CN117073713A

CN117073713A - Step counting calibration method, system and equipment

Info

Publication number: CN117073713A
Application number: CN202210501645.8A
Authority: CN
Inventors: 周峰
Original assignee: Huawei Technologies Co Ltd
Current assignee: Huawei Technologies Co Ltd
Priority date: 2022-05-09
Filing date: 2022-05-09
Publication date: 2023-11-17

Abstract

The embodiment of the invention provides a step counting calibration method, a step counting calibration system and step counting calibration equipment. In the technical scheme provided by the embodiment of the invention, the first terminal equipment is connected with the first wearable equipment and the foot wearable equipment, and the method comprises the following steps: the first terminal equipment acquires first step counting data, and acquires second step counting data acquired by the first wearable equipment and third step counting data acquired by the foot wearable equipment; determining target equipment according to the first step counting data, the second step counting data and the third step counting data; generating step counting calibration information according to the first user characteristics, the equipment information of the first terminal equipment, the equipment information of the first wearable equipment and the target equipment; and uploading the step counting calibration information to cloud equipment. Therefore, when a user uses a plurality of electronic devices to count steps at the same time, the electronic device with the most accurate step count can be determined, so that the number of steps seen by the user is closest to the actual number of steps.

Description

Step counting calibration method, system and equipment

[ field of technology ]

The present invention relates to the field of computer technologies, and in particular, to a step counting calibration method, system, and apparatus.

[ background Art ]

Current electronic devices (e.g., terminal devices, wearable devices) can collect the number of steps of a user. Because the electronic devices are worn by users in different positions (such as the wearable device is generally worn on the wrist of the user, the mobile phone may be held in the hand, put in a pocket or be wrapped by the user, etc.), the exercise behavior habits of the users are different, and when the users carry the terminal device (such as the mobile phone) and the wearable device (such as the smart watch or the smart bracelet) to perform walking or running and other exercises, the number of steps obtained by the two electronic devices is different in most cases.

The steps recorded on the electronic equipment are related to hardware configuration, software algorithm version, user motion gesture and habit, but currently, industry manufacturers adopt a cutting method in the aspect of calculating the steps, so that the deviation between the steps seen by the user and the actual steps is larger.

[ invention ]

In view of this, the embodiments of the present invention provide a step counting calibration method, system, and device, where when a user uses a plurality of electronic devices to count steps at the same time, the electronic device with the most accurate step counting can be determined, so that the number of steps seen by the user is closest to the actual number of steps.

In a first aspect, an embodiment of the present invention provides a step counting calibration method applied to a first terminal device, where the first terminal device is connected to both a first wearable device and a foot wearable device, and the method includes:

Acquiring first step counting data, and acquiring second step counting data acquired by the first wearable device and third step counting data acquired by the foot wearable device;

determining target equipment according to the first step counting data, the second step counting data and the third step counting data;

generating step counting calibration information according to the first user characteristics, the equipment information of the first terminal equipment, the equipment information of the first wearable equipment and the target equipment;

and uploading the step counting calibration information to cloud equipment.

Thus, when a user uses a plurality of electronic devices to count steps at the same time, a target electronic device with more accurate step counting can be determined according to the plurality of electronic devices. Moreover, the step counting calibration information recorded by the cloud is related to the user characteristics, the equipment information of the terminal equipment and the equipment information of the wearable equipment. That is, if the user characteristics change, or the terminal device changes or the wearable device changes, the step count calibration information may also change accordingly.

With reference to the first aspect, in certain implementations of the first aspect, the target device includes the first terminal device or the first wearable device.

With reference to the first aspect, in certain implementation manners of the first aspect, the determining a target device according to the first step counting data, the second step counting data and the third step counting data includes:

determining step counting data closest to third step counting data in the first step counting data and the second step counting data according to the first step counting data, the second step counting data and the third step counting data;

when the step counting data closest to the third step counting data is the first step counting data, determining that the first terminal equipment is the target equipment;

and when the step counting data closest to the third step counting data is the second step counting data, determining that the first wearable device is the target device.

In this scheme, the third step counting data is the step counting data of the foot wearing device, the data is more accurate theoretically, and then which of the step counting data collected by other devices is closer to the step counting data of the foot wearing device, and which device is considered to be more accurate in step counting, and the more accurate device is recorded in the cloud. In this way, even in the event that the foot worn device is not enabled, the step count data of which of the other non-foot devices that are enabled can be determined more accurately by the cloud.

With reference to the first aspect, in certain implementation manners of the first aspect, the acquiring the first step counting data, and acquiring the second step counting data acquired by the first wearable device and the third step counting data acquired by the foot wearable device include:

sending a first instruction to the first wearable device and the foot wearable device and starting a step counting calibration operation, wherein the first instruction is used for indicating the first wearable device and the foot wearable device to start the step counting calibration operation;

stopping the step counting calibration operation to obtain first step counting data after a preset time period, and sending a second instruction to the first wearable device and the foot wearable device, wherein the second instruction is used for indicating the first wearable device and the foot wearable device to stop the step counting calibration operation;

and receiving the second step counting data sent by the first wearable device and the third step counting data sent by the foot wearable device.

With reference to the first aspect, in certain implementations of the first aspect, the first user characteristic includes one or more of: the gender, age, height, weight and stride of the user of the first terminal device.

With reference to the first aspect, in certain implementations of the first aspect, the device information includes a device type and a device model.

In a second aspect, an embodiment of the present invention provides a step counting calibration method, which is applied to a second terminal device, where the second terminal device is connected to a second wearable device, and the method includes:

generating query information according to the second user characteristics, the equipment information of the second terminal equipment and the equipment information of the second wearable equipment;

sending a query instruction to cloud equipment according to the query information, wherein the cloud equipment stores a step counting calibration information set, and the query instruction is used for enabling the cloud equipment to query a query result from the step counting calibration information set according to the query information;

receiving a query result sent by the cloud device;

and if the query result comprises the target equipment, displaying the step counting data acquired by the target equipment.

With reference to the second aspect, in certain implementations of the second aspect, the target device includes the second terminal device or the second wearable device;

when the query result comprises the second terminal equipment, displaying step counting data acquired by the second terminal equipment;

And when the query result comprises the second wearable device, displaying step counting data acquired by the second wearable device.

With reference to the second aspect, in certain implementations of the second aspect, the step counting calibration information set includes at least one step counting calibration information.

In a third aspect, an embodiment of the present invention provides a step counting calibration method, which is applied to a cloud device, where the cloud device stores a step counting calibration information set, and the method includes:

receiving a query instruction carrying query information uploaded by a second terminal device;

inquiring a query result corresponding to the query information from the step counting calibration information collection set according to the query instruction;

and sending the query result to the second terminal equipment.

With reference to the third aspect, in some implementations of the third aspect, the query result includes a target device or a query failure.

With reference to the third aspect, in certain implementations of the third aspect, the step-counting calibration information set includes at least one step-counting calibration information; the step counting calibration information comprises a first user characteristic, device information of a first terminal device, device information of a first wearable device and a target device.

With reference to the third aspect, in some implementations of the third aspect, the query information includes a second user feature, device information of the second terminal device, and device information of a second wearable device.

With reference to the third aspect, in some implementations of the third aspect, the querying, according to the query instruction, a query result corresponding to the query information from the step counting calibration information set includes:

determining the similarity between the step counting calibration information and the query information in the step counting calibration information collection according to the query instruction;

judging whether the similarity is larger than or equal to a set threshold value;

if the similarity is judged to be greater than or equal to a set threshold, judging whether the target device in the step counting calibration information corresponding to the maximum similarity comprises the first terminal device or the first wearable device;

if the target equipment in the step counting calibration information corresponding to the maximum similarity is judged to comprise the first terminal equipment, generating the query result comprising the second terminal equipment;

and if the first more accurate equipment target equipment in the step counting calibration information corresponding to the maximum similarity is judged to comprise the first wearable equipment, generating the query result comprising the second wearable equipment.

With reference to the third aspect, in some implementations of the third aspect, after the determining whether the similarity is greater than or equal to a set threshold, the method further includes:

and if the similarity is judged to be smaller than the set threshold value, generating the query result comprising query failure.

With reference to the third aspect, in some implementations of the third aspect, before receiving the query instruction carrying the query information uploaded by the second terminal device, the method further includes:

receiving the step counting calibration information uploaded by at least one first terminal device;

storing the step counting calibration information into the step counting calibration information collection set.

In a fourth aspect, an embodiment of the present invention provides a step counting calibration system, including: the first terminal device according to any of the first aspect, the second terminal device according to any of the second aspect and the cloud device according to any of the third aspect. In a fifth aspect, an embodiment of the present invention provides a first terminal device, including a processor and a memory, where the memory is configured to store a computer program, the computer program including program instructions that, when executed by the processor, cause the first terminal device to perform a method according to any one of the first aspect.

In a sixth aspect, an embodiment of the present invention provides a second terminal device, including a processor and a memory, where the memory is configured to store a computer program, the computer program including program instructions that, when executed by the processor, cause the second terminal device to perform a method according to any one of the second aspects.

In a seventh aspect, an embodiment of the present invention provides a cloud device, including a processor and a memory, where the memory is configured to store a computer program, where the computer program includes program instructions, when executed by the processor, cause the cloud device to perform a method according to any one of the third aspect.

In an eighth aspect, embodiments of the present invention provide a computer readable storage medium storing a computer program comprising program instructions which, when executed by a computer, cause the computer to perform a method as described above.

In the technical scheme of the step counting calibration method, the step counting calibration system and the electronic equipment provided by the embodiment of the invention, the first terminal equipment is connected with the first wearable equipment and the foot wearable equipment, and the method comprises the following steps: the first terminal equipment acquires first step counting data, and acquires second step counting data acquired by the first wearable equipment and third step counting data acquired by the foot wearable equipment; determining target equipment according to the first step counting data, the second step counting data and the third step counting data; generating step counting calibration information according to the first user characteristics, the equipment information of the first terminal equipment, the equipment information of the first wearable equipment and the target equipment; and uploading the step counting calibration information to cloud equipment. Therefore, when a user uses a plurality of electronic devices to count steps at the same time, the electronic device with the most accurate step count can be determined, so that the number of steps seen by the user is closest to the actual number of steps.

[ description of the drawings ]

In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings that are needed in the embodiments will be briefly described below, it being obvious that the drawings in the following description are only some embodiments of the present invention, and that other drawings may be obtained according to these drawings without inventive effort for a person skilled in the art.

FIG. 1 is a block diagram of a step counting calibration system according to an embodiment of the present invention;

FIG. 2 is a detailed view of the step calibration system of FIG. 1;

FIG. 3 is a block diagram of a step-counting calibration system according to an embodiment of the present invention;

FIG. 4 is a block diagram of a step-counting calibration system according to an embodiment of the present invention;

fig. 5 is a signaling interaction diagram of a step counting calibration method according to an embodiment of the present invention;

FIG. 6 is a flowchart of determining a target device according to the first step-counting data, the second step-counting data and the third step-counting data by the first terminal device in FIG. 5;

FIG. 7 is a signaling interaction diagram of another step-counting calibration method according to an embodiment of the present invention;

FIG. 8 is a flowchart of the cloud end device in FIG. 7 according to a query command to query a query result corresponding to query information from the step counting calibration information set;

Fig. 9 is a schematic structural diagram of a first terminal device according to an embodiment of the present invention;

fig. 10 is a schematic structural diagram of a second terminal device according to an embodiment of the present invention;

fig. 11 is a schematic structural diagram of a cloud device according to an embodiment of the present invention;

fig. 12 is a schematic structural diagram of an electronic device according to an embodiment of the present invention;

fig. 13 is a software structure block diagram of an electronic device according to an embodiment of the present invention.

[ detailed description ] of the invention

For a better understanding of the technical solution of the present invention, the following detailed description of the embodiments of the present invention refers to the accompanying drawings.

It should be understood that the described embodiments are merely some, but not all, embodiments of the invention. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.

The terminology used in the embodiments of the invention is for the purpose of describing particular embodiments only and is not intended to be limiting of the invention. As used in this application and the appended claims, the singular forms "a," "an," and "the" are intended to include the plural forms as well, unless the context clearly indicates otherwise.

It should be understood that the term "and/or" as used herein is merely one way of describing an association of associated objects, meaning that there may be three relationships, e.g., a and/or b, which may represent: the first and second cases exist separately, and the first and second cases exist separately. In addition, the character "/" herein generally indicates that the front and rear associated objects are an "or" relationship.

The steps recorded on the electronic equipment are related to hardware configuration, software algorithm version, user motion gesture and habit, but currently, industry manufacturers adopt a cutting method in the aspect of calculating the steps, so that the deviation between the steps seen by the user and the actual steps is larger. In the same period of time, the user uses the terminal equipment and the wearable equipment to synchronously take the steps, based on the step number generated by the terminal equipment, or based on the step number generated by the wearable equipment, or based on the step number generated by the electronic equipment with the largest step number.

For example, the user carries the mobile phone and the watch at the point 12-point 30 minutes, the mobile phone counts 1000 steps, the watch counts 1010 steps, and the total number of steps of 12-point 30 minutes in the total number of steps in the day can use 1000 steps generated by the mobile phone, and 1010 steps generated by the watch are not used, but in practice, the number of steps generated by the watch may be more real.

For example, the user carries the mobile phone and the watch at the point 12-point 30 minutes, the mobile phone counts 1000 steps, the watch counts 1010 steps, 1010 steps generated by the watch are used in the total steps of 12-point 30 minutes in the day, 1000 steps generated by the mobile phone are not used, but in practice, the steps generated by the mobile phone may be more real.

For example, the user carries the mobile phone and the watch at the point 12-point 30 minutes, the mobile phone counts 1000 steps, the watch counts 1010 steps, 1010 steps generated by the watch with the largest step number can be used for counting the steps of the point 12-point 30 minutes in the number of steps in the day, 1000 steps generated by the mobile phone with the smaller step number are not used, but in practice, the possible step number generated by the mobile phone is more real.

In summary, when a user uses a plurality of electronic devices to count steps at the same time, the current step counting calibration method cannot determine the electronic device with the most accurate step counting, so that the deviation between the number of steps seen by the user and the actual number of steps is larger.

Based on the technical problems, the embodiment of the invention provides a step counting calibration method, a step counting calibration system and step counting calibration equipment, which can determine the most accurate electronic equipment for step counting when a user uses a plurality of electronic equipment for step counting at the same time, so that the number of steps seen by the user is closest to the actual number of steps.

Fig. 1 is a schematic diagram of a step counting calibration system according to an embodiment of the present invention, fig. 2 is a detailed diagram of the step counting calibration system in fig. 1, and fig. 3 is a schematic diagram of another step counting calibration system according to an embodiment of the present invention. As shown in fig. 1, the step count calibration system includes a first terminal device 10, a first wearable device 20, and a foot wearable device 30; the first terminal device 10 is wirelessly connected with the first wearable device 20 and the foot wearable device 30; there is no connection between first wearable device 20 and foot wearable device 30. For example, the first terminal device 10 and the first wearable device 20 are bluetooth connected, and the first terminal device 10 and the foot wearable device 30 are bluetooth connected.

In the embodiment of the present invention, the first terminal device 10 includes a terminal device having a computing capability, for example: cell phones, tablets, notebook computers, etc., are typically held in the hand of a user, in a pocket or in a bag. The first terminal device 10 may detect information such as the number of steps, the movement track, etc. of the user. The first wearable device 20 comprises an intelligent wearable device, such as: smart watches, smart bracelets, etc., are typically worn by a user on the wrist. The first wearable device 20 may detect information of the user's step number, calories, heart rate, blood oxygen saturation, maximum oxygen consumption, etc. Foot wear device 30 includes a smart device worn on or tied to a user's foot, such as: running fairy devices tied on the shoe belts, intelligent running shoes or intelligent insoles worn on the feet, etc. Foot wear device 30 may detect whether the running gesture of the user is correct while running, primarily detecting data of the user's touchdown time, flight time, landing impact, etc.

For example, when a user carries a mobile phone, a watch and a running eidolon device at the same time, the user can listen to songs by using the mobile phone, record a GPS track route, measure data such as heart rate, oxygen consumption and the like during exercise by using the watch, and detect running gestures by using the running eidolon device.

The first terminal device 10, the first wearable device 20, and the foot wearable device 30 each include a data acquisition module and a data transmission module. For example, the data acquisition module includes a step counting sensor, a heart rate sensor, and the like. The data acquisition module is used for mainly recording the step number information of the user and the heart rate information of the user. The data transmission module is used for transmission interaction of collected data among a plurality of devices, and is generally connected through Bluetooth, but not limited by Bluetooth; for example, a hot spot is opened through a mobile phone, and the watch/bracelet and the running fairy device are connected with the mobile phone through a local area network. The first terminal device 10 further includes a logic processing module, where the logic processing module is configured to combine the motion data collected by the three devices, i.e. the first terminal device 10, the first wearable device 20, and the foot wearable device 30, to present a complete piece of motion data for the user.

As shown in fig. 2, the first terminal device 10 includes a first data presentation unit 11, a data collision detection unit 12, a data merging unit 13, a first step counting unit 14, a track unit 15, and a first information interaction unit 16. The first wearable device 20 comprises a second data presentation unit 21, a second step counting unit 22, a heart rate unit 23 and a second information interaction unit 24. Foot wear device 30 includes a third step counter unit 31, a running pose unit 32, and a third information interaction unit 33. The first terminal device 10 is wirelessly connected with the second information interaction unit 24 of the first wearable device 20 and the third information interaction unit 33 of the foot wearable device 30 through the first information interaction unit 16.

The first information interaction unit 16, the second information interaction unit 24, and the third information interaction unit 33 are configured to send and receive control commands between multiple devices and data collected by the multiple devices.

In the embodiment of the present invention, when the first information interaction unit 16 is configured to detect that the first information interaction unit 16 is wirelessly connected with the second information interaction unit 24 and the third information interaction unit 33, a first instruction is sent to both the second information interaction unit 24 and the third information interaction unit 33, and a step starting signal is sent to the first step starting unit 14, where the first instruction is configured to instruct the first wearable device 20 and the foot wearable device 30 to start step starting calibration operation. The second information interaction unit 24 is configured to send a step starting signal to the second step counting unit 22 according to the first instruction, and the second step counting unit 22 is configured to start a step counting calibration operation according to the step starting signal; specifically, the second step counting unit 22 is configured to start processing the data collected by the step counting sensor of the first wearable device 20 to obtain the step number according to the step counting start signal. The third information interaction unit 33 is configured to send a step starting signal to the third step counting unit 31 according to the first instruction, and the third step counting unit 31 is configured to start a step counting calibration operation according to the step starting signal; specifically, the third step counting unit 31 is configured to start processing the data collected by the step counting sensor of the foot wearable apparatus 30 to obtain the step number according to the step counting start signal. The first step counting unit 14 is used for starting step counting calibration operation according to the step counting starting signal; specifically, the first step counting unit 14 is configured to start processing the data collected by the step counting sensor of the first terminal device 10 according to the step counting start signal to obtain the step number. At this time, the first terminal device 10, the first wearable device 20, and the foot wearable device 30 simultaneously turn on the step counting calibration operation. The first step counting unit 14, the second step counting unit 22 and the third step counting unit 31 each independently start the independent storage unit, and record the accumulated step number from the time of receiving the first instruction.

It should be noted that, while the first step counting unit 14, the second step counting unit 22 and the third step counting unit 31 start the step counting calibration operation, the track unit 15, the heart rate unit 23 and the running gesture unit 32 also start to operate simultaneously. Specifically, the track unit 15 is configured to record geographical location information of running of the user, and convert the geographical location information into a GPS track of movement of the user; the heart rate unit 23 is configured to obtain a heart rate by processing data collected by the heart rate sensor of the first wearable device 20; the running gesture unit 32 is used to determine the running gesture of the user by processing the user running gesture information.

The second data presentation unit 21 of the first wearable device 20 is configured to display the number of steps of the second step counting unit 22 and the heart rate of the heart rate unit 23 on the first wearable device 20.

In this embodiment of the present invention, the first information interaction unit 16 is further configured to send a step counting stopping signal to the first step counting unit 14 after a preset time period, and send second instructions to the second information interaction unit 24 and the third information interaction unit 33, where the second instructions are used to instruct the first wearable device 20 and the foot wearable device 30 to stop the step counting calibration operation. The first step counting unit 14 is configured to stop the step counting calibration operation according to the step counting stop signal, generate first step counting data according to the step counting calibration operation, and send the first step counting data to the data collision detection unit 12. The first step counting data is the total step number of the user accumulated by the first terminal device 10 in a preset time period. The second information interaction unit 24 is further configured to send a step counting stopping signal to the second step counting unit 22 according to the second instruction, the second step counting unit 22 stops the step counting calibration operation according to the step counting stopping signal, generates second step counting data according to the step counting calibration operation, and sends the second step counting data to the second information interaction unit 24; the second information interaction unit 24 sends the second step counting data to the first information interaction unit 16; the first information interaction unit 16 sends the second step-counting data to the data collision detection unit 12. The second step counting data is the total step number of the user accumulated by the first wearable device 20 in the preset time period. The third information interaction unit 33 is further configured to send a step stopping signal to the third step counting unit 31 according to the second instruction, the third step counting unit 31 stops the step counting calibration operation according to the step stopping signal, generates third step counting data according to the step counting calibration operation, and sends the third step counting data to the third information interaction unit 33; the third information interaction unit 33 sends the third step count data to the first information interaction unit 16; the first information interaction unit 16 sends the third step count data to the data collision detection unit 12. Wherein the third step count data is a total number of steps of the user accumulated by foot wear device 30 over a preset period of time. At this time, the first terminal device 10, the first wearable device 20, and the foot wearable device 30 stop the step count calibration operation. The first step counting unit 14, the second step counting unit 22, and the third step counting unit 31 stop continuing to accumulate the step numbers to the independent storage units.

It should be noted that, while the first step counting unit 14, the second step counting unit 22 and the third step counting unit 31 stop the step counting calibration operation, the track unit 15, the heart rate unit 23 and the running gesture unit 32 stop working at the same time. Specifically, the track unit 15 is further configured to stop recording the geographical location information of the running of the user, and send the historical user movement GPS track to the data merging unit 13. The heart rate unit 23 is configured to stop processing data acquired by the heart rate sensor of the first wearable device 20 and send the historical heart rate to the third information interaction unit 33; the third information interaction unit 33 sends the historic heart rate to the first information interaction unit 16; the first information interaction unit 16 sends the historical heart rate to the data merging unit 13. The running gesture unit 32 is configured to stop processing the running gesture information of the user, and send the historical running gesture of the user to the third information interaction unit 33; the third information interaction unit 33 sends the historical running gesture of the user to the first information interaction unit 16; the first information interaction unit 16 sends the historical running gesture of the user to the data merging unit 13.

In the embodiment of the present invention, the data collision detection unit 12 is configured to determine the target device according to the first step counting data collected by the first terminal device 10, the second step counting data collected by the first wearable device 20, and the third step counting data collected by the foot wearable device 30 during the step counting calibration operation. The target device includes the first terminal device 10 or the first wearable device 20. The data collision detection unit 12 specifically functions to: determining step counting data closest to third step counting data in the first step counting data and the second step counting data according to the first step counting data, the second step counting data and the third step counting data; when the step counting data closest to the third step counting data is the first step counting data, determining the first terminal device 10 as the target device; when the step count data closest to the third step count data is the second step count data, the first wearable device 20 is determined to be the target device. The data collision detection unit 12 is further configured to send the step counting data of the target device to the data merging unit 13.

It should be noted that, the three electronic devices, i.e., the first terminal device 10, the first wearable device 20, and the foot wearable device 30, can all count steps. Taking the running sprite device as an example, since the running sprite device is tied on a shoelace for use, the accuracy of the data of the step counting is higher than that of the first terminal device 10 and the first wearable device 20. Because only the user lifts his foot, the running sprite device is triggered to generate data, whereas if the user stands in place to throw his arm, only first terminal device 10 and first wearable device 20 are triggered to count steps, but the running sprite device does not generate a step count. In addition, if the swing arm amplitude is insufficient in some extreme scenes when the user is running and walking, the running eidolon device may not perform the steps, but the first terminal device 10 and the first wearable device 20 may not perform the steps. Moreover, the applicant also finds that the step counting accuracy of the running eidolon device is higher through actual test data.

In order to prevent single measurement errors, the first terminal device 10 may initiate the first instruction and the second instruction multiple times during the movement of the user, and perform multiple result comparisons to obtain which device of the first terminal device 10 and the first wearable device 20 is more accurate for the user to step.

The first terminal device 10 records which device is more accurate for the user, and when the user does not use the running sprite device later and only uses the first terminal device 10 and the first wearable device 20, when the two devices are inconsistent in step count data, the step count data of one device more accurate for the user, that is, the step count data of the target device, can be selected.

The data merging unit 13 is configured to merge the step counting data of the target device, the historical user movement GPS track, the historical heart rate and the historical running gesture of the user, generate a complete piece of movement data, and send the complete piece of movement data to the first data presenting unit 11. The first data presentation unit 11 is configured to display the one complete piece of motion data in the form of a chart or the like.

In the embodiment of the present invention, the first terminal device 10 is used as a master control device and has an instruction for starting/stopping step counting calibration operation; first wearable device 20 and running eidolon device act as slave devices, and after receiving the instruction from the master device, the independent step counting is started/stopped, and after stopping, step counting data can be sent to the master device. The master control equipment has the capability of data accuracy comparison and marking more accurate equipment. For the same user, after the first terminal device 10 and the first wearable device 20 are identified which device is more accurate to the user, if the first terminal device 10 and the first wearable device 20 have no hardware replacement or large software upgrade (the main control device can be identified by the device software version number), the step counting calibration operation is not required all the time, and the power consumption of the device can be effectively reduced.

Optionally, as shown in fig. 3, the step counting calibration system further includes a cloud device 60, where the cloud device 60 stores a step counting calibration information set; the first terminal device 10 is wirelessly connected with the cloud device 60. In the embodiment of the present invention, the data collision detection unit of the first terminal device 10 is further configured to send device information of the target device to the first information interaction unit; the first information interaction unit is further configured to generate step counting calibration information according to the first user characteristic, the device information of the first terminal device 10, the device information of the first wearable device 20, and the target device, and upload the step counting calibration information to the cloud device 60. The cloud end device is used for storing the step counting calibration information into the step counting calibration information collection set. Wherein the first user characteristic comprises one or more of the following: the sex, age, height, weight and stride of the user of the first terminal device 10. The device information includes a device type and a device model, for example, the device type includes a mobile phone or a watch, and the device model includes a software and hardware version number. For example, the step count calibration information includes: the male age of the user is 30-34 years old, the height is 170-175 cm, the weight is 70-75 kg, the stride of the user is 80-100 cm, the user uses a type A mobile phone, a type B watch and the step counting data of the type B watch are more accurate.

In summary, when the user wears the three devices, i.e., the first terminal device 10, the first wearable device 20 and the foot wearable device 30, at the same time, the step counting data of the first terminal device 10 and the first wearable device 20 are respectively compared with the step counting data of the foot wearable device 30 with the most accurate step counting, so that the step counting data of the first terminal device 10 or the first wearable device 20 is more matched with the actual step number of the user according to the behavior habit of the user, and a cut-off mode is avoided.

Fig. 4 is a schematic diagram of another step counting calibration system according to an embodiment of the present invention. As shown in fig. 4, the step counting calibration system includes a second terminal device 40, a second wearable device 50, a cloud device 60 shown in fig. 3, and at least one first terminal device 10 shown in fig. 1-3; the second terminal device 40 and the second wearable device 50 are wirelessly connected. For example, the second terminal device 40 and the second wearable device 50 are bluetooth connected. The first terminal device 10 and the second terminal device 40 are both wirelessly connected with the cloud device 60.

In the embodiment of the present invention, the second terminal device 40 includes a terminal device having a computing capability, for example: cell phones, tablets, notebook computers, etc., are typically held in the hand of a user, in a pocket or in a bag. The second terminal device 40 may detect information of the user's steps, movement trajectories, etc. The second wearable device 50 includes smart wearable devices such as: smart watches, smart bracelets, etc., are typically worn by a user on the wrist. The second wearable device 50 may detect information of the user's step number, calories, heart rate, blood oxygen saturation, maximum oxygen consumption, etc.

In the embodiment of the present invention, the first terminal device 10 is configured to upload the generated step counting calibration information to the cloud device 60. Cloud device 60 stores a step-counting calibration information collection. The cloud device 60 is configured to receive the step counting calibration information uploaded by the at least one first terminal device 10, and store the step counting calibration information into a step counting calibration information set. The step counting calibration information set comprises at least one step counting calibration information; the step count calibration information includes the first user characteristic, the device information of the first terminal device 10, the device information of the first wearable device 20, and the target device. For example: the step counting calibration information comprises: the male age of the user is 30-34 years old, the height is 170-175 cm, the weight is 70-75 kg, the stride of the user is 80-100 cm, the user uses a type A mobile phone, a type B watch and the step counting data of the type B watch are more accurate.

The second terminal device 40 is configured to obtain a second user characteristic of a user of the second terminal device 40, device information of the second terminal device 40, and device information of the second wearable device 50. The device information includes a device type including a cellular phone or a wristwatch, and a device model including a software and hardware version number, for example. The second wearable device 50 is configured to send device information of the second wearable device 50 to the second terminal device 40. The second terminal device 40 is further configured to generate query information according to the second user characteristic, device information of the second terminal device 40, and device information of the second wearable device 50, and send a query instruction to the cloud device 60 according to the query information.

In the embodiment of the present invention, the user of the second terminal device 40 does not use the running wizard device, but uses the second terminal device 40 and the second wearable device 50 at the same time, for the user, which device of the second terminal device 40 and the second wearable device 50 is more accurate in step counting, and query information needs to be reported to the cloud device 60 to query which device of the second terminal device 40 and the second wearable device 50 is more accurate in step counting.

For example: the query information includes: the male of the user, age group 30-34 years, height 170-175 cm, weight 70-75 kg, stride of the user 80-100 cm, use A model mobile phone, B model watch.

The cloud device 60 is configured to query a query result corresponding to the query information from the step counting calibration information set according to the query instruction. The query result includes the target device or the query failed. The cloud device 60 is specifically configured to determine, according to the query instruction, a similarity between the step counting calibration information and the query information in the step counting calibration information set; judging whether the similarity is larger than or equal to a set threshold value; if the similarity is judged to be greater than or equal to the set threshold, judging whether the target equipment in the step counting calibration information corresponding to the maximum similarity comprises the first terminal equipment 10 or the first wearable equipment 20; if it is determined that the target device in the step counting calibration information corresponding to the maximum similarity includes the first terminal device 10, generating a query result including the second terminal device 40; if it is determined that the target device in the step counting calibration information corresponding to the maximum similarity includes the first wearable device 20, a query result including the second wearable device 50 is generated. The cloud device 60 is further specifically configured to generate a query result including a query failure if the similarities are determined to be smaller than the set threshold. The cloud device 60 is further configured to send the query result to the second terminal device 40.

The second terminal device 40 is further configured to receive a query result sent by the cloud device 60, and display step counting data collected by the target device when the query result includes the target device. The second more accurate device includes a second terminal device 40 or a second wearable device 50, where the second terminal device 40 is specifically configured to display step counting data collected by the second terminal device 40 when the query result includes the second terminal device 40; when the query result includes the second wearable device 50, step counting data acquired by the second wearable device 50 is displayed. The second terminal device 40 is further configured to display step counting data defaulted by the system when the query result includes a query failure. For example, the step counting data defaulted by the system includes step counting data of the second terminal device 40, step counting data of the second wearable device 50, or the largest step counting data among the step counting data of the second terminal device 40 and the step counting data of the second wearable device 50.

For example, when the user M has a running sprite device and uses the mobile phone P and the watch E, the watch E counts steps more accurately, and the mobile phone P uploads step count calibration information to the cloud device 60; user N does not have running sprite equipment and uses handset Q and watch F, handset Q uploads query information to cloud device 60; the cloud device 60 compares the step counting calibration information of the user M with the query information of the user N, and sends a more accurate query result of the step counting of the watch F to the mobile phone Q; when the user N uses the mobile phone Q and the watch to count steps at the same time, the step count data of the watch F is displayed.

In the embodiment of the present invention, the cloud device 60 may continuously accumulate the step counting calibration information of the first terminal device 10, and the more the step counting calibration information is accumulated, the more accurate query result can be obtained for the user who uses the second terminal device 40 and the second wearable device 50 at the same time, but does not use the foot wearable device 30. According to the embodiment of the invention, the adaptive calculation is carried out according to the software and hardware version of the equipment and the behavior habit of the user, so that the step counting data of which equipment is used by a certain user is closer to the actual step number of the user.

Based on the system architecture shown in fig. 1-3, an embodiment of the present invention provides a step counting calibration method. Fig. 5 is a signaling interaction diagram of a step counting calibration method according to an embodiment of the present invention. As shown in fig. 5, the first wearable device, the foot wearable device, and the cloud device are respectively wirelessly connected with the first terminal device, and the method includes:

and 102, starting a step counting calibration operation by the first terminal equipment.

In the embodiment of the present invention, the first terminal device includes a terminal device having a computing capability, for example: cell phones, tablets, notebook computers, etc., are typically held in the hand of a user, in a pocket or in a bag. The first terminal device can detect information such as the number of steps, the movement track and the like of the user. The first wearable device includes an intelligent wearable device, such as: smart watches, smart bracelets, etc., are typically worn by a user on the wrist. The first wearable device may detect information of a user's steps, calories, heart rate, blood oxygen saturation, maximum oxygen consumption, etc. Foot wear devices include smart devices worn on or tied to the user's foot, such as: running fairy devices tied on the shoe belts, intelligent running shoes or intelligent insoles worn on the feet, etc. The foot wearing device can detect whether the running gesture of the user is correct or not when the user runs, and mainly detect data such as the ground contact time, the flight time, the ground impact and the like of the user. For example, when a user carries a mobile phone, a watch and a running eidolon device at the same time, the user can listen to songs by using the mobile phone, record a GPS track route, measure data such as heart rate, oxygen consumption and the like during exercise by using the watch, and detect running gestures by using the running eidolon device.

The first terminal device, the first wearable device and the foot wearable device all comprise a data acquisition module and a data transmission module. For example, the data acquisition module includes a step counting sensor, a heart rate sensor, and the like. The data acquisition module is used for mainly recording the step number information of the user and the heart rate information of the user. The data transmission module is used for transmission interaction of collected data among a plurality of devices, and is generally connected through Bluetooth, but not limited by Bluetooth; for example, a hot spot is opened through a mobile phone, and the watch/bracelet and the running fairy device are connected with the mobile phone through a local area network. The first terminal device further comprises a logic processing module, wherein the logic processing module is used for combining the motion data collected by the first terminal device, the first wearable device and the foot wearable device, and presenting a piece of complete motion data for a user.

In the step, as shown in fig. 2, when the first information interaction unit of the first terminal device detects that the first information interaction unit is in wireless connection with the second information interaction unit and the third information interaction unit, a step starting signal is sent to the first step counting unit; the first step counting unit starts step counting calibration operation according to the step counting starting signal; specifically, the first step counting unit starts to process the data acquired by the step counting sensor of the first terminal equipment according to the step counting starting signal to obtain the step number.

Step 104, the first terminal device sends a first instruction to the first wearable device.

In this step, as shown in fig. 2, when the first information interaction unit of the first terminal device detects that the first information interaction unit is wirelessly connected with the second information interaction unit and the third information interaction unit, a first instruction is further sent to the second information interaction unit of the first wearable device, where the first instruction is used to instruct the first wearable device to start the step counting calibration operation.

And 106, the first wearable device starts step counting calibration operation according to the first instruction.

In the step, as shown in fig. 2, a second information interaction unit of the first wearable device sends a step starting signal to a second step counting unit according to a first instruction, and the second step counting unit starts step counting calibration operation according to the step starting signal; specifically, the second step counting unit starts to process the data acquired by the step counting sensor of the first wearable device according to the step counting starting signal to obtain the step number.

Step 108, the first terminal device sends a first instruction to the foot-worn device.

In this embodiment of the present invention, as shown in fig. 2, when the first information interaction unit of the first terminal device detects that the first information interaction unit is wirelessly connected with the second information interaction unit and the third information interaction unit, a first instruction is further sent to the third information interaction unit of the foot wearing device, where the first instruction is used to instruct the foot wearing device to start the step counting calibration operation.

Step 110, the foot wearing device starts a step counting calibration operation according to a first instruction.

In this step, as shown in fig. 2, the third information interaction unit of the foot wearing device sends a step starting step counting signal to the third step counting unit according to the first instruction, and the third step counting unit starts step counting calibration operation according to the step starting step counting signal; specifically, the third step counting unit starts to process the data acquired by the step counting sensor of the foot wearing equipment according to the step counting starting signal to obtain the step number.

It should be noted that, step 102, step 104 and step 108 are performed simultaneously. Since the time from the receipt of the first instruction to the start of the step count calibration operation is very fast, which may be ignored, the first terminal device, the first wearable device, and the foot wearable device may be considered to be simultaneously in the start of the step count calibration operation.

And 112, stopping the step counting calibration operation by the first terminal equipment, and generating first step counting data according to the step counting calibration operation.

In the embodiment of the present invention, as shown in fig. 5, after a preset time period, the first terminal device stops the step counting calibration operation.

In this step, as shown in fig. 2, the first information interaction unit of the first terminal device is further configured to send a step stopping signal to the first step counting unit after a preset time period, where the first step counting unit stops the step counting calibration operation according to the step stopping signal, and generates first step counting data according to the step counting calibration operation. The first step counting data is the total step number of the user accumulated by the first terminal equipment in a preset time period.

Step 114, the first terminal device sends a second instruction to the first wearable device.

In this step, as shown in fig. 2, the first information interaction unit of the first terminal device is further configured to send a second instruction to the second information interaction unit of the first wearable device after a preset time period, where the second instruction is used to instruct the first wearable device to stop the step counting calibration operation.

And step 116, stopping the step counting calibration operation by the first wearable device according to the second instruction, and generating second step counting data according to the step counting calibration operation.

In this step, as shown in fig. 2, the second information interaction unit of the first wearable device sends a step counting stopping signal to the second step counting unit according to the second instruction, and the second step counting unit stops the step counting calibration operation according to the step counting stopping signal and generates second step counting data according to the step counting calibration operation. The second step counting data is the total step number of the user accumulated by the first wearable device in a preset time period.

Step 118, the first wearable device sends the second step counting data to the first terminal device.

In this step, as shown in fig. 2, the second step counting unit of the first wearable device sends the second step counting data to the second information interaction unit of the first terminal device, and the second information interaction unit sends the second step counting data to the first information interaction unit of the first terminal device.

Step 120, the first terminal device sends a second instruction to the foot-worn device.

In this step, as shown in fig. 2, after a preset time period, the first information interaction unit of the first terminal device further sends a second instruction to the third information interaction unit of the foot wearing device, where the second instruction is used to instruct the foot wearing device to stop the step counting calibration operation.

Step 122, the foot wearing device stops the step counting calibration operation according to the second instruction, and generates third step counting data according to the step counting calibration operation.

In this step, as shown in fig. 2, the third information interaction unit of the foot wearing device sends a step counting stopping signal to the third step counting unit according to the second instruction, and the third step counting unit stops the step counting calibration operation according to the step counting stopping signal and generates third step counting data according to the step counting calibration operation. The third step counting data is the total step number of the user accumulated by the foot wearing equipment in a preset time period.

Step 124, the foot wear device sends third step count data to the first terminal device.

In this step, as shown in fig. 2, the foot wearing device transmits third step counting data to the third information interaction unit; and the third information interaction unit sends the third step counting data to the first information interaction unit of the first terminal equipment.

It should be noted that, step 112, step 114 and step 118 are performed simultaneously. Since the time from the reception of the second instruction to the stop of the step count calibration operation is very fast, which can be ignored, the first terminal device, the first wearable device, and the foot wearable device can be considered to be simultaneously stopped.

Step 126, the first terminal device determines the target device according to the first step counting data, the second step counting data and the third step counting data.

In this step, as shown in fig. 2, the first step counting unit of the first terminal device sends the first step counting data to the data collision detecting unit. The first information interaction unit of the first terminal equipment sends the second step counting data and the third step counting data to the data conflict detection unit. The data conflict detection unit of the first terminal equipment determines target equipment according to first step counting data acquired by the first terminal equipment, second step counting data acquired by the first wearable equipment and third step counting data acquired by the foot wearable equipment in the step counting calibration operation process.

In the embodiment of the invention, the target device comprises a first terminal device or a first wearable device.

In the embodiment of the present invention, as shown in fig. 6, step 126 specifically includes:

in step 126a, the first terminal device determines, according to the first step counting data, the second step counting data and the third step counting data, step counting data closest to the third step counting data in the first step counting data and the second step counting data.

In this step, as shown in fig. 2, the data collision detection unit of the first terminal device determines, according to the first step counting data, the second step counting data, and the third step counting data, step counting data closest to the third step counting data in the first step counting data and the second step counting data.

Step 126b, when the step counting data closest to the third step counting data is the first step counting data, the first terminal device determines that the first terminal device is the target device, and continues to execute step 128.

In this step, as shown in fig. 2, if the data collision detection unit of the first terminal device determines that the step counting data closest to the third step counting data is the first step counting data, it determines that the first terminal device is the target device.

It should be noted that, the three electronic devices, i.e., the first terminal device, the first wearable device, and the foot wearable device, can all count steps. Taking the running eidolon equipment as an example, the running eidolon equipment is tied on a shoelace for use, and the accuracy of the data of step counting is higher than that of the first terminal equipment and the first wearable equipment. Because only the user lifts his foot, the running sprite device is triggered to generate data, and if the user stands in place to throw his arm, the first terminal device and the first wearable device are only triggered to perform step counting, but the running sprite device does not generate step counting. In addition, when the user is running and walking, if the swing arm amplitude is not enough and the like in some extreme scenes, the running eidolon equipment can perform walking, and the first terminal equipment and the first wearable equipment can not perform walking. Moreover, the applicant also finds that the step counting accuracy of the running eidolon device is higher through actual test data.

Step 126c, when the step counting data closest to the third step counting data is the second step counting data, the first terminal device determines that the first wearable device is the target device, and continues to execute step 128.

In this step, as shown in fig. 2, if the data collision detection unit of the first terminal device determines that the step counting data closest to the third step counting data is the second step counting data, it determines that the first wearable device is the target device.

In order to prevent single measurement errors, the first terminal device can initiate the first instruction and the second instruction for multiple times in the motion process of the user, and multiple result comparisons are carried out to obtain which device in the first terminal device and the first wearable device is more accurate for the user to step.

Step 128, the first terminal device generates step counting calibration information according to the first user characteristic, the device information of the first terminal device, the device information of the first wearable device and the target device.

In this step, as shown in fig. 2, the data collision detection unit of the first terminal device sends the device information of the target device to the first information interaction unit; the first information interaction unit is further configured to generate step counting calibration information according to the first user characteristic, the device information of the first terminal device, the device information of the first wearable device, and the target device.

In an embodiment of the present invention, the first user characteristic includes one or more of the following: the gender, age, height, weight and stride of the user of the first terminal device. The device information includes a device type and a device model, for example, the device type includes a mobile phone or a watch, and the device model includes a software and hardware version number.

And 130, the first terminal equipment transmits the step counting calibration information to the cloud equipment last time.

In this step, as shown in fig. 3, the first terminal device uploads the step counting calibration information to the cloud device.

Step 132, the cloud device stores the step counting calibration information into the step counting calibration information collection set.

In this step, as shown in fig. 3, the cloud device stores the step counting calibration information into the step counting calibration information set. Wherein the first user characteristic comprises one or more of the following: the gender, age, height, weight and stride of the user of the first terminal device. For example, the step count calibration information includes: the male age of the user is 30-34 years old, the height is 170-175 cm, the weight is 70-75 kg, the stride of the user is 80-100 cm, the user uses a type A mobile phone, a type B watch and the step counting data of the type B watch are more accurate.

According to the technical scheme of the step counting calibration method, when a user wears three devices, namely the first terminal device, the first wearable device and the running eidolon device, step counting data of the first terminal device and step counting data of the first wearable device are respectively compared with the most accurate step counting data of the running eidolon device, so that step counting data of the first terminal device or the first wearable device and the actual step number of the user are more matched for the behavior habit of the user, and a one-step cutting mode is avoided.

In the technical scheme provided by the embodiment of the invention, the first terminal equipment is connected with the first wearable equipment and the foot wearable equipment, and the first terminal equipment acquires first step counting data and acquires second step counting data acquired by the first wearable equipment and third step counting data acquired by the foot wearable equipment; determining target equipment according to the first step counting data, the second step counting data and the third step counting data; generating step counting calibration information according to the first user characteristics, the equipment information of the first terminal equipment, the equipment information of the first wearable equipment and the target equipment; and uploading the step counting calibration information to cloud equipment. Therefore, when a user uses a plurality of electronic devices to count steps at the same time, the electronic device with the most accurate step count can be determined, so that the number of steps seen by the user is closest to the actual number of steps.

Based on the system architecture shown in fig. 4, an embodiment of the present invention provides a further step counting calibration method. Fig. 7 is a signaling interaction diagram of another step counting calibration method according to an embodiment of the present invention. As shown in fig. 7, the second terminal device and at least one first terminal device are respectively connected with the cloud device in a wireless manner, and the second wearable device is connected with the second terminal device in a wireless manner, and the method includes:

Step 202, the first terminal device uploads the step counting calibration information to the cloud device.

In this step, as shown in fig. 4, the first terminal device uploads the step counting calibration information to the cloud device.

In the embodiment of the invention, the step counting calibration information comprises a first user characteristic, equipment information of a first terminal equipment, equipment information of a first wearable equipment and target equipment. Wherein the first user characteristic comprises one or more of the following: the gender, age, height, weight and stride of the user of the first terminal device. The device information includes a device type and a device model, for example, the device type includes a mobile phone or a watch, and the device model includes a software and hardware version number.

For example, the step count calibration information includes: the male age of the user is 30-34 years old, the height is 170-175 cm, the weight is 70-75 kg, the stride of the user is 80-100 cm, the user uses a type A mobile phone, a type B watch and the step counting data of the type B watch are more accurate.

Step 204, the cloud device stores the step counting calibration information into the step counting calibration information collection set.

In this step, as shown in fig. 4, the cloud device stores the step counting calibration information into the step counting calibration information set.

In the embodiment of the invention, the cloud device stores a step counting calibration information set, and the step counting calibration information set comprises at least one step counting calibration information.

Step 206, the second terminal device generates query information according to the second user feature, the device information of the second terminal device, and the device information of the second wearable device.

In the embodiment of the present invention, the second terminal device includes a terminal device having a computing capability, for example: cell phones, tablets, notebook computers, etc., are typically held in the hand of a user, in a pocket or in a bag. The second terminal device can detect information such as the number of steps and the movement track of the user. The second wearable device includes a smart wearable device, such as: smart watches, smart bracelets, etc., are typically worn by a user on the wrist. The second wearable device may detect information of a user's steps, calories, heart rate, blood oxygen saturation, maximum oxygen consumption, etc.

In this step, as shown in fig. 4, the second terminal device generates query information according to the second user feature, the device information of the second terminal device, and the device information of the second wearable device.

In the embodiment of the invention, the query information comprises the second user characteristics, the equipment information of the second terminal equipment and the equipment information of the second wearable equipment. Wherein the second user characteristic comprises: gender, age, height, weight and stride of the user of the second terminal device. The device information includes a device type and a device model, for example, the device type includes a mobile phone or a watch, and the device model includes a software and hardware version number. For example: the query information includes: the male of the user, age group 30-34 years, height 170-175 cm, weight 70-75 kg, stride of the user 80-100 cm, use A model mobile phone, B model watch.

In the embodiment of the present invention, before step 206, the method further includes:

step 204', the second wearable device sends device information of the second wearable device to the second terminal device.

The second wearable device needs to acquire device information of the second wearable device before generating the query information. In this step, as shown in fig. 4, the second wearable device sends device information of the second wearable device to the second terminal device.

And step 208, the second terminal equipment sends a query instruction to the cloud terminal equipment according to the query information.

In this step, as shown in fig. 4, the second terminal device sends a query instruction to the cloud device according to the query information. The query instruction carries query information, and the query instruction is used for enabling the cloud device to query a query result corresponding to the query information from the step counting calibration information collection set according to the query instruction.

In the embodiment of the invention, the user of the second terminal equipment does not use the foot wearing equipment, but uses the second terminal equipment and the second wearing equipment at the same time, so that the user needs to report the query information to the cloud end equipment to query which equipment of the second terminal equipment and the second wearing equipment is more accurate in step counting.

Step 210, the cloud device queries a query result corresponding to the query information from the step counting calibration information set according to the query instruction.

In this step, as shown in fig. 4, the cloud device queries, according to the query instruction, a query result corresponding to the query information from the step counting calibration information set. Wherein the query result includes the target device or the query failure. The target device comprises a second terminal device or a second wearable device.

In the embodiment of the present invention, as shown in fig. 8, step 210 specifically includes:

step 210a, the cloud device determines similarity between the step counting calibration information and the query information in the step counting calibration information aggregate according to the query instruction.

In this step, as shown in fig. 4, the cloud device determines the similarity between the step counting calibration information and the query information in the step counting calibration information aggregate according to the query instruction.

Step 210b, the cloud device determines whether the similarity is greater than or equal to a set threshold, if yes, step 210c is executed; if not, go to step 210f.

In this step, as shown in fig. 4, the cloud device determines whether the similarity is greater than or equal to a set threshold.

Step 210c, the cloud device judges whether the target device in the step counting calibration information corresponding to the maximum similarity comprises a first terminal device or a first wearable device, and if the target device in the step counting calibration information corresponding to the maximum similarity comprises the first terminal device, step 210d is executed; if the target device in the step counting calibration information corresponding to the maximum similarity includes the first wearable device, step 210e is executed.

In this step, as shown in fig. 4, the cloud device determines whether the target device in the step counting calibration information corresponding to the maximum similarity includes the first terminal device or the first wearable device.

Step 210d, the cloud device generates a query result including the second terminal device, and continues to execute step 212.

In this step, as shown in fig. 4, if the cloud device determines that the target device in the step counting calibration information corresponding to the maximum similarity includes the first terminal device, a query result including the second terminal device is generated.

Step 210e, the cloud device generates a query result including the second wearable device, and continues to execute step 212.

In this step, as shown in fig. 4, if the cloud device determines that the target device in the step counting calibration information corresponding to the maximum similarity includes the first wearable device, a query result including the second wearable device is generated.

Step 210f, the cloud device generates a query result including the query failure, and continues to execute step 212.

In this step, as shown in fig. 4, if the cloud device determines that the similarities are smaller than the set threshold, a query result including a query failure is generated.

Step 212, the cloud device sends a query result to the second terminal device, where the query result includes the target device or the query fails.

In this step, as shown in fig. 4, the cloud device sends the query result to the second terminal device, where the query result includes the target device or the query fails.

Step 214, when the query result includes the target device, the second terminal device displays the step counting data collected by the target device.

In this step, as shown in fig. 4, when the query result includes the target device, the second terminal device displays the step counting data collected by the target device. Specifically, when the query result includes the second terminal device, the second terminal device displays the step counting data collected by the second terminal device; when the query result comprises the second wearable device, the second terminal device displays the step counting data acquired by the second wearable device. And when the query result comprises query failure, the second terminal equipment displays default step counting data of the system. For example, the step counting data defaulted by the system comprises step counting data of the second terminal device, step counting data of the second wearable device or the largest step counting data in the step counting data of the second terminal device and the step counting data of the second wearable device.

For example, when the user M has the running eidolon device and uses the mobile phone P and the watch E, the watch E counts steps more accurately, and the mobile phone P uploads step counting calibration information to the cloud device; the user N does not have running eidolon equipment, and the mobile phone Q and the watch F are used, so that the mobile phone Q uploads the query information to the cloud equipment; the cloud device 60 compares the step counting calibration information of the user M with the query information of the user N, and sends a more accurate query result of the step counting of the watch F to the mobile phone Q; when the user N uses the mobile phone Q and the watch to count steps at the same time, the step count data of the watch F is displayed.

In the embodiment of the invention, the cloud end device can continuously accumulate the step counting calibration information of the first terminal device, and the more the accumulated step counting calibration information is, the more accurate query result can be obtained for the user who uses the second terminal device and the second wearable device at the same time without using the running eidolon device. According to the embodiment of the invention, the adaptive calculation is carried out according to the software and hardware version of the equipment and the behavior habit of the user, so that the step counting data of which equipment is used by a certain user is closer to the actual step number of the user.

Fig. 9 is a schematic structural diagram of a first terminal device according to an embodiment of the present invention, and it should be understood that the first terminal device 400 is capable of executing each step of the first terminal device in the step counting calibration method, and will not be described in detail herein to avoid repetition. The first terminal apparatus 400 includes: a first processing unit 401 and a first transceiving unit 402.

The first processing unit 401 is configured to determine a target device according to first step counting data acquired by the first terminal device, second step counting data acquired by the first wearable device, and third step counting data acquired by the foot wearable device during a step counting calibration operation; generating step counting calibration information according to the first user characteristics, the equipment information of the first terminal equipment, the equipment information of the first wearable equipment and the target equipment.

The second transceiver unit 402 is configured to upload the step counting calibration information to a cloud device, so that the cloud device stores the step counting calibration information in a step counting calibration information set.

Optionally, the target device includes the first terminal device or the first wearable device.

Optionally, the first processing unit 401 is specifically configured to determine, according to the first step count data, the second step count data, and the third step count data, step count data closest to the third step count data in the first step count data and the second step count data; when the step counting data closest to the third step counting data is the first step counting data, determining that the first terminal equipment is the target equipment; and when the step counting data closest to the third step counting data is the second step counting data, determining that the first wearable device is the target device.

Optionally, the second transceiver unit 402 is further configured to send a first instruction to both the first wearable device and the running sprite device and start the step counting calibration operation, where the first instruction is used to instruct the first wearable device and the running sprite device to start the step counting calibration operation.

Optionally, the first processing unit 401 is further configured to stop the step counting calibration operation after a preset time period to obtain first step counting data; second transceiver 402 is further configured to send a second instruction to both the first wearable device and the running sprite device, the second instruction being configured to instruct the first wearable device and the running sprite device to stop the step count calibration operation; and receiving second step counting data sent by the first wearable device and third step counting data sent by the running eidolon device.

Optionally, the first user characteristic comprises one or more of the following: the gender, age, height, weight and stride of the user of the first terminal device.

Optionally, the device information includes a device type and a device model.

Fig. 10 is a schematic structural diagram of a second terminal device according to an embodiment of the present invention, and it should be understood that the second terminal device 500 is capable of executing each step of the second terminal device in the step counting calibration method, and will not be described in detail herein to avoid repetition. The second terminal apparatus 500 includes: a second processing unit 501 and a second transceiving unit 502.

The second processing unit 501 is configured to generate query information according to a second user characteristic, device information of the second terminal device, and device information of the second wearable device.

The second transceiver unit 502 is configured to send a query instruction to a cloud device according to the query information, where the cloud device stores a step counting calibration information set, and the query instruction is configured to enable the cloud device to query a query result from the step counting calibration information set according to the query information; the second transceiver 502 is further configured to receive a query result sent by the cloud device.

Optionally, the second processing unit 501 is further configured to display step counting data collected by the target device when the query result includes the target device.

Optionally, the target device includes the second terminal device or the second wearable device.

Optionally, the step counting calibration information set includes at least one step counting calibration information.

Fig. 11 is a schematic structural diagram of a cloud device according to an embodiment of the present invention, and it should be understood that the cloud device 600 can execute each step of the cloud device in the step-counting calibration method, and in order to avoid repetition, details are not described herein. Cloud device 600 includes: a third transceiver unit 601 and a third processing unit 602.

The third transceiver 601 is configured to receive a query instruction carrying query information, which is uploaded by the second terminal device.

The third processing unit 602 is configured to query, according to the query instruction, a query result corresponding to the query information from the step counting calibration information set.

The third transceiver 601 is further configured to send the query result to the second terminal device.

Optionally, the query result includes a target device or a query failure.

Optionally, the step counting calibration information set includes at least one step counting calibration information; the step counting calibration information comprises a first user characteristic, device information of a first terminal device, device information of a first wearable device and a target device.

Optionally, the query information includes a second user feature, device information of the second terminal device, and device information of a second wearable device.

Optionally, the third processing unit 602 is specifically configured to determine, according to the query instruction, a similarity between the step counting calibration information and the query information in the step counting calibration information set; judging whether the similarity is larger than or equal to a set threshold value; if the similarity is judged to be greater than or equal to a set threshold, judging whether the target device in the step counting calibration information corresponding to the maximum similarity comprises the first terminal device or the first wearable device; if the target equipment in the step counting calibration information corresponding to the maximum similarity is judged to comprise the first terminal equipment, generating the query result comprising the second terminal equipment; and if the target equipment in the step counting calibration information corresponding to the maximum similarity is judged to comprise the first wearable equipment, generating the query result comprising the second wearable equipment.

Optionally, the third processing unit 602 is further specifically configured to generate the query result including query failure if it is determined that the similarities are smaller than the set threshold.

Optionally, the third transceiver 601 is further configured to receive the step counting calibration information uploaded by at least one of the first terminal devices; the third processing unit 602 is further configured to store the step counting calibration information into the step counting calibration information set.

It should be understood that the first terminal device 400, the second terminal device 500, and the cloud device 600 herein are embodied in the form of functional units. The term "unit" herein may be implemented in software and/or hardware, without specific limitation. For example, a "unit" may be a software program, a hardware circuit or a combination of both that implements the functions described above. The hardware circuitry may include application specific integrated circuits (application specific integrated circuit, ASICs), electronic circuits, processors (e.g., shared, proprietary, or group processors, etc.) and memory for executing one or more software or firmware programs, merged logic circuits, and/or other suitable components that support the described functions.

Thus, the elements of the examples described in the embodiments of the present invention can be implemented in electronic hardware, or in a combination of computer software and electronic hardware. Whether such functionality is implemented as hardware or software depends upon the particular application and design constraints imposed on the solution. Skilled artisans may implement the described functionality in varying ways for each particular application, but such implementation decisions should not be interpreted as causing a departure from the scope of the present invention.

The embodiment of the application provides electronic equipment which can be terminal equipment or circuit equipment built in the terminal equipment. The electronic device may be adapted to perform the functions/steps of the method embodiments described above.

Fig. 12 is a schematic structural diagram of an electronic device 300 according to an embodiment of the present application. The electronic device 300 may include a processor 310, an external memory interface 320, an internal memory 321, a universal serial bus (universal serial bus, USB) interface 330, a charge management module 340, a power management module 341, a battery 342, an antenna 1, an antenna 2, a mobile communication module 350, a wireless communication module 360, an audio module 370, a speaker 370A, a receiver 370B, a microphone 370C, an ear-piece interface 370D, a sensor module 380, keys 390, a motor 391, an indicator 392, a camera 393, a display screen 394, and a user identification module (subscriber identification module, SIM) card interface 395, among others. The sensor module 380 may include a pressure sensor 380A, a gyroscope sensor 380B, an air pressure sensor 380C, a magnetic sensor 380D, an acceleration sensor 380E, a distance sensor 380F, a proximity sensor 380G, a fingerprint sensor 380H, a temperature sensor 380J, a touch sensor 380K, an ambient light sensor 380L, a bone conduction sensor 380M, and the like.

It should be understood that the illustrated structure of the embodiment of the present application does not constitute a specific limitation on the electronic device 300. In other embodiments of the application, electronic device 300 may include more or less components than illustrated, or certain components may be combined, or certain components may be split, or different arrangements of components. The illustrated components may be implemented in hardware, software, or a combination of software and hardware.

The processor 310 may include one or more processing units, such as: the processor 310 may include an application processor (application processor, AP), a modem processor, a graphics processor (graphics processing unit, GPU), an image signal processor (image signal processor, ISP), a controller, a video codec, a digital signal processor (digital signal processor, DSP), a baseband processor, and/or a neural network processor (neural-network processing unit, NPU), etc. Wherein the different processing units may be separate devices or may be integrated in one or more processors.

The controller can generate operation control signals according to the instruction operation codes and the time sequence signals to finish the control of instruction fetching and instruction execution.

A memory may also be provided in the processor 310 for storing instructions and data. In some embodiments, the memory in the processor 310 is a cache memory. The memory may hold instructions or data that the processor 310 has just used or recycled. If the processor 310 needs to reuse the instruction or data, it may be called directly from the memory. Repeated accesses are avoided and the latency of the processor 310 is reduced, thereby improving the efficiency of the system.

In some embodiments, processor 310 may include one or more interfaces. The interfaces may include an integrated circuit (inter-integrated circuit, I2C) interface, an integrated circuit built-in audio (inter-integrated circuit sound, I2S) interface, a pulse code modulation (pulse code modulation, PCM) interface, a universal asynchronous receiver transmitter (universal asynchronous receiver/transmitter, UART) interface, a mobile industry processor interface (mobile industry processor interface, MIPI), a general-purpose input/output (GPIO) interface, a subscriber identity module (subscriber identity module, SIM) interface, and/or a universal serial bus (universal serial bus, USB) interface, among others.

The I2C interface is a bi-directional synchronous serial bus comprising a serial data line (SDA) and a serial clock line (derail clock line, SCL). In some embodiments, the processor 310 may contain multiple sets of I2C buses. The processor 310 may be coupled to the touch sensor 380K, charger, flash, camera 393, etc., respectively, via different I2C bus interfaces. For example: the processor 310 may couple the touch sensor 380K through an I2C interface, such that the processor 310 communicates with the touch sensor 380K through an I2C bus interface, implementing the touch functionality of the electronic device 300.

The I2S interface may be used for audio communication. In some embodiments, the processor 310 may contain multiple sets of I2S buses. The processor 310 may be coupled to the audio module 370 via an I2S bus to enable communication between the processor 310 and the audio module 370. In some embodiments, the audio module 370 may communicate audio signals to the wireless communication module 360 via the I2S interface to enable answering calls via the bluetooth headset.

PCM interfaces may also be used for audio communication to sample, quantize and encode analog signals. In some embodiments, the audio module 370 and the wireless communication module 360 may be coupled by a PCM bus interface. In some embodiments, the audio module 370 may also transmit audio signals to the wireless communication module 360 via the PCM interface to enable phone answering via the bluetooth headset. Both the I2S interface and the PCM interface may be used for audio communication.

The UART interface is a universal serial data bus for asynchronous communications. The bus may be a bi-directional communication bus. It converts the data to be transmitted between serial communication and parallel communication. In some embodiments, a UART interface is typically used to connect the processor 310 with the wireless communication module 360. For example: the processor 310 communicates with a bluetooth module in the wireless communication module 360 through a UART interface to implement a bluetooth function. In some embodiments, the audio module 370 may transmit audio signals to the wireless communication module 360 through a UART interface to implement a function of playing music through a bluetooth headset.

The MIPI interface may be used to connect the processor 310 to peripheral devices such as the display screen 394, the camera 393, and the like. The MIPI interfaces include camera serial interfaces (camera serial interface, CSI), display serial interfaces (display serial interface, DSI), and the like. In some embodiments, processor 310 and camera 393 communicate through a CSI interface, implementing the photographing function of electronic device 300. The processor 310 and the display screen 394 communicate via a DSI interface to implement the display functions of the electronic device 300.

The GPIO interface may be configured by software. The GPIO interface may be configured as a control signal or as a data signal. In some embodiments, a GPIO interface may be used to connect processor 310 with camera 393, display 394, wireless communication module 360, audio module 370, sensor module 380, and the like. The GPIO interface may also be configured as an I2C interface, an I2S interface, a UART interface, an MIPI interface, etc.

The USB interface 330 is an interface conforming to the USB standard specification, and may specifically be a Mini USB interface, a Micro USB interface, a USB Type C interface, or the like. The USB interface 330 may be used to connect a charger to charge the electronic device 300, or may be used to transfer data between the electronic device 300 and a peripheral device. And can also be used for connecting with a headset, and playing audio through the headset. The interface may also be used to connect other electronic devices, such as AR devices, etc.

It should be understood that the interfacing relationship between the modules illustrated in the embodiments of the present application is only illustrative, and is not meant to limit the structure of the electronic device 300. In other embodiments of the present application, the electronic device 300 may also employ different interfacing manners in the above embodiments, or a combination of multiple interfacing manners.

The charge management module 340 is configured to receive a charge input from a charger. The charger can be a wireless charger or a wired charger. In some wired charging embodiments, the charge management module 340 may receive a charging input of a wired charger through the USB interface 330. In some wireless charging embodiments, the charge management module 340 may receive wireless charging input through a wireless charging coil of the electronic device 300. The battery 342 is charged by the charge management module 340, and the electronic device may be powered by the power management module 341.

The power management module 341 is configured to connect the battery 342, the charge management module 340 and the processor 310. The power management module 341 receives input from the battery 342 and/or the charge management module 340 to power the processor 310, the internal memory 321, the display screen 394, the camera 393, the wireless communication module 360, and the like. The power management module 341 may also be configured to monitor battery capacity, battery cycle number, battery health (leakage, impedance), and other parameters. In other embodiments, the power management module 341 may also be disposed in the processor 310. In other embodiments, the power management module 341 and the charging management module 340 may also be disposed in the same device.

The wireless communication function of the electronic device 300 may be implemented by the antenna 1, the antenna 2, the mobile communication module 350, the wireless communication module 360, a modem processor, a baseband processor, and the like.

The antennas 1 and 2 are used for transmitting and receiving electromagnetic wave signals. Each antenna in the electronic device 300 may be used to cover a single or multiple communication bands. Different antennas may also be multiplexed to improve the utilization of the antennas. For example: the antenna 1 may be multiplexed into a diversity antenna of a wireless local area network. In other embodiments, the antenna may be used in conjunction with a tuning switch.

The mobile communication module 350 may provide a solution for wireless communication, including 2G/3G/4G/5G, etc., applied on the electronic device 300. The mobile communication module 350 may include at least one filter, switch, power amplifier, low noise amplifier (low noise amplifier, LNA), etc. The mobile communication module 350 may receive electromagnetic waves from the antenna 1, perform processes such as filtering, amplifying, and the like on the received electromagnetic waves, and transmit the processed electromagnetic waves to the modem processor for demodulation. The mobile communication module 350 may amplify the signal modulated by the modem processor, and convert the signal into electromagnetic waves through the antenna 1 to radiate the electromagnetic waves. In some embodiments, at least some of the functional modules of the mobile communication module 350 may be disposed in the processor 310. In some embodiments, at least some of the functional modules of the mobile communication module 350 may be provided in the same device as at least some of the modules of the processor 310.

The modem processor may include a modulator and a demodulator. The modulator is used for modulating the low-frequency baseband signal to be transmitted into a medium-high frequency signal. The demodulator is used for demodulating the received electromagnetic wave signal into a low-frequency baseband signal. The demodulator then transmits the demodulated low frequency baseband signal to the baseband processor for processing. The low frequency baseband signal is processed by the baseband processor and then transferred to the application processor. The application processor outputs sound signals through an audio device (not limited to speaker 370A, receiver 370B, etc.), or displays images or video through display screen 394. In some embodiments, the modem processor may be a stand-alone device. In other embodiments, the modem processor may be provided in the same device as the mobile communication module 350 or other functional module, independent of the processor 310.

The wireless communication module 360 may provide solutions for wireless communication including wireless local area network (wireless local area networks, WLAN) (e.g., wireless fidelity (wireless fidelity, wi-Fi) network), bluetooth (BT), global navigation satellite system (global navigation satellite system, GNSS), frequency modulation (frequency modulation, FM), near field wireless communication technology (near field communication, NFC), infrared technology (IR), etc., as applied to the electronic device 300. The wireless communication module 360 may be one or more devices that integrate at least one communication processing module. The wireless communication module 360 receives electromagnetic waves via the antenna 2, modulates the electromagnetic wave signals, filters the electromagnetic wave signals, and transmits the processed signals to the processor 310. The wireless communication module 360 may also receive a signal to be transmitted from the processor 310, frequency modulate it, amplify it, and convert it to electromagnetic waves for radiation via the antenna 2.

In some embodiments, antenna 1 and mobile communication module 350 of electronic device 300 are coupled, and antenna 2 and wireless communication module 360 are coupled, such that electronic device 300 may communicate with a network and other devices via wireless communication techniques. The wireless communication techniques may include the Global System for Mobile communications (global system for mobile communications, GSM), general packet radio service (general packet radio service, GPRS), code division multiple access (code division multiple access, CDMA), wideband code division multiple access (wideband code division multiple access, WCDMA), time division code division multiple access (time-division code division multiple access, TD-SCDMA), long term evolution (long term evolution, LTE), BT, GNSS, WLAN, NFC, FM, and/or IR techniques, among others. The GNSS may include a global satellite positioning system (global positioning system, GPS), a global navigation satellite system (global navigation satellite system, GLONASS), a beidou satellite navigation system (beidou navigation satellite system, BDS), a quasi zenith satellite system (quasi-zenith satellite system, QZSS) and/or a satellite based augmentation system (satellite based augmentation systems, SBAS).

The electronic device 300 implements display functions through a GPU, a display screen 394, an application processor, and the like. The GPU is a microprocessor for image processing, connected to the display screen 394 and the application processor. The GPU is used to perform mathematical and geometric calculations for graphics rendering. Processor 310 may include one or more GPUs that execute program instructions to generate or change display information.

The display screen 394 is used for displaying images, videos, and the like. The display screen 394 includes a display panel. The display panel may employ a liquid crystal display (liquid crystal display, LCD), an organic light-emitting diode (OLED), an active-matrix organic light-emitting diode (AMOLED) or an active-matrix organic light-emitting diode (matrix organic light emitting diode), a flexible light-emitting diode (flex), a mini, a Micro led, a Micro-OLED, a quantum dot light-emitting diode (quantum dot light emitting diodes, QLED), or the like. In some embodiments, the electronic device 300 may include 1 or N display screens 394, N being a positive integer greater than 1.

Electronic device 300 may implement capture functionality through an ISP, camera 393, video codec, GPU, display 394, and application processor, among others.

The ISP is used to process the data fed back by camera 393. For example, when photographing, the shutter is opened, light is transmitted to the camera photosensitive element through the lens, the optical signal is converted into an electric signal, and the camera photosensitive element transmits the electric signal to the ISP for processing and is converted into an image visible to naked eyes. ISP can also optimize the noise, brightness and skin color of the image. The ISP can also optimize parameters such as exposure, color temperature and the like of a shooting scene. In some embodiments, the ISP may be provided in the camera 393.

Camera 393 is used to capture still images or video. The object generates an optical image through the lens and projects the optical image onto the photosensitive element. The photosensitive element may be a charge coupled device (charge coupled device, CCD) or a Complementary Metal Oxide Semiconductor (CMOS) phototransistor. The photosensitive element converts the optical signal into an electrical signal, which is then transferred to the ISP to be converted into a digital image signal. The ISP outputs the digital image signal to the DSP for processing. The DSP converts the digital image signal into an image signal in a standard RGB, YUV, or the like format. In some embodiments, electronic device 300 may include 1 or N cameras 393, N being a positive integer greater than 1.

The digital signal processor is used for processing digital signals, and can process other digital signals besides digital image signals. For example, when the electronic device 300 is selecting a frequency bin, the digital signal processor is used to fourier transform the frequency bin energy, or the like.

Video codecs are used to compress or decompress digital video. The electronic device 300 may support one or more video codecs. Thus, the electronic device 300 may play or record video in a variety of encoding formats, such as: dynamic picture experts group (moving picture experts group, MPEG) 1, MPEG2, MPEG3, MPEG4, etc.

The NPU is a neural-network (NN) computing processor, and can rapidly process input information by referencing a biological neural network structure, for example, referencing a transmission mode between human brain neurons, and can also continuously perform self-learning. Applications such as intelligent cognition of the electronic device 300 may be implemented by the NPU, for example: image recognition, face recognition, speech recognition, text understanding, etc.

The external memory interface 320 may be used to connect an external memory card, such as a Micro SD card, to enable expansion of the memory capabilities of the electronic device 300. The external memory card communicates with the processor 310 through an external memory interface 320 to implement data storage functions. For example, files such as music, video, etc. are stored in an external memory card.

The internal memory 321 may be used to store computer executable program code comprising instructions. The internal memory 321 may include a storage program area and a storage data area. The storage program area may store an application program (such as a sound playing function, an image playing function, etc.) required for at least one function of the operating system, etc. The storage data area may store data created during use of the electronic device 300 (e.g., audio data, phonebook, etc.), and so on. In addition, the internal memory 321 may include a high-speed random access memory, and may also include a nonvolatile memory, such as at least one magnetic disk storage device, a flash memory device, a universal flash memory (universal flash storage, UFS), and the like. The processor 310 performs various functional applications of the electronic device 300 and data processing by executing instructions stored in the internal memory 321, and/or instructions stored in a memory provided in the processor.

The electronic device 300 may implement audio functionality through an audio module 370, a speaker 370A, a receiver 370B, a microphone 370C, an ear-headphone interface 370D, and an application processor, among others. Such as music playing, recording, etc.

The audio module 370 is used to convert digital audio information into an analog audio signal output and also to convert an analog audio input into a digital audio signal. The audio module 370 may also be used to encode and decode audio signals. In some embodiments, the audio module 370 may be disposed in the processor 310, or some of the functional modules of the audio module 370 may be disposed in the processor 310.

Speaker 370A, also known as a "horn," is used to convert audio electrical signals into sound signals. The electronic device 300 may listen to music, or to hands-free conversations, through the speaker 370A.

A receiver 370B, also referred to as a "earpiece", is used to convert the audio electrical signal into a sound signal. When electronic device 300 is answering a telephone call or voice message, voice may be received by placing receiver 370B close to the human ear.

Microphone 370C, also referred to as a "microphone," is used to convert sound signals into electrical signals. When making a call or transmitting voice information, the user can sound near the microphone 370C through the mouth, inputting a sound signal to the microphone 370C. The electronic device 300 may be provided with at least one microphone 370C. In other embodiments, the electronic device 300 may be provided with two microphones 370C, and may implement a noise reduction function in addition to collecting sound signals. In other embodiments, the electronic device 300 may also be provided with three, four, or more microphones 370C to enable collection of sound signals, noise reduction, identification of sound sources, directional recording functions, etc.

The earphone interface 370D is for connecting a wired earphone. The headset interface 370D may be a USB interface 330 or a 3.5mm open mobile electronic device platform (open mobile terminal platform, OMTP) standard interface, a american cellular telecommunications industry association (cellular telecommunications industry association of the USA, CTIA) standard interface.

The pressure sensor 380A is configured to sense a pressure signal and convert the pressure signal into an electrical signal. In some embodiments, the pressure sensor 380A may be disposed on the display screen 394. Pressure sensor 380A.

Such as resistive pressure sensors, inductive pressure sensors, capacitive pressure sensors, etc. The capacitive pressure sensor may be a capacitive pressure sensor comprising at least two parallel plates with conductive material. When a force is applied to the pressure sensor 380A, the capacitance between the electrodes changes. The electronic device 300 determines the strength of the pressure from the change in capacitance. When a touch operation is applied to the display screen 394, the electronic apparatus 300 detects the touch operation intensity according to the pressure sensor 380A. The electronic device 300 may also calculate the location of the touch based on the detection signal of the pressure sensor 380A. In some embodiments, touch operations that act on the same touch location, but at different touch operation strengths, may correspond to different operation instructions. For example: and executing an instruction for checking the short message when the touch operation with the touch operation intensity smaller than the first pressure threshold acts on the short message application icon. And executing an instruction for newly creating the short message when the touch operation with the touch operation intensity being greater than or equal to the first pressure threshold acts on the short message application icon.

The gyro sensor 380B may be used to determine a motion gesture of the electronic device 300. In some embodiments, the angular velocity of electronic device 300 about three axes (i.e., x, y, and z axes) may be determined by gyro sensor 380B. The gyro sensor 380B may be used for photographing anti-shake. For example, when the shutter is pressed, the gyro sensor 380B detects the shake angle of the electronic device 300, calculates the distance to be compensated by the lens module according to the angle, and makes the lens counteract the shake of the electronic device 300 through the reverse motion, so as to realize anti-shake. The gyro sensor 380B may also be used for navigating, somatosensory game scenes.

The air pressure sensor 380C is used to measure air pressure. In some embodiments, the electronic device 300 calculates altitude from barometric pressure values measured by the barometric pressure sensor 380C, aiding in positioning and navigation.

The magnetic sensor 380D includes a hall sensor. The electronic device 300 may detect the opening and closing of the flip holster using the magnetic sensor 380D. In some embodiments, when the electronic device 300 is a flip machine, the electronic device 300 may detect the opening and closing of the flip according to the magnetic sensor 380D. And then according to the detected opening and closing state of the leather sheath or the opening and closing state of the flip, the characteristics of automatic unlocking of the flip and the like are set.

The acceleration sensor 380E may detect the magnitude of acceleration of the electronic device 300 in various directions (typically three axes). The magnitude and direction of gravity may be detected when the electronic device 300 is stationary. The electronic equipment gesture recognition method can also be used for recognizing the gesture of the electronic equipment, and is applied to horizontal and vertical screen switching, pedometers and other applications.

A distance sensor 380F for measuring distance. The electronic device 300 may measure the distance by infrared or laser. In some embodiments, the electronic device 300 may range using the distance sensor 380F to achieve fast focus.

The proximity light sensor 380G may include, for example, a Light Emitting Diode (LED) and a light detector, such as a photodiode. The light emitting diode may be an infrared light emitting diode. The electronic device 300 emits infrared light outward through the light emitting diode. The electronic device 300 uses a photodiode to detect infrared reflected light from nearby objects. When sufficient reflected light is detected, it may be determined that an object is in the vicinity of the electronic device 300. When insufficient reflected light is detected, the electronic device 300 may determine that there is no object in the vicinity of the electronic device 300. The electronic device 300 can detect that the user holds the electronic device 300 close to the ear by using the proximity light sensor 380G, so as to automatically extinguish the screen to achieve the purpose of saving power. The proximity light sensor 380G may also be used in holster mode, pocket mode to automatically unlock and lock the screen.

The ambient light sensor 380L is used to sense ambient light level. The electronic device 300 may adaptively adjust the brightness of the display screen 394 based on the perceived ambient light level. The ambient light sensor 380L may also be used to automatically adjust white balance during photographing. The ambient light sensor 380L may also cooperate with the proximity light sensor 380G to detect if the electronic device 300 is in a pocket to prevent false touches.

The fingerprint sensor 380H is used to collect a fingerprint. The electronic device 300 can utilize the collected fingerprint characteristics to realize fingerprint unlocking, access an application lock, fingerprint photographing, fingerprint incoming call answering and the like.

The temperature sensor 380J is used to detect temperature. In some embodiments, the electronic device 300 performs a temperature processing strategy using the temperature detected by the temperature sensor 380J. For example, when the temperature reported by temperature sensor 380J exceeds a threshold, electronic device 300 performs a reduction in performance of a processor located in the vicinity of temperature sensor 380J in order to reduce power consumption to implement thermal protection. In other embodiments, when the temperature is below another threshold, the electronic device 300 heats the battery 342 to avoid the low temperature causing the electronic device 300 to shut down abnormally. In other embodiments, when the temperature is below a further threshold, the electronic device 300 performs boosting of the output voltage of the battery 342 to avoid abnormal shutdown caused by low temperatures.

Touch sensor 380K, also known as a "touch device". The touch sensor 380K may be disposed on the display screen 394, and the touch sensor 380K and the display screen 394 form a touch screen, which is also referred to as a "touch screen". The touch sensor 380K is for detecting a touch operation acting thereon or thereabout. The touch sensor may communicate the detected touch operation to the application processor to determine the touch event type. Visual output related to touch operations may be provided through the display screen 394. In other embodiments, touch sensor 380K may also be located on a surface of electronic device 300 other than at display 394.

The bone conduction sensor 380M may acquire a vibration signal. In some embodiments, bone conduction sensor 380M may acquire a vibration signal of a human vocal tract vibrating bone pieces. The bone conduction sensor 380M may also contact the pulse of the human body to receive the blood pressure pulsation signal. In some embodiments, bone conduction sensor 380M may also be provided in the headset, in combination with an osteoinductive headset. The audio module 370 may analyze the voice signal based on the vibration signal of the sound portion vibration bone block obtained by the bone conduction sensor 380M, so as to implement a voice function. The application processor can analyze heart rate information based on the blood pressure beat signals acquired by the bone conduction sensor 380M, so as to realize a heart rate detection function.

The keys 390 include a power on key, a volume key, etc. Key 390 may be a mechanical key. Or may be a touch key. The electronic device 300 may receive key inputs, generating key signal inputs related to user settings and function controls of the electronic device 300.

The motor 391 may generate a vibration alert. The motor 391 may be used for incoming call vibration alerting as well as for touch vibration feedback. For example, touch operations acting on different applications (e.g., photographing, audio playing, etc.) may correspond to different vibration feedback effects. The motor 391 may also correspond to different vibration feedback effects by touch operations applied to different areas of the display screen 394. Different application scenarios (such as time reminding, receiving information, alarm clock, game, etc.) can also correspond to different vibration feedback effects. The touch vibration feedback effect may also support customization.

The indicator 392 may be an indicator light, which may be used to indicate a state of charge, a change in charge, a message indicating a missed call, a notification, etc.

The SIM card interface 395 is for interfacing with a SIM card. The SIM card may be inserted into the SIM card interface 395 or removed from the SIM card interface 395 to enable contact and separation with the electronic device 300. The electronic device 300 may support 1 or N SIM card interfaces, N being a positive integer greater than 1. The SIM card interface 395 may support Nano SIM cards, micro SIM cards, and the like. The same SIM card interface 395 can be used to insert multiple cards simultaneously. The types of the plurality of cards may be the same or different. The SIM card interface 395 may also be compatible with different types of SIM cards. The SIM card interface 395 may also be compatible with external memory cards. The electronic device 300 interacts with the network through the SIM card to realize functions such as communication and data communication. In some embodiments, the electronic device 300 employs esims, namely: an embedded SIM card. The eSIM card can be embedded in the electronic device 300 and cannot be separated from the electronic device 300.

The software system of the electronic device 300 may employ a layered architecture, an event driven architecture, a microkernel architecture, a microservice architecture, or a cloud architecture. In the embodiment of the invention, taking an Android system with a layered architecture as an example, a software structure of the electronic device 300 is illustrated.

Fig. 13 is a software block diagram of an electronic device 300 according to an embodiment of the invention.

The layered architecture divides the software into several layers, each with distinct roles and branches. The layers communicate with each other through a software interface. In some embodiments, the Android system is divided into four layers, from top to bottom, an application layer, an application framework layer, an Zhuoyun row (Android run) and system libraries, and a kernel layer, respectively.

The application layer may include a series of application packages.

As shown in fig. 13, the application package may include applications for cameras, gallery, calendar, phone calls, maps, navigation, WLAN, bluetooth, music, video, short messages, etc.

The application framework layer provides an application programming interface (application programming interface, API) and programming framework for application programs of the application layer. The application framework layer includes a number of predefined functions.

As shown in fig. 13, the application framework layer may include a window manager, a content provider, a view system, a phone manager, a resource manager, a notification manager, and the like.

The window manager is used for managing window programs. The window manager can acquire the size of the display screen, judge whether a status bar exists, lock the screen, intercept the screen and the like.

The content provider is used to store and retrieve data and make such data accessible to applications. The data may include video, images, audio, calls made and received, browsing history and bookmarks, phonebooks, etc.

The view system includes visual controls, such as controls to display text, controls to display pictures, and the like. The view system may be used to build applications. The display interface may be composed of one or more views. For example, a display interface including a text message notification icon may include a view displaying text and a view displaying a picture.

The telephony manager is used to provide the communication functions of the electronic device 300. Such as the management of call status (including on, hung-up, etc.).

The resource manager provides various resources for the application program, such as localization strings, icons, pictures, layout files, video files, and the like.

The notification manager allows the application to display notification information in a status bar, can be used to communicate notification type messages, can automatically disappear after a short dwell, and does not require user interaction. Such as notification manager is used to inform that the download is complete, message alerts, etc. The notification manager may also be a notification in the form of a chart or scroll bar text that appears on the system top status bar, such as a notification of a background running application, or a notification that appears on the screen in the form of a dialog window. For example, a text message is prompted in a status bar, a prompt tone is emitted, the electronic device vibrates, and an indicator light blinks, etc.

Android run time includes a core library and virtual machines. Android run time is responsible for scheduling and management of the Android system.

The core library consists of two parts: one part is a function which needs to be called by java language, and the other part is a core library of android.

The application layer and the application framework layer run in a virtual machine. The virtual machine executes java files of the application program layer and the application program framework layer as binary files. The virtual machine is used for executing the functions of object life cycle management, stack management, thread management, security and exception management, garbage collection and the like.

The system library may include a plurality of functional modules. For example: surface manager (surface manager), media Libraries (Media Libraries), three-dimensional graphics processing Libraries (e.g., openGL ES), 2D graphics engines (e.g., SGL), etc.

The surface manager is used to manage the display subsystem and provides a fusion of 2D and 3D layers for multiple applications.

Media libraries support a variety of commonly used audio, video format playback and recording, still image files, and the like. The media library may support a variety of audio and video encoding formats, such as MPEG4, h.264, MP3, AAC, AMR, JPG, PNG, etc.

The three-dimensional graphic processing library is used for realizing three-dimensional graphic drawing, image rendering, synthesis, layer processing and the like.

The 2D graphics engine is a drawing engine for 2D drawing.

The kernel layer is a layer between hardware and software. The inner core layer at least comprises a display driver, a camera driver, an audio driver and a sensor driver.

The workflow of the electronic device 300 software and hardware is illustrated below in connection with capturing a photo scene.

When touch sensor 380K receives a touch operation, a corresponding hardware interrupt is issued to the kernel layer. The kernel layer processes the touch operation into the original input event (including information such as touch coordinates, time stamp of touch operation, etc.). The original input event is stored at the kernel layer. The application framework layer acquires an original input event from the kernel layer, and identifies a control corresponding to the input event. Taking the touch operation as a touch click operation, taking a control corresponding to the click operation as an example of a control of a camera application icon, the camera application calls an interface of an application framework layer, starts the camera application, further starts a camera driver by calling a kernel layer, and captures a still image or video through a camera 393.

Embodiments of the present application provide a computer readable storage medium having instructions stored therein which, when executed on a terminal device, cause the terminal device to perform the functions/steps as in the method embodiments described above.

Embodiments of the present application also provide a computer program product comprising instructions which, when run on a computer or any of the at least one processor, cause the computer to perform the functions/steps as in the method embodiments described above.

In the embodiments of the present application, "at least one" means one or more, and "a plurality" means two or more. "and/or", describes an association relation of association objects, and indicates that there may be three kinds of relations, for example, a and/or B, and may indicate that a alone exists, a and B together, and B alone exists. Wherein A, B may be singular or plural. The character "/" generally indicates that the context-dependent object is an "or" relationship. "at least one of the following" and the like means any combination of these items, including any combination of single or plural items. For example, at least one of a, b and c may represent: a, b, c, a-b, a-c, b-c, or a-b-c, wherein a, b, c may be single or plural.

Those of ordinary skill in the art will appreciate that the various elements and algorithm steps described in the embodiments disclosed herein can be implemented as a combination of electronic hardware, computer software, and electronic hardware. Whether such functionality is implemented as hardware or software depends upon the particular application and design constraints imposed on the solution. Skilled artisans may implement the described functionality in varying ways for each particular application, but such implementation decisions should not be interpreted as causing a departure from the scope of the present application.

It will be clear to those skilled in the art that, for convenience and brevity of description, specific working procedures of the above-described systems, apparatuses and units may refer to corresponding procedures in the foregoing method embodiments, and are not repeated herein.

In several embodiments provided by the present application, any of the functions, if implemented in the form of software functional units and sold or used as a stand-alone product, may be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present application may be embodied essentially or in a part contributing to the prior art or in a part of the technical solution in the form of a software product stored in a storage medium, comprising several instructions for causing an electronic device (which may be a personal computer, a server, a network device, etc.) to perform all or part of the steps of the method according to the embodiments of the present application. And the aforementioned storage medium includes: a U-disk, a removable hard disk, a read-only memory (ROM), a random access memory (random access memory, RAM), a magnetic disk, or an optical disk, or other various media capable of storing program codes.

The foregoing is merely exemplary embodiments of the present application, and any person skilled in the art may easily conceive of changes or substitutions within the technical scope of the present application, which should be covered by the present application. The protection scope of the present application shall be subject to the protection scope of the claims.

Claims

1. A step counting calibration method, characterized by being applied to a first terminal device, the first terminal device being connected to both a first wearable device and a foot wearable device, the method comprising:

and uploading the step counting calibration information to cloud equipment.

2. The method of claim 1, wherein the target device comprises the first terminal device or the first wearable device.

3. The method according to claim 1 or 2, wherein said determining a target device from said first step count data, said second step count data and said third step count data comprises:

4. The method of any of claims 1-3, wherein the acquiring first step count data and the acquiring second step count data acquired by the first wearable device and third step count data acquired by the foot wearable device comprises:

5. The method of any of claims 1-4, wherein the first user characteristic comprises one or more of: the gender, age, height, weight and stride of the user of the first terminal device.

6. The method of any of claims 1-5, wherein the device information includes a device type and a device model.

7. A step counting calibration method, characterized by being applied to a second terminal device, the second terminal device being connected to a second wearable device, the method comprising:

receiving a query result sent by the cloud device;

8. The method of claim 7, wherein the target device comprises the second terminal device or the second wearable device;

9. The method according to claim 7 or 8, wherein the step count calibration information set comprises at least one step count calibration information.

10. A step counting calibration method, which is applied to a cloud device, wherein the cloud device stores a step counting calibration information set, and the method comprises:

and sending the query result to the second terminal equipment.

11. The method of claim 10, wherein the query result comprises a target device or a query failure.

12. The method of claim 11, wherein the step count calibration information collection includes at least one step count calibration information; the step counting calibration information comprises a first user characteristic, device information of a first terminal device, device information of a first wearable device and a target device.

13. The method of claim 12, wherein the query information comprises a second user characteristic, device information of the second terminal device, device information of a second wearable device.

14. The method of claim 13, wherein querying out the query results corresponding to the query information from the step-counting calibration information set according to the query instruction comprises:

and if the target equipment in the step counting calibration information corresponding to the maximum similarity is judged to comprise the first wearable equipment, generating the query result comprising the second wearable equipment.

15. The method of claim 13, wherein after determining whether the similarity is greater than or equal to a set threshold, further comprising:

16. The method of claim 13, wherein before receiving the query instruction carrying the query information uploaded by the second terminal device, further comprises:

17. A step counting calibration system, the system comprising: the first terminal device of any of claims 1-6, the second terminal device of any of claims 7-9, and the cloud device of any of claims 10-16.

18. A first terminal device comprising a processor and a memory, wherein the memory is for storing a computer program comprising program instructions which, when executed by the processor, cause the first terminal device to perform the method of any of claims 1-6.

19. A second terminal device comprising a processor and a memory, wherein the memory is for storing a computer program comprising program instructions which, when executed by the processor, cause the second terminal device to perform the method of any of claims 7-9.

20. A cloud device comprising a processor and a memory, wherein the memory is configured to store a computer program, the computer program comprising program instructions that, when executed by the processor, cause the cloud device to perform the method of any of claims 10-16.

21. A computer readable storage medium, characterized in that the computer readable storage medium stores a computer program comprising program instructions which, when executed by a computer, cause the computer to perform the method of any of claims 1-16.