WO2018076205A1 - 一种步幅校准方法、相关设备及系统 - Google Patents

一种步幅校准方法、相关设备及系统 Download PDF

Info

Publication number
WO2018076205A1
WO2018076205A1 PCT/CN2016/103393 CN2016103393W WO2018076205A1 WO 2018076205 A1 WO2018076205 A1 WO 2018076205A1 CN 2016103393 W CN2016103393 W CN 2016103393W WO 2018076205 A1 WO2018076205 A1 WO 2018076205A1
Authority
WO
WIPO (PCT)
Prior art keywords
user
stride
motion
actual
preset database
Prior art date
Application number
PCT/CN2016/103393
Other languages
English (en)
French (fr)
Inventor
余尚春
王怀勇
邵潇杰
Original Assignee
华为技术有限公司
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by 华为技术有限公司 filed Critical 华为技术有限公司
Priority to US16/345,598 priority Critical patent/US11237017B2/en
Priority to EP16919864.5A priority patent/EP3521764B1/en
Priority to PCT/CN2016/103393 priority patent/WO2018076205A1/zh
Priority to CN201680090283.0A priority patent/CN109844460B/zh
Publication of WO2018076205A1 publication Critical patent/WO2018076205A1/zh

Links

Images

Classifications

    • 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
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01C—MEASURING DISTANCES, LEVELS OR BEARINGS; SURVEYING; NAVIGATION; GYROSCOPIC INSTRUMENTS; PHOTOGRAMMETRY OR VIDEOGRAMMETRY
    • G01C25/00—Manufacturing, calibrating, cleaning, or repairing instruments or devices referred to in the other groups of this subclass
    • 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
    • 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
    • G06F16/23—Updating
    • G06F16/2379—Updates performed during online database operations; commit processing

Definitions

  • the present invention relates to the field of mobile terminal technologies, and in particular, to a stride calibration method, related equipment, and system.
  • consumer electronic products such as mobile devices (including smart phones, tablet computers, etc.) are equipped with various types of motion sensors, such as accelerometers, gyroscopes, and magnetometers, to identify whether the user is walking or not.
  • motion sensors such as accelerometers, gyroscopes, and magnetometers.
  • the running state of the running and can count the user's sports steps, sports posture and calorie consumption and other sports indicators to provide users with better application functions and experiences.
  • a mobile device configured with the motion sensor may be configured with a distance monitoring component (eg, a GPS module) or may not be configured with a distance monitoring component.
  • a mobile device equipped with a distance monitoring component such as a smart phone, can accurately measure the actual moving distance of the user through a Global Navigation Satellite System (GPS, Beidou, etc.).
  • GPS Global Navigation Satellite System
  • Beidou Beidou
  • a mobile device that is not configured with the distance monitoring component, such as a wearable device cannot directly measure the actual moving distance of the user, and the moving distance of the user is mainly obtained by the following two methods.
  • the user's stride is estimated according to the physical information input by the user, such as height, weight, age, etc., and then the estimated stride and the number of motion steps collected by the motion sensor are used to calculate the user's exercise distance. .
  • the calculation results obtained in this way are not very reliable, and there is usually a large error between the calculated motion distance and the actual motion distance of the user.
  • the actual moving distance of the user measured by the counterpart device is obtained by establishing a communication connection (for example, a Bluetooth connection) with another device configured with a distance monitoring component (for example, a GPS module).
  • a communication connection for example, a Bluetooth connection
  • a distance monitoring component for example, a GPS module
  • a wearable device that is not configured with a GPS module establishes a Bluetooth connection with a smart phone configured with a GPS module, and the wearable device obtains the actual moving distance of the user measured by the smart phone through a Bluetooth connection.
  • This approach requires a communication connection between the wearable device and the smartphone, and the GPS module of the smartphone is always working.
  • the prior art techniques for acquiring the user's motion distance are not ideal, and it is not convenient for the user to count the motion distance through the mobile device.
  • the embodiment of the invention provides a stride calibration method, a related device and a system, which can perform step estimation and calibration on a device not equipped with a distance monitoring component, thereby improving the accuracy of calculating the user's motion distance by the device. Moreover, the device can independently and accurately calculate the user's motion distance after the calibration is completed.
  • a stride calibration method for use on a first device side.
  • the method includes: the first device detects that the user is walking or running, and collects the number of motion steps of the user, determines whether the step of the user in the preset database needs to be calibrated, and if calibration is required, The second device requests to obtain the actual moving distance of the user. Then, the first device may calculate the actual stride of the user according to the actual moving distance of the user and the number of motion steps of the user. Finally, the first device may update the stride of the user in the preset database by using the calculated actual stride.
  • a stride calibration method for use on a second device side. The method includes: receiving, by the second device, a request sent by the first device, in response to the request, collecting an actual moving distance of the user, and transmitting the actual moving distance of the user to the first device.
  • the request is that the first device transmits after detecting that the user is walking or running, and determines that the step of the user in the preset database needs to be calibrated.
  • the stride of the user in the preset database is used to provide the first device to calculate the moving distance of the user.
  • the actual moving distance collected by the second device on the first device side not configured with the distance monitoring component and the first device may be acquired.
  • the actual number of motion steps performs step calibration on the stride in the preset database to improve the accuracy of the first device to calculate the user's motion distance.
  • the first device can independently and accurately calculate the user's motion distance after the calibration is completed.
  • the preset database may further include: a motion state parameter of the user, where the motion state parameter of the user corresponds to a stride of the user.
  • the motion state parameter of the user may include at least one of the following: a motion step frequency, a motion type, and a motion environment in which the user is located.
  • the preset database may further include: physical information of the user, The physical sign information of the user corresponds to the stride of the user.
  • the first device may further collect the motion state parameter of the user, and according to the actual motion distance of the user in the motion state characterized by the same motion state parameter. And the number of motion steps, the actual stride of the user in the motion state characterized by the same motion state parameter is calculated. Then, the first device may update the stride of the user in the motion state represented by the same motion state parameter in the preset database by using the calculated actual stride.
  • the preset database may also include the latest calibration time corresponding to the user's stride.
  • the first device may determine whether the difference between the latest calibration time and the current time is greater than a preset time threshold, and if yes, determine that the user's stride in the preset database needs to be calibrated. Otherwise, it is determined that the user's stride in the preset database does not need to be calibrated.
  • the first device may also filter out illegal data in the data representing the actual moving distance.
  • a stride calibration method for use on a second device side.
  • the method includes: the second device detects, by the first device, that the user is walking or running, determining whether the step of the user in the preset database needs to be calibrated, and if calibration is required, collecting the actual motion of the user. Distance, and requesting the first device to obtain the number of motion steps of the user.
  • the second device may calculate an actual motion stride of the user according to the number of motion steps of the user and the actual motion distance of the user, and update the preset database by using the actual motion stride of the user.
  • the user's stride then sends the preset database to the first device.
  • a stride calibration method for use on a first device side.
  • the method includes: the first device detects that the user is walking or running, collects the number of motion steps of the user, receives a request sent by the second device, and sends the user to the second device in response to the request. The number of movement steps.
  • the first device finally receives a preset database sent by the second device.
  • the request is that the second device transmits after detecting that the user is walking or running, and determines that the user's stride needs to be calibrated in the preset database.
  • the preset database may be used by the first device according to the preset data.
  • the stride of the user in the library and the number of motion steps of the user calculate the distance of movement of the user.
  • the actual moving distance collected by the second device on the second device side configured with the distance monitoring component and the collected by the first device can be realized.
  • the actual number of motion steps performs step calibration on the step size in the preset database, and sends the calibrated preset database to the first device not configured with the distance monitoring component, thereby improving the calculation of the first device.
  • the first device can independently and accurately calculate the user's motion distance after the calibration is completed.
  • the preset database may further include: a motion state parameter of the user, where the motion state parameter of the user corresponds to a stride of the user.
  • the motion state parameter of the user may include at least one of the following: a motion step frequency, a motion type, and a motion environment in which the user is located.
  • the preset database may further include: physical information of the user, and the physical information of the user corresponds to the stride of the user.
  • the first device may further collect the motion state parameter of the user.
  • the second device may request the first device to acquire the motion state parameter of the user, and calculate the actual motion distance and the number of motion steps according to the motion state represented by the user in the same motion state parameter.
  • the preset database may also include the latest calibration time corresponding to the user's stride.
  • the second device may determine whether the difference between the latest calibration time and the current time is greater than a preset time threshold. If it is greater, determine that the user's stride needs to be calibrated; otherwise, determine the user. The stride does not need to be calibrated.
  • the second device may also filter out data in the data representing the number of motion steps of the user. Illegal data.
  • a stride calibration method for use on a second device side.
  • the method includes: the second device detects that the user is walking or running, and determines whether the step of the user in the preset database needs to be calibrated. If calibration is needed, the actual moving distance of the user may be collected and collected. The number of motion steps of the user.
  • the second device may be based on the number of motion steps of the user and the user Calculating the actual motion step of the user, and updating the stride of the user in the preset database by using the actual motion stride of the user, and then transmitting the pre-order to the first device Set up a database.
  • a stride calibration method for use on a first device side. The method includes: receiving, by a first device, a preset database sent by the second device.
  • the preset database may be used by the first device to calculate a moving distance of the user according to the stride of the user in the preset database and the number of motion steps of the user.
  • the actual moving distance collected by the second device on the second device side configured with the distance monitoring component and the second device may be acquired.
  • the actual number of motion steps performs step calibration on the step size in the preset database, and sends the calibrated preset database to the first device not configured with the distance monitoring component, thereby improving the calculation of the first device.
  • the first device can independently and accurately calculate the user's motion distance after the calibration is completed.
  • a mobile device being a first device, which may include: a motion sensor, a processor, and a transceiver, where:
  • the motion sensor is configured to detect that the user is walking or running, and collect the number of motion steps of the user;
  • the processor is configured to determine whether it is necessary to calibrate the stride of the user in the preset database, if calibration is needed;
  • the transceiver is configured to: if the processor determines that the step of the user in the preset database needs to be calibrated, request the second device to obtain an actual moving distance of the user; the second device is used to: Collecting an actual moving distance of the user; the stride of the user in the preset database is used to provide the first device to calculate a moving distance of the user;
  • the processor is further configured to calculate an actual stride of the user according to the actual moving distance of the user and the number of motion steps of the user, and update the preset database by using the calculated actual stride The user's stride.
  • a mobile device is provided, the mobile device being a second device, which can include: a distance monitoring component and a transceiver, wherein:
  • the transceiver can be configured to receive a request sent by the first device
  • the distance monitoring component can be configured to collect an actual moving distance of the user in response to the request
  • the transceiver is further configured to send the actual distance of the user to the first device.
  • the preset database may be used by the first device to calculate a moving distance of the user according to the stride of the user in the preset database and the number of motion steps of the user.
  • the preset database may further include: a motion state parameter of the user, where the motion state parameter of the user corresponds to a stride of the user.
  • the motion state parameter of the user may include at least one of the following: a motion step frequency, a motion type, and a motion environment in which the user is located.
  • the preset database may further include: physical information of the user, and the physical information of the user corresponds to the stride of the user.
  • the motion sensor may be further configured to collect a motion state parameter of the user when the user detects that the user is walking or running.
  • the processor may be further configured to calculate, according to an actual moving distance and a number of moving steps of the user in a motion state characterized by the same motion state parameter, an actual state of the user in a motion state characterized by the same motion state parameter. Steps, and using the calculated actual stride, to update the stride of the user in the preset database in the motion state characterized by the same motion state parameter.
  • a mobile device is provided, the mobile device being a second device, which can include: a distance monitoring component and a transceiver, wherein: a distance monitoring component, a processor, and a transceiver, wherein:
  • the processor is configured to detect, by the first device, that the user is walking or running;
  • the processor is further configured to determine whether it is necessary to calibrate the stride of the user in the preset database
  • the distance monitoring component is configured to collect an actual moving distance of the user if the processor determines that the step of the user in the preset database needs to be calibrated;
  • the transceiver is configured to request, by the first device, the number of motion steps of the user;
  • the processor is further configured to calculate an actual motion stride of the user according to the number of motion steps of the user and an actual movement distance of the user, and update the preset database by using an actual motion stride of the user.
  • the stride of the user is further configured to calculate an actual motion stride of the user according to the number of motion steps of the user and an actual movement distance of the user, and update the preset database by using an actual motion stride of the user. The stride of the user;
  • the transceiver is further configured to send the preset database to the first device, where the preset database is used by the first device according to the user's stride in the preset database and the user
  • the number of motion steps calculates the motion distance of the user.
  • a mobile device being a first device, which can include: a motion sensor, a processor, and a transceiver, wherein:
  • the motion sensor can be used to detect that the user is walking or running, and collecting the number of motion steps of the user;
  • the transceiver may be configured to receive a request sent by the second device, and send the number of motion steps of the user to the second device in response to the request;
  • the transceiver is further configured to receive the preset database sent by the second device.
  • the request is that the second device transmits after detecting that the user is walking or running, and determines that the user's stride needs to be calibrated in the preset database.
  • the preset database may be used by the first device to calculate a moving distance of the user according to the stride of the user in the preset database and the number of motion steps of the user.
  • the preset database may further include: a motion state parameter of the user, where the motion state parameter of the user corresponds to a stride of the user.
  • the motion state parameter of the user may include at least one of the following: a motion step frequency, a motion type, and a motion environment in which the user is located.
  • the preset database may further include: physical information of the user, and the physical information of the user corresponds to the stride of the user.
  • the transceiver may be further configured to: if the processor determines that the step of the user in the preset database needs to be calibrated, request the first device to acquire a motion state parameter of the user.
  • the first device is configured to collect the motion state parameter of the user.
  • the processor may be further configured to calculate an actual step of the user in a motion state characterized by the same motion state parameter according to an actual motion distance and a motion step number of the user in a motion state characterized by the same motion state parameter. And using the calculated actual stride to update the stride of the user in the preset database in the motion state characterized by the same motion state parameter.
  • a mobile device is provided, the mobile device being a first device, and a functional unit for performing the method of the first aspect.
  • a mobile device is provided, the mobile device being a second device, which can include a functional unit for performing the method of the second aspect.
  • a mobile device is provided, the mobile device being a first device, and comprising a functional unit for performing the method of the third aspect.
  • a mobile device is provided, the mobile device being a second device, and comprising a functional unit for performing the method of the fourth aspect.
  • a stride calibration system comprising: a first device and a second device, wherein:
  • the first device is configured to detect that the user is walking or running, and collect the number of motion steps of the user;
  • the first device is further configured to determine whether it is necessary to calibrate the stride of the user in the preset database, and if the calibration is required, request the second device to obtain the actual moving distance of the user;
  • the stride of the user in the database is used to provide the first device with a calculated distance of movement of the user;
  • the second device is configured to collect an actual moving distance of the user
  • the first device is further configured to calculate an actual stride of the user according to the actual moving distance of the user and the number of motion steps of the user, and update the preset database by using the calculated actual stride.
  • the stride of the user in the middle is further configured to calculate an actual stride of the user according to the actual moving distance of the user and the number of motion steps of the user, and update the preset database by using the calculated actual stride.
  • a stride calibration system comprising: a first device and a second device, wherein:
  • the first device is configured to detect that the user is walking or running, and collect the number of motion steps of the user;
  • the second device is configured to: after detecting, by the first device, that the user is walking or running, determining whether the step of the user in the preset database needs to be calibrated, and if calibration is required, collecting the user Actual moving distance, and requesting the first device to acquire the number of motion steps of the user; the stride of the user in the preset database is used to provide the first device to calculate the moving distance of the user ;
  • the second device is further configured to calculate an actual motion stride of the user according to the number of motion steps of the user and an actual motion distance of the user, and update the preset by using an actual motion stride of the user.
  • the stride of the user in the database is further configured to calculate an actual motion stride of the user according to the number of motion steps of the user and an actual motion distance of the user, and update the preset by using an actual motion stride of the user.
  • the second device is further configured to send the preset database to the first device.
  • a readable non-volatile storage medium storing computer instructions, the computer instructions being executed to implement the method described in the first aspect above.
  • a readable non-volatile storage medium storing computer instructions, the computer instructions being executed to implement the method described in the second aspect above.
  • a readable non-volatile storage medium storing computer instructions, the computer instructions being executed to implement the method described in the third aspect above.
  • a readable non-volatile storage medium storing computer instructions, the computer instructions being executed to implement the method described in the fourth aspect above.
  • the step estimation and calibration of the device not equipped with the distance monitoring component can be implemented, thereby improving the accuracy of calculating the user's motion distance by the device.
  • the device can independently and accurately calculate the user's motion distance after the calibration is completed.
  • FIG. 1 is a schematic diagram of an application scenario designed according to an embodiment of the present invention.
  • FIG. 2 is a schematic diagram of a database including an estimated stride of a user according to an embodiment of the present invention
  • FIG. 3 is a schematic flow chart of a stride calibration method according to an embodiment of the present invention.
  • FIG. 5 is a schematic diagram of a hardware architecture of an apparatus not configured with a distance monitoring component according to an embodiment of the present invention
  • FIG. 6 is a schematic diagram of a hardware architecture of a device configured with a distance monitoring component according to an embodiment of the present invention
  • FIG. 7 is a schematic diagram of cooperative interaction of various components in the device described in the embodiment of FIG. 5 and the device in FIG. 6;
  • FIG. 8 is a schematic diagram of functional modules of a stride calibration system and related devices according to an embodiment of the present invention.
  • FIG. 9 is a schematic diagram of functional blocks of another stride calibration system and related devices according to an embodiment of the present invention.
  • FIG. 1 is a schematic diagram of an application scenario according to an embodiment of the present invention. As shown in FIG. 1, the user carries both the wearable device 10 and the smartphone 20 while running or walking. among them:
  • the smartphone 20 is provided with a distance monitoring component that can directly measure the actual moving distance of the user.
  • the distance monitoring component may be a GPS module, and the actual moving distance of the user can be directly measured by the satellite positioning system, and can be mainly used in an outdoor open environment.
  • the distance monitoring component may also be an RF (Radio Frequency) positioning module, such as a Wi-Fi positioning module or a 3G positioning module, and may be mainly used to locate the user in an indoor environment. And measure the actual distance of the user's movement.
  • RF Radio Frequency
  • the wearable device 10 is not configured with a distance monitoring component, and the actual moving distance of the user cannot be directly measured.
  • the wearable device 10 is equipped with a motion sensor, such as an accelerometer, a gyroscope, a magnetometer, etc., to recognize the user's exercise state (whether walking or running), stride frequency, sports environment, etc., and can count the user's motion. Step count.
  • wearable device 10 may also count other user's vital parameters, such as heartbeat, respiration rate, and the like.
  • the wearable device 10 side may be configured with a stride estimation model for estimating the motion stride of the user and a preset database.
  • the variable of the stride estimation model may be an influencing factor of the stride.
  • the preset database can be used to record a mapping relationship between the influencing factors and the stride.
  • the influencing factors of the stride may include one or more of the following: the user's physical information (such as gender, height, weight, age, etc.), the type of exercise (walking or running), and the step frequency (ie, unit time). The number of movement steps inside) and the sports environment (flat road, slope, etc.).
  • the motion type, the step frequency, and the motion environment may be collectively referred to as a motion state parameter for indicating a motion state of the user.
  • the height of a person with a higher height is larger than that of a person with a shorter height.
  • the stride of a man is larger than that of a woman.
  • the young man has a larger stride than the old man, and the stride is moderate.
  • the pace of a user running fast is larger than that of a slow running, and the stride of the user when walking fast is larger than that of a slow walking.
  • the factors affecting the stride may also include other factors, such as exercise heart rate, exercise respiration rate, and no limitation here.
  • the wearable device 10 can collect the above motion state parameters through a motion sensor.
  • the motion sensor can sense the difference between walking and running, usually the human body When running, the upper and lower amplitudes of the body perpendicular to the ground are relatively large.
  • the motion sensor can perceive the number of motion steps of the user per unit time, and the more the number of motion steps per unit time, the larger the step frequency, and vice versa.
  • the motion sensor can perceive the difference of the human body in different sports environments.
  • the difference between the movement state of the human body on a flat road and the motion state of the human body on the slope can be obtained through statistical analysis of a large amount of empirical data.
  • the example is only one implementation of the embodiment of the present invention.
  • the specific implementation of the method for obtaining the motion state parameter by using the motion sensor is not limited in the embodiment of the present invention.
  • the wearable device 10 can be used to display the interface 30, and the user can input his/her own physical information such as gender, height, weight, and the like in the interface 30.
  • pedospeed indicates the user's exercise cadence (unit can be step / minute).
  • the function f can be used to map the corresponding stride according to the height and the motion step frequency.
  • the function f can be expressed as:
  • a and b represent the weights of the various factors
  • m and n represent the indices of the various factors
  • c represents the adjustment increment.
  • a machine learning algorithm can be used to train the values of a, b, m, n, and c. During training, a large number of known stride frequencies and known heights are used as inputs, and the known stride frequency and the actual stride corresponding to the known height are used as outputs.
  • the stride estimation model f may also be other models for estimating the stride, which is not limited herein. Moreover, not limited to the two influencing factors of height and stride frequency, the independent variable of the function f may include more or less factors affecting the stride, that is, the stride estimation model may also be from more dimensions or less dimensions. Estimate the stride.
  • the preset database may be as shown in FIG. 2, wherein: the X axis represents the user's motion pitch, and the Y axis represents the user's height, Z.
  • the axis represents the user's stride.
  • the height and the step frequency jointly affect the stride, and the mapping relationship between the stride estimation model exists between the combination of the height and the step frequency formation and the stride.
  • the user's exercise step frequency is larger, and the user's stride is correspondingly larger.
  • the coordinate point A in the figure indicates: when height When the user's exercise step frequency of 170 cm is 110 steps per minute (steps/minute), the user's step size can be estimated to be 60 cm by the above-described stride estimation model.
  • the coordinate point B in the figure indicates that when the user's exercise step frequency of 170 cm is 80 steps per minute (step/minute), the user's step size can be estimated to be 50 cm by the above-described stride estimation model.
  • the examples are merely illustrative of the embodiments of the invention and should not be construed as limiting.
  • the user with a higher height has a relatively larger stride.
  • the coordinate point B in the figure indicates that when the user's exercise step frequency of 170 cm is 80 steps per minute (steps/minute), the user's step size can be estimated to be 50 cm by the above-described stride estimation model.
  • the coordinate point C in the figure indicates that when the user's exercise step frequency of 190 cm is 80 steps per minute (step/minute), the user's step size can be estimated to be 70 cm by the above-described stride estimation model.
  • the examples are merely illustrative of the embodiments of the invention and should not be construed as limiting.
  • preset database is not limited to that shown in FIG. 2, and may also reflect more or less mapping relationship between stride influence factors and strides.
  • the preset database may be established or initialized in the following manner.
  • the preset database configured on the wearable device 10 side can be applied to any possible users.
  • human vital signs such as height
  • the state of motion of humans such as the pace of motion
  • the wearable device 10 can estimate the corresponding stride of all possible users (different signs) in different motion states according to the stride estimation model, and estimate the stride and the corresponding signs of the stride.
  • Information and motion states are correspondingly populated into the preset database.
  • the preset database may include a corresponding stride of all possible users (different signs) estimated by the stride estimation model in different motion states, such that any user wears the wearable device 10 to run. Or while walking, the wearable device 10 can estimate the corresponding stride.
  • the preset database configured on the wearable device 10 side may also be applied only to the user of the wearable device 10.
  • the wearable device 10 can receive the physical information (such as height) input by the user through the interface 30.
  • the wearable device 10 can recognize the motion of the user. a state (eg, a sports pitch), using the user's vital information and motion state to estimate the user's motion in accordance with the stride estimation model
  • the stride in the state, and the estimated stride, and the corresponding physical information and motion state corresponding to the stride are filled into the preset database. That is to say, the preset database may be blank at the initial moment.
  • the wearable device 10 can continuously fill the preset database during the user's use of the wearable device 10, which can reduce the amount of data managed by the preset database.
  • the wearable device 10 may also obtain the preset database for the user from the server after receiving the physical information input by the user through the interface 30.
  • the server may be a service platform of the wearable device 10, and may be used to manage the stride corresponding to all possible users (different signs) calculated by the stride estimation model in different motion states.
  • the preset database obtained from the server may be specifically represented by a table, which records the stride corresponding to the user in different motion states, and may refer to the subsequent table 1.
  • the step frequency in the preset database may also be roughly divided into several step frequency ranges, specifically, the high speed step frequency, the medium speed step frequency, and the low speed step frequency as shown in FIG. 2 .
  • the user's motion distance can be estimated by using an average stride corresponding to a step frequency range.
  • the step frequency range corresponding to the low-speed step frequency is 40 steps/minute to 60 steps/minute, and there are 100 discrete step frequency values A 1 to A 100 in the range .
  • the stride in the preset database is an estimated value obtained by using the stride estimation model, and cannot accurately reflect the actual stride of the user, which may result in using the preset database.
  • the calculated distance of the stride is also not accurate.
  • the user wears the wearable device 10 and the smart phone 20 at the same time, and the wearable device 10 calculates the motion distance of the user as L1 by multiplying the stride in the preset database by the number of motion steps.
  • the smartphone 20 directly uses GPS to measure the user's moving distance as L2, and there is often a deviation between L2 and L1.
  • the embodiment of the present invention provides a stride calibration method, which can perform step estimation on a device (such as the wearable device 10) that is not configured with the distance monitoring component. Calibration, which in turn increases the accuracy of the device in calculating the user's range of motion. Moreover, the device can independently and accurately calculate the user's motion distance after the calibration is completed.
  • the main principles involved in the embodiments of the present invention include: distance data collected by a device configured with a distance monitoring component (such as the aforementioned smart phone 20, hereinafter referred to as a second device), and a device not equipped with a distance monitoring component (such as the foregoing).
  • a distance monitoring component such as the aforementioned smart phone 20, hereinafter referred to as a second device
  • a device not equipped with a distance monitoring component such as the foregoing
  • the step size in the preset database on the side of the wearable device 10 hereinafter referred to as the first device.
  • the first device can accurately calculate the user motion distance by using the stride in the preset database independently.
  • FIG. 3 is a step calibration method according to an embodiment of the present invention.
  • the first device uses the distance data collected by the second device (configured with a distance monitoring component, such as a GPS module, an RF positioning module), and the pre-processing on the first device side.
  • the stride in the database is calibrated, and the user's moving distance is calculated according to the stride in the preset database after the calibration is completed. The following expands the description:
  • the first device detects that the user is running or walking.
  • the first device may be configured with a motion sensor such as an accelerometer, a gyroscope, a magnetometer, and the like.
  • the first device can identify whether the type of exercise the user is in is running or walking.
  • the first device collects the number of motion steps of the user. Specifically, the first device may count, by using the motion sensor, the number of motion steps of the user.
  • the first device determines whether it is necessary to calibrate the stride of the user in the preset database. Specifically, if calibration is required, S107-S111 is performed, otherwise S117 is performed.
  • the preset database may be configured in the first device, and the first device uses the stride in the preset database to estimate a moving distance of the user.
  • the preset database please refer to FIG. 2 and related content, and details are not described herein again.
  • the first device requests the second device to acquire an actual moving distance of the user.
  • the second device may be configured with a distance monitoring component for collecting the actual moving distance of the user.
  • the first device may send a request to the second device to request to obtain an actual moving distance of the user, and reference may be made to S107.
  • the second device receives the request, and in response to the request, collects an actual moving distance of the user, and may refer to S109. Then, the second device sends the collected actual distance of the user to the first device, and may refer to S111.
  • the user needs to carry the first device and the second device to run or walk.
  • the first device can be used to monitor the motion state of the user.
  • the second device is configured to receive a trigger of the first device to turn on the GPS, and collect an actual moving distance of the user. In this way, the user does not need to manually turn on the GPS of the second device, which saves user operations and avoids unnecessary power consumption.
  • first device there is a communication connection between the first device and the second device, such as a Bluetooth communication connection or the like, to implement data communication between the first device and the second device.
  • a communication connection such as a Bluetooth communication connection or the like, to implement data communication between the first device and the second device.
  • the first device calculates an actual motion step of the user according to the actual moving distance and the collected number of the moving steps. Width. Specifically, the actual motion step is the actual motion distance ⁇ the number of motion steps.
  • the first device updates the stride of the user in the preset database by using the actual motion stride. It can be understood that the updated step size of the user in the preset database is the actual stride of the user, and the step size in the updated preset database is used to calculate the motion distance of the user. The accuracy of the results.
  • the first device calculates a motion distance of the user according to the collected motion step number and the motion stride of the user in the preset database.
  • the preset database related to the embodiment of the present invention may include a motion state parameter of the user in addition to the stride of the user.
  • the motion state parameter of the user is used to represent the motion state of the user, and may specifically include at least one of the following: a type of exercise (running or walking), a stride frequency, and a sports environment in which the user is located (eg, a flat road) , slope, etc.).
  • the first device may also acquire the motion state parameter when detecting that the user is running or walking. Specifically, the first device may collect the motion state parameter of the user by using a motion sensor. For the acquisition of the physical information of the user, reference may be made to FIG. 1 and related content. I won't go into details here.
  • a set of motion state parameters corresponds to one step.
  • the step size of the user in the preset database may be as shown in Table 1.
  • the user's stride is determined by the state of motion of the user.
  • the preset database may include a stride corresponding to multiple users in different motion states, and may even include corresponding strides of all possible users (different signs) in different motion states, so that The first device can be applied to more users.
  • Table 1 is only an implementation manner provided by the embodiment of the present invention, and should not be construed as limiting.
  • the embodiment of the present invention does not limit the specific step frequency corresponding to the "low speed walking", “high speed walking”, “low speed running” and “high speed running” in Table 1, and may be defined according to actual conditions.
  • the motion state of the user may be further divided, and is not limited to the four motion states in Table 1.
  • the preset database may further include a latest calibration time corresponding to the stride of the user, and is used to indicate the time when the stride of the user is updated last time.
  • the first device may determine whether the difference between the latest calibration time and the current time is greater than a preset time threshold, and if yes, determine that the user's stride needs to be calibrated; otherwise, determine the user. The stride does not need to be calibrated.
  • the user's stride is as shown in Table 1. If the time when the corresponding step of the user in the "low speed walking” state is updated last time is "September 1, 2016", and the current time "October 1, 2016” is different by 30 days, then the said The first device can determine that the corresponding stride of the user in the "low speed walking” state needs to be calibrated.
  • Table 1 the time when the corresponding step of the user in the "low speed walking” state is updated last time is "September 1, 2016”, and the current time "October 1, 2016” is different by 30 days.
  • the first device may also trigger calibration of the preset database according to a user's instruction. That is to say, whether the user stride needs to be calibrated in the preset database can also be determined by the user.
  • the first device may further determine, according to other conditions, whether the pre- Set the user's stride in the database to correct.
  • the first device may also trigger calibration on the preset database when the total running mileage of the user reaches a preset mileage value (for example, 500 kilometers). It can be understood that the total running mileage of the user reaches a preset mileage value (for example, 500 kilometers), which indicates that the user's athletic ability has been significantly improved, and the motion stride may change (for example, become larger).
  • the embodiment of the present invention does not limit the conditions for triggering calibration of the preset database.
  • the first device may request the second device to obtain the actual moving distance of the user, which may be referred to S107. -S111.
  • the second device may send the distance data to the first device once every fixed time (for example, 1 minute).
  • the distance data received by the first device to characterize the actual moving distance may be as shown in Table 2.
  • the first device monitors, by the motion sensor, that the user is in a low-speed running state in the first minute, and the second device collects the user in the first minute.
  • the sporting distance is 150 meters.
  • the first device may further monitor, by using a motion sensor, a motion state of the user at other times (eg, 2nd minute, 3rd minute, etc.), and the second device may also collect the The distance traveled by the user during the other time.
  • the first device may calculate the actual motion stride of the user and update the preset according to the actual motion distance obtained from the second device.
  • the stride of the user in the database is the first device.
  • Step 1 The first device calculates, according to the actual moving distance and the number of moving steps in the motion state characterized by the user in the same motion state parameter, the actual state of the user in the motion state characterized by the same motion state parameter. Stride.
  • the first device may divide the actual moving distance corresponding to "low speed running” (for example, 150 meters in the first minute) by the number of steps corresponding to "low speed running” (for example, 300 steps in the first minute).
  • the actual stride of the user in the "low speed running” exercise state that is, 50 cm.
  • the first device can set the actual distance of the user under "high-speed running” (for example, 300 meters in the second minute) and the number of steps in "high-speed running” (for example, 500 in the second minute). Step), and then divide the two to obtain the actual stride of the user in the "high-speed running" state of motion, that is, 60 cm.
  • the first device can calculate the actual stride of the user under “low speed walking” and “high speed walking” respectively, and details are not described herein again.
  • the examples are merely illustrative of the embodiments of the invention and should not be construed as limiting.
  • the first device may also perform statistics on the actual motion distance and the number of motion steps in the same motion state, and then calculate the actual stride by using the total actual motion distance and the total motion step number in the same state.
  • the first device may count the total actual moving distance (ie, the total distance in the second to 59 minutes) and the "high speed running" of the user under "high speed running” in Table 2.
  • the total number of steps e.g., the total number of steps in the 2nd to 59th minutes
  • dividing the two to obtain the actual stride of the user in the "high-speed running" motion state are merely illustrative of the embodiments of the invention and should not be construed as limiting.
  • Step 2 The first device updates the stride of the user in the motion state represented by the same motion state parameter in the preset database by using the calculated actual stride.
  • the first device may set the stride corresponding to “low speed running” in Table 1 (ie, 40 cm) updated to the calculated actual stride (ie 50 cm).
  • the first device may use the calculated actual stride of the user in three motion states of “high-speed running”, “low-speed walking” and “high-speed walking” to update the corresponding table 1 in FIG. 1 .
  • the corresponding steps of “High Speed Running”, “Low Speed Walking” and “High Speed Walking” are not repeated here.
  • the accuracy of calculating the moving distance of the user by the first device can be improved. And, after the calibration is completed, the first device can accurately calculate the motion distance of the user independently (without relying on the second device).
  • the first device may preprocess the distance data for the distance data that is obtained from the second device and that characterizes the actual moving distance. , filtering illegal data.
  • the illegal data refers to data that does not conform to natural laws and common sense. For example, a distance of 1000 meters in 1 minute is far beyond the limits of civilization.
  • the examples are merely illustrative of the embodiments of the invention and should not be construed as limiting.
  • FIG. 4 is another step calibration method according to an embodiment of the present invention.
  • the execution body of the stride calibration process is the second device (equipped with a distance monitoring component), and the second device will The preset database after the calibration is completed is sent to the first device, so that the first device calculates the moving distance of the user according to the stride in the preset database.
  • the second device detects that the user is walking or running.
  • the second device may detect, by the first device, that the user is walking or running.
  • the first device detects that the user is running or walking through the motion sensor, and may refer to S201.
  • the first device may send a notification to the second device to inform the second device that the user is walking or running, and may refer to S205.
  • the first device may count the number of motion steps of the user by using the motion sensor, and refer to S203.
  • the second device can be configured with a motion sensor that can be used to directly detect that the user is walking or running through the motion sensor.
  • the second device determines whether it is necessary to calibrate the stride of the user in the preset database. Specifically, if calibration is required, S209 and S211-S213 are performed.
  • the second device and the first device may each be configured with the preset database, and the two maintain the preset database synchronously.
  • the preset database please refer to FIG. 2 and related content, and details are not described herein again.
  • details on how to determine whether the step size of the user in the preset database needs to be calibrated refer to the related content in the embodiment of FIG. 3. Said.
  • the second device collects an actual moving distance of the user. Specifically, the second device may collect the actual moving distance of the user by using a distance monitoring module.
  • the second device acquires the number of motion steps of the user.
  • the second device may request the first device to acquire the number of motion steps of the user.
  • the first device can be configured with a motion sensor that can be used to collect the number of motion steps of the user.
  • the second device may send a request to the first device to request to obtain the number of motion steps of the user, and reference may be made to S211.
  • the first device receives the request, and sends the collected motion steps of the user to the second device in response to the request, and may refer to S213.
  • the second device may be configured with a motion sensor that can be used to directly collect the number of motion steps of the user through the motion sensor.
  • the first device may send the number of motion steps of the user to the second device every fixed time (eg, 1 minute).
  • the number of motion steps received by the second device can be as shown in Table 2.
  • the first device in order to ensure the accuracy of the stride calibration, may preprocess the data for data representing the number of motion steps of the user obtained from the first device. Filter illegal data.
  • the illegal data refers to data that does not conform to natural laws and common sense. For example, a step of 100 steps in 1 second is far beyond the limits of civilization.
  • the examples are merely illustrative of the embodiments of the invention and should not be construed as limiting.
  • first device there is a communication connection between the first device and the second device, such as a Bluetooth communication connection or the like, to implement data communication between the first device and the second device.
  • a communication connection such as a Bluetooth communication connection or the like, to implement data communication between the first device and the second device.
  • the second device may calculate the actual content of the user according to the number of motion steps of the user and the actual distance of the user. Movement step. Specifically, the actual motion step is the actual motion distance ⁇ the number of motion steps.
  • the second device may use the actual motion stride to update a stride of the user in the preset database.
  • the second device may send the preset database to the first device, so that the first device may be according to the updated location in the preset database. Calculating the motion distance of the user by the step size of the user may improve the accuracy of the first device calculating the motion distance of the user.
  • the first device updates the stride of the user in the preset database by using the actual motion stride.
  • the updated step size of the user in the preset database is the actual stride of the user, and the step size in the updated preset database is used to calculate the motion distance of the user. The accuracy of the results.
  • the preset database may include the motion state parameter of the user in addition to the stride of the user.
  • the motion state parameter of the user may include the motion state parameter of the user in addition to the stride of the user.
  • FIG. 2 and FIG. 3 where not Narration.
  • the second device when detecting, by the first device, that the user is running or walking, may further request the first device to acquire a motion state parameter of the user.
  • the second device may be configured with a motion sensor through which motion state parameters of the user may be directly acquired without being obtained by the first device.
  • the second device may calculate the actual motion stride of the user and update the user according to the number of motion steps of the user obtained from the first device. Preset the user's stride in the database:
  • Step one the second device calculates, according to the actual moving distance and the number of moving steps in the motion state characterized by the user in the same motion state parameter, the actual state of the user in the motion state characterized by the same motion state parameter. Stride.
  • the second device may divide the actual moving distance (150 meters in the first minute) corresponding to the "low speed running” by the number of steps corresponding to the "low speed running” (for example, 300 steps in the first minute).
  • the actual stride of the user in the "low speed running” state of motion ie 50 cm.
  • the second device can set the actual distance of the user under "high speed running” (for example, 300 meters in the second minute) and the number of steps in "high speed running” (for example, 500 in the second minute). Step), and then divide the two to obtain the actual stride of the user in the "high-speed running” state of motion, that is, 60 cm.
  • the second device can calculate the actual stride of the user under “low speed walking” and “high speed walking” respectively, and details are not described herein again.
  • the second device can also perform actual moving distance and transport in the same motion state.
  • the number of moving steps is counted, and then the actual stride is calculated using the total actual moving distance and the total number of moving steps in the same state.
  • the second device can count the total actual moving distance (ie, the total distance in the second to 59 minutes) and the "high speed running" of the user under "high speed running” in Table 2.
  • the total number of steps e.g., the total number of steps in the 2nd to 59th minutes
  • dividing the two to obtain the actual stride of the user in the "high-speed running" motion state are merely illustrative of the embodiments of the invention and should not be construed as limiting.
  • Step 2 The second device updates the stride of the user in the motion state represented by the same motion state parameter in the preset database by using the calculated actual stride.
  • the accuracy of the first device calculating the motion distance of the user by using the preset database may be improved. And, after the calibration is completed, the first device can accurately calculate the motion distance of the user independently (without relying on the second device).
  • the first device and the second device provided by the embodiment of the present invention are as follows: The first device 100 and the second device 200 shown in FIG. 5 and FIG. 6, respectively.
  • the first device 100 is not configured with a distance monitoring module, such as a GPS module or an RF positioning module, and cannot directly measure the actual moving distance of the user.
  • the first device 100 can be configured with a motion sensor capable of acquiring motion types (running or walking) of the user in motion, stride frequency, or motion state parameters such as the motion environment in which the user is located (eg, a flat road, a slope, etc.).
  • the first device 100 may be the wearable device 10 in FIG. 1 , and may specifically include: a smart bracelet, smart glasses, smart accessories, smart clothing, and the like.
  • the second device 200 can be configured with a distance monitoring module, such as a GPS module and an RF positioning module, which can directly measure the actual moving distance of the user.
  • the second device 200 can also be configured with a motion sensor capable of collecting the type of motion (running or walking) of the user in motion, the stride frequency or the sports environment in which the user is located (eg, a flat road, a slope) Etc.) and other motion state parameters.
  • the second device 200 may be the smart phone 20 in FIG. 1 or other portable terminals configured with a distance monitoring module.
  • the first device 100 may include a processor 101, a memory 102 (one or more computer readable storage media), a communication module 103, and an input and output system 105. These components can communicate over one or more communication buses 104.
  • the input and output system 105 is mainly used to implement the interaction function between the first device 100 and the user/external environment, and mainly includes the input and output devices of the first device 100.
  • the input and output system 105 can include a touch screen controller 1052, an audio controller 1052, and a sensor controller 1053. Each controller may be coupled to a corresponding peripheral device (a touch screen 1054, an audio circuit 1055, and a motion sensor 1056.
  • the motion sensor 1056 may include an accelerometer, a gyroscope, a magnetometer, etc., for monitoring user motion. The state, the user's motion data is collected, such as the number of motion steps, the motion step frequency, etc. It should be noted that the input and output system 105 may also include other I/O peripherals.
  • the processor 101 can be integrated to include: one or more CPUs, a clock module, and a power management module.
  • the clock module is primarily used to generate the clocks required for data transfer and timing control for the processor 101.
  • the power management module is mainly used to provide a stable, high-accuracy voltage for the processor 101, the communication module 103, and the input/output system 105 and the like.
  • the communication module 103 is configured to receive and transmit wireless signals, and mainly integrates the receiver and the transmitter of the first device 100.
  • the communication module 103 can include, but is not limited to, a Wi-Fi module and a Bluetooth module.
  • the Wi-Fi module and the Bluetooth module can be used for other communication devices, for example, the second device 200, and establish communication connections such as Wi-Fi and Bluetooth to achieve close-range data communication (as shown in FIG. 1).
  • the communication module 103 can be implemented on a separate chip.
  • Memory 102 is coupled to processor 101 for storing various software programs and/or sets of instructions.
  • memory 102 can include high speed random access memory, and can also include non-volatile memory, such as one or more magnetic disk storage devices, flash memory devices, or other non-volatile solid state storage devices.
  • the memory 102 can store an operating system (hereinafter referred to as a system) such as an embedded operating system such as ANDROID, IOS, WINDOWS, or LINUX.
  • the memory 102 can also store a network communication program that can be used to communicate with one or more terminal devices, such as the second device.
  • the memory 102 can also store a user interface program that can realistically display the content of the application through a graphical user interface, such as interface 30 in FIG. Come out and receive user control operations on the application through input controls such as menus, dialogs, and buttons.
  • the second device 200 can include a processor 201, a memory 202 (one or more computer readable storage media), a communication module 203, an input output system 205, and a distance monitoring module 206. These components can communicate over one or more communication buses 204.
  • the distance monitoring module 206 is primarily operable to measure the user of the second device 200.
  • the distance monitoring module 206 can be a GPS module, and can directly measure the actual moving distance of the user through the satellite positioning system, and can be mainly used in an outdoor open environment.
  • the distance monitoring module 206 can also be an RF (Radio Frequency) positioning module, such as a Wi-Fi positioning module or a 3G positioning module, and can be mainly used to locate the user in an indoor environment. And measure the actual distance of the user's movement.
  • RF Radio Frequency
  • the distance monitoring module 206 can be an RF positioning module, such as a Wi-Fi positioning module, a 3G positioning module, which can be used to locate and measure a user using a satellite positioning system. It should be understood that the measurement results of the distance monitoring module 206 are highly accurate and reliable.
  • the distance monitoring module 206 is an integrated circuit that integrates an RF RF chip, a baseband chip, and a core processor, and adds related peripheral circuits.
  • the input and output system 205 is mainly used to implement an interaction function between the second device 200 and the user/external environment, and mainly includes input and output devices of the second device 200.
  • the input and output system 205 can include a touch screen controller 2051, a camera controller 2052, an audio controller 2053, and a sensor management module 2054. Each controller may be coupled to a corresponding peripheral device (touch screen 2055, camera 2056, audio circuit 2057, and sensor 2058. Note that the input/output system 205 may also include other I/O peripherals.
  • the processor 201 can be integrated to include: one or more CPUs, a clock module, and a power management module.
  • the clock module is primarily used to generate the clocks required for data transfer and timing control for the processor 201.
  • the power management module is mainly used to provide a stable, high-accuracy voltage for the processor 201, the communication module 203, the input/output system 205, and the distance monitoring module 206.
  • the communication module 203 is configured to receive and transmit radio frequency signals, and mainly integrates the receiver and the transmitter of the second device 200.
  • the communication module 203 communicates with the communication network and other communication devices via radio frequency signals.
  • the communication module 203 may include, but is not limited to, a mobile communication module (eg, a 3G module), a Wi-Fi module, a Bluetooth module, and the like.
  • the Wi-Fi module and the Bluetooth module can be used separately for Other communication devices, such as the first device 100, establish communication connections such as Wi-Fi, Bluetooth, etc. to achieve close-range data communication (as shown in FIG. 1).
  • the communication module 203 can be implemented on a separate chip.
  • Memory 202 is coupled to processor 201 for storing various software programs and/or sets of instructions.
  • memory 202 can include high speed random access memory, and can also include non-volatile memory, such as one or more magnetic disk storage devices, flash memory devices, or other non-volatile solid state storage devices.
  • the memory 202 can store an operating system (hereinafter referred to as a system) such as an embedded operating system such as ANDROID, IOS, WINDOWS, or LINUX.
  • the memory 202 can also store a network communication program that can be used to communicate with one or more additional devices, one or more terminal devices, one or more network devices.
  • the memory 202 can also store a user interface program, which can realistically display the content of the application through a graphical operation interface, and receive user control operations on the application through input controls such as menus, dialog boxes, and keys. .
  • the first device 100 shown in FIG. 5 may be the first device in the foregoing content
  • the second device 200 shown in FIG. 6 may be the second device in the foregoing all content.
  • the embodiment of FIG. 3 is taken as an example to describe the cooperation relationship between the components in the first device 100 and the components in the second device 200 in the embodiment of the present invention. Please refer to FIG. 7.
  • the touch screen 1054 receives the body sign information such as height and weight input by the user.
  • the touch screen 1054 can display the interface 30 shown in FIG. 1 to receive the physical sign information input by the user.
  • the touch screen 1054 can send the user's vital sign information to the processor 101.
  • the processor 101 can establish a preset database suitable for the user according to the physical condition information of the user. For details, refer to the foregoing embodiment of FIG. 2 for the process of establishing the preset database, and details are not described herein again.
  • the motion sensor 1056 detects that the user is running or walking and collects the number of motion steps of the user. In a particular implementation, motion sensor 1056 can buffer the collected data characterizing the actual motion distance in memory 102 or an internal storage medium of motion sensor 1056 or other storage medium within first device 100.
  • the motion sensor 1056 can notify the processor 101 of the event that the user is running or walking.
  • the processor 101 can determine whether it is necessary to calibrate the stride of the user in the preset database. Specifically, if calibration is not required, the user's stride in the preset database may be directly utilized. For calculating the motion distance, reference may be made to 20; if calibration is required, the second device 200 may be requested to acquire the actual moving distance of the user, which may be referred to 8. For the specific implementation of the determination, please refer to the embodiment of FIG. 3, and details are not described herein again.
  • the processor 101 can instruct the communication module 103, such as a Bluetooth module, to send a request to the second device 200.
  • the request is for requesting the second device 200 to obtain the actual moving distance of the user.
  • the communication module 103 sends a request to the second device 200 to request the actual distance of movement of the user.
  • the second device 200 receives the request through the communication module 203, such as a Bluetooth module.
  • the communication module 203 transmits the request to the processor 201, and the processor 201 responds to the request, and sends a ranging instruction to the distance monitoring module 206, and the trigger distance monitoring module 206 collects the actual moving distance of the user. .
  • the distance monitoring module 206 collects the actual moving distance of the user in response to the ranging instruction sent by the processor 201, and feeds back the collected actual moving distance of the user to the processor 201.
  • the processor 201 then instructs the communication module 203 to transmit the actual distance of movement of the user to the first device 100.
  • the distance monitoring module 206 may cache the collected data representing the actual moving distance in the internal storage medium of the memory 202 or the distance monitoring module 206 or other storage medium in the second device 200.
  • the communication module 203 transmits the actual moving distance of the user to the first device 100.
  • the communication module 103 of the first device receives the actual moving distance of the user, and can notify the processor 101 of the receiving event of the actual moving distance of the user.
  • the processor 101 acquires an actual moving distance of the user and a number of motion steps of the user.
  • the processor 101 calculates an actual stride of the user according to the actual moving distance of the user and the number of motion steps of the user, and updates the preset database by using the calculated actual stride.
  • the user's stride For details, refer to the embodiment of FIG. 3, and details are not described herein again.
  • the processor 101 may calculate the motion distance of the user by using the stride of the user in the preset database, and send the calculated motion distance to the touch screen 1054, and the touch screen 1054 may display the Movement distance.
  • FIG. 5 is only an implementation manner of the embodiment of the present invention.
  • the first device 100 may further include more or fewer components, which are not limited herein.
  • FIG. 6 is only one implementation of the embodiment of the present invention.
  • the second device 200 may further include more or fewer components, which are not limited herein.
  • FIG. 8 is a schematic structural diagram of an embodiment of a first device and a second device provided by an embodiment of the present invention, and a communication system configured by the two. As shown in FIG. 8, there may be a communication connection between the first device 300 and the second device 400, such as a Bluetooth connection, enabling data communication between the two.
  • a communication connection between the first device 300 and the second device 400 such as a Bluetooth connection, enabling data communication between the two.
  • the first device 300 may include a motion monitoring unit 301, a calibration unit 303, a communication unit 305, and a computing unit 307.
  • the first device 300 side may be configured with a preset database 309, and the stride in the preset database 309 may be used for providing the first device 300 to calculate the moving distance of the user. among them:
  • the motion monitoring unit 301 can be configured to detect that the user is walking or running, and collect the number of motion steps of the user;
  • the calibration unit 303 can be configured to determine whether it is necessary to calibrate the stride of the user in the preset database
  • the communication unit 305 can be configured to request the second device 400 to obtain the actual moving distance of the user if the calibration unit 303 determines that the step of the user in the preset database needs to be calibrated;
  • the calculating unit 307 is configured to calculate an actual stride of the user according to the actual moving distance of the user and the number of motion steps of the user;
  • the calibration unit 303 is further configured to update the stride of the user in the preset database by using the calculated actual stride.
  • the preset database may further include: a motion state parameter of the user, where the motion state parameter of the user corresponds to a stride of the user.
  • the motion state parameter of the user includes at least one of the following: a motion step frequency, a motion type, and a motion environment in which the user is located. For details, refer to the foregoing embodiment.
  • the motion monitoring unit 301 is further configured to collect the motion state parameter of the user when the user is detected to be walking or running.
  • the calculation unit 307 can also be used to operate on the same basis according to the user
  • the actual motion distance and the number of motion steps in the motion state characterized by the dynamic state parameter are calculated, and the actual stride of the user in the motion state characterized by the same motion state parameter is calculated.
  • the calibration unit 303 is further configured to update the stride of the user in the motion state characterized by the same motion state parameter in the preset database by using the calculated actual stride.
  • the second device 400 may include a communication unit 401 and a distance monitoring unit 403. among them:
  • the communication unit 401 can be configured to receive a request sent by the first device 300.
  • the distance monitoring unit 403 can be configured to collect an actual moving distance of the user in response to the request;
  • the communication unit 401 can also be configured to transmit the actual moving distance of the user to the first device 300.
  • the request is sent by the first device 300 through the communication unit 305 after detecting that the user is walking or running, and determining that the user's stride needs to be calibrated in the preset database.
  • the first device 300 may be a mobile device configured with a motion sensor and not configured with a distance monitoring unit (such as a GPS), such as a smart bracelet, a smart watch, a smart accessory, and the like.
  • the second device 400 may be a mobile device configured with a distance detecting unit, such as a smart phone, a smart bracelet, or the like.
  • FIG. 9 is a schematic structural diagram of another embodiment of a first device and a second device according to an embodiment of the present invention, and a communication system configured by the two.
  • a communication connection between the first device 500 and the second device 600 such as a Bluetooth connection, enabling data communication between the two.
  • the first device 500 side may be configured with a preset database 505, and the stride in the preset database 505 may be used for providing the first device 500 to calculate the moving distance of the user.
  • the second device side maintains a preset database 609, and the second device can calibrate the stride in the preset database 609, and send the calibrated preset database 609 to the first device 500, and the preset database has been updated. 505.
  • the first device 500 may include a motion monitoring unit 501 and a communication unit 505. among them:
  • the motion monitoring unit 501 can be configured to detect that the user is walking or running, collecting the motion of the user Step count;
  • the communication unit 505 is configured to receive a request sent by the second device, and send the number of motion steps of the user to the second device in response to the request.
  • the request is sent by the second device 600 after detecting that the user is walking or running through the first device 500 and determining that the user's stride needs to be calibrated in the preset database 609.
  • the second device 600 may include a communication unit 601, a calibration unit 603, a distance monitoring unit 605, and a calculation unit 607. among them:
  • the communication unit 601 can be configured to detect, by the first device 500, that the user is walking or running;
  • the calibration unit 603 can be configured to determine whether it is necessary to calibrate the stride of the user in the preset database
  • the distance monitoring unit 605 can be configured to: if the calibration unit 605 determines that the step of the user in the preset database needs to be calibrated, collect the actual moving distance of the user, and obtain the number of motion steps of the user;
  • the calculating unit 607 is further configured to calculate an actual motion step of the user according to the motion step number of the user and the actual motion distance of the user,
  • the calibration unit 603 is further configured to update the stride of the user in the preset database by using an actual motion stride of the user;
  • the communication unit 601 can also be configured to send the preset database to the first device 500.
  • the preset database may further include: a motion state parameter of the user, and the motion state parameter of the user corresponds to a stride of the user.
  • the motion state parameter of the user may include at least one of the following: a motion step frequency, a motion type, and a motion environment in which the user is located. For details, refer to the foregoing embodiment.
  • the communication unit 601 in the second device 600 is further configured to request the first device 500 to acquire the motion state parameter of the user.
  • the motion monitoring unit 501 in the first device 500 can be used to collect the motion state parameters of the user.
  • the calculating unit 607 in the second device 600 is configured to calculate, according to the actual moving distance and the number of moving steps in the motion state characterized by the user in the same motion state parameter, the motion state represented by the user in the same motion state parameter.
  • the actual stride below.
  • the calibration unit 603 in the second device 600 can be configured to update the stride of the user in the motion state characterized by the same motion state parameter in the preset database by using the calculated actual stride.
  • the first device 500 may be a mobile device configured with a motion sensor and not configured with a distance monitoring unit (such as a GPS), such as a smart bracelet, a smart watch, a smart accessory, and the like.
  • the second device 600 may be a mobile device configured with a distance detecting unit, such as a smart phone, a smart bracelet, or the like.
  • an embodiment of the present invention further provides a communication system, where the communication system includes a first device and a second device.
  • the communication system may be the communication system shown in FIG. 8, the first device may be the first device 300, and the second device may be the second device 400.
  • the first device may be the first device 100 described in the embodiment of FIG. 5, and the second device may be the second device 200 described in the embodiment of FIG. It should be understood that the first device may also be the first device described in the embodiment of FIG. 3, and the second device may also be the second device described in the embodiment of FIG. 3.
  • the communication system may be the communication system shown in FIG. 9, the first device may be the first device 500, and the second device may be the second device 600.
  • the first device may be the first device 100 described in the embodiment of FIG. 5, and the second device may be the second device 200 described in the embodiment of FIG. It should be understood that the first device may also be the first device described in the embodiment of FIG. 4, and the second device may also be the second device described in the embodiment of FIG. 4.
  • the embodiment of the present invention implements a preset database (including the user's stride) for calculating the motion distance of the user on the device (ie, the first device) side that is not configured with the distance monitoring component.
  • the step of adjusting the stride in the preset database may be performed by acquiring the actual moving distance of the user by the device configured with the distance monitoring component (ie, the second device), so that the first device calculates the moving distance. The accuracy.
  • the first device can independently calculate the user's motion distance independently.
  • embodiments of the present invention can be provided as a method, system, or computer program product. Accordingly, the present invention may take the form of an entirely hardware embodiment, an entirely software embodiment, or a combination of software and hardware. Moreover, the present invention may employ computer-usable storage media (including but not limited to disk storage and storage) in one or more of the computer-usable program code embodied therein. The form of a computer program product implemented on an optical memory or the like.
  • the computer program instructions can also be stored in a computer readable memory that can direct a computer or other programmable data processing device to operate in a particular manner, such that the instructions stored in the computer readable memory produce an article of manufacture comprising the instruction device.
  • the apparatus implements the functions specified in one or more blocks of a flow or a flow and/or block diagram of the flowchart.
  • These computer program instructions can also be loaded onto a computer or other programmable data processing device such that a series of operational steps are performed on a computer or other programmable device to produce computer-implemented processing for execution on a computer or other programmable device.
  • the instructions provide steps for implementing the functions specified in one or more of the flow or in a block or blocks of a flow diagram.

Landscapes

  • Engineering & Computer Science (AREA)
  • General Physics & Mathematics (AREA)
  • Physics & Mathematics (AREA)
  • Radar, Positioning & Navigation (AREA)
  • Remote Sensing (AREA)
  • Theoretical Computer Science (AREA)
  • Databases & Information Systems (AREA)
  • Manufacturing & Machinery (AREA)
  • General Engineering & Computer Science (AREA)
  • Data Mining & Analysis (AREA)
  • Measurement Of Distances Traversed On The Ground (AREA)
  • Measurement Of The Respiration, Hearing Ability, Form, And Blood Characteristics Of Living Organisms (AREA)
  • Navigation (AREA)

Abstract

本文公开一种步幅校准方法。该方法包括：第一设备检测到用户在步行或跑步，并采集所述用户的运动步数，判断是否需要对预设数据库中所述用户的步幅进行校准，如果需要校准，则向第二设备请求获取所述用户的实际运动距离；所述预设数据库中所述用户的步幅用于提供给所述第一设备计算出所述用户的运动距离；所述第一设备根据所述用户的实际运动距离和所述用户的运动步数计算出所述用户的实际步幅，并利用计算得到的所述实际步幅更新所述预设数据库中的所述用户的步幅。上述方案可实现对未配置有距离监测元件的所述第一设备进行步幅估算校准，进而提高所述第一设备计算用户运动距离的准确性。

Description

一种步幅校准方法、相关设备及系统 技术领域
本发明涉及移动终端技术领域，尤其涉及一种步幅校准方法、相关设备及系统。
背景技术
近年来消费型电子产品，如移动设备(Mobile Device，包含智能型手机、平板计算机等)均配置有各类型的运动传感器，例如加速度计、陀螺仪及磁力计等，能够识别用户是处于步行还是跑步的运动状态，并能够统计用户的运动步数、运动姿态和卡路里消耗等运动指标，以提供用户更佳的应用功能和体验。
目前，配置有所述运动传感器的移动设备可以同时配置有距离监测元件(例如GPS模块)，也可以未配置有距离监测元件。配置有距离监测元件的移动设备，例如智能手机，可以通过卫星导航定位系统(Global Navigation Satellite System，常见的有GPS、北斗等)准确地测量出用户的实际运动距离。未配置所述距离监测元件的移动设备，例如可穿戴设备，无法直接测量出用户的实际运动距离，主要通过下述两种方式来获取用户的运动距离。
第一种方式，根据用户预先输入的体征信息，例如身高、体重、年龄等，估算出用户的步幅，然后利用估算出的步幅和运动传感器采集到的运动步数来计算用户的运动距离。这种方式得到的计算结果不太可信，计算出的运动距离与用户的实际运动距离之间通常存在较大误差。
第二种方式，通过和配置有距离监测元件(例如GPS模块)的其他设备建立通信连接(例如蓝牙连接)来获取对方设备测量到的用户的实际运动距离。例如，未配置有GPS模块的可穿戴设备与配置有GPS模块的智能手机建立蓝牙连接，可穿戴设备通过蓝牙连接来获取智能手机测量到的用户的实际运动距离。这种方式需要可穿戴设备与智能手机之间始终保持有通信连接，并且智能手机的GPS模块一直处于工作状态。
对于未配置所述距离监测元件的移动设备，现有技术中提供的获取用户的运动距离技术手段都不太理想，不便于用户通过这种移动设备来统计运动距离。
发明内容
本发明实施例提供了一种步幅校准方法、相关设备及系统，可实现对未配置有距离监测元件的设备进行步幅估算校准，进而提高该设备计算用户运动距离的准确性。并且，在校准完成后该设备可以独立的准确的计算出用户运动距离。
第一方面，提供了一种步幅校准方法，应用于第一设备侧。所述方法包括：第一设备检测到用户在步行或跑步，并采集所述用户的运动步数，判断是否需要对预设数据库中所述用户的步幅进行校准，如果需要校准，则可以向第二设备请求获取所述用户的实际运动距离。然后，所述第一设备可以根据所述用户的实际运动距离和所述用户的运动步数计算出所述用户的实际步幅。最后，所述第一设备可以利用计算得到的所述实际步幅更新所述预设数据库中的所述用户的步幅。
第二方面，提供了一种步幅校准方法，应用于第二设备侧。所述方法包括：第二设备接收第一设备发送的请求，响应所述请求，采集所述用户的实际运动距离，并将所述用户的实际运动距离发送给所述第一设备。
这里，所述请求是所述第一设备在检测到所述用户在步行或跑步，并判断出需要对所述预设数据库中所述用户的步幅进行校准后发送的。
本发明实施例中，所述预设数据库中所述用户的步幅用于提供给所述第一设备计算出所述用户的运动距离。
通过实施第一方面和第二方面描述的步幅校准方法，可实现在未配置有距离监测元件的所述第一设备侧利用第二设备采集到的实际运动距离和所述第一设备采集到的实际运动步数对预设数据库中的步幅进行步幅校准，以提高所述第一设备计算用户运动距离的准确性。并且，在校准完成后所述第一设备可以独立的准确的计算出用户运动距离。
结合第一方面或第二方面，所述预设数据库还可以包括：所述用户的运动状态参数，所述用户的运动状态参数与所述用户的步幅相对应。所述用户的运动状态参数可包括以下至少一项：运动步频、运动类型、所述用户所处的运动环境。在一些实施例中，所述预设数据库还可以包括：所述用户的体征信息， 所述用户的体征信息与所述用户的步幅相对应。
具体的，在所述检测到用户在步行或跑步时，所述第一设备还可以采集所述用户的运动状态参数，并根据所述用户在相同运动状态参数表征的运动状态下的实际运动距离和运动步数，计算得到所述用户在所述相同运动状态参数表征的运动状态下的实际步幅。然后，所述第一设备可以利用计算得到的所述实际步幅更新所述预设数据库中所述用户在所述相同运动状态参数表征的运动状态下的步幅。
在一些实施例中，所述预设数据库还可包括所述用户的步幅对应的最新校准时间。具体实现中，所述第一设备可以判断所述最新校准时间与当前时间的差值是否大于预设时间阈值，如果大于，则判定所述预设数据库中的所述用户的步幅需要校准，否则，则判定所述预设数据库中的所述用户的步幅不需要校准。
在一些实施例中，在所述第一设备向第二设备请求获取所述用户的实际运动距离之后，所述第一设备还可以过滤掉表征所述实际运动距离的数据中的非法数据。
第三方面，提供了一种步幅校准方法，应用于第二设备侧。所述方法包括：第二设备通过第一设备检测到用户在步行或跑步，判断是否需要对预设数据库中所述用户的步幅进行校准，如果需要校准，则可以采集所述用户的实际运动距离，并向所述第一设备请求获取所述用户的运动步数。所述第二设备可以根据所述用户的运动步数和所述用户的实际运动距离计算出所述用户的实际运动步幅，并利用所述用户的实际运动步幅更新所述预设数据库中所述用户的步幅，然后向所述第一设备发送所述预设数据库。
第四方面，提供了一种步幅校准方法，应用于第一设备侧。所述方法包括：第一设备检测到用户在步行或跑步，采集所述用户的运动步数，接收所述第二设备发送的请求，响应所述请求，向所述第二设备发送所述用户的运动步数。所述第一设备最后接收所述第二设备发送的预设数据库。
这里，所述请求是所述第二设备在检测到用户在步行或跑步，并判断出需要对预设数据库中所述用户的步幅进行校准之后发送的。
本发明实施例中，所述预设数据库可用于所述第一设备根据所述预设数据 库中所述用户的步幅和所述用户的运动步数计算出所述用户的运动距离。
通过实施第三方面和第四方面描述的步幅校准方法，可实现在配置有距离监测元件的所述第二设备侧利用第二设备采集到的实际运动距离和所述第一设备采集到的实际运动步数对预设数据库中的步幅进行步幅校准，并将校准后的所述预设数据库发送给未配置有距离监测元件的所述第一设备，进而提高所述第一设备计算用户运动距离的准确性。并且，在校准完成后所述第一设备可以独立的准确的计算出用户运动距离。
结合第三方面或第四方面，所述预设数据库还可以包括：所述用户的运动状态参数，所述用户的运动状态参数与所述用户的步幅相对应。所述用户的运动状态参数可包括以下至少一项：运动步频、运动类型、所述用户所处的运动环境。在一些实施例中，所述预设数据库还可以包括：所述用户的体征信息，所述用户的体征信息与所述用户的步幅相对应。
具体实现中，在所述检测到用户在步行或跑步时，所述第一设备还可以采集所述用户的运动状态参数。所述第二设备可以向所述第一设备请求获取所述用户的运动状态参数，并根据所述用户在相同运动状态参数表征的运动状态下的实际运动距离和运动步数，计算得到所述用户在所述相同运动状态参数表征的运动状态下的实际步幅，最后利用计算得到的所述实际步幅更新所述预设数据库中所述用户在所述相同运动状态参数表征的运动状态下的步幅。
在一些实施例中，所述预设数据库还可包括所述用户的步幅对应的最新校准时间。具体实现中，所述第二设备可以判断所述最新校准时间与当前时间的差值是否大于预设时间阈值，如果大于，则判定所述用户的步幅需要校准，否则，则判定所述用户的步幅不需要校准。
在一些实施例中，在所述第二设备向所述第一设备请求获取所述用户的运动步数之后，所述第二设备还可以过滤掉表征所述用户的运动步数的数据中的非法数据。
第五方面，提供了一种步幅校准方法，应用于第二设备侧。所述方法包括：第二设备检测到用户在步行或跑步，判断是否需要对预设数据库中所述用户的步幅进行校准，如果需要校准，则可以采集所述用户的实际运动距离，并采集所述用户的运动步数。所述第二设备可以根据所述用户的运动步数和所述用户 的实际运动距离计算出所述用户的实际运动步幅，并利用所述用户的实际运动步幅更新所述预设数据库中所述用户的步幅，然后向所述第一设备发送所述预设数据库。
第六方面，提供了一种步幅校准方法，应用于第一设备侧。所述方法包括：第一设备接收所述第二设备发送的预设数据库。
本发明实施例中，所述预设数据库可用于所述第一设备根据所述预设数据库中所述用户的步幅和所述用户的运动步数计算出所述用户的运动距离。
通过实施第五方面和第六方面描述的步幅校准方法，可实现在配置有距离监测元件的所述第二设备侧利用第二设备采集到的实际运动距离和所述第二设备采集到的实际运动步数对预设数据库中的步幅进行步幅校准，并将校准后的所述预设数据库发送给未配置有距离监测元件的所述第一设备，进而提高所述第一设备计算用户运动距离的准确性。并且，在校准完成后所述第一设备可以独立的准确的计算出用户运动距离。
第七方面，提供了一种移动设备，所述移动设备是第一设备，可包括：运动传感器、处理器和收发器，其中：
所述运动传感器用于检测到用户在步行或跑步，并采集所述用户的运动步数；
所述处理器用于判断是否需要对预设数据库中所述用户的步幅进行校准，如果需要校准；
所述收发器用于如果所述处理器判断需要对所述预设数据库中所述用户的步幅进行校准，则向第二设备请求获取所述用户的实际运动距离；所述第二设备用于采集所述用户的实际运动距离；所述预设数据库中所述用户的步幅用于提供给所述第一设备计算出所述用户的运动距离；
所述处理器还用于根据所述用户的实际运动距离和所述用户的运动步数计算出所述用户的实际步幅，并利用计算得到的所述实际步幅更新所述预设数据库中的所述用户的步幅。
第八方面，提供了一种移动设备，所述移动设备是第二设备，可包括：距离监测元件和收发器，其中：
所述收发器可用于接收第一设备发送的请求；
所述距离监测元件可用于响应所述请求，采集所述用户的实际运动距离；
所述收发器还可用于所述用户的实际运动距离发送给所述第一设备。
本发明实施例中，所述预设数据库可用于所述第一设备根据所述预设数据库中所述用户的步幅和所述用户的运动步数计算出所述用户的运动距离。
结合第七方面或第八方面，所述预设数据库还可以包括：所述用户的运动状态参数，所述用户的运动状态参数与所述用户的步幅相对应。所述用户的运动状态参数可包括以下至少一项：运动步频、运动类型、所述用户所处的运动环境。在一些实施例中，所述预设数据库还可以包括：所述用户的体征信息，所述用户的体征信息与所述用户的步幅相对应。
具体实现中，所述运动传感器还可用于在所述检测到用户在步行或跑步时，采集所述用户的运动状态参数。所述处理器还可用于：根据所述用户在相同运动状态参数表征的运动状态下的实际运动距离和运动步数，计算得到所述用户在所述相同运动状态参数表征的运动状态下的实际步幅，并利用计算得到的所述实际步幅更新所述预设数据库中所述用户在所述相同运动状态参数表征的运动状态下的步幅。
第九方面，提供了一种移动设备，所述移动设备是第二设备，可包括：距离监测元件和收发器，其中：距离监测元件、处理器和收发器，其中：
所述处理器用于通过第一设备检测到用户在步行或跑步；
所述处理器还用于判断是否需要对预设数据库中所述用户的步幅进行校准；
所述距离监测元件用于如果所述处理器判断需要对所述预设数据库中所述用户的步幅进行校准，则采集所述用户的实际运动距离；
所述收发器用于向所述第一设备请求获取所述用户的运动步数；
所述处理器还用于根据所述用户的运动步数和所述用户的实际运动距离计算出所述用户的实际运动步幅，并利用所述用户的实际运动步幅更新所述预设数据库中所述用户的步幅；
所述收发器还用于向所述第一设备发送所述预设数据库；所述预设数据库用于所述第一设备根据所述预设数据库中所述用户的步幅和所述用户的运动步数计算出所述用户的运动距离。
第十方面，提供了一种移动设备，所述移动设备是第一设备，可包括：运动传感器、处理器和收发器，其中：
所述运动传感器可用于检测到用户在步行或跑步，采集所述用户的运动步数；
所述收发器可用于接收所述第二设备发送的请求，响应所述请求，向所述第二设备发送所述用户的运动步数；
所述收发器还可用于接收所述第二设备发送的所述预设数据库。
这里，所述请求是所述第二设备在检测到用户在步行或跑步，并判断出需要对预设数据库中所述用户的步幅进行校准之后发送的。
本发明实施例中，所述预设数据库可用于所述第一设备根据所述预设数据库中所述用户的步幅和所述用户的运动步数计算出所述用户的运动距离。
结合第九方面或第十方面，所述预设数据库还可以包括：所述用户的运动状态参数，所述用户的运动状态参数与所述用户的步幅相对应。所述用户的运动状态参数可包括以下至少一项：运动步频、运动类型、所述用户所处的运动环境。在一些实施例中，所述预设数据库还可以包括：所述用户的体征信息，所述用户的体征信息与所述用户的步幅相对应。
具体实现中，所述收发器还可用于如果所述处理器判断需要对所述预设数据库中所述用户的步幅进行校准，则向所述第一设备请求获取所述用户的运动状态参数；所述第一设备用于采集所述用户的运动状态参数。所述处理器还可用于根据所述用户在相同运动状态参数表征的运动状态下的实际运动距离和运动步数，计算得到所述用户在所述相同运动状态参数表征的运动状态下的实际步幅，并利用计算得到的所述实际步幅更新所述预设数据库中所述用户在所述相同运动状态参数表征的运动状态下的步幅。
第十一方面，提供了一种移动设备，所述移动设备是第一设备，可包括用于执行第一方面方法的功能单元。
第十二方面，提供了一种移动设备，所述移动设备是第二设备，可包括用于执行第二方面方法的功能单元。
第十三方面，提供了一种移动设备，所述移动设备是第一设备，可包括用于执行第三方面方法的功能单元。
第十四方面，提供了一种移动设备，所述移动设备是第二设备，可包括用于执行第四方面方法的功能单元。
第十五方面，提供了一种步幅校准系统，其特征在于，包括：第一设备和第二设备，其中：
所述第一设备用于检测到用户在步行或跑步，并采集所述用户的运动步数；
所述第一设备还用于判断是否需要对预设数据库中所述用户的步幅进行校准，如果需要校准，则向所述第二设备请求获取所述用户的实际运动距离；所述预设数据库中所述用户的步幅用于提供给所述第一设备计算出所述用户的运动距离；
所述第二设备用于采集所述用户的实际运动距离；
所述第一设备还用于根据所述用户的实际运动距离和所述用户的运动步数计算出所述用户的实际步幅，并利用计算得到的所述实际步幅更新所述预设数据库中的所述用户的步幅。
第十六方面，提供了一种步幅校准系统，其特征在于，包括：第一设备和第二设备，其中：
所述第一设备用于检测到用户在步行或跑步，并采集所述用户的运动步数；
所述第二设备用于在通过所述第一设备检测到用户在步行或跑步后，判断是否需要对预设数据库中所述用户的步幅进行校准，如果需要校准，则采集所述用户的实际运动距离，并向所述第一设备请求获取所述用户的运动步数；所述预设数据库中所述用户的步幅用于提供给所述第一设备计算出所述用户的运动距离；
所述第二设备还用于根据所述用户的运动步数和所述用户的实际运动距离计算出所述用户的实际运动步幅，并利用所述用户的实际运动步幅更新所述预设数据库中所述用户的步幅；
所述第二设备还用于向所述第一设备发送所述预设数据库。
第十七方面，提供了一种存储计算机指令的可读非易失性存储介质，所述计算机指令被执行以实现上述第一方面描述的方法。
第十八方面，提供了一种存储计算机指令的可读非易失性存储介质，所述计算机指令被执行以实现上述第二方面描述的方法。
第十九方面，提供了一种存储计算机指令的可读非易失性存储介质，所述计算机指令被执行以实现上述第三方面描述的方法。
第二十方面，提供了一种存储计算机指令的可读非易失性存储介质，所述计算机指令被执行以实现上述第四方面描述的方法。
实施本发明实施例，可实现对未配置有距离监测元件的设备进行步幅估算校准，进而提高该设备计算用户运动距离的准确性。并且，在校准完成后该设备可以独立的准确的计算出用户运动距离。
附图说明
为了更清楚地说明本发明实施例中的技术方案，下面将对实施例描述中所需要使用的附图作简单地介绍。
图1是本发明实施例设计的一种应用场景的示意图；
图2是本发明实施例提供的一种包括用户的估算步幅的数据库的示意图；
图3是本发明实施例提供的一种步幅校准方法的流程示意图；
图4是本发明实施例提供的另一种步幅校准方法的流程示意图；
图5是本发明实施例提供的一种未配置距离监测元件的设备的硬件架构示意图；
图6是本发明实施例提供的一种配置有距离监测元件的设备的硬件架构示意图；
图7是图5实施例描述的设备和图6实施例描述的设备内各个部件的协作交互示意图；
图8是本发明实施例提供的一种步幅校准系统以及相关设备的功能模块示意图；
图9是本发明实施例提供的另一种步幅校准系统以及相关设备的功能模块示意图。
具体实施方式
本发明的实施方式部分使用的术语仅用于对本发明的具体实施例进行解释，而非旨在限定本发明。
图1是本发明实施例涉及的一种应用场景的示意图。如图1所示，用户同时携带可穿戴设备10和智能手机20在跑步或步行。其中：
智能手机20配置有距离监测元件，能够直接测量出该用户的实际运动距离。具体实现中，该距离监测元件可以是GPS模块，能够通过卫星定位系统直接测量出该用户的实际运动距离，可主要用于室外开阔环境。在一些实施例中，该距离监测元件也可以是RF(Radio Frequency，中文：射频)定位模块，例如Wi-Fi定位模块或3G定位模块等，可主要用于在室内环境中对该用户进行定位，并测量出该用户的实际运动距离。
可穿戴设备10未配置距离监测元件，不能直接测量出用户的实际运动距离。可穿戴设备10配置有运动传感器，例如加速度计、陀螺仪及磁力计等，能够识别出用户的运动状态(是步行还是跑步)、步频、运动环境等等，并且能够统计出该用户的运动步数。在一些实施例中，可穿戴设备10还可以统计用户的其他体征参数，例如心跳、呼吸率等。
本发明实施例中，可穿戴设备10和智能手机20之间可存在无线通信连接，例如蓝牙连接，可实现二者之间的数据通信。
本发明实施例中，可穿戴设备10侧可配置有用于估算用户的运动步幅的步幅估算模型以及预设数据库。所述步幅估算模型的变量可以是步幅的影响因素。所述预设数据库可用于记录所述影响因素与步幅之间的映射关系。
本发明实施例中，步幅的影响因素可包括以下一项或多项：用户的体征信息(例如性别、身高、体重、年龄等)、运动类型(步行或跑步)、步频(即单位时间内的运动步数)和运动环境(平路、坡路等)等。其中，所述运动类型、步频和运动环境可概括称为运动状态参数，用于指示用户的运动状态。通常，身高较高的人的步幅比身高较矮的人的步幅大，男性的步幅比女性的步幅大，年轻人比老人的步幅大，体型适中的人的步幅比体型肥胖的人的步幅大。通常，用户快速跑步时的步幅比慢速跑步时的步幅大，用户快速步行时的步幅比慢速步行时的步幅大。实际应用中，影响步幅的因素还可包括其他因素，例如运动心跳、运动呼吸率，这里不作限制。
具体实现中，可穿戴设备10可通过运动传感器来采集到上述运动状态参数。对于上述运动类型，运动传感器可以感知出步行和跑步的区别，通常人体 在跑步时，身体垂直于地面的上下振幅比较大。对于上述步频，运动传感器可感知出单位时间内用户的运动步数，单位时间内的运动步数越多，步频越大，反之越小。对于上述运动环境，运动传感器可感知出人体在不同运动环境下的差别，例如人体在平路上步行的运动状态和人体在坡路上的运动状态的区别可以通过大量经验数据的统计分析得出。示例仅仅是本发明实施例的一种实现方式，关于如何利用运动传感器获取到所述运动状态参数的具体实现，本发明实施例不做限制。
具体实现中，穿戴设备10可用于显示界面30，用户可以在界面30中输入自己的体征信息，例如性别、身高、体重等等。
以身高和步频这两种影响因素为例，本发明实施例涉及的所述步幅估算模型可表示为：step＝f(height，pedospeed)，其中，step表示步幅，height表示用户的身高，pedospeed表示用户的运动步频(单位可以是步/分钟)。函数f可用于根据身高和运动步频映射出相应的步幅。
具体的，函数f可以表示为：
f(height，pedospeed)＝a*pedospeedm+b*heightn+c
其中，a、b表示各项因式的权重，m、n表示各因素的指数，c表示调整增量。具体实施时，可以采用机器学习算法来训练出a、b、m、n和c的值。训练时，使用大量的已知步频和已知身高作为输入，使用所述已知步频和已知身高对应的实际步幅作为输出。
需要说明的，不限于上述算法表达式，所述步幅估算模型f还可以是其他用于估算步幅的模型，这里不做限制。并且，不限于身高和步频这两种影响因素，函数f的自变量可包括更多或更少影响步幅的因素，即所述步幅估算模型还可以从更多维度或更少维度来估算步幅。
以身高和步频这两种影响因素为例，本发明实施例涉及的所述预设数据库可如图2所示，其中：X轴表示用户的运动步频，Y轴表示用户的身高，Z轴表示用户的步幅。如图2所示，身高和步频共同影响步幅，身高和步频形成的组合与步幅之间存在所述步幅估算模型所表示的映射关系。
具体的，对于身高固定的单个用户(例如身高为170厘米)，该用户的运动步频越大，用户的步幅也相应越大。例如，图中的坐标点A表示：当身高 为170厘米的用户的运动步频为110步每分钟(步/分钟)时，通过上述步幅估算模型可估算出该用户的步幅为60厘米。图中的坐标点B表示：当身高为170厘米的用户的运动步频为80步每分钟(步/分钟)时，通过上述步幅估算模型可估算出该用户的步幅为50厘米。示例仅仅用于解释本发明实施例，不应构成限定。
具体的，对于步频相同的两个或多个用户，身高较高的用户的步幅相对较大。例如，图中坐标点B表示：当身高为170厘米的用户的运动步频为80步每分钟(步/分钟)时，通过上述步幅估算模型可估算出该用户的步幅为50厘米。图中坐标点C表示：当身高为190厘米的用户的运动步频为80步每分钟(步/分钟)时，通过上述步幅估算模型可估算出该用户的步幅为70厘米。示例仅仅用于解释本发明实施例，不应构成限定。
需要说明的，所述预设数据库不限于图2所示，还可以体现更多或更少的步幅影响因素与步幅之间的映射关系。
本发明实施例中，可以通过下述方式建立或初始化所述预设数据库。
第一种方式，配置在可穿戴设备10侧的所述预设数据库可以适用任何可能的用户。应理解的，人类的体征信息(例如身高)处于一个有限的合理范围中，可以被一一列举出来。人类的运动状态(例如运动步频)也处于一个有限的合理范围中，也可以被一一列举出来。因此，可穿戴设备10可以按照所述步幅估算模型估算出全部可能的用户(不同的体征)在不同运动状态下对应的步幅，并将估算出的步幅，以及该步幅对应的体征信息和运动状态对应的填充到所述预设数据库中。也即是说，所述预设数据库可包括利用所述步幅估算模型估算出的全部可能的用户(不同的体征)在不同运动状态下对应的步幅，这样任何用户佩戴可穿戴设备10跑步或步行时，可穿戴设备10都能估算出相应的步幅。
第二种方式，配置在可穿戴设备10侧的所述预设数据库也可以仅适用可穿戴设备10的使用者。具体实现中，可穿戴设备10可以通过界面30接收使用者输入的体征信息(例如身高)，当该使用者佩戴可穿戴设备10跑步或步行时，可穿戴设备10可识别出该使用者的运动状态(例如运动步频)，利用该使用者的体征信息和运动状态按照所述步幅估算模型估算出该使用者在该运动 状态下的步幅，并将估算出的步幅，以及该步幅对应的体征信息和运动状态对应的填充到所述预设数据库中。也即是说，所述预设数据库在初始时刻可以是空白的。可穿戴设备10可以在用户使用可穿戴设备10的过程中不断填充所述预设数据库，这样可减小所述预设数据库管理的数据量。
针对上述第二种方式，可穿戴设备10也可以在通过界面30接收使用者输入的体征信息后，从服务器获取针对该使用者的所述预设数据库。具体的，所述服务器可以是可穿戴设备10的服务平台，可用于管理利用所述步幅估算模型计算出的全部可能的用户(不同的体征)在不同运动状态下对应的步幅。从服务器获取到的所述预设数据库可具体表现为一张表格，该表格记录了该使用者在不同运动状态下对应的步幅，可参考后续表1。
在一些实施例中，所述预设数据库中的步频还可以粗略的分成几个步频范围，具体可如图2所示的高速步频、中速步频和低速步频。具体实现，可以利用一个步频范围对应的平均步幅估算用户的运动距离。
举例说明，假设低速步频对应的步频范围是40步/分钟至60步/分钟，且该范围内有100个离散的步频值A1～A100。那么，该低速步频对应的平均步幅
Figure PCTCN2016103393-appb-000001
当可穿戴设备10检测到用户处于低速跑步状态时，可穿戴设备10可以根据低速步频对应的平均步幅A，以及用户的运动步数N，估算出该用户的运动距离L＝A*N，其中：A>0，L>0，N为正整数。需要说明的，示例仅仅用于解释说明本发明实施例，不应构成限定。
可以理解的，所述预设数据库中的步幅均是利用所述步幅估算模型得到的估计值，并不能够准确的反映出用户的实际步幅，这样会导致利用所述预设数据库中的步幅计算出的运动距离也不准确。如图1所示，用户同时佩戴可穿戴设备10和智能手机20跑步，可穿戴设备10利用所述预设数据库中的步幅乘以运动步数计算出该用户的运动距离为L1。然而，智能手机20直接利用GPS测量出该用户的运动距离为L2，L2与L1之间往往存在偏差。
为了提高可穿戴设备10计算用户的运动距离的准确度，本发明实施例提供了一种步幅校准方法，可实现对未配置有距离监测元件的设备(如可穿戴设备10)进行步幅估算校准，进而提高该设备计算用户运动距离的准确性。并且，在校准完成后该设备可以独立的准确的计算出用户运动距离。
本发明实施例涉及的主要原理包括：利用配置有距离监测元件的设备(如前述智能手机20，下面称为第二设备)采集到的距离数据，对未配置有距离监测元件的设备(如前述可穿戴设备10，下面称为第一设备)侧的所述预设数据库中的步幅进行校准。并且，在校准完成后所述第一设备可以利用所述预设数据库中的步幅独立的准确的计算出用户运动距离。
下面结合附图详细描述本发明实施例提供的步幅校准方法。
图3是本发明实施例提供的一种步幅校准方法。在图3实施例中，所述第一设备利用所述第二设备(配置有距离监测元件，例如GPS模块、RF定位模块)采集到的距离数据，对所述第一设备侧的所述预设数据库中的步幅进行校准，根据校准完成后的所述预设数据库中的步幅计算用户的运动距离。下面展开描述：
S101，所述第一设备检测到用户在跑步或步行。具体的，所述第一设备可配置有运动传感器，例如加速度计、陀螺仪和磁力计等等。所述第一设备可以识别出所述用户所处的运动类型是跑步还是步行。
S103，所述第一设备采集所述用户的运动步数。具体的所述第一设备可以通过所述运动传感器统计出处所述用户的运动步数。
S105，所述第一设备判断是否需要对预设数据库中所述用户的步幅进行校准。具体的，如果需要校准，则执行S107-S111，否则执行S117。
本发明实施例中，所述预设数据库可配置在所述第一设备中，用于所述第一设备利用所述预设数据库中的步幅估算所述用户的运动距离。关于所述预设数据库的说明和实现请参考图2及相关内容，这里不再赘述。
S107-S111，所述第一设备向所述第二设备请求获取所述用户的实际运动距离。具体的，所述第二设备可配置有距离监测元件，用于采集所述用户的实际运动距离。
具体实现中，所述第一设备可以向所述第二设备发送请求，以请求获得所述用户的实际运动距离，可参考S107。相应的，所述第二设备接收到该请求，并响应该请求，采集所述用户的实际运动距离，可参考S109。然后，所述第二设备将采集到的所述用户的实际运动距离发送给所述第一设备，可参考S111。
应理解的，本发明实施例中，所述用户需要携带所述第一设备和所述第二设备跑步或步行。所述第一设备可用于监测所述用户的运动状态。所述第二设备可用于接收所述第一设备的触发而开启GPS，并采集所述用户的实际运动距离。这样，所述用户无需手动开启所述第二设备的GPS，既节省用户操作又可避免不必要的电量消耗。
应理解的，所述第一设备和所述第二设备之间存在通信连接，例如蓝牙通信连接等，以实现所述第一设备与所述第二设备之间的数据通信。
S113，在获得所述第二设备采集到的所述用户的实际运动距离之后，所述第一设备根据所述实际运动距离和采集到的所述运动步数计算出所述用户的实际运动步幅。具体的，所述实际运动步幅＝所述实际运动距离÷所述运动步数。
S115，所述第一设备利用所述实际运动步幅更新所述预设数据库中所述用户的步幅。可以理解的，所述预设数据库中更新后的所述用户的步幅即所述用户的实际步幅，利用更新后的所述预设数据库中的步幅计算所述用户的运动距离可提高结果的准确度。
S117，所述第一设备根据采集到的所述运动步数和所述预设数据库中所述用户的运动步幅计算出所述用户的运动距离。
下面详细说明上述S105-S115描述的步幅校正过程。
参考前述内容可知，本发明实施例涉及的所述预设数据库除了包括所述用户的步幅外，还可以包括所述用户的运动状态参数。所述用户的运动状态参数用于表征所述用户所处的运动状态，具体可包括以下至少一项：运动类型(跑步或步行)、步频、所述用户所处的运动环境(例如平路、坡路等)。
具体实现中，在检测到所述用户在跑步或步行时，所述第一设备还可以获取所述运动状态参数。具体的，所述第一设备可以通过运动传感器采集到所述用户的运动状态参数。关于所述用户的体征信息的获取可参考图1及相关内容， 这里不赘述。
具体实现中，在所述预设数据库中，一组运动状态参数对应一个步幅。举例说明，所述预设数据库中所述用户的步幅可以如表1所示。
运动状态 低速步行 高速步行 低速跑步 高速跑步
步幅(厘米) 30 45 40 60
表1
应理解的，对于单个用户(身高、体重等体征信息是固定的)来说，该用户的步幅由所述用户所处的运动状态决定。参考前述内容可知，所述预设数据库可以包括多个用户在不同运动状态下对应的步幅，甚至可以包括全部可能的用户(不同的体征)在不同运动状态下对应的步幅，这样可使所述第一设备能够适用更多用户。
需要说明的，表1仅仅是本发明实施例提供的一种实现方式，不应构成限定。本发明实施例对表1中的“低速步行”、“高速步行”、“低速跑步”和“高速跑步”各自对应的具体步频不作限制，可以根据实际情况界定。具体实施时，还可以将用户的运动状态区分的更细，不限于表1中的四种运动状态。
本发明实施例中，所述预设数据库还可包括所述用户的步幅对应的最新校准时间，用于指示出所述用户的步幅最近一次被更新的时间。具体实现中，所述第一设备可判断所述最新校准时间与当前时间的差值是否大于预设时间阈值，如果大于，则判定所述用户的步幅需要校准，否则，则判定所述用户的步幅不需要校准。
举例说明，假设所述预设时间阈值为15天，所述用户的步幅如表1所示。如果所述用户在“低速步行”状态下对应的步幅最近一次被更新的时间是“2016年9月1日”，距离当前时间“2016年10月1日”相差30天，那么，所述第一设备可判定所述用户在“低速步行”状态下对应的步幅需要校准。示例仅仅用于解释本发明实施例，不应构成限定。
在一些实施例中，所述第一设备也可以按照用户的指令触发对所述预设数据库实施校准。也即是说，所述预设数据库中所述用户步幅是否需要校准还可以由用户决定。
需要说明的，所述第一设备还可以根据其他条件来决定是否需要对所述预 设数据库中所述用户的步幅进行校正。例如，所述第一设备还可以在所述用户的跑步总里程达到预设里程值(例如500公里)时，触发对所述预设数据库实施校准。可以理解的，所述用户的跑步总里程达到预设里程值(例如500公里)可表明所述用户的运动能力有了显著提升，运动步幅可能会出现变化(例如变大)。本发明实施例对触发校准所述预设数据库的条件不作限制。
本发明实施例中，如果需要对所述预设数据库中所述用户的步幅进行校准，则所述第一设备可以向所述第二设备请求获取所述用户的实际运动距离，可参考S107-S111。具体实现中，所述第二设备可以每隔固定时间(如1分钟)向所述第一设备发送一次距离数据。例如，所述第一设备接收到的表征所述实际运动距离的距离数据可如表2所示。
Figure PCTCN2016103393-appb-000002
表2
从表2可以看出，所述第一设备通过运动传感器监测到所述用户在第1分钟内处于低速跑步的运动状态，所述第二设备采集到所述用户在所述第1分钟内的运动距离是150米。同样的，所述第一设备还可以通过运动传感器监测到所述用户在其他时间(例如第2分钟、第3分钟等)内所处的运动状态，所述第二设备还可以采集到所述用户在所述其他时间内的运动距离。
需要说明的，表2仅仅用于解释本发明实施例，不应构成限定。
本发明实施例中，依据从所述第二设备那获得的所述实际运动距离，所述第一设备可具体通过下述步骤来计算出所述用户的实际运动步幅并更新所述预设数据库中所述用户的步幅：
步骤一，所述第一设备根据所述用户在相同运动状态参数表征的运动状态下的实际运动距离和运动步数，计算得到所述用户在所述相同运动状态参数表征的运动状态下的实际步幅。
举例说明，假设通过所述第二设备获取到的所述实际运动距离如表2所示。那么，所述第一设备可将“低速跑步”对应的实际运动距离(例如第1分钟内的150米)除以“低速跑步”对应的步数(例如第1分钟内的300步)得到所述用户在“低速跑步”的运动状态下的实际步幅，即50厘米。同样的，所述第一设备可将所述用户在“高速跑步”下的实际运动距离(例如第2分钟内的300米)和“高速跑步”下的步数(例如第2分钟内的500步)，然后将二者相除得到所述用户在“高速跑步”的运动状态下的实际步幅，即60厘米。同理，所述第一设备可计算得到所述用户分别在“低速步行”和“高速步行”下的实际步幅，这里不再赘述。示例仅仅用于解释本发明实施例，不应构成限定。
实际应用中，所述第一设备还可以对相同运动状态下的实际运动距离和运动步数进行统计，然后利用所述相同状态下总的实际运动距离和总的运动步数计算出实际步幅。例如，如表2所示，所述第一设备可统计表2中所述用户在“高速跑步”下的总实际运动距离(即第2至59分钟内的总距离)和“高速跑步”下的总步数(例如第2至59分钟内的总步数)，然后将二者相除得到所述用户在“高速跑步”的运动状态下的实际步幅。示例仅仅用于解释本发明实施例，不应构成限定。
可以理解的，通过步骤一计算得到的所述实际步幅更加真实的反映了所述用户在各个运动状态下的真实步幅。
步骤二，所述第一设备利用计算得到的所述实际步幅更新所述预设数据库中所述用户在所述相同运动状态参数表征的运动状态下的步幅。
举例说明，假设所述预设数据库中所述用户在各种运动状态下的步幅如表1所示，那么，所述第一设备可以将表1中“低速跑步”对应的步幅(即40厘米)更新为计算得到的实际步幅(即50厘米)。同理，所述第一设备可以利用计算得到的所述用户分别在“高速跑步”、“低速步行”和“高速步行”这三种运动状态下的实际步幅，来相应更新表1中的“高速跑步”、“低速步行”和“高速步行”各自对应的步幅，这里不再赘述。
可以理解的，通过对所述预设数据库中所述用户的步幅进行校准，可提高所述第一设备计算所述用户的运动距离的准确度。并且，在校准完成后，所述第一设备可以独立的(不依赖所述第二设备)准确计算出所述用户的运动距离。
在一些实施例中，为了保证步幅校准的准确度，对于从所述第二设备那获取来的表征所述实际运动距离的距离数据，所述第一设备可对所述距离数据进行预处理，过滤非法数据。这里，所述非法数据是指不符合自然规律和常识的数据。例如，1分钟内的运动距离为1000米就远远超出人类的极限。示例仅仅用于解释本发明实施例，不应构成限定。
图4是本发明实施例提供的另一种步幅校准方法。图4实施例与图3实施例的主要区别在于，在图4实施例中，所述步幅校准过程的执行主体是所述第二设备(配置有距离监测元件)，所述第二设备将校准完成后的所述预设数据库发送给所述第一设备，以使所述第一设备根据所述预设数据库中的步幅计算用户的运动距离。下面展开描述：
S201-S205，所述第二设备检测到用户在步行或跑步。
在一种实现方式中，所述第二设备可以通过所述第一设备检测到用户在步行或跑步。所述第一设备通过运动传感器检测到用户在跑步或步行，可参考S201。然后，所述第一设备可以向所述第二设备发送通知，以告知所述第二设备所述用户在步行或跑步，可参考S205。具体实现中，在检测到用户在步行或跑步后，所述第一设备可以通过所述运动传感器统计出所述用户的运动步数，可参考S203。
在另一种实现方式中，所述第二设备可配置有运动传感器，可用于通过该运动传感器直接检测到所述用户在步行或跑步。
S207，所述第二设备判断是否需要对预设数据库中所述用户的步幅进行校准。具体的，如果需要校准，则执行S209和S211-S213。
具体实现中，所述第二设备和所述第一设备可以各自配置有所述预设数据库，二者同步维护所述预设数据库。关于所述预设数据库的说明和实现请参考图2及相关内容，这里不再赘述。关于如何判断是否需要对预设数据库中所述用户的步幅进行校准的具体实现可参考图3实施例中的相关内容，这里不再赘 述。
S209，所述第二设备采集所述用户的实际运动距离。具体的，所述第二设备可以通过距离监测模块采集所述用户的实际运动距离。
S211-S213，所述第二设备获取所述用户的运动步数。
在一种实现方式中，所述第二设备可以向所述第一设备请求获取所述用户的运动步数。所述第一设备可配置有运动传感器，可用于采集所述用户的运动步数。具体实现中，所述第二设备可以向所述第一设备发送请求，以请求获得所述用户的运动步数，可参考S211。相应的，所述第一设备接收到该请求，并响应该请求，将采集到的所述用户的运动步数发送给所述第二设备，可参考S213。
在另一种实现方式中，所述第二设备可配置有运动传感器，可用于通过该运动传感器直接采集到所述用户的运动步数。
具体实现中，所述第一设备可以每隔固定时间(如1分钟)向所述第二设备发送一次所述用户的运动步数。例如，所述第二设备接收到的运动步数可如表2所示。在一些实施例中，为了保证步幅校准的准确度，对于从所述第一设备那获取来的表征所述用户的运动步数的数据，所述第一设备可对该数据进行预处理，过滤非法数据。这里，所述非法数据是指不符合自然规律和常识的数据。例如，1秒钟内的运动步数为100步就远远超出人类的极限。示例仅仅用于解释本发明实施例，不应构成限定。
应理解的，所述第一设备和所述第二设备之间存在通信连接，例如蓝牙通信连接等，以实现所述第一设备与所述第二设备之间的数据通信。
S215，在获得所述第一设备采集到的所述用户的运动步数之后，所述第二设备可根据所述用户的运动步数和所述用户的实际运动距离计算出所述用户的实际运动步幅。具体的，所述实际运动步幅＝所述实际运动距离÷所述运动步数。
S217，所述第二设备可利用所述实际运动步幅更新所述预设数据库中所述用户的步幅。
S219，在更新所述预设数据库之后，所述第二设备可以向所述第一设备发送所述预设数据库，以使所述第一设备可以根据所述预设数据库中更新后的所 述用户的步幅计算所述用户的运动距离，可提高所述第一设备计算所述用户的运动距离的准确性。
S221，相应的，所述第一设备利用所述实际运动步幅更新所述预设数据库中所述用户的步幅。可以理解的，所述预设数据库中更新后的所述用户的步幅即所述用户的实际步幅，利用更新后的所述预设数据库中的步幅计算所述用户的运动距离可提高结果的准确度。
参考前述内容可知，本发明实施例涉及的所述预设数据库除了包括所述用户的步幅外，还可以包括所述用户的运动状态参数，具体可参考图2及图3实施例，这里不赘述。
具体实现中，在通过所述第一设备检测到所述用户在跑步或步行时，所述第二设备还可以向所述第一设备请求获取所述用户的运动状态参数。在一些实施例中，所述第二设备可以配置有运动传感器，可通过该运动传感器直接采集到所述用户的运动状态参数，无需通过所述第一设备获得。
本发明实施例中，依据从所述第一设备那获得的所述用户的运动步数，所述第二设备可具体通过下述步骤来计算出所述用户的实际运动步幅并更新所述预设数据库中所述用户的步幅：
步骤一，所述第二设备根据所述用户在相同运动状态参数表征的运动状态下的实际运动距离和运动步数，计算得到所述用户在所述相同运动状态参数表征的运动状态下的实际步幅。
举例说明，假设通过所述第一设备获取到的所述用户的运动步数如表2所示。那么，所述第二设备可将“低速跑步”对应的实际运动距离(第1分钟内的150米)除以“低速跑步”对应的步数(例如第1分钟内的300步)得到所述用户在“低速跑步”的运动状态下的实际步幅，即50厘米。同样的，所述第二设备可将所述用户在“高速跑步”下的实际运动距离(例如第2分钟内的300米)和“高速跑步”下的步数(例如第2分钟内的500步)，然后将二者相除得到所述用户在“高速跑步”的运动状态下的实际步幅，即60厘米。同理，所述第二设备可计算得到所述用户分别在“低速步行”和“高速步行”下的实际步幅，这里不再赘述。
实际应用中，所述第二设备还可以对相同运动状态下的实际运动距离和运 动步数进行统计，然后利用所述相同状态下总的实际运动距离和总的运动步数计算出实际步幅。例如，如表2所示，所述第二设备可统计表2中所述用户在“高速跑步”下的总实际运动距离(即第2至59分钟内的总距离)和“高速跑步”下的总步数(例如第2至59分钟内的总步数)，然后将二者相除得到所述用户在“高速跑步”的运动状态下的实际步幅。示例仅仅用于解释本发明实施例，不应构成限定。
可以理解的，通过上述步骤一计算得到的所述实际步幅更加真实的反映了所述用户在各个运动状态下的真实步幅。
步骤二，所述第二设备利用计算得到的所述实际步幅更新所述预设数据库中所述用户在所述相同运动状态参数表征的运动状态下的步幅。
可以理解的，通过对所述预设数据库中所述用户的步幅进行校准，可提高所述第一设备利用所述预设数据库计算所述用户的运动距离的准确度。并且，在校准完成后，所述第一设备可以独立的(不依赖所述第二设备)准确计算出所述用户的运动距离。
需要说明的，图4实施例中未提及的内容可参考图3实施例，这里不再赘述。
下面介绍本发明实施例提供的所述第一设备和所述第二设备，可分别如图5、图6所示的第一设备100和第二设备200。
第一设备100未配置距离监测模块，例如GPS模块、RF定位模块，不能直接测量出用户的实际运动距离。第一设备100可配置有运动传感器，能够采集运动中的用户的运动类型(跑步或步行)、步频或所述用户所处的运动环境(例如平路、坡路等)等运动状态参数。具体实现中，第一设备100可以是图1中的可穿戴设备10，具体可包括：智能手环、智能眼镜、智能佩饰、智能服装等。
第二设备200可配置有距离监测模块，例如GPS模块、RF定位模块，能够直接测量出用户的实际运动距离。在一些实施例中，第二设备200也可配置有运动传感器，能够采集运动中的用户的运动类型(跑步或步行)、步频或所述用户所处的运动环境(例如平路、坡路等)等运动状态参数。具体实现中， 第二设备200可以是图1中的智能手机20，也可以是配置有距离监测模块的其他便携终端。
参考图5，第一设备100可包括：处理器101、存储器102(一个或多个计算机可读存储介质)、通信模块103、输入输出系统105。这些部件可在一个或多个通信总线104上通信。
输入输出系统105主要用于实现第一设备100和用户/外部环境之间的交互功能，主要包括第一设备100的输入输出装置。具体实现中，输入输出系统105可包括触摸屏控制器1052、音频控制器1052以及传感器控制器1053。其中，各个控制器可与各自对应的外围设备(触摸屏1054、音频电路1055以及运动传感器1056耦合。具体实现中，运动传感器1056可包括加速度计、陀螺仪和磁力计等，用于监测用户的运动状态，采集用户的运动数据，例如运动步数、运动步频等。需要说明的，输入输出系统105还可以包括其他I/O外设。
处理器101可集成包括：一个或多个CPU、时钟模块以及电源管理模块。所述时钟模块主要用于为处理器101产生数据传输和时序控制所需要的时钟。所述电源管理模块主要用于为处理器101、通信模块103以及输入输出系统105等提供稳定的、高精确度的电压。
通信模块103用于接收和发送无线信号，主要集成了第一设备100的接收器和发射器。具体实现中，通信模块103可包括但不限于：Wi-Fi模块、蓝牙模块。Wi-Fi模块、蓝牙模块可分别用于其他通信设备，例如第二设备200，建立Wi-Fi、蓝牙等通信连接，以实现近距离的数据通信(可如图1所示)。在一些实施例中，可在单独的芯片上实现通信模块103。
存储器102与处理器101耦合，用于存储各种软件程序和/或多组指令。具体实现中，存储器102可包括高速随机存取的存储器，并且也可包括非易失性存储器，例如一个或多个磁盘存储设备、闪存设备或其他非易失性固态存储设备。存储器102可以存储操作系统(下述简称系统)，例如ANDROID，IOS，WINDOWS，或者LINUX等嵌入式操作系统。存储器102还可以存储网络通信程序，该网络通信程序可用于与一个或多个终端设备，例如所述第二设备，进行通信。存储器102还可以存储用户接口程序，该用户接口程序可以通过图形化的操作界面，例如图1中的界面30，将应用程序的内容形象逼真的显示 出来，并通过菜单、对话框以及按键等输入控件接收用户对应用程序的控制操作。
参考图6，第二设备200可包括：处理器201、存储器202(一个或多个计算机可读存储介质)、通信模块203、输入输出系统205和距离监测模块206。这些部件可在一个或多个通信总线204上通信。
距离监测模块206主要可用于对第二设备200的用户进行测距。具体实现中，距离监测模块206可以是GPS模块，能够通过卫星定位系统直接测量出该用户的实际运动距离，可主要用于室外开阔环境。在一些实施例中，距离监测模块206也可以是RF(Radio Frequency，中文：射频)定位模块，例如Wi-Fi定位模块或3G定位模块等，可主要用于在室内环境中对该用户进行定位，并测量出该用户的实际运动距离。在一些实施例中，距离监测模块206可以是RF定位模块，例如Wi-Fi定位模块、3G定位模块，可用于利用卫星定位系统对用户进行定位、测距。应理解的，距离监测模块206的测量结果是高精度、可信赖的。具体实现中，距离监测模块206就是集成了RF射频芯片、基带芯片和核心处理器，并加上相关外围电路而组成的一个集成电路。
输入输出系统205主要用于实现第二设备200和用户/外部环境之间的交互功能，主要包括第二设备200的输入输出装置。具体实现中，输入输出系统205可包括触摸屏控制器2051、摄像头控制器2052、音频控制器2053以及传感器管理模块2054。其中，各个控制器可与各自对应的外围设备(触摸屏2055、摄像头2056、音频电路2057以及传感器2058耦合。需要说明的，输入输出系统205还可以包括其他I/O外设。
处理器201可集成包括：一个或多个CPU、时钟模块以及电源管理模块。所述时钟模块主要用于为处理器201产生数据传输和时序控制所需要的时钟。所述电源管理模块主要用于为处理器201、通信模块203、输入输出系统205以及距离监测模块206等提供稳定的、高精确度的电压。
通信模块203用于接收和发送射频信号，主要集成了第二设备200的接收器和发射器。通信模块203通过射频信号与通信网络和其他通信设备通信。具体实现中，通信模块203可包括但不限于：移动通信模块(例如3G模块)、Wi-Fi模块、蓝牙模块等等。具体实现中，Wi-Fi模块、蓝牙模块可分别用于与 其他通信设备，例如第一设备100，建立Wi-Fi、蓝牙等通信连接，以实现近距离的数据通信(可如图1所示)。在一些实施例中，可在单独的芯片上实现通信模块203。
存储器202与处理器201耦合，用于存储各种软件程序和/或多组指令。具体实现中，存储器202可包括高速随机存取的存储器，并且也可包括非易失性存储器，例如一个或多个磁盘存储设备、闪存设备或其他非易失性固态存储设备。存储器202可以存储操作系统(下述简称系统)，例如ANDROID，IOS，WINDOWS，或者LINUX等嵌入式操作系统。存储器202还可以存储网络通信程序，该网络通信程序可用于与一个或多个附加设备，一个或多个终端设备，一个或多个网络设备进行通信。存储器202还可以存储用户接口程序，该用户接口程序可以通过图形化的操作界面将应用程序的内容形象逼真的显示出来，并通过菜单、对话框以及按键等输入控件接收用户对应用程序的控制操作。
可以理解的，图5所示的第一设备100可以是前述全部内容中的所述第一设备，图6所示的第二设备200可以是前述全部内容中的所述第二设备。下面以图3实施例为例，详细说明第一设备100中的各个部件和第二设备200中的各个部件在本发明实施例中的协作关系，请参考图7。
1.触摸屏1054接收到用户输入的身高、体重等体征信息。具体实现中，触摸屏1054可以显示图1所示的界面30，以接收用户输入的体征信息。
2.触摸屏1054可以将所述用户的体征信息发送至处理器101。
3.处理器101可以根据所述用户的体征信息建立适用于所述用户的预设数据库。具体的，关于所述预设数据库的建立过程可参考前述图2实施例，这里不再赘述。
4-5.运动传感器1056检测到所述用户在跑步或步行，并采集所述用户的运动步数。具体实现中，运动传感器1056可以将采集到的表征所述实际运动距离的数据缓存在存储器102或者运动传感器1056的内部存储介质或者第一设备100内的其他存储介质中。
6-7.运动传感器1056可将所述用户在跑步或步行的事件通知给处理器101。处理器101可判断是否需要对预设数据库中所述用户的步幅进行校准。具体的，如果不需要校准，则可以直接利用所述预设数据库中所述用户的步幅 计算运动距离，可参考20；如果需要校准，则可向第二设备200请求获取所述用户的实际运动距离，可参考8。关于该判断的具体实现请参考图3实施例，这里不再赘述。
8.如果判断出需要对预设数据库中所述用户的步幅进行校准，处理器101可指令通信模块103，例如蓝牙模块，向第二设备200发送请求。所述请求用于向第二设备200请求获得所述用户的实际运动距离。
9.通信模块103向第二设备200发送请求，以请求获得所述用户的实际运动距离。相应的，第二设备200通过通信模块203，例如蓝牙模块，接收到所述请求。
10-11.通信模块203将所述请求传输给处理器201，处理器201响应所述请求，并向距离监测模块206下发测距指令，触发距离监测模块206采集所述用户的实际运动距离。
12-14.距离监测模块206响应处理器201下发的测距指令，采集所述用户的实际运动距离，并将采集到的所述用户的实际运动距离反馈给处理器201。然后处理器201指令通信模块203向第一设备100发送所述用户的实际运动距离。
具体实现中，距离监测模块206可以将采集到的表征所述实际运动距离的数据缓存在存储器202或者距离监测模块206的内部存储介质或者第二设备200内的其他存储介质中。
15.通信模块203向第一设备100发送所述用户的实际运动距离。相应的，第一设备的通信模块103接收到所述用户的实际运动距离，并可以将所述用户的实际运动距离的接收事件通知给处理器101。
16-17.处理器101获取所述用户的实际运动距离和所述用户的运动步数。
18-19.处理器101根据所述用户的实际运动距离和所述用户的运动步数计算出所述用户的实际步幅，并利用计算出的所述实际步幅更新所述预设数据库中所述用户的步幅。具体的，可参考图3实施例，这里不再赘述。
20-22.最后，处理器101可以利用所述预设数据库中所述用户的步幅计算出所述用户的运动距离，并将计算出的运动距离发送至触摸屏1054，触摸屏1054可以显示出该运动距离。
需要说明的，图5仅仅是本发明实施例的一种实现方式，实际应用中，第一设备100还可以包括更多或更少的部件，这里不作限制。图6仅仅是本发明实施例的一种实现方式，实际应用中，第二设备200还可以包括更多或更少的部件，这里不作限制。
图8示出了本发明实施例提供的第一设备和第二设备的一种实施例，以及二者构成的通信系统的结构示意图。如图8所示，第一设备300和第二设备400之间可存在通信连接，例如蓝牙连接，可实现二者之间的数据通信。下面展开描述。
如图8所示，第一设备300可包括：运动监测单元301、校准单元303、通信单元305和计算单元307。第一设备300侧可配置有预设数据库309，预设数据库309中的步幅可用于用于提供给第一设备300计算出所述用户的运动距离。其中：
运动监测单元301可用于检测到用户在步行或跑步，并采集所述用户的运动步数；
校准单元303可用于判断是否需要对预设数据库中所述用户的步幅进行校准；
通信单元305可用于如果校准单元303判断出需要对预设数据库中所述用户的步幅进行校准，则向第二设备400请求获取所述用户的实际运动距离；
计算单元307可用于根据所述用户的实际运动距离和所述用户的运动步数计算出所述用户的实际步幅；
校准单元303还可用于利用计算得到的所述实际步幅更新所述预设数据库中的所述用户的步幅。
本发明实施例中，所述预设数据库还可包括：所述用户的运动状态参数，所述用户的运动状态参数与所述用户的步幅相对应。所述用户的运动状态参数包括以下至少一项：运动步频、运动类型、所述用户所处的运动环境，具体可参考前述实施例。
具体的，运动监测单元301还可用于在所述检测到用户在步行或跑步时，采集所述用户的运动状态参数。计算单元307还可用于根据所述用户在相同运 动状态参数表征的运动状态下的实际运动距离和运动步数，计算得到所述用户在所述相同运动状态参数表征的运动状态下的实际步幅。校准单元303还可用于利用计算得到的所述实际步幅更新所述预设数据库中所述用户在所述相同运动状态参数表征的运动状态下的步幅。
如图8所示，第二设备400可包括：通信单元401和距离监测单元403。其中：
通信单元401可用于接收第一设备300发送的请求；
距离监测单元403可用于响应所述请求，采集所述用户的实际运动距离；
通信单元401还可用于将所述用户的实际运动距离发送给第一设备300。
具体的，所述请求是第一设备300在检测到所述用户在步行或跑步，并判断出需要对所述预设数据库中所述用户的步幅进行校准后通过通信单元305发送的。
具体实现中，第一设备300可以是配置有运动传感器，未配置有距离监测单元(如GPS)的移动设备，例如智能手环、智能手表、智能佩饰等。第二设备400可以是配置有距离检测单元的移动设备，例如智能手机、智能手环等。
需要说明，图8实施例中未提及的内容以及各个功能单元的具体实现，请参考图3实施例，这里不再赘述。
图9示出了本发明实施例提供的第一设备和第二设备的另一种实施例，以及二者构成的通信系统的结构示意图。如图9所示，第一设备500和第二设备600之间可存在通信连接，例如蓝牙连接，可实现二者之间的数据通信。下面展开描述。具体实现中，第一设备500侧可配置有预设数据库505，预设数据库505中的步幅可用于用于提供给第一设备500计算出所述用户的运动距离。第二设备侧维护有预设数据库609，所述第二设备可以对预设数据库609中的步幅进行校准，并将校准后的预设数据库609发送给第一设备500，已更新预设数据库505。
如图9所示，第一设备500可包括：运动监测单元501和通信单元505。其中：
运动监测单元501可用于检测到用户在步行或跑步，采集所述用户的运动 步数；
通信单元505可用于接收所述第二设备发送的请求，响应所述请求，向所述第二设备发送所述用户的运动步数。
具体的，所述请求是第二设备600在通过第一设备500检测到用户在步行或跑步，并判断出需要对预设数据库609中所述用户的步幅进行校准之后发送的。
如图9所示，第二设备600可包括：通信单元601、校准单元603、距离监测单元605和计算单元607。其中：
通信单元601可用于通过第一设备500检测到用户在步行或跑步；
校准单元603可用于判断是否需要对预设数据库中所述用户的步幅进行校准；
距离监测单元605可用于如果校准单元605判断出需要对预设数据库中所述用户的步幅进行校准，则采集所述用户的实际运动距离，并获取所述用户的运动步数；
计算单元607还可用于根据所述用户的运动步数和所述用户的实际运动距离计算出所述用户的实际运动步幅，
校准单元603还可用于利用所述用户的实际运动步幅更新所述预设数据库中所述用户的步幅；
通信单元601还可用于向第一设备500发送所述预设数据库。
在图9实施例中，所述预设数据库还可包括：所述用户的运动状态参数，所述用户的运动状态参数与所述用户的步幅相对应。所述用户的运动状态参数可包括以下至少一项：运动步频、运动类型、所述用户所处的运动环境，具体可参考前述实施例。
具体的，第二设备600中的通信单元601还可用于向第一设备500请求获取所述用户的运动状态参数。相应的，第一设备500中的运动监测单元501可用于采集所述用户的运动状态参数。第二设备600中的计算单元607可用于根据所述用户在相同运动状态参数表征的运动状态下的实际运动距离和运动步数，计算得到所述用户在所述相同运动状态参数表征的运动状态下的实际步幅。第二设备600中的校准单元603可用于利用计算得到的所述实际步幅更新所述预设数据库中所述用户在所述相同运动状态参数表征的运动状态下的步幅。
具体实现中，第一设备500可以是配置有运动传感器，未配置有距离监测单元(如GPS)的移动设备，例如智能手环、智能手表、智能佩饰等。第二设备600可以是配置有距离检测单元的移动设备，例如智能手机、智能手环等。
需要说明，图9实施例中未提及的内容以及各个功能单元的具体实现，请参考图4实施例，这里不再赘述。
另外，本发明实施例还提供了一种通信系统，所述通信系统包括第一设备和第二设备。
在一种实施例中，所述通信系统可以是图8所示的通信系统，所述第一设备可以是第一设备300，所述第二设备可以是第二设备400。在一些实施例中，所述第一设备可以是图5实施例描述的第一设备100，所述第二设备可以是图6实施例描述的第二设备200。应理解的，所述第一设备还可以是图3实施例中描述的所述第一设备，所述第二设备还可以是图3实施例中描述的所述第二设备。
在另一种实施例中，所述通信系统可以是图9所示的通信系统，所述第一设备可以是第一设备500，所述第二设备可以是第二设备600。在一些实施例中，所述第一设备可以是图5实施例描述的第一设备100，所述第二设备可以是图6实施例描述的第二设备200。应理解的，所述第一设备还可以是图4实施例中描述的所述第一设备，所述第二设备还可以是图4实施例中描述的所述第二设备。
综上所述，实施本发明实施例，对于未配置有距离监测元件的设备(即所述第一设备)侧的用于计算用户的运动距离的预设数据库(包含所述用户的步幅)，可通过配置有距离监测元件的设备(即所述第二设备)获取到所述用户的实际运动距离对所述预设数据库中的步幅进行校准，可提高所述第一设备计算运动距离的准确性。并且，在校准完成后，所述第一设备可以独立的准确的计算出用户运动距离。
本领域内的技术人员应明白，本发明的实施例可提供为方法、系统、或计算机程序产品。因此，本发明可采用完全硬件实施例、完全软件实施例、或结合软件和硬件方面的实施例的形式。而且，本发明可采用在一个或多个其中包含有计算机可用程序代码的计算机可用存储介质(包括但不限于磁盘存储器和 光学存储器等)上实施的计算机程序产品的形式。
本发明是参照根据本发明实施例的方法、设备(系统)、和计算机程序产品的流程图和/或方框图来描述的。应理解可由计算机程序指令实现流程图和/或方框图中的每一流程和/或方框、以及流程图和/或方框图中的流程和/或方框的结合。可提供这些计算机程序指令到通用计算机、专用计算机、嵌入式处理机或其他可编程数据处理设备的处理器以产生一个机器，使得通过计算机或其他可编程数据处理设备的处理器执行的指令产生用于实现在流程图一个流程或多个流程和/或方框图一个方框或多个方框中指定的功能的装置。
这些计算机程序指令也可存储在能引导计算机或其他可编程数据处理设备以特定方式工作的计算机可读存储器中，使得存储在该计算机可读存储器中的指令产生包括指令装置的制造品，该指令装置实现在流程图一个流程或多个流程和/或方框图一个方框或多个方框中指定的功能。
这些计算机程序指令也可装载到计算机或其他可编程数据处理设备上，使得在计算机或其他可编程设备上执行一系列操作步骤以产生计算机实现的处理，从而在计算机或其他可编程设备上执行的指令提供用于实现在流程图一个流程或多个流程和/或方框图一个方框或多个方框中指定的功能的步骤。
显然，本领域的技术人员可以对本发明进行各种改动和变型而不脱离本发明的精神和范围。这样，倘若本发明的这些修改和变型属于本发明权利要求及其等同技术的范围之内，则本发明也意图包含这些改动和变型在内。

Claims (20)

  1. 一种步幅校准方法，其特征在于，包括：
    第一设备检测到用户在步行或跑步，并采集所述用户的运动步数；
    所述第一设备判断是否需要对预设数据库中所述用户的步幅进行校准，如果需要校准，则向第二设备请求获取所述用户的实际运动距离；所述预设数据库中所述用户的步幅用于提供给所述第一设备计算出所述用户的运动距离；
    所述第一设备根据所述用户的实际运动距离和所述用户的运动步数计算出所述用户的实际步幅；
    所述第一设备利用计算得到的所述实际步幅更新所述预设数据库中的所述用户的步幅。
  2. 如权利要求1所述的方法，其特征在于，所述预设数据库还包括：所述用户的运动状态参数，所述用户的运动状态参数与所述用户的步幅相对应；
    所述方法还包括：在所述检测到用户在步行或跑步时，所述第一设备采集所述用户的运动状态参数；
    所述第一设备根据所述用户的实际运动距离和所述用户的运动步数计算出所述用户的实际步幅，并利用计算得到的所述实际步幅更新所述预设数据库中的所述用户的步幅，包括：
    所述第一设备根据所述用户在相同运动状态参数表征的运动状态下的实际运动距离和运动步数，计算得到所述用户在所述相同运动状态参数表征的运动状态下的实际步幅；
    所述第一设备利用计算得到的所述实际步幅更新所述预设数据库中所述用户在所述相同运动状态参数表征的运动状态下的步幅。
  3. 如权利要求2所述的方法，其特征在于，所述用户的运动状态参数包括以下至少一项：运动步频、运动类型、所述用户所处的运动环境。
  4. 如权利要求1-3中任一项所述的方法，其特征在于，所述预设数据库还包括：所述用户的体征信息，所述用户的体征信息与所述用户的步幅相对应。
  5. 如权利要求1-4中任一项所述的方法，其特征在于，所述预设数据库还包括所述用户的步幅对应的最新校准时间；所述判断是否需要对预设数据库中 所述用户的步幅进行校准，包括：判断所述最新校准时间与当前时间的差值是否大于预设时间阈值，如果大于，则判定所述用户的步幅需要校准，否则，则判定所述用户的步幅不需要校准。
  6. 如权利要求1-5中任一项所述的方法，其特征在于，在所述第一设备向第二设备请求获取所述用户的实际运动距离之后，还包括：所述第一设备过滤掉表征所述实际运动距离的数据中的非法数据。
  7. 一种步幅校准方法，其特征在于，包括：
    第二设备检测到用户在步行或跑步；
    所述第二设备判断是否需要对预设数据库中所述用户的步幅进行校准，如果需要校准，则采集所述用户的实际运动距离，并获取所述用户的运动步数；所述预设数据库中所述用户的步幅用于提供给所述第一设备计算出所述用户的运动距离；
    所述第二设备根据所述用户的运动步数和所述用户的实际运动距离计算出所述用户的实际运动步幅；
    所述第二设备利用所述用户的实际运动步幅更新所述预设数据库中所述用户的步幅；
    所述第二设备向所述第一设备发送所述预设数据库；所述预设数据库用于所述第一设备根据所述预设数据库中所述用户的步幅和所述用户的运动步数计算出所述用户的运动距离。
  8. 如权利要求7所述的方法，其特征在于，所述预设数据库还包括：所述用户的运动状态参数，所述用户的运动状态参数与所述用户的步幅相对应；
    所述方法还包括：如果需要校准，则所述第二设备向所述第一设备请求获取所述用户的运动状态参数；所述第一设备用于采集所述用户的运动状态参数；
    所述第二设备根据所述用户的实际运动距离和所述用户的运动步数计算出所述用户的实际步幅，并利用计算得到的所述实际步幅更新所述预设数据库中的所述用户的步幅，包括：
    所述第二设备根据所述用户在相同运动状态参数表征的运动状态下的实际运动距离和运动步数，计算得到所述用户在所述相同运动状态参数表征的运动状态下的实际步幅；
    所述第二设备利用计算得到的所述实际步幅更新所述预设数据库中所述用户在所述相同运动状态参数表征的运动状态下的步幅。
  9. 如权利要求8所述的方法，其特征在于，所述用户的运动状态参数包括以下至少一项：运动步频、运动类型、所述用户所处的运动环境。
  10. 如权利要求7-9中任一项所述的方法，其特征在于，所述预设数据库还包括：所述用户的体征信息，所述用户的体征信息与所述用户的步幅相对应。
  11. 如权利要求7-10中任一项所述的方法，其特征在于，所述预设数据库还包括所述用户的步幅对应的最新校准时间；所述第二设备判断是否需要对预设数据库中所述用户的步幅进行校准，包括：所述第二设备判断所述最新校准时间与当前时间的差值是否大于预设时间阈值，如果大于，则判定所述用户的步幅需要校准，否则，则判定所述用户的步幅不需要校准。
  12. 如权利要求7-11中任一项所述的方法，其特征在于，在所述第二设备向所述第一设备请求获取所述用户的运动步数之后，还包括：所述第二设备过滤掉表征所述用户的运动步数的数据中的非法数据。
  13. 一种步幅校准方法，其特征在于，包括：
    第一设备检测到用户在步行或跑步，采集所述用户的运动步数；
    所述第一设备接收所述第二设备发送的请求，响应所述请求，向所述第二设备发送所述用户的运动步数；所述请求是所述第二设备在检测到用户在步行或跑步，并判断出需要对预设数据库中所述用户的步幅进行校准之后发送的；所述第二设备用于采集所述用户的实际运动距离，根据所述用户的运动步数和所述用户的实际运动距离计算出所述用户的实际运动步幅，利用所述用户的实际运动步幅更新所述预设数据库中所述用户的步幅，并向所述第一设备发送所述预设数据库；所述预设数据库中所述用户的步幅用于提供给所述第一设备计算出所述用户的运动距离；
    所述第一设备接收所述第二设备发送的所述预设数据库。
  14. 一种移动设备，所述移动设备是第一设备，其特征在于，包括：运动传感器、处理器和收发器，其中：
    所述运动传感器用于检测到用户在步行或跑步，并采集所述用户的运动步数；
    所述处理器用于判断是否需要对预设数据库中所述用户的步幅进行校准，如果需要校准；
    所述收发器用于如果所述处理器判断需要对所述预设数据库中所述用户的步幅进行校准，则向第二设备请求获取所述用户的实际运动距离；所述第二设备用于采集所述用户的实际运动距离；所述预设数据库中所述用户的步幅用于提供给所述第一设备计算出所述用户的运动距离；
    所述处理器还用于根据所述用户的实际运动距离和所述用户的运动步数计算出所述用户的实际步幅，并利用计算得到的所述实际步幅更新所述预设数据库中的所述用户的步幅。
  15. 如权利要求14所述的设备，其特征在于，所述预设数据库还包括：所述用户的运动状态参数，所述用户的运动状态参数与所述用户的步幅相对应；
    所述运动传感器还用于在所述检测到用户在步行或跑步时，采集所述用户的运动状态参数；
    所述处理器还用于：根据所述用户在相同运动状态参数表征的运动状态下的实际运动距离和运动步数，计算得到所述用户在所述相同运动状态参数表征的运动状态下的实际步幅，并利用计算得到的所述实际步幅更新所述预设数据库中所述用户在所述相同运动状态参数表征的运动状态下的步幅。
  16. 一种移动设备，所述移动设备是第二设备，其特征在于，包括：距离监测元件、处理器和收发器，其中：
    所述处理器用于通过第一设备检测到用户在步行或跑步；
    所述处理器还用于判断是否需要对预设数据库中所述用户的步幅进行校准；
    所述距离监测元件用于如果所述处理器判断需要对所述预设数据库中所述用户的步幅进行校准，则采集所述用户的实际运动距离；
    所述收发器用于向所述第一设备请求获取所述用户的运动步数；
    所述处理器还用于根据所述用户的运动步数和所述用户的实际运动距离计算出所述用户的实际运动步幅，并利用所述用户的实际运动步幅更新所述预设数据库中所述用户的步幅；
    所述收发器还用于向所述第一设备发送所述预设数据库；所述预设数据库 用于所述第一设备根据所述预设数据库中所述用户的步幅和所述用户的运动步数计算出所述用户的运动距离。
  17. 如权利要求16所述的设备，其特征在于，所述预设数据库还包括：所述用户的运动状态参数，所述用户的运动状态参数与所述用户的步幅相对应；
    所述收发器还用于如果所述处理器判断需要对所述预设数据库中所述用户的步幅进行校准，则向所述第一设备请求获取所述用户的运动状态参数；所述第一设备用于采集所述用户的运动状态参数；
    所述处理器还用于根据所述用户在相同运动状态参数表征的运动状态下的实际运动距离和运动步数，计算得到所述用户在所述相同运动状态参数表征的运动状态下的实际步幅，并利用计算得到的所述实际步幅更新所述预设数据库中所述用户在所述相同运动状态参数表征的运动状态下的步幅。
  18. 一种移动设备，所述移动设备是第一设备，其特征在于，包括：运动传感器、处理器和收发器，其中：
    所述运动传感器可用于检测到用户在步行或跑步，采集所述用户的运动步数；
    所述收发器可用于接收所述第二设备发送的请求，响应所述请求，向所述第二设备发送所述用户的运动步数；所述请求是所述第二设备在检测到用户在步行或跑步，并判断出需要对预设数据库中所述用户的步幅进行校准之后发送的；所述第二设备用于采集所述用户的实际运动距离，根据所述用户的运动步数和所述用户的实际运动距离计算出所述用户的实际运动步幅，利用所述用户的实际运动步幅更新所述预设数据库中所述用户的步幅，并向所述第一设备发送所述预设数据库；所述预设数据库中所述用户的步幅用于提供给所述第一设备计算出所述用户的运动距离；
    所述收发器还可用于接收所述第二设备发送的所述预设数据库。
  19. 一种步幅校准系统，其特征在于，包括：第一设备和第二设备，其中：
    所述第一设备用于检测到用户在步行或跑步，并采集所述用户的运动步数；
    所述第一设备还用于判断是否需要对预设数据库中所述用户的步幅进行校准，如果需要校准，则向所述第二设备请求获取所述用户的实际运动距离；所述预设数据库中所述用户的步幅用于提供给所述第一设备计算出所述用户 的运动距离；
    所述第二设备用于采集所述用户的实际运动距离；
    所述第一设备还用于根据所述用户的实际运动距离和所述用户的运动步数计算出所述用户的实际步幅，并利用计算得到的所述实际步幅更新所述预设数据库中的所述用户的步幅。
  20. 一种步幅校准系统，其特征在于，包括：第一设备和第二设备，其中：
    所述第一设备用于检测到用户在步行或跑步，并采集所述用户的运动步数；
    所述第二设备用于在通过所述第一设备检测到用户在步行或跑步后，判断是否需要对预设数据库中所述用户的步幅进行校准，如果需要校准，则采集所述用户的实际运动距离，并向所述第一设备请求获取所述用户的运动步数；所述预设数据库中所述用户的步幅用于提供给所述第一设备计算出所述用户的运动距离；
    所述第二设备还用于根据所述用户的运动步数和所述用户的实际运动距离计算出所述用户的实际运动步幅，并利用所述用户的实际运动步幅更新所述预设数据库中所述用户的步幅；
    所述第二设备还用于向所述第一设备发送所述预设数据库。
PCT/CN2016/103393 2016-10-26 2016-10-26 一种步幅校准方法、相关设备及系统 WO2018076205A1 (zh)

Priority Applications (4)

Application Number Priority Date Filing Date Title
US16/345,598 US11237017B2 (en) 2016-10-26 2016-10-26 Stride length calibration method and system, and related device
EP16919864.5A EP3521764B1 (en) 2016-10-26 2016-10-26 Stride calibrating method, and relevant device and system
PCT/CN2016/103393 WO2018076205A1 (zh) 2016-10-26 2016-10-26 一种步幅校准方法、相关设备及系统
CN201680090283.0A CN109844460B (zh) 2016-10-26 2016-10-26 一种步幅校准方法、相关设备及系统

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
PCT/CN2016/103393 WO2018076205A1 (zh) 2016-10-26 2016-10-26 一种步幅校准方法、相关设备及系统

Publications (1)

Publication Number Publication Date
WO2018076205A1 true WO2018076205A1 (zh) 2018-05-03

Family

ID=62022959

Family Applications (1)

Application Number Title Priority Date Filing Date
PCT/CN2016/103393 WO2018076205A1 (zh) 2016-10-26 2016-10-26 一种步幅校准方法、相关设备及系统

Country Status (4)

Country Link
US (1) US11237017B2 (zh)
EP (1) EP3521764B1 (zh)
CN (1) CN109844460B (zh)
WO (1) WO2018076205A1 (zh)

Cited By (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US11123931B2 (en) 2016-06-08 2021-09-21 Trumpf Laser- Und Systemtechnik Gmbh Methods and devices for producing three-dimensional objects by selectively solidifying a construction material applied in layers
CN114343621A (zh) * 2022-01-14 2022-04-15 深圳市爱都科技有限公司 步幅校准方法、装置、服务器和计算机可读存储介质
WO2022156651A1 (zh) * 2021-01-25 2022-07-28 维沃移动通信有限公司 步长获取方法和电子设备

Families Citing this family (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN111141308B (zh) * 2019-12-25 2022-03-01 歌尔科技有限公司 一种步距校正方法、装置和可穿戴设备
EP4081825A4 (en) * 2020-02-07 2023-05-03 Samsung Electronics Co., Ltd. ELECTRONIC DISTANCE DEVICE USING ULTRA-WIDEBAND COMMUNICATIONS AND OPERATING METHOD THEREOF
CN112606347B (zh) * 2020-12-22 2022-09-20 西诺控股集团有限公司 自动校准注塑机喷嘴中心与头板定位圈同轴的方法及系统
CN113211527B (zh) * 2021-05-17 2022-09-27 北京大豪工缝智控科技有限公司 切布电机的控制方法、装置、设备及存储介质
CN113810845B (zh) * 2021-09-17 2022-10-14 广州悦跑信息科技有限公司 一种基于多角度监测的有效跑动距离统计方法及系统

Citations (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US6813582B2 (en) * 2002-07-31 2004-11-02 Point Research Corporation Navigation device for personnel on foot
CN101881625A (zh) * 2008-08-19 2010-11-10 幻音科技(深圳)有限公司 步幅校正方法、测距方法及计步装置
CN102853844A (zh) * 2011-06-27 2013-01-02 富泰华工业（深圳）有限公司 计步系统及具有数据传输功能的计步器
CN104937376A (zh) * 2012-11-07 2015-09-23 谷歌技术控股有限责任公司 计步器装置中基于频率的跨步长度修正的系统和方法
CN105403228A (zh) * 2015-12-18 2016-03-16 北京朗动科技有限公司 一种运动距离的确定方法和装置

Family Cites Families (7)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US7057551B1 (en) 2004-04-27 2006-06-06 Garmin Ltd. Electronic exercise monitor and method using a location determining component and a pedometer
US8831909B2 (en) * 2011-09-22 2014-09-09 Microsoft Corporation Step detection and step length estimation
TWI457539B (zh) 2012-12-19 2014-10-21 Ind Tech Res Inst 多姿態步距校正定位系統與方法
US20140309964A1 (en) * 2013-04-11 2014-10-16 Microsoft Corporation Internal Sensor Based Personalized Pedestrian Location
JP2015184159A (ja) 2014-03-25 2015-10-22 セイコーエプソン株式会社 相関係数補正方法、運動解析方法、相関係数補正装置及びプログラム
US10001386B2 (en) * 2014-04-03 2018-06-19 Apple Inc. Automatic track selection for calibration of pedometer devices
FR3021226B1 (fr) * 2014-05-20 2021-07-09 Withings Procede de calcul de l'activite d'un utilisateur

Patent Citations (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US6813582B2 (en) * 2002-07-31 2004-11-02 Point Research Corporation Navigation device for personnel on foot
CN101881625A (zh) * 2008-08-19 2010-11-10 幻音科技(深圳)有限公司 步幅校正方法、测距方法及计步装置
CN102853844A (zh) * 2011-06-27 2013-01-02 富泰华工业（深圳）有限公司 计步系统及具有数据传输功能的计步器
CN104937376A (zh) * 2012-11-07 2015-09-23 谷歌技术控股有限责任公司 计步器装置中基于频率的跨步长度修正的系统和方法
CN105403228A (zh) * 2015-12-18 2016-03-16 北京朗动科技有限公司 一种运动距离的确定方法和装置

Non-Patent Citations (1)

* Cited by examiner, † Cited by third party
Title
See also references of EP3521764A4 *

Cited By (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US11123931B2 (en) 2016-06-08 2021-09-21 Trumpf Laser- Und Systemtechnik Gmbh Methods and devices for producing three-dimensional objects by selectively solidifying a construction material applied in layers
WO2022156651A1 (zh) * 2021-01-25 2022-07-28 维沃移动通信有限公司 步长获取方法和电子设备
CN114343621A (zh) * 2022-01-14 2022-04-15 深圳市爱都科技有限公司 步幅校准方法、装置、服务器和计算机可读存储介质

Also Published As

Publication number Publication date
EP3521764A1 (en) 2019-08-07
CN109844460B (zh) 2021-08-20
US11237017B2 (en) 2022-02-01
US20190271564A1 (en) 2019-09-05
EP3521764A4 (en) 2019-11-13
EP3521764B1 (en) 2022-04-13
CN109844460A (zh) 2019-06-04

Similar Documents

Publication Publication Date Title
WO2018076205A1 (zh) 一种步幅校准方法、相关设备及系统
JP6684797B2 (ja) ウェアラブルデバイス間の接続関係を提供するシステムおよび方法
CN106462665B (zh) 可穿戴电子设备以及估计生活方式度量的方法
US9060682B2 (en) Distributed systems and methods to measure and process sport motions
EP3012756B1 (en) Computing weight control profile
US10001386B2 (en) Automatic track selection for calibration of pedometer devices
Mladenov et al. A step counter service for Java-enabled devices using a built-in accelerometer
JP6152763B2 (ja) 運動支援装置及び運動支援方法、運動支援プログラム
US10289902B2 (en) Data analysis device, data analysis method and storage medium
US20150185042A1 (en) Dynamic computation of distance of travel on wearable devices
US20150185045A1 (en) Dynamic calibration of relationships of motion units
CN105675048A (zh) 平衡识别精确度与耗电量的无线系统和方法
CN106030246B (zh) 用于对对象的周期性运动的循环数目进行计数的设备、方法和系统
CN107515004B (zh) 步长计算装置及方法
US10914793B2 (en) Method and system for magnetometer calibration
JP5757982B2 (ja) 活動支援装置、携帯端末、及び、活動支援システム
US20210353234A1 (en) Fitness Tracking System and Method of Operating a Fitness Tracking System
JP6999748B2 (ja) スポーツ又は健康活動を管理するための携帯計器
WO2016063661A1 (ja) 情報処理装置、情報処理方法、およびプログラム
US10352724B1 (en) Calibration factors for step frequency bands
Bardyn et al. MEMS inertial motion sensing watch for measuring walking and running activities
CN204428017U (zh) 具生理动量记录的表环
US20220095957A1 (en) Estimating Caloric Expenditure Based on Center of Mass Motion and Heart Rate
Nguyen et al. Adaptive step length estimation support indoor positioning system using low-cost inertial measurement units
US20220390238A1 (en) Route smoothing with map matched positioning coordinates

Legal Events

Date Code Title Description
121 Ep: the epo has been informed by wipo that ep was designated in this application

Ref document number: 16919864

Country of ref document: EP

Kind code of ref document: A1

NENP Non-entry into the national phase

Ref country code: DE

ENP Entry into the national phase

Ref document number: 2016919864

Country of ref document: EP

Effective date: 20190504