliminarily distinguished.
  • the user may also include a warm-up phase before the actual exercise.
  • the user's physical condition may be further understood to pre-adjust the first evaluation threshold.
  • warm-up actions can be set in a targeted manner to determine how well the user has completed these warm-up actions, and the higher the level, the better the physical condition of the user. Understandably, the evaluation of the quality of the warm-up action can be determined by the evaluation parameters of the warm-up action (such as the completion angle and duration of the warm-up action), etc. Adjustment.
  • the pre-adjustment step of the first evaluation threshold value in the warm-up phase can more accurately distinguish the difference between users, and can more specifically designate the user's scientific exercise.
  • the basic parameter information input by the user can be acquired through the parameter input area preset on the TV interface. Understandably, that is, the user can input the basic information parameters of the user to the TV in an active input manner.
  • the user can also use a cloud server or electronic device (such as a weight scale for measuring body fat rate, a smart bracelet for measuring heart rate, etc.)
  • the method of initiating an invocation request of basic information parameters is to receive the basic information parameters sent by the cloud or electronic device of the associated account.
  • the method of obtaining basic parameter information by using the cloud server or electronic device associated with other accounts is more efficient than the method of user's active input, and its accuracy is also guaranteed.
  • the first evaluation threshold is calculated according to the basic information parameters, and is used to provide evaluation criteria.
  • the first evaluation threshold may be calculated by using a preset algorithm.
  • an optional implementation is to first classify the basic information parameters according to preset parameter classification standards, such as basic physical parameters, exercise purposes and previous training experience;
  • the basic information parameters are given the first weight, and the evaluation result of the category is obtained by weighted calculation according to the basic information parameters in the same category.
  • the basic body parameters can be divided into multiple parameters, and each parameter in the same category is given the first weight, The evaluation result of the basic body parameter type can be obtained through weighted calculation; finally, a second weight is assigned to the basic information parameters of different categories, and the first evaluation threshold is obtained by weighting according to the evaluation results of different categories.
  • a second weight is assigned to the basic information parameters of different categories, and the first evaluation threshold can be obtained by weighted calculation.
  • a corresponding monitoring module can be activated according to the type of the key evaluation parameters of the user's current exercise action, and the monitoring module can be used to obtain the key evaluation parameters of the current user action.
  • the TV will judge the type of the key evaluation parameter of the current action; if the type of the key evaluation parameter is the action angle, start the camera module, and use the camera module to obtain the action angle of the current action ; If the type of the key evaluation parameter is duration, start the camera module and the timing module, and use the camera module and the timing module to obtain the duration of the current action.
  • the user's action is determined to complete the evaluation.
  • the evaluation of the action can be completed by using a preset evaluation table.
  • the classification type of the basic information parameter the basic information stored in the evaluation table is used.
  • the mapping information between the parameter and the action completion evaluation, and the first evaluation threshold, determine the user's action completion evaluation.
  • the user can adjust the first evaluation threshold in real time according to the action completion evaluation in the exercise stage, and specifically, the preset threshold adjustment conditions can be used for judgment. If the threshold adjustment condition is reached, the first evaluation threshold is adjusted according to the threshold adjustment condition. Understandably, with the progress of the user's movement, the user's actions may become more and more standard, or the opposite is possible. Targeted guidance of users to exercise.
  • an embodiment of the present application provides a computer-readable storage medium, including a computer program, and when the computer program is executed by a processor, the steps of the method described in the foregoing first aspect are implemented.
  • the first evaluation threshold is set by acquiring the basic information parameters of the user, and more reasonable evaluation criteria can be set according to the physical conditions of different users; when the user is exercising, the key evaluation parameters of the current user action are acquired by acquiring , and the set first evaluation threshold to determine the user's action completion evaluation, so as to flexibly adjust the first evaluation threshold according to the actual completion of the user's action.
  • differentiated exercise services can be provided to the user, so that the user can perform targeted physical exercise, and the physical fitness of the user can be effectively improved.
  • FIG. 1 is a schematic structural diagram of an electronic device provided by an embodiment of the present application.
  • Fig. 2 is a software structural block diagram of an electronic device provided by an embodiment of the present application.
  • FIG. 3 a is a schematic diagram of information input through interaction of a TV interface provided by an embodiment of the present application.
  • Figure 3b is a schematic diagram of yet another implementation of information input through TV interface interaction provided by an embodiment of the present application.
  • FIG. 3c is a schematic diagram of physical fitness assessment through TV interface interaction provided by an embodiment of the present application.
  • FIG. 4a is a schematic diagram of inputting basic physical parameters of a user through a TV interface provided by an embodiment of the present application
  • FIG. 4b is a schematic diagram showing a connectable smart bracelet on a TV interface according to an embodiment of the present application
  • 4c is a schematic diagram of prompting a user to use a connected smart bracelet for heart rate measurement operation on a TV interface provided by an embodiment of the present application;
  • Figure 4d is a schematic diagram of inputting the user's exercise purpose through a TV interface
  • 4e is a schematic diagram of inputting a user's previous training experience through a TV interface provided by an embodiment of the present application
  • 4f is a schematic diagram of selecting a training item through an interface provided by an embodiment of the present application.
  • 4g is another schematic diagram of selecting a training item through an interface provided by an embodiment of the present application.
  • FIG. 5 is a schematic diagram of entering a warm-up scene through a TV interface provided by an embodiment of the present application
  • FIG. 6a is a schematic diagram of instructing a user to do a warm-up action provided by an embodiment of the present application
  • Fig. 6b is another schematic diagram of instructing a user to do a warm-up action provided by an embodiment of the present application
  • Fig. 7a is a schematic diagram of using a multi-camera device to identify the tilt angle of a user when performing a head stretching warm-up action provided by an embodiment of the present application;
  • 7b is another schematic diagram of using a multi-camera device to identify the inclination angle of a user when performing a head stretching warm-up action provided by an embodiment of the present application;
  • FIG. 8a is a schematic diagram of an action correction reminder message provided by an embodiment of the present application.
  • 8b is a schematic diagram of another action correction reminder message provided by an embodiment of the present application.
  • 8c is a schematic diagram of another action correction reminder message provided by an embodiment of the present application.
  • 9a is a schematic interface diagram of an adaptive iterative action evaluation standard provided by an embodiment of the present application.
  • FIG. 9b is a schematic interface diagram of another adaptive iterative action evaluation standard provided by an embodiment of the present application.
  • first and second are only used for descriptive purposes, and should not be construed as indicating or implying relative importance or implicitly indicating the number of indicated technical features.
  • a feature defined as “first” or “second” may expressly or implicitly include one or more of that feature.
  • plural means two or more.
  • words such as “exemplary” or “for example” are used to represent examples, illustrations or illustrations. Any embodiments or designs described in the embodiments of the present application as “exemplary” or “such as” should not be construed as preferred or advantageous over other embodiments or designs. Rather, the use of words such as “exemplary” or “such as” is intended to present the related concepts in a specific manner.
  • FIG. 1 shows a schematic structural diagram of an electronic device 100 .
  • the electronic device 100 may include a processor 110, an external memory interface 120, an internal memory 121, a universal serial bus (USB) interface 130, a charge management module 140, a power management module 141, a battery 142, an antenna 1, an antenna 2 , mobile communication module 150, wireless communication module 160, audio module 170, speaker 170A, receiver 170B, microphone 170C, headphone jack 170D, sensor module 180, buttons 190, motor 191, indicator 192, camera 193, display screen 194, and Subscriber identification module (subscriber identification module, SIM) card interface 195 and so on.
  • SIM Subscriber identification module
  • the sensor module 180 may include a pressure sensor 180A, a gyroscope sensor 180B, an air pressure sensor 180C, a magnetic sensor 180D, an acceleration sensor 180E, a distance sensor 180F, a proximity light sensor 180G, a fingerprint sensor 180H, a temperature sensor 180J, a touch sensor 180K, and ambient light. Sensor 180L, bone conduction sensor 180M, etc.
  • the structures illustrated in the embodiments of the present application do not constitute a specific limitation on the electronic device 100 .
  • the electronic device 100 may include more or less components than shown, or combine some components, or separate some components, or arrange different components.
  • the illustrated components may be implemented in hardware, software, or a combination of software and hardware.
  • the processor 110 may include one or more processing units, for example, the processor 110 may include an application processor (application processor, AP), a modem processor, a graphics processor (graphics processing unit, GPU), an image signal processor (image signal processor, ISP), controller, video codec, digital signal processor (digital signal processor, DSP), baseband processor, and/or neural-network processing unit (neural-network processing unit, NPU), etc. Wherein, different processing units may be independent devices, or may be integrated in one or more processors.
  • application processor application processor, AP
  • modem processor graphics processor
  • ISP image signal processor
  • controller video codec
  • digital signal processor digital signal processor
  • baseband processor baseband processor
  • neural-network processing unit neural-network processing unit
  • the controller can generate an operation control signal according to the instruction operation code and timing signal, and complete the control of fetching and executing instructions.
  • a memory may also be provided in the processor 110 for storing instructions and data.
  • the memory in processor 110 is cache memory. This memory may hold instructions or data that have just been used or recycled by the processor 110 . If the processor 110 needs to use the instruction or data again, it can be called directly from the memory. Repeated accesses are avoided and the latency of the processor 110 is reduced, thereby increasing the efficiency of the system.
  • the processor 110 may include one or more interfaces.
  • the interface may include an integrated circuit (inter-integrated circuit, I2C) interface, an integrated circuit built-in audio (inter-integrated circuit sound, I2S) interface, a pulse code modulation (pulse code modulation, PCM) interface, a universal asynchronous transceiver (universal asynchronous transmitter) receiver/transmitter, UART) interface, mobile industry processor interface (MIPI), general-purpose input/output (GPIO) interface, subscriber identity module (SIM) interface, and / or universal serial bus (universal serial bus, USB) interface, etc.
  • I2C integrated circuit
  • I2S integrated circuit built-in audio
  • PCM pulse code modulation
  • PCM pulse code modulation
  • UART universal asynchronous transceiver
  • MIPI mobile industry processor interface
  • GPIO general-purpose input/output
  • SIM subscriber identity module
  • USB universal serial bus
  • the I2C interface is a bidirectional synchronous serial bus consisting of a serial data line (SDA) and a serial clock line (SCL).
  • the processor 110 may contain multiple sets of I2C buses.
  • the processor 110 can be respectively coupled to the touch sensor 180K, the charger, the flash, the camera 193 and the like through different I2C bus interfaces.
  • the processor 110 may couple the touch sensor 180K through the I2C interface, so that the processor 110 and the touch sensor 180K communicate with each other through the I2C bus interface, so as to realize the touch function of the electronic device 100 .
  • the I2S interface can be used for audio communication.
  • the processor 110 may contain multiple sets of I2S buses.
  • the processor 110 may be coupled with the audio module 170 through an I2S bus to implement communication between the processor 110 and the audio module 170 .
  • the audio module 170 can transmit audio signals to the wireless communication module 160 through the I2S interface, so as to realize the function of answering calls through a Bluetooth headset.
  • the PCM interface can also be used for audio communications, sampling, quantizing and encoding analog signals.
  • the audio module 170 and the wireless communication module 160 may be coupled through a PCM bus interface.
  • the audio module 170 can also transmit audio signals to the wireless communication module 160 through the PCM interface, so as to realize the function of answering calls through the Bluetooth headset. Both the I2S interface and the PCM interface can be used for audio communication.
  • the UART interface is a universal serial data bus used for asynchronous communication.
  • the bus may be a bidirectional communication bus. It converts the data to be transmitted between serial communication and parallel communication.
  • a UART interface is typically used to connect the processor 110 with the wireless communication module 160 .
  • the processor 110 communicates with the Bluetooth module in the wireless communication module 160 through the UART interface to implement the Bluetooth function.
  • the audio module 170 can transmit audio signals to the wireless communication module 160 through the UART interface, so as to realize the function of playing music through the Bluetooth headset.
  • the MIPI interface can be used to connect the processor 110 with peripheral devices such as the display screen 194 and the camera 193 .
  • MIPI interfaces include camera serial interface (CSI), display serial interface (DSI), etc.
  • the processor 110 communicates with the camera 193 through a CSI interface, so as to realize the photographing function of the electronic device 100 .
  • the processor 110 communicates with the display screen 194 through the DSI interface to implement the display function of the electronic device 100 .
  • the GPIO interface can be configured by software.
  • the GPIO interface can be configured as a control signal or as a data signal.
  • the GPIO interface may be used to connect the processor 110 with the camera 193, the display screen 194, the wireless communication module 160, the audio module 170, the sensor module 180, and the like.
  • the GPIO interface can also be configured as I2C interface, I2S interface, UART interface, MIPI interface, etc.
  • the USB interface 130 is an interface that conforms to the USB standard specification, and may specifically be a Mini USB interface, a Micro USB interface, a USB Type C interface, and the like.
  • the USB interface 130 can be used to connect a charger to charge the electronic device 100, and can also be used to transmit data between the electronic device 100 and peripheral devices. It can also be used to connect headphones to play audio through the headphones.
  • the interface can also be used to connect other electronic devices, such as AR devices.
  • the interface connection relationship between the modules illustrated in the embodiments of the present application is only a schematic illustration, and does not constitute a structural limitation of the electronic device 100 .
  • the electronic device 100 may also adopt different interface connection manners in the foregoing embodiments, or a combination of multiple interface connection manners.
  • the charging management module 140 is used to receive charging input from the charger.
  • the charger may be a wireless charger or a wired charger.
  • the charging management module 140 may receive charging input from the wired charger through the USB interface 130 .
  • the charging management module 140 may receive wireless charging input through a wireless charging coil of the electronic device 100 . While the charging management module 140 charges the battery 142 , it can also supply power to the electronic device through the power management module 141 .
  • the power management module 141 is used for connecting the battery 142 , the charging management module 140 and the processor 110 .
  • the power management module 141 receives input from the battery 142 and/or the charge management module 140, and supplies power to the processor 110, the internal memory 121, the display screen 194, the camera 193, and the wireless communication module 160.
  • the power management module 141 can also be used to monitor parameters such as battery capacity, battery cycle times, battery health status (leakage, impedance).
  • the power management module 141 may also be provided in the processor 110 .
  • the power management module 141 and the charging management module 140 may also be provided in the same device.
  • the wireless communication function of the electronic device 100 may be implemented by the antenna 1, the antenna 2, the mobile communication module 150, the wireless communication module 160, the modulation and demodulation processor, the baseband processor, and the like.
  • Antenna 1 and Antenna 2 are used to transmit and receive electromagnetic wave signals.
  • Each antenna in electronic device 100 may be used to cover a single or multiple communication frequency bands. Different antennas can also be reused to improve antenna utilization.
  • the antenna 1 can be multiplexed as a diversity antenna of the wireless local area network. In other embodiments, the antenna may be used in conjunction with a tuning switch.
  • the mobile communication module 150 may provide wireless communication solutions including 2G/3G/4G/5G etc. applied on the electronic device 100 .
  • the mobile communication module 150 may include at least one filter, switch, power amplifier, low noise amplifier (LNA) and the like.
  • the mobile communication module 150 can receive electromagnetic waves from the antenna 1, filter and amplify the received electromagnetic waves, and transmit them to the modulation and demodulation processor for demodulation.
  • the mobile communication module 150 can also amplify the signal modulated by the modulation and demodulation processor, and then turn it into an electromagnetic wave for radiation through the antenna 1 .
  • at least part of the functional modules of the mobile communication module 150 may be provided in the processor 110 .
  • at least part of the functional modules of the mobile communication module 150 may be provided in the same device as at least part of the modules of the processor 110 .
  • the modem processor may include a modulator and a demodulator.
  • the modulator is used to modulate the low frequency baseband signal to be sent into a medium and high frequency signal.
  • the demodulator is used to demodulate the received electromagnetic wave signal into a low frequency baseband signal. Then the demodulator transmits the demodulated low-frequency baseband signal to the baseband processor for processing.
  • the low frequency baseband signal is processed by the baseband processor and passed to the application processor.
  • the application processor outputs sound signals through audio devices (not limited to the speaker 170A, the receiver 170B, etc.), or displays images or videos through the display screen 194 .
  • the modem processor may be a stand-alone device.
  • the modem processor may be independent of the processor 110, and may be provided in the same device as the mobile communication module 150 or other functional modules.
  • the wireless communication module 160 can provide applications on the electronic device 100 including wireless local area networks (WLAN) (such as wireless fidelity (Wi-Fi) networks), bluetooth (BT), global navigation satellites Wireless communication solutions such as global navigation satellite system (GNSS), frequency modulation (FM), near field communication (NFC), and infrared technology (IR).
  • WLAN wireless local area networks
  • BT Bluetooth
  • GNSS global navigation satellite system
  • FM frequency modulation
  • NFC near field communication
  • IR infrared technology
  • the wireless communication module 160 may be one or more devices integrating at least one communication processing module.
  • the wireless communication module 160 receives electromagnetic waves via the antenna 2 , frequency modulates and filters the electromagnetic wave signals, and sends the processed signals to the processor 110 .
  • the wireless communication module 160 can also receive the signal to be sent from the processor 110 , perform frequency modulation on it, amplify it, and convert it into electromagnetic waves for radiation through the antenna 2 .
  • the antenna 1 of the electronic device 100 is coupled with the mobile communication module 150, and the antenna 2 is coupled with the wireless communication module 160, so that the electronic device 100 can communicate with the network and other devices through wireless communication technology.
  • the wireless communication technology may include global system for mobile communications (GSM), general packet radio service (GPRS), code division multiple access (CDMA), broadband Code Division Multiple Access (WCDMA), Time Division Code Division Multiple Access (TD-SCDMA), Long Term Evolution (LTE), BT, GNSS, WLAN, NFC , FM, and/or IR technology, etc.
  • the GNSS may include global positioning system (global positioning system, GPS), global navigation satellite system (global navigation satellite system, GLONASS), Beidou navigation satellite system (beidou navigation satellite system, BDS), quasi-zenith satellite system (quasi satellite system) -zenith satellite system, QZSS) and/or satellite based augmentation systems (SBAS).
  • global positioning system global positioning system, GPS
  • global navigation satellite system global navigation satellite system, GLONASS
  • Beidou navigation satellite system beidou navigation satellite system, BDS
  • quasi-zenith satellite system quadsi satellite system
  • QZSS quasi-zenith satellite system
  • SBAS satellite based augmentation systems
  • the electronic device 100 implements a display function through a GPU, a display screen 194, an application processor, and the like.
  • the GPU is a microprocessor for image processing, and is connected to the display screen 194 and the application processor.
  • the GPU is used to perform mathematical and geometric calculations for graphics rendering.
  • Processor 110 may include one or more GPUs that execute program instructions to generate or alter display information.
  • Display screen 194 is used to display images, videos, and the like.
  • Display screen 194 includes a display panel.
  • the display panel can be a liquid crystal display (LCD), an organic light-emitting diode (OLED), an active-matrix organic light-emitting diode or an active-matrix organic light-emitting diode (active-matrix organic light).
  • LED diode AMOLED
  • flexible light-emitting diode flexible light-emitting diode (flex light-emitting diode, FLED), Miniled, MicroLed, Micro-oLed, quantum dot light-emitting diode (quantum dot light emitting diodes, QLED) and so on.
  • the electronic device 100 may include one or N display screens 194 , where N is a positive integer greater than one.
  • the electronic device 100 may implement a shooting function through an ISP, a camera 193, a video codec, a GPU, a display screen 194, an application processor, and the like.
  • the ISP is used to process the data fed back by the camera 193 .
  • the shutter is opened, the light is transmitted to the camera photosensitive element through the lens, the light signal is converted into an electrical signal, and the camera photosensitive element transmits the electrical signal to the ISP for processing, and converts it into an image visible to the naked eye.
  • ISP can also perform algorithm optimization on image noise, brightness, and skin tone.
  • ISP can also optimize the exposure, color temperature and other parameters of the shooting scene.
  • the ISP may be provided in the camera 193 .
  • Camera 193 is used to capture still images or video.
  • the object is projected through the lens to generate an optical image onto the photosensitive element.
  • the photosensitive element may be a charge coupled device (CCD) or a complementary metal-oxide-semiconductor (CMOS) phototransistor.
  • CMOS complementary metal-oxide-semiconductor
  • the photosensitive element converts the optical signal into an electrical signal, and then transmits the electrical signal to the ISP to convert it into a digital image signal.
  • the ISP outputs the digital image signal to the DSP for processing.
  • DSP converts digital image signals into standard RGB, YUV and other formats of image signals.
  • the electronic device 100 may include 1 or N cameras 193 , where N is a positive integer greater than 1.
  • a digital signal processor is used to process digital signals, in addition to processing digital image signals, it can also process other digital signals. For example, when the electronic device 100 selects a frequency point, the digital signal processor is used to perform Fourier transform on the frequency point energy and so on.
  • Video codecs are used to compress or decompress digital video.
  • the electronic device 100 may support one or more video codecs.
  • the electronic device 100 can play or record videos of various encoding formats, such as: Moving Picture Experts Group (moving picture experts group, MPEG) 1, MPEG2, MPEG3, MPEG4 and so on.
  • MPEG Moving Picture Experts Group
  • MPEG2 moving picture experts group
  • MPEG3 MPEG4
  • MPEG4 Moving Picture Experts Group
  • the NPU is a neural-network (NN) computing processor.
  • NN neural-network
  • Applications such as intelligent cognition of the electronic device 100 can be implemented through the NPU, such as image recognition, face recognition, speech recognition, text understanding, and the like.
  • the external memory interface 120 can be used to connect an external memory card, such as a Micro SD card, to expand the storage capacity of the electronic device 100 .
  • the external memory card communicates with the processor 110 through the external memory interface 120 to realize the data storage function. For example to save files like music, video etc in external memory card.
  • Internal memory 121 may be used to store computer executable program code, which includes instructions.
  • the internal memory 121 may include a storage program area and a storage data area.
  • the storage program area can store an operating system, an application program required for at least one function (such as a sound playback function, an image playback function, etc.), and the like.
  • the storage data area may store data (such as audio data, phone book, etc.) created during the use of the electronic device 100 and the like.
  • the internal memory 121 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, universal flash storage (UFS), and the like.
  • the processor 110 executes various functional applications and data processing of the electronic device 100 by executing instructions stored in the internal memory 121 and/or instructions stored in a memory provided in the processor.
  • the electronic device 100 may implement audio functions through an audio module 170, a speaker 170A, a receiver 170B, a microphone 170C, an earphone interface 170D, an application processor, and the like. Such as music playback, recording, etc.
  • the audio module 170 is used for converting digital audio information into analog audio signal output, and also for converting analog audio input into digital audio signal. Audio module 170 may also be used to encode and decode audio signals. In some embodiments, the audio module 170 may be provided in the processor 110 , or some functional modules of the audio module 170 may be provided in the processor 110 .
  • Speaker 170A also referred to as a "speaker" is used to convert audio electrical signals into sound signals.
  • the electronic device 100 can listen to music through the speaker 170A, or listen to a hands-free call.
  • the receiver 170B also referred to as "earpiece" is used to convert audio electrical signals into sound signals.
  • the voice can be answered by placing the receiver 170B close to the human ear.
  • the microphone 170C also called “microphone” or “microphone” is used to convert sound signals into electrical signals.
  • the user can make a sound by approaching the microphone 170C through a human mouth, and input the sound signal into the microphone 170C.
  • the electronic device 100 may be provided with at least one microphone 170C. In other embodiments, the electronic device 100 may be provided with two microphones 170C, which can implement a noise reduction function in addition to collecting sound signals. In other embodiments, the electronic device 100 may further be provided with three, four or more microphones 170C to collect sound signals, reduce noise, identify sound sources, and implement directional recording functions.
  • the earphone jack 170D is used to connect wired earphones.
  • the earphone interface 170D may be the USB interface 130, or may be a 3.5mm open mobile terminal platform (OMTP) standard interface, a cellular telecommunications industry association of the USA (CTIA) standard interface.
  • OMTP open mobile terminal platform
  • CTIA cellular telecommunications industry association of the USA
  • the pressure sensor 180A is used to sense pressure signals, and can convert the pressure signals into electrical signals.
  • the pressure sensor 180A may be provided on the display screen 194 .
  • the capacitive pressure sensor may be comprised of at least two parallel plates of conductive material.
  • the electronic device 100 determines the intensity of the pressure according to the change in capacitance.
  • a touch operation acts on the display screen 194
  • the electronic device 100 detects the intensity of the touch operation according to the pressure sensor 180A.
  • the electronic device 100 may also calculate the touched position according to the detection signal of the pressure sensor 180A.
  • touch operations acting on the same touch position but with different touch operation intensities may correspond to different operation instructions.
  • the instruction for viewing the short message is executed.
  • the instruction to create a new short message is executed.
  • the gyro sensor 180B may be used to determine the motion attitude of the electronic device 100 .
  • the angular velocity of electronic device 100 about three axes ie, x, y, and z axes
  • the gyro sensor 180B can be used for image stabilization.
  • the gyro sensor 180B detects the angle at which the electronic device 100 shakes, calculates the distance that the lens module needs to compensate for according to the angle, and allows the lens to counteract the shake of the electronic device 100 through reverse motion to achieve anti-shake.
  • the gyro sensor 180B can also be used for navigation and somatosensory game scenarios.
  • the air pressure sensor 180C is used to measure air pressure.
  • the electronic device 100 calculates the altitude through the air pressure value measured by the air pressure sensor 180C to assist in positioning and navigation.
  • the magnetic sensor 180D includes a Hall sensor.
  • the electronic device 100 can detect the opening and closing of the flip holster using the magnetic sensor 180D.
  • the electronic device 100 can detect the opening and closing of the flip according to the magnetic sensor 180D. Further, according to the detected opening and closing state of the leather case or the opening and closing state of the flip cover, characteristics such as automatic unlocking of the flip cover are set.
  • the acceleration sensor 180E can detect the magnitude of the acceleration of the electronic device 100 in various directions (generally three axes).
  • the magnitude and direction of gravity can be detected when the electronic device 100 is stationary. It can also be used to identify the posture of electronic devices, and can be used in applications such as horizontal and vertical screen switching, pedometers, etc.
  • the electronic device 100 can measure the distance through infrared or laser. In some embodiments, when shooting a scene, the electronic device 100 can use the distance sensor 180F to measure the distance to achieve fast focusing.
  • Proximity light sensor 180G may include, for example, light emitting diodes (LEDs) and light detectors, such as photodiodes.
  • the light emitting diodes may be infrared light emitting diodes.
  • the electronic device 100 emits infrared light to the outside through the light emitting diode.
  • Electronic device 100 uses photodiodes to detect infrared reflected light from nearby objects. When sufficient reflected light is detected, it can be determined that there is an object near the electronic device 100 . When insufficient reflected light is detected, the electronic device 100 may determine that there is no object near the electronic device 100 .
  • the electronic device 100 can use the proximity light sensor 180G to detect that the user holds the electronic device 100 close to the ear to talk, so as to automatically turn off the screen to save power.
  • Proximity light sensor 180G can also be used in holster mode, pocket mode automatically unlocks and locks the screen.
  • the ambient light sensor 180L is used to sense ambient light brightness.
  • the electronic device 100 can adaptively adjust the brightness of the display screen 194 according to the perceived ambient light brightness.
  • the ambient light sensor 180L can also be used to automatically adjust the white balance when taking pictures.
  • the ambient light sensor 180L can also cooperate with the proximity light sensor 180G to detect whether the electronic device 100 is in a pocket, so as to prevent accidental touch.
  • the fingerprint sensor 180H is used to collect fingerprints.
  • the electronic device 100 can use the collected fingerprint characteristics to realize fingerprint unlocking, accessing application locks, taking pictures with fingerprints, answering incoming calls with fingerprints, and the like.
  • the temperature sensor 180J is used to detect the temperature.
  • the electronic device 100 uses the temperature detected by the temperature sensor 180J to execute a temperature processing strategy. For example, when the temperature reported by the temperature sensor 180J exceeds a threshold value, the electronic device 100 reduces the performance of the processor located near the temperature sensor 180J in order to reduce power consumption and implement thermal protection.
  • the electronic device 100 when the temperature is lower than another threshold, the electronic device 100 heats the battery 142 to avoid abnormal shutdown of the electronic device 100 caused by the low temperature.
  • the electronic device 100 boosts the output voltage of the battery 142 to avoid abnormal shutdown caused by low temperature.
  • Touch sensor 180K also called “touch panel”.
  • the touch sensor 180K may be disposed on the display screen 194 , and the touch sensor 180K and the display screen 194 form a touch screen, also called a “touch screen”.
  • the touch sensor 180K is used to detect a touch operation on or near it.
  • the touch sensor can pass the detected touch operation to the application processor to determine the type of touch event.
  • Visual output related to touch operations may be provided through display screen 194 .
  • the touch sensor 180K may also be disposed on the surface of the electronic device 100 , which is different from the location where the display screen 194 is located.
  • the bone conduction sensor 180M can acquire vibration signals.
  • the bone conduction sensor 180M can acquire the vibration signal of the vibrating bone mass of the human voice.
  • the bone conduction sensor 180M can also contact the pulse of the human body and receive the blood pressure beating signal.
  • the bone conduction sensor 180M can also be disposed in the earphone, combined with the bone conduction earphone.
  • the audio module 170 can analyze the voice signal based on the vibration signal of the vocal vibration bone block obtained by the bone conduction sensor 180M, so as to realize the voice function.
  • the application processor can analyze the heart rate information based on the blood pressure beat signal obtained by the bone conduction sensor 180M, and realize the function of heart rate detection.
  • the keys 190 include a power-on key, a volume key, and the like. Keys 190 may be mechanical keys. It can also be a touch key.
  • the electronic device 100 may receive key inputs and generate key signal inputs related to user settings and function control of the electronic device 100 .
  • Motor 191 can generate vibrating cues.
  • the motor 191 can be used for vibrating alerts for incoming calls, and can also be used for touch vibration feedback.
  • touch operations acting on different applications can correspond to different vibration feedback effects.
  • the motor 191 can also correspond to different vibration feedback effects for touch operations on different areas of the display screen 194 .
  • Different application scenarios for example: time reminder, receiving information, alarm clock, games, etc.
  • the touch vibration feedback effect can also support customization.
  • the indicator 192 can be an indicator light, which can be used to indicate the charging state, the change of the power, and can also be used to indicate a message, a missed call, a notification, and the like.
  • the SIM card interface 195 is used to connect a SIM card.
  • the SIM card can be contacted and separated from the electronic device 100 by inserting into the SIM card interface 195 or pulling out from the SIM card interface 195 .
  • the electronic device 100 may support 1 or N SIM card interfaces, where N is a positive integer greater than 1.
  • the SIM card interface 195 can support Nano SIM card, Micro SIM card, SIM card and so on. Multiple cards can be inserted into the same SIM card interface 195 at the same time. The types of the plurality of cards may be the same or different.
  • the SIM card interface 195 can also be compatible with different types of SIM cards.
  • the SIM card interface 195 is also compatible with external memory cards.
  • the electronic device 100 interacts with the network through the SIM card to implement functions such as call and data communication.
  • the electronic device 100 employs an eSIM, ie: an embedded SIM card.
  • the eSIM card can be embedded in the electronic device 100 and cannot be separated from the electronic device 100 .
  • the software system of the electronic device 100 may adopt a layered architecture, an event-driven architecture, a microkernel architecture, a microservice architecture, or a cloud architecture.
  • the embodiments of the present application take an Android system with a layered architecture as an example to exemplarily describe the software structure of the electronic device 100 .
  • FIG. 2 is a block diagram of the software structure of the electronic device 100 according to the embodiment of the present application.
  • the layered architecture divides the software into several layers, and each layer has a clear role and division of labor. Layers communicate with each other through software interfaces.
  • the Android system is divided into four layers, which are, from top to bottom, an application layer, an application framework layer, an Android runtime (Android runtime) and a system library, and a kernel layer.
  • the application layer can include a series of application packages.
  • the application package can include applications such as camera, gallery, calendar, call, map, navigation, WLAN, Bluetooth, music, video, short message and so on.
  • the application framework layer provides an application programming interface (application programming interface, API) and a programming framework for applications in the application layer.
  • the application framework layer includes some predefined functions.
  • the application framework layer may include window managers, content providers, view systems, telephony managers, resource managers, notification managers, and the like.
  • a window manager is used to manage window programs.
  • the window manager can get the size of the display screen, determine whether there is a status bar, lock the screen, take screenshots, etc.
  • Content providers are used to store and retrieve data and make these data accessible to applications.
  • the data may include video, images, audio, calls made and received, browsing history and bookmarks, phone book, etc.
  • the view system includes visual controls, such as controls for displaying text, controls for displaying pictures, and so on. View systems can be used to build applications.
  • a display interface can consist of one or more views.
  • the display interface including the short message notification icon may include a view for displaying text and a view for displaying pictures.
  • the phone manager is used to provide the communication function of the electronic device 100 .
  • the management of call status including connecting, hanging up, etc.).
  • the resource manager provides various resources for the application, such as localization strings, icons, pictures, layout files, video files and so on.
  • the notification manager enables applications to display notification information in the status bar, which can be used to convey notification-type messages, and can disappear automatically after a brief pause without user interaction. For example, the notification manager is used to notify download completion, message reminders, etc.
  • the notification manager can also display notifications in the status bar at the top of the system in the form of graphs or scroll bar text, such as notifications of applications running in the background, and notifications that appear on the screen in the form of dialog windows. For example, text information is prompted in the status bar, a prompt sound is issued, the electronic device vibrates, and the indicator light flashes.
  • Android Runtime includes core libraries and a virtual machine. Android runtime is responsible for scheduling and management of the Android system.
  • the core library consists of two parts: one is the function functions that the java language needs to call, and the other is the core library of Android.
  • the application layer and the application framework layer run in virtual machines.
  • the virtual machine executes the java files of the application layer and the application framework layer as binary files.
  • the virtual machine is used to perform functions such as object lifecycle management, stack management, thread management, safety and exception management, and garbage collection.
  • a system library can include multiple functional modules. For example: surface manager (surface manager), media library (Media Libraries), 3D graphics processing library (eg: OpenGL ES), 2D graphics engine (eg: SGL), etc.
  • surface manager surface manager
  • media library Media Libraries
  • 3D graphics processing library eg: OpenGL ES
  • 2D graphics engine eg: SGL
  • the Surface Manager is used to manage the display subsystem and provides a fusion of 2D and 3D layers for multiple applications.
  • the media library supports playback and recording of a variety of commonly used audio and video formats, as well as still image files.
  • the media library can support a variety of audio and video encoding formats, such as: MPEG4, H.264, MP3, AAC, AMR, JPG, PNG, etc.
  • the 3D graphics processing library is used to implement 3D graphics drawing, image rendering, compositing, and layer processing.
  • 2D graphics engine is a drawing engine for 2D drawing.
  • the kernel layer is the layer between hardware and software.
  • the kernel layer contains at least display drivers, camera drivers, audio drivers, and sensor drivers.
  • a corresponding hardware interrupt is sent to the kernel layer.
  • the kernel layer processes touch operations into raw input events (including touch coordinates, timestamps of touch operations, etc.). Raw input events are stored at the kernel layer.
  • the application framework layer obtains the original input event from the kernel layer, and identifies the control corresponding to the input event. Taking the touch operation as a touch click operation, and the control corresponding to the click operation is the control of the camera application icon, for example, the camera application calls the interface of the application framework layer to start the camera application, and then starts the camera driver by calling the kernel layer.
  • the camera 193 captures still images or video.
  • the processor 110 of the electronic device 100 executes the executable program code in the internal memory 121, it can implement the steps performed in the action adaptive evaluation method provided by the embodiment of the present application, and the electronic device 100 may be a television.
  • the present application proposes an action-adaptive evaluation method, which can provide users with differentiated services, enable users to perform effective physical exercise, and improve their physical fitness.
  • the user is using a TV (in the embodiment of the present application, the electronic device 100 may specifically refer to a TV, and the TV may also be called a smart screen, which has functions such as intelligent interaction with the user, and is not limited to traditional (for watching videos and other multimedia information.)
  • the first evaluation threshold can be set according to the user's basic physical parameters, exercise purpose, previous training experience, etc.
  • the first evaluation threshold is used to provide an evaluation standard, which can generally reflect information such as the physical fitness and interest direction of the user participating in the exercise.
  • the first evaluation threshold may specifically be a value in the interval [0, 1].
  • the weights corresponding to the three conditions can all be taken as 1/3, and the coefficients can be taken as 1.
  • the first evaluation threshold can be obtained as 100%.
  • the first evaluation threshold of 100% indicates that for the user in the account registration stage, the basic physical parameters, exercise purpose, previous training experience and other information input by the user can know that the user has good physical fitness, often exercise, and expects this exercise to get Better exercise fat loss results, so the user's evaluation criteria will be set to high.
  • the first evaluation threshold is obtained as 60%.
  • the first evaluation threshold of 60% indicates that in the account registration stage, the user can know that the user's physical fitness is average, does not exercise often, and is not interested in this exercise according to the basic physical parameters, exercise purpose, previous training experience and other information input by the user.
  • the user's evaluation standard With an entertainment-oriented training mentality, the user's evaluation standard will be set to a lower level. Understandably, when the user exercises under this lower evaluation standard, it will be easier for the user to complete the current action and move on to the next step, and under this evaluation standard, the feedback of the completion of the action is mostly "" Perfect", or "Awesome". Understandably, in a scenario with a low evaluation standard, the smart sports application on the TV mainly aims to encourage the user to exercise, and does not have high requirements on the user's action completion.
  • the first evaluation threshold can distinguish the physical conditions of different users, and set different evaluation standards for different users.
  • the evaluation standard refers to the standard suitable for different users determined after analyzing the user's basic information parameters. For example, the result obtained after analyzing the user's basic information is 100%, indicating that the user's actions can be evaluated according to the highest standard. The result obtained after analyzing the basic information of the user is 80%, indicating that the current physical state of the user is not suitable for evaluation according to the highest standard, and the user can be evaluated according to 80% of the highest standard. Further, in the process of subsequent exercise, the first evaluation threshold may be adjusted according to the actual completion of the user's action.
  • the user in addition to the questionnaire, can also be required to complete a set of physical fitness assessment actions (such as FMS (Functional movement screen, functional motion detection), etc.) Setting of the first evaluation threshold.
  • FMS evaluation it can be used to detect the user's overall motion control stability, body balance, flexibility, and proprioceptive capabilities. Through FMS evaluation, the user's overall physical profile can be easily identified.
  • using the first evaluation threshold setting for the completion of the physical fitness evaluation action has a higher accuracy than the threshold setting method in which the user inputs basic physical parameters, exercise purpose, previous training experience and other information.
  • the user's basic physical parameters, exercise purpose, previous training experience and other information can be entered through interaction with the TV interface. Specifically, the information to be entered in advance can be guided in a certain order, and the information entry can be realized through interface interaction.
  • Figures 3a and 3b show schematic diagrams of implementing information entry through interaction on a TV interface.
  • the TV interface displays a variety of entry controls (such as buttons, pictures) for inputting information.
  • entry controls such as buttons, pictures
  • the user can enter the phase according to the selected entry control.
  • Corresponding information entry interface Specifically, Fig. 3a adopts a button-type entry control, and the user can select a button option such as a basic body parameter by clicking and other operations, and enter the information input interface of the basic body parameter.
  • Figure 3b uses a clickable picture-type entry control, and the user can select the picture of the previous training experience by clicking and other operation methods, and enter the information input interface of the previous training experience. It can be understood that the implementation manner of the entry control is not specifically limited, as long as the user can achieve the purpose of information input through the interface interaction of the TV.
  • Figure 3c shows a schematic diagram of physical fitness assessment through TV interface interaction.
  • the user in addition to using information input methods such as basic physical parameters, the user can also select physical fitness assessment through the TV interface. Specifically, the user can select a physical fitness evaluation entry through operations such as clicking, and perform physical fitness evaluation.
  • the basic physical parameters of the user may include parameters such as BMI, body fat rate, completion time of running 1,000 kilometers, vital capacity, grip strength, bench press, foot thrust, and the like.
  • the basic body parameter reflects the basic body profile of the user, and has a certain reference significance for the setting of the first evaluation threshold.
  • the setting of the first evaluation threshold may be dynamically adjusted according to actions (one or more groups) selected by the user or recommended by the system. If the user chooses a fat-reducing exercise, BMI, body fat percentage, etc. can be used as items with higher weights, so as to obtain a more accurate evaluation of the user's basic physical parameters (such as excellent, good, and average, etc.). It is understandable that in different action scenarios, the value of the first evaluation threshold will be adjusted dynamically, rather than being fixed.
  • the exercise action recommended by the system may be determined according to the user's exercise purpose.
  • the user's exercise purpose is to exercise to reduce fat
  • the system will mainly recommend actions related to fat reduction.
  • the exercise purpose may also include the user's exercise expectation.
  • the user's exercise expectation may be to obtain sufficient and effective exercise effects, or it may be the exercise expectation of recreational exercise only. It can be understood that the motion expectation can also be used as a weight item to adjust the first evaluation threshold.
  • Fig. 4a shows a schematic diagram of inputting basic body parameters of a user through a TV interface.
  • the user can fill in the basic body parameters by filling in the TV interface. It is understandable that the user does not necessarily know all the basic body parameters of the user, so the relevant basic body information can be automatically filled in by means of real-time input.
  • the user can trigger the connection operation with the device related to the basic body parameter by selecting the button of "real-time acquisition".
  • the TV when the TV detects the user's request for real-time heart rate acquisition, it will search for electronic devices that can measure heart rate, such as a smart bracelet (with a heart rate measurement function), and associate with the device. electronic devices are connected.
  • 4b and 4ab show schematic diagrams of the communication connection between the TV and the smart bracelet.
  • the smart bracelet that can be connected can be displayed on the TV interface. After the user selects the bracelet he wears, as shown in Figure 4c, the user is prompted on the TV interface to use the connected smart bracelet to measure the heart rate.
  • the smart bracelet After the user measures the heart rate through the smart bracelet, the smart bracelet sends the heart rate to the connected TV. After the TV receives the heart rate, it will jump to the interface for entering basic body parameters of the TV, and automatically fill in the heart rate (average value) into the heart rate item on the basic body parameter interface of the TV.
  • the user can also enter the function of basic physical parameters through the associated account.
  • the user can obtain the basic physical parameters of the user through the cloud that has an associated account relationship with the TV by selecting the button of "Associated Acquisition", wherein these basic physical parameters can be associated with the TV.
  • Other electronic devices are uploaded to the cloud.
  • a smart bracelet that has an account-linked relationship with a TV uploads the user's heart rate to the cloud of the linked account, or uploads the user's body fat rate to the cloud of the linked account through a body fat scale.
  • the associated acquisition of the basic body parameters does not necessarily need to be realized through the cloud, and may also be realized by directly communicating with other electronic devices that have an associated account relationship with the TV.
  • a TV initiates a service for acquiring basic physical parameters. After receiving the service, the electronic device associated with the account can send the basic physical parameters related to the user to the TV to complete the rapid entry of basic physical parameters.
  • FIG. 4d shows a schematic diagram of entering a user's motion purpose through a TV interface.
  • the user's exercise purpose can be specific purpose such as training cardiopulmonary ability, waist strength, leg strength, etc. Among them, for this kind of exercise purpose with clear goals, it can be considered that the user has a reward for the exercise.
  • its coefficient can be set to 1 (100%).
  • the TV will push the exercise related to the cardiorespiratory ability training, so that the user can complete the training more purposefully. Further, as shown in FIG.
  • the user can obtain the user's exercise purpose through a cloud or an electronic device that has an account relationship with the TV by selecting the button of "Associate Acquire". Understandably, the user may already include information on the purpose of exercise on the electronic device that has an account relationship with the TV.
  • the user's current exercise plan and specific exercise habits can be obtained by collecting information related to the user on the electronic device of the associated account, for example, the user-related information can be obtained through the user's mobile phone.
  • the user can quickly record the user's exercise purpose to the TV through the electronic device associated with the account relationship and the cloud.
  • FIG. 4e shows a schematic diagram of recording the user's previous training experience through a TV interface.
  • the user can input the previous training experience, such as running, swimming, push-ups, barbell lifting, etc., by filling in the text in the interface or by pulling down the option box.
  • the previous training experience such as running, swimming, push-ups, barbell lifting, etc.
  • personal evaluations of previous sports experience can be selectively entered, such as running and swimming as excellent, push-ups and barbell lifting as fair and so on.
  • the personal evaluation of the previous exercise experience can be used to calculate or adjust the first evaluation threshold. Further, as shown in FIG.
  • the user can obtain the user's previous training experience through a cloud or an electronic device that has an account relationship with the TV by selecting the "Associate Acquire" button. Specifically, for example, it can be determined from the running data of the user in the smart bracelet that the user often runs.
  • the TV may prompt the user on the interface whether to continue training related to running, or select other training items for body parts that are difficult to exercise in running. Users can select their favorite training items through this interface.
  • the TV can also be based on personal evaluations such as running and swimming are excellent, push-ups and barbell lifting are average, etc., and it is analyzed that the user lacks strength training, and can prompt on the TV interface according to the personal evaluation.
  • the user lacks strength training, whether to perform strength sports. Understandably, when the user enters the user's previous training experience, it can not only be used to set the first evaluation threshold, but also provide reasonable suggestions for the user's movement direction, so as to make the user's exercise more targeted.
  • the first evaluation threshold can be obtained by weighted calculation, and the first evaluation threshold can be regarded as a basic evaluation standard for the user. .
  • the basic information parameters can be classified according to the preset parameter classification standards, such as the above-mentioned basic physical parameters, exercise purposes and previous training experience.
  • a weight According to the basic information parameters in the same category, the evaluation results of the category are obtained by weighted calculation.
  • the basic body parameters can be divided into multiple parameters, and the first weight is assigned to each parameter in the same category, which can be obtained through weighted calculation.
  • the evaluation result of the basic body parameter type (which can be a specific value); finally, a second weight is given to the basic information parameters of different categories, and the first evaluation threshold is obtained by weighting according to the evaluation results of different categories.
  • a second weight is given to the basic information parameters of different categories, and the first evaluation threshold can be obtained by weighted calculation.
  • one more warm-up stage can be added.
  • the second evaluation threshold can be obtained according to the parameter data obtained in the warm-up stage. Evaluation threshold.
  • the TV continuously collects user image information, and detects the user's skeletal nodes according to the image information. During the user's stretching action, the TV will use the detected skeletal nodes to calculate the key angle, duration and other parameters when the user's action is completed.
  • these parameters can be preset according to different actions, for example, the inclination angle of the head stretched to the left or right, the inclination angle of the waist stretched to the left or right, the duration of the plank, and some fixed duration of the action, etc. Further, the parameters collected in this warm-up stage may also use the relevant data of the historical warm-up.
  • Fig. 5 shows a schematic diagram of entering the warm-up scene through the TV interface.
  • the TV interface will prompt the user whether to warm up, and explain that the warm-up process helps to make the action more standardized and effective, and the user can Select Confirm to enter the warm-up scene to perform the warm-up action before smart exercise.
  • the specific warm-up action has a certain correlation with the action in the smart exercise stage. For example, if the head training type action is performed in the smart exercise stage, the warm-up action is also related to the head training warm-up accordingly.
  • this warm-up stage is user-selectable, and the evaluation parameters obtained through this warm-up stage can be converted into the warm-up completion degree represented by a numerical value, and the evaluation criteria of user actions can be dynamically adjusted more accurately, and a more reasonable second stage can be obtained. Evaluation threshold.
  • Figures 6a and 6b show schematic diagrams of instructing the user to do warm-up actions, as shown in Figures 6a and 6b, which correspond to two different types of warm-up actions, respectively head tilt angle and waist tilt angle. It is understandable that for different types of warm-up actions, the corresponding key angle or duration and other parameters are different, the TV can require the user to perform the same warm-up actions as displayed on its interface in a certain order, and the key angle when the action is completed. , duration and other parameters are recorded in real time to determine the user's current physical condition according to the user's warm-up results, and flexibly adjust the evaluation criteria of the training process.
  • the camera of the TV will continuously monitor the user's actions, and determine the specific value of the parameter according to the result of the image/video recognition.
  • the angle shown in Figure 6a when the user performs the warm-up exercise of waist stretching, the angle shown in Figure 6a will be identified and calculated based on the user's skeletal nodes to obtain the minimum angle that the user can achieve, such as 110 degrees.
  • the user when the user performs the warm-up exercise of head stretching, the user will identify and calculate the angle shown in Figure 6b based on the user's skeletal nodes to obtain the maximum angle that the user can achieve, such as 130 degrees. .
  • parameters such as duration and jump height can also be calculated. For example, when the warm-up is a plank, the parameter that needs to be recorded in the warm-up is the user's tablet. The duration of the hold.
  • functions such as angle recognition and calculation can also be performed in combination with other camera equipment. It is understandable that, generally only 2D images can be obtained by using the camera equipment that comes with the TV, and the recognition accuracy of parameters that require high spatial observation such as angle is average. In this embodiment of the present application, other camera devices may be combined to detect parameters such as angles from different observation angles.
  • FIG. 7a shows a schematic diagram of using multiple camera devices to identify the tilt angle of the user when performing the head stretching warm-up action. It can be seen from FIG. 7a that the camera of the mobile device can be used behind the user to photograph the user. Combined with the shooting of the user from the front of the TV, the user can be shot in multiple directions from the front and the back of the user, and more angle information can be obtained.
  • FIG. 7b shows another method using multiple camera devices to identify the inclination angle of the user when performing the head stretching warm-up action. It can be seen from Fig. 7b that three camera devices can be used to simultaneously collect the user's tilt angle to obtain more angle information.
  • the camera of the TV is responsible for photographing the user from the front; the mobile device (such as a tablet computer) on the lower left side of Figure 7b shoots the user from the left behind the user; the mobile device (such as a mobile phone) on the lower right side of Figure 7b, from the back of the user
  • the user is photographed on the right side of Fig. 7b, and the user image photographed by the TV and the user image photographed by the mobile device on the lower left side of Fig. 7b can obtain three user images of different angles; the user's head tilt angle can be more accurately calculated from the three user images.
  • the optimal user head tilt angle can be calculated by a preset algorithm (such as a neural network algorithm), which is better than using a TV camera alone.
  • the tilt angle of the user's head calculated by the 2D image captured by the device is more accurate.
  • the multi-camera device solution adopted in the embodiments of the present application is not limited to the recognition of angles, but may also be 3D recognition of other action-related parameters (such as jump height, jump distance, etc.). Further, in addition to applying the multi-camera device solution in the warm-up process, it is also possible to identify and calculate the relevant parameters of the action completion in real time during the user's movement, which can improve the accuracy of the evaluation.
  • the monitoring module includes a camera module (camera), a timing module, a length, distance measurement module, an AI intelligent module, etc.
  • the type of the key evaluation parameter is an action angle
  • the camera module is activated, and the camera module is used to obtain the current action.
  • Action angle when the type of key evaluation parameter is duration
  • the camera module and timing module are activated, and the camera module and timing module are used to obtain the duration of the current action.
  • the TV may include various monitoring modules such as a camera module and a timing module. When monitoring different actions, the corresponding modules are automatically invoked according to the types of key evaluation parameters.
  • the monitoring module may be configured inside the TV or provided by a peripheral device, which is not limited here.
  • parameters such as the key angle and duration when the user's action is completed can be used to feed back the parameters to the action evaluation module of the TV, so that the second evaluation threshold can be obtained by adjusting based on the first evaluation threshold.
  • the classification results of different user evaluations may be displayed on the interface. Specifically, if the first evaluation threshold is 100% (1), under the first evaluation threshold, when the completion quality of the user's warm-up action exceeds 50% and is less than 70%, the first evaluation threshold is adjusted according to the preset adjustment rule , if the completion quality of the warm-up action exceeds 50% and falls by 20%, the first evaluation threshold of 100% will drop to 80%, and a second evaluation threshold of 80% temporarily adjusted according to the warm-up situation is obtained.
  • the second evaluation threshold can be regarded as the first evaluation threshold adjusted according to the warm-up situation, and here it is only for distinguishing the fine-tuning of the values after the warm-up.
  • the level can be improved by imitating standard actions (the first evaluation threshold can be increased while the level is improved); Ground, when the completion quality of the user's warm-up action is greater than 70% and less than 90%, the interface will prompt the normal level; when the user's warm-up action completion quality reaches or exceeds 90%, the interface will prompt the professional level.
  • the training of users at different levels corresponds to different evaluation standards, which can meet the training needs of different users.
  • the correction reminder information of the action may also be displayed on the interface according to the (adjusted) first evaluation threshold.
  • Figures 8a-8c show schematic diagrams of action correction reminder information.
  • the quality of user action completion is within 50%-70%, as can be seen from Figure 8a, only evaluation results (such as excellent, good and fair) are provided on the TV interface, reminding the user that the Motion correction is performed against motion.
  • the quality of the user's actions is within 70%-90%, it can be seen from Figure 8b that the TV interface will prompt the user which actions need to be corrected and an explanation of how to correct them.
  • the user When the user is exercising, the user only needs to imitate the action to meet the requirements under the evaluation standard (reaching At present, the score of 50 or more under the first evaluation threshold standard is sufficient), at this time, the user is only to be reminded to do normal training according to the action.
  • the completion quality of the user's warm-up action is within 70%-90%, it means that the evaluation standard at this time is general.
  • the user can judge which actions the user is not doing well according to the collected image information, and remind the user to perform specific actions. Just imitate it carefully.
  • the completion quality of the user's warm-up action is greater than 90%, it means that the evaluation standard at this time is relatively high.
  • the action correction function can also be directly implemented according to the first evaluation threshold, which will not be repeated here.
  • the evaluation in the process of the user exercising, can also be based on the user's real-time action completion evaluation (for example, the action completion evaluation higher than 90 points is excellent, and other actions are completed in the same way), and iteratively iterates adaptively.
  • the evaluation standard of the action that is, adjusting the second evaluation threshold
  • the user level can be upgraded by one level, such as from ordinary level to professional level, specifically, such as the evaluation at the first evaluation threshold of 80%
  • the first evaluation threshold can be increased by 10%.
  • the first evaluation threshold becomes 90%. Understandably, when the first evaluation threshold is raised, it means that the upper limit of the score is also increasing, and the user needs to still reach the user’s average score of the first three training sessions higher than 90 points under the raised first evaluation threshold (the first average threshold is 90 points).
  • the user level or the first evaluation threshold can continue to be increased until the user level or the first evaluation threshold reaches the highest value; when the average score of the first three training sessions of the user is different
  • the score is lower than 70 points (general)
  • the user level can be lowered by one level accordingly, such as from ordinary level to entry level, and the first evaluation threshold is lowered. Among them, when the user level is already the entry level (the lowest level), it will not be downgraded.
  • Figures 9a-9b show schematic interface diagrams of adaptive iterative action evaluation criteria (first evaluation threshold) according to the user's real-time action completion status.
  • first evaluation threshold adaptive iterative action evaluation criteria
  • the user realizes the function of self-adaptive evaluation of actions by intelligently interacting with the interface of the TV.
  • the TV obtains the basic information parameters of the user through the interface displayed on the screen.
  • the basic information parameters can be specifically divided into basic physical parameters, exercise purpose, and previous training experience, etc., and basic information parameters can also be obtained by entering the physical fitness evaluation.
  • the user can complete the input of basic information parameters by selecting methods such as clicking to select.
  • the basic information parameters can be manually input by the user, or the user can obtain the basic information parameters synchronously in real time through the cloud, an electronic device with the same account, etc., and can be automatically filled in on the interface.
  • the user when searching for electronic devices in the cloud and with the same account, as shown in Figures 4b and 4c, the user can select the correct and available electronic device through the prompt information displayed on the TV interface.
  • the user After inputting the user's basic information parameters, the user can also be prompted to warm up through the interface, so as to preliminarily based on the key evaluation parameters in the warm-up action (parameters used to evaluate the completion of the user's actions, there can be multiple key evaluation parameters, such as The inclination angle of the user's head, waist inclination angle, knee bending angle, etc.), dynamically adjust the first evaluation threshold set by the basic information parameters, which is conducive to setting more reasonable evaluation standards according to the physical conditions of different users.
  • the current first evaluation threshold can be adjusted in real time through the key evaluation parameters in the action acquired in real time, and the first evaluation threshold can be raised or lowered according to the completion of the user action.
  • the user can complete the intelligent information interaction with the TV through the TV interface.
  • the TV will make intelligent responses according to the specific input information of the user (including the image information captured by the camera equipment), and provide differentiated sports services for different users. , adjust the evaluation criteria dynamically, flexibly and reasonably.
  • the first evaluation threshold is set by acquiring the basic information parameters of the user, and more reasonable evaluation criteria can be set according to the physical conditions of different users; when the user is exercising, the key evaluation parameters of the current user action are acquired by acquiring , and the set first evaluation threshold to determine the user's action completion evaluation, so as to flexibly adjust the first evaluation threshold according to the actual completion of the user's action.
  • differentiated exercise services can be provided to the user, so that the user can perform targeted physical exercise, and the physical fitness of the user can be effectively improved.
  • the present application also provides a computer storage medium, where a computer program is stored on the computer-readable storage medium, and when the computer program is executed by a processor, the steps of the action adaptive evaluation method in the embodiment are implemented.
  • a computer program is stored on the computer-readable storage medium, and when the computer program is executed by a processor, the steps of the action adaptive evaluation method in the embodiment are implemented.
  • Module completion means dividing the internal structure of the device into different functional units or modules to complete all or part of the functions described above.

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Abstract

本申请公开了一种动作自适应评价方法、电子设备和存储介质。其中，该方法包括：获取用户的基本信息参数；根据基本信息参数得到第一评价阈值，其中，第一评价阈值用于提供评价标准；获取用户当前动作的关键评价参数；根据关键评价参数和第一评价阈值确定用户的动作完成评价；根据动作完成评价调整第一评价阈值。采用该动作自适应评价方法能够给用户提供差异化的运动服务，使得用户能够进行有针对性的身体锻炼，有效提高用户的身体体质。

Description

动作自适应评价方法、电子设备和存储介质 技术领域
本申请涉及运动健康领域，尤其涉及一种动作自适应评价方法、电子设备和存储介质。
背景技术
现代社会人们的生活节奏越来越快，或多或少存在身体健康问题，如何在快节奏的工作下保持良好的身体状态成为一个急需解决的问题。目前，利用电视进行智能运动指导是一种不错的家庭运动方案。但是，不同个体的运动能力、身体协调性等差别很大，无法针对性地指导用户运动。
发明内容
有鉴于此，本申请实施例提供了一种动作自适应评价方法、电子设备和存储介质，用以解决目前智能运动无法针对性地指导用户运动的问题。
第一方面，本申请实施例提供了一种动作自适应评价方法，首先，通过利用用户的基本信息参数得到一个对用户身体状况具有初步参考作用的第一评价阈值，以针对不同用户的身体状况设置不同的评价阈值，做到对用户动作评价的初步区分；然后，还将根据用户在当前运动时的关键评价参数(如动作完成的关键角度、持续时长等)实时反映用户当前运动的具体状况，并予以评价，根据评价结果实时地调整第一评价阈值，使得第一评价阈值能够根据用户动作的完成情况实时地进行调整，实现更有针对性地用户指导效果。
进一步地，以上提及的基本信息参数具体可以包括用户的基础身体参数、运动目的和既往训练经历，或者是，用户经过体适能评估得到的参数。可以理解地，基本信息参数反映的是用户基本的信息概况，通过了解该基本信息，能够为设置第一评价阈值提供重要的评价标准，初步区分开不同用户的评价阈值。
进一步地，用户在正式进行运动之前还可包括热身阶段。其中，在该热身阶段可对用户的身体状况做进一步的了解，以对第一评价阈值进行预调整。具体地，可针对性地设置热身动作，以确定用户对于这些热身动作完成的程度有多高，越高则代表用户的身体状况越佳。可以理解地，热身动作好坏的评价可通过热身动作的评价参数(如热身动作完成的角度、持续时长)等，确定用户的热身完成度，并根据该热身完成度对第一评价阈值进行预调整。该热身阶段对第一评价阈值的预调整步骤，能够更加精确地区分用户之间的区别，能够更有针对性地指定用户科学运动。
进一步地，在获取用户的基本信息参数时，可通过电视界面预设的参数输入区域，获取用户输入的基本参数信息。可以理解地，即用户可以采用主动输入的方式将用户的基本信息参数输入到电视。除了用户通过参数输入区域主动输入基本参数信息的方式，用户还可以通过与电视具有相关联账号的云端服务器或电子设备(如测量体脂率的体重秤、测量心率的智能手环等)，通过发起基本信息参数的调用请求的方式，接收由相关联账号的云端或电子设备发送的基本信息参数。采用该与其他相关联账号的云端服务器或电子设备获取基本参数信 息的方式，相比用户主动输入的方式，其效率更快，其准确性也有保证。
进一步地，第一评价阈值是根据基本信息参数计算得到的，用于提供评价标准。该第一评价阈值可采用预设的算法计算得到。具体地，可选的一种实施方式是，首先按照预设定的参数分类标准将基本信息参数分类，如分为基础身体参数、运动目的和既往训练经历多种类型；然后对同一类别中的基本信息参数赋予第一权重，根据同一类别中的基本信息参数，加权计算得到类别的评价结果，例如，基础身体参数可分为多项参数，对每项同一类别中的参数赋予第一权重，通过加权计算可得到该基础身体参数类型的评价结果；最后对不同类别的基本信息参数赋予第二权重，根据不同类别的评价结果加权得到第一评价阈值，例如，在分别得到基础身体参数、运动目的和既往训练经历的评价结果后，赋予不同类别的基本信息参数第二权重，可加权计算得到第一评价阈值。
进一步地，在用户运动时，可根据用户当前运动动作的关键评价参数的类型，启动相应的监测模块，并采用该监测模块获取当前用户动作的关键评价参数。具体地，在用户运动时，电视将判断当前动作的关键评价参数的类型；若所述关键评价参数的类型为动作角度，启动摄像模块，并采用所述摄像模块获取当前动作的所述动作角度；若所述关键评价参数的类型为时长，启动摄像模块和计时模块，并采用所述摄像模块和计时模块获取当前动作的所述时长。
进一步地，用户在运动时根据关键评价参数和第一评价阈值确定用户的动作完成评价，该动作完成评价可采用预设的评价表，根据基本信息参数的分类类型，利用评价表存储的基本信息参数与动作完成评价的映射信息，以及所述第一评价阈值，确定用户的动作完成评价。
进一步地，用户在运动阶段可根据动作完成评价实时地对第一评价阈值进行调整，具体地，可采用预设的阈值调整条件进行判断。若达到阈值调整条件，根据阈值调整条件调整第一评价阈值。可以理解地，随着用户运动的进展，用户的动作可能做得越来越标准，也有可能相反，此时，可利用动作完成评价实时地调整第一评价阈值，提高或降低评价标准，更有针对性地指导用户进行运动。
第二方面，本申请实施例提供了一种带屏幕的电子设备，包括存储器、处理器以及存储在所述存储器中并可在所述处理器上运行的计算机程序，所述处理器执行所述计算机程序时实现如下步骤：
首先，通过利用用户的基本信息参数得到一个对用户身体状况具有初步参考作用的第一评价阈值，以针对不同用户的身体状况设置不同的评价阈值，做到对用户动作评价的初步区分；然后，还将根据用户在当前运动时的关键评价参数(如动作完成的关键角度、持续时长等)实时反映用户当前运动的具体状况，并予以评价，根据评价结果实时地调整第一评价阈值，使得第一评价阈值能够根据用户动作的完成情况实时地进行调整，实现更有针对性地用户指导效果。
以上提及的基本信息参数具体可以包括用户的基础身体参数、运动目的和既往训练经历，或者是，用户经过体适能评估得到的参数。可以理解地，基本信息参数反映的是用户基本的信息概况，通过了解该基本信息，能够为设置第一评价阈值提供重要的评价标准，初步区分开不同用户的评价阈值。
进一步地，用户在正式进行运动之前还可包括热身阶段。其中，在该热身阶段可对用户的身体状况做进一步的了解，以对第一评价阈值进行预调整。具体地，可针对性地设置热身 动作，以确定用户对于这些热身动作完成的程度有多高，越高则代表用户的身体状况越佳。可以理解地，热身动作好坏的评价可通过热身动作的评价参数(如热身动作完成的角度、持续时长)等，确定用户的热身完成度，并根据该热身完成度对第一评价阈值进行预调整。该热身阶段对第一评价阈值的预调整步骤，能够更加精确地区分用户之间的区别，能够更有针对性地指定用户科学运动。
进一步地，在获取用户的基本信息参数时，可通过电视界面预设的参数输入区域，获取用户输入的基本参数信息。可以理解地，即用户可以采用主动输入的方式将用户的基本信息参数输入到电视。除了用户通过参数输入区域主动输入基本参数信息的方式，用户还可以通过与电视具有相关联账号的云端服务器或电子设备(如测量体脂率的体重秤、测量心率的智能手环等)，通过发起基本信息参数的调用请求的方式，接收由相关联账号的云端或电子设备发送的基本信息参数。采用该与其他相关联账号的云端服务器或电子设备获取基本参数信息的方式，相比用户主动输入的方式，其效率更快，其准确性也有保证。
进一步地，第一评价阈值是根据基本信息参数计算得到的，用于提供评价标准。该第一评价阈值可采用预设的算法计算得到。具体地，可选的一种实施方式是，首先按照预设定的参数分类标准将基本信息参数分类，如分为基础身体参数、运动目的和既往训练经历多种类型；然后对同一类别中的基本信息参数赋予第一权重，根据同一类别中的基本信息参数，加权计算得到类别的评价结果，例如，基础身体参数可分为多项参数，对每项同一类别中的参数赋予第一权重，通过加权计算可得到该基础身体参数类型的评价结果；最后对不同类别的基本信息参数赋予第二权重，根据不同类别的评价结果加权得到第一评价阈值，例如，在分别得到基础身体参数、运动目的和既往训练经历的评价结果后，赋予不同类别的基本信息参数第二权重，可加权计算得到第一评价阈值。
进一步地，在用户运动时，可根据用户当前运动动作的关键评价参数的类型，启动相应的监测模块，并采用该监测模块获取当前用户动作的关键评价参数。具体地，在用户运动时，电视将判断当前动作的关键评价参数的类型；若所述关键评价参数的类型为动作角度，启动摄像模块，并采用所述摄像模块获取当前动作的所述动作角度；若所述关键评价参数的类型为时长，启动摄像模块和计时模块，并采用所述摄像模块和计时模块获取当前动作的所述时长。
进一步地，用户在运动时根据关键评价参数和第一评价阈值确定用户的动作完成评价，该动作完成评价可采用预设的评价表，根据基本信息参数的分类类型，利用评价表存储的基本信息参数与动作完成评价的映射信息，以及所述第一评价阈值，确定用户的动作完成评价。
进一步地，用户在运动阶段可根据动作完成评价实时地对第一评价阈值进行调整，具体地，可采用预设的阈值调整条件进行判断。若达到阈值调整条件，根据阈值调整条件调整第一评价阈值。可以理解地，随着用户运动的进展，用户的动作可能做得越来越标准，也有可能相反，此时，可利用动作完成评价实时地调整第一评价阈值，提高或降低评价标准，更有针对性地指导用户进行运动。
第三方面，本申请实施例提供了一种计算机可读存储介质，包括计算机程序，所述计算机程序被处理器执行时实现上述第一方面所述方法的步骤。
在本申请实施例中，通过获取用户的基本信息参数设定第一评价阈值，可根据不同用户的身体状况设定更合理的评价标准；在用户运动时，通过获取当前用户动作的关键评价参数， 以及设定好的第一评价阈值，确定用户的动作完成评价，以根据用户动作实际的完成情况，灵活调整第一评价阈值。本申请实施例中，能够给用户提供差异化的运动服务，使得用户能够进行有针对性的身体锻炼，有效提高用户的身体体质。
附图说明
为了更清楚地说明本申请实施例的技术方案，下面将对实施例中所需要使用的附图作简单地介绍，显而易见地，下面描述中的附图仅仅是本申请的一些实施例，对于本领域普通技术人员来讲，在不付出创造性劳动性的前提下，还可以根据这些附图获得其它的附图。
图1是本申请一实施例提供的一种电子设备的结构示意图；
图2是本申请一实施例提供的一种电子设备的软件结构框图；
图3a是本申请一实施例提供的一种通过电视界面交互实现信息录入的示意图；
图3b是本申请一实施例提供的又一种通过电视界面交互实现信息录入的示意图；
图3c是本申请一实施例提供的一种通过电视界面交互进行体适能评估的示意图；
图4a是本申请一实施例提供的一种通过电视界面录入用户基础身体参数的示意图；
图4b是本申请一实施例提供的一种电视界面上显示可连接的智能手环的示意图；
图4c是本申请一实施例提供的一种在电视界面上提示用户采用连接的智能手环进行心率测量操作的示意图；
图4d通过电视界面录入用户运动目的的示意图；
图4e是本申请一实施例提供的一种通过电视界面录入用户既往训练经历的示意图；
图4f是本申请一实施例提供的一种通过界面选择训练项目的示意图；
图4g是本申请一实施例提供的又一种通过界面选择训练项目的示意图；
图5是本申请一实施例提供的一种通过电视界面进入热身场景的示意图；
图6a是本申请一实施例提供的一种指导用户做热身动作的示意图；
图6b是本申请一实施例提供的又一种指导用户做热身动作的示意图；
图7a是本申请一实施例提供的一种采用多摄像设备识别用户在进行头部拉伸热身动作时的倾斜角度的示意图；
图7b是本申请一实施例提供的另一种采用多摄像设备识别用户在进行头部拉伸热身动作时的倾斜角度的示意图；
图8a是本申请一实施例提供的一种动作校正提醒信息的示意图；
图8b是本申请一实施例提供的另一种动作校正提醒信息的示意图；
图8c是本申请一实施例提供的又一种动作校正提醒信息的示意图；
图9a是本申请一实施例提供的一种自适应迭代动作评价标准的界面示意图；
图9b是本申请一实施例提供的另一种自适应迭代动作评价标准的界面示意图。
具体实施方式
下面结合本申请实施例中的附图，对本申请实施例中的技术方案进行描述。其中，在本申请实施例的描述中，除非另有说明，“/”表示或的意思，例如，A/B可以表示A或B；本文中的“和/或”仅仅是一种描述关联对象的关联关系，表示可以存在三种关系，例如，A和/或B，可以表示：单独存在A，同时存在A和B，单独存在B这三种情况。
以下，术语“第一”、“第二”仅用于描述目的，而不能理解为指示或暗示相对重要性或者隐含指明所指示的技术特征的数量。由此，限定有“第一”、“第二”的特征可以明示或者隐含地包括一个或者更多个该特征。在本申请实施例的描述中，除非另有说明，“多个”的含义是两个或两个以上。
在本申请实施例中，“示例性的”或者“例如”等词用于表示作例子、例证或说明。本申请实施例中被描述为“示例性的”或者“例如”的任何实施例或设计方案不应被解释为比其它实施例或设计方案更优选或更具优势。确切而言，使用“示例性的”或者“例如”等词旨在以具体方式呈现相关概念。
图1示出了电子设备100的结构示意图。
电子设备100可以包括处理器110，外部存储器接口120，内部存储器121，通用串行总线(universal serial bus，USB)接口130，充电管理模块140，电源管理模块141，电池142，天线1，天线2，移动通信模块150，无线通信模块160，音频模块170，扬声器170A，受话器170B，麦克风170C，耳机接口170D，传感器模块180，按键190，马达191，指示器192，摄像头193，显示屏194，以及用户标识模块(subscriber identification module，SIM)卡接口195等。其中传感器模块180可以包括压力传感器180A，陀螺仪传感器180B，气压传感器180C，磁传感器180D，加速度传感器180E，距离传感器180F，接近光传感器180G，指纹传感器180H，温度传感器180J，触摸传感器180K，环境光传感器180L，骨传导传感器180M等。
可以理解的是，本申请实施例示意的结构并不构成对电子设备100的具体限定。在本申请另一些实施例中，电子设备100可以包括比图示更多或更少的部件，或者组合某些部件，或者拆分某些部件，或者不同的部件布置。图示的部件可以以硬件，软件或软件和硬件的组合实现。
处理器110可以包括一个或多个处理单元，例如：处理器110可以包括应用处理器(application processor，AP)，调制解调处理器，图形处理器(graphics processing unit，GPU)，图像信号处理器(image signal processor，ISP)，控制器，视频编解码器，数字信号处理器(digital signal processor，DSP)，基带处理器，和/或神经网络处理器(neural-network processing unit，NPU)等。其中，不同的处理单元可以是独立的器件，也可以集成在一个或多个处理器中。
控制器可以根据指令操作码和时序信号，产生操作控制信号，完成取指令和执行指令的控制。
处理器110中还可以设置存储器，用于存储指令和数据。在一些实施例中，处理器110中的存储器为高速缓冲存储器。该存储器可以保存处理器110刚用过或循环使用的指令或数据。如果处理器110需要再次使用该指令或数据，可从所述存储器中直接调用。避免了重复存取，减少了处理器110的等待时间，因而提高了系统的效率。
在一些实施例中，处理器110可以包括一个或多个接口。接口可以包括集成电路(inter-integrated circuit，I2C)接口，集成电路内置音频(inter-integrated circuit sound，I2S)接口，脉冲编码调制(pulse code modulation，PCM)接口，通用异步收发传输器(universal asynchronous receiver/transmitter，UART)接口，移动产业处理器接口(mobile industry processor interface，MIPI)，通用输入输出(general-purpose input/output，GPIO)接口，用户标识模块(subscriber identity module，SIM)接口，和/或通用串行总线(universal serial bus，USB)接口等。
I2C接口是一种双向同步串行总线，包括一根串行数据线(serial data line，SDA)和一根串 行时钟线(derail clock line，SCL)。在一些实施例中，处理器110可以包含多组I2C总线。处理器110可以通过不同的I2C总线接口分别耦合触摸传感器180K，充电器，闪光灯，摄像头193等。例如：处理器110可以通过I2C接口耦合触摸传感器180K，使处理器110与触摸传感器180K通过I2C总线接口通信，实现电子设备100的触摸功能。
I2S接口可以用于音频通信。在一些实施例中，处理器110可以包含多组I2S总线。处理器110可以通过I2S总线与音频模块170耦合，实现处理器110与音频模块170之间的通信。在一些实施例中，音频模块170可以通过I2S接口向无线通信模块160传递音频信号，实现通过蓝牙耳机接听电话的功能。
PCM接口也可以用于音频通信，将模拟信号抽样，量化和编码。在一些实施例中，音频模块170与无线通信模块160可以通过PCM总线接口耦合。在一些实施例中，音频模块170也可以通过PCM接口向无线通信模块160传递音频信号，实现通过蓝牙耳机接听电话的功能。所述I2S接口和所述PCM接口都可以用于音频通信。
UART接口是一种通用串行数据总线，用于异步通信。该总线可以为双向通信总线。它将要传输的数据在串行通信与并行通信之间转换。在一些实施例中，UART接口通常被用于连接处理器110与无线通信模块160。例如：处理器110通过UART接口与无线通信模块160中的蓝牙模块通信，实现蓝牙功能。在一些实施例中，音频模块170可以通过UART接口向无线通信模块160传递音频信号，实现通过蓝牙耳机播放音乐的功能。
MIPI接口可以被用于连接处理器110与显示屏194，摄像头193等外围器件。MIPI接口包括摄像头串行接口(camera serial interface，CSI)，显示屏串行接口(display serial interface，DSI)等。在一些实施例中，处理器110和摄像头193通过CSI接口通信，实现电子设备100的拍摄功能。处理器110和显示屏194通过DSI接口通信，实现电子设备100的显示功能。
GPIO接口可以通过软件配置。GPIO接口可以被配置为控制信号，也可被配置为数据信号。在一些实施例中，GPIO接口可以用于连接处理器110与摄像头193，显示屏194，无线通信模块160，音频模块170，传感器模块180等。GPIO接口还可以被配置为I2C接口，I2S接口，UART接口，MIPI接口等。
USB接口130是符合USB标准规范的接口，具体可以是Mini USB接口，Micro USB接口，USB Type C接口等。USB接口130可以用于连接充电器为电子设备100充电，也可以用于电子设备100与外围设备之间传输数据。也可以用于连接耳机，通过耳机播放音频。该接口还可以用于连接其他电子设备，例如AR设备等。
可以理解的是，本申请实施例示意的各模块间的接口连接关系，只是示意性说明，并不构成对电子设备100的结构限定。在本申请另一些实施例中，电子设备100也可以采用上述实施例中不同的接口连接方式，或多种接口连接方式的组合。
充电管理模块140用于从充电器接收充电输入。其中，充电器可以是无线充电器，也可以是有线充电器。在一些有线充电的实施例中，充电管理模块140可以通过USB接口130接收有线充电器的充电输入。在一些无线充电的实施例中，充电管理模块140可以通过电子设备100的无线充电线圈接收无线充电输入。充电管理模块140为电池142充电的同时，还可以通过电源管理模块141为电子设备供电。
电源管理模块141用于连接电池142，充电管理模块140与处理器110。电源管理模块141接收电池142和/或充电管理模块140的输入，为处理器110，内部存储器121，显示屏 194，摄像头193，和无线通信模块160等供电。电源管理模块141还可以用于监测电池容量，电池循环次数，电池健康状态(漏电，阻抗)等参数。在其他一些实施例中，电源管理模块141也可以设置于处理器110中。在另一些实施例中，电源管理模块141和充电管理模块140也可以设置于同一个器件中。
电子设备100的无线通信功能可以通过天线1，天线2，移动通信模块150，无线通信模块160，调制解调处理器以及基带处理器等实现。
天线1和天线2用于发射和接收电磁波信号。电子设备100中的每个天线可用于覆盖单个或多个通信频带。不同的天线还可以复用，以提高天线的利用率。例如：可以将天线1复用为无线局域网的分集天线。在另外一些实施例中，天线可以和调谐开关结合使用。
移动通信模块150可以提供应用在电子设备100上的包括2G/3G/4G/5G等无线通信的解决方案。移动通信模块150可以包括至少一个滤波器，开关，功率放大器，低噪声放大器(low noise amplifier，LNA)等。移动通信模块150可以由天线1接收电磁波，并对接收的电磁波进行滤波，放大等处理，传送至调制解调处理器进行解调。移动通信模块150还可以对经调制解调处理器调制后的信号放大，经天线1转为电磁波辐射出去。在一些实施例中，移动通信模块150的至少部分功能模块可以被设置于处理器110中。在一些实施例中，移动通信模块150的至少部分功能模块可以与处理器110的至少部分模块被设置在同一个器件中。
调制解调处理器可以包括调制器和解调器。其中，调制器用于将待发送的低频基带信号调制成中高频信号。解调器用于将接收的电磁波信号解调为低频基带信号。随后解调器将解调得到的低频基带信号传送至基带处理器处理。低频基带信号经基带处理器处理后，被传递给应用处理器。应用处理器通过音频设备(不限于扬声器170A，受话器170B等)输出声音信号，或通过显示屏194显示图像或视频。在一些实施例中，调制解调处理器可以是独立的器件。在另一些实施例中，调制解调处理器可以独立于处理器110，与移动通信模块150或其他功能模块设置在同一个器件中。
无线通信模块160可以提供应用在电子设备100上的包括无线局域网(wireless local area networks，WLAN)(如无线保真(wireless fidelity，Wi-Fi)网络)，蓝牙(bluetooth，BT)，全球导航卫星系统(global navigation satellite system，GNSS)，调频(frequency modulation，FM)，近距离无线通信技术(near field communication，NFC)，红外技术(infrared，IR)等无线通信的解决方案。无线通信模块160可以是集成至少一个通信处理模块的一个或多个器件。无线通信模块160经由天线2接收电磁波，将电磁波信号调频以及滤波处理，将处理后的信号发送到处理器110。无线通信模块160还可以从处理器110接收待发送的信号，对其进行调频，放大，经天线2转为电磁波辐射出去。
在一些实施例中，电子设备100的天线1和移动通信模块150耦合，天线2和无线通信模块160耦合，使得电子设备100可以通过无线通信技术与网络以及其他设备通信。所述无线通信技术可以包括全球移动通讯系统(global system for mobile communications，GSM)，通用分组无线服务(general packet radio service，GPRS)，码分多址接入(code division multiple access，CDMA)，宽带码分多址(wideband code division multiple access，WCDMA)，时分码分多址(time-division code division multiple access，TD-SCDMA)，长期演进(long term evolution，LTE)，BT，GNSS，WLAN，NFC，FM，和/或IR技术等。所述GNSS可以包括全球卫星定位系统(global positioning system，GPS)，全球导航卫星系统(global navigation satellite system，GLONASS)， 北斗卫星导航系统(beidou navigation satellite system，BDS)，准天顶卫星系统(quasi-zenith satellite system，QZSS)和/或星基增强系统(satellite based augmentation systems，SBAS)。
电子设备100通过GPU，显示屏194，以及应用处理器等实现显示功能。GPU为图像处理的微处理器，连接显示屏194和应用处理器。GPU用于执行数学和几何计算，用于图形渲染。处理器110可包括一个或多个GPU，其执行程序指令以生成或改变显示信息。
显示屏194用于显示图像，视频等。显示屏194包括显示面板。显示面板可以采用液晶显示屏(liquid crystal display，LCD)，有机发光二极管(organic light-emitting diode，OLED)，有源矩阵有机发光二极体或主动矩阵有机发光二极体(active-matrix organic light emitting diode的，AMOLED)，柔性发光二极管(flex light-emitting diode，FLED)，Miniled，MicroLed，Micro-oLed，量子点发光二极管(quantum dot light emitting diodes，QLED)等。在一些实施例中，电子设备100可以包括1个或N个显示屏194，N为大于1的正整数。
电子设备100可以通过ISP，摄像头193，视频编解码器，GPU，显示屏194以及应用处理器等实现拍摄功能。
ISP用于处理摄像头193反馈的数据。例如，拍照时，打开快门，光线通过镜头被传递到摄像头感光元件上，光信号转换为电信号，摄像头感光元件将所述电信号传递给ISP处理，转化为肉眼可见的图像。ISP还可以对图像的噪点，亮度，肤色进行算法优化。ISP还可以对拍摄场景的曝光，色温等参数优化。在一些实施例中，ISP可以设置在摄像头193中。
摄像头193用于捕获静态图像或视频。物体通过镜头生成光学图像投射到感光元件。感光元件可以是电荷耦合器件(charge coupled device，CCD)或互补金属氧化物半导体(complementary metal-oxide-semiconductor，CMOS)光电晶体管。感光元件把光信号转换成电信号，之后将电信号传递给ISP转换成数字图像信号。ISP将数字图像信号输出到DSP加工处理。DSP将数字图像信号转换成标准的RGB，YUV等格式的图像信号。在一些实施例中，电子设备100可以包括1个或N个摄像头193，N为大于1的正整数。
数字信号处理器用于处理数字信号，除了可以处理数字图像信号，还可以处理其他数字信号。例如，当电子设备100在频点选择时，数字信号处理器用于对频点能量进行傅里叶变换等。
视频编解码器用于对数字视频压缩或解压缩。电子设备100可以支持一种或多种视频编解码器。这样，电子设备100可以播放或录制多种编码格式的视频，例如：动态图像专家组(moving picture experts group，MPEG)1，MPEG2，MPEG3，MPEG4等。
NPU为神经网络(neural-network，NN)计算处理器，通过借鉴生物神经网络结构，例如借鉴人脑神经元之间传递模式，对输入信息快速处理，还可以不断的自学习。通过NPU可以实现电子设备100的智能认知等应用，例如：图像识别，人脸识别，语音识别，文本理解等。
外部存储器接口120可以用于连接外部存储卡，例如Micro SD卡，实现扩展电子设备100的存储能力。外部存储卡通过外部存储器接口120与处理器110通信，实现数据存储功能。例如将音乐，视频等文件保存在外部存储卡中。
内部存储器121可以用于存储计算机可执行程序代码，所述可执行程序代码包括指令。内部存储器121可以包括存储程序区和存储数据区。其中，存储程序区可存储操作系统，至少一个功能所需的应用程序(比如声音播放功能，图像播放功能等)等。存储数据区可存储电子设备100使用过程中所创建的数据(比如音频数据，电话本等)等。此外，内部存储器121可以 包括高速随机存取存储器，还可以包括非易失性存储器，例如至少一个磁盘存储器件，闪存器件，通用闪存存储器(universal flash storage，UFS)等。处理器110通过运行存储在内部存储器121的指令，和/或存储在设置于处理器中的存储器的指令，执行电子设备100的各种功能应用以及数据处理。
电子设备100可以通过音频模块170，扬声器170A，受话器170B，麦克风170C，耳机接口170D，以及应用处理器等实现音频功能。例如音乐播放，录音等。
音频模块170用于将数字音频信息转换成模拟音频信号输出，也用于将模拟音频输入转换为数字音频信号。音频模块170还可以用于对音频信号编码和解码。在一些实施例中，音频模块170可以设置于处理器110中，或将音频模块170的部分功能模块设置于处理器110中。
扬声器170A，也称“喇叭”，用于将音频电信号转换为声音信号。电子设备100可以通过扬声器170A收听音乐，或收听免提通话。
受话器170B，也称“听筒”，用于将音频电信号转换成声音信号。当电子设备100接听电话或语音信息时，可以通过将受话器170B靠近人耳接听语音。
麦克风170C，也称“话筒”，“传声器”，用于将声音信号转换为电信号。当拨打电话或发送语音信息时，用户可以通过人嘴靠近麦克风170C发声，将声音信号输入到麦克风170C。电子设备100可以设置至少一个麦克风170C。在另一些实施例中，电子设备100可以设置两个麦克风170C，除了采集声音信号，还可以实现降噪功能。在另一些实施例中，电子设备100还可以设置三个，四个或更多麦克风170C，实现采集声音信号，降噪，还可以识别声音来源，实现定向录音功能等。
耳机接口170D用于连接有线耳机。耳机接口170D可以是USB接口130，也可以是3.5mm的开放移动电子设备平台(open mobile terminal platform，OMTP)标准接口，美国蜂窝电信工业协会(cellular telecommunications industry association of the USA，CTIA)标准接口。
压力传感器180A用于感受压力信号，可以将压力信号转换成电信号。在一些实施例中，压力传感器180A可以设置于显示屏194。压力传感器180A
的种类很多，如电阻式压力传感器，电感式压力传感器，电容式压力传感器等。电容式压力传感器可以是包括至少两个具有导电材料的平行板。当有力作用于压力传感器180A，电极之间的电容改变。电子设备100根据电容的变化确定压力的强度。当有触摸操作作用于显示屏194，电子设备100根据压力传感器180A检测所述触摸操作强度。电子设备100也可以根据压力传感器180A的检测信号计算触摸的位置。在一些实施例中，作用于相同触摸位置，但不同触摸操作强度的触摸操作，可以对应不同的操作指令。例如：当有触摸操作强度小于第一压力阈值的触摸操作作用于短消息应用图标时，执行查看短消息的指令。当有触摸操作强度大于或等于第一压力阈值的触摸操作作用于短消息应用图标时，执行新建短消息的指令。
陀螺仪传感器180B可以用于确定电子设备100的运动姿态。在一些实施例中，可以通过陀螺仪传感器180B确定电子设备100围绕三个轴(即，x，y和z轴)的角速度。陀螺仪传感器180B可以用于拍摄防抖。示例性的，当按下快门，陀螺仪传感器180B检测电子设备100抖动的角度，根据角度计算出镜头模组需要补偿的距离，让镜头通过反向运动抵消电子设备100的抖动，实现防抖。陀螺仪传感器180B还可以用于导航，体感游戏场景。
气压传感器180C用于测量气压。在一些实施例中，电子设备100通过气压传感器180C 测得的气压值计算海拔高度，辅助定位和导航。
磁传感器180D包括霍尔传感器。电子设备100可以利用磁传感器180D检测翻盖皮套的开合。在一些实施例中，当电子设备100是翻盖机时，电子设备100可以根据磁传感器180D检测翻盖的开合。进而根据检测到的皮套的开合状态或翻盖的开合状态，设置翻盖自动解锁等特性。
加速度传感器180E可检测电子设备100在各个方向上(一般为三轴)加速度的大小。当电子设备100静止时可检测出重力的大小及方向。还可以用于识别电子设备姿态，应用于横竖屏切换，计步器等应用。
距离传感器180F，用于测量距离。电子设备100可以通过红外或激光测量距离。在一些实施例中，拍摄场景，电子设备100可以利用距离传感器180F测距以实现快速对焦。
接近光传感器180G可以包括例如发光二极管(LED)和光检测器，例如光电二极管。发光二极管可以是红外发光二极管。电子设备100通过发光二极管向外发射红外光。电子设备100使用光电二极管检测来自附近物体的红外反射光。当检测到充分的反射光时，可以确定电子设备100附近有物体。当检测到不充分的反射光时，电子设备100可以确定电子设备100附近没有物体。电子设备100可以利用接近光传感器180G检测用户手持电子设备100贴近耳朵通话，以便自动熄灭屏幕达到省电的目的。接近光传感器180G也可用于皮套模式，口袋模式自动解锁与锁屏。
环境光传感器180L用于感知环境光亮度。电子设备100可以根据感知的环境光亮度自适应调节显示屏194亮度。环境光传感器180L也可用于拍照时自动调节白平衡。环境光传感器180L还可以与接近光传感器180G配合，检测电子设备100是否在口袋里，以防误触。
指纹传感器180H用于采集指纹。电子设备100可以利用采集的指纹特性实现指纹解锁，访问应用锁，指纹拍照，指纹接听来电等。
温度传感器180J用于检测温度。在一些实施例中，电子设备100利用温度传感器180J检测的温度，执行温度处理策略。例如，当温度传感器180J上报的温度超过阈值，电子设备100执行降低位于温度传感器180J附近的处理器的性能，以便降低功耗实施热保护。在另一些实施例中，当温度低于另一阈值时，电子设备100对电池142加热，以避免低温导致电子设备100异常关机。在其他一些实施例中，当温度低于又一阈值时，电子设备100对电池142的输出电压执行升压，以避免低温导致的异常关机。
触摸传感器180K，也称“触控面板”。触摸传感器180K可以设置于显示屏194，由触摸传感器180K与显示屏194组成触摸屏，也称“触控屏”。触摸传感器180K用于检测作用于其上或附近的触摸操作。触摸传感器可以将检测到的触摸操作传递给应用处理器，以确定触摸事件类型。可以通过显示屏194提供与触摸操作相关的视觉输出。在另一些实施例中，触摸传感器180K也可以设置于电子设备100的表面，与显示屏194所处的位置不同。
骨传导传感器180M可以获取振动信号。在一些实施例中，骨传导传感器180M可以获取人体声部振动骨块的振动信号。骨传导传感器180M也可以接触人体脉搏，接收血压跳动信号。在一些实施例中，骨传导传感器180M也可以设置于耳机中，结合成骨传导耳机。音频模块170可以基于所述骨传导传感器180M获取的声部振动骨块的振动信号，解析出语音信号，实现语音功能。应用处理器可以基于所述骨传导传感器180M获取的血压跳动信号解析心率信息，实现心率检测功能。
按键190包括开机键，音量键等。按键190可以是机械按键。也可以是触摸式按键。电子设备100可以接收按键输入，产生与电子设备100的用户设置以及功能控制有关的键信号输入。
马达191可以产生振动提示。马达191可以用于来电振动提示，也可以用于触摸振动反馈。例如，作用于不同应用(例如拍照，音频播放等)的触摸操作，可以对应不同的振动反馈效果。作用于显示屏194不同区域的触摸操作，马达191也可对应不同的振动反馈效果。不同的应用场景(例如：时间提醒，接收信息，闹钟，游戏等)也可以对应不同的振动反馈效果。触摸振动反馈效果还可以支持自定义。
指示器192可以是指示灯，可以用于指示充电状态，电量变化，也可以用于指示消息，未接来电，通知等。
SIM卡接口195用于连接SIM卡。SIM卡可以通过插入SIM卡接口195，或从SIM卡接口195拔出，实现和电子设备100的接触和分离。电子设备100可以支持1个或N个SIM卡接口，N为大于1的正整数。SIM卡接口195可以支持Nano SIM卡，Micro SIM卡，SIM卡等。同一个SIM卡接口195可以同时插入多张卡。所述多张卡的类型可以相同，也可以不同。SIM卡接口195也可以兼容不同类型的SIM卡。SIM卡接口195也可以兼容外部存储卡。电子设备100通过SIM卡和网络交互，实现通话以及数据通信等功能。在一些实施例中，电子设备100采用eSIM，即：嵌入式SIM卡。eSIM卡可以嵌在电子设备100中，不能和电子设备100分离。
电子设备100的软件系统可以采用分层架构，事件驱动架构，微核架构，微服务架构，或云架构。本申请实施例以分层架构的Android系统为例，示例性说明电子设备100的软件结构。
图2是本申请实施例的电子设备100的软件结构框图。
分层架构将软件分成若干个层，每一层都有清晰的角色和分工。层与层之间通过软件接口通信。在一些实施例中，将Android系统分为四层，从上至下分别为应用程序层，应用程序框架层，安卓运行时(Android runtime)和系统库，以及内核层。
应用程序层可以包括一系列应用程序包。
如图2所示，应用程序包可以包括相机，图库，日历，通话，地图，导航，WLAN，蓝牙，音乐，视频，短信息等应用程序。
应用程序框架层为应用程序层的应用程序提供应用编程接口(application programming interface，API)和编程框架。应用程序框架层包括一些预先定义的函数。
如图2所示，应用程序框架层可以包括窗口管理器，内容提供器，视图系统，电话管理器，资源管理器，通知管理器等。
窗口管理器用于管理窗口程序。窗口管理器可以获取显示屏大小，判断是否有状态栏，锁定屏幕，截取屏幕等。
内容提供器用来存放和获取数据，并使这些数据可以被应用程序访问。所述数据可以包括视频，图像，音频，拨打和接听的电话，浏览历史和书签，电话簿等。
视图系统包括可视控件，例如显示文字的控件，显示图片的控件等。视图系统可用于构建应用程序。显示界面可以由一个或多个视图组成的。例如，包括短信通知图标的显示界面，可以包括显示文字的视图以及显示图片的视图。
电话管理器用于提供电子设备100的通信功能。例如通话状态的管理(包括接通，挂断等)。
资源管理器为应用程序提供各种资源，比如本地化字符串，图标，图片，布局文件，视频文件等等。
通知管理器使应用程序可以在状态栏中显示通知信息，可以用于传达告知类型的消息，可以短暂停留后自动消失，无需用户交互。比如通知管理器被用于告知下载完成，消息提醒等。通知管理器还可以是以图表或者滚动条文本形式出现在系统顶部状态栏的通知，例如后台运行的应用程序的通知，还可以是以对话窗口形式出现在屏幕上的通知。例如在状态栏提示文本信息，发出提示音，电子设备振动，指示灯闪烁等。
Android Runtime包括核心库和虚拟机。Android runtime负责安卓系统的调度和管理。
核心库包含两部分：一部分是java语言需要调用的功能函数，另一部分是安卓的核心库。
应用程序层和应用程序框架层运行在虚拟机中。虚拟机将应用程序层和应用程序框架层的java文件执行为二进制文件。虚拟机用于执行对象生命周期的管理，堆栈管理，线程管理，安全和异常的管理，以及垃圾回收等功能。
系统库可以包括多个功能模块。例如：表面管理器(surface manager)，媒体库(Media Libraries)，三维图形处理库(例如：OpenGL ES)，2D图形引擎(例如：SGL)等。
表面管理器用于对显示子系统进行管理，并且为多个应用程序提供了2D和3D图层的融合。
媒体库支持多种常用的音频，视频格式回放和录制，以及静态图像文件等。媒体库可以支持多种音视频编码格式，例如:MPEG4，H.264，MP3，AAC，AMR，JPG，PNG等。
三维图形处理库用于实现三维图形绘图，图像渲染，合成，和图层处理等。
2D图形引擎是2D绘图的绘图引擎。
内核层是硬件和软件之间的层。内核层至少包含显示驱动，摄像头驱动，音频驱动，传感器驱动。
下面结合捕获拍照场景，示例性说明电子设备100软件以及硬件的工作流程。
当触摸传感器180K接收到触摸操作，相应的硬件中断被发给内核层。内核层将触摸操作加工成原始输入事件(包括触摸坐标，触摸操作的时间戳等信息)。原始输入事件被存储在内核层。应用程序框架层从内核层获取原始输入事件，识别该输入事件所对应的控件。以该触摸操作是触摸单击操作，该单击操作所对应的控件为相机应用图标的控件为例，相机应用调用应用框架层的接口，启动相机应用，进而通过调用内核层启动摄像头驱动，通过摄像头193捕获静态图像或视频。
具体地，该电子设备100的处理器110执行内部存储器121中可执行程序代码时，可实现本申请实施例提供的动作自适应评价方法中所执行的步骤，该电子设备100具体可以是一台电视。
现代社会人们的生活节奏越来越快，或多或少存在身体健康问题，如何在快节奏的工作下保持良好的身体状态成为一个急需解决的问题。目前，利用电视(智慧电视、智慧屏)进行智能运动指导是一种不错的家庭运动方案。但是，不同个体的运动能力、身体协调性等差别很大，若对所有用户均采用单一的评价标准来衡量动作完成情况显然是不精确的，不仅无法有效地指导用户完成运动，甚至在某些动作训练过程中还可能对用户身体造成损伤。
当前电视上的运动应用，绝大多数并不支持动作指导，多数仅充当视频播放器，只有少 数实现动作识别的应用实现简单的计数统计。进一步地，即便运动应用支持智能动作指导，也只是根据确定的度量标准给予动作评价反馈，无法对不同用户进行针对性锻炼，以达到个体锻炼最优效果的目的。
鉴于此，本申请提出了一种动作自适应评价方法，能够给用户提供差异化的服务，使得用户能够进行有效的身体锻炼，提高用户的身体体质。
在一实施例中，用户在利用电视(在本申请实施例中，电子设备100具体可以是指电视，该电视亦可称为智慧屏，具有与用户进行智慧交互等功能，并不限定于传统的用于观看视频等多媒体信息的电视。)进行运动锻炼的账号注册阶段，可根据用户的基础身体参数、运动目的、既往训练经历等设置第一评价阈值。该第一评价阈值用于提供评价标准，能够从总体上反映用户参与运动的身体素质、兴致方向等信息。该第一评价阈值具体可以是[0，1]区间内的数值，例如，当用户的基础身体参数为优异(如BMI(Body Mass Index，体质指数)达标，此时仅以BMI作为评价的参数)、既往训练经历丰富、运动目的为运动减脂时，该三条件对应的权重可均取为1/3，系数均取为1，将三者加权后可得到第一评价阈值为100％。该第一评价阈值为100％表明对于用户在账号注册阶段，由用户输入的基础身体参数、运动目的、既往训练经历等信息可得知该用户身体素质较好、经常运动且期望本次运动得到较好的运动减脂结果，因此该用户的评价标准将设置为高。可以理解地，在高标准的评价标准下，用户需要将动作做得更加到位才能继续后续环节的动作，用户将进行目标性(如减脂)更强的智能运动。相对地，当用户的基础身体参数为一般、既往训练经历少、运动目的为仅娱乐时，该三条件对应的权重可均取为1/3，系数均取为0.6，将三者加权后可得到第一评价阈值为60％。该第一评价阈值为60％可表明对于用户在账号注册阶段，根据用户输入的基础身体参数、运动目的、既往训练经历等信息可得知该用户身体素质一般、不经常运动且对本次运动抱着娱乐为主的训练心态，因此该用户的评价标准将设置为较低。可以理解地，当用户在该较低的评价标准下进行运动时，用户将较容易完成当前动作并进入到下一环节的动作，并且，在该评价标准下，反馈的动作完成情况多数为“完美”、或“真棒”。可以理解地，在评价标准较低的场景下，电视上的智能运动应用以鼓励用户进行运动的目的为主，对用户动作完成度的要求不高。
可以理解地，第一评价阈值可区分不同用户的身体状况，为不同的用户设置不同的评价标准。该评价标准是指对用户基本信息参数分析后确定的适合不同用户所制定的标准，例如，用户基本信息分析后得出的结果为100％，说明可以按最高的标准对用户动作进行评价、若用户基本信息分析后得出的结果为80％，说明当前用户的身体状态还不适合按照最高标准来进行评价、按照最高标准的80％对用户进行动作评价即可。进一步地，在后续运动的过程中，可根据用户实际的动作完成情况对第一评价阈值进行调整。
进一步地，在用户账号注册阶段，除问卷外，还可要求用户完成一套体适能评估动作(如FMS(Functional movement screen，功能性运动检测)等)，以评估用户的运动能力，完成用户第一评价阈值的设定。具体地，如FMS评估，其可用以检测用户整体的动作控制稳定性、身体平衡能力、柔韧度、以及本体感觉等能力的检测，通过FMS评估，可简易地识别用户整体的身体概况。在一实施例中，采用该体适能评估动作完成的第一评价阈值的设定，其准确率可比用户输入基础身体参数、运动目的、既往训练经历等信息这种阈值设定方式更高。
在一实施例中，用户的基础身体参数、运动目的、既往训练经历等信息可通过与电视的 界面交互完成信息的录入。具体地，可按照一定的顺序对需预先录入的信息进行引导，通过界面交互实现信息录入。
图3a和图3b示出通过电视界面交互实现信息录入的示意图。从图3a和图3b中可以看到，电视界面上显示有多种信息录入的入口控件(如按钮、图片)，用户在采用点击、手势操控等交互方式后，可根据选择的入口控件进入相对应的信息录入界面。具体地，图3a采用的是按钮式的入口控件，用户可通过点击等操作选择如基础身体参数的按钮选项，进入到该基础身体参数的信息录入界面。图3b采用的是可点击的图片式入口控件，用户可通过点击等操作方式选择如既往训练经历的图片，进入到该既往训练经历的信息录入界面。可以理解地，入口控件的实现方式不进行具体的限定，用户通过电视的界面交互能够实现信息录入的目的即可。
图3c示出通过电视界面交互进行体适能评估的示意图。从图3c中可以看到，除了采用如基础身体参数等信息录入的方式，用户还可以通过电视界面选择体适能评估。具体地，用户可通过点击等操作选择体适能评估入口，进行体适能评估。
在一实施例中，用户的基础身体参数可包括如BMI、体脂率、跑1千公里的完成时间、肺活量、握力、卧推力、脚推力等参数。该基础身体参数反映的是用户基础的身体概况，对第一评价阈值的设定具有一定的参考意义。进一步地，第一评价阈值的设定可根据用户选择或系统推荐的动作(一组或多组)进行动态调整。若用户选择减脂的运动，则BMI、体脂率等可作为权重较高的项，以更精确地得到用户基础身体参数的评价(如优异、良好和一般等)。可以理解地，在不同动作的场景下，第一评价阈值的值会动态地进行调整，而不是固定的。
在一实施例中，系统推荐的运动动作可根据用户的运动目的决定，当用户的运动目的为运动减脂时，系统将主要推荐与减脂相关的动作。进一步地，运动目的除了包括具体的锻炼方向，还可以包括用户的运动期望。例如，用户的运动期望可以是得到充分、有效的运动效果，也可以是仅娱乐锻炼的运动期望。可以理解地，该运动期望也可作为其中的权重项调整第一评价阈值。
图4a示出通过电视界面录入用户基础身体参数的示意图。从图4a中可以看到，用户可在电视界面上通过填写的方式，将基础身体参数填入。可以理解地，用户不一定知道自身所有的基础身体参数，因此可采用实时录入的方式自动填入相关的基础身体信息。具体地，如图4a所示，用户可通过选择“实时获取”的按钮，触发与该项基础身体参数相关设备的连接操作。具体地，若用户想要填入自身的心率，则电视在检测到用户选择心率实时获取的需求时，将搜索如智能手环(具有测心率功能)等可测心率的电子设备，并与该电子设备进行连接。图4b和4ab示出了电视与智能手环进行通信连接的示意图。从图4b中可看到，电视在检测到可测心率的智能手环时，可在电视界面上显示可连接的智能手环。当用户选择自身所佩戴的手环后，如图4c所示，在电视界面上提示用户采用连接的智能手环进行心率测量操作。用户通过智能手环测量心率后，智能手环将心率发送到连接的电视。电视接收到心率后将跳转到电视基础身体参数录入的界面，并将心率(可取平均值)自动填入到电视基础身体参数界面上的心率项。
进一步地，如图4a所示，用户还可以通过相关联账号录入基础身体参数的功能。具体地，在图4a中，用户可通过选择“关联获取”的按钮，通过与电视具有关联账号关系的云端获取用户的基础身体参数，其中，这些基础身体参数可以是与电视具有关联账号关系的其他电子 设备上传到云端的。例如，与电视具有关联账号关系的智能手环将用户心率上传至关联账号的云端，或者，通过体脂称将用户体脂率上传到关联账号的云端。进一步地，该基础身体参数的关联获取不一定需通过云端实现，还可以是直接与电视具有关联账号关系的其他电子设备进行通信的方式实现。例如，电视发起基础身体参数获取的服务，关联账号的电子设备在接收到该服务后，可将用户相关的基础身体参数发送到电视，完成基础身体参数的快速录入。
图4d示出通过电视界面录入用户运动目的的示意图。从图4d可以看到，用户的运动目的具体可以是训练心肺能力、腰部力量、腿部力量等具体的目的，其中，对于这种有明确目标的运动目的，可认为用户对运动是抱有回报的运动期望，此时在设置第一评价阈值时，其系数可设置为1(100％)。进一步地，当用户的运动目的具体为训练心肺能力时，电视将推送与训练心肺能力相关的运动，使得用户能够更有目的性地完成训练。进一步地，如图4d所示，用户可通过选择“关联获取”的按钮，通过与电视具有关联账号关系的云端或电子设备获取用户的运动目的。可以理解地，用户在与电视具有关联账号关系的电子设备上，可能已经包括运动目的的信息。例如可通过采集关联账号电子设备上与用户相关的信息，可以得到用户正在进行的运动计划以及具体的运动习惯等，例如，通过用户手机获取用户有关的信息。在本实施例中，用户可通过关联账号关系的电子设备、云端将用户的运动目的快速录入到电视。
图4e示出通过电视界面录入用户既往训练经历的示意图。从图4e中可以看到，在电视界面上具有输入界面，用户可采用在界面中填写文字，或下拉选项框的方式录入既往训练经历，如跑步、游泳、俯卧撑、举杠铃等既往训练经历。进一步地，既往运动经历的个人评价可选择性地录入，如跑步、游泳为优异，俯卧撑、举杠铃为一般等。该既往运动经历的个人评价可用于计算或调整第一评价阈值。进一步地，如图4e所示，用户可通过选择“关联获取”的按钮，通过与电视具有关联账号关系的云端或电子设备获取用户的既往训练经历。具体地，如可通过智能手环中用户的跑步数据确定用户经常进行跑步。在一实施例中，如图4f所示，电视可在界面上提示用户是否继续跑步相关的训练，或者选择其他跑步难以锻炼到的身体部位的训练项目。用户可通过该界面选择喜好的训练项目。在一实施例中，如图4g所示，电视还可根据如跑步、游泳为优异，俯卧撑、举杠铃为一般等的个人评价，分析得到用户缺乏力量训练，可根据个人评价在电视界面上提示用户缺乏力量训练，是否进行力量方面的运动。可以理解地，用户在录入用户既往训练经历时，不仅可用于设置第一评价阈值，还可对用户的运动方向提供合理地建议，以让用户的锻炼更具针对性。
可以理解地，在得到用户的基础身体参数、运动目的以及既往训练经历等信息后，可通过加权计算的方式得到第一评价阈值，该第一评价阈值可看作是对用户的一个基础评价标准。具体地，可按照预设定的参数分类标准将基本信息参数分类，如分为以上所述的基础身体参数、运动目的和既往训练经历多种类型；然后对同一类别中的基本信息参数赋予第一权重，根据同一类别中的基本信息参数，加权计算得到类别的评价结果，例如，基础身体参数可分为多项参数，对每项同一类别中的参数赋予第一权重，通过加权计算可得到该基础身体参数类型的评价结果(可以是具体的数值)；最后对不同类别的基本信息参数赋予第二权重，根据不同类别的评价结果加权得到第一评价阈值，例如，在分别得到基础身体参数、运动目的和既往训练经历的评价结果后，赋予不同类别的基本信息参数第二权重，可加权计算得到第一评价阈值。
进一步地，除了根据用户的基础身体参数、运动目的、既往训练经历等设置第一评价阈值之外，还可以添加多一个热身阶段，基于第一评价阈值，根据热身阶段得到的参数数据得到第二评价阈值。具体地，在用户热身阶段期间，电视持续地采集用户图像信息，并根据图像信息检测用户的骨骼节点。在用户拉伸动作过程中，电视将利用检测到的骨骼节点计算用户动作完成时的关键角度、持续时长等参数。其中，这些参数可以是根据不同的动作所预先设置的，例如，头部向左或向右拉伸的倾斜角度、腰部向左或向右拉伸的倾斜角度、平板撑持续时长以及某些固定动作的持续时长等。进一步地，该热身阶段采集的参数也可以采用历史热身的相关数据。
在一实施例中，在进入正式的智能运动之前，用户可在电视界面上选择是否进行热身。具体地，图5示出通过电视界面进入热身场景的示意图，从图5中可以看到，电视界面上将提示用户是否热身，并说明热身过程有助于让动作做得更加规范有效，用户可选择确认进入到热身场景进行智慧运动前的热身动作。其中，具体的热身动作与智慧运动阶段的动作具有一定的关联性，例如智慧运动阶段进行的是头部训练类型的动作，则热身动作也相应地与头部训练热身相关。可以理解地，该热身阶段是用户可选的，通过该热身阶段得到的评价参数能够转换为数值表示的热身完成度，可更加精确地动态调整用户动作的评价标准，得到更为合理的第二评价阈值。
图6a和图6b示出指导用户做热身动作的示意图，如图6a和图6b所示，其分别对应两种不同类型的热身动作，分别是头部倾斜角度和腰部倾斜角度。可以理解地，对于不同类型的热身动作，其对应的关键角度或持续时长等参数是不同的，电视可按照一定顺序要求用户做出与其界面显示相同的热身动作，并对动作完成时的关键角度、持续时长等参数进行实时记录，以根据用户热身的结果确定用户当前的身体状况，灵活地调整训练过程的评价标准。
可以理解地，在用户进行热身时，电视的摄像头将持续监测用户的动作，并根据图像/视频识别的结果确定参数的具体数值。例如，如图6a所示，用户在进行腰部拉伸的热身运动时，将基于用户的骨骼节点，对图6a示的角度进行识别计算，得到用户所能达到的最小角度，如110度。同样地，如图6b所示，用户在进行头部拉伸的热身运动时，将基于用户的骨骼节点，对图6b示的角度进行识别计算，得到用户所能达到的最大角度，如130度。进一步地，除了对用户热身阶段中关键角度这类参数的计算，还可以是对如持续时长，跳跃高度等参数的计算，例如热身为平板撑时，该热身中需重点记录的参数为用户平板撑的持续时长。
在一实施例中，除了采用电视自带的摄像设备，还可以结合其他摄像设备完成角度识别及计算等功能。可以理解地，采用电视自带的摄像设备一般仅能得到2D图像，在对角度等空间观察要求高的参数的识别准确性一般。本申请实施例中，可结合其他摄像设备，从不同的观测角度检测如角度的参数。
图7a示出一采用多个摄像设备识别用户在进行头部拉伸热身动作时的倾斜角度的示意图。从图7a中可以看到，可以在用户身后，采用移动设备的摄像头对用户进行拍摄。结合电视正面对用户进行的拍摄，可从用户的正面和反面对用户进行多方位的拍摄，得到更多的角度信息。图7b示出另一采用多个摄像设备识别用户在进行头部拉伸热身动作时的倾斜角度。从图7b中可以看到，可采用3个摄像设备同时采集用户的倾斜角度，得到更多的角度信息。具体地，电视的摄像头负责从正面拍摄用户；图7b左下侧的移动设备(如平板电脑)，从用户背后的左侧拍摄用户；图7b右下侧的移动设备(如手机)，从用户背后的右侧拍摄用户， 与电视拍摄的用户图像、图7b左下侧移动设备拍摄的用户图像，可得到三个不同角度的用户图像；通过该三个用户图像更准确地计算用户头部倾斜角度。除了图7a或图7b所举的实施例，其他可行的多摄像设备方案(如4摄像头等方案)也应包含在本申请方案中。示例性地，对于具有多摄像头的一个电子设备中，如一台电视包括多个摄像头的情况，亦可通过电视多个摄像头拍摄得到的多个不同图像，帮助更准确地计算用户头部倾斜角度。在本申请实施例中，采用如图7a或图7b方案采集到的角度信息，可通过预设的算法(如神经网络算法)计算得到算法最优的用户头部倾斜角度，比单独采用电视摄像设备采集的2D图像计算的用户头部倾斜角度更准确。需要说明的是，本申请实施例采用的多摄像设备方案不局限于对角度的识别，还可以是对其他动作相关参数(如跳跃高度、跳跃距离等)的3D识别。进一步地，除了在热身过程中应用该多摄像设备方案，还可以在用户运动的过程中，实时对动作完成的相关参数进行识别及计算，能够提高评价的准确性。
进一步地，在获取用户当前动作的关键评价参数时，具体可包括如下步骤：
1)判断当前动作的关键评价参数的类型。
2)根据所述当前动作的关键评价参数的类型启动相应的监测模块。
3)采用所述监测模块获取当前动作的关键评价参数。
其中，监测模块包括摄像模块(摄像头)、计时模块、长度、距离测量模块、AI智能模块等，具体地，当关键评价参数的类型为动作角度，启动摄像模块，并采用摄像模块获取当前动作的动作角度；当关键评价参数的类型为时长，启动摄像模块和计时模块，并采用摄像模块和计时模块获取当前动作的时长。可以理解地，电视可包括摄像模块、计时模块等多种监测模块，在对不同动作进行监测时，根据关键评价参数的类型自动调用相应的模块。可以理解地，监测模块可以是电视内部配置的，也可以是外设设备提供的，在此不作限定。
进一步地，可利用用户动作完成时的关键角度、持续时长等参数，将该参数反馈到电视的动作评估模块，从而在基于第一评价阈值的基础上调整得到第二评价阈值。基于该第二评价阈值可在界面上显示对用户不同评价的分类结果。具体地，如第一评价阈值为100％(1)时，在该第一评价阈值下，当用户热身动作完成质量超过50％小于70％时，将该第一评价阈值根据预设的调整规则，如热身动作完成质量超过50％小于70％时下降20％，则第一评价阈值100％将下降到80％，得到根据热身情况临时调整的第二评价阈值80％。该第二评价阈值可看作是根据热身情况调整后的第一评价阈值，这里仅是为了区分热身后的数值微调对两者进行称呼上的区分。在用户热身动作完成质量超过50％小于70％时，电视界面将提示为入门级，并提醒用户坚持锻炼，通过模仿标准动作可提升等级(等级提升的同时可提高第一评价阈值)；同理地，当用户热身动作完成质量为大于70％小于90％时，界面将提示普通级；当用户热身动作完成质量为达到或超过90％时，界面将提示为专业级。用户在不同等级下的训练对应不同的评价标准，可满足不同用户的训练需求。
在一实施例中，还可以根据(调整后的)第一评价阈值，在界面上显示动作的校正提醒信息。具体地，图8a-图8c示出动作校正提醒信息的示意图。当在调整后的第一评价阈值下，用户动作完成质量在50％-70％内，从图8a中可以看到，在电视界面仅提供评价结果(如优异、良好和一般)，提醒用户可对照动作进行动作校正。当用户动作完成质量在70％-90％内，从图8b中可以看到，在电视界面将提示用户具体的哪些动作需要校正，以及大致如何校正的说明。当用户动作完成质量在大于90％内，从图8c中可以看到，在电视界面将分析显示出用 户动作与演示动作的差别，并具体地说明如何校正动作。在图8b和图8c中，将至少调用电视的摄像模块对用户动作进行实时检测，并按照预设定的判定集，输出如图8b和图8c的校正动作说明。可以理解地，调整后的第一评价阈值越高，说明评价标准越高，对用户动作的准确性要求也越高。对于不同的动作完成质量，可采用不同的动作校正方法。例如，当用户热身动作完成质量在50％-70％内，说明此时的评价标准是较低的，在用户运动时，用户仅需要按照动作进行模仿即可达到该评价标准下的要求(达到目前第一评价阈值标准下的50分以上即可)，此时仅提醒用户训练时根据动作正常做即可。当用户热身动作完成质量在70％-90％内，说明此时的评价标准一般，在用户运动时，可根据采集的图像信息判别用户在哪些动作上做得不好，提醒用户在具体的动作上认真模仿即可。当用户热身动作完成质量在大于90％内，说明此时的评价标准较高，在用户运动时，用户即使知道自己哪里动作做得不好也不知道该怎么校正过来，此时可根据预先设定的判定集，如动作为下蹲时，用户下蹲动作角度偏离过大的，可将用户下蹲动作的图和训练动作的图作对比，用户在界面上看到分析对比后一目了然，可有针对性地对动作进行校正，直至达到最佳的运动锻炼效果。
可以理解地，如用户运动前无热身或无热身历史数据，亦可直接根据第一评价阈值实现动作校正的功能，在此不再赘述。
在一实施例中，在用户进行运动的过程中，还可根据用户实时的动作完成评价(例如，高于90分的动作完成评价为优异，其他动作完成评价同理设置)，自适应地迭代动作的评价标准(即调整第二评价阈值)，并在界面上可视化地提升用户等级，直至达到最高的评价标准，其中，动作完成评价根据运动汇总的关键评价参数和当前的第一评价阈值确定。具体地，当用户前三次训练平均分高于90分(优异)时，用户等级可相应提升一级，如从普通级提升到专业级，具体地，如在80％的第一评价阈值的评价标准下，用户前三次训练平均分高于90分(优异)时，可将第一评价阈值提高10％。第一评价阈值变为90％。可以理解地，当第一评价阈值升高，说明评分的上限也在提高，用户需要在提高后的第一评价阈值下仍达到用户前三次训练平均分高于90分(第一平均阈值为90％的90分和第一平均阈值为80％的90分不同)时，才可继续提高用户等级或第一评价阈值，直至用户等级或第一评价阈值达到最高值；当用户前三次训练平均分低于70分(一般)时，用户等级可相应下降一级，如从普通级下降到入门级，并下调第一评价阈值。其中，当用户等级已经是入门级(最低等级)时，则不降级。
具体地，图9a-9b示出根据用户实时的动作完成情况自适应迭代动作评价标准(第一评价阈值)的界面示意图。如图9a所示，当用户前三次训练平均分高于90分时，电视将在界面上提示用户动作的评价标准已升级，并提示用户需做出更加标准的动作。当用户前三次训练平均分低于70分时，电视将在界面上提示用户动作的评价标准已降级，并提示用户从较低的标准重新提高评价标准。
在本申请实施例中，用户通过与电视的界面智能交互，实现了动作自适应评价的功能。具体地，首先电视通过屏幕显示的界面，获取用户的基本信息参数。该基本信息参数具体可分为基础身体参数、运动目的和既往训练经历等内容，还可以通过进入体适能评估获取基本信息参数。如图3a、3b所示，用户可通过点击选择等选择方式完成基本信息参数的录入。进一步地，基本信息参数可以是用户自己手动输入的，也可以是用户通过云端、同账号的电子设备等，实时同步获取到基本信息参数，并可在界面上自动完成填入。其中，在搜索云端、 同账号的电子设备时，如图4b、4c，用户可通过电视界面显示的提示信息选择正确可用的电子设备。在录入完用户的基本信息参数后，还可通过界面提示用户进行热身，以初步根据热身动作中的关键评价参数(用于评价用户动作完成情况的参数，该关键评价参数可以有多个，如用户头部的倾斜角度、腰部倾斜角度、膝盖弯曲角度等)，动态对基本信息参数设定的第一评价阈值进行调整，有利于根据不同用户的身体状况设定更合理的评价标准。最后，在用户进行运动时，可通过实时获取的动作中的关键评价参数对当前的第一评价阈值进行实时调整，根据用户动作完成的情况，提高或降低第一评价阈值，在用户动作做得较标准时，提出更高的要求，或者，在用户动作做得不是很标准时，适当降低要求，提高用户参与的积极性。以上实现的流程，用户全程可通过电视界面与电视完成智能的信息交互，电视将根据用户具体输入的信息(包括摄像设备拍摄的图像信息)，作出智能反应，针对不同用户提供差异化的运动服务，动态、灵活、合理地调整评价标准。
在本申请实施例中，通过获取用户的基本信息参数设定第一评价阈值，可根据不同用户的身体状况设定更合理的评价标准；在用户运动时，通过获取当前用户动作的关键评价参数，以及设定好的第一评价阈值，确定用户的动作完成评价，以根据用户动作实际的完成情况，灵活调整第一评价阈值。本申请实施例中，能够给用户提供差异化的运动服务，使得用户能够进行有针对性的身体锻炼，有效提高用户的身体体质。
本申请还提供一种计算机存储介质，该计算机可读存储介质上存储有计算机程序，该计算机程序被处理器执行时实现实施例中动作自适应评价方法的步骤，为避免重复，此处不一一赘述。
应当明确，所描述的实施例仅仅是本申请一部分实施例，而不是全部的实施例。基于本申请中的实施例，本领域普通技术人员在没有做出创造性劳动前提下所获得的所有其它实施例，都属于本申请保护的范围。
所属领域的技术人员可以清楚地了解到，为了描述的方便和简洁，仅以上述各功能单元、模块的划分进行举例说明，实际应用中，可以根据需要而将上述功能分配由不同的功能单元、模块完成，即将装置的内部结构划分成不同的功能单元或模块，以完成以上描述的全部或者部分功能。
以上实施例仅用以说明本申请的技术方案，而非对其限制；尽管参照前述实施例对本申请进行了详细的说明，本领域的普通技术人员应当理解：其依然可对前述各实施例所存储的技术方案进行修改，或者对其中部分技术特征进行等同替换；而这些修改或者替换，并不使相应技术方案的本质脱离本申请各实施例技术方案的精神和范围，均应包含在本申请的保护范围内。

Claims (19)

  1. 一种动作自适应评价方法，应用于带屏幕的电子设备，所述动作在所述屏幕上显示，其特征在于，包括：
    获取用户的基本信息参数；
    根据所述基本信息参数得到第一评价阈值，其中，所述第一评价阈值用于提供评价标准；
    获取所述用户当前动作的关键评价参数；
    根据所述关键评价参数和所述第一评价阈值确定所述用户的动作完成评价；
    根据所述动作完成评价调整所述第一评价阈值。
  2. 根据权利要求1所述的方法，其特征在于，在所述根据所述基本信息参数得到第一评价阈值之后，还包括：
    获取所述用户热身动作的评价参数；
    根据所述评价参数确定用户的热身完成度；
    根据所述热身完成度预调整所述第一评价阈值。
  3. 根据权利要求1所述的方法，其特征在于，所述获取用户的基本信息参数，包括：
    发起查找相关联账号的云端或电子设备请求；
    接收所述相关联账号的云端或电子设备的回复，确定存在所述相关联账号的云端或电子设备；
    发起所述基本信息参数的调用请求；
    获取所述相关联账号的云端或电子设备发送的所述基本信息参数。
  4. 根据权利要求1所述的方法，其特征在于，所述根据所述基本信息参数得到第一评价阈值，包括：
    对所述基本信息参数进行分类；
    对同一类别中的所述基本信息参数赋予第一权重，根据所述同一类别中的所述基本信息参数，加权计算得到类别的评价结果；
    对不同类别的所述基本信息参数赋予第二权重，根据所述不同类别的所述评价结果加权得到所述第一评价阈值。
  5. 根据权利要求1所述的方法，其特征在于，所述获取所述用户当前动作的关键评价参数，包括：
    判断当前动作的关键评价参数的类型；
    根据所述当前动作的关键评价参数的类型启动相应的监测模块；
    采用所述监测模块获取当前动作的关键评价参数。
  6. 根据权利要求5所述的方法，其特征在于，所述监测模块包括摄像模块和计时模块，所述获取所述用户当前动作的关键评价参数，包括：
    判断当前动作的关键评价参数的类型；
    若所述关键评价参数的类型为动作角度，启动所述摄像模块，并采用所述摄像模块获取当前动作的所述动作角度；
    若所述关键评价参数的类型为时长，启动所述摄像模块和所述计时模块，并采用所述摄像模块和所述计时模块获取当前动作的所述时长。
  7. 根据权利要求1所述的方法，其特征在于，所述根据所述关键评价参数和所述第一评 价阈值确定所述用户的动作完成评价，包括：
    按照预设定的参数分类标准将所述基本信息参数分类；
    根据所述第一评价阈值、分类好的所述基本信息参数，以及预设的评价表，确定所述动作完成评价，其中，所述评价表存储有所述基本信息参数与所述动作完成评价的映射信息。
  8. 根据权利要求1所述的方法，其特征在于，所述根据所述动作完成评价调整所述第一评价阈值，包括：
    判断所述动作完成评价是否达到预设的阈值调整条件，其中，所述阈值调整条件包括一个或多个；
    若达到所述阈值调整条件，根据所述阈值调整条件调整所述第一评价阈值。
  9. 根据权利要求1-8任一项所述的方法，其特征在于，所述基本信息参数包括基础身体参数、运动目的和既往训练经历，或者包括采用体适能评估得到的参数。
  10. 一种带屏幕的电子设备，包括存储器、处理器以及存储在所述存储器中并可在所述处理器上运行的计算机程序，其特征在于，所述处理器执行所述计算机程序时实现如下步骤：
    获取用户的基本信息参数；
    根据所述基本信息参数得到第一评价阈值，其中，所述第一评价阈值用于提供评价标准；
    获取所述用户当前动作的关键评价参数；
    根据所述关键评价参数和所述第一评价阈值确定所述用户的动作完成评价；
    根据所述动作完成评价调整所述第一评价阈值。
  11. 根据权利要求10所述的电子设备，其特征在于，所述处理器执行所述计算机程序，还实现如下步骤：
    获取所述用户热身动作的评价参数；
    根据所述评价参数确定用户的热身完成度；
    根据所述热身完成度预调整所述第一评价阈值。
  12. 根据权利要求10所述的电子设备，其特征在于，所述处理器执行所述计算机程序，实现所述获取用户的基本信息参数时，包括：
    发起查找相关联账号的云端或电子设备请求；
    接收所述相关联账号的云端或电子设备的回复，确定存在所述相关联账号的云端或电子设备；
    发起所述基本信息参数的调用请求；
    获取所述相关联账号的云端或电子设备发送的所述基本信息参数。
  13. 根据权利要求10所述的电子设备，其特征在于，所述处理器执行所述计算机程序，实现所述根据所述基本信息参数得到第一评价阈值时，包括：
    对所述基本信息参数进行分类；
    对同一类别中的所述基本信息参数赋予第一权重，根据所述同一类别中的所述基本信息参数，加权计算得到类别的评价结果；
    对不同类别的所述基本信息参数赋予第二权重，根据所述不同类别的所述评价结果加权得到所述第一评价阈值。
  14. 根据权利要求10所述的电子设备，其特征在于，所述处理器执行所述计算机程序，实现所述获取当前动作的关键评价参数时，包括：
    判断当前动作的关键评价参数的类型；
    根据所述当前动作的关键评价参数的类型启动相应的监测模块；
    采用所述监测模块获取当前动作的关键评价参数。
  15. 根据权利要求14所述的电子设备，其特征在于，所述监测模块包括摄像模块和计时模块，所述处理器执行所述计算机程序，实现所述获取所述用户当前动作的关键评价参数时，包括：
    判断当前动作的关键评价参数的类型；
    若所述关键评价参数的类型为动作角度，启动所述摄像模块，并采用所述摄像模块获取当前动作的所述动作角度；
    若所述关键评价参数的类型为时长，启动所述摄像模块和所述计时模块，并采用所述摄像模块和所述计时模块获取当前动作的所述时长。
  16. 根据权利要求10所述的电子设备，其特征在于，所述处理器执行所述计算机程序，实现所述根据所述关键评价参数和所述第一评价阈值确定用户的动作完成评价时，包括：
    按照预设定的参数分类标准将所述基本信息参数分类；
    根据所述第一评价阈值、分类好的所述基本信息参数，以及预设的评价表，确定所述动作完成评价，其中，所述评价表存储有所述基本信息参数与所述动作完成评价的映射信息。
  17. 根据权利要求10所述的电子设备，其特征在于，所述处理器执行所述计算机程序，实现所述根据所述动作完成评价调整所述第一评价阈值时，包括：
    判断所述动作完成评价是否达到预设的阈值调整条件，其中，所述阈值调整条件包括一个或多个；
    若达到所述阈值调整条件，根据所述阈值调整条件调整所述第一评价阈值。
  18. 根据权利要求10-17任一项所述的电子设备，其特征在于，所述基本信息参数包括基础身体参数、运动目的和既往训练经历，或者包括采用体适能评估得到的参数。
  19. 一种计算机可读存储介质，所述计算机可读存储介质存储有计算机程序，其特征在于，所述计算机程序被处理器执行时实现如权利要求1至9任一项所述动作自适应评价方法的步骤。
PCT/CN2021/129715 2020-11-12 2021-11-10 动作自适应评价方法、电子设备和存储介质 WO2022100597A1 (zh)

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