WO2021004398A1 - 一种运动数据监测方法和装置 - Google Patents

一种运动数据监测方法和装置 Download PDF

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Publication number
WO2021004398A1
WO2021004398A1 PCT/CN2020/100223 CN2020100223W WO2021004398A1 WO 2021004398 A1 WO2021004398 A1 WO 2021004398A1 CN 2020100223 W CN2020100223 W CN 2020100223W WO 2021004398 A1 WO2021004398 A1 WO 2021004398A1
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Prior art keywords
electronic device
user
ground
angular velocity
acceleration
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PCT/CN2020/100223
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English (en)
French (fr)
Inventor
徐腾
陈霄汉
杨斌
李玥
Original Assignee
华为技术有限公司
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Priority to EP20836789.6A priority Critical patent/EP3988183A4/en
Priority to US17/624,171 priority patent/US20220362654A1/en
Publication of WO2021004398A1 publication Critical patent/WO2021004398A1/zh

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    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01C—MEASURING DISTANCES, LEVELS OR BEARINGS; SURVEYING; NAVIGATION; GYROSCOPIC INSTRUMENTS; PHOTOGRAMMETRY OR VIDEOGRAMMETRY
    • G01C22/00—Measuring distance traversed on the ground by vehicles, persons, animals or other moving solid bodies, e.g. using odometers, using pedometers
    • G01C22/006—Pedometers
    • A—HUMAN NECESSITIES
    • A63—SPORTS; GAMES; AMUSEMENTS
    • A63B—APPARATUS FOR PHYSICAL TRAINING, GYMNASTICS, SWIMMING, CLIMBING, OR FENCING; BALL GAMES; TRAINING EQUIPMENT
    • A63B71/00—Games or sports accessories not covered in groups A63B1/00 - A63B69/00
    • A63B71/06—Indicating or scoring devices for games or players, or for other sports activities
    • A—HUMAN NECESSITIES
    • A63—SPORTS; GAMES; AMUSEMENTS
    • A63B—APPARATUS FOR PHYSICAL TRAINING, GYMNASTICS, SWIMMING, CLIMBING, OR FENCING; BALL GAMES; TRAINING EQUIPMENT
    • A63B71/00—Games or sports accessories not covered in groups A63B1/00 - A63B69/00
    • A63B71/06—Indicating or scoring devices for games or players, or for other sports activities
    • A63B71/0619—Displays, user interfaces and indicating devices, specially adapted for sport equipment, e.g. display mounted on treadmills
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00—Measuring for diagnostic purposes; Identification of persons
    • A61B5/103—Detecting, measuring or recording devices for testing the shape, pattern, colour, size or movement of the body or parts thereof, for diagnostic purposes
    • A61B5/11—Measuring movement of the entire body or parts thereof, e.g. head or hand tremor, mobility of a limb
    • A61B5/112—Gait analysis
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00—Measuring for diagnostic purposes; Identification of persons
    • A61B5/103—Detecting, measuring or recording devices for testing the shape, pattern, colour, size or movement of the body or parts thereof, for diagnostic purposes
    • A61B5/11—Measuring movement of the entire body or parts thereof, e.g. head or hand tremor, mobility of a limb
    • A61B5/1121—Determining geometric values, e.g. centre of rotation or angular range of movement
    • A61B5/1122—Determining geometric values, e.g. centre of rotation or angular range of movement of movement trajectories
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00—Measuring for diagnostic purposes; Identification of persons
    • A61B5/103—Detecting, measuring or recording devices for testing the shape, pattern, colour, size or movement of the body or parts thereof, for diagnostic purposes
    • A61B5/11—Measuring movement of the entire body or parts thereof, e.g. head or hand tremor, mobility of a limb
    • A61B5/1123—Discriminating type of movement, e.g. walking or running
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00—Measuring for diagnostic purposes; Identification of persons
    • A61B5/68—Arrangements of detecting, measuring or recording means, e.g. sensors, in relation to patient
    • A61B5/6801—Arrangements of detecting, measuring or recording means, e.g. sensors, in relation to patient specially adapted to be attached to or worn on the body surface
    • A61B5/6802—Sensor mounted on worn items
    • A61B5/681—Wristwatch-type devices
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00—Measuring for diagnostic purposes; Identification of persons
    • A61B5/72—Signal processing specially adapted for physiological signals or for diagnostic purposes
    • A61B5/7235—Details of waveform analysis
    • A61B5/7264—Classification of physiological signals or data, e.g. using neural networks, statistical classifiers, expert systems or fuzzy systems
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01C—MEASURING DISTANCES, LEVELS OR BEARINGS; SURVEYING; NAVIGATION; GYROSCOPIC INSTRUMENTS; PHOTOGRAMMETRY OR VIDEOGRAMMETRY
    • G01C19/00—Gyroscopes; Turn-sensitive devices using vibrating masses; Turn-sensitive devices without moving masses; Measuring angular rate using gyroscopic effects
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01P—MEASURING LINEAR OR ANGULAR SPEED, ACCELERATION, DECELERATION, OR SHOCK; INDICATING PRESENCE, ABSENCE, OR DIRECTION, OF MOVEMENT
    • G01P13/00—Indicating or recording presence, absence, or direction, of movement
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01P—MEASURING LINEAR OR ANGULAR SPEED, ACCELERATION, DECELERATION, OR SHOCK; INDICATING PRESENCE, ABSENCE, OR DIRECTION, OF MOVEMENT
    • G01P15/00—Measuring acceleration; Measuring deceleration; Measuring shock, i.e. sudden change of acceleration
    • G01P15/18—Measuring acceleration; Measuring deceleration; Measuring shock, i.e. sudden change of acceleration in two or more dimensions
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B2503/00—Evaluating a particular growth phase or type of persons or animals
    • A61B2503/10—Athletes
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B2505/00—Evaluating, monitoring or diagnosing in the context of a particular type of medical care
    • A61B2505/09—Rehabilitation or training
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B2562/00—Details of sensors; Constructional details of sensor housings or probes; Accessories for sensors
    • A61B2562/02—Details of sensors specially adapted for in-vivo measurements
    • A61B2562/0219—Inertial sensors, e.g. accelerometers, gyroscopes, tilt switches
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00—Measuring for diagnostic purposes; Identification of persons
    • A61B5/74—Details of notification to user or communication with user or patient ; user input means
    • A61B5/742—Details of notification to user or communication with user or patient ; user input means using visual displays
    • A—HUMAN NECESSITIES
    • A63—SPORTS; GAMES; AMUSEMENTS
    • A63B—APPARATUS FOR PHYSICAL TRAINING, GYMNASTICS, SWIMMING, CLIMBING, OR FENCING; BALL GAMES; TRAINING EQUIPMENT
    • A63B71/00—Games or sports accessories not covered in groups A63B1/00 - A63B69/00
    • A63B71/06—Indicating or scoring devices for games or players, or for other sports activities
    • A63B71/0619—Displays, user interfaces and indicating devices, specially adapted for sport equipment, e.g. display mounted on treadmills
    • A63B2071/0658—Position or arrangement of display
    • A63B2071/0661—Position or arrangement of display arranged on the user
    • A—HUMAN NECESSITIES
    • A63—SPORTS; GAMES; AMUSEMENTS
    • A63B—APPARATUS FOR PHYSICAL TRAINING, GYMNASTICS, SWIMMING, CLIMBING, OR FENCING; BALL GAMES; TRAINING EQUIPMENT
    • A63B2220/00—Measuring of physical parameters relating to sporting activity
    • A63B2220/30—Speed
    • A63B2220/34—Angular speed
    • A—HUMAN NECESSITIES
    • A63—SPORTS; GAMES; AMUSEMENTS
    • A63B—APPARATUS FOR PHYSICAL TRAINING, GYMNASTICS, SWIMMING, CLIMBING, OR FENCING; BALL GAMES; TRAINING EQUIPMENT
    • A63B2220/00—Measuring of physical parameters relating to sporting activity
    • A63B2220/40—Acceleration
    • A—HUMAN NECESSITIES
    • A63—SPORTS; GAMES; AMUSEMENTS
    • A63B—APPARATUS FOR PHYSICAL TRAINING, GYMNASTICS, SWIMMING, CLIMBING, OR FENCING; BALL GAMES; TRAINING EQUIPMENT
    • A63B2220/00—Measuring of physical parameters relating to sporting activity
    • A63B2220/80—Special sensors, transducers or devices therefor
    • A63B2220/83—Special sensors, transducers or devices therefor characterised by the position of the sensor
    • A63B2220/836—Sensors arranged on the body of the user
    • A—HUMAN NECESSITIES
    • A63—SPORTS; GAMES; AMUSEMENTS
    • A63B—APPARATUS FOR PHYSICAL TRAINING, GYMNASTICS, SWIMMING, CLIMBING, OR FENCING; BALL GAMES; TRAINING EQUIPMENT
    • A63B2225/00—Miscellaneous features of sport apparatus, devices or equipment
    • A63B2225/50—Wireless data transmission, e.g. by radio transmitters or telemetry
    • A—HUMAN NECESSITIES
    • A63—SPORTS; GAMES; AMUSEMENTS
    • A63B—APPARATUS FOR PHYSICAL TRAINING, GYMNASTICS, SWIMMING, CLIMBING, OR FENCING; BALL GAMES; TRAINING EQUIPMENT
    • A63B2230/00—Measuring physiological parameters of the user
    • A63B2230/62—Measuring physiological parameters of the user posture

Definitions

  • This application relates to the field of terminals, and in particular to a method and device for monitoring exercise data.
  • the wearable device can be worn directly on the body, or a portable device integrated into the user's clothes or accessories.
  • wearable devices such as energy bracelets and pedometer shoes can be used to record parameters such as the number of steps moved, distance, and calories consumed during running.
  • the actions included can include walking, trotting, jumping, lateral movement, etc.
  • the existing smart wearable devices cannot perform well. Monitoring these motion characteristics cannot provide users with a better sports experience.
  • the embodiments of the present application provide a kind of exercise data monitoring, which can monitor the exercise data of the user's diversified sports (for example, basketball) in real time, and improve the user's exercise experience.
  • diversified sports for example, basketball
  • an embodiment of the application provides a method for monitoring exercise data, including: an electronic device collects a user's angular velocity signal and an acceleration signal; the electronic device acquires the waveform characteristics of the angular velocity signal based on the angular velocity signal, and acquires the waveform characteristics of the acceleration signal based on the acceleration signal.
  • the electronic device determines the user's gait characteristics according to the waveform characteristics of the angular velocity signal and the waveform characteristics of the acceleration signal.
  • the gait characteristics include the flight time from the user's foot off the ground to the time before touching the ground; the electronic device determines the movement data according to the gait characteristics , Movement data includes jump height.
  • the electronic device can acquire the user's motion data by collecting the user's angular velocity signal and acceleration signal, and processing the angular velocity signal and acceleration signal.
  • the above-mentioned user’s angular velocity signal and acceleration signal can be collected by six-axis sensors. The cost is low and there is no need to perform time synchronization transmission processing and data fusion processing on multiple sensor units. It can monitor the user’s diversified sports activities in real time (for example, basketball Exercise data (such as jumping height) to improve the user’s exercise experience.
  • the electronic device collecting the angular velocity signal and acceleration signal of the user includes: the electronic device collecting the angular velocity signal and acceleration signal of the user's foot or leg.
  • the user's feet include the user's instep, sole and other parts, and the user's legs include the user's ankle, calf, knee, and thigh.
  • the electronic device determining the motion data according to the gait feature includes: the electronic device determines the first component of the jump height according to the flight time; the electronic device determines the second component of the jump height according to the acceleration signal integration during the flight time ; The electronic device determines the jump height according to the first component and the second component.
  • the embodiment of the present application combines the flight time and the acceleration signal integration within the flight time to determine the jumping height, which can improve the accuracy of the jumping height.
  • the electronic device determining the first component of the jump height according to the flight time includes: Among them, H t represents the first component, ⁇ t represents the flight time, and g represents the acceleration of gravity; the second component of the jump height determined by the electronic device according to the acceleration integral during the flight time includes: Wherein, H a represents a second component, ⁇ t represents the flight time, t 0 represents the initial time of flight time, k is a calibration parameter, acc z represents an acceleration signal component of a user in the local horizontal coordinate system of the z-axis direction; electronic apparatus according to the first The first component and the second component to determine the jump height include: when
  • the electronic device determining the user's gait characteristics according to the waveform characteristics of the angular velocity signal and the waveform characteristics of the acceleration signal includes: the electronic device determines the user's gait characteristics according to the waveform characteristics of the angular velocity signal, the waveform characteristics of the acceleration signal, and the attitude angle matrix The user's gait characteristics and the attitude angle matrix are determined based on the angular velocity signal and the acceleration signal.
  • the posture angle matrix includes the angle of the carrier coordinate system of the electronic device relative to the local horizontal coordinate system over a period of time, which can be used to represent the posture characteristics of the user. In this way, when the user's action changes are more complicated or the action changes quickly, the user's action can be further recognized according to the posture angle matrix, and the motion data can be determined more accurately.
  • the method further includes: the electronic device constructs a posture angle correction matrix according to preset conditions, where the preset conditions include a preset user's foot speed before the ground is 0 and the vertical displacement is 0, and After the user's foot touches the ground, the speed is 0 and the vertical displacement is 0; the electronic device corrects the attitude angle matrix according to the attitude angle correction matrix.
  • the preset conditions include a preset user's foot speed before the ground is 0 and the vertical displacement is 0, and After the user's foot touches the ground, the speed is 0 and the vertical displacement is 0; the electronic device corrects the attitude angle matrix according to the attitude angle correction matrix.
  • the electronic device correcting the attitude angle matrix according to the attitude angle correction matrix includes:
  • R c C*R
  • C represents the posture angle correction matrix
  • R is the posture angle matrix
  • R c is the posture angle matrix after correction
  • ⁇ , ⁇ , ⁇ are the rotation angles of the x-axis, y-axis, and z-axis in the local horizontal coordinate system, respectively
  • V x , v y , v z are the velocity components in the x-axis, y-axis, and z-axis directions respectively
  • H z is the displacement in the z-axis direction
  • S is the displacement of the user's foot from the ground to before touching the ground
  • ⁇ t is the time interval from when the user's foot is off the ground to before it touches the ground.
  • the motion data further includes at least one of the moving distance, the number of steps, and the moving speed of the user.
  • the exercise data may also include the user's heartbeat, body temperature, calorie consumption, etc., which are not limited in this application.
  • the method further includes: the electronic device performs zero-speed correction according to the local minimum point of the moving speed in the time interval from ground contact to ground clearance, and/or, the electronic device performs zero-speed correction according to the ground contact to ground clearance time interval.
  • the distance correction is performed on the local minimum point of the displacement in the vertical direction in the time interval.
  • the method further includes: the electronic device classifies actions according to the waveform characteristics of the angular velocity signal, the waveform characteristics of the acceleration signal, and the motion data, and the action classification results include vertical jump, running jump, and lateral movement. At least one. In this way, users can get a clearer understanding of their own movement based on the action classification results, which can improve user experience.
  • the method further includes: the electronic device performs template matching between the exercise data and the database data, and outputs the user's role classification and/or character tag, which enhances the user's interest in participating in sports and can improve the user Experience.
  • an embodiment of the present application provides an electronic device, including: an acquisition unit, configured to collect a user's angular velocity signal and acceleration signal; an acquisition unit, configured to acquire waveform characteristics of the angular velocity signal based on the angular velocity signal, and acquire acceleration based on the acceleration signal
  • the waveform characteristics of the signal; the determining unit is used to determine the gait characteristics of the user according to the waveform characteristics of the angular velocity signal and the waveform characteristics of the acceleration signal.
  • the gait characteristics include the flight time from the user's foot off the ground to before the ground touches; the determining unit It is also used to determine motion data according to gait characteristics, and the motion data includes jump height.
  • the collecting unit is used to collect the angular velocity signal and acceleration signal of the user's foot or leg.
  • the determining unit is configured to: determine the first component of the jump height according to the flight time; determine the second component of the jump height according to the acceleration signal integration during the flight time; determine according to the first component and the second component Jump height.
  • H t represents the first component
  • ⁇ t represents the flight time
  • g represents the acceleration of gravity
  • H a represents a second component
  • [Delta] t represents the flight time
  • the initial time t 0 indicates the flight time
  • k is a calibration parameter
  • ACC z represents an acceleration signal component of a user in the local horizontal coordinate system of the z-axis direction
  • the threshold ⁇ H is the preset threshold
  • H is the jump height.
  • the determining unit is configured to determine the user's gait characteristics according to the waveform characteristics of the angular velocity signal, the waveform characteristics of the acceleration signal, and an attitude angle matrix, and the attitude angle matrix is determined according to the angular velocity signal and the acceleration signal.
  • the determining unit is further configured to: construct a posture angle correction matrix according to preset conditions.
  • the preset conditions include a preset user’s foot speed before the ground is 0 and vertical displacement is 0, and the user After the foot touches the ground, the velocity is 0 and the vertical displacement is 0; the attitude angle matrix is corrected according to the attitude angle correction matrix.
  • R c C*R
  • C represents the posture angle correction matrix
  • R is the posture angle matrix
  • R c is the posture angle matrix after correction
  • ⁇ , ⁇ , ⁇ are the rotation angles of the x-axis, y-axis, and z-axis in the local horizontal coordinate system, respectively
  • V x , v y , v z are the velocity components in the x-axis, y-axis, and z-axis directions respectively
  • H z is the displacement in the z-axis direction
  • S is the displacement of the user's foot from the ground to before touching the ground
  • ⁇ t is the time interval from when the user's foot is off the ground to before it touches the ground.
  • the motion data further includes at least one of the moving distance, the number of steps, and the moving speed of the user.
  • the determining unit is further configured to: perform a zero-speed correction according to the local minimum point of the moving speed in the time interval from touchdown to ground clearance, and/or, according to the time interval from touchdown to ground clearance The local minimum point of displacement in the vertical direction is distance corrected.
  • the determining unit is further used to classify actions according to the waveform characteristics of the angular velocity signal, the waveform characteristics of the acceleration signal, and the motion data, and the result of the action classification includes at least one of vertical jump, running jump, and lateral movement.
  • the result of the action classification includes at least one of vertical jump, running jump, and lateral movement.
  • the determining unit is further used to perform template matching between the motion data and the database data, and output the role classification and/or person tag of the user.
  • embodiments of the present application provide a computer-readable storage medium, including instructions, which when run on a computer, cause the computer to execute any one of the methods provided in the first aspect.
  • embodiments of the present application provide a computer program product containing instructions, which when run on a computer, cause the computer to execute any of the methods provided in the first aspect.
  • an embodiment of the present application provides a chip system, which includes a processor and may also include a memory, configured to implement any of the methods provided in the first aspect.
  • the chip system can be composed of chips, or can include chips and other discrete devices.
  • the embodiments of the present application also provide a device, which may be a processing device, an electronic device, or a chip.
  • the device includes a processor, configured to implement any one of the methods provided in the first aspect.
  • the device may also include a memory for storing program instructions and data.
  • the memory may be a memory integrated in the device or an off-chip memory provided outside the device.
  • the memory is coupled with the processor, and the processor can call and execute the program instructions stored in the memory to implement any one of the methods provided in the first aspect.
  • the device may also include a communication interface, which is used for the device to communicate with other devices.
  • FIG. 1 is a schematic structural diagram of an electronic device provided by an embodiment of the application.
  • FIG. 2 is a schematic diagram of a roll angle, a pitch angle, and a yaw angle provided by an embodiment of the application;
  • Figure 3 is a schematic diagram of a local horizontal coordinate system provided by an embodiment of the application.
  • FIG. 4 is a schematic diagram of the product form of an electronic device provided by an embodiment of the application.
  • FIG. 5 is a schematic flowchart of a method suitable for exercise data monitoring provided by an embodiment of the application
  • FIG. 6 is a schematic diagram of a waveform diagram of a gyroscope sensor and an acceleration sensor for constant speed walking and vertical jump provided by an embodiment of the application;
  • FIG. 7 is a schematic diagram of correcting speed or Z-axis displacement provided by an embodiment of the application.
  • FIG. 8 is a schematic diagram of a flow of classifying and recognizing action types through a classifier based on respective waveform characteristics and motion data of a gyroscope and an acceleration sensor according to an embodiment of the application;
  • FIG. 9 is a schematic diagram of vertical jump, running jump, and lateral movement provided by an embodiment of the application.
  • FIG. 10 is a schematic diagram of a template matching process provided by an embodiment of the application.
  • FIG. 11 is a schematic structural diagram of yet another electronic device provided by an embodiment of the application.
  • the embodiment of the present application provides a method for monitoring sports data, which is applied to sports data monitoring scenarios of various sports, such as sports data monitoring scenarios of basketball, volleyball, badminton, long jump, high jump, hurdles, parkour, etc.
  • Movement data can include flight time, jump height, number of jumps, movement distance, number of steps, movement speed, etc.
  • the electronic device may specifically be a smart foot ring 100.
  • the smart foot ring 100 may include a processor 110, a sensor module 120, a communication module 130, a power supply 140, a display screen 150, and so on.
  • the sensor module may include a gyroscope sensor 120A and an acceleration sensor 120B.
  • the structure illustrated in the embodiment of the present invention does not constitute a limitation on the smart foot ring 100. It may include more or fewer components than shown, or combine certain components, or split certain components, or arrange different components.
  • the illustrated components can be implemented in hardware, software, or a combination of software and hardware.
  • the processor 110 may include one or more processing units.
  • the processor 110 may include an application processor (AP), a modem processor, a graphics processing unit (GPU), and an image signal processor. (image signal processor, ISP), controller, memory, video codec, digital signal processor (digital signal processor, DSP), baseband processor, and/or neural network processor (Neural-network Processing Unit, NPU) Wait.
  • AP application processor
  • modem processor modem processor
  • GPU graphics processing unit
  • image signal processor image signal processor
  • ISP image signal processor
  • controller memory
  • video codec digital signal processor
  • DSP digital signal processor
  • baseband processor baseband processor
  • neural network processor Neural-network Processing Unit, NPU
  • the controller may be a decision maker who directs the various components of the smart foot ring 100 to coordinate work according to instructions. It is the nerve center and command center of Smart Foot Ring 100.
  • the controller generates operation control signals according to the instruction operation code and timing signals to complete the control of fetching and executing instructions.
  • a memory may also be provided in the processor 110 to store instructions and data.
  • the memory in the processor is a cache memory. It can save the instructions or data that the processor has just used or recycled. If the processor needs to use the instruction or data again, it can be directly called from the memory. It avoids repeated access and reduces the waiting time of the processor, thereby improving the efficiency of the system.
  • the gyro sensor 120A can be used to determine the movement posture of the smart foot ring 100.
  • the angular velocity of the smart foot ring 100 around the three axes of the local horizontal coordinate system ie, x-axis, y-axis, and z-axis
  • the gyroscope sensor can also be called three-axis Gyro.
  • the gyroscope sensor can respectively sense all-round dynamic information of up and down tilt, front and back tilt, and left and right tilt.
  • the attitude angle of the smart anklet refers to the angle between the carrier coordinate system and the local horizontal coordinate system, which can be represented by three angles: roll angle, pitch angle, and yaw angle.
  • the gyroscope sensor can be used for shooting anti-shake. Exemplarily, when the shutter is pressed, the gyroscope sensor monitors the jitter angle of the smart foot ring 100, and calculates the distance that the lens module needs to compensate according to the angle, so that the lens can counteract the jitter of the smart foot ring 100 through reverse movement to achieve anti-shake .
  • the gyroscope sensor can also be used for navigation and somatosensory game scenes.
  • the coordinate system of the gyroscope sensor is the local horizontal coordinate system.
  • the origin O of the local horizontal coordinate system is located at the center of mass of the carrier (ie, the device containing the gyroscope sensor, such as the electronic device 100), the x-axis points east (E) along the local latitude, and the y-axis points along the local meridian.
  • North (N) the z-axis is perpendicular to the local horizontal plane, points upward along the local geographic vertical, and forms a right-handed rectangular coordinate system with the x-axis and y-axis.
  • the plane formed by the x-axis and the y-axis is the local horizontal plane
  • the plane formed by the y-axis and the z-axis is the local meridian. Therefore, it is understandable that the coordinate system of the gyroscope sensor is: taking the gyroscope sensor as the origin O, pointing east along the local latitude line as the x-axis, pointing north along the local meridian line as the y-axis, and pointing upward along the local geographic vertical line ( That is, the opposite direction of the geographic vertical) is the z-axis.
  • the acceleration sensor 120B can monitor the magnitude of the acceleration of the smart foot ring 100 in various directions (ie, the x, y, and z axes of the local horizontal coordinate system), and the acceleration sensor can also be called a three-axis accelerator. When the smart foot ring 100 is stationary, the magnitude and direction of gravity can be monitored. It can also be used to identify the terminal's posture, apply to horizontal and vertical screen switching, pedometer and other applications.
  • the three-axis accelerator and the three-axis gyroscope together can be called a six-axis sensor.
  • the communication module 130 can provide applications on the smart foot ring 100 including wireless local area networks (WLAN) (for example, wireless fidelity (WiFi)), Bluetooth, global navigation satellite system, GNSS), frequency modulation (FM), near field communication (NFC), infrared technology (infrared, IR) and other wireless communication solutions communication processing module.
  • WLAN wireless local area networks
  • FM frequency modulation
  • NFC near field communication
  • IR infrared technology
  • the communication module 130 may be one or more devices integrating at least one communication processing module.
  • the communication module receives electromagnetic waves via an antenna, modulates the frequency of the electromagnetic wave signals and filters them, and sends the processed signals to the processor.
  • the communication module 130 can also receive the signal to be sent from the processor, perform frequency modulation, amplify it, and convert it into electromagnetic waves for radiation through the antenna.
  • the smart foot ring 100 realizes the display function through the GPU, the display 150, and the application processor.
  • GPU is a microprocessor for image processing, connected to the display screen and the application processor.
  • the GPU is used to perform mathematical and geometric calculations for graphics rendering.
  • the processor 110 may include one or more GPUs, which execute program instructions to generate or change display information.
  • the display screen 150 is used to display images, videos, etc.
  • the display screen includes a display panel.
  • the display panel can adopt liquid crystal display (LCD), organic light-emitting diode (OLED), active-matrix organic light-emitting diode or active-matrix organic light-emitting diode (active-matrix organic light-emitting diode).
  • LCD liquid crystal display
  • OLED organic light-emitting diode
  • active-matrix organic light-emitting diode active-matrix organic light-emitting diode
  • AMOLED Miniled, MicroLed, Micro-oLed, quantum dot light emitting diode (QLED), etc.
  • the power supply 140 is used to supply power to the processor, the display screen, and the communication module.
  • the smart footband 100 may also include an external memory, an audio module, a camera, an indicator (such as an indicator light), etc., which are not limited in this application.
  • FIG. 4 shows a schematic diagram of a product form of an electronic device 100 provided by an embodiment of the present application.
  • the electronic device may specifically be a smart anklet 100, which may include a wristband and a dial.
  • the smart anklet 100 can be worn on the user's ankle through a wristband, and display exercise data, action classification results, character classification, and/or character tags, etc., through the display screen of the dial.
  • a more general motion monitoring method is based on the optical motion capture system to monitor the spatial three-dimensional coordinates of the target points distributed on the surface of the target, thereby monitoring the motion characteristics of the target.
  • This solution pastes a large number of target points on the target surface before deployment and use, and the model needs to be calibrated before use.
  • the basic principle is based on the principle of computer vision imaging, which is realized by a set of sophisticated and complex optical cameras. Multiple high-speed cameras track the target points distributed on the target surface from different angles to complete the monitoring of the movement characteristics of the whole body.
  • the installation and operation of this optical motion capture system is very complicated and costly, which makes it difficult to promote and has poor universality.
  • Another commonly used motion monitoring method is the motion monitoring method based on distributed sensors.
  • This method is based on the distributed sensors on the target surface to collect the parameters of the nodes of each part of the target, and the sensor data of the nodes of each part are time-aligned through the time synchronization device.
  • the parameters collected by the sensors of each node are transmitted to the data processing unit through the wireless protocol in real time for data fusion processing, and the actions are identified and classified according to the output results after fusion.
  • the main disadvantage of this scheme is that multiple displacement sensors are pasted on various parts of the athlete's body, which is costly, requires a large amount of preliminary work, and requires time synchronization transmission processing of each sensor unit, complex data fusion processing, and large data volume.
  • the present application provides a method for monitoring exercise data.
  • the electronic device collects the angular velocity signal and acceleration signal of the user, and processes the angular velocity signal and acceleration signal to obtain the user's exercise data.
  • the above-mentioned user’s angular velocity signal and acceleration signal can be collected by six-axis sensors. The cost is low and there is no need to perform time synchronization transmission processing and data fusion processing on multiple sensor units. It can monitor the user’s diversified sports activities in real time (for example, basketball Exercise data (such as jumping height) to improve the user’s exercise experience.
  • an embodiment of the present application provides a method for monitoring exercise data, including:
  • the electronic device collects the angular velocity signal and acceleration signal of the user.
  • the electronic device may obtain the acceleration signal of the user through the acceleration sensor, and the acceleration signal of the user includes the sampling value of the acceleration of the electronic device along the three coordinate axes of the local horizontal coordinate system.
  • the electronic device can obtain the angular velocity signal of the user through the gyroscope, and the angular velocity signal of the user includes the sampling value of the angular velocity of the electronic device along the three coordinate axes of the local horizontal coordinate system.
  • the electronic device can collect the angular velocity signal and acceleration signal of the user's foot or leg.
  • the user's feet include the user's instep, sole and other parts, and the user's legs include the user's ankle, calf, knee, and thigh.
  • the electronic device can be integrated in the user's shoe sole, upper or insole to collect the angular velocity signal and acceleration signal of the user's foot.
  • the electronic device may be a smart ankle, which is worn on the ankle or calf of the user to collect the angular velocity signal and acceleration signal of the ankle or calf of the user.
  • the electronic device can be placed in a sports knee pad or bandage to collect the angular velocity signal and acceleration signal of the user's knee or thigh. In the following, an example is described by taking the electronic device collecting the angular velocity signal and acceleration signal of the user's foot as an example.
  • the electronic device acquires the waveform characteristics of the angular velocity signal based on the angular velocity signal, and acquires the waveform characteristics of the acceleration signal based on the acceleration signal.
  • the electronic device can extract respective waveform characteristics based on the angular velocity signal collected by the gyroscope sensor and the acceleration signal collected by the acceleration sensor.
  • the waveform characteristics include the number of crests, the number of troughs, the crest-to-peak value, the skewness, and the kurtosis.
  • the electronic device determines the gait characteristics of the user according to the waveform characteristics of the angular velocity signal and the waveform characteristics of the acceleration signal, and the gait characteristics of the user include the flight time from when the user's feet are off the ground to before touching the ground.
  • An action cycle refers to the time taken for a complete action (for example, walking or jumping).
  • An action cycle can include a series of transitions of typical postures, and this typical posture change can be divided into different phases/periods.
  • an action cycle may include a ground-off phase (also referred to as a ground-off period), an airborne phase (also referred to as a vacant period), and a ground-contact phase (also referred to as a ground-contact period).
  • Ground clearance can refer to the process of lifting the heel until the foot is off the ground.
  • the air phase can refer to the process of foot movement in the air.
  • the ground contact phase can refer to the process in which the center of gravity shifts from the heel to the full foot after the heel touches the ground until all the feet touch the ground. From the early to the end of the ground-off period, the acceleration of the user's foot gradually increases; from the early to the end of the ground contact period, the acceleration of the user's foot gradually decreases.
  • the movement process of one foot can be regarded as a static state during the period of lifting and touching the ground.
  • the value of the gyroscope is close to zero, and the value of the acceleration sensor is approximately equal to the acceleration of gravity.
  • Exemplary can be based on criteria Determine whether the user is stationary.
  • acc thr 1g
  • gyro thr 0.2rad/s
  • g is the unit of gravitational acceleration
  • 1g is approximately equal to 9.8m/s ⁇ 2.
  • the gravity axis vector of the electronic device for example, smart foot ring
  • the gravity axis of the previous step that is, the gravity axis calculated according to the static state the last time
  • the user's gait characteristics are determined based on the waveform characteristics of the angular velocity signal and the waveform characteristics of the acceleration signal, so as to achieve single-step segmentation and solve the flight time of each step.
  • Single-step segmentation that is, segment each action cycle of the movement process within a period of time.
  • two adjacent peaks of the waveform diagram of the acceleration sensor may represent an action cycle, and the action corresponding to the action cycle may be a step of walking, a step of running, or a vertical jump.
  • the user's gait characteristics may also include the distance from the place speed and the touch point speed. Among them, the departure point is at the end of the departure period, and the touchdown point is at the early stage of the touchdown period.
  • FIG. 6 it is a schematic diagram of the waveform diagram (the broken line part) of the gyro sensor for normal speed walking and vertical jump (for example, the vertical vertical jump) and the waveform diagram (solid line part) of the acceleration sensor. According to the waveform characteristics of the gyroscope sensor, it is possible to distinguish between normal speed walking and vertical jump.
  • the amplitude of the waveform change is relatively large (the number of crests is more), and the posture change of the foot in the air state is small during the vertical jump, so the amplitude of the waveform change of the gyroscope is relatively small (the number of crests is less).
  • the location (smaller peak-to-peak value) and contact location (larger peak-to-peak value) can be separated according to the waveform characteristic area of the acceleration sensor. Alternatively, the location and the touch point can be separated according to the waveform area of the acceleration sensor and the gyro sensor.
  • the ground acceleration (acceleration corresponding to the touch point) is about 6g
  • the ground acceleration of vertical jump is about 7g
  • the ground acceleration is about 14g
  • the electronic device determines motion data according to the gait feature.
  • the exercise data may include at least one of the user's jumping height (for example, vertical jump height, running jump height), moving distance, number of steps, and moving speed in sports.
  • the exercise data may also include the user's heartbeat, body temperature, calorie consumption, etc., which are not limited in this application.
  • the electronic device can determine the first component of the jumping height according to the flight time; determine the second component of the jumping height according to the acceleration signal integration during the flight time; determine the jumping height according to the first component and the second component .
  • the embodiment of the present application combines the flight time and the acceleration signal integration within the flight time to determine the jumping height, which can improve the accuracy of the jumping height.
  • the electronic device determining the first component of the jump height according to the flight time includes:
  • H t represents the first component
  • ⁇ t represents the flight time
  • g represents the acceleration of gravity
  • the electronic device determining the second component of the jump height according to the acceleration integral includes:
  • H a represents a second component
  • ⁇ t represents the flight time
  • t 0 represents the initial time of flight time
  • k is a calibration parameter
  • acc z represents the signal component of acceleration in the local horizontal user coordinate system z-axis direction
  • the electronic device determining the jumping height according to the first component and the second component includes:
  • the threshold ⁇ H is the preset threshold
  • H is the jump height
  • the electronic device may determine the motion data according to the gait characteristics and the posture angle matrix, and the posture angle matrix is determined according to the angular velocity signal and the acceleration signal.
  • the posture angle matrix includes the angle of the carrier coordinate system of the electronic device relative to the local horizontal coordinate system over a period of time, which can be used to represent the posture characteristics of the user. In this way, when the user's action changes are more complicated or the action changes quickly, the user's action can be further recognized according to the posture angle matrix, and the motion data can be determined more accurately.
  • the electronic device corrects the attitude angle matrix according to the attitude angle correction matrix.
  • the electronic device can construct a posture angle correction matrix according to preset conditions.
  • the preset conditions include a preset user's foot speed before the ground is 0 and vertical displacement is 0, and the user's foot after contact with the ground speed is 0 and the vertical direction The displacement is zero.
  • Before leaving the place can refer to the early period of the period of leaving the ground (earth phase), and after the ground contact can refer to the latter period of the period of contacting the ground (ground contact).
  • the electronic device can correct all posture angle matrices from the time the foot is lifted to the ground. In this way, the temperature drift and time drift caused by the gyroscope sensor and acceleration sensor can be effectively eliminated.
  • R c C*R
  • C represents the posture angle correction matrix
  • R is the posture angle matrix
  • R c is the posture angle matrix after correction
  • ⁇ , ⁇ , and ⁇ are the rotation angles of the x-axis, y-axis, and z-axis, respectively
  • v x , v y , V z are the velocity components in the x-axis, y-axis, and z-axis directions
  • H z is the displacement in the z-axis direction
  • S is the displacement from the user to the ground after the user leaves the ground;
  • the time interval before the ground that is, the time of flight.
  • the attitude angle correction matrix is expressed by the direction cosine, and the attitude angle correction matrix may also be expressed according to Euler angles or quaternion values, which is not limited in this application.
  • zero-speed correction can be performed on the movement speed of the foot in the time interval from the ground contact to the ground clearance and the displacement in the vertical direction (ie, the Z axis) during the movement.
  • the time interval from ground contact to ground clearance may include ground contact phase and ground clearance phase.
  • the local minimum point of velocity/Z-axis displacement can be searched in the time interval from ground contact to ground clearance.
  • the local minimum point corresponds to the time of zero velocity/zero displacement, such as
  • the moving speed and displacement at the time corresponding to the local minimum point can be adjusted to zero to reduce the positioning error. In this way, the temperature drift and time drift caused by the gyroscope sensor and acceleration sensor can be effectively eliminated.
  • the smart anklet can determine the user's motion data based on the angular velocity signal and acceleration signal of one foot. If the user wears smart ankle rings on both feet, the user's motion data can be compared and corrected according to the time stamps of the motion data in the two foot rings, so as to obtain more accurate motion data.
  • the electronic device classifies actions according to the waveform characteristics of the angular velocity signal, the waveform characteristics of the acceleration signal, and the motion data, and the result of the action classification includes at least one of vertical jump, running jump, and lateral movement.
  • the type of action can be classified and recognized by the classifier.
  • combining features such as waveform features with motion data can improve the accuracy of classification.
  • the waveform characteristics include the number of crests, troughs, crest-to-peak values, skewness, kurtosis, etc.; motion data includes jump height, movement distance, and flight time.
  • the classifier can be a logistic regression (LR) classifier, a decision tree (DT) classifier, a random forest (RF) classifier, or a gradient boosting decision tree (GBDT) classification This application is not limited.
  • the action classification results may include vertical jump, running and jumping, walking and running, and lateral movement, etc., and may also include other actions, which are not limited in this application. In this way, users can get a clearer understanding of their own movement based on the action classification results, which can improve user experience.
  • the electronic device performs template matching between the motion data and the database data, and outputs the user's role classification and/or person tag.
  • the database data can include data of multiple users.
  • the data of users can include the user's sports data (jump height, flight time, movement speed, etc.), user parameters (for example, height, weight, arms span, shooting Hit rate, activity), action classification results (vertical jump, running jump and lateral movement), etc.
  • Normalization is to eliminate the dimensional influence between different data indicators, so that the data indicators are in the same order of magnitude.
  • the exercise data of the current user can be expressed as G j (n), where j represents the j-th field/time data input by the current user.
  • G j (n) may also include the current user's action classification results and user parameters.
  • the action classification results may include vertical jumping, running and jumping, and lateral movement.
  • External input parameters may include the current user's height, weight, Parameters such as wingspan and shooting percentage.
  • the electronic device can perform template matching on G j (n) and F i (n), and output the user's role classification and/or person tag.
  • the matching rule may be the principle of maximizing correlation coefficient R(i,j):
  • the electronic device can output the user's role classification and/or person tag. For example, if the user's movement speed and vertical jump height values are low, and the height is high, the character can be classified as center forward, and if the user's movement speed and activity value are large, the character can be classified as defender. For another example, if the user's weight exceeds 80kg and the vertical jump height exceeds 70cm, the character tag Dali King Kong can be output, and if the user's vertical jump height exceeds 90cm, the character tag can be output as spring legs. In this way, the user's interest in participating in sports is enhanced, and the user experience can be improved.
  • the electronic device can acquire the user's motion data by collecting the user's angular velocity signal and acceleration signal, and processing the angular velocity signal and acceleration signal.
  • the above-mentioned user’s angular velocity signal and acceleration signal can be collected by six-axis sensors. The cost is low and there is no need to perform time synchronization transmission processing and data fusion processing on multiple sensor units. It can monitor the user’s diversified sports activities in real time (for example, basketball Exercise data (such as jumping height) to improve the user’s exercise experience.
  • inventions of the present application also provide a device for monitoring exercise data, which is characterized in that the device can be applied to the electronic equipment described above.
  • the device is used to execute various functions or steps performed by the mobile phone in the above method embodiments.
  • FIG. 11 shows a possible structural schematic diagram of the electronic device involved in the foregoing embodiment, and the electronic device is used to implement the methods described in the foregoing method embodiments. , which specifically includes: an acquisition unit 1101, an acquisition unit 1102, and a determination unit 1103.
  • the collection unit 1101 is used to support the electronic device to perform the process 501 shown in FIG. 5; the obtaining unit 1102 is used to support the electronic device to perform the process 502 shown in FIG.
  • the process 503-506 is shown.
  • all relevant content of each step involved in the above method embodiment can be cited in the function description of the corresponding function module, and will not be repeated here.
  • the embodiments of the present application also provide a computer storage medium, the computer storage medium includes computer instructions, when the computer instructions run on the above-mentioned electronic device, the electronic device is caused to execute each function or step performed by the mobile phone in the above-mentioned method embodiment .
  • the embodiments of the present application also provide a computer program product, which when the computer program product runs on a computer, causes the computer to execute each function or step performed by the mobile phone in the above method embodiment.
  • the disclosed device and method may be implemented in other ways.
  • the device embodiments described above are merely illustrative.
  • the division of the modules or units is only a logical function division.
  • there may be other division methods for example, multiple units or components may be It can be combined or integrated into another device, or some features can be omitted or not implemented.
  • the displayed or discussed mutual coupling or direct coupling or communication connection may be indirect coupling or communication connection through some interfaces, devices or units, and may be in electrical, mechanical or other forms.
  • the units described as separate parts may or may not be physically separate.
  • the parts displayed as units may be one physical unit or multiple physical units, that is, they may be located in one place, or they may be distributed to multiple different places. . Some or all of the units may be selected according to actual needs to achieve the objectives of the solutions of the embodiments.
  • each unit in each embodiment of the present application may be integrated into one processing unit, or each unit may exist alone physically, or two or more units may be integrated into one unit.
  • the above-mentioned integrated unit can be implemented in the form of hardware or software functional unit.
  • the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a readable storage medium.
  • the technical solutions of the embodiments of the present application are essentially or the part that contributes to the prior art, or all or part of the technical solutions can be embodied in the form of software products, which are stored in a storage medium It includes several instructions to make a device (may be a single-chip microcomputer, a chip, etc.) or a processor (processor) execute all or part of the steps of the methods described in the various embodiments of the present application.
  • the aforementioned storage medium includes: U disk, mobile hard disk, read only memory (read only memory, ROM), random access memory (random access memory, RAM), magnetic disk or optical disk and other media that can store program codes.

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Abstract

本申请实施例提供一种运动数据监测方法和装置，涉及终端领域，能够实时监测用户在动作多样化的体育运动(例如，篮球运动)的运动数据，提升用户的运动体验。其方法为：电子设备采集用户的角速度信号和加速度信号；电子设备基于角速度信号获取角速度信号的波形特征，基于加速度信号获取加速度信号的波形特征；电子设备根据角速度信号的波形特征和加速度信号的波形特征确定用户的步态特征，步态特征包括用户的足部离地后到触地前的腾空时间；电子设备根据步态特征确定运动数据，运动数据包括跳跃高度。本申请实施例应用于各种体育运动的运动数据监测场景中。

Description

一种运动数据监测方法和装置
本申请要求在2019年7月5日提交中国国家知识产权局、申请号为201910604486.2的中国专利申请的优先权，发明名称为“一种运动数据监测方法和装置”的中国专利申请的优先权，其全部内容通过引用结合在本申请中。
技术领域
本申请涉及终端领域，尤其涉及一种运动数据监测方法和装置。
背景技术
随着通信技术的不断发展，越来越多的电子设备(例如，可穿戴设备(wearable device，WD))进入我们的视野。可穿戴设备即可以直接穿在身上，或是整合到用户的衣服或配件的一种便携式设备。
可穿戴设备的应用之一是记录用户的运动过程。例如能量手环、计步鞋等可穿戴设备，可以用来记录跑步过程中的移动步数、距离、消耗的卡路里等参数。
但是，针对动作更加多样化的体育运动，例如篮球、排球、跑酷等运动，其包含的动作可以包括走、小步跑、跳跃、侧向移动等，现有的智能穿戴设备无法很好得监测这些动作特征，从而无法提供给用户更好的运动体验。
发明内容
本申请实施例提供一种运动数据监测，能够实时监测用户在动作多样化的体育运动(例如，篮球运动)的运动数据，提升用户的运动体验。
第一方面，本申请实施例提供一种运动数据监测方法，包括：电子设备采集用户的角速度信号和加速度信号；电子设备基于角速度信号获取角速度信号的波形特征，基于加速度信号获取加速度信号的波形特征；电子设备根据角速度信号的波形特征和加速度信号的波形特征确定用户的步态特征，步态特征包括用户的足部离地后到触地前的腾空时间；电子设备根据步态特征确定运动数据，运动数据包括跳跃高度。
基于本申请提供的运动数据监测方法，电子设备可以通过采集用户的角速度信号和加速度信号，并对角速度信号和加速度信号进行处理以获取用户的运动数据。上述用户的角速度信号和加速度信号可以通过六轴传感器采集得到，成本低且无需对多个传感器单元进行时间同步传输处理和数据融合处理，能够实时监测用户在动作多样化的体育运动(例如，篮球运动)的运动数据(如跳跃高度)，提升用户的运动体验。
在一种可能的实现方式中，电子设备采集用户的角速度信号和加速度信号包括：电子设备采集用户的足部或腿部的角速度信号和加速度信号。用户的足部包括用户的脚面、脚底等部位，用户的腿部包括用户的脚踝、小腿、膝盖以及大腿等部位。
在一种可能的实现方式中，电子设备根据步态特征确定运动数据包括:电子设备根据腾空时间确定跳跃高度的第一分量；电子设备根据腾空时间内的加速度信号积分确定跳跃高度的第二分量；电子设备根据第一分量和第二分量确定跳跃高度。本申请实施例结合腾空时间和腾空时间内的加速度信号积分来确定跳跃高度，可以提高跳跃高度的精确度。
在一种可能的实现方式中，电子设备根据腾空时间确定跳跃高度的第一分量包括：
Figure PCTCN2020100223-appb-000001
其中，H t表示第一分量，Δt表示腾空时间，g表示重力加速度；电子设备根据腾空时间内的加速度积分确定跳跃高度的第二分量包括：
Figure PCTCN2020100223-appb-000002
其 中，H a表示第二分量，Δt表示腾空时间，t 0表示腾空时间的初始时刻，k为矫正参数，acc z表示用户的加速度在当地水平坐标系z轴方向的信号分量；电子设备根据第一分量和第二分量确定跳跃高度包括：当|H a-H t|<ΔH时,
Figure PCTCN2020100223-appb-000003
其中，阈值ΔH为预设阈值，H为跳跃高度。
在一种可能的实现方式中，电子设备根据角速度信号的波形特征和加速度信号的波形特征确定用户的步态特征包括：电子设备根据角速度信号的波形特征、加速度信号的波形特征和姿态角矩阵确定用户的步态特征，姿态角矩阵是根据角速度信号和加速度信号确定的。姿态角矩阵包括一段时间内电子设备的载体坐标系相对于当地水平坐标系的角度，可以用于表示用户的姿态特征。这样，当用户的动作变化较复杂或动作变化较快时，可以进一步根据姿态角矩阵识别用户的动作，能够更精准地确定运动数据。
在一种可能的实现方式中，该方法还包括：电子设备根据预设条件构造姿态角校正矩阵，预设条件包括预设用户的足部离地前速度为0且垂直方向位移为0，以及用户的足部触地后速度为0且垂直方向位移为0；电子设备根据姿态角校正矩阵对姿态角矩阵进行矫正。这样，可以有效消除陀螺仪传感器和加速度传感器带来的温漂和时漂。
在一种可能的实现方式中，电子设备根据姿态角校正矩阵对姿态角矩阵进行矫正包括：
R c＝C*R；
Figure PCTCN2020100223-appb-000004
γ＝γ 1+γ 2，
Figure PCTCN2020100223-appb-000005
Figure PCTCN2020100223-appb-000006
Figure PCTCN2020100223-appb-000007
其中，C表示姿态角校正矩阵，R为姿态角矩阵，R c为校正后的姿态角矩阵，α、β、γ分别为当地水平坐标系下的x轴、y轴、z轴方向的旋转角度，v x、v y、v z分别为x轴、y轴、z轴方向上的速度分量，H z为z轴方向上的位移，S为用户的足部离地后到触地前的位移；Δt为用户的足部离地后到触地前的时间间隔。
在一种可能的实现方式中，运动数据还包括用户的移动距离、步数、移动速度中的至少一种。运动数据还可以包括用户的心跳、体温和卡路里消耗量等，本申请不做限定。
在一种可能的实现方式中，该方法还包括：电子设备根据触地到离地时间区间内移动速度的局部极小值点进行零速校正，和/或，电子设备根据触地到离地时间区间内垂直方向上位移的局部极小值点进行距离校正。这样，可以有效消除陀螺仪传感器和加速度传感器带来的温漂和时漂。
在一种可能的实现方式中，该方法还包括：电子设备根据角速度信号的波形特征、加速度信号的波形特征和运动数据进行动作分类，动作分类结果包括纵跳、跑跳、侧向移动中的至少一种。这样一来，用户可以根据动作分类结果更清楚得了解自身的运动情况，能够提高用户体验。
在一种可能的实现方式中，该方法还包括：电子设备对运动数据与数据库数据进行模板匹配，输出用户的角色分类和/或人物标签，增强了用户参与体育运动的趣味性，可以提升用户体验。
第二方面，本申请实施例提供一种电子设备，包括：采集单元，用于采集用户的角速度信号和加速度信号；获取单元，用于基于角速度信号获取角速度信号的波形特征，基于加速度信号获取加速度信号的波形特征；确定单元，用于根据角速度信号的波形特征和加速度信 号的波形特征确定用户的步态特征，步态特征包括用户的足部离地后到触地前的腾空时间；确定单元，还用于根据步态特征确定运动数据，运动数据包括跳跃高度。
在一种可能的实现方式中，采集单元用于：采集用户的足部或腿部的角速度信号和加速度信号。
在一种可能的实现方式中，确定单元用于:根据腾空时间确定跳跃高度的第一分量；根据腾空时间内的加速度信号积分确定跳跃高度的第二分量；根据第一分量和第二分量确定跳跃高度。
在一种可能的实现方式中，
Figure PCTCN2020100223-appb-000008
其中，H t表示第一分量，Δt表示腾空时间，g表示重力加速度；
Figure PCTCN2020100223-appb-000009
其中，H a表示第二分量，Δt表示腾空时间，t 0表示腾空时间的初始时刻，k为矫正参数，acc z表示用户的加速度在当地水平坐标系z轴方向的信号分量；当|H a-H t|<ΔH时,
Figure PCTCN2020100223-appb-000010
其中，阈值ΔH为预设阈值，H为跳跃高度。
在一种可能的实现方式中，确定单元用于：根据角速度信号的波形特征、加速度信号的波形特征和姿态角矩阵确定用户的步态特征，姿态角矩阵是根据角速度信号和加速度信号确定的。
在一种可能的实现方式中，确定单元还用于：根据预设条件构造姿态角校正矩阵，预设条件包括预设用户的足部离地前速度为0且垂直方向位移为0，以及用户的足部触地后速度为0且垂直方向位移为0；根据姿态角校正矩阵对姿态角矩阵进行矫正。
在一种可能的实现方式中，R c＝C*R；
Figure PCTCN2020100223-appb-000011
γ＝γ 1+γ 2，
Figure PCTCN2020100223-appb-000012
Figure PCTCN2020100223-appb-000013
Figure PCTCN2020100223-appb-000014
其中，C表示姿态角校正矩阵，R为姿态角矩阵，R c为校正后的姿态角矩阵，α、β、γ分别为当地水平坐标系下的x轴、y轴、z轴方向的旋转角度，v x、v y、v z分别为x轴、y轴、z轴方向上的速度分量，H z为z轴方向上的位移，S为用户的足部离地后到触地前的位移；Δt为用户的足部离地后到触地前的时间间隔。
在一种可能的实现方式中，运动数据还包括用户的移动距离、步数、移动速度中的至少一种。
在一种可能的实现方式中，确定单元还用于：根据触地到离地时间区间内移动速度的局部极小值点进行零速校正，和/或，根据触地到离地时间区间内垂直方向上位移的局部极小值点进行距离校正。
在一种可能的实现方式中，确定单元还用于：根据角速度信号的波形特征、加速度信号的波形特征和运动数据进行动作分类，动作分类结果包括纵跳、跑跳、侧向移动中的至少一种。
在一种可能的实现方式中，确定单元还用于：对运动数据与数据库数据进行模板匹配，输出用户的角色分类和/或人物标签。
第二方面及其各种可能的实现方式的技术效果可以参见第一方面及其各种可能的实现方式的技术效果，此处不再赘述。
第三方面，本申请实施例提供一种计算机可读存储介质，包括指令，当其在计算机上运行时，使得计算机执行上述第一方面提供的任意一种方法。
第四方面，本申请实施例提供了一种包含指令的计算机程序产品，当其在计算机上运行时，使得计算机执行上述第一方面提供的任意一种方法。
第五方面，本申请实施例提供了一种芯片系统，该芯片系统包括处理器，还可以包括存储器，用于实现上述第一方面提供的任意一种方法。该芯片系统可以由芯片构成，也可以包含芯片和其他分立器件。
第六方面，本申请实施例还提供了一种装置，该装置可以是处理设备、电子设备或芯片。该装置包括处理器，用于实现上述第一方面提供的任意一种方法。该装置还可以包括存储器，用于存储程序指令和数据，存储器可以是集成在该装置内的存储器，或设置在该装置外的片外存储器。该存储器与该处理器耦合，该处理器可以调用并执行该存储器中存储的程序指令，用于实现上述第一方面提供的任意一种方法。该装置还可以包括通信接口，该通信接口用于该装置与其它设备进行通信。
附图说明
图1为本申请实施例提供的一种电子设备的结构示意图；
图2为本申请实施例提供的一种滚转角、俯仰角、偏航角的示意图；
图3为本申请实施例提供的一种当地水平坐标系的示意图；
图4为本申请实施例提供的一种电子设备的产品形态示意图；
图5为本申请实施例提供的一种适用于运动数据监测方法的流程示意图；
图6为本申请实施例提供的一种为常速走和纵跳的陀螺仪传感器和加速度传感器的波形图的示意图；
图7为本申请实施例提供的一种对速度或Z轴位移进行矫正的示意图；
图8为本申请实施例提供的一种基于陀螺仪与加速度传感器各自的波形特征和运动数据，通过分类器对动作种类进行分类识别的流程示意图；
图9为本申请实施例提供的一种纵跳、跑跳和侧向移动的示意图；
图10为本申请实施例提供的一种模板匹配的流程示意图；
图11为本申请实施例提供的又一种电子设备的结构示意图。
具体实施方式
下面将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，在本申请的描述中，除非另有说明，“至少一个”是指一个或多个，“多个”是指两个或多于两个。另外，为了便于清楚描述本申请实施例的技术方案，在本申请的实施例中，采用了“第一”、“第二”等字样对功能和作用基本相同的相同项或相似项进行区分。本领域技术人员可以理解“第一”、“第二”等字样并不对数量和执行次序进行限定，并且“第一”、“第二”等字样也并不限定一定不同。
本申请实施例提供一种运动数据监测方法，应用于各种体育运动的运动数据监测场景中，例如应用于篮球、排球、羽毛球、跳远、跳高、跨栏、跑酷等运动的运动数据监测场景。运动数据可以包括腾空时间、跳跃高度、跳跃次数、移动距离、步数、移动速度等。
如图1所示，为本申请实施例提供的一种电子设备的结构示意图，该电子设备具体可以为智能脚环100。智能脚环100可以包括处理器110，传感器模块120，通信模块130，电源140，显示屏150，等。其中传感器模块可以包括陀螺仪传感器120A和加速度传感器120B等。
本发明实施例示意的结构并不构成对智能脚环100的限定。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，存储器，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，也可以是集成在同一个处理器中。
控制器可以是指挥智能脚环100的各个部件按照指令协调工作的决策者。是智能脚环100的神经中枢和指挥中心。控制器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，处理器中的存储器为高速缓冲存储器。可以保存处理器刚用过或循环使用的指令或数据。如果处理器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，减少了处理器的等待时间，因而提高了系统的效率。
陀螺仪传感器120A可以用于确定智能脚环100的运动姿态。在一些实施例中，可以通过陀螺仪传感器确定智能脚环100围绕当地水平坐标系的三个轴(即，x轴，y轴和z轴)的角速度，因此陀螺仪传感器也可以称为三轴陀螺仪。如图2所示，陀螺仪传感器可以分别感应上下倾斜、前后倾斜、左右倾斜的全方位动态信息。智能脚环的姿态角是指载体坐标系与当地水平坐标系之间的夹角，可用滚转(roll)角、俯仰(pitch)角、偏航角(yaw)角三个角表示。陀螺仪传感器可以用于拍摄防抖。示例性的，当按下快门，陀螺仪传感器监测智能脚环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智能脚环100的抖动，实现防抖。陀螺仪传感器还可以用于导航，体感游戏场景。
其中，陀螺仪传感器的坐标系是当地水平坐标系。如图3所示，当地水平坐标系的原点O位于载体(即包含陀螺仪传感器的设备，如电子设备100)的质心，x轴沿当地纬线指向东(E)，y轴沿当地子午线线指向北(N)，z轴垂直于当地水平面，沿当地地理垂线指向上，并与x轴和y轴构成右手直角坐标系。其中，x轴与y轴构成的平面即为当地水平面，y轴与z轴构成的平面即为当地子午面。因此，可以理解的是，陀螺仪传感器的坐标系是：以陀螺仪传感器为原点O，沿当地纬线指向东为x轴，沿当地子午线线指向北为y轴，沿当地地理垂线指向上(即地理垂线的反方向)为z轴。
加速度传感器120B可监测智能脚环100在各个方向上(即，当地水平坐标系的x，y和z轴)加速度的大小，加速度传感器也可以称为三轴加速器。当智能脚环100静止时可监测出重力的大小及方向。还可以用于识别终端姿态，应用于横竖屏切换，计步器等应用。
三轴加速器和三轴陀螺仪合在一起可以称为六轴传感器。
通信模块130可以提供应用在智能脚环100上的包括无线局域网(wireless local area networks，WLAN)(例如，无线保真(wireless fidelity，WiFi))、蓝牙，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的通信处理模块。通信模块130可以是集成至少一个通信处理模块的一个或多个器件。通信模块经由天线接收电磁波，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。通信模 块130还可以从处理器接收待发送的信号，对其进行调频，放大，经天线转为电磁波辐射出去。
智能脚环100通过GPU，显示屏150，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150用于显示图像，视频等。显示屏包括显示面板。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)，Miniled，MicroLed，Micro-oLed，量子点发光二极管(quantum dot light emitting diodes，QLED)等。
电源140用于为处理器，显示屏，和通信模块等供电。
智能脚环100还可以包括外部存储器、音频模块、摄像头、指示器(例如指示灯)等，本申请不做限定。
如图4所示，其示出本申请实施例提供的一种电子设备100的产品形态示意图。该电子设备具体可以为智能脚环100，该智能脚环100可以包括腕带和表盘。该智能脚环100可以通过腕带佩戴在用户的脚腕上，通过表盘的显示屏显示运动数据、动作分类结果、角色分类和/或人物标签等等。
目前，在监测体育活动的运动数据时，一种比较通用的动作监测方法是基于光学动作捕捉系统监测目标物表面分布的靶标点的空间三维坐标，从而对目标的动作特征进行监测。该方案在部署使用前在目标表面粘贴大量靶标点，且使用前需要对模型进行校正。其基本原理基于计算机视觉成像原理，通过一整套精密而复杂的光学摄像头来实现，由多个高速摄像机从不同角度对目标表面分布的靶标点进行跟踪从而来完成全身的动作特征的监测。这种光学动作捕捉系统安装操作非常繁杂，成本高昂，从而导致其推广困难，普适性较差。
另一种常用的动作监测方法是基于分布式传感器的动作监测方法，该方法是基于目标表面的分布式传感器采集目标各个部位节点的参数，通过时间同步装置将各部位节点的传感器数据进行时间对准，并将各节点传感器采集的参数通过无线协议实时传输给数据处理单元进行数据的融合处理，根据融合后输出的结果进行动作的识别与分类。在使用该监测方法前，需要进行目标表面各节点传感器的预置与时间同步校准。该方案的主要缺点是在运动员身体各个部位粘贴多个位移传感器，成本高，前期工作量大，且要求各传感器单元时间同步传输处理，数据融合处理复杂，数据量大。
为了解决上述问题，本申请提供一种运动数据监测方法，电子设备通过采集用户的角速度信号和加速度信号，并对角速度信号和加速度信号进行处理以获取用户的运动数据。上述用户的角速度信号和加速度信号可以通过六轴传感器采集得到，成本低且无需对多个传感器单元进行时间同步传输处理和数据融合处理，能够实时监测用户在动作多样化的体育运动(例如，篮球运动)的运动数据(如跳跃高度)，提升用户的运动体验。
为了便于理解，以下结合附图对本申请实施例提供的运动数据监测方法进行具体介绍。
如图5所示，本申请实施例提供一种运动数据监测方法，包括：
501、电子设备采集用户的角速度信号和加速度信号。
电子设备可以通过加速度传感器获取用户的加速度信号，用户的加速度信号包括该电子设备沿当地水平坐标系的三个坐标轴的加速度的采样值。电子设备可以通过陀螺仪获取用户的角速度信号，用户的角速度信号包括该电子设备沿当地水平坐标系的三个坐标轴的角速度 的采样值。
电子设备可以采集用户的足部或腿部的角速度信号和加速度信号。用户的足部包括用户的脚面、脚底等部位，用户的腿部包括用户的脚踝、小腿、膝盖以及大腿等部位。例如，该电子设备可以集成在用户的鞋底、鞋面或鞋垫中，以采集用户的足部的角速度信号和加速度信号。或者，该电子设备可以为智能脚环，佩戴在用户的脚踝或小腿，以采集用户的脚踝或小腿的角速度信号和加速度信号。或者，该电子设备可以放置在运动护膝或绷带中，采集用户的膝盖或大腿的角速度信号和加速度信号。下文以电子设备采集用户的足部的角速度信号和加速度信号为例进行说明。
502、电子设备基于角速度信号获取角速度信号的波形特征，基于加速度信号获取加速度信号的波形特征。
电子设备可以基于陀螺仪传感器采集到的角速度信号与加速度传感器采集到的加速度信号提取出各自的波形特征，波形特征包括波峰数、波谷数、波峰峰值、偏态和峰态等。
503、电子设备根据角速度信号的波形特征和加速度信号的波形特征确定用户的步态特征，用户的步态特征包括用户的足部离地后到触地前的腾空时间。
可以理解的是，人体进行体育运动的过程可以包括多个动作周期。一个动作周期是指一个完整动作(例如，走或跳)所用的时间。一个动作周期可以包括一系列典型姿位的转移，可以将这种典型姿位变化划分成不同的时相(gait phase/period)。例如，一个动作周期可以包括离地相(也可以称为离地期间)、腾空相(也可以称为腾空期间)和触地相(也可以称为触地期间)。离地相可以是指足跟抬起直至足部离地的过程。腾空相可以是指足部在空中活动的过程。触地相可以是指足跟接触地面之后，重心由足跟向全足转移直至足部全部着地的过程。从离地期间的前期到末期，用户足部的加速度逐渐增加；从触地期间的前期到末期，用户足部的加速度逐渐减少。
以一侧足部的运动过程为例，其在离地期间和触地期间可以认为是静止状态，此时陀螺仪的值接近于零，加速度传感器的值约等于重力加速度。
示例性的，可以基于判别准则
Figure PCTCN2020100223-appb-000015
判断用户是否为静止状态。
其中，
Figure PCTCN2020100223-appb-000016
acc thr＝1g，gyro thr＝0.2rad/s；g为重力加速度单位，1g约等于9.8m/s^2。
若确定用户为静止状态，可以根据静止时的加速传感器的三轴数据求解出电子设备(例如，智能脚环)的重力轴矢量
Figure PCTCN2020100223-appb-000017
若用户为运动状态(非静止状态)，可以沿用上一步重力轴(即最近一次根据静止状态计算得到的重力轴)。
而后，基于角速度信号的波形特征与加速度信号的波形特征确定用户的步态特征，从而实现单步分割，求解每一步的腾空时间。单步分割，即分割一段时间内的运动过程的每一个动作周期。例如，加速度传感器的波形图的两个相邻波峰可以表示一个动作周期，该动作周期对应的动作可以是行走的一步，可以是跑步的一步，也可以是一次纵跳等等。用户的步态特征还可以包括离地点速度和触地点速度等。其中，离地点位于离地期间的末期，触地点位于触地期间的前期。
如图6所示，为常速走和纵跳(例如，垂直纵跳)的陀螺仪传感器的波形图(虚线部分)和加速度传感器的波形图(实线部分)的示意图。可以根据陀螺仪传感器的波形特征区分常速走和纵跳，这是由于在常速走时，足部在腾空状态(即离地后到触地前的状态)下会发生 姿态变化，因此陀螺仪的波形变化幅度较大(波峰数较多)，而在纵跳时，足部在腾空状态下的姿态变化很小，因此陀螺仪的波形变化幅度也相对较小(波峰数较少)。可以根据加速度传感器的波形特征区分离地点(波峰峰值较小)和触地点(波峰峰值较大)。或者，可以根据加速度传感器和陀螺仪传感器的波形区分离地点和触地点。由加速度传感器波形图可知，常速走的离地加速度(离地点对应的加速度)约为4g，g＝9.8m/s 2，触地加速度(触地点对应的加速度)约为6g，腾空时间约为1420-1330＝90单位毫秒，每单位毫秒可以为5ms，即腾空时间为450ms；纵跳的离地加速度约为7g，触地加速度约为14g，腾空时间约为1940-1840＝100单位毫秒，即腾空时间为500ms。
504、电子设备根据步态特征确定运动数据。
运动数据可以包括用户在体育运动中的跳跃高度(例如，纵跳高度、跑跳高度)、移动距离、步数、移动速度中的至少一种。运动数据还可以包括用户的心跳、体温和卡路里消耗量等，本申请不做限定。
以运动数据为跳跃高度为例，电子设备可以根据腾空时间确定跳跃高度的第一分量；根据腾空时间内的加速度信号积分确定跳跃高度的第二分量；根据第一分量和第二分量确定跳跃高度。本申请实施例结合腾空时间和腾空时间内的加速度信号积分来确定跳跃高度，可以提高跳跃高度的精确度。
示例性的，电子设备根据腾空时间确定跳跃高度的第一分量包括：
Figure PCTCN2020100223-appb-000018
其中，H t表示第一分量，Δt表示腾空时间，g表示重力加速度；
电子设备根据加速度积分确定跳跃高度的第二分量包括：
Figure PCTCN2020100223-appb-000019
其中，H a表示第二分量，Δt表示腾空时间，t 0表示腾空时间的初始时刻，k为矫正参数，acc z表示所述用户的加速度在当地水平坐标系z轴方向的信号分量；
电子设备根据第一分量和第二分量确定跳跃高度包括：
当|H a-H t|<ΔH时,
Figure PCTCN2020100223-appb-000020
其中，阈值ΔH为预设阈值，H为跳跃高度。
在一些实施例中，电子设备可以根据步态特征和姿态角矩阵确定运动数据，姿态角矩阵是根据角速度信号和加速度信号确定的。姿态角矩阵包括一段时间内电子设备的载体坐标系相对于当地水平坐标系的角度，可以用于表示用户的姿态特征。这样，当用户的动作变化较复杂或动作变化较快时，可以进一步根据姿态角矩阵识别用户的动作，能够更精准地确定运动数据。
可选的，电子设备根据姿态角校正矩阵对姿态角矩阵进行矫正。电子设备可以根据预设条件构造姿态角校正矩阵，预设条件包括预设用户的足部离地前速度为0且垂直方向位移为0，以及用户的足部触地后速度为0且垂直方向位移为0。离地点前可以是指离地期间(离地相)的前期，触地后可以是指触地期间(触地相)的后期。基于线性补偿原则，电子设备可以对足部离地到触地期间内的所有姿态角矩阵进行校正。这样，可以有效消除陀螺仪传感器和加速度传感器带来的温漂和时漂。
示例性的，R c＝C*R；
Figure PCTCN2020100223-appb-000021
γ＝γ 1+γ 2，
Figure PCTCN2020100223-appb-000022
Figure PCTCN2020100223-appb-000023
Figure PCTCN2020100223-appb-000024
其中，C表示姿态角校正矩阵，R为姿态角矩阵，R c为校正后的姿态角矩阵，α、β、γ分别为x轴、y轴、z轴方向的旋转角度，v x、v y、v z分别为x轴、y轴、z轴方向上的速度分量，H z为z轴方向上的位移，S为用户离地后到触地前的位移；Δt为用户离地后到触地前的时间间隔，即腾空时间。
本申请实施例中，姿态角校正矩阵是以方向余弦表示的，姿态角校正矩阵也可以是根据欧拉角或四元值表示，本申请不做限定。
在一些实施例中，可以对足部在运动过程中的触地到离地时间区间内的移动速度和垂直方向上(即Z轴)的位移进行零速矫正。触地到离地时间区间可以包括触地相和离地相。如图7中的(a)所示，可以在触地到离地时间区间内搜索速度/Z轴位移的局部极小点，该局部极小值点对应时刻为零速度/零位移时刻，如图7中的(b)所示，可以将该局部极小值点对应时刻的移动速度和位移调整为零，减小定位误差。这样，可以有效消除陀螺仪传感器和加速度传感器带来的温漂和时漂。
可以理解的是，以电子设备为智能脚环为例，若用户的一只脚佩戴智能脚环，该智能脚环可以根据一只脚的角速度信号和加速度信号确定用户的运动数据。若用户的双脚都佩戴有智能脚环，可以根据两只脚环中运动数据的时间戳对用户的运动数据进行比对和矫正，以便获取更精确的运动数据。
505、电子设备根据角速度信号的波形特征、加速度信号的波形特征和运动数据进行动作分类，动作分类结果包括纵跳、跑跳、侧向移动中的至少一种。
如图8所示，可以基于陀螺仪与加速度传感器各自的波形特征和运动数据，通过分类器对动作种类进行分类识别。相比仅基于波形特征或仅基于运动数据进行动作分类，将波形特征和运动数据等特征结合起来，可以提高分类的准确性。
其中，波形特征包括波峰数、波谷数、波峰峰值、偏态、峰态等；运动数据包括跳跃高度、移动距离、腾空时间等。分类器可以是逻辑回归分类(logistic regression，LR)器、决策树(decision tree，DT)分类器、随机森林(random forest，RF)分类器或梯度提升决策树(gradient boosting decision tree，GBDT)分类器等，本申请不做限定。
如图9所示，以篮球运动为例，动作分类结果可以包括垂直纵跳、跑跳、走跑和侧向移动等，还可以包括其他动作，本申请不做限定。这样一来，用户可以根据动作分类结果更清楚得了解自身的运动情况，能够提高用户体验。
506、电子设备对运动数据与数据库数据进行模板匹配，输出用户的角色分类和/或人物标签。
以篮球运动为例，数据库数据可以包括多个用户的数据，用户的数据可以包括用户的运动数据(跳跃高度、腾空时间、移动速度等)、用户参数(例如，身高、体重、臂展、投篮命中率、活跃度)、动作分类结果(纵跳、跑跳和侧向移动)等。数据库数据可以表示为f i(n)：其中，i表示数据库的第i个用户的数据；n＝1，2...N，N表示用户的数据的特征维数(包括跳跃高度、腾空时间、移动速度、身高、体重、臂展、纵跳和跑跳等)。对数据库f i(n)进行归一化处理可以得到F i(n)：
Figure PCTCN2020100223-appb-000025
归一化处理即消除不同数据指标之间的量纲影响，使各数据指标处于同一数量级。当前用户的运动数据可以表示为G j(n)，j表示当前用户输入的第j场/次的数据。可选的，G j(n)还可以包括当前用户的动作分类结果和用户参数，动作分类结果可以包括纵跳、跑跳和侧向移动等，外界输入参数可以包括当前用户的身高、体重、臂展和投篮命中率等参数。
如图10所示，电子设备可以对G j(n)与F i(n)进行模板匹配，输出用户的角色分类和/或人 物标签。示例性的，匹配规则可以为相关系数R(i,j)最大原则：
Figure PCTCN2020100223-appb-000026
模板匹配后，电子设备可以输出用户的角色分类和/或人物标签。例如，若用户移动速度和纵跳高度值较低、身高较高，可以输出角色分类为中锋，若用户移动速度与活跃度值较大，可以输出角色分类为后卫。再例如，若用户的体重超过80kg，纵跳高度超过70cm，可以输出人物标签大力金刚，若用户纵跳高度超过90cm，可以输出人物标签为弹簧腿。这样一来，增强了用户参与体育运动的趣味性，可以提升用户体验。
基于本申请提供的运动数据监测方法，电子设备可以通过采集用户的角速度信号和加速度信号，并对角速度信号和加速度信号进行处理以获取用户的运动数据。上述用户的角速度信号和加速度信号可以通过六轴传感器采集得到，成本低且无需对多个传感器单元进行时间同步传输处理和数据融合处理，能够实时监测用户在动作多样化的体育运动(例如，篮球运动)的运动数据(如跳跃高度)，提升用户的运动体验。
本申请另一些实施例还提供一种监测运动数据的装置，其特征在于，该装置可以应用于包括上述电子设备。该装置用于执行上述方法实施例中手机执行的各个功能或者步骤。
在采用对应各个功能划分各个功能模块的情况下，图11示出了上述实施例中所涉及的电子设备的一种可能的结构示意图，该电子设备用于实现以上各个方法实施例中记载的方法，其具体包括：采集单元1101、获取单元1102和确定单元1103。
其中，采集单元1101，用于支持电子设备执行图5所示的过程501；获取单元1102，用于支持电子设备执行图5所示的过程502；确定单元1103用于支持电子设备执行图5所示的过程503-506。其中，上述方法实施例涉及的各步骤的所有相关内容均可以援引到对应功能模块的功能描述，在此不再赘述。
本申请实施例还提供一种计算机存储介质，该计算机存储介质包括计算机指令，当所述计算机指令在上述电子设备上运行时，使得该电子设备执行上述方法实施例中手机执行的各个功能或者步骤。
本申请实施例还提供一种计算机程序产品，当所述计算机程序产品在计算机上运行时，使得所述计算机执行上述方法实施例中手机执行的各个功能或者步骤。
通过以上实施方式的描述，所属领域的技术人员可以清楚地了解到，为描述的方便和简洁，仅以上述各功能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模块完成，即将装置的内部结构划分成不同的功能模块，以完成以上描述的全部或者部分功能。
在本申请所提供的几个实施例中，应该理解到，所揭露的装置和方法，可以通过其它的方式实现。例如，以上所描述的装置实施例仅仅是示意性的，例如，所述模块或单元的划分，仅仅为一种逻辑功能划分，实际实现时可以有另外的划分方式，例如多个单元或组件可以结合或者可以集成到另一个装置，或一些特征可以忽略，或不执行。另一点，所显示或讨论的相互之间的耦合或直接耦合或通信连接可以是通过一些接口，装置或单元的间接耦合或通信连接，可以是电性，机械或其它的形式。
所述作为分离部件说明的单元可以是或者也可以不是物理上分开的，作为单元显示的部件可以是一个物理单元或多个物理单元，即可以位于一个地方，或者也可以分布到多个不同地方。可以根据实际的需要选择其中的部分或者全部单元来实现本实施例方案的目的。
另外，在本申请各个实施例中的各功能单元可以集成在一个处理单元中，也可以是各个 单元单独物理存在，也可以两个或两个以上单元集成在一个单元中。上述集成的单元既可以采用硬件的形式实现，也可以采用软件功能单元的形式实现。
所述集成的单元如果以软件功能单元的形式实现并作为独立的产品销售或使用时，可以存储在一个可读取存储介质中。基于这样的理解，本申请实施例的技术方案本质上或者说对现有技术做出贡献的部分或者该技术方案的全部或部分可以以软件产品的形式体现出来，该软件产品存储在一个存储介质中，包括若干指令用以使得一个设备(可以是单片机，芯片等)或处理器(processor)执行本申请各个实施例所述方法的全部或部分步骤。而前述的存储介质包括：U盘、移动硬盘、只读存储器(read only memory，ROM)、随机存取存储器(random access memory，RAM)、磁碟或者光盘等各种可以存储程序代码的介质。
以上内容，仅为本申请的具体实施方式，但本申请的保护范围并不局限于此，任何在本申请揭露的技术范围内的变化或替换，都应涵盖在本申请的保护范围之内。因此，本申请的保护范围应以所述权利要求的保护范围为准。

Claims (24)

  1. 一种运动数据监测方法，其特征在于，包括：
    电子设备采集用户的角速度信号和加速度信号；
    所述电子设备基于所述角速度信号获取所述角速度信号的波形特征，基于所述加速度信号获取所述加速度信号的波形特征；
    所述电子设备根据所述角速度信号的波形特征和所述加速度信号的波形特征确定用户的步态特征，所述步态特征包括所述用户的足部离地后到触地前的腾空时间；
    所述电子设备根据所述步态特征确定运动数据，所述运动数据包括跳跃高度。
  2. 根据权利要求1所述的运动数据监测方法，其特征在于，所述电子设备采集用户的角速度信号和加速度信号包括：
    所述电子设备采集所述用户的足部或腿部的角速度信号和加速度信号。
  3. 根据权利要求1或2所述的运动数据监测方法，其特征在于，所述电子设备根据所述步态特征确定运动数据包括:
    所述电子设备根据所述腾空时间确定所述跳跃高度的第一分量；
    所述电子设备根据所述腾空时间内的加速度信号积分确定所述跳跃高度的第二分量；
    所述电子设备根据所述第一分量和所述第二分量确定所述跳跃高度。
  4. 根据权利要求3所述的运动数据监测方法，其特征在于，
    所述电子设备根据所述腾空时间确定所述跳跃高度的第一分量包括：
    Figure PCTCN2020100223-appb-100001
    其中，H t表示所述第一分量，Δt表示所述腾空时间，g表示重力加速度；
    所述电子设备根据所述腾空时间内的加速度积分确定所述跳跃高度的第二分量包括：
    Figure PCTCN2020100223-appb-100002
    其中，H a表示所述第二分量，Δt表示所述腾空时间，t 0表示所述腾空时间的初始时刻，k为矫正参数，acc z表示所述用户的加速度在当地水平坐标系z轴方向的信号分量；
    所述电子设备根据所述第一分量和所述第二分量确定所述跳跃高度包括：
    当|H a-H t|<ΔH时,
    Figure PCTCN2020100223-appb-100003
    其中，阈值ΔH为预设阈值，H为所述跳跃高度。
  5. 根据权利要求1-4任一项所述的运动数据监测方法，其特征在于，所述电子设备根据所述角速度信号的波形特征和所述加速度信号的波形特征确定用户的步态特征包括：
    所述电子设备根据所述角速度信号的波形特征、所述加速度信号的波形特征和姿态角矩阵确定用户的步态特征，所述姿态角矩阵是根据所述角速度信号和所述加速度信号确定的。
  6. 根据权利要求5所述的运动数据监测方法，其特征在于，所述方法还包括：
    所述电子设备根据预设条件构造姿态角校正矩阵，所述预设条件包括预设所述用户的足部离地前速度为0且垂直方向位移为0，以及所述用户的足部触地后速度为0且垂直方向位移为0；
    所述电子设备根据所述姿态角校正矩阵对所述姿态角矩阵进行矫正。
  7. 根据权利要求6所述的运动数据监测方法，其特征在于，所述电子设备根据所述姿态角校正矩阵对所述姿态角矩阵进行矫正包括：
    R c＝C*R；
    Figure PCTCN2020100223-appb-100004
    γ＝γ 1+γ 2，
    Figure PCTCN2020100223-appb-100005
    Figure PCTCN2020100223-appb-100006
    Figure PCTCN2020100223-appb-100007
    其中，C表示所述姿态角校正矩阵，R为所述姿态角矩阵，R c为校正后的姿态角矩阵，α、β、γ分别为当地水平坐标系下的x轴、y轴、z轴方向的旋转角度，v x、v y、v z分别为x轴、y轴、z轴方向上的速度分量，H z为z轴方向上的位移，S为所述用户的足部离地后到触地前的位移；Δt为所述用户的足部离地后到触地前的时间间隔。
  8. 根据权利要求1-7任一项所述的运动数据监测方法，其特征在于，
    所述运动数据还包括所述用户的移动距离、步数、移动速度中的至少一种。
  9. 根据权利要求1-8任一项所述的运动数据监测方法，其特征在于，所述方法还包括：
    所述电子设备根据触地到离地时间区间内移动速度的局部极小值点进行零速校正，和/或
    所述电子设备根据触地到离地时间区间内垂直方向上位移的局部极小值点进行距离校正。
  10. 根据权利要求1-9任一项所述的运动数据监测方法，其特征在于，所述方法还包括：
    所述电子设备根据所述角速度信号的波形特征、所述加速度信号的波形特征和所述运动数据进行动作分类，动作分类结果包括纵跳、跑跳、侧向移动中的至少一种。
  11. 根据权利要求1-10任一项所述的运动数据监测方法，其特征在于，所述方法还包括：
    所述电子设备对所述运动数据与数据库数据进行模板匹配，输出用户的角色分类和/或人物标签。
  12. 一种电子设备，其特征在于，包括：
    采集单元，用于采集用户的角速度信号和加速度信号；
    获取单元，用于基于所述角速度信号获取所述角速度信号的波形特征，基于所述加速度信号获取所述加速度信号的波形特征；
    确定单元，用于根据所述角速度信号的波形特征和所述加速度信号的波形特征确定用户的步态特征，所述步态特征包括所述用户的足部离地后到触地前的腾空时间；
    所述确定单元，还用于根据所述步态特征确定运动数据，所述运动数据包括跳跃高度。
  13. 根据权利要求12所述的电子设备，其特征在于，所述采集单元用于：
    采集所述用户的足部或腿部的角速度信号和加速度信号。
  14. 根据权利要求12或13所述的电子设备，其特征在于，所述确定单元用于:
    根据所述腾空时间确定所述跳跃高度的第一分量；
    根据所述腾空时间内的加速度信号积分确定所述跳跃高度的第二分量；
    根据所述第一分量和所述第二分量确定所述跳跃高度。
  15. 根据权利要求14所述的电子设备，其特征在于，
    Figure PCTCN2020100223-appb-100008
    其中，H t表示所述第一分量，Δt表示所述腾空时间，g表示重力加速度；
    Figure PCTCN2020100223-appb-100009
    其中，H a表示所述第二分量，Δt表示所述腾空时间，t 0表示所述腾空时间的初始时刻，k为矫正参数，acc z表示所述用户的加速度在当地水平坐标系z轴方向的信号分量；
    当|H a-H t|<ΔH时,
    Figure PCTCN2020100223-appb-100010
    其中，阈值ΔH为预设阈值，H为所述跳跃高度。
  16. 根据权利要求12-15任一项所述的电子设备，其特征在于，所述确定单元用于：
    根据所述角速度信号的波形特征、所述加速度信号的波形特征和姿态角矩阵确定用户的步态特征，所述姿态角矩阵是根据所述角速度信号和所述加速度信号确定的。
  17. 根据权利要求16所述的电子设备，其特征在于，所述确定单元还用于：
    根据预设条件构造姿态角校正矩阵，所述预设条件包括预设所述用户的足部离地前速度为0且垂直方向位移为0，以及所述用户的足部触地后速度为0且垂直方向位移为0；
    根据所述姿态角校正矩阵对所述姿态角矩阵进行矫正。
  18. 根据权利要求17所述的电子设备，其特征在于，
    R c＝C*R；
    Figure PCTCN2020100223-appb-100011
    γ＝γ 1+γ 2，
    Figure PCTCN2020100223-appb-100012
    Figure PCTCN2020100223-appb-100013
    Figure PCTCN2020100223-appb-100014
    其中，C表示所述姿态角校正矩阵，R为所述姿态角矩阵，R c为校正后的姿态角矩阵，α、β、γ分别为当地水平坐标系下的x轴、y轴、z轴方向的旋转角度，v x、v y、v z分别为x轴、y轴、z轴方向上的速度分量，H z为z轴方向上的位移，S为所述用户的足部离地后到触地前的位移；Δt为所述用户的足部离地后到触地前的时间间隔。
  19. 根据权利要求12-18任一项所述的电子设备，其特征在于，
    所述运动数据还包括所述用户的移动距离、步数、移动速度中的至少一种。
  20. 根据权利要求12-19任一项所述的电子设备，其特征在于，所述确定单元还用于：
    根据触地到离地时间区间内移动速度的局部极小值点进行零速校正，和/或
    根据触地到离地时间区间内垂直方向上位移的局部极小值点进行距离校正。
  21. 根据权利要求12-20任一项所述的电子设备，其特征在于，所述确定单元还用于：
    根据所述角速度信号的波形特征、所述加速度信号的波形特征和所述运动数据进行动作分类，动作分类结果包括纵跳、跑跳、侧向移动中的至少一种。
  22. 根据权利要求12-21任一项所述的电子设备，其特征在于，所述确定单元还用于：
    对所述运动数据与数据库数据进行模板匹配，输出用户的角色分类和/或人物标签。
  23. 一种运动数据监测装置，其特征在于，包括处理器，所述处理器与存储器耦合，所述存储器中存储有指令，所述处理器调用并执行所述指令时，使所述装置执行权利要求1-11中任一项所述的运动数据监测方法。
  24. 一种计算机可读存储介质，其特征在于，包括指令，当其在计算机上运行时，使得计算机执行权利要求1至11中任一项所述的运动数据监测方法。
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