WO2022206703A1 - 一种检测穿戴设备佩戴松紧的方法、装置和系统 - Google Patents

一种检测穿戴设备佩戴松紧的方法、装置和系统 Download PDF

Info

Publication number
WO2022206703A1
WO2022206703A1 PCT/CN2022/083467 CN2022083467W WO2022206703A1 WO 2022206703 A1 WO2022206703 A1 WO 2022206703A1 CN 2022083467 W CN2022083467 W CN 2022083467W WO 2022206703 A1 WO2022206703 A1 WO 2022206703A1
Authority
WO
WIPO (PCT)
Prior art keywords
wearable device
action
wearing
tightness
data
Prior art date
Application number
PCT/CN2022/083467
Other languages
English (en)
French (fr)
Inventor
郭建华
徐腾
孙宇
Original Assignee
华为技术有限公司
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by 华为技术有限公司 filed Critical 华为技术有限公司
Priority to EP22778885.8A priority Critical patent/EP4292519A1/en
Publication of WO2022206703A1 publication Critical patent/WO2022206703A1/zh

Links

Images

Classifications

    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00—Measuring for diagnostic purposes; Identification of persons
    • A61B5/103—Detecting, measuring or recording devices for testing the shape, pattern, colour, size or movement of the body or parts thereof, for diagnostic purposes
    • A61B5/11—Measuring movement of the entire body or parts thereof, e.g. head or hand tremor, mobility of a limb
    • A61B5/1123—Discriminating type of movement, e.g. walking or running
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00—Measuring for diagnostic purposes; Identification of persons
    • A61B5/103—Detecting, measuring or recording devices for testing the shape, pattern, colour, size or movement of the body or parts thereof, for diagnostic purposes
    • A61B5/11—Measuring movement of the entire body or parts thereof, e.g. head or hand tremor, mobility of a limb
    • A61B5/1118—Determining activity level
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00—Measuring for diagnostic purposes; Identification of persons
    • A61B5/103—Detecting, measuring or recording devices for testing the shape, pattern, colour, size or movement of the body or parts thereof, for diagnostic purposes
    • A61B5/11—Measuring movement of the entire body or parts thereof, e.g. head or hand tremor, mobility of a limb
    • A61B5/112—Gait analysis
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00—Measuring for diagnostic purposes; Identification of persons
    • A61B5/68—Arrangements of detecting, measuring or recording means, e.g. sensors, in relation to patient
    • A61B5/6801—Arrangements of detecting, measuring or recording means, e.g. sensors, in relation to patient specially adapted to be attached to or worn on the body surface
    • A61B5/6802—Sensor mounted on worn items
    • A61B5/6804—Garments; Clothes
    • A61B5/6807—Footwear
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00—Measuring for diagnostic purposes; Identification of persons
    • A61B5/68—Arrangements of detecting, measuring or recording means, e.g. sensors, in relation to patient
    • A61B5/6801—Arrangements of detecting, measuring or recording means, e.g. sensors, in relation to patient specially adapted to be attached to or worn on the body surface
    • A61B5/6813—Specially adapted to be attached to a specific body part
    • A61B5/6829—Foot or ankle
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F3/00—Input arrangements for transferring data to be processed into a form capable of being handled by the computer; Output arrangements for transferring data from processing unit to output unit, e.g. interface arrangements
    • G06F3/01—Input arrangements or combined input and output arrangements for interaction between user and computer
    • G06F3/016—Input arrangements with force or tactile feedback as computer generated output to the user
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N3/00—Computing arrangements based on biological models
    • G06N3/02—Neural networks
    • G06N3/08—Learning methods
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
    • G06V40/00—Recognition of biometric, human-related or animal-related patterns in image or video data
    • G06V40/20—Movements or behaviour, e.g. gesture recognition
    • G06V40/28—Recognition of hand or arm movements, e.g. recognition of deaf sign language
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B2562/00—Details of sensors; Constructional details of sensor housings or probes; Accessories for sensors
    • A61B2562/02—Details of sensors specially adapted for in-vivo measurements
    • A61B2562/0219—Inertial sensors, e.g. accelerometers, gyroscopes, tilt switches
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F2218/00—Aspects of pattern recognition specially adapted for signal processing
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F2218/00—Aspects of pattern recognition specially adapted for signal processing
    • G06F2218/12—Classification; Matching
    • G—PHYSICS
    • G08—SIGNALLING
    • G08B—SIGNALLING OR CALLING SYSTEMS; ORDER TELEGRAPHS; ALARM SYSTEMS
    • G08B21/00—Alarms responsive to a single specified undesired or abnormal condition and not otherwise provided for
    • G08B21/18—Status alarms
    • G08B21/24—Reminder alarms, e.g. anti-loss alarms

Definitions

  • Embodiments of the present invention relate to the technical field of electronic devices, and in particular, to a method, device, and system for detecting the tightness of a wearable device.
  • wearable devices are widely used in people's life, work and study.
  • the wearable device can detect the user's health status and the user's movement status.
  • the data collected by the wearable device is inaccurate, resulting in inaccurate assessment of the user's health or exercise by the wearable device, affecting the detection performance of the wearable device. Therefore, how to detect the tightness of the wearable device is a technical problem to be solved in the art.
  • the embodiments of the present application provide a method, device and system for detecting the wearing tightness of a wearable device, which are used to detect the wearing tightness of the wearable device and ensure the detection performance of the wearable device.
  • an embodiment of the present application provides a method for detecting wearing tightness of a wearable device.
  • the execution body of the method may be an electronic device (such as a wearable device) or a component located in the electronic device (for example, a chip, a chip system or processor, etc.), the following description takes the execution subject being an electronic device as an example.
  • the method includes: collecting motion data of the user when it is detected that the wearable device is in a wearing state. The motion data of the first motion in the motion data of the user is identified. Determine the wearing tightness of the wearable device corresponding to the action data of the first action.
  • the motion data of the user may include acceleration and/or angular velocity.
  • the wearing tightness of the wearable device can be understood as the degree of tightness (such as normal wearing of the wearable device, loose wearing of the wearable device, and tight wearing of the wearable device, etc.), and can also be understood as a specific value.
  • the first action is a certain action in the user's exercise process.
  • the first action corresponds to the position where the wearable device is worn.
  • the first action may include an arm swing action and the like.
  • the first motion may include a jumping motion, a kicking motion, and the like.
  • the embodiments of the present application can determine the wearing tightness of the wearable device according to the user's motion data, thereby avoiding the problem of inaccurate motion data collection, making the motion data collection more reliable, and laying a foundation for providing more professional guidance for the user.
  • determining the wearing tightness of the wearable device corresponding to the motion data of the first action may specifically be: according to the motion data of the first action and the corresponding relationship between the preset motion data and the wearing tightness, determine the tightness of the wearable device. The tightness of the wearable device.
  • the corresponding relationship between the preset exercise data and the wearing tightness can be understood as: first, a corresponding relationship between the exercise data and the wearing tightness, that is, the value of the exercise data corresponds to the wearing tightness one-to-one.
  • the acceleration value is 30 m/s 2 , which corresponds to the wearing tightness being normal wearing.
  • the second is the correspondence between a set of exercise data and the wearing tightness, that is, the numerical interval of the exercise data corresponds to the wearing tightness.
  • the value interval of the acceleration is 30-50 m/s 2 , which corresponds to the wearing tightness being normal wearing.
  • the wearable device can determine the wearing tightness of the wearable device according to the user's motion data, and can detect the wearing tightness of the wearable device without an additional hardware device to drive the action of the wearable device, thereby effectively avoiding the problem of inaccurate motion data collection. , which makes the collection of motion data more reliable and lays the foundation for providing users with more professional guidance.
  • the wearing tightness of the wearable device is determined according to the motion data of the first action and the corresponding relationship between the preset motion data and the wearing tightness, which may be specifically: identifying the first action in the motion data.
  • Action data of the first action node According to the action data of the first action node, the first feature data corresponding to the first action node is determined.
  • the wearing tightness of the wearable device is determined according to the first characteristic data and the corresponding relationship between the preset motion data and the wearing tightness.
  • the first characteristic data includes: the number of peaks of the acceleration waveform, the number of peaks of the angular velocity waveform, the number of valleys of the acceleration waveform, the number of valleys of the angular velocity waveform, the peak value of the acceleration waveform, the peak value of the angular velocity waveform, the At least one of the mean value, the mean value of the angular velocity, the gradient of the acceleration waveform, and the gradient of the angular velocity waveform.
  • the mean value of the acceleration can be understood as the mean value of the acceleration within the preset time period.
  • the mean value of the angular velocity can be understood as the mean value of the angular velocity within the preset time period.
  • the gradient of the acceleration waveform can be understood as the slope of the tangent to the preset position in the acceleration waveform.
  • the gradient of the angular velocity waveform can be understood as the slope of the tangent to the preset position in the angular velocity waveform.
  • determining the wearing tightness of the wearable device corresponding to the action data of the first action may specifically be: according to the action data of the first action and the wearing tightness model, determining the wearing tightness corresponding to the action data of the first action.
  • the motion data of the first action is used as the input of the wearing tightness model, and the wearing tightness of the wearable device is taken as the output of the wearing tightness model.
  • the method for detecting the wearing tightness of the wearable device may further include: according to the wearing tightness of the wearable device. , generates prompt information, and the prompt information presents the detection result of the wearing tightness of the wearable device in a preset presentation form.
  • the preset presentation form includes one or more combinations of the following: sound presentation form, text presentation form, vibration presentation form and light presentation form.
  • the phenomenon that the user's wearable device is easy to fall off and lose during the user's exercise can be effectively avoided, and at the same time, the user's wear and tear during the exercise can be avoided. Risk of collision and accidental collision.
  • the wearing tightness of the wearable device includes: normal wearing of the wearable device, loose wearing of the wearable device, and tight wearing of the wearable device.
  • the method for detecting the wearing tightness of the wearable device further includes: determining the wearing tightness of the wearable device at each moment within the first duration. According to the wearing tightness of the wearable device at each moment in the first duration, the second duration in which the wearable device is loosely worn is determined. According to the first duration and the second duration, and the first exercise energy calculated by the wearable device, the second exercise energy of the user within the first duration is calculated. The first exercise energy is calculated when the wearing state of the wearable device is normal or tight within the first period of time.
  • both the first exercise energy and the second exercise energy may be understood as the exercise energy consumption of the user.
  • the calories consumed by the user's exercise the calories consumed by the user's exercise, and the like.
  • the second duration may refer to a continuous duration, or may refer to the sum of multiple non-consecutive durations. That is to say, the second duration may be a continuous duration during which the wearable device is loosely worn, or may be the sum of multiple discontinuous durations during which the wearable device is loosely worn.
  • the wearable device may evaluate the exercise energy of the user in the second period of time.
  • the wearable device can determine the actual exercise energy of the user's exercise in the second period of time according to the proportion of time when the wearable device is loosely worn and the estimated exercise energy, so that the user's exercise data is more credible, so as to facilitate Remind the user to pay attention to adjust the wearing tightness of the wearable device when running next time.
  • the first action includes a take-off action, and the first action node includes the foot leaving the ground and/or the foot touching the ground; or, the first action includes an arm swing action, and the first action node includes the arm swinging at the Designated positions on the front of the body and/or arm swings at designated positions on the back of the body.
  • the wearable device is used to be worn on the user's feet or shoes.
  • an embodiment of the present application provides a device for detecting tightness of wearing of a wearable device, the device includes: a collection unit configured to collect motion data of a user when it is detected that the wearable device is in a wearing state.
  • the identifying unit is configured to identify the motion data of the first motion in the motion data of the user.
  • the first determining unit is configured to determine the wearing tightness of the wearable device corresponding to the action data of the first action.
  • the first determining unit is further configured to: determine the wearing tightness of the wearable device according to the motion data of the first action and the preset corresponding relationship between the motion data and the wearing tightness.
  • the first determining unit is further configured to: identify the action data of the first action node in the action data of the first action. According to the action data of the first action node, the first feature data corresponding to the first action node is determined. The wearing tightness of the wearable device is determined according to the first characteristic data and the corresponding relationship between the preset motion data and the wearing tightness.
  • the first characteristic data includes: the number of peaks of the acceleration waveform, the number of peaks of the angular velocity waveform, the number of valleys of the acceleration waveform, the number of valleys of the angular velocity waveform, the peak value of the acceleration waveform, the peak value of the angular velocity waveform, the At least one of the mean value, the mean value of the angular velocity, the gradient of the acceleration waveform, and the gradient of the angular velocity waveform.
  • the first determining unit is further configured to: determine the wearing tightness of the wearable device corresponding to the motion data of the first action according to the motion data of the first action and the wearing tightness model.
  • the motion data of the first action is used as the input of the wearing tightness model, and the wearing tightness of the wearable device is taken as the output of the wearing tightness model.
  • the apparatus for detecting the wearing tightness of the wearable device further includes: a generating unit, configured to generate prompt information according to the wearing tightness of the wearable device, and the prompt information presents the wearable device in a preset presentation form Test results of wearing tightness.
  • the preset presentation form includes one or more combinations of the following: sound presentation form, text presentation form, vibration presentation form and light presentation form.
  • the phenomenon that the user's wearable device is easy to fall off and lose during the user's exercise can be effectively avoided, and at the same time, the user's wear and tear during the exercise can be avoided. Risk of collision and accidental collision.
  • the wearing tightness of the wearable device includes: normal wearing of the wearable device, loose wearing of the wearable device, and tight wearing of the wearable device.
  • the apparatus for detecting the wearing tightness of the wearable device further includes: a second determining unit, configured to determine the wearing tightness of the wearable device at each moment within the first duration.
  • the third determining unit is configured to determine the second duration of loose wearing of the wearable device according to the wearing tightness of the wearable device at each moment in the first duration.
  • the calculation unit is configured to calculate the second exercise energy of the user within the first duration according to the first duration and the second duration, and the first exercise energy calculated by the wearable device. The first exercise energy is calculated when the wearing state of the wearable device is normal or tight within the first period of time.
  • the wearable device may evaluate the exercise energy of the user in the second period of time.
  • the wearable device can determine the actual exercise energy of the user's exercise in the second period of time according to the proportion of time when the wearable device is loosely worn and the estimated exercise energy, so that the user's exercise data is more credible, so as to facilitate Remind the user to pay attention to adjust the wearing tightness of the wearable device when running next time.
  • the first action includes a take-off action, and the first action node includes the foot leaving the ground and/or the foot touching the ground; or, the first action includes an arm swing action, and the first action node includes the arm swinging at the Designated positions on the front of the body and/or arm swings at designated positions on the back of the body.
  • the wearable device is used to be worn on the user's feet or shoes.
  • the apparatus has the function of implementing any method in the above aspects and possible implementation manners.
  • This function can be implemented by hardware or by executing corresponding software by hardware.
  • the hardware or software includes at least one module or unit corresponding to the above-mentioned functions.
  • an embodiment of the present application provides a system for detecting wearing tightness of a wearable device, the system comprising: a wearable device, configured to collect motion data of a user when it is detected that the wearable device is in a wearing state.
  • the motion data of the first motion in the motion data of the user is identified.
  • the non-wearable device is used to: receive the wearing tightness of the wearable device, and generate prompt information according to the wearing tightness of the wearable device, and the prompt information is used to prompt the user for the detection result of the wearing tightness of the wearable device.
  • the function of detecting the wearing tightness of the wearable device extends to multiple devices, and the cooperative operation between the multiple devices not only solves the user's wearing tightness problem, but also increases the user's multiple device linkage experience.
  • an embodiment of the present application provides a system for detecting wearing tightness of a wearable device, the system includes: a wearable device, configured to: collect motion data of a user when it is detected that the wearable device is in a wearing state; Movement data is sent to non-wearable devices.
  • the non-wearable device is used for: receiving the motion data sent by the wearable device, and identifying the motion data of the first action in the motion data; and determining the wearing tightness of the wearable device corresponding to the motion data of the first action.
  • the non-wearable device is further configured to: generate prompt information according to the wearing tightness of the wearable device, and the prompt information is used to prompt the user for the detection result of the wearing tightness of the wearable device.
  • the function of detecting the wearing tightness and prompting of the wearable device is extended to multiple devices, and the cooperative operation between the multiple devices not only solves the problem of the user's wearing tightness, but also increases the user's experience of linking multiple devices.
  • a computer-readable storage medium including computer instructions, which, when the computer instructions are executed on a terminal, cause the terminal to execute the method described in the above aspects and any possible implementation manners.
  • a sixth aspect provides a computer program product, which when the computer program product runs on a computer, causes the computer to execute the method described in the above aspect and any one of the possible implementation manners.
  • a chip system including a processor.
  • the processor executes an instruction, the processor executes the method described in the above aspect and any one of the possible implementation manners.
  • FIG. 1 is a schematic structural diagram of a wearable device provided by an embodiment of the present application
  • FIG. 2 is a schematic flowchart of a method for detecting tightness of wearing of a wearable device provided by an embodiment of the present application
  • FIG. 3 is a schematic diagram of an application scenario of a method for detecting the tightness of a wearable device provided by an embodiment of the present application
  • FIG. 4 is a schematic diagram of an application scenario of a method for detecting the tightness of a wearable device provided by an embodiment of the present application
  • FIG. 5 is a schematic diagram of an application scenario of a method for detecting the tightness of a wearable device provided by an embodiment of the present application
  • FIG. 6a is a schematic diagram of an application scenario of a method for detecting the tightness of a wearable device provided by an embodiment of the present application
  • FIG. 6b is a schematic diagram of an application scenario of a method for detecting the tightness of a wearable device provided by an embodiment of the present application
  • FIG. 7 is a schematic flowchart of a method for detecting tightness of wearing of a wearable device in an application scenario provided by an embodiment of the present application
  • FIG. 8 is a schematic flowchart of a method for detecting tightness of wearing of a wearable device in an application scenario provided by an embodiment of the present application;
  • FIG. 9 is a schematic flowchart of a method for detecting tightness of wearing of a wearable device in an application scenario provided by an embodiment of the present application.
  • FIG. 10 is a schematic flowchart of a method for detecting tightness of wearing of a wearable device provided by an embodiment of the present application
  • FIG. 11 is a schematic flowchart of a method for detecting tightness of wearing of a wearable device according to an embodiment of the present application
  • FIG. 12 is a schematic structural diagram of a device for detecting tightness of wearing of a wearable device according to an embodiment of the present application.
  • first and second are only used for descriptive purposes, and should not be construed as indicating or implying relative importance or implicitly indicating the number of indicated technical features.
  • a feature defined as “first” or “second” may expressly or implicitly include one or more of that feature.
  • plural means two or more.
  • words such as “exemplary” or “for example” are used to represent examples, illustrations or illustrations. Any embodiments or designs described in the embodiments of the present application as “exemplary” or “such as” should not be construed as preferred or advantageous over other embodiments or designs. Rather, the use of words such as “exemplary” or “such as” is intended to present the related concepts in a specific manner.
  • wearable devices are widely used in people's life, work and study.
  • the wearable device can detect the user's health status and the user's movement status.
  • the wearable device is loosely worn on the user's body, the data collected by the wearable device is inaccurate, resulting in inaccurate assessment of the user's health or exercise by the wearable device, affecting the detection performance of the wearable device.
  • the wearing tightness of the wearable device can be detected in the following ways: the pressure value on the bottom shell of the wearable device is detected by the pressure sensor arranged on the bottom shell of the wearable device, and the wearable device is judged according to the detected pressure value.
  • the wearing tightness of the device solves the problem of detecting the wearing tightness of the wearable device, improves the comfort of the user, and the accuracy of the detection performance of the wearable device.
  • the embodiment of the present application provides another method for detecting the wearing tightness of a wearable device: when it is detected that the wearable device is in a wearing state, the user's motion data is collected. Identify the action data of the first action in the user's running data. Determine the wearing tightness of the wearable device corresponding to the action data of the first action. In this way, the embodiments of the present application can determine the wearing tightness of the wearable device according to the user's motion data, thereby avoiding the problem of inaccurate motion data collection, making the motion data collection more reliable, and laying a foundation for providing more professional guidance for the user.
  • determining the wearing tightness of the wearable device corresponding to the motion data of the first action can be implemented in the following ways: Mode 1: Determine the wearable device according to the motion data of the first action and the corresponding relationship between the motion data and the wearing tightness. Wear tightness. Exemplarily, the first feature data corresponding to the first action node of the first action of the user is determined according to the action data of the first action. According to the corresponding relationship between the feature data and the wearing tightness, and the first feature data corresponding to the first action node, the wearing tightness of the wearable device is determined.
  • Method 2 According to the motion data of the first action and the wearing tightness model, determine the wearing tightness of the wearable device corresponding to the motion data of the first action.
  • the motion data of the first action is used as the input of the wearing tightness model, and the wearing tightness of the wearable device is used as the output of the wearing tightness model, and the wearing tightness model is obtained based on the exercise data and the wearing tightness training of the wearable device.
  • the method for detecting the wearing tightness of the wearable device further includes: generating prompt information according to the wearing tightness of the wearable device, and the prompt information presents the detection result of the wearing tightness of the wearable device to the user in a preset presentation form.
  • the preset presentation form includes one or more combinations of the following: sound presentation form, text presentation form, vibration presentation form and light presentation form.
  • the method for tightening the wearing of the wearable device provided in the embodiment of the present application may have one or more execution bodies.
  • the executing body of the method for detecting the wearing tightness of the wearable device may be the wearable device.
  • the executors of the method for detecting the wearing tightness of the wearable device may include a wearable device and a non-wearable device, and the non-wearable device may be a mobile phone, a computer, a headset, a Watches, bracelets and other equipment.
  • the cooperation between the wearable device and the non-wearable device can be implemented in multiple ways. Illustratively, as follows:
  • Method 1 When the wearable device detects that the wearable device is in the wearing state, it collects the user's motion data, identifies the motion data of the first action in the user's motion data, determines the wearing tightness of the wearable device corresponding to the motion data of the first action, and Send the wear tightness of the wearable device to the non-wearable device.
  • the wearable device may collect motion data of the user when detecting that the wearable device is in a wearing state.
  • the wearable device identifies the motion data of the first motion in the collected motion data of the user, where the first motion includes at least one motion node.
  • the wearable device determines the first feature data corresponding to the first action node of the user's first action.
  • the wearable device determines the wearing tightness of the wearable device according to the correspondence between the motion data (eg, the first standard data of the first action node) and the wearing tightness stored in the standard database, and the first characteristic data corresponding to the first action node .
  • the wearable device sends the wearing tightness of the wearable device to the non-wearable device.
  • the non-wearable device receives the wearing tightness of the wearable device, and generates prompt information according to the wearing tightness of the wearable device to prompt the user of the detection result of the wearing tightness of the wearable device.
  • Method 2 When the wearable device detects that the wearable device is in a wearing state, the user's motion data is collected. The wearable device sends the collected motion data to the non-wearable device. The non-wearable device receives the motion data sent by the wearable device, identifies the motion data of the first action in the motion data, and determines the wearing tightness of the wearable device corresponding to the motion data of the first action. Specifically, the non-wearable device may identify motion data of a first action in the motion data, where the first action includes at least one action node. The non-wearable device determines the first feature data corresponding to the first action node of the first action of the user.
  • the non-wearable device determines the wearing tightness of the wearable device according to the correspondence between the motion data (eg, the first standard data of the first action node) and the wearing tightness stored in the standard database, and the first characteristic data corresponding to the first action node Spend. Further, the non-wearable device generates prompt information according to the wearing tightness of the wearable device to prompt the user of the detection result of the wearing tightness of the wearable device.
  • the motion data eg, the first standard data of the first action node
  • the non-wearable device generates prompt information according to the wearing tightness of the wearable device to prompt the user of the detection result of the wearing tightness of the wearable device.
  • FIG. 1 shows a schematic structural diagram of the wearable device 100 .
  • the wearable device 100 may include a processor 110, a memory 120, a universal serial bus (USB) interface 130, a charging management module 140, a power management module 141, a battery 142, a sensor module 150, a display screen 160, an antenna 1, The wireless communication module 170, and the audio module 180, etc.
  • the sensor module 150 may include an acceleration sensor 150A, a gyroscope sensor 150B, and the like.
  • the audio module 180 may include a speaker 180A, a receiver 180B, a microphone 180C, and the like.
  • the structures illustrated in the embodiments of the present invention do not constitute a specific limitation on the wearable device 100 .
  • the wearable device 100 may include more or less components than shown, or combine some components, or separate some components, or arrange different components.
  • the illustrated components may be implemented in hardware, software, or a combination of software and hardware.
  • the processor 110 may include one or more processing units, for example, the processor 110 may include an application processor (application processor, AP), a modem processor, a graphics processor (graphics processing unit, GPU), an image signal processor (image signal processor, ISP), controller, video codec, digital signal processor (digital signal processor, DSP), baseband processor, and/or neural-network processing unit (neural-network processing unit, NPU), etc. Wherein, different processing units may be independent devices, or may be integrated in one or more processors.
  • application processor application processor, AP
  • modem processor graphics processor
  • ISP image signal processor
  • controller video codec
  • digital signal processor digital signal processor
  • baseband processor baseband processor
  • neural-network processing unit neural-network processing unit
  • the controller can generate an operation control signal according to the instruction operation code and timing signal, and complete the control of fetching and executing instructions.
  • a memory may also be provided in the processor 110 for storing instructions and data.
  • the memory in processor 110 is cache memory. This memory may hold instructions or data that have just been used or recycled by the processor 110 . If the processor 110 needs to use the instruction or data again, it can be called directly from the memory. Repeated accesses are avoided and the latency of the processor 110 is reduced, thereby increasing the efficiency of the system.
  • the processor 110 may include one or more interfaces.
  • the interface may include an integrated circuit (inter-integrated circuit, I2C) interface, an integrated circuit built-in audio (inter-integrated circuit sound, I2S) interface, a pulse code modulation (pulse code modulation, PCM) interface, a universal asynchronous transceiver (universal asynchronous transmitter) receiver/transmitter, UART) interface, mobile industry processor interface (MIPI), general-purpose input/output (GPIO) interface, subscriber identity module (SIM) interface, and / or universal serial bus (universal serial bus, USB) interface, etc.
  • I2C integrated circuit
  • I2S integrated circuit built-in audio
  • PCM pulse code modulation
  • PCM pulse code modulation
  • UART universal asynchronous transceiver
  • MIPI mobile industry processor interface
  • GPIO general-purpose input/output
  • SIM subscriber identity module
  • USB universal serial bus
  • the interface connection relationship between the modules illustrated in the embodiment of the present invention is only a schematic illustration, and does not constitute a structural limitation of the wearable device 100 .
  • the wearable device 100 may also adopt different interface connection manners in the foregoing embodiments, or a combination of multiple interface connection manners.
  • Memory 120 may be used to store computer-executable program code, which includes instructions.
  • the memory 120 may include a stored program area and a stored data area.
  • the storage program area can store an operating system, an application program required for at least one function (such as a sound playback function, an image playback function, etc.), and the like.
  • the storage data area can store data (such as audio data, phone book, etc.) created during the use of the wearable device 100 and the like.
  • the memory 120 may include high-speed random access memory, and may also include non-volatile memory, such as at least one magnetic disk storage device, flash memory device, universal flash storage (UFS), and the like.
  • the processor 110 executes various functional applications and data processing of the wearable device 100 by executing the instructions stored in the memory 120 and/or the instructions stored in the memory provided in the processor.
  • the charging management module 140 is used to receive charging input from the charger.
  • the charger may be a wireless charger or a wired charger.
  • the charging management module 140 may receive charging input from the wired charger through the USB interface 130 .
  • the charging management module 140 may receive wireless charging input through the wireless charging coil of the wearable device 100 . While the charging management module 140 charges the battery 142 , it can also supply power to the wearable device through the power management module 141 .
  • the power management module 141 is used for connecting the battery 142 , the charging management module 140 and the processor 110 .
  • the power management module 141 receives input from the battery 142 and/or the charging management module 140, and supplies power to the processor 110, the memory 120, the display screen 160, the wireless communication module 170, and the like.
  • the power management module 141 can also be used to monitor parameters such as battery capacity, battery cycle times, battery health status (leakage, impedance).
  • the power management module 141 may also be provided in the processor 110 .
  • the power management module 141 and the charging management module 140 may also be provided in the same device.
  • the acceleration sensor 150A can detect the magnitude of the acceleration of the wearable device 100 in various directions (generally three axes).
  • the magnitude and direction of gravity can be detected when the wearable device 100 is stationary. It can also be used to identify the posture of wearable devices, and can be used in applications such as horizontal and vertical screen switching, pedometers, etc.
  • the gyro sensor 150B may be used to determine the motion posture of the wearable device 100 .
  • the angular velocity of the wearable device 100 about three axes ie, the x, y and z axes
  • the gyro sensor 150B can be used for image stabilization.
  • the gyroscope sensor 150B detects the shaking angle of the wearable device 100, calculates the distance to be compensated by the lens module according to the angle, and allows the lens to offset the shaking of the wearable device 100 through reverse motion to achieve anti-shake.
  • the gyro sensor 150B can also be used for navigation and somatosensory game scenarios.
  • the wireless communication function of the wearable device 100 may be implemented by the antenna 1 , the wireless communication module 170 , the modem processor, the baseband processor, and the like.
  • the antenna 1 is used to transmit and receive electromagnetic wave signals.
  • Each antenna in wearable device 100 may be used to cover a single or multiple communication frequency bands. Different antennas can also be reused to improve antenna utilization. In other embodiments, the antenna may be used in conjunction with a tuning switch.
  • the wearable device 100 implements a display function through a GPU, a display screen 160, an application processor, and the like.
  • the GPU is a microprocessor for image processing, and is connected to the display screen 160 and the application processor.
  • the GPU is used to perform mathematical and geometric calculations for graphics rendering.
  • Processor 110 may include one or more GPUs that execute program instructions to generate or alter display information.
  • the display screen 160 is used to display images, videos, and the like.
  • the display screen 160 includes a display panel.
  • the display panel can be a liquid crystal display (LCD), an organic light-emitting diode (OLED), an active-matrix organic light-emitting diode or an active-matrix organic light-emitting diode (active-matrix organic light).
  • LED organic light-emitting diode
  • AMOLED organic light-emitting diode
  • FLED flexible light-emitting diode
  • Miniled MicroLed, Micro-oLed, quantum dot light-emitting diode (quantum dot light emitting diodes, QLED) and so on.
  • the wearable device 100 may include 1 or N display screens 160 , where N is a positive integer greater than 1.
  • the wireless communication module 170 can provide applications on the wearable device 100 including wireless local area networks (WLAN) (such as wireless fidelity (Wi-Fi) networks), bluetooth (BT), global navigation satellites Wireless communication solutions such as global navigation satellite system (GNSS), frequency modulation (FM), near field communication (NFC), and infrared technology (IR).
  • WLAN wireless local area networks
  • BT Bluetooth
  • GNSS global navigation satellite system
  • FM frequency modulation
  • NFC near field communication
  • IR infrared technology
  • the wireless communication module 170 may be one or more devices integrating at least one communication processing module.
  • the wireless communication module 170 receives electromagnetic waves via the antenna 1 , frequency modulates and filters the electromagnetic wave signals, and sends the processed signals to the processor 110 .
  • the wireless communication module 170 can also receive the signal to be sent from the processor 110 , perform frequency modulation on the signal, amplify the signal, and then convert it into an electromagnetic wave for radiation through the antenna 1 .
  • the audio module 180 is used for converting digital audio information into analog audio signal output, and also for converting analog audio input into digital audio signal. Audio module 180 may also be used to encode and decode audio signals. In some embodiments, the audio module 180 may be provided in the processor 110 , or some functional modules of the audio module 180 may be provided in the processor 110 .
  • Speaker 180A also referred to as “speaker” is used to convert audio electrical signals into sound signals.
  • the wearable device 100 can listen to music through the speaker 180A, or listen to a hands-free call.
  • the receiver 180B also called “earpiece” is used to convert audio electrical signals into sound signals.
  • the wearable device 100 answers a call or a voice message, the voice can be answered by placing the receiver 180B close to the human ear.
  • the microphone 180C also called “microphone” or “microphone” is used to convert sound signals into electrical signals.
  • the user can make a sound by approaching the microphone 180C through the human mouth, and input the sound signal into the microphone 180C.
  • the electronic device 300 may be provided with at least one microphone 180C.
  • the wearable device 100 may be provided with two microphones 180C, which can implement a noise reduction function in addition to collecting sound signals.
  • the wearable device 100 may further be provided with three, four or more microphones 180C to collect sound signals, reduce noise, identify sound sources, and implement directional recording functions.
  • the wearable device 100 may also include other functional units, which are not limited in this embodiment of the present application.
  • the following takes the architecture shown in FIG. 1 as an example to describe the method for detecting the tightness of the wearing of the wearable device provided by the embodiment of the present application.
  • Each unit in the following embodiments may have the components shown in FIG. 1 , which will not be repeated.
  • the name of the message or the name of the parameter in the message interacted with each other is just an example, and other names may also be used in the specific implementation.
  • Generate in the embodiments of the present application can also be understood as creating or determining, and “including” in the embodiments of the present application can also be understood as “carrying”, which is uniformly described here, and the embodiments of the present application do not make any reference to this. Specific restrictions.
  • the method for tightening the wearing of the wearable device may have one or more execution bodies.
  • execution bodies For different execution subjects, here is a detailed description:
  • the executing body of the method for detecting the wearing tightness of the wearable device may be the wearable device.
  • FIG. 2 is a schematic flowchart of a method for detecting the tightness of a wearable device provided by an embodiment of the present application.
  • the execution subject of the method may be the wearable device, and the method may include:
  • the wearable device collects motion data of the user.
  • the wearing state of the wearable device may refer to: the wearable device may be worn on the user's arm or wrist, or the wearable device may also be worn on the user's ankle or running shoes. Specifically, the wearable device is worn on the user's running shoes. Specifically, the wearable device may be connected to the running shoe through a buckle, and of course, may also be connected in other fitting manners, which are not specifically limited in the embodiments of the present application. Wherein, the wearable device may be worn on the upper, upper or shoelace of the running shoe, specifically, the wearable device is worn on the shoelace of the user. It can be seen that the method for detecting the tightness of wearing of the wearable device provided by the embodiments of the present application adds a tightness detection solution in the scenario of wearing running shoes.
  • the wearable device collects the motion data of the user, which can be implemented in the following manner: Manner 1, the acceleration of the first body part collected by the acceleration sensor on the wearable device. In a second manner, a gyro sensor on the wearable device collects the angular velocity of the first body part. Manner 3: The acceleration sensor on the wearable device collects the acceleration of the first body part, and the gyro sensor on the wearable device collects the angular velocity of the first body part.
  • the first body part is related to the movement of the user.
  • FIG. 3 is a schematic diagram of an application scenario of a method for detecting wearing tightness of a wearable device provided by an embodiment of the present application.
  • the first body part may be the foot of the human body.
  • the acceleration sensor on the wearable device collects the acceleration of the user's foot
  • the gyro sensor on the wearable device collects the angular velocity of the user's foot.
  • Example 2 taking the movement of the user as an arm swinging movement as an example, correspondingly, the first body part may be an arm of a human body. Then, during the arm swing movement of the user, the acceleration sensor on the wearable device collects the acceleration of the user's arm, and/or the gyro sensor on the wearable device collects the angular velocity of the user's arm.
  • the wearable device identifies the motion data of the first motion in the motion data of the user.
  • the first action is a certain action during the user's movement.
  • the first action corresponds to the position where the wearable device is worn.
  • the first action may include an arm swing action and the like.
  • the first motion may include a jumping motion, a kicking motion, and the like.
  • the first action may include any action that the human body can perform, which is not specifically limited in the embodiment of the present application.
  • the first action may include at least one action node.
  • the action node can be understood as a node where a certain body part of the user changes when the user performs an action.
  • the action node may include two action nodes, such as the foot off the ground and the foot on the ground.
  • the action nodes may include action nodes such as a designated position of the arm swinging on the front side of the body and a designated position of the arm swinging on the back side of the body.
  • the wearable device identifies the motion data of the first action in the user's motion data, which can be specifically implemented as follows: the wearable device determines the pre-stored motions and their corresponding standard data according to the collected real-time motion data during the user's motion, and the corresponding standard data. Action data for the first action. That is to say, the wearable device compares the collected motion data with the standard data of each action, and determines the first motion data similar to the standard data of the first action from the collected motion data. The wearable device determines the action corresponding to the first motion data as the first motion, and determines the first motion data as motion data of the first motion.
  • the wearable device compares the collected motion data with the standard data of each action, determines the standard data of the first action that is close to the first motion data, and the wearable device determines the first action as the action corresponding to the first motion data.
  • the first motion data is the motion data of the first action.
  • the wearable device determines the wearing tightness of the wearable device corresponding to the motion data of the first action.
  • S203 can be specifically implemented in the following manner:
  • the wearable device determines the wearing tightness of the wearable device according to the motion data of the first action and the corresponding relationship between the preset motion data and the wearing tightness. In other words, the wearable device determines the wearing tightness of the wearable device according to the action data of the first action and the corresponding relationship between the standard data of the first action and the wearing tightness stored in the standard database.
  • the corresponding relationship between the preset exercise data and the wearing tightness can be understood as: first, a corresponding relationship between the exercise data and the wearing tightness, that is, the value of the exercise data corresponds to the wearing tightness one-to-one.
  • the acceleration value is 30 m/s 2 , which corresponds to the wearing tightness being normal wearing.
  • the second is the correspondence between a set of exercise data and the wearing tightness, that is, the numerical interval of the exercise data corresponds to the wearing tightness.
  • the value interval of the acceleration is 30-50 m/s 2 , which corresponds to the wearing tightness being normal wearing.
  • the wearable device may determine the action data of each action node according to the action data of the first action. Exemplary:
  • the wearable device identifies the action data of the first action node in the action data of the first action.
  • the first action node may be determined according to at least one of a sudden change of motion data, an acceleration direction and an angular velocity direction.
  • the wearable device determines the action waveform formed by the action data of the first body part in the process of the user performing the first action.
  • the wearable device determines the action data of the first action node according to the action waveform.
  • the wearable device determines the characteristic data corresponding to the first action node according to the action data of each action node, which can be implemented as follows:
  • the wearable device determines the first feature data corresponding to the first action node according to the action data of the first action node.
  • the first characteristic data may include, but is not limited to, at least one of the following: the number of peaks of the acceleration waveform or the angular velocity waveform, the number of troughs of the acceleration waveform or the angular velocity waveform, the peak value of the acceleration waveform or the angular velocity waveform, the average value of the angular velocity or the angular velocity, the acceleration waveform or characteristic data such as the gradient of the angular velocity waveform.
  • the first feature data may also include other feature data, which is not specifically limited in this embodiment of the present application.
  • S2032 may be specifically implemented as: the wearable device determines an action waveform formed by the action data of the first body part in the process of the user performing the first action.
  • the wearable device determines, according to the action waveform, the triggering moment of the first action node and the first characteristic data corresponding to the first preset time within which the triggering moment is located.
  • the first preset time may refer to a period of time, and the length of the period of time is set according to the actual situation, which is not specifically limited in this embodiment of the present application.
  • the first action node of the first action may be that the user's foot leaves the ground or the user's foot touches the ground.
  • the wearable device determines the acceleration waveform formed by the acceleration data of the user's foot in the process of taking off.
  • the wearable device determines, according to the acceleration waveform, that the moment when the acceleration is greater than the preset acceleration is the first moment when the foot leaves the ground, and determines the acceleration data corresponding to the first preset time within the first moment.
  • the wearable device calculates the first characteristic data within the first preset time according to the acceleration data corresponding to the first preset time at the first moment.
  • the wearable device determines the wearing tightness of the wearable device according to the first feature data corresponding to the first action node and the preset correspondence between the motion data and the wearing tightness.
  • the wearable device determines the wearing tightness of the wearable device according to the correspondence between the motion data stored in the standard database (for example, the standard data of the first action node) and the wearing tightness, and the first characteristic data corresponding to the first action node. Spend.
  • the standard data in the standard database may be pushed by the cloud server, or downloaded by the wearable device, or pre-stored in the wearable device.
  • the standard data may be action data corresponding to the first action performed by an ordinary person, or may be historical data of a user wearing the device. Specifically, the standard data can be screened according to parameters such as the user's gender, height, and weight.
  • the standard data in the standard database may specifically be: standard data of the first action node in the process of the user performing the first action when the wearable device is in different wearing tightnesses.
  • the types of the standard data may include but are not limited to at least one of the following: the number of peaks of the acceleration waveform, the number of peaks of the angular velocity waveform, the number of valleys of the acceleration waveform, the number of valleys of the angular velocity waveform, the peak value of the acceleration waveform, the peak value of the angular velocity waveform , the mean value of acceleration, the mean value of angular velocity, the gradient of acceleration waveform, the gradient of angular velocity waveform and other data.
  • the first action node of the first action may be that the user's foot leaves the ground or the user's foot touches the ground.
  • the action data is the acceleration of the user's foot
  • the first action node is the user's foot leaving the ground
  • the standard data is the number of peaks to illustrate:
  • S2033 can be specifically implemented as follows: the wearable device according to the number of peaks corresponding to the first preset time at the trigger moment, and the pre-stored number of peaks when the wearable device is in different wearing tightness, the user's foot leaves during the jumping action.
  • the number of standard wave crests on the ground determines the tightness of the wearable device.
  • the wearable device can determine the wearing tightness of the wearable device according to the user's motion data, and can detect the wearing tightness of the wearable device without an additional hardware device to drive the action of the wearable device, thereby effectively avoiding the problem of inaccurate motion data collection. , which makes the collection of motion data more reliable and lays the foundation for providing users with more professional guidance.
  • the wearable device determines the wearing tightness of the wearable device corresponding to the motion data of the first action according to the motion data of the first action and the wearing tightness model. Among them, the motion data of the first action is used as the input of the wearing tightness model, and the wearing tightness of the wearable device is used as the output of the wearing tightness model.
  • the wearing tightness model is obtained based on the exercise data and the wearing tightness training.
  • the specific implementation method of the model training is as follows There are no specific restrictions on the application.
  • the method for detecting the wearing tightness of the wearable device may further include: S204 , the wearable device generates prompt information according to the wearing tightness to prompt the user the detection result of the wearing tightness of the wearable device.
  • the wearing tightness of the wearable device can be understood as the wearing tightness of the wearable device, and can also be understood as a specific value.
  • the wearing tightness of the wearable device may include normal wearing of the wearable device, loose wearing of the wearable device, and tight wearing of the wearable device.
  • S204 can be specifically implemented as: when the wearing tightness of the wearable device is greater than the threshold, the wearable device determines that the wearable device is tight, and passes the detection result of the wearing tightness through the first prompt message prompt to the user. When the wearing tightness of the wearable device is equal to or close to the threshold, the wearable device determines that the wearable device is properly worn, and prompts the user with the detection result of the normal wearing through the second prompt information. When the wearing tightness of the wearable device is less than the threshold, the wearable device determines that the wearable device is loosely worn, and prompts the user with the detection result of the wearing looseness through third prompt information.
  • the first prompt information, the second prompt information and the third prompt information may all prompt the user in different presentation forms.
  • the first prompt information, the second prompt information and the third prompt information can all be displayed to the user through a user interface (UI), or the user can be prompted by the LED lights emitting lights of different colors, or the intensity of the vibration can be used to prompt the user. and/or different vibration times to prompt the user, or prompt the user by means of sound.
  • UI user interface
  • the user may also be prompted by a combination of different presentation forms, which is not specifically limited in this embodiment of the present application.
  • FIG. 4 is a schematic diagram of an application scenario of a method for detecting wearing tightness of a wearable device provided by an embodiment of the present application.
  • the wearable device displays the generated second prompt information through the user interface (for example, the user interface UI displays “normally worn”), and the wearable device vibrates once to remind the user The wearable device is worn normally.
  • the wearable device When it is detected that the wearable device is loosely worn, the wearable device displays the generated third prompt information through the user interface (eg, "loosely worn” is displayed on the user interface UI), and the wearable device vibrates twice to prompt the user that the wearable device is loosely worn.
  • the number of vibrations of the wearable device can be arbitrarily set, which is not specifically limited in the embodiment of the present application.
  • the user interface UI can be prompted by a combined presentation form of text, vibration and sound. For example, when it is detected that the wearable device is properly worn, the wearable device displays the generated second prompt information through the user interface (for example, the user interface UI displays "normally worn"), and the wearable device vibrates once, and at the same time the wearable device sends out the first type of prompt information. Prompt sound to remind the user that the wearable device is properly worn.
  • FIG. 5 is a schematic diagram of an application scenario of a method for detecting tightness of wearing of a wearable device provided by an embodiment of the present application.
  • the wearable device displays the generated third prompt information through the user interface (for example, "loosely worn” is displayed on the user interface UI), and the wearable device vibrates twice, while wearing The device emits a second tone to remind the user to wear the device loosely.
  • the number of vibrations of the wearable device can be arbitrarily set, and the selection of the prompt sound under different detection results can also be arbitrarily set, which is not specifically limited in this embodiment of the present application.
  • FIG. 6a is a schematic diagram of an application scenario of a method for detecting tightness of wearing of a wearable device provided by an embodiment of the present application.
  • the wearable device displays the generated second prompt information through the user interface (for example, the user interface UI displays "normally worn"), and the LED light set on the wearable device emits The first prompt light is used to prompt the user that the wearable device is properly worn.
  • FIG. 6b is a schematic diagram of an application scenario of a method for detecting tightness of wearing of a wearable device provided by an embodiment of the present application.
  • the wearable device displays the generated third prompt information through the user interface (for example, the user interface UI displays "Loose Wearing"), and the LED light set on the wearable device emits
  • the second type of prompt light is to prompt the user to wear the device loosely.
  • the first prompt light may be green light
  • the second prompt light may be red light.
  • the LED lights provided on the wearable device can be arranged but not limited to the periphery of the screen of the wearable device. In this way, the user wearing the wearable device is in a dark place, and the user wearing the wearable device can remind other users to effectively prevent the risk of being accidentally bumped.
  • the presentation form of the sound may specifically be: the presentation form of the voice broadcast. That is to say, the detection result of the tightness of the wearable device can also be displayed in the form of voice broadcast.
  • the phenomenon that the user's wearable device is easy to fall off and lose during the user's exercise can be effectively avoided, and at the same time, the user's wear and tear during the exercise can be avoided. Risk of collision and accidental collision.
  • the wearable device can evaluate the exercise energy of the user's exercise according to the user's exercise data. For example, when the user is running, the wearable device can evaluate the user's running based on exercise data such as the user's running distance, running speed, and running duration. movement energy. When the wearable device is loosely worn, the user's running distance, running speed, running time and other exercise data collected by the wearable device are inaccurate, which will affect the accuracy of the wearable device's assessment of the user's exercise energy based on the collected user's exercise data. In order to make the motion energy of the user's motion output by the wearable device in any state, the accuracy is high. As shown in FIG. 2 , a method for detecting the tightness of a wearable device provided by an embodiment of the present application further includes:
  • the wearable device determines the wearing tightness of the wearable device at each moment in the first duration.
  • the wearable device determines the wearing tightness of the wearable device at each moment within the second preset time (ie, the first duration).
  • the wearable device determines a second duration of loose wearing of the wearable device according to the wearing tightness of the wearable device at each moment in the first duration.
  • the second duration may refer to a continuous duration, or may refer to the sum of multiple non-consecutive durations.
  • the wearable device records the loose wearing time of the wearable device according to the wearing tightness of the wearable device at each moment within the second preset time period and issues a reminder alarm.
  • the reminder alarm is used to remind the user that the wearable device is loose.
  • the reminder alarm may include an alarm bell alarm or a warning light alarm, and the like.
  • other forms of reminder alarms may also be included, which are not specifically limited in this embodiment of the present application.
  • the wearable device calculates the second exercise energy of the user within the first duration according to the first duration and the second duration, and the first exercise energy calculated by the wearable device.
  • the first exercise energy is calculated when the wearing state of the wearable device is normal or tight within the first period of time.
  • S207 can be specifically implemented as follows: the wearable device calculates the second period of loose wearing of the wearable device according to the loose wearing time of the wearable device, and then determines the proportion of the loose wearing time according to the ratio of the second period of loose wearing to the first period of time. The wearable device determines the second exercise energy of the user within the second preset time according to the proportion of time when the wearable device is loosely worn and the first exercise energy calculated by the wearable device.
  • the wearable device may determine the wearing tightness of the wearable device in real time during the running process of the user for the second preset time (that is, the above-mentioned first duration).
  • the wearable device evaluates the exercise energy according to the exercise data of the user collected at the second preset time.
  • the wearable device calculates the compensation movement energy according to the proportion of time when the wear is loose and the wearable device according to the movement energy (that is, the first movement energy) evaluated by the user during the running process for the second preset time, and the compensation movement energy can be Multiply the estimated exercise energy by the percentage of time when the wearing is loose.
  • the wearable device can determine the actual running energy of the user during the running process for the second preset time (that is, the above-mentioned second exercise energy), and the actual running energy can be the difference between the estimated running energy and the compensated running energy .
  • the wearable device may evaluate the exercise energy of the user at the second preset time.
  • the wearable device can determine the actual exercise energy of the user's exercise at the second preset time according to the time proportion of the loose wearing time and the estimated exercise energy, so that the user's exercise data is more credible. In order to remind the user to pay attention to adjusting the wearing tightness of the wearable device when running next time.
  • FIG. 7 is a schematic flowchart of a method for detecting tightness of wearing of a wearable device in an application scenario provided by an embodiment of the present application.
  • the method includes: S701, a user wears a wearable device on a shoelace of a running shoe. S702, the user performs the wearing tightness detection of the wearable device through a warm-up action before running (such as jumping in place). S703.
  • the wearable device collects the user's motion data through an acceleration sensor and/or a gyroscope sensor.
  • the wearable device identifies the motion data of the take-off action in the collected motion data, and determines the characteristic data of the foot leaving the ground and the foot touching the ground in the take-off action.
  • the take-off action is the above-mentioned first action
  • the feet leaving the ground and the feet touching the ground are the above-mentioned action nodes
  • S704 may specifically be that the wearable device determines that the user is performing the take-off action.
  • acceleration waveform The wearable device determines, according to the acceleration waveform, that the moment when the acceleration is greater than the preset acceleration is the first moment when the foot leaves the ground, and determines the acceleration data corresponding to the first preset time within the first moment.
  • the wearable device calculates feature data within the first preset time according to the acceleration data corresponding to the first preset time at the first moment, and the feature data may include but not be limited to at least one of the following: the number of peaks, Characteristic data such as trough number, peak value, acceleration mean value, and acceleration waveform gradient.
  • the wearable device stores the correspondence between the standard data of the first action node (such as the foot leaves the ground and the foot contacts the ground) and the wearing tightness stored in the standard database, and the characteristic data corresponding to the foot leaving the ground and the foot contact The characteristic data corresponding to the ground determines the tightness of the wearable device.
  • the wearable device determines whether the wearable device is loosely worn according to the relationship between the wearing tightness and the threshold.
  • the wearable device determines that the wearable device is loosely worn.
  • the wearable device determines that the wearable device is normally worn.
  • the wearable device determines that the wearable device is tight. If the wearable device determines that the wearing is not loose, the end process is performed; if the wearable device determines that the wearing is loose, S707 is performed. S707, the wearable device generates prompt information to prompt the user to adjust.
  • FIG. 8 is a schematic flowchart of a method for detecting tightness of wearing of a wearable device in an application scenario provided by an embodiment of the present application.
  • the method includes: S801 , the wearable device collects motion data of a user running for a second preset time (that is, the above-mentioned first time duration).
  • S802 The wearable device determines the wearing tightness at each moment within the second preset time according to the collected motion data of the user running for the second preset time.
  • S803 the wearable device determines whether the wearable device is loosely worn according to the relationship between the wearing tightness and the threshold. If not, execute the end process. If yes, execute S804.
  • S804 the wearable device generates prompt information to prompt the user that the wearable device is loosely worn, and records the time when the wearable device is loosely worn.
  • FIG. 9 is a schematic flowchart of a method for detecting tightness of wearing of a wearable device in an application scenario provided by an embodiment of the present application.
  • the method includes: S901 , the wearable device evaluates the exercise energy according to the collected exercise data of the user during the running process. S902, the wearable device determines whether the wearable device is loosely worn during the user's running. If the wearable device determines that the wearable device is loosely worn during the user's running, S903 is executed; if the wearable device determines that the wearable device is not loosely worn during the user's running, S904 is executed. S903.
  • the wearable device determines the loose wearing time within the second preset time, and determines the loose wearing time proportion according to the ratio of the loose wearing time to the second preset time.
  • the wearable device calculates the compensation movement energy according to the proportion of time when the wear is loose and the wearable device according to the movement energy (that is, the first movement energy) evaluated by the user during the running process for the second preset time, and the compensation movement energy can be Multiply the estimated exercise energy by the percentage of time when the wearing is loose.
  • the wearable device determines the actual running energy (that is, the above-mentioned second exercise energy) of the user during the running process for the second preset time, and the actual running energy may be the difference between the estimated running energy and the compensated running energy. S904, the wearable device determines that the exercise energy evaluated by the wearable device is the actual exercise energy.
  • the executors of the method for detecting the wearing tightness of the wearable device may include a wearable device and a non-wearable device.
  • the cooperation between the wearable device and the non-wearable device can be implemented in multiple ways. Specifically, it can be described as follows:
  • FIG. 10 is a schematic flowchart of a method for detecting the tightness of a wearable device provided by an embodiment of the present application.
  • the method may include: 1. When it is detected that the wearable device is in a wearing state, the wearable device collects User's exercise data. 2 The wearable device identifies the motion data of the first action in the collected motion data, and determines the first feature data corresponding to the first action node of the user's first action. Specifically, the wearable device identifies the motion data of the first action in the collected motion data of the user, and determines the motion waveform formed by the motion data of the first body part in the process of the user performing the first motion.
  • the wearable device determines, according to the action waveform, the trigger moment of the first action node, and the corresponding first feature data within the first preset time at the trigger moment.
  • the wearable device determines the wearing tightness of the wearable device according to the correspondence between the standard data of the first action node and the wearing tightness stored in the standard database, and the first characteristic data corresponding to the first action node.
  • the wearable device sends the detection result corresponding to the wearing tightness to the non-wearable device.
  • the wearable device can send the detection result corresponding to the wearing tightness to the non-wearable device through Bluetooth.
  • other transmission modes may also be used, which are not specifically limited in the embodiments of the present application.
  • the non-wearable device receives the detection result of the wearing tightness of the wearable device sent by the wearable device, and prompts the detection result to the user in different ways. details as follows:
  • the non-wearable device can be a watch or a wristband
  • the watch or the wristband receives the detection result of the wearing tightness of the wearable device sent by the wearable device, and generates prompt information according to the detection result
  • the prompt information can be On the user interface UI, it may be presented by text, and/or prompted by a presentation form of vibration.
  • the watch or the bracelet when it is detected that the wearable device is worn normally, the watch or the bracelet will display the generated prompt information through the user interface (for example, the user interface UI displays "normally worn"), and the watch or the bracelet Vibrate once to remind the user that the wearable device is properly worn.
  • the watch or bracelet When it is detected that the wearable device is loosely worn, the watch or bracelet will display the generated prompt information through the user interface (for example, "loosely worn” is displayed on the user interface UI), and the wearable device vibrates twice to remind the user that the wearable device is loosely worn.
  • the number of vibrations of the wearable device can be arbitrarily set, which is not specifically limited in the embodiment of the present application.
  • the non-wearable device can be an earphone
  • the earphone receives the detection result of the wearing tightness of the wearable device sent by the wearable device, and generates prompt information according to the detection result, and the prompt information can be prompted in the form of voice.
  • the non-wearable device can be a mobile phone
  • the mobile phone receives the detection result of the wearing tightness of the wearable device sent by the wearable device, and generates prompt information according to the detection result.
  • the prompt information can be presented in text on the user interface UI. And/or, prompting via vibration/LED light presentation.
  • the mobile phone when it is detected that the wearable device is worn normally, the mobile phone will display the generated prompt information through the user interface (for example, the user interface UI displays "normal wearing"), and the LED light set on the mobile phone will emit light.
  • the first prompt light is used to prompt the user that the wearable device is properly worn.
  • the mobile phone when it is detected that the wearable device is loosely worn, the mobile phone will display the generated prompt information through the user interface (for example, "loose wearing” is displayed on the user interface UI), and the LED light set on the mobile phone will issue a second prompt light to prompt the user to wear the device loosely.
  • the first prompt light may be green light
  • the second prompt light may be red light. What needs to be added here is that, of course, the prompt method on the mobile phone can also be a prompt on the bright screen of the mobile phone.
  • the presentation form of the sound may specifically be: the presentation form of the voice broadcast. That is to say, the mobile phone can display the detection result of the wearing tightness of the wearable device in the form of voice broadcast.
  • FIG. 11 is a schematic flowchart of a method for detecting the tightness of a wearable device provided by an embodiment of the present application.
  • the method may include: (1) When it is detected that the wearable device is in a wearing state, the wearable device collects the movement of the user data. 2The wearable device is sending exercise data to the non-wearable device. Specifically, the wearable device can send the motion data to the non-wearable device through Bluetooth. Of course, other transmission modes may also be used, which are not specifically limited in the embodiments of the present application.
  • the non-wearable device receives the user's motion data sent by the wearable device, identifies the motion data of the first action in the motion data, and determines the first feature data corresponding to the first action node of the user's first action. Specifically, the non-wearable device determines, according to the user's action data, an action waveform formed by the action data of the first body part in the process of the user performing the first action. The non-wearable device determines, according to the action waveform, the trigger moment of the first action node, and the first feature data corresponding to the first preset time at the trigger moment. The non-wearable device determines the wearing tightness of the wearable device according to the correspondence between the standard data of the first action node and the wearing tightness stored in the standard database, and the first characteristic data corresponding to the first action node.
  • the non-wearable device has different prompting methods for prompting the user of the detection result of the wearing tightness of the wearable device. details as follows:
  • the non-wearable device can be a watch or a wristband
  • the watch or the wristband generates prompt information according to the wearing tightness of the wearable device, and the prompt information can be presented by text on the user interface UI, and/or, Prompt through the presentation of vibrations.
  • the watch or the bracelet when it is detected that the wearable device is worn normally, the watch or the bracelet will display the generated prompt information through the user interface (for example, the user interface UI displays "normally worn"), and the watch or the bracelet Vibrate once to remind the user that the wearable device is properly worn.
  • the watch or bracelet When it is detected that the wearable device is loosely worn, the watch or bracelet will display the generated prompt information through the user interface (for example, "loosely worn” is displayed on the user interface UI), and the wearable device vibrates twice to remind the user that the wearable device is loosely worn.
  • the number of vibrations of the wearable device can be arbitrarily set, which is not specifically limited in the embodiment of the present application.
  • the non-wearable device can be an earphone
  • the earphone generates prompt information according to the wearing tightness of the wearable device, and the prompt information can be prompted in the form of voice.
  • the non-wearable device can be a mobile phone
  • the mobile phone will generate prompt information according to the wearing tightness of the wearable device, and the prompt information can be presented in text on the user interface UI, and/or in the form of vibration/LED light. .
  • the mobile phone when it is detected that the wearable device is worn normally, the mobile phone will display the generated prompt information through the user interface (for example, the user interface UI displays "normal wearing"), and the LED light set on the mobile phone will emit light.
  • the first prompt light is used to prompt the user that the wearable device is properly worn.
  • the mobile phone when it is detected that the wearable device is loosely worn, the mobile phone will display the generated prompt information through the user interface (for example, "loose wearing” is displayed on the user interface UI), and the LED light set on the mobile phone will issue a second prompt light to prompt the user to wear the device loosely.
  • the first prompt light may be green light
  • the second prompt light may be red light. What needs to be added here is that, of course, the prompt method on the mobile phone can also be a prompt on the bright screen of the mobile phone.
  • the presentation form of the sound may specifically be: the presentation form of the voice broadcast. That is to say, the mobile phone can display the detection result of the wearing tightness of the wearable device in the form of voice broadcast.
  • the function of detecting the wearing tightness and prompting of the wearable device is extended to multiple devices, and the cooperative operation between the multiple devices not only solves the problem of the user's wearing tightness, but also increases the user's experience of linking multiple devices.
  • FIG. 12 is a device for detecting the tightness of a wearable device provided by an embodiment of the present application, and the device 1200 may include:
  • the collection unit 1201 is configured to collect the motion data of the user when it is detected that the wearable device is in the wearing state;
  • the identification unit 1202 is used to identify the motion data of the first action in the motion data of the user;
  • the first determining unit 1203 is configured to determine the wearing tightness of the wearable device corresponding to the motion data of the first action.
  • the first determining unit 1203 is further configured to:
  • the wearing tightness of the wearable device is determined.
  • the first determining unit 1203 is further configured to:
  • the action data of the first action node determine the first feature data corresponding to the first action node
  • the wearing tightness of the wearable device is determined according to the first characteristic data and the corresponding relationship between the preset motion data and the wearing tightness.
  • the first characteristic data includes: the number of peaks of the acceleration waveform, the number of peaks of the angular velocity waveform, the number of valleys of the acceleration waveform, the number of valleys of the angular velocity waveform, the peak value of the acceleration waveform, the peak value of the angular velocity waveform, the At least one of the mean value, the mean value of the angular velocity, the gradient of the acceleration waveform, and the gradient of the angular velocity waveform.
  • the first determining unit 1203 is further configured to:
  • the wearing tightness model determine the wearing tightness of the wearable device corresponding to the action data of the first action
  • the motion data of the first action is used as the input of the wearing tightness model, and the wearing tightness of the wearable device is taken as the output of the wearing tightness model.
  • the device for detecting the tightness of the wearable device provided by the embodiments of the present application may further include:
  • the generating unit 1204 is configured to generate prompt information according to the wearing tightness of the wearable device, and the prompt information presents the detection result of the wearing tightness of the wearable device in a preset presentation form;
  • the preset presentation form includes one or more combinations of the following: sound presentation form, text presentation form, vibration presentation form and light presentation form.
  • the wearing tightness of the wearable device includes: normal wearing of the wearable device, loose wearing of the wearable device, and tight wearing of the wearable device.
  • the device for detecting the tightness of the wearable device provided by the embodiments of the present application may further include:
  • the second determining unit 1205 is configured to determine the wearing tightness of the wearable device at each moment within the first duration
  • the third determining unit 1206 is configured to determine the second duration of loose wearing of the wearable device according to the wearing tightness of the wearable device at each moment in the first duration;
  • the calculation unit 1207 is configured to calculate the second exercise energy of the user within the first duration according to the first duration and the second duration, and the first exercise energy calculated by the wearable device; wherein, the first exercise energy is within the first duration Calculated when the wearing state of the wearable device is normal or tight.
  • the first action includes a take-off action
  • the first action node includes the foot leaving the ground and/or the foot touching the ground
  • the first action includes an arm swing action, and the first action node includes a designated position where the arm swings on the front side of the body and/or a designated position where the arm swings on the back side of the body.
  • the wearable device is intended to be worn on a user's foot or shoe.
  • the above-mentioned apparatus 1200 may be implemented by code or by circuit.
  • the apparatus may be a complete machine of a terminal device.
  • the acquisition unit 1201 may be an acquisition circuit, and may also be implemented by a sensor (such as the acceleration sensor 150A and/or the gyro sensor 150B as shown in FIG. 1 ).
  • the identifying unit 1202 , the first determining unit 1203 , the generating unit 1204 , the second determining unit 1205 , the third determining unit 1206 and the calculating unit 1207 may be processors (such as the processor 110 shown in FIG. 1 ).
  • Embodiments of the present application further provide a chip system, where the chip system includes at least one processor and at least one interface circuit.
  • the processor and interface circuits may be interconnected by wires.
  • interface circuits may be used to receive signals from other devices, such as memory.
  • an interface circuit may be used to send signals to other devices, such as a processor.
  • the interface circuit may read the instructions stored in the memory and send the instructions to the processor.
  • the electronic device can be made to execute each step executed by the wearable device in the above embodiments.
  • the chip system may also include other discrete devices, which are not specifically limited in this embodiment of the present application.
  • An embodiment of the present application further provides an apparatus, the apparatus is included in an electronic device, and the apparatus has a function of implementing the behavior of the electronic device in any of the methods in the foregoing embodiments.
  • This function can be implemented by hardware or by executing corresponding software by hardware.
  • the hardware or software includes at least one module or unit corresponding to the above-mentioned functions. For example, detecting a module or unit, and determining a module or unit, etc.
  • the embodiments of the present application further provide a computer-readable storage medium, including computer instructions, when the computer instructions are executed on the electronic device, the electronic device is made to execute any of the methods in the foregoing embodiments.
  • Embodiments of the present application further provide a computer program product, which, when the computer program product runs on a computer, causes the computer to execute any of the methods in the foregoing embodiments.
  • the above-mentioned terminal and the like include corresponding hardware structures and/or software modules for executing each function.
  • the embodiments of the present application can be implemented in hardware or a combination of hardware and computer software. Whether a function is performed by hardware or computer software driving hardware depends on the specific application and design constraints of the technical solution. Those skilled in the art may implement the described functionality using different methods for each particular application, but such implementations should not be considered beyond the scope of the embodiments of the present invention.
  • each functional module may be divided corresponding to each function, or two or more functions may be integrated into one processing module.
  • the above-mentioned integrated modules can be implemented in the form of hardware, and can also be implemented in the form of software function modules. It should be noted that, the division of modules in the embodiment of the present invention is schematic, and is only a logical function division, and there may be other division manners in actual implementation.
  • Each functional unit in each of the embodiments of the embodiments of the present application may be integrated into one processing unit, or each unit may exist physically alone, or two or more units may be integrated into one unit.
  • the above-mentioned integrated units may be implemented in the form of hardware, or may be implemented in the form of software functional units.
  • the integrated unit if implemented in the form of a software functional unit and sold or used as an independent product, may be stored in a computer-readable storage medium.
  • a computer-readable storage medium includes several instructions for causing a computer device (which may be a personal computer, a server, or a network device, etc.) or a processor to execute all or part of the steps of the methods described in the various embodiments of the present application.
  • the aforementioned storage medium includes: flash memory, removable hard disk, read-only memory, random access memory, magnetic disk or optical disk and other media that can store program codes.

Landscapes

  • Health & Medical Sciences (AREA)
  • Engineering & Computer Science (AREA)
  • Life Sciences & Earth Sciences (AREA)
  • Physics & Mathematics (AREA)
  • General Health & Medical Sciences (AREA)
  • Biomedical Technology (AREA)
  • Molecular Biology (AREA)
  • Biophysics (AREA)
  • Theoretical Computer Science (AREA)
  • Veterinary Medicine (AREA)
  • Heart & Thoracic Surgery (AREA)
  • Public Health (AREA)
  • Pathology (AREA)
  • Animal Behavior & Ethology (AREA)
  • Surgery (AREA)
  • Medical Informatics (AREA)
  • General Engineering & Computer Science (AREA)
  • Physiology (AREA)
  • General Physics & Mathematics (AREA)
  • Dentistry (AREA)
  • Oral & Maxillofacial Surgery (AREA)
  • Human Computer Interaction (AREA)
  • Data Mining & Analysis (AREA)
  • Software Systems (AREA)
  • Mathematical Physics (AREA)
  • Computing Systems (AREA)
  • Evolutionary Computation (AREA)
  • Computational Linguistics (AREA)
  • Computer Vision & Pattern Recognition (AREA)
  • Psychiatry (AREA)
  • Social Psychology (AREA)
  • Artificial Intelligence (AREA)
  • Multimedia (AREA)
  • User Interface Of Digital Computer (AREA)
  • Measurement Of The Respiration, Hearing Ability, Form, And Blood Characteristics Of Living Organisms (AREA)

Abstract

本申请公开了一种检测穿戴设备佩戴松紧的方法、装置和系统，该方法包括在检测到穿戴设备处于佩戴状态时，采集用户的运动数据。识别用户的运动数据中第一动作的动作数据。确定第一动作的动作数据对应的穿戴设备佩戴松紧度。这样，本申请实施例可以根据用户的运动数据确定穿戴设备佩戴松紧度，进而避免运动数据采集不准确的问题，使得运动数据的采集更加可靠，为用户提供更加专业的指导奠定基础。

Description

一种检测穿戴设备佩戴松紧的方法、装置和系统
本申请要求于2021年03月31日提交中国专利局、申请号为202110347924.9、申请名称为“一种检测穿戴设备佩戴松紧的方法、装置和系统”的中国专利申请的优先权，其全部内容通过引用结合在本申请中。
技术领域
本发明实施例涉及电子设备技术领域，尤其涉及一种检测穿戴设备佩戴松紧的方法、装置和系统。
背景技术
随着技术的发展，穿戴设备普遍应用在人们生活、工作和学习中。例如，穿戴设备可以检测用户的健康状况和用户的运动情况等。当穿戴设备在用户身上佩戴较松时，穿戴设备采集到的数据不准确，会导致穿戴设备对用户的健康状况或运动情况的评估不准确，影响穿戴设备的检测性能。因此，如何检测穿戴设备佩戴松紧是本领域有待解决的技术问题。
发明内容
本申请实施例提供的一种检测穿戴设备佩戴松紧的方法、装置和系统，用于检测穿戴设备佩戴松紧，确保穿戴设备的检测性能。
第一方面，本申请实施例提供的一种检测穿戴设备佩戴松紧的方法，该方法的执行主体可以是电子设备(如穿戴设备)，也可以是位于电子设备中的部件(例如，芯片，芯片系统或处理器等)，下面以执行主体是电子设备为例进行描述。该方法包括：检测到穿戴设备处于佩戴状态时，采集用户的运动数据。识别用户的运动数据中第一动作的动作数据。确定第一动作的动作数据对应的穿戴设备佩戴松紧度。
其中，用户的运动数据可以包括加速度和/或角速度。穿戴设备佩戴松紧度可以理解为松紧程度(如穿戴设备佩戴正常、穿戴设备佩戴松动和穿戴设备佩戴紧等)，也可以理解为具体数值。
其中，该第一动作是用户运动过程中的某一动作。该第一动作与穿戴设备佩戴的位置对应，当穿戴设备佩戴在用户的手臂或手腕上时，第一动作可以包括摆臂动作等。当穿戴设备佩戴在用户的脚腕或跑鞋上时，第一动作可以包括起跳动作，踢腿动作，等等。
这样，本申请实施例可以根据用户的运动数据确定穿戴设备佩戴松紧度，进而可以避免运动数据采集不准确的问题，使得运动数据的采集更加可靠，为用户提供更加专业的指导奠定基础。
一种可能的实现方式中，确定第一动作的动作数据对应的穿戴设备佩戴松紧度，具体可以为：根据第一动作的动作数据，及预设的运动数据与佩戴松紧度的对应关系，确定穿戴设备佩戴松紧度。
其中，预设的运动数据与佩戴松紧度的对应关系，可以理解为：第一种，一个运动数据与佩戴松紧度的对应关系，也就是说，运动数据的数值与佩戴松紧度一一对应。示例性的，以运动数据为加速度为例，加速度值为30m/s 2，其与佩戴松紧度为佩戴正常对应。第二种，一组运动数据与佩戴松紧度的对应关系，也就是说，运动数据的数值区间 与佩戴松紧度对应。示例性的，以运动数据为加速度为例，加速度的数值区间为30-50m/s 2，其与佩戴松紧度为佩戴正常对应。
本申请实施例，穿戴设备根据用户的运动数据即可确定穿戴设备的佩戴松紧，无需额外的硬件装置驱动穿戴设备动作，即可检测穿戴设备佩戴松紧，进而可以有效避免动作数据采集不准确的问题，使得动作数据的采集更加可靠，为用户提供更加专业的指导奠定基础。
一种可能的实现方式中，根据第一动作的动作数据，及预设的运动数据与佩戴松紧度的对应关系，确定穿戴设备佩戴松紧度，具体可以为：识别出第一动作的动作数据中第一动作节点的动作数据。根据第一动作节点的动作数据，确定第一动作节点对应的第一特征数据。根据第一特征数据，及预设的运动数据与佩戴松紧度的对应关系，确定穿戴设备佩戴松紧度。
一种可能的实现方式中，第一特征数据包括：加速度波形的波峰数、角速度波形的波峰数、加速度波形的波谷数、角速度波形的波谷数、加速度波形的峰值、角速度波形的峰值、加速度的均值、角速度的均值、加速度波形的梯度、角速度波形的梯度中的至少一项。
其中，加速度的均值，可以理解为预设时间段内加速度的均值。角速度的均值，可以理解为预设时间段内角速度的均值。加速度波形的梯度，可以理解为加速度波形中的预设位置的切线的斜率。角速度波形的梯度，可以理解为角速度波形中的预设位置的切线的斜率。
一种可能的实现方式中，确定第一动作的动作数据对应的穿戴设备佩戴松紧度，具体可以为：根据第一动作的动作数据，及佩戴松紧模型，确定第一动作的动作数据对应的穿戴设备佩戴松紧度。其中，第一动作的动作数据作为佩戴松紧模型的输入，穿戴设备佩戴松紧度作为佩戴松紧模型的输出。
一种可能的实现方式中，在确定第一动作的动作数据对应的穿戴设备佩戴松紧度之后，本申请实施例提供的一种检测穿戴设备佩戴松紧的方法还可以包括：根据穿戴设备佩戴松紧度，生成提示信息，提示信息采用预设呈现形式呈现穿戴设备佩戴松紧度的检测结果。其中，预设呈现形式包括以下一项或多项组合：声音呈现形式、文字呈现形式、振动呈现形式和灯光呈现形式。
在本申请实施例中，通过采用不同的形式将检测结果提示给用户，可以有效避免在用户运动的过程中用户的穿戴设备佩戴易脱落、丢失的现象，同时，避免用户在运动过程中的被撞、误撞的风险。
一种可能的实现方式中，穿戴设备佩戴松紧度包括：穿戴设备佩戴正常、穿戴设备佩戴松动和穿戴设备佩戴紧。
在一些实施例中，本申请实施例提供的一种检测穿戴设备佩戴松紧的方法还包括：确定在第一时长内各时刻的穿戴设备佩戴松紧度。根据第一时长内各时刻的穿戴设备佩戴松紧度，确定穿戴设备佩戴松动的第二时长。根据第一时长和第二时长，及穿戴设备计算的第一运动能量，计算用户在第一时长内的第二运动能量。其中，第一运动能量是在第一时长内穿戴设备佩戴状态为正常或紧的情况下计算得到的。
其中，第一运动能量和第二运动能量均可以理解为用户的运动能耗。如，用户运动消耗的热量，用户运动消耗的卡路里等。
其中，第二时长可以指连续的时长，也可以指多个非连续时长之和。也就是说，第二时长可以为穿戴设备佩戴松动的一段连续时长，也可以为穿戴设备佩戴松动的多个非连续时长之和。
因此，在本申请实施例中穿戴设备可以评估用户在第二时长的运动能量。在穿戴设备佩戴松的情况下，穿戴设备可以根据佩戴松动的时间占比，及评估的运动能量，确定用户在第二时长的运动的实际运动能量，使得用户的运动数据更可信，以便于提醒用户下次运行时注意调整穿戴设备的佩戴松紧。
一种可能的实现方式中，第一动作包括起跳动作，第一动作节点包括足部离开地面和/或足部接触地面；或者，第一动作包括摆臂动作，第一动作节点包括手臂摆动在身体前侧的指定位置和/或手臂摆动在身体后侧的指定位置。
一种可能的实现方式中，穿戴设备用于佩戴在用户的足部或鞋上。
第二方面，本申请实施例提供的一种检测穿戴设备佩戴松紧的装置，该装置包括：采集单元，用于检测到穿戴设备处于佩戴状态时，采集用户的运动数据。识别单元，用于识别用户的运动数据中第一动作的动作数据。第一确定单元，用于确定第一动作的动作数据对应的穿戴设备佩戴松紧度。这样，本申请实施例可以根据用户的运动数据确定穿戴设备佩戴松紧度，进而可以避免运动数据采集不准确的问题，使得运动数据的采集更加可靠，为用户提供更加专业的指导奠定基础。
一种可能的实现方式中，第一确定单元还用于：根据第一动作的动作数据，及预设的运动数据与佩戴松紧度的对应关系，确定穿戴设备佩戴松紧度。
一种可能的实现方式中，第一确定单元还用于：识别出第一动作的动作数据中第一动作节点的动作数据。根据第一动作节点的动作数据，确定第一动作节点对应的第一特征数据。根据第一特征数据，及预设的运动数据与佩戴松紧度的对应关系，确定穿戴设备佩戴松紧度。
一种可能的实现方式中，第一特征数据包括：加速度波形的波峰数、角速度波形的波峰数、加速度波形的波谷数、角速度波形的波谷数、加速度波形的峰值、角速度波形的峰值、角速度的均值、角速度的均值、加速度波形的梯度、角速度波形的梯度中的至少一项。
一种可能的实现方式中，第一确定单元还用于：根据第一动作的动作数据，及佩戴松紧模型，确定第一动作的动作数据对应的穿戴设备佩戴松紧度。其中，第一动作的动作数据作为佩戴松紧模型的输入，穿戴设备佩戴松紧度作为佩戴松紧模型的输出。
在一些实施例中，本申请实施例提供的一种检测穿戴设备佩戴松紧的装置还包括：生成单元，用于根据穿戴设备佩戴松紧度，生成提示信息，提示信息采用预设呈现形式呈现穿戴设备佩戴松紧度的检测结果。其中，预设呈现形式包括以下一项或多项组合：声音呈现形式、文字呈现形式、振动呈现形式和灯光呈现形式。
在本申请实施例中，通过采用不同的形式将检测结果提示给用户，可以有效避免在用户运动的过程中用户的穿戴设备佩戴易脱落、丢失的现象，同时，避免用户在运动过程中的被撞、误撞的风险。
一种可能的实现方式中，穿戴设备佩戴松紧度包括：穿戴设备佩戴正常、穿戴设备佩戴松动和穿戴设备佩戴紧。
在一些实施例中，本申请实施例提供的一种检测穿戴设备佩戴松紧的装置还包括： 第二确定单元，用于确定在第一时长内各时刻的穿戴设备佩戴松紧度。第三确定单元，用于根据第一时长内各时刻的穿戴设备佩戴松紧度，确定穿戴设备佩戴松动的第二时长。计算单元，用于根据第一时长和第二时长，及穿戴设备计算的第一运动能量，计算用户在第一时长内的第二运动能量。其中，第一运动能量是在第一时长内穿戴设备佩戴状态为正常或紧的情况下计算得到的。
因此，在本申请实施例中穿戴设备可以评估用户在第二时长的运动能量。在穿戴设备佩戴松的情况下，穿戴设备可以根据佩戴松动的时间占比，及评估的运动能量，确定用户在第二时长的运动的实际运动能量，使得用户的运动数据更可信，以便于提醒用户下次运行时注意调整穿戴设备的佩戴松紧。
一种可能的实现方式中，第一动作包括起跳动作，第一动作节点包括足部离开地面和/或足部接触地面；或者，第一动作包括摆臂动作，第一动作节点包括手臂摆动在身体前侧的指定位置和/或手臂摆动在身体后侧的指定位置。
一种可能的实现方式中，穿戴设备用于佩戴在用户的足部或鞋上。
可以理解的，该装置具有实现上述方面及可能的实现方式中任一方法的功能。该功能可以通过硬件实现，也可以通过硬件执行相应的软件实现。硬件或软件包括至少一个与上述功能相对应的模块或单元。
第三方面，本申请实施例提供的一种检测穿戴设备佩戴松紧的系统，该系统包括：穿戴设备，用于：在检测到穿戴设备处于佩戴状态时，采集用户的运动数据。识别用户的运动数据中第一动作的动作数据。确定第一动作的动作数据对应的穿戴设备佩戴松紧度，并将穿戴设备佩戴松紧度发送给非穿戴设备。非穿戴设备，用于：接收穿戴设备佩戴松紧度，并根据穿戴设备佩戴松紧度生成提示信息，提示信息用于提示用户穿戴设备佩戴松紧度的检测结果。
在本申请实施例中，检测穿戴设备佩戴松紧功能延伸至多个设备，通过多个设备之间的配合作业，既解决了用户的佩戴松紧问题，又增加了用户多个设备联动体验。
第四方面，本申请实施例提供的一种检测穿戴设备佩戴松紧的系统，该系统包括：穿戴设备，用于：在检测到穿戴设备处于佩戴状态时，采集用户的运动数据；将采集到的运动数据发送给非穿戴设备。非穿戴设备，用于：接收穿戴设备发送的运动数据，并识别运动数据中第一动作的动作数据；确定第一动作的动作数据对应的穿戴设备佩戴松紧度。
一种可能的实现方式中，非穿戴设备还用于：根据穿戴设备佩戴松紧度生成提示信息，提示信息用于提示用户穿戴设备佩戴松紧度的检测结果。
在本申请实施例中，检测穿戴设备佩戴松紧与提示功能延伸至多个设备，通过多个设备之间的配合作业，既解决了用户的佩戴松紧问题，又增加了用户多个设备联动体验。
第五方面、提供一种计算机可读存储介质，包括计算机指令，当计算机指令在终端上运行时，使得终端执行如上述方面及其中任一种可能的实现方式中所述的方法。
第六方面、提供一种计算机程序产品，当计算机程序产品在计算机上运行时，使得计算机执行如上述方面中及其中任一种可能的实现方式中所述的方法。
第七方面、提供一种芯片系统，包括处理器，当处理器执行指令时，处理器执行如上述方面中及其中任一种可能的实现方式中所述的方法。
其中，上述第二方面至第七方面中各个实施例的具体实施方式及对应的技术效果可 以参见上述第一方面的具体实施方式及技术效果。
附图说明
为了更清楚地说明本申请实施例中的技术方案，下面将对实施例或现有技术描述中所需要使用的附图作简单地介绍，显而易见地，下面描述中的附图仅仅是本申请的一些实施例，对于本领域普通技术人员来讲，在不付出创造性劳动的前提下，还可以根据这些附图获得其它的附图。
图1为本申请实施例提供的一种穿戴设备的结构示意图；
图2为本申请实施例提供的一种检测穿戴设备佩戴松紧的方法的流程示意图；
图3为本申请实施例提供的一种检测穿戴设备佩戴松紧的方法的应用场景示意图；
图4为本申请实施例提供的一种检测穿戴设备佩戴松紧的方法的应用场景示意图；
图5为本申请实施例提供的一种检测穿戴设备佩戴松紧的方法的应用场景示意图；
图6a为本申请实施例提供的一种检测穿戴设备佩戴松紧的方法的应用场景示意图；
图6b为本申请实施例提供的一种检测穿戴设备佩戴松紧的方法的应用场景示意图；
图7为本申请实施例提供的一种应用场景中检测穿戴设备佩戴松紧的方法的流程示意图；
图8为本申请实施例提供的一种应用场景中检测穿戴设备佩戴松紧的方法的流程示意图；
图9为本申请实施例提供的一种应用场景中检测穿戴设备佩戴松紧的方法的流程示意图；
图10为本申请实施例提供的一种检测穿戴设备佩戴松紧的方法的流程示意图；
图11为本申请实施例提供的一种检测穿戴设备佩戴松紧的方法的流程示意图；
图12为本申请实施例提供的一种检测穿戴设备佩戴松紧的装置的结构示意图。
具体实施方式
在本申请实施例的描述中，除非另有说明，“/”表示或的意思，例如，A/B可以表示A或B；本文中的“和/或”仅仅是一种描述关联对象的关联关系，表示可以存在三种关系，例如，A和/或B，可以表示：单独存在A，同时存在A和B，单独存在B这三种情况。
以下，术语“第一”、“第二”仅用于描述目的，而不能理解为指示或暗示相对重要性或者隐含指明所指示的技术特征的数量。由此，限定有“第一”、“第二”的特征可以明示或者隐含地包括一个或者更多个该特征。在本申请实施例的描述中，除非另有说明，“多个”的含义是两个或两个以上。
在本申请实施例中，“示例性的”或者“例如”等词用于表示作例子、例证或说明。本申请实施例中被描述为“示例性的”或者“例如”的任何实施例或设计方案不应被解释为比其它实施例或设计方案更优选或更具优势。确切而言，使用“示例性的”或者“例如”等词旨在以具体方式呈现相关概念。
随着技术的发展，穿戴设备普遍应用在人们生活、工作和学习中。例如，穿戴设备可以检测用户的健康状况和用户的运动情况等。当穿戴设备在用户身上佩戴较松时，穿戴设备采集到的数据不准确，会导致穿戴设备对用户的健康状况或运动情况的评估不准确，影响穿戴设备的检测性能。
为了确保穿戴设备的检测性能，可以采用以下方式检测穿戴设备佩戴松紧：通过设置在穿戴设备的底壳上的压力传感器检测穿戴设备底壳上受到的压力值，并根据检测到 的压力值判断穿戴设备的佩戴松紧性，解决了对穿戴设备的佩戴松紧性进行检测的问题，提高了用户的舒适度，以及穿戴设备检测性能的准确度。
本申请实施例提供另一种检测穿戴设备佩戴松紧的方法：在检测到穿戴设备处于佩戴状态时，采集用户的运动数据。识别用户的运行数据中第一动作的动作数据。确定第一动作的动作数据对应的穿戴设备佩戴松紧度。这样，本申请实施例可以根据用户的运动数据确定穿戴设备佩戴松紧度，进而可以避免运动数据采集不准确的问题，使得运动数据的采集更加可靠，为用户提供更加专业的指导奠定基础。
进一步的，确定第一动作的动作数据对应的穿戴设备佩戴松紧度，具体可采用以下方式实现：方式一，根据第一动作的动作数据，及运动数据与佩戴松紧度的对应关系，确定穿戴设备佩戴松紧度。示例性的，根据第一动作的动作数据，确定用户的第一动作的第一动作节点对应的第一特征数据。根据特征数据与佩戴松紧度的对应关系，及第一动作节点对应的第一特征数据，确定穿戴设备佩戴松紧度。方式二，根据第一动作的动作数据，及佩戴松紧模型，确定第一动作的动作数据对应的穿戴设备佩戴松紧度。其中，第一动作的动作数据作为佩戴松紧模型的输入，穿戴设备佩戴松紧度作为佩戴松紧模型的输出，该佩戴松紧模型基于运动数据和穿戴设备佩戴松紧度训练得到的。
进一步的，本申请实施例提供的检测穿戴设备佩戴松紧的方法还包括：根据穿戴设备佩戴松紧度生成提示信息，该提示信息采用预设呈现形式将穿戴设备佩戴松紧度的检测结果呈现给用户。其中，预设呈现形式包括以下一项或多项组合：声音呈现形式、文字呈现形式、振动呈现形式和灯光呈现形式。这样，可以有效直观的将检测结果展示给用户，以达到及时提醒的作用。
本申请实施例提供的穿戴设备佩戴松紧的方法的执行主体可以为一个或者多个。
当该检测穿戴设备佩戴松紧的方法的执行主体为一个时，该检测穿戴设备佩戴松紧的方法的执行主体可以为穿戴设备。
当该检测穿戴设备佩戴松紧的方法的执行主体为至少两个时，该检测穿戴设备佩戴松紧的方法的执行主体可以包括穿戴设备和非穿戴设备，该非穿戴设备可以为手机、电脑、耳机、手表、手环等设备。其中，穿戴设备与非穿戴式设备之间的配合作业可以有多种实现方式。示例性地，可以如下所述：
方式一：穿戴设备在检测到穿戴设备处于佩戴状态时，采集用户的运动数据，识别用户的运动数据中第一动作的动作数据，确定第一动作的动作数据对应的穿戴设备佩戴松紧度，并将穿戴设备佩戴松紧度发送给非穿戴设备。具体可以为：穿戴设备在检测到穿戴设备处于佩戴状态时，采集用户的运动数据。穿戴设备在采集到的用户的运动数据中识别第一动作的动作数据，该第一动作包括至少一个动作节点。穿戴设备确定用户的第一动作的第一动作节点对应的第一特征数据。该穿戴设备根据标准数据库中存储的运动数据(如，第一动作节点的第一标准数据)与佩戴松紧度的对应关系，及第一动作节点对应的第一特征数据，确定穿戴设备佩戴松紧度。穿戴设备将穿戴设备佩戴松紧度发送给非穿戴设备。非穿戴设备接收穿戴设备佩戴松紧度，并根据穿戴设备佩戴松紧度生成提示信息以提示用户穿戴设备佩戴松紧度的检测结果。
方式二：穿戴设备在检测到穿戴设备处于佩戴状态时，采集用户的运动数据。穿戴设备将采集到的运动数据发送给非穿戴设备。该非穿戴设备接收穿戴设备发送的运动数据，并识别运动数据中第一动作的动作数据，确定第一动作的动作数据对应的穿戴设备 佩戴松紧度。具体可以为：非穿戴设备在运动数据中识别第一动作的动作数据，该第一动作包括至少一个动作节点。该非穿戴设备确定用户的第一动作的第一动作节点对应的第一特征数据。该非穿戴设备根据标准数据库中存储的运动数据(如，第一动作节点的第一标准数据)与佩戴松紧度的对应关系，及第一动作节点对应的第一特征数据，确定穿戴设备佩戴松紧度。进一步的，非穿戴设备根据穿戴设备佩戴松紧度生成提示信息以提示用户穿戴设备佩戴松紧度的检测结果。穿戴设备与非穿戴式设备之间的配合作业还可以有其他方式。
以下对穿戴设备或非穿戴设备的结构进行描述。穿戴设备与非穿戴设备的结构可以相同。本申请实施例以穿戴设备与非穿戴设备的结构相同为例进行说明，图1示出了穿戴设备100的结构示意图。
穿戴设备100可以包括处理器110，存储器120，通用串行总线(universal serial bus，USB)接口130，充电管理模块140，电源管理模块141，电池142，传感器模块150，显示屏160，天线1，无线通信模块170，以及音频模块180等。其中传感器模块150可以包括加速度传感器150A，陀螺仪传感器150B等。音频模块180可以包括扬声器180A，受话器180B，麦克风180C等。
可以理解的是，本发明实施例示意的结构并不构成对穿戴设备100的具体限定。在本申请另一些实施例中，穿戴设备100可以包括比图示更多或更少的部件，或者组合某些部件，或者拆分某些部件，或者不同的部件布置。图示的部件可以以硬件，软件或软件和硬件的组合实现。
处理器110可以包括一个或多个处理单元，例如：处理器110可以包括应用处理器(application processor，AP)，调制解调处理器，图形处理器(graphics processing unit，GPU)，图像信号处理器(image signal processor，ISP)，控制器，视频编解码器，数字信号处理器(digital signal processor，DSP)，基带处理器，和/或神经网络处理器(neural-network processing unit，NPU)等。其中，不同的处理单元可以是独立的器件，也可以集成在一个或多个处理器中。
控制器可以根据指令操作码和时序信号，产生操作控制信号，完成取指令和执行指令的控制。
处理器110中还可以设置存储器，用于存储指令和数据。在一些实施例中，处理器110中的存储器为高速缓冲存储器。该存储器可以保存处理器110刚用过或循环使用的指令或数据。如果处理器110需要再次使用该指令或数据，可从所述存储器中直接调用。避免了重复存取，减少了处理器110的等待时间，因而提高了系统的效率。
在一些实施例中，处理器110可以包括一个或多个接口。接口可以包括集成电路(inter-integrated circuit，I2C)接口，集成电路内置音频(inter-integrated circuit sound，I2S)接口，脉冲编码调制(pulse code modulation，PCM)接口，通用异步收发传输器(universal asynchronous receiver/transmitter，UART)接口，移动产业处理器接口(mobile industry processor interface，MIPI)，通用输入输出(general-purpose input/output，GPIO)接口，用户标识模块(subscriber identity module，SIM)接口，和/或通用串行总线(universal serial bus，USB)接口等。
可以理解的是，本发明实施例示意的各模块间的接口连接关系，只是示意性说明，并不构成对穿戴设备100的结构限定。在本申请另一些实施例中，穿戴设备100也可以 采用上述实施例中不同的接口连接方式，或多种接口连接方式的组合。
存储器120可以用于存储计算机可执行程序代码，所述可执行程序代码包括指令。存储器120可以包括存储程序区和存储数据区。其中，存储程序区可存储操作系统，至少一个功能所需的应用程序(比如声音播放功能，图像播放功能等)等。存储数据区可存储穿戴设备100使用过程中所创建的数据(比如音频数据，电话本等)等。此外，存储器120可以包括高速随机存取存储器，还可以包括非易失性存储器，例如至少一个磁盘存储器件，闪存器件，通用闪存存储器(universal flash storage，UFS)等。处理器110通过运行存储在存储器120的指令，和/或存储在设置于处理器中的存储器的指令，执行穿戴设备100的各种功能应用以及数据处理。
充电管理模块140用于从充电器接收充电输入。其中，充电器可以是无线充电器，也可以是有线充电器。在一些有线充电的实施例中，充电管理模块140可以通过USB接口130接收有线充电器的充电输入。在一些无线充电的实施例中，充电管理模块140可以通过穿戴设备100的无线充电线圈接收无线充电输入。充电管理模块140为电池142充电的同时，还可以通过电源管理模块141为穿戴设备供电。
电源管理模块141用于连接电池142，充电管理模块140与处理器110。电源管理模块141接收电池142和/或充电管理模块140的输入，为处理器110，存储器120，显示屏160和无线通信模块170等供电。电源管理模块141还可以用于监测电池容量，电池循环次数，电池健康状态(漏电，阻抗)等参数。在其他一些实施例中，电源管理模块141也可以设置于处理器110中。在另一些实施例中，电源管理模块141和充电管理模块140也可以设置于同一个器件中。
加速度传感器150A可检测穿戴设备100在各个方向上(一般为三轴)加速度的大小。当穿戴设备100静止时可检测出重力的大小及方向。还可以用于识别穿戴设备姿态，应用于横竖屏切换，计步器等应用。
陀螺仪传感器150B可以用于确定穿戴设备100的运动姿态。在一些实施例中，可以通过陀螺仪传感器150B确定穿戴设备100围绕三个轴(即，x，y和z轴)的角速度。陀螺仪传感器150B可以用于拍摄防抖。示例性的，当按下快门，陀螺仪传感器150B检测穿戴设备100抖动的角度，根据角度计算出镜头模组需要补偿的距离，让镜头通过反向运动抵消穿戴设备100的抖动，实现防抖。陀螺仪传感器150B还可以用于导航，体感游戏场景。
穿戴设备100的无线通信功能可以通过天线1，无线通信模块170，调制解调处理器以及基带处理器等实现。
天线1用于发射和接收电磁波信号。穿戴设备100中的每个天线可用于覆盖单个或多个通信频带。不同的天线还可以复用，以提高天线的利用率。在另外一些实施例中，天线可以和调谐开关结合使用。
穿戴设备100通过GPU，显示屏160，以及应用处理器等实现显示功能。GPU为图像处理的微处理器，连接显示屏160和应用处理器。GPU用于执行数学和几何计算，用于图形渲染。处理器110可包括一个或多个GPU，其执行程序指令以生成或改变显示信息。
显示屏160用于显示图像，视频等。显示屏160包括显示面板。显示面板可以采用液晶显示屏(liquid crystal display，LCD)，有机发光二极管(organic light-emitting diode， OLED)，有源矩阵有机发光二极体或主动矩阵有机发光二极体(active-matrix organic light emitting diode的，AMOLED)，柔性发光二极管(flex light-emitting diode，FLED)，Miniled，MicroLed，Micro-oLed，量子点发光二极管(quantum dot light emitting diodes，QLED)等。在一些实施例中，穿戴设备100可以包括1个或N个显示屏160，N为大于1的正整数。
无线通信模块170可以提供应用在穿戴设备100上的包括无线局域网(wireless local area networks，WLAN)(如无线保真(wireless fidelity，Wi-Fi)网络)，蓝牙(bluetooth，BT)，全球导航卫星系统(global navigation satellite system，GNSS)，调频(frequency modulation，FM)，近距离无线通信技术(near field communication，NFC)，红外技术(infrared，IR)等无线通信的解决方案。无线通信模块170可以是集成至少一个通信处理模块的一个或多个器件。无线通信模块170经由天线1接收电磁波，将电磁波信号调频以及滤波处理，将处理后的信号发送到处理器110。无线通信模块170还可以从处理器110接收待发送的信号，对其进行调频，放大，经天线1转为电磁波辐射出去。
音频模块180用于将数字音频信息转换成模拟音频信号输出，也用于将模拟音频输入转换为数字音频信号。音频模块180还可以用于对音频信号编码和解码。在一些实施例中，音频模块180可以设置于处理器110中，或将音频模块180的部分功能模块设置于处理器110中。
扬声器180A，也称“喇叭”，用于将音频电信号转换为声音信号。穿戴设备100可以通过扬声器180A收听音乐，或收听免提通话。
受话器180B，也称“听筒”，用于将音频电信号转换成声音信号。当穿戴设备100接听电话或语音信息时，可以通过将受话器180B靠近人耳接听语音。
麦克风180C，也称“话筒”，“传声器”，用于将声音信号转换为电信号。当拨打电话或发送语音信息时，用户可以通过人嘴靠近麦克风180C发声，将声音信号输入到麦克风180C。电子设备300可以设置至少一个麦克风180C。在另一些实施例中，穿戴设备100可以设置两个麦克风180C，除了采集声音信号，还可以实现降噪功能。在另一些实施例中，穿戴设备100还可以设置三个，四个或更多麦克风180C，实现采集声音信号，降噪，还可以识别声音来源，实现定向录音功能等。
当然，穿戴设备100还可以包括其他功能单元，本申请实施例对此不进行限定。
下面以图1所示架构为例，对本申请实施例提供的检测穿戴设备佩戴松紧的方法进行描述。下述实施例中的各单元可以具备图1所示部件，不予赘述。需要说明的是，本申请的实施例中各个设备之间交互的消息名称或消息中的参数名称等只是一个示例，具体实现中也可以采用其他的名称。本申请实施例中的生成(generate)也可以理解为创建(create)或者确定，本申请实施例中的“包括”也可以理解为“携带”，在此统一说明，本申请实施例对此不作具体限定。
如上述，本申请实施例提供的穿戴设备佩戴松紧的方法的执行主体可以为一个或者多个。针对不同的执行主体，在此进行详细说明：
第一种，当该检测穿戴设备佩戴松紧的方法的执行主体为一个时，该检测穿戴设备佩戴松紧的方法的执行主体可以为穿戴设备。
图2为本申请实施例提供的一种检测穿戴设备佩戴松紧的方法的流程示意图，如图2所示，该方法的执行主体可以为该穿戴设备，该方法可以包括：
S201、在检测到穿戴设备处于佩戴状态时，穿戴设备采集用户的运动数据。
示例性的，穿戴设备处于佩戴状态，可以指：穿戴设备可以佩戴在用户的手臂或手腕上，或者，穿戴设备也可以佩戴在用户的脚腕上或跑鞋上。具体的，穿戴设备佩戴在用户的跑鞋上。具体的，该穿戴设备可以通过卡扣连接在跑鞋上，当然也可以是其他贴合式的连接方式，本申请实施例不做具体限定。其中，穿戴设备可以佩戴在跑鞋的鞋面或鞋帮或鞋带上，具体的，穿戴设备佩戴在用户的鞋带上。可见，本申请实施例提供的检测穿戴设备佩戴松紧的方法，增加了跑鞋佩戴场景下的佩戴松紧检测方案。
示例性的，穿戴设备采集用户的运动数据，示例性地，可采用以下方式实现：方式一，穿戴设备上的加速度传感器采集的第一身体部位的加速度。方式二，穿戴设备上的陀螺仪传感器采集第一身体部位的角速度。方式三，穿戴设备上的加速度传感器采集第一身体部位的加速度，及穿戴设备上的陀螺仪传感器采集第一身体部位的角速度。上述实现方式中，第一身体部位与用户的运动相关。
示例1，图3为本申请实施例提供的一种检测穿戴设备佩戴松紧的方法的应用场景示意图。如图3所示，以用户的运动是蹦跳运动为例，相应的，第一身体部位可以为人体的足部。则，用户在做蹦跳过程中，穿戴设备上的加速度传感器采集用户的足部的加速度，和/或，穿戴设备上的陀螺仪传感器采集用户的足部的角速度。
示例2，以用户的运动是摆臂运动为例，相应的，第一身体部位可以为人体的手臂。则，用户在做摆臂运动过程中，穿戴设备上的加速度传感器采集用户的手臂的加速度，和/或，穿戴设备上的陀螺仪传感器采集用户的手臂的角速度。
S202、穿戴设备识别用户的运动数据中第一动作的动作数据。
该第一动作是用户运动过程中的某一动作。该第一动作与穿戴设备佩戴的位置对应，当穿戴设备佩戴在用户的手臂或手腕上时，第一动作可以包括摆臂动作等。当穿戴设备佩戴在用户的脚腕或跑鞋上时，第一动作可以包括起跳动作，踢腿动作，等等。当然，第一动作可以包括人体能够完成的任一动作，本申请实施例不做具体限定。
该第一动作可以包括至少一个动作节点。该动作节点可以理解为用户在做一个动作的过程中，用户的某个身体部位发生变化的节点。例如，以第一动作为起跳动作为例，动作节点可以包括足部离地和足部触地等两个动作节点。以第一动作为摆臂动作为例，动作节点可以包括手臂摆动在身体前侧的指定位置和手臂摆动在身体后侧的指定位置等动作节点。
其中，穿戴设备识别用户的运动数据中第一动作的动作数据，具体可实现为：穿戴设备根据采集到的用户运动过程中的实时运动数据，预先存储的各动作及其对应的标准数据，确定第一动作的动作数据。也就是说，穿戴设备将采集到的运动数据与各动作的标准数据进行比较，从采集到的运动数据中确定与第一动作的标准数据类似的第一运动数据。穿戴设备将第一运动数据对应的动作确定为第一动作，并确定第一运动数据为第一动作的动作数据。或者说，穿戴设备将采集到的运动数据与各动作的标准数据进行比较，确定与第一运动数据接近的第一动作的标准数据，穿戴设备将第一动作确定为第一运动数据对应的动作，第一运动数据即为第一动作的动作数据。
S203、穿戴设备确定第一动作的动作数据对应的穿戴设备佩戴松紧度。
示例性的，S203具体可采用以下方式实现：
方式一：穿戴设备根据第一动作的动作数据，及预设的运动数据与佩戴松紧度的对应关系，确定穿戴设备佩戴松紧度。或者说，穿戴设备根据第一动作的动作数据，及标准数据库 中存储的第一动作的标准数据与佩戴松紧度的对应关系，确定穿戴设备佩戴松紧度。
其中，预设的运动数据与佩戴松紧度的对应关系，可以理解为：第一种，一个运动数据与佩戴松紧度的对应关系，也就是说，运动数据的数值与佩戴松紧度一一对应。示例性的，以运动数据为加速度为例，加速度值为30m/s 2，其与佩戴松紧度为佩戴正常对应。第二种，一组运动数据与佩戴松紧度的对应关系，也就是说，运动数据的数值区间与佩戴松紧度对应。示例性的，以运动数据为加速度为例，加速度的数值区间为30-50m/s 2，其与佩戴松紧度为佩戴正常对应。
又由于第一动作可以包括至少一个动作节点。为了准确的确定穿戴设备佩戴松紧度，穿戴设备可以根据第一动作的动作数据，确定各个动作节点的动作数据。示例性的：
S2031、穿戴设备识别出第一动作的动作数据中第一动作节点的动作数据。
该第一动作节点可以根据运动数据突变，加速度方向和角速度方向中的至少一项确定。
具体可实现为：穿戴设备确定用户在做第一动作的过程中第一身体部位的动作数据形成的动作波形。穿戴设备根据动作波形，确定第一动作节点的动作数据。
为了更准确的确定穿戴设备佩戴松紧度，穿戴设备根据各个动作节点的动作数据，确定第一动作节点对应的特征数据，具体可实现为：
S2032、穿戴设备根据第一动作节点的动作数据，确定第一动作节点对应的第一特征数据。
该第一特征数据可以包括但不局限于以下至少一项：加速度波形或角速度波形的波峰数、加速度波形或角速度波形的波谷数、加速度波形或角速度波形的峰值、角速度或角速度的均值、加速度波形或角速度波形的梯度等特征数据。当然，第一特征数据还可以包括其他特征数据，本申请实施例不做具体限定。
示例性的，S2032具体可实现为：穿戴设备确定用户在做第一动作的过程中第一身体部位的动作数据形成的动作波形。穿戴设备根据动作波形，确定第一动作节点的触发时刻，及在该触发时刻所在的第一预设时间内对应的第一特征数据。
该第一预设时间可以指一段时间，该段时间的长短根据实际情况设定，本申请实施例不做具体限定。
沿用上述示例1，以第一动作是起跳动作为例，相应的，第一动作的第一动作节点可以为用户足部离开地面或用户足部接触地面。以动作数据为用户的足部的加速度，第一动作节点为用户足部离开地面进行说明：
A、穿戴设备确定用户在做起跳动作的过程中足部的加速度数据形成的加速度波形。
B、穿戴设备根据加速度波形确定加速度大于预设加速度的时刻为足部离开地面的第一时刻，及并确定在该第一时刻所在的第一预设时间内对应的加速度数据。穿戴设备根据在该第一时刻所在的第一预设时间内对应的加速度数据，计算在第一预设时间内的第一特征数据。
S2033、穿戴设备根据第一动作节点对应的第一特征数据，及预设的运动数据与佩戴松紧度的对应关系，确定穿戴设备佩戴松紧度。
也就是说，穿戴设备根据标准数据库中存储的运动数据(如，第一动作节点的标准数据)与佩戴松紧度的对应关系，及第一动作节点对应的第一特征数据，确定穿戴设备佩戴松紧度。
上述实现方式中，标准数据库中的标准数据可以是云服务器推送的，或者是穿戴设备下载的，再或者是穿戴设备中预先存储的。其中，该标准数据可以是普通人执行第一动作对应的动作数据，也可以是穿戴设备的用户的历史数据。具体的，该标准数据可以根据用户的性别、身高、体重等参数筛选的。其中，标准数据库中的标准数据具体可以是：在穿戴设备处于不同佩戴松紧度的情况下用户做第一动作的过程中第一动作节点的标准数据。其中，该标准数据的种类可以包括但不限于以下至少一项：加速度波形的波峰数、角速度波形的波峰数、加速度波形的波谷数、角速度波形的波谷数、加速度波形的峰值、角速度波形的峰值、加速度的均值、角速度的均值、加速度波形的梯度、角速度波形的梯度等数据。
沿用上述示例1，以第一动作是起跳动作为例，相应的，第一动作的第一动作节点可以为用户足部离开地面或用户足部接触地面。以动作数据为用户的足部的加速度，第一动作节点为用户足部离开地面，且标准数据为波峰数进行说明：
S2033具体可实现为：穿戴设备根据在触发时刻所在的第一预设时间内对应的波峰数，及预先存储的在穿戴设备处于不同佩戴松紧度的情况下用户做起跳动作的过程中足部离开地面的标准波峰数，确定穿戴设备的佩戴松紧度。
本申请实施例，穿戴设备根据用户的动作数据即可确定穿戴设备的佩戴松紧，无需额外的硬件装置驱动穿戴设备动作，即可检测穿戴设备佩戴松紧，进而可以有效避免动作数据采集不准确的问题，使得动作数据的采集更加可靠，为用户提供更加专业的指导奠定基础。
方式二：穿戴设备根据所述第一动作的动作数据，及佩戴松紧模型，确定第一动作的动作数据对应的穿戴设备佩戴松紧度。其中，第一动作的动作数据作为佩戴松紧模型的输入，穿戴设备佩戴松紧度作为佩戴松紧模型的输出，该佩戴松紧模型基于运动数据和佩戴松紧度训练得到的，该模型训练的具体实现方法本申请不做具体限定。
进一步的，本申请实施例提供的检测穿戴设备佩戴松紧的方法还可以包括：S204、穿戴设备根据佩戴松紧度，生成提示信息以提示用户穿戴设备佩戴松紧度的检测结果。其中，穿戴设备佩戴松紧度可以理解为穿戴设备佩戴松紧程度，也可以理解为具体的数值。当穿戴设备佩戴松紧度理解为穿戴设备佩戴松紧程度时，该穿戴设备佩戴松紧度可以包括穿戴设备佩戴正常、穿戴设备佩戴松动和穿戴设备佩戴紧。当穿戴设备佩戴松紧度理解为具体数值时，S204具体可实现为：当穿戴设备的佩戴松紧度大于阈值时，穿戴设备确定穿戴设备佩戴紧，并将佩戴紧度的检测结果通过第一提示信息提示给用户。当穿戴设备的佩戴松紧度等于或接近阈值时，穿戴设备确定穿戴设备佩戴正常，并将佩戴正常的检测结果通过第二提示信息提示给用户。当穿戴设备的佩戴松紧度小于阈值时，穿戴设备确定穿戴设备佩戴松，并将佩戴松度的检测结果通过第三提示信息提示给用户。
其中，第一提示信息、第二提示信息和第三提示信息均可以通过不同的呈现形式提示用户。例如，第一提示信息、第二提示信息和第三提示信息均可以通过用户界面(user interface，UI)显示给用户，或者，通过LED灯发出不同颜色的光提示用户，或者，通过振动的强度和/或振动次数不同提示用户，或者，通过声音的方式提示用户。当然，也可以通过不同呈现形式组合的方式提示用户，本申请实施例不做具体限定。
示例性的，呈现形式一：在用户界面UI上可以通过文字和振动的呈现形式进行提示。例如，图4为本申请实施例提供的一种检测穿戴设备佩戴松紧的方法的应用场景示意图。 如图4所示，当检测到穿戴设备佩戴正常时，穿戴设备将生成的第二提示信息通过用户界面显示(如用户界面UI上显示“佩戴正常”)，且穿戴设备振动一次，来提示用户穿戴设备佩戴正常。当检测到穿戴设备佩戴松时，穿戴设备将生成的第三提示信息通过用户界面显示(如用户界面UI上显示“佩戴松”)，且穿戴设备振动两次，来提示用户穿戴设备佩戴松。当然，穿戴设备振动次数可以任意设定，本申请实施例不做具体限定。
呈现形式二：在用户界面UI上可以通过文字、振动和声音的组合呈现形式进行提示。例如，当检测到穿戴设备佩戴正常时，穿戴设备将生成的第二提示信息通过用户界面显示(如用户界面UI上显示“佩戴正常”)，且穿戴设备振动一次，同时穿戴设备发出第一种提示音，来提示用户穿戴设备佩戴正常。图5为本申请实施例提供的一种检测穿戴设备佩戴松紧的方法的应用场景示意图。如图5所示，当检测到穿戴设备佩戴松时，穿戴设备将生成的第三提示信息通过用户界面显示(如用户界面UI上显示“佩戴松”)，且穿戴设备振动两次，同时穿戴设备发出第二种提示音，来提示用户穿戴设备佩戴松。当然，穿戴设备振动次数可以任意设定，及在不同检测结果下提示音的选取也可以任意设置，本申请实施例不做具体限定。
呈现形式三：在用户界面UI上可以通过文字和LED灯的组合呈现形式进行提示。例如，图6a为本申请实施例提供的一种检测穿戴设备佩戴松紧的方法的应用场景示意图。如图6a所示，当检测到穿戴设备佩戴正常时，穿戴设备将生成的第二提示信息通过用户界面显示(如用户界面UI上显示“佩戴正常”)，且穿戴设备上设置的LED灯发出第一种提示光，来提示用户穿戴设备佩戴正常。图6b为本申请实施例提供的一种检测穿戴设备佩戴松紧的方法的应用场景示意图。如图6b所示，当检测到穿戴设备佩戴松时，穿戴设备将生成的第三提示信息通过用户界面显示(如用户界面UI上显示“佩戴松”)，且穿戴设备上设置的LED灯发出第二种提示光，来提示用户穿戴设备佩戴松。其中，第一种提示光可以为绿光，第二种提示光可以为红光。这里需要补充的是，穿戴设备上设置的LED灯可以排布但并不局限于在穿戴设备的屏幕的周边。这样，用户佩戴穿戴设备处于黑暗的地方，用户佩戴穿戴设备可以提醒其他用户，有效防止被误撞的风险。
当然，声音的呈现形式具体可以为：语音播报的呈现形式。也就是说，穿戴设备的穿戴松紧度的检测结果也可以通过语音播报的形式展示。
在本申请实施例中，通过采用不同的形式将检测结果提示给用户，可以有效避免在用户运动的过程中用户的穿戴设备佩戴易脱落、丢失的现象，同时，避免用户在运动过程中的被撞、误撞的风险。
在一些实施例中，穿戴设备能够根据用户的运动数据评估用户运动的运动能量，例如，用户在跑步的过程中，穿戴设备可以根据用户的跑步距离、跑步速度、跑步时长等运动数据评估用户跑步的运动能量。当穿戴设备佩戴松时，穿戴设备采集的用户的跑步距离、跑步速度、跑步时长等运动数据不准确，会影响穿戴设备根据采集的用户的运动数据评估用户运动的运动能量的准确性。为了使得穿戴设备无论在何种状态下输出的用户运动的运动能量准确性高。如图2所示，本申请实施例提供的一种检测穿戴设备佩戴松紧的方法还包括：
S205、穿戴设备确定在第一时长内各时刻的穿戴设备佩戴松紧度。
也就是说，在用户做第二预设时间的运动过程中，穿戴设备确定第二预设时间(也就是第一时长)内各时刻的穿戴设备佩戴松紧度。
S206、穿戴设备根据第一时长内各时刻的穿戴设备佩戴松紧度，确定穿戴设备佩戴松动的第二时长。
该第二时长可以指连续的时长，也可以指多个非连续时长之和。
另外，穿戴设备根据第二预设时间内各时刻的穿戴设备佩戴松紧度，记录穿戴设备佩戴松动的时间并发出提醒告警。
该提醒告警用于提醒用户穿戴设备佩戴松动。该提醒告警可以包括警铃告警或警示灯告警等。当然，还可以包括其他形式的提醒告警，本申请实施例不做具体限定。
S207、穿戴设备根据第一时长和第二时长，及穿戴设备计算的第一运动能量，计算用户在第一时长内的第二运动能量。
其中，第一运动能量是在第一时长内穿戴设备佩戴状态为正常或紧的情况下计算得到的。
S207具体可实现为：穿戴设备根据穿戴设备佩戴松动的时间，计算穿戴设备佩戴松动的第二时长，再根据佩戴松动的第二时长与第一时长的比值，确定佩戴松动的时间占比。穿戴设备根据穿戴设备佩戴松动的时间占比，及穿戴设备计算的第一运动能量，确定用户在第二预设时间内的第二运动能量。
示例性的，假设用户的运动是跑步，用户在第二预设时间(也就是上述的第一时长)的跑步过程中，穿戴设备可以实时确定穿戴设备的佩戴松紧度。穿戴设备根据在第二预设时间采集到的用户的运动数据评估的运动能量。穿戴设备根据佩戴松动的时间占比，及穿戴设备根据用户在第二预设时间的跑步过程中评估的运动能量(也就是上述的第一运动能量)，计算补偿运动能量，该补偿运行能量可以为佩戴松动的时间占比乘以评估的运动能量。这样，穿戴设备即可确定用户在第二预设时间的跑步过程中的实际运行能量(也就是上述的第二运动能量)，该实际运行能量可以为评估的运行能量与补偿运行能量的差值。
因此，在本申请实施例中穿戴设备可以评估用户在第二预设时间的运动能量。在穿戴设备佩戴松的情况下，穿戴设备可以根据佩戴松动的时间占比，及评估的运动能量，确定用户在第二预设时间的运动的实际运动能量，使得用户的运动数据更可信，以便于提醒用户下次运行时注意调整穿戴设备的佩戴松紧。
以下结合应用场景对本申请实施例提供的检测穿戴设备佩戴松紧的方法进行详细说明。以跑步应用场景为例：
在跑步前，图7为本申请实施例提供的一种应用场景中检测穿戴设备佩戴松紧的方法的流程示意图。如图7所示，该方法包括：S701、用户将穿戴设备佩戴在跑鞋的鞋带上。S702、用户通过跑前的热身动作(如原地起跳)进行穿戴设备的佩戴松紧检测。S703、在用户执行起跳动作时，穿戴设备通过加速度传感器和/或陀螺仪传感器采集用户的运动数据。S704、穿戴设备在采集到的运动数据中识别起跳动作的动作数据，并确定起跳动作中足部离开地面和足部接触地面的特征数据。其中，起跳动作即为上述的第一动作，足部离开地面和足部接触地面均为上述的动作节点，S704具体可以为，穿戴设备确定用户在做起跳动作的过程中足部的加速度数据形成的加速度波形。穿戴设备根据加速度波形确定加速度大于预设加速度的时刻为足部离开地面的第一时刻，及并确定在该第一时刻所在的第一预设时间内对应的加速度数据。穿戴设备根据在该第一时刻所在的第一预设时间内对应的加速度数据，计算在第一预设时间内的特征数据，该特征数据可以包括 但不局限于以下至少一项：波峰数、波谷数、峰值、加速度的均值、加速度波形的梯度等特征数据。S705、穿戴设备根据标准数据库中存储的第一动作节点(如足部离开地面和足部接触地面)的标准数据与佩戴松紧度的对应关系，及足部离开地面对应的特征数据和足部接触地面对应的特征数据，确定穿戴设备佩戴松紧度。S706、穿戴设备根据佩戴松紧度与阈值的关系，确定穿戴设备佩戴是否松动。其中，当穿戴设备的佩戴松紧度小于阈值时，穿戴设备确定穿戴设备佩戴松。当穿戴设备的佩戴松紧度等于或接近阈值时，穿戴设备确定穿戴设备佩戴正常。当穿戴设备的佩戴松紧度大于阈值时，穿戴设备确定穿戴设备佩戴紧。若穿戴设备确定佩戴不松动，则执行结束流程；若穿戴设备确定佩戴松动，则执行S707。S707、穿戴设备生成提示信息以提示用户进行调整。
在跑步过程中，图8为本申请实施例提供的一种应用场景中检测穿戴设备佩戴松紧的方法的流程示意图。如图8所示，该方法包括：S801、穿戴设备采集用户跑步第二预设时间(也就是上述的第一时长)的运动数据。S802、穿戴设备根据采集到的用户跑步第二预设时间的运动数据，确定在第二预设时间内的各时刻的佩戴松紧度。S803、穿戴设备根据佩戴松紧度与阈值的关系，确定穿戴设备佩戴是否松动。若否，则执行结束流程。若是，则执行S804。S804、穿戴设备生成提示信息以提示用户穿戴设备佩戴松动，并记录穿戴设备佩戴松动的时间。
在跑步完，图9为本申请实施例提供的一种应用场景中检测穿戴设备佩戴松紧的方法的流程示意图。如图9所示，该方法包括：S901、穿戴设备根据采集到的用户跑步过程中的运动数据，评估的运动能量。S902、穿戴设备判断在用户的跑步期间穿戴设备是否佩戴松动。若穿戴设备判断在用户的跑步期间穿戴设备佩戴松动，则执行S903；若穿戴设备判断在用户的跑步期间穿戴设备没有佩戴松动，则执行S904。S903、穿戴设备确定第二预设时间内的佩戴松动的时间，并根据佩戴松动的时间与第二预设时间的比值，确定佩戴松动的时间占比。穿戴设备根据佩戴松动的时间占比，及穿戴设备根据用户在第二预设时间的跑步过程中评估的运动能量(也就是上述的第一运动能量)，计算补偿运动能量，该补偿运行能量可以为佩戴松动的时间占比乘以评估的运动能量。穿戴设备确定用户在第二预设时间的跑步过程中的实际运行能量(也就是上述的第二运动能量)，该实际运行能量可以为评估的运行能量与补偿运行能量的差值。S904、穿戴设备确定穿戴设备评估的运动能量即为实际运动能量。
第二种，当该检测穿戴设备佩戴松紧的方法的执行主体为至少两个时，该检测穿戴设备佩戴松紧的方法的执行主体可以包括穿戴设备和非穿戴设备。
其中，穿戴设备与非穿戴式设备之间的配合作业可以有多种实现方式。具体可以如下所述：
方式一：图10为本申请实施例提供的一种检测穿戴设备佩戴松紧的方法的流程示意图，如图10所示，该方法可以包括：①在检测到穿戴设备处于佩戴状态时，穿戴设备采集用户的运动数据。②穿戴设备在采集的运动数据中识别第一动作的动作数据，并确定用户的第一动作的第一动作节点对应的第一特征数据。具体的，穿戴设备在采集到的用户的动作数据中识别第一动作的动作数据，确定用户在做第一动作的过程中第一身体部位的动作数据形成的动作波形。穿戴设备根据动作波形，确定第一动作节点的触发时刻，及在该触发时刻的第一预设时间内对应的第一特征数据。穿戴设备根据标准数据库中存储的第一动作节点的标准数据与佩戴松紧度的对应关系，及第一动作节点对应的第一特 征数据，确定穿戴设备佩戴松紧度。③穿戴设备将佩戴松紧度对应的检测结果发送给非穿戴设备。具体的，穿戴设备可以通过蓝牙将佩戴松紧度对应的检测结果发送给非穿戴设备。当然，也可以采用其他的传输方式，本申请实施例不做具体限定。
其中，针对非穿戴设备的具体类型不同，非穿戴设备接收到穿戴设备发送的穿戴设备佩戴松紧度的检测结果，并将该检测结果提示给用户的提示方式不同。具体如下：
示例性的，④若该非穿戴设备可以为手表或手环，则手表或手环接收到穿戴设备发送的穿戴设备佩戴松紧度的检测结果，并根据该检测结果生成提示信息，该提示信息可以在用户界面UI上可以通过文字呈现，和/或，通过振动的呈现形式进行提示。
示例性的，如图4所示，当检测到穿戴设备佩戴正常时，手表或手环将生成的提示信息通过用户界面显示(如用户界面UI上显示“佩戴正常”)，且手表或手环振动一次，来提示用户穿戴设备佩戴正常。当检测到穿戴设备佩戴松时，手表或手环将生成的提示信息通过用户界面显示(如用户界面UI上显示“佩戴松”)，且穿戴设备振动两次，来提示用户穿戴设备佩戴松。当然，穿戴设备振动次数可以任意设定，本申请实施例不做具体限定。
⑤若该非穿戴设备可以为耳机，则耳机接收到穿戴设备发送的穿戴设备佩戴松紧度的检测结果，并根据该检测结果生成提示信息，该提示信息可以通过语音的呈现形式进行提示。
⑥若该非穿戴设备可以为手机，则手机接收到穿戴设备发送的穿戴设备佩戴松紧度的检测结果，并根据该检测结果生成提示信息，该提示信息可以在用户界面UI上可以通过文字呈现，和/或，通过振动/LED灯的呈现形式进行提示。
示例性的，如图6a所示，当检测到穿戴设备佩戴正常时，手机将生成的提示信息通过用户界面显示(如用户界面UI上显示“佩戴正常”)，且手机上设置的LED灯发出第一种提示光，来提示用户穿戴设备佩戴正常。如图6b所示，当检测到穿戴设备佩戴松时，手机将生成的提示信息通过用户界面显示(如用户界面UI上显示“佩戴松”)，且手机上设置的LED灯发出第二种提示光，来提示用户穿戴设备佩戴松。其中，第一种提示光可以为绿光，第二种提示光可以为红光。这里需要补充的是，当然，手机上的提示方式还可以是手机亮屏提示。
当然，声音的呈现形式具体可以为：语音播报的呈现形式。也就是说，手机可以将穿戴设备的穿戴松紧度的检测结果通过语音播报的形式展示。
其中，各个步骤的具体实现可以参见上述实施例中的相关内容，本申请实施例中不再赘述。
方式二：
图11为本申请实施例提供的一种检测穿戴设备佩戴松紧的方法的流程示意图，如图11所示，该方法可以包括：①在检测到穿戴设备处于佩戴状态时，穿戴设备采集用户的运动数据。②穿戴设备在将运动数据发送给非穿戴设备。具体的，穿戴设备可以通过蓝牙将运动数据发送给非穿戴设备。当然，也可以采用其他的传输方式，本申请实施例不做具体限定。③非穿戴设备接收穿戴设备发送的用户的运动数据，并在运动数据中识别第一动作的动作数据，确定用户的第一动作的第一动作节点对应的第一特征数据。具体的，非穿戴设备根据用户的动作数据，确定用户在做第一动作的过程中第一身体部位的动作数据形成的动作波形。非穿戴设备根据动作波形，确定第一动作节点的触发时刻， 及在该触发时刻的第一预设时间内对应的第一特征数据。非穿戴根据标准数据库中存储的第一动作节点的标准数据与佩戴松紧度的对应关系，及第一动作节点对应的第一特征数据，确定穿戴设备佩戴松紧度。
其中，针对非穿戴设备的具体类型不同，非穿戴设备将穿戴设备佩戴松紧度的检测结果提示给用户的提示方式不同。具体如下：
示例性的，④若该非穿戴设备可以为手表或手环，则手表或手环根据穿戴设备佩戴松紧度生成提示信息，该提示信息可以在用户界面UI上可以通过文字呈现，和/或，通过振动的呈现形式进行提示。
示例性的，如图4所示，当检测到穿戴设备佩戴正常时，手表或手环将生成的提示信息通过用户界面显示(如用户界面UI上显示“佩戴正常”)，且手表或手环振动一次，来提示用户穿戴设备佩戴正常。当检测到穿戴设备佩戴松时，手表或手环将生成的提示信息通过用户界面显示(如用户界面UI上显示“佩戴松”)，且穿戴设备振动两次，来提示用户穿戴设备佩戴松。当然，穿戴设备振动次数可以任意设定，本申请实施例不做具体限定。
⑤若该非穿戴设备可以为耳机，则耳机根据穿戴设备佩戴松紧度生成提示信息，该提示信息可以通过语音的呈现形式进行提示。
⑥若该非穿戴设备可以为手机，则手机根据穿戴设备佩戴松紧度生成提示信息，该提示信息可以在用户界面UI上可以通过文字呈现，和/或，通过振动/LED灯的呈现形式进行提示。
示例性的，如图6a所示，当检测到穿戴设备佩戴正常时，手机将生成的提示信息通过用户界面显示(如用户界面UI上显示“佩戴正常”)，且手机上设置的LED灯发出第一种提示光，来提示用户穿戴设备佩戴正常。如图6b所示，当检测到穿戴设备佩戴松时，手机将生成的提示信息通过用户界面显示(如用户界面UI上显示“佩戴松”)，且手机上设置的LED灯发出第二种提示光，来提示用户穿戴设备佩戴松。其中，第一种提示光可以为绿光，第二种提示光可以为红光。这里需要补充的是，当然，手机上的提示方式还可以是手机亮屏提示。
当然，声音的呈现形式具体可以为：语音播报的呈现形式。也就是说，手机可以将穿戴设备的穿戴松紧度的检测结果通过语音播报的形式展示。
其中，各个步骤的具体实现可以参见上述实施例中的相关内容，本申请实施例中不再赘述。
在本申请实施例中，检测穿戴设备佩戴松紧与提示功能延伸至多个设备，通过多个设备之间的配合作业，既解决了用户的佩戴松紧问题，又增加了用户多个设备联动体验。
图12为本申请实施例提供的一种检测穿戴设备佩戴松紧的装置，该装置1200可以包括：
采集单元1201，用于检测到穿戴设备处于佩戴状态时，采集用户的运动数据；
识别单元1202，用于识别用户的运动数据中第一动作的动作数据；
第一确定单元1203，用于确定第一动作的动作数据对应的穿戴设备佩戴松紧度。
在一种可实现方式中，第一确定单元1203还用于：
根据第一动作的动作数据，及预设的运动数据与佩戴松紧度的对应关系，确定穿戴设备佩戴松紧度。
在一种可实现方式中，第一确定单元1203还用于：
识别出第一动作的动作数据中第一动作节点的动作数据；
根据第一动作节点的动作数据，确定第一动作节点对应的第一特征数据；
根据第一特征数据，及预设的运动数据与佩戴松紧度的对应关系，确定穿戴设备佩戴松紧度。
在一种可实现方式中，第一特征数据包括：加速度波形的波峰数、角速度波形的波峰数、加速度波形的波谷数、角速度波形的波谷数、加速度波形的峰值、角速度波形的峰值、加速度的均值、角速度的均值、加速度波形的梯度、角速度波形的梯度中的至少一项。
在一种可实现方式中，第一确定单元1203还用于：
根据第一动作的动作数据，及佩戴松紧模型，确定第一动作的动作数据对应的穿戴设备佩戴松紧度；
其中，第一动作的动作数据作为佩戴松紧模型的输入，穿戴设备佩戴松紧度作为佩戴松紧模型的输出。
在一些实施例中，本申请实施例提供的一种检测穿戴设备佩戴松紧的装置还可以包括：
生成单元1204，用于根据穿戴设备佩戴松紧度，生成提示信息，提示信息采用预设呈现形式呈现穿戴设备佩戴松紧度的检测结果；
其中，预设呈现形式包括以下一项或多项组合：声音呈现形式、文字呈现形式、振动呈现形式和灯光呈现形式。
在一种可实现方式中，穿戴设备佩戴松紧度包括：穿戴设备佩戴正常、穿戴设备佩戴松动和穿戴设备佩戴紧。
在一些实施例中，本申请实施例提供的一种检测穿戴设备佩戴松紧的装置还可以包括：
第二确定单元1205，用于确定在第一时长内各时刻的穿戴设备佩戴松紧度；
第三确定单元1206，用于根据第一时长内各时刻的穿戴设备佩戴松紧度，确定穿戴设备佩戴松动的第二时长；
计算单元1207，用于根据第一时长和第二时长，及穿戴设备计算的第一运动能量，计算用户在第一时长内的第二运动能量；其中，第一运动能量是在第一时长内穿戴设备佩戴状态为正常或紧的情况下计算得到的。
在一种可实现方式中，第一动作包括起跳动作，第一动作节点包括足部离开地面和/或足部接触地面；或者，
第一动作包括摆臂动作，第一动作节点包括手臂摆动在身体前侧的指定位置和/或手臂摆动在身体后侧的指定位置。
在一种可实现方式中，穿戴设备用于佩戴在用户的足部或鞋上。
可选的，上述装置1200可以由代码实现也可由电路实现，具体的，该装置可以是终端设备的整机。示例性的，采集单元1201可以是采集电路，也可以由传感器(如图1所示的加速度传感器150A和/或陀螺仪传感器150B)实现。识别单元1202、第一确定单元1203、生成单元1204、第二确定单元1205、第三确定单元1206和计算单元1207可以是处理器(如图1所示的处理器110)。
可选的，该可能的设计中，上述图1～图11所示方法实施例中涉及电子设备的各步骤的所有相关内容均可以援引到对应功能模块的功能描述，在此不再赘述。该可能的设计中所述的电子设备用于执行图1～图11所示检测穿戴设备佩戴松紧的方法中电子设备的功能，因此可以达到与上述检测穿戴设备佩戴松紧的方法相同的效果。
本申请实施例还提供一种芯片系统，该芯片系统包括至少一个处理器和至少一个接口电路。处理器和接口电路可通过线路互联。例如，接口电路可用于从其它装置(例如存储器)接收信号。又例如，接口电路可用于向其它装置(例如处理器)发送信号。示例性的，接口电路可读取存储器中存储的指令，并将该指令发送给处理器。当所述指令被处理器执行时，可使得电子设备执行上述实施例中的穿戴设备执行的各个步骤。当然，该芯片系统还可以包含其他分立器件，本申请实施例对此不作具体限定。
本申请实施例还提供一种装置，该装置包含在电子设备中，该装置具有实现上述实施例中任一方法中电子设备行为的功能。该功能可以通过硬件实现，也可以通过硬件执行相应的软件实现。硬件或软件包括至少一个与上述功能相对应的模块或单元。例如，检测模块或单元、以及确定模块或单元等。
本申请实施例还提供一种计算机可读存储介质，包括计算机指令，当计算机指令在电子设备上运行时，使得电子设备执行如上述实施例中任一方法。
本申请实施例还提供一种计算机程序产品，当计算机程序产品在计算机上运行时，使得计算机执行如上述实施例中任一方法。
可以理解的是，上述终端等为了实现上述功能，其包含了执行各个功能相应的硬件结构和/或软件模块。本领域技术人员应该很容易意识到，结合本文中所公开的实施例描述的各示例的单元及算法步骤，本申请实施例能够以硬件或硬件和计算机软件的结合形式来实现。某个功能究竟以硬件还是计算机软件驱动硬件的方式来执行，取决于技术方案的特定应用和设计约束条件。本领域技术人员可以对每个特定的应用来使用不同方法来实现所描述的功能，但是这种实现不应认为超出本发明实施例的范围。
本申请实施例可以根据上述方法示例对上述终端等进行功能模块的划分，例如，可以对应各个功能划分各个功能模块，也可以将两个或两个以上的功能集成在一个处理模块中。上述集成的模块既可以采用硬件的形式实现，也可以采用软件功能模块的形式实现。需要说明的是，本发明实施例中对模块的划分是示意性的，仅仅为一种逻辑功能划分，实际实现时可以有另外的划分方式。
通过以上的实施方式的描述，所属领域的技术人员可以清楚地了解到，为描述的方便和简洁，仅以上述各功能模块的划分进行举例说明，实际应用中，可以根据需要而将上述功能分配由不同的功能模块完成，即将装置的内部结构划分成不同的功能模块，以完成以上描述的全部或者部分功能。上述描述的系统，装置和单元的具体工作过程，可以参考前述方法实施例中的对应过程，在此不再赘述。
在本申请实施例各个实施例中的各功能单元可以集成在一个处理单元中，也可以是各个单元单独物理存在，也可以两个或两个以上单元集成在一个单元中。上述集成的单元既可以采用硬件的形式实现，也可以采用软件功能单元的形式实现。
所述集成的单元如果以软件功能单元的形式实现并作为独立的产品销售或使用时，可以存储在一个计算机可读取存储介质中。基于这样的理解，本申请实施例的技术方案本质上或者说对现有技术做出贡献的部分或者该技术方案的全部或部分可以以软件产品 的形式体现出来，该计算机软件产品存储在一个存储介质中，包括若干指令用以使得一台计算机设备(可以是个人计算机，服务器，或者网络设备等)或处理器执行本申请各个实施例所述方法的全部或部分步骤。而前述的存储介质包括：快闪存储器、移动硬盘、只读存储器、随机存取存储器、磁碟或者光盘等各种可以存储程序代码的介质。
以上所述，仅为本申请的具体实施方式，但本申请的保护范围并不局限于此，任何在本申请揭露的技术范围内的变化或替换，都应涵盖在本申请的保护范围之内。因此，本申请的保护范围应以所述权利要求的保护范围为准。

Claims (26)

  1. 一种检测穿戴设备佩戴松紧的方法，其特征在于，所述方法包括：
    检测到穿戴设备处于佩戴状态时，采集用户的运动数据；
    识别所述用户的运动数据中第一动作的动作数据；
    确定所述第一动作的动作数据对应的穿戴设备佩戴松紧度。
  2. 根据权利要求1所述的方法，其特征在于，所述确定所述第一动作的动作数据对应的穿戴设备佩戴松紧度，包括：
    根据所述第一动作的动作数据，及预设的运动数据与佩戴松紧度的对应关系，确定所述穿戴设备佩戴松紧度。
  3. 根据权利要求2所述的方法，其特征在于，所述根据所述第一动作的动作数据，及预设的运动数据与佩戴松紧度的对应关系，确定所述穿戴设备佩戴松紧度，包括：
    识别出所述第一动作的动作数据中第一动作节点的动作数据；
    根据所述第一动作节点的动作数据，确定所述第一动作节点对应的第一特征数据；
    根据所述第一特征数据，及所述预设的运动数据与佩戴松紧度的对应关系，确定穿戴设备佩戴松紧度。
  4. 根据权利要求3所述的方法，其特征在于，
    所述第一特征数据包括：加速度波形的波峰数、角速度波形的波峰数、加速度波形的波谷数、角速度波形的波谷数、加速度波形的峰值、角速度波形的峰值、加速度的均值、角速度的均值、加速度波形的梯度、角速度波形的梯度中的至少一项。
  5. 根据权利要求1所述的方法，其特征在于，所述确定所述第一动作的动作数据对应的穿戴设备佩戴松紧度，包括：
    根据所述第一动作的动作数据，及佩戴松紧模型，确定所述第一动作的动作数据对应的穿戴设备佩戴松紧度；
    其中，所述第一动作的动作数据作为所述佩戴松紧模型的输入，所述穿戴设备佩戴松紧度作为所述佩戴松紧模型的输出。
  6. 根据权利要求1-5中任一项所述的方法，其特征在于，在确定所述第一动作的动作数据对应的穿戴设备佩戴松紧度之后，还包括：
    根据所述穿戴设备佩戴松紧度，生成提示信息，所述提示信息采用预设呈现形式呈现所述穿戴设备佩戴松紧度的检测结果；
    其中，所述预设呈现形式包括以下一项或多项组合：声音呈现形式、文字呈现形式、振动呈现形式和灯光呈现形式。
  7. 根据权利要求1-6中任一项所述的方法，其特征在于，所述穿戴设备佩戴松紧度包括：穿戴设备佩戴正常、穿戴设备佩戴松动和穿戴设备佩戴紧。
  8. 根据权利要求1-7中任一项所述的方法，其特征在于，还包括：
    确定在第一时长内各时刻的穿戴设备佩戴松紧度；
    根据所述第一时长内各时刻的穿戴设备佩戴松紧度，确定穿戴设备佩戴松动的第二时长；
    根据所述第一时长和所述第二时长，及穿戴设备计算的第一运动能量，计算所述用户在所述第一时长内的第二运动能量；其中，所述第一运动能量是在所述第一时长内所述穿戴设备佩戴状态为正常或紧的情况下计算得到的。
  9. 根据权利要求3所述的方法，其特征在于，所述第一动作包括起跳动作，所述第一动作节点包括足部离开地面和/或足部接触地面；或者，
    所述第一动作包括摆臂动作，所述第一动作节点包括手臂摆动在身体前侧的指定位置和/或手臂摆动在身体后侧的指定位置。
  10. 根据权利要求1-9中任一项所述的方法，其特征在于，所述穿戴设备用于佩戴在所述用户的足部或鞋上。
  11. 一种检测穿戴设备佩戴松紧的装置，其特征在于，所述装置包括：
    采集单元，用于检测到穿戴设备处于佩戴状态时，采集用户的运动数据；
    识别单元，用于识别所述用户的运动数据中第一动作的动作数据；
    第一确定单元，用于确定所述第一动作的动作数据对应的穿戴设备佩戴松紧度。
  12. 根据权利要求11所述的装置，其特征在于，所述第一确定单元还用于：
    根据所述第一动作的动作数据，及预设的运动数据与佩戴松紧度的对应关系，确定所述穿戴设备佩戴松紧度。
  13. 根据权利要求12所述的装置，其特征在于，所述第一确定单元还用于：
    识别出所述第一动作的动作数据中第一动作节点的动作数据；
    根据所述第一动作节点的动作数据，确定所述第一动作节点对应的第一特征数据；
    根据所述第一特征数据，及所述预设的运动数据与佩戴松紧度的对应关系，确定穿戴设备佩戴松紧度。
  14. 根据权利要求13所述的装置，其特征在于，
    所述第一特征数据包括：加速度波形的波峰数、角速度波形的波峰数、加速度波形的波谷数、角速度波形的波谷数、加速度波形的峰值、角速度波形的峰值、加速度的均值、角速度的均值、加速度波形的梯度、角速度波形的梯度中的至少一项。
  15. 根据权利要求11所述的装置，其特征在于，所述第一确定单元还用于：
    根据所述第一动作的动作数据，及佩戴松紧模型，确定所述第一动作的动作数据对应的穿戴设备佩戴松紧度；
    其中，所述第一动作的动作数据作为所述佩戴松紧模型的输入，所述穿戴设备佩戴松紧度作为所述佩戴松紧模型的输出。
  16. 根据权利要求11-15中任一项所述的装置，其特征在于，还包括：
    生成单元，用于根据所述穿戴设备佩戴松紧度，生成提示信息，所述提示信息采用预设呈现形式呈现所述穿戴设备佩戴松紧度的检测结果；
    其中，所述预设呈现形式包括以下一项或多项组合：声音呈现形式、文字呈现形式、振动呈现形式和灯光呈现形式。
  17. 根据权利要求11-16中任一项所述的装置，其特征在于，所述穿戴设备佩戴松紧度包括：穿戴设备佩戴正常、穿戴设备佩戴松动和穿戴设备佩戴紧。
  18. 根据权利要求11-17中任一项所述的装置，其特征在于，还包括：
    第二确定单元，用于确定在第一时长内各时刻的穿戴设备佩戴松紧度；
    第三确定单元，用于根据所述第一时长内各时刻的穿戴设备佩戴松紧度，确定穿戴设备佩戴松动的第二时长；
    计算单元，用于根据所述第一时长和所述第二时长，及穿戴设备计算的第一运动能量，计算所述用户在所述第一时长内的第二运动能量；其中，所述第一运动能量是在所述第一时长内所述穿戴设备佩戴状态为正常或紧的情况下计算得到的。
  19. 根据权利要求13所述的装置，其特征在于，所述第一动作包括起跳动作，所述第一动作节点包括足部离开地面和/或足部接触地面；或者，
    所述第一动作包括摆臂动作，所述第一动作节点包括手臂摆动在身体前侧的指定位置和/或手臂摆动在身体后侧的指定位置。
  20. 根据权利要求11-19中任一项所述的装置，其特征在于，所述穿戴设备用于佩戴在所述用户的足部或鞋上。
  21. 一种检测穿戴设备佩戴松紧的系统，其特征在于，所述系统包括：
    穿戴设备，用于：在检测到所述穿戴设备处于佩戴状态时，采集用户的运动数据；识别所述用户的运动数据中第一动作的动作数据；确定所述第一动作的动作数据对应的穿戴设备佩戴松紧度，并将穿戴设备佩戴松紧度发送给非穿戴设备；
    所述非穿戴设备，用于：接收所述穿戴设备佩戴松紧度，并根据所述穿戴设备佩戴松紧度生成提示信息，所述提示信息用于提示用户穿戴设备佩戴松紧度的检测结果。
  22. 一种检测穿戴设备佩戴松紧的系统，其特征在于，所述系统包括：
    穿戴设备，用于：在检测到所述穿戴设备处于佩戴状态时，采集用户的运动数据；将采集到的所述运动数据发送给非穿戴设备；
    所述非穿戴设备，用于：接收所述穿戴设备发送的所述运动数据，并识别所述运动数据中第一动作的动作数据；确定所述第一动作的动作数据对应的穿戴设备佩戴松紧度。
  23. 根据权利要求22所述的系统，其特征在于，
    所述非穿戴设备还用于：根据所述穿戴设备佩戴松紧度生成提示信息，所述提示信息用于提示用户穿戴设备佩戴松紧度的检测结果。
  24. 一种计算机可读存储介质，其特征在于，所述计算机可读存储介质包括计算机指令，当所述计算机指令在电子设备上运行时，使得所述电子设备执行如权利要求1-10 中任一项所述的检测穿戴设备佩戴松紧的方法。
  25. 一种计算机程序产品，其特征在于，当所述程序被处理器调用时，权利要求1-10中任一项所述的检测穿戴设备佩戴松紧的方法被执行。
  26. 一种芯片系统，其特征在于，包括一个或多个处理器，当所述一个或多个处理器执行指令时，所述一个或多个处理器执行如权利要求1-10中任一项所述的检测穿戴设备佩戴松紧的方法。
PCT/CN2022/083467 2021-03-31 2022-03-28 一种检测穿戴设备佩戴松紧的方法、装置和系统 WO2022206703A1 (zh)

Priority Applications (1)

Application Number Priority Date Filing Date Title
EP22778885.8A EP4292519A1 (en) 2021-03-31 2022-03-28 Method, apparatus, and system for detecting the tightness of wearable device

Applications Claiming Priority (2)

Application Number Priority Date Filing Date Title
CN202110347924.9 2021-03-31
CN202110347924.9A CN115147915A (zh) 2021-03-31 2021-03-31 一种检测穿戴设备佩戴松紧的方法、装置和系统

Publications (1)

Publication Number Publication Date
WO2022206703A1 true WO2022206703A1 (zh) 2022-10-06

Family

ID=83403341

Family Applications (1)

Application Number Title Priority Date Filing Date
PCT/CN2022/083467 WO2022206703A1 (zh) 2021-03-31 2022-03-28 一种检测穿戴设备佩戴松紧的方法、装置和系统

Country Status (3)

Country Link
EP (1) EP4292519A1 (zh)
CN (1) CN115147915A (zh)
WO (1) WO2022206703A1 (zh)

Cited By (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN115381409A (zh) * 2022-10-31 2022-11-25 深圳市心流科技有限公司 一种穿戴式检测装置的伸缩速度调控方法
CN115462805A (zh) * 2022-11-09 2022-12-13 深圳市心流科技有限公司 智能穿戴设备的控制方法、装置、智能终端及存储介质

Citations (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN104352227A (zh) * 2014-11-07 2015-02-18 英华达（南京）科技有限公司 环形穿戴设备及其松紧度的控制方法
WO2016102416A1 (en) * 2014-12-22 2016-06-30 Koninklijke Philips N.V. Context informed wearable device
CN106441413A (zh) * 2016-09-19 2017-02-22 广东小天才科技有限公司 穿戴设备佩戴松紧性检测方法和装置
CN109150220A (zh) * 2018-06-27 2019-01-04 努比亚技术有限公司 可穿戴设备及其松紧度的调节方法、计算机存储介质

Patent Citations (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN104352227A (zh) * 2014-11-07 2015-02-18 英华达（南京）科技有限公司 环形穿戴设备及其松紧度的控制方法
WO2016102416A1 (en) * 2014-12-22 2016-06-30 Koninklijke Philips N.V. Context informed wearable device
CN106441413A (zh) * 2016-09-19 2017-02-22 广东小天才科技有限公司 穿戴设备佩戴松紧性检测方法和装置
CN109150220A (zh) * 2018-06-27 2019-01-04 努比亚技术有限公司 可穿戴设备及其松紧度的调节方法、计算机存储介质

Cited By (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN115381409A (zh) * 2022-10-31 2022-11-25 深圳市心流科技有限公司 一种穿戴式检测装置的伸缩速度调控方法
CN115462805A (zh) * 2022-11-09 2022-12-13 深圳市心流科技有限公司 智能穿戴设备的控制方法、装置、智能终端及存储介质

Also Published As

Publication number Publication date
EP4292519A9 (en) 2024-02-21
CN115147915A (zh) 2022-10-04
EP4292519A1 (en) 2023-12-20

Similar Documents

Publication Publication Date Title
WO2022206703A1 (zh) 一种检测穿戴设备佩戴松紧的方法、装置和系统
WO2020151387A1 (zh) 一种基于用户运动状态的推荐方法及电子设备
US8519835B2 (en) Systems and methods for sensory feedback
WO2021036568A1 (zh) 辅助健身的方法和电子装置
US20140350883A1 (en) Platform for Generating Sensor Data
CN113827185A (zh) 穿戴设备佩戴松紧程度的检测方法、装置及穿戴设备
CN111202955A (zh) 运动数据处理方法及电子设备
WO2021213337A1 (zh) 可穿戴电子设备的使用监测方法、介质及其电子设备
WO2021238460A1 (zh) 风险预警方法、风险行为信息获取方法和电子设备
CN115525372B (zh) 显示界面的方法和装置
WO2022213834A1 (zh) 一种运动指导信息的确定方法、电子设备和运动指导系统
CN113996046B (zh) 热身判断方法、装置及电子设备
CN110072295A (zh) 双通道通信方法、装置、第一终端及介质
CN113457106B (zh) 一种跑步姿态检测方法与穿戴设备
US20230402150A1 (en) Adaptive Action Evaluation Method, Electronic Device, and Storage Medium
WO2022042275A1 (zh) 测量距离的方法、装置、电子设备及可读存储介质
WO2021233018A1 (zh) 运动后肌肉疲劳度的检测方法及装置、电子设备
CN113380374B (zh) 基于运动状态感知的辅助运动方法、电子设备及存储介质
CN114100101B (zh) 一种跑步姿态检测方法及设备
WO2023093570A1 (zh) 一种提示方法、装置、电子设备以及计算机可读存储介质
WO2022161027A1 (zh) 动作提示图标序列生成方法、电子设备和可读存储介质
WO2020238894A1 (zh) 运动轨迹记录方法及相关设备
WO2022062978A1 (zh) 数据处理方法及电子设备
WO2020237444A1 (zh) 一种移动终端最大发射功率的控制方法以及移动终端
CN117073713A (zh) 一种计步校准方法、系统和设备

Legal Events

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

Ref document number: 22778885

Country of ref document: EP

Kind code of ref document: A1

WWE Wipo information: entry into national phase

Ref document number: 2022778885

Country of ref document: EP

ENP Entry into the national phase

Ref document number: 2022778885

Country of ref document: EP

Effective date: 20230911

NENP Non-entry into the national phase

Ref country code: DE