Method for detecting wearing state of wearable device
By detecting the wearing status in wearable devices and prompting users to make adjustments, the impact of wearing status on data accuracy is resolved, and the monitoring accuracy of the device under different wearing statuses is improved.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Patents(China)
- Current Assignee / Owner
- BEIJING HONOR DEVICE CO LTD
- Filing Date
- 2022-01-04
- Publication Date
- 2026-07-14
AI Technical Summary
The wearing status of wearable devices has a significant impact on the accuracy of monitoring data, especially when worn too tightly or too loosely, which can lead to large differences in test results.
Wearable devices use data collected by sensors to determine if the wearing status is loose, and then prompt the user to adjust the wearing status through voice, vibration, or display prompts. The device also monitors the user's response over a certain period of time and adjusts the wearing status accordingly to improve data accuracy.
It improves the accuracy of data monitoring of wearable devices under different wearing conditions and reduces data errors caused by wearing discomfort.
Smart Images
Figure CN116421142B_ABST
Abstract
Description
Technical Field
[0001] This application relates to the field of terminal technology, and in particular to a method for detecting the wearing status of a wearable device. Background Technology
[0002] Wearable devices are increasingly popular due to their lightweight and portability, allowing users to wear them anytime, anywhere. Wearable devices can include smart bracelets, smartwatches, Bluetooth headsets, and smart glasses.
[0003] Existing wearable devices can monitor users' physiological data, such as body temperature, heart rate, blood oxygen, blood pressure, and blood sugar. However, when wearable devices are worn too tightly or too loosely, the monitored data varies considerably. Therefore, when using wearable devices for daily monitoring, the test results are greatly affected by the way the wearer is worn. Summary of the Invention
[0004] This application provides a method for detecting the wearing status of a wearable device. After determining that the user is wearing the wearable device in a loose wearing state based on data collected by at least one sensor, the wearable device prompts the user to adjust the wearing status of the wearable device, thereby improving the accuracy of the wearable device detection data.
[0005] To achieve the above objectives, this application adopts the following technical solution:
[0006] In a first aspect, embodiments of this application provide a method for detecting the wearing status of a wearable device, comprising:
[0007] The wearable device collects multiple target data from the wearer according to a preset collection cycle; the target data is used to characterize the wearer's heart rate; the wearable device determines the absolute value of the difference between adjacent target data in the multiple target data, and determines the number of the first absolute values among the absolute values, where adjacent target data are data collected in adjacent time, and the first absolute value is greater than a first threshold; if the number is greater than the first threshold, the wearable device determines the wearing state as a loose wearing state.
[0008] This can be understood as follows: when a wearable device collects multiple target data points within a preset sampling period, if the absolute value of the difference between adjacent target data points exceeds a first threshold, indicating significant fluctuations in the data values corresponding to multiple target data points, the wearable device can determine that the wearing state is loose. Therefore, by adjusting the tightness of the wearable device's fit, the accuracy of the data detected by the wearable device is improved.
[0009] In one possible implementation, the detection method may further include:
[0010] If the number of wearable devices is less than or equal to the first threshold, then the wearable device determines the wearing state as either a tight-fitting state or a normal-fitting state.
[0011] In other words, among the multiple target data collected by the wearable device, the number of adjacent target data with an absolute value greater than the first threshold is small, meaning that the data values corresponding to multiple target data fluctuate less, and the wearable device determines the wearing state as a tight wearing state or a normal wearing state.
[0012] In another possible implementation, the detection method may also include:
[0013] Wearable devices determine the difference between the maximum and minimum values among multiple target data points;
[0014] If the wearable device determines that the difference between the maximum and minimum values is greater than the difference threshold, and the number of such differences is greater than the second threshold, then the wearable device determines that the wearing state is a loose wearing state; the second threshold is less than the first threshold.
[0015] If the wearable device determines that the difference between the maximum and minimum values is greater than the difference threshold, and the number of values is less than or equal to the second threshold, then the wearable device determines the wearing state as either a tight-fitting state or a normal-fitting state.
[0016] In other words, when a wearable device determines that the difference between the maximum and minimum values among multiple target data is large, it indicates that the values of the target data collected by the wearable device fluctuate significantly. In this case, if the number of first absolute values determined by the wearable device is greater than the second threshold, it can be determined that the user's current wearing state of the wearable device is a loose wearing state.
[0017] In another possible implementation, after the wearable device determines the difference between the maximum and minimum values in the target data, the method further includes:
[0018] If the wearable device determines that the difference between the maximum and minimum values is less than or equal to the difference threshold, and the number of differences is greater than the first threshold, then the wearable device determines the wearing state as a loose wearing state.
[0019] If the wearable device determines that the difference between the maximum and minimum values is less than or equal to the difference threshold, and the number of differences is less than or equal to the first number threshold, then the wearable device determines the wearing state as either a tight-fitting state or a normal-fitting state.
[0020] In another possible implementation, after the wearable device determines that the wearing state is a loose wearing state, the detection method may further include:
[0021] The wearable device prompts the user to adjust the wearing status using at least one prompting method within a first preset time period; the at least one prompting method includes: voice prompt, vibration prompt, sound and light prompt, or display prompt information.
[0022] In other words, once the wearable device determines that the wearing state is loose, it can prompt the user to adjust the wearing state. For example, the wearable device can prompt the user through voice, such as by broadcasting the message "To accurately record data, please tighten the device." Alternatively, the wearable device can also prompt the user to adjust the wearing state by vibrating while displaying a prompt message. This application embodiment does not limit the method of the wearable device prompting the user.
[0023] In another possible implementation, after the wearable device prompts the user to adjust the wearing status using at least one prompting method within a first preset duration, the detection method further includes:
[0024] If the wearable device does not receive the first operation from the user within the second preset time period, the wearable device determines whether the number of prompts has reached the threshold. The first operation is the user adjusting the wearing status from a loose wearing status to a tight wearing status or a normal wearing status.
[0025] If the wearable device determines that the number of prompts is less than the threshold, the wearable device will determine the wearing status again after a third preset time period based on the collected target data of the wearer.
[0026] In other words, if a wearable device determines that the user is wearing it in a loose state, and after prompting the user to adjust the wearing state, the wearable device does not receive any such adjustment from the user, then if the number of prompts to the user is less than a threshold, the wearable device can re-detect the wearing state.
[0027] In another possible implementation, after the wearable device prompts the user to adjust the wearing status using at least one prompting method within a first preset duration, the detection method may further include:
[0028] The wearable device responds to the wearer's first action and determines whether the wearing state changes from a loose wearing state to a tight wearing state or a normal wearing state.
[0029] In other words, after the wearable device prompts the user to adjust the wearing status, the wearable device receives the user's operation to adjust the wearing status from a loose wearing state to a tight wearing state or a normal wearing state, and the wearable device's wearing status switches from a loose wearing state to a tight wearing state or a normal wearing state. This improves the accuracy of the wearable device's detection data.
[0030] In another possible implementation, the wearable device collects multiple target data points from the wearer according to a preset collection period, including:
[0031] Wearable devices collect target data from the wearer during exercise according to a preset sampling period.
[0032] In other words, the method for detecting the wearing status of a wearable device according to the embodiments of this application can be applied to situations where the user is exercising, i.e., when the wearable device is in exercise mode. Of course, this detection method can also be applied to wearable devices in sleep mode, normal mode, etc., and is not limited here.
[0033] In another possible implementation, after the wearable device determines that the wearing state is a loose wearing state, the detection method may further include:
[0034] If the wearable device receives the first operation from the user within the second preset time period, the wearable device will no longer prompt the user to adjust the wearing status during this exercise.
[0035] In other words, if the wearable device determines that the wearing state is loose during a workout, and the wearable device receives an operation from the user to adjust the wearing state from loose to tight or normal, the wearable device will not prompt the user to adjust the wearing state again during this workout.
[0036] In another possible implementation, after the wearable device determines that the wearing state is a loose wearing state, the method further includes:
[0037] Wearable devices automatically adjust the tightness of the fit.
[0038] In other words, if the wristband of a wearable device is made of a flexible material and has an automatic stretching function, the wearable device can automatically adjust the tightness of the fit after determining that the wearing state is a loose fit.
[0039] In another possible implementation, the target data is data collected by an optical heart rate sensor.
[0040] In a second aspect, this application provides a wearable device, comprising: a touch screen, the touch screen including a touch sensor and a display screen; one or more processors; a memory; wherein the memory stores one or more computer programs, the one or more computer programs including instructions, which, when executed by the wearable device, cause the wearable device to perform the wearing state detection method as described in any one of the first aspects above.
[0041] Thirdly, this application provides a computer-readable storage medium storing instructions that, when executed on a wearable device, cause the wearable device to perform the wearing state detection method as described in any one of the first aspects.
[0042] Fourthly, this application provides a computer program product, which includes computer instructions that, when executed on a wearable device, cause the wearable device to perform the wearing state detection method as described in any one of the first aspects.
[0043] Understandably, the wearable device described in the second aspect, the computer storage medium described in the third aspect, and the computer program product described in the fourth aspect are all used to execute the corresponding methods provided above. Therefore, the beneficial effects they can achieve can be referred to the beneficial effects in the corresponding methods provided above, and will not be repeated here. Attached Figure Description
[0044] Figure 1 This is a schematic diagram of the hardware structure of a wearable device provided in an embodiment of this application;
[0045] Figure 2 A schematic flowchart illustrating a method for detecting the wearing status of a wearable device provided in an embodiment of this application;
[0046] Figure 3 A schematic diagram of a smartwatch provided as an embodiment of this application;
[0047] Figure 4 A schematic diagram of another smartwatch provided in an embodiment of this application;
[0048] Figure 5 This is a schematic diagram illustrating a usage scenario of a smartwatch provided in an embodiment of this application;
[0049] Figure 6 A flowchart illustrating a method for detecting the wearing status of a smartwatch, as provided in an embodiment of this application;
[0050] Figure 7 A flowchart illustrating another method for detecting the wearing status of a smartwatch provided in an embodiment of this application;
[0051] Figure 8 A schematic diagram of a smartwatch wristband provided in an embodiment of this application;
[0052] Figure 9 This is a schematic diagram of the structure of a wearable device provided in an embodiment of this application. Detailed Implementation
[0053] The technical solutions of the embodiments of this application will be described below with reference to the accompanying drawings. In the description of the embodiments of this application, unless otherwise stated, " / " means "or," for example, A / B can mean A or B; the term "and / or" in this document is merely a description of the relationship between related objects, indicating that three relationships can exist. For example, A and / or B can represent: A existing alone, A and B existing simultaneously, and B existing alone.
[0054] Hereinafter, the terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of indicated technical features. Therefore, a feature defined as "first" or "second" may explicitly or implicitly include one or more of that feature. In the description of embodiments of this application, unless otherwise stated, "a plurality of" means two or more.
[0055] In the embodiments of this application, the terms "exemplary" or "for example" are used to indicate that something is an example, illustration, or description. Any embodiment or design that is described as "exemplary" or "for example" in the embodiments of this application should not be construed as being more preferred or advantageous than other embodiments or design. Specifically, the use of the terms "exemplary" or "for example" is intended to present the relevant concepts in a specific manner.
[0056] This application provides a method for detecting the wearing status of a wearable device. In this method, the wearable device can determine that the user is wearing the wearable device in a loose wearing state based on the data collected by each sensor, and then prompt the user to adjust the wearing status of the wearable device, thereby improving the accuracy of the wearable device detection data.
[0057] For example, the method for detecting the wearing status of wearable devices provided in this application embodiment can be applied to wearable devices with displays such as smartwatches, smart bracelets, and smart glasses, and this application embodiment does not impose any limitations on this.
[0058] Figure 1 This is a schematic diagram of the hardware structure of a wearable device provided in an embodiment of this application. Figure 1As shown, the wearable device 100 may include a processor 110, a memory 120, a display screen 130, a power module 140, a sensor module 150, a positioning module 160, etc. The sensor module 150 may include an optical heart rate sensor 150A, a touch sensor 150B, etc.
[0059] It is understood that the structures illustrated in the embodiments of this application do not constitute a specific limitation on the wearable device 100. In other embodiments of this application, the wearable device 100 may include more or fewer components than illustrated, or combine some components, or split some components, or have different component arrangements. The illustrated components may be implemented in hardware, software, or a combination of software and hardware.
[0060] The processor 110 may include one or more processing units, such as an application processor (AP), a modem processor, an image signal processor (ISP), a controller, a memory, a video codec, a digital signal processor (DSP), etc. These different processing units may be independent devices or integrated into one or more processors.
[0061] The controller can serve as the neural center and command center of the wearable device 100. The controller can generate operation control signals based on instruction opcodes and timing signals to control the fetching and execution of instructions.
[0062] An operating system for electronic device 100 can be installed on the application processor to manage the hardware and software resources of electronic device 100. This includes managing and configuring memory, determining the priority of system resource allocation, controlling input and output devices, operating the network, managing the file system, and managing drivers. The operating system can also provide a user interface for interacting with the system. Various types of software, such as drivers and applications (Apps), can be installed within the operating system.
[0063] Memory 120 is used to store instructions and data. In some embodiments, memory 120 is a cache memory. This memory can store instructions or data that have been used or repeatedly used by processor 110. If processor 110 needs to use the instruction or data again, it can directly retrieve it from memory 120. This avoids repeated accesses, reduces the waiting time of processor 110, and thus improves system efficiency.
[0064] In some embodiments, the memory 120 may also be disposed in the processor 110, that is, the processor 110 includes the memory 120. This application embodiment does not limit this.
[0065] Display screen 130 is used to display images, videos, etc. Display screen 130 includes a display panel. The display panel may be a liquid crystal display (LCD), an organic light-emitting diode (OLED), an active-matrix organic light-emitting diode (AMOLED), a flexible light-emitting diode (FLED), a miniature LED, a microLED, a quantum dot light-emitting diode (QLED), etc. In some embodiments, the wearable device 100 may include one or N displays 130, where N is a positive integer greater than 1.
[0066] The power module 140 can be used to power the various components included in the wearable device 100. In some embodiments, the power module 140 can be a battery, such as a rechargeable battery.
[0067] The 150A optical heart rate sensor is used to measure heart rate.
[0068] Touch sensor 150B, also known as a "touch panel," can be located on display screen 130. The touch sensor 150B and display screen 130 together form a touchscreen, also known as a "touch screen." Touch sensor 150B is used to detect touch operations applied to or near it. The touch sensor can transmit the detected touch operation to the application processor to determine the type of touch event. Visual output related to the touch operation can be provided through display screen 130. In other embodiments, touch sensor 150B may also be located on the surface of wearable device 100, in a different position than display screen 130.
[0069] The sensor module 150 may also include pressure sensors, gyroscope sensors, heart rate sensors, magnetic sensors, acceleration sensors, distance sensors, proximity sensors, temperature sensors, touch sensors, and ambient light sensors.
[0070] A positioning module 160 is used to locate the wearable device 100. In this embodiment, the positioning module 160 can receive data from a global navigation satellite system (GNSS), including latitude and longitude, altitude, etc. The wearable device 100 can obtain its altitude through the GNSS altitude data. The GNSS may include a global positioning system (GPS), a global navigation satellite system (GLONASS), a BeiDou navigation satellite system (BDS), a quasi-zenith satellite system (QZSS), a Galileo satellite navigation system (GSNS), and / or a satellite-based augmentation system (SBAS).
[0071] The technical solutions involved in the following embodiments can all be implemented in the wearable device 100 with the above-described hardware structure.
[0072] In some embodiments, when a user wears a wearable device, the device can determine its wearing status based on data collected by various sensors (e.g., pressure sensors, heart rate sensors, etc.). Wearing status includes loose wearing, normal wearing, and tight wearing. If the wearable device determines that the user is wearing the device in a loose wearing state based on the sensor data, it can notify the user that the wearing status is loose, allowing the user to adjust the wearing position. Therefore, by adjusting the tightness of the wearable device, the accuracy of the monitoring data is improved.
[0073] It should be explained that the above-described method for detecting the wearing status of wearable devices can be applied to wearable devices in any operating mode. These operating modes can include sports mode, sleep mode, normal mode, etc. For example, assuming the wearable device is in sports mode, it determines the wearing status of the wearable device based on data collected by various sensors.
[0074] For ease of understanding, the following describes in detail the method for detecting the wearing status of a wearable device provided in the embodiments of this application, with reference to the accompanying drawings.
[0075] Figure 2 This is a schematic flowchart illustrating a method for detecting the wearing status of a wearable device, as provided in an embodiment of this application. Figure 2 As shown, taking a smartwatch as an example of a wearable device, the detection method may include the following steps:
[0076] Step 201: The smartwatch collects multiple target data from the wearer according to a preset collection cycle.
[0077] The target data is used to characterize the heart rate of the wearer.
[0078] In this embodiment, after the smartwatch is powered on, it can monitor in real time and collect multiple target data points from the user according to a preset collection period. Then, the smartwatch can determine the tightness of the user's fit based on the collected target data.
[0079] As an example, such as Figure 3 As shown, when a user wears the smartwatch 300, the optical heart rate sensor 310 installed in the smartwatch collects data in real time. The smartwatch can then obtain the data collected by the optical heart rate sensor in real time. Furthermore, the smartwatch determines the tightness of the fit based on the data collected by the optical heart rate sensor.
[0080] Among them, optical heart rate sensors are one of the most widely used sensors for heart rate detection in smart wearable devices. They employ photoplethysmography (PPG) to measure heart rate and other biometric indicators. Their working principle is as follows: the optical heart rate sensor shines a capacitive light onto the skin; the light reflected back through the skin tissue is received by the optical heart rate sensor and converted into an electrical signal. This electrical signal is then converted into a digital signal, and the heart rate is calculated based on the absorbance of the blood.
[0081] In one possible scenario, suppose a user wears a smartwatch while exercising, i.e., the smartwatch is in sports mode. The optical heart rate sensor collects data in real time, and the smartwatch detects the user's wearing status during exercise based on the data collected by the optical heart rate sensor.
[0082] As an example, such as Figure 4 As shown, the smartwatch's settings interface can be configured as follows: Figure 4 As shown in Figure (A), in response to the user's operation of the working mode settings interface (e.g., touch, double-tap, or press), the smartwatch displays the working mode settings interface, as shown below. Figure 4 As shown in Figure (B), after receiving the user's command to select the sports mode, the smartwatch displays an "OK" control.Figure 4 As shown in Figure (C), the smartwatch switches to sports mode in response to the user's touch of the "OK" control. In sports mode, the smartwatch can monitor and acquire data from the optical heart rate sensor in real time during exercise. Then, based on this data, the smartwatch can determine the tightness of the watch when worn by the user in sports mode and prompt the user to adjust the fit. This avoids the problem of light leakage between the optical heart rate sensor and the wrist during exercise, which could lead to inaccurate heart rate measurements.
[0083] In this embodiment, the specific process by which the smartwatch determines the user's wearing status based on data collected by the optical heart rate sensor can be found in the following sections. Figure 6 and Figure 7 The introduction process will not be detailed here.
[0084] Step 202: After determining the tightness based on multiple target data, the smartwatch judges whether the tightness has reached the tightness threshold.
[0085] Among them, the tightness threshold is the minimum tightness when the user wears the smartwatch in a loose wearing state.
[0086] In this embodiment of the application, after the smartwatch collects multiple target data, it can determine the tightness of the user wearing the smartwatch based on the multiple target data, and then determine whether the tightness of the smartwatch reaches the tightness threshold based on the tightness of the smartwatch.
[0087] In some embodiments, after collecting multiple target data points, the smartwatch can determine the tightness of the user's wearing of the smartwatch based on the magnitude of the corresponding data values. For example, if the smartwatch determines that the fluctuations in the data values corresponding to the multiple target data points are small, i.e., the differences in the data values are small, the smartwatch can determine that the user is wearing the smartwatch tightly. If the smartwatch determines that the fluctuations in the data values corresponding to the multiple target data points are large, i.e., the differences in the data values are large, the smartwatch can determine that the user is wearing the smartwatch loosely.
[0088] In one possible scenario, if the smartwatch determines that the tightness of the user's smartwatch is within a certain threshold, then the smartwatch determines that the user's current wearing state is a loose wearing state.
[0089] In another possible scenario, if the smartwatch determines that the tightness of the user's smartwatch is not within the tightness threshold, then the smartwatch determines that the user's current wearing status is either normal or tight.
[0090] Step 203: The smartwatch prompts the user that the wearing status is loose.
[0091] In this embodiment, after determining in step 202 that the user is wearing the smartwatch in a loose-wearing state, the smartwatch can notify the user that the wearing state is loose. Here, the smartwatch can notify the user that the current wearing state is loose for a first preset duration.
[0092] As an example, a smartwatch can indicate to the user that the smartwatch is loosely worn by vibrating or displaying a system pop-up message on the screen. Figure 5 As shown, once the smartwatch determines that the user is currently wearing it in a loosely fitted state, it can vibrate while displaying a prompt message: "To accurately record data, please tighten the watch and keep it at least one finger's width away from your joints." For example, the smartwatch can vibrate continuously and display the prompt message for a first preset duration, such as 5 seconds, 10 seconds, or 15 seconds. Furthermore, the user can adjust the tightness of the smartwatch based on the prompt message, changing it from a loosely fitted state to a properly fitted state, thus improving the accuracy of the smartwatch's monitoring data.
[0093] It should be noted that the above example of the smartwatch prompting the user through vibration and display of prompt information is only an exemplary description. The smartwatch may also prompt the user through at least one of the following methods: voice, flashing lights, or beeping sounds. This application embodiment does not limit this.
[0094] Step 204: The smartwatch determines whether it has received the user's operation.
[0095] Among them, the user's operation can be to adjust the wearing status from loose wearing status to tight wearing status or normal wearing status, that is, the user tightens the smartwatch's wristband.
[0096] In this embodiment, after the smartwatch prompts the user that the smartwatch is in a loose wearing state, the smartwatch can determine whether it has received any user input within a second preset time period (e.g., 30 seconds or 1 minute). That is, after the smartwatch prompts the user that the current wearing state is loose, the smartwatch can determine whether the user wants to adjust the wearing state of the smartwatch.
[0097] In some embodiments, the smartwatch receives a user's action within a second preset time period, indicating that the user has promptly adjusted the smartwatch's wearing status. This improves the accuracy of the smartwatch's monitoring data.
[0098] If the smartwatch determines in step 204 that it has not received the user's operation, then step 205 is executed; otherwise, the process ends.
[0099] Step 205: The smartwatch determines whether the number of prompts has reached the threshold.
[0100] The "number of prompts" threshold is a pre-set maximum number of times the smartwatch will prompt the user when it determines that the user is currently wearing the device in a loose-fitting state. For example, the threshold could be 2 or 3 times.
[0101] In this embodiment of the application, if the smartwatch does not receive any operation from the user to change the wearing status of the smartwatch within the second preset time period, that is, the user ignores the prompt from the smartwatch, the smartwatch continues to determine whether the number of prompts has reached the number threshold.
[0102] If the smartwatch determines in step 205 that the number of prompts has reached the threshold, then step 206 is executed; otherwise, the process ends.
[0103] Step 206: After the smartwatch records the number of prompts, it continues to step 201.
[0104] In this embodiment, if the smartwatch determines that the current number of prompts has not reached the threshold, the smartwatch can, after recording the number of prompts already made, re-detect the tightness of the user's wearing of the smartwatch. For example, after recording the number of prompts already made, the smartwatch can re-detect the tightness of the user's wearing of the smartwatch after a third preset time period (e.g., 3 minutes or 5 minutes). That is, the smartwatch restarts the implementation process of step 201.
[0105] This can be understood as follows: to ensure users are aware of the initial notification from the smartwatch, after the initial notification that the wearer is in a loose fit, the smartwatch can re-detect the tightness of the fit. For example, the smartwatch can delay for a period of time before re-detecting the tightness. If the smartwatch determines that the tightness has reached a threshold, it will notify the user again, continuing until the number of notifications reaches a threshold. Alternatively, after notifying the user that the wearer is in a loose fit, if the smartwatch detects the user's instruction to stop notifying or tighten the wristband, it will no longer notify the user.
[0106] In this embodiment, the method by which the smartwatch prompts the user again can be the same as or different from the method used when it first prompts the user; no limitation is made here. For example, if the smartwatch uses vibration and simultaneous display of the prompt information when it first prompts the user, it can also use vibration and simultaneous display of the prompt information when it prompts the user again. Alternatively, the smartwatch can use voice and simultaneous display of the prompt information when it prompts the user again, and so on.
[0107] In one possible scenario of this application embodiment, when a user wears a smartwatch, the smartwatch responds to the user's settings and sets its working mode to sports mode. For example, when a user starts cycling, the smartwatch can respond to the user's settings and set its working mode to sports mode for cycling. During cycling, the sensors in the smartwatch upload the collected data to the smartwatch, allowing the smartwatch to acquire the data collected by each sensor. The smartwatch determines the tightness of the smartwatch worn by the user during cycling based on the data collected by at least one sensor. If the smartwatch determines that the user is wearing the smartwatch in a loose wearing state, it can prompt the user that the current wearing state is loose. If the smartwatch does not receive a user's wristband adjustment operation within a second preset time period, it will check the user's current wearing state again after a third preset time period (e.g., 5 minutes). If the smartwatch again determines that the user's current wearing state is loose, it can prompt the user again. This avoids the situation where the user is unaware of the smartwatch's prompt process when it first prompts them during exercise. If the smartwatch prompts the user a certain number of times (e.g., 3 times), the smartwatch will no longer prompt the user about the current wearing status of the smartwatch during subsequent rides.
[0108] When a user wears the smartwatch in a loose position while cycling, the smartwatch prompts the user to adjust the tightness of the wristband. This avoids errors in the physiological data monitored by the smartwatch during cycling, such as preventing the smartwatch from detecting a heart rate that is too high or too low, thus improving the accuracy of the smartwatch's monitoring data.
[0109] In this embodiment, during the process of a user wearing a smartwatch, the smartwatch determines that the user is wearing the smartwatch in a loose wearing state based on data collected by at least one sensor, and promptly prompts the user to adjust the wearing state of the smartwatch, thereby improving the accuracy of the smartwatch in monitoring the user's physiological data.
[0110] As an example, the following is combined with Figure 6 and Figure 7The process by which a smartwatch determines a user's wearing status based on data collected by an optical heart rate sensor is described in detail.
[0111] Figure 6 This is a flowchart illustrating a method for detecting the wearing status of a smartwatch, as provided in an embodiment of this application. Figure 6 As shown, the process may include the following steps:
[0112] Step 601: The smartwatch collects data via an optical heart rate sensor.
[0113] In this embodiment, after the user wears the smartwatch, the optical heart rate sensor shines a capacitive light onto the skin. The light reflected back through the skin tissue is received by the optical heart rate sensor and converted into an electrical signal. The optical heart rate sensor then reports this electrical signal to the smartwatch. The smartwatch then receives the data collected by the optical heart rate sensor.
[0114] Here, the optical heart rate sensor can acquire data at the first frequency.
[0115] In some embodiments, assuming the sampling frequency of the optical heart rate sensor is a second frequency (e.g., 100Hz), the smartwatch downsamples the frequency of the data collected by the optical heart rate sensor, reducing the sampling frequency of the optical heart rate sensor to a first frequency (e.g., 25Hz).
[0116] Step 602: The smartwatch acquires data within the fourth preset time period.
[0117] In this embodiment, the smartwatch acquires data from an optical heart rate sensor at a second frequency until it acquires data within a fourth preset time period. For example, the smartwatch acquires data from the optical heart rate sensor over a period of 30 seconds.
[0118] This can be understood as follows: when a smartwatch acquires a large amount of data from its optical heart rate sensor, the smartwatch can determine the user's wearing status more accurately based on this data.
[0119] Step 603: The smartwatch counts the number of adjacent data whose absolute difference is greater than the first threshold.
[0120] The first threshold is a pre-set value that determines the data collected by the optical heart rate sensor as a large glitch signal. In this embodiment, after the smartwatch acquires the data collected by the optical heart rate sensor within a fourth preset time period, it counts the number of times the absolute value of the difference between adjacent data points is greater than the first threshold. That is, the smartwatch counts the number of electrical signals collected by the optical heart rate sensor within the fourth preset time period that are large glitch signals.
[0121] Step 604: The smartwatch determines whether the number is greater than the first threshold.
[0122] The first threshold is a pre-set minimum value used to determine that the smartwatch is currently in a loose-wearing state.
[0123] In this embodiment of the application, after the smartwatch determines the number of times the absolute value of the difference between adjacent data collected by the optical heart rate sensor is greater than a first threshold, it determines whether the number is greater than the first threshold.
[0124] If, in step 604, the number of times the absolute value of the difference between adjacent data is greater than the first threshold is greater than the first threshold, then step 605 is executed; otherwise, step 606 is executed.
[0125] Step 605: The smartwatch determines that the current wearing status is a loose wearing status.
[0126] Step 606: The smartwatch determines whether the current wearing status is tight wearing or normal wearing.
[0127] In this embodiment, if the smartwatch determines that the number of absolute values of the differences between adjacent data that are greater than a first threshold is greater than a first threshold value, then the user's wearing state of the smartwatch is determined to be a loose wearing state. If the smartwatch determines that the number of absolute values of the differences between adjacent data that are greater than a first threshold is less than or equal to the first threshold value, then the user's wearing state of the smartwatch is determined to be a tight wearing state or a normal wearing state.
[0128] As an example, suppose the first threshold is 6*10⁴ and the first number threshold is 300. The smartwatch acquires electrical signals from the optical heart rate sensor at a sampling frequency of 25Hz over 30 seconds. That is, the smartwatch can acquire 750 data points from the optical heart rate sensor. The smartwatch counts the number of adjacent data points whose absolute difference is greater than 6*10⁴. If the smartwatch determines that the number of adjacent data points with an absolute difference greater than 6*10⁴ is greater than 300 (for example, 350), then the smartwatch determines that the user is wearing the smartwatch in a loose wearing state. If the smartwatch determines that the number of adjacent data points with an absolute difference greater than 6*10⁴ is less than or equal to 300 (for example, 100), then the smartwatch determines that the user is wearing the smartwatch in a tight wearing state or a normal wearing state.
[0129] Understandably, when a user wears a smartwatch loosely, there is a higher probability of light leakage between the smartwatch and the wrist, resulting in more large spikes in the data collected by the optical heart rate sensor. When a user wears a smartwatch tightly or normally, the probability of light leakage between the smartwatch and the wrist is lower, and there are fewer large spikes in the data collected by the optical heart rate sensor.
[0130] It should be noted that the values in the above examples are only for illustrative purposes. The specific first threshold and first number threshold need to be determined according to the actual scenario in which the user wears the smartwatch, and are not limited here.
[0131] Figure 7 This is a flowchart illustrating another method for detecting the wearing status of a smartwatch, provided in an embodiment of this application. Figure 7 As shown, the process may also include the following steps:
[0132] Step 701: The smartwatch collects data via an optical heart rate sensor.
[0133] Step 702: The smartwatch acquires data within the fourth preset time period.
[0134] Step 703: The smartwatch counts the number of adjacent data whose absolute values of differences are greater than the first threshold.
[0135] In the embodiments of this application, the implementation process of steps 701 to 703 can be referred to the implementation process of steps 601 to 603 described above, and will not be repeated here.
[0136] Step 704: The smartwatch determines whether the difference between the maximum and minimum values is greater than the difference threshold.
[0137] The difference threshold can be a value determined based on the magnitude of the data collected by the optical heart rate sensor within a fourth preset time period.
[0138] In this embodiment, after the smartwatch acquires the data collected by the optical heart rate sensor within a fourth preset time period, it determines the maximum and minimum values of the data within the fourth preset time period and calculates the difference between the maximum and minimum values. After determining the difference between the maximum and minimum values of the data collected by the optical heart rate sensor, the smartwatch determines whether the difference between the maximum and minimum values is greater than a difference threshold.
[0139] If the smartwatch determines in step 704 that the difference between the maximum and minimum values is less than the difference threshold, then proceed to step 705; otherwise, proceed to step 706.
[0140] Step 705: The smartwatch determines whether the number is greater than the first threshold.
[0141] In the embodiments of this application, the implementation process of step 705 can be referred to the implementation process of step 604 above, and will not be repeated here.
[0142] Step 706: The smartwatch determines whether the number is greater than the second threshold.
[0143] The second threshold is defined as the minimum value of the loose-wearing state of the smartwatch when the difference between the maximum and minimum values is less than a threshold value. The second threshold is less than the first threshold. For example, if the first threshold is 300, the second threshold is 240.
[0144] Understandably, when the difference between the maximum and minimum values of the data collected by the optical heart rate sensor from a smartwatch exceeds a threshold, it indicates that the data collected by the smartwatch fluctuates significantly. In this case, the smartwatch can determine that the user is currently wearing the smartwatch in a loose-fitting state when the number of times the absolute value of the difference between adjacent data points exceeds the first threshold is greater than the second threshold.
[0145] Step 707: The smartwatch determines that the current wearing status is a loose wearing status.
[0146] Step 708: The smartwatch determines whether the current wearing status is tight wearing or normal wearing.
[0147] In one possible scenario, if the smartwatch determines that the difference between the maximum and minimum values of the data collected by the optical heart rate sensor is less than or equal to a difference threshold, and the smartwatch determines that the number of adjacent data with absolute differences greater than a first threshold is greater than a first number threshold, then the smartwatch determines that the current wearing state is a loose wearing state.
[0148] As an example, suppose the first threshold is 6*10⁴, the first number threshold is 300, and the difference threshold is 2*10⁶. The smartwatch acquires electrical signals from the optical heart rate sensor at a sampling frequency of 25Hz over 30 seconds. That is, the smartwatch can acquire 750 data points from the optical heart rate sensor. The smartwatch calculates the difference between the maximum and minimum values among these 750 data points. If the smartwatch determines that the difference between the maximum and minimum values is greater than 2*10⁶, and the number of adjacent data points with absolute differences greater than 6*10⁴ is greater than 300 (for example, if the number of adjacent data points with absolute differences greater than 6*10⁴ is 350), then the smartwatch determines that the user is wearing the smartwatch in a loose-fitting state.
[0149] In another possible scenario, if the smartwatch determines that the difference between the maximum and minimum values of the data collected by the optical heart rate sensor is less than or equal to the difference threshold, and the smartwatch determines that the number of adjacent data with absolute differences greater than the first threshold is less than or equal to the first number threshold, then the smartwatch determines that the current wearing state is either a tight wearing state or a normal wearing state.
[0150] As an example, if the smartwatch determines that the difference between the maximum and minimum values is less than 2*106 (e.g., the difference between the maximum and minimum values is 1.5*106), and the number of adjacent data with absolute differences greater than 6*104 is less than 300 (e.g., the number of adjacent data with absolute differences greater than 6*104 is 280), then the smartwatch determines that the user is wearing the smartwatch in a tight-fitting state or a normal-fitting state.
[0151] In another possible scenario, if the smartwatch determines that the difference between the maximum and minimum values of the data collected by the optical heart rate sensor is greater than a difference threshold, and the smartwatch determines that the number of absolute values of the differences between adjacent data that are greater than the first threshold is greater than the second threshold, then the smartwatch determines that the current wearing state is a loose wearing state.
[0152] As an example, if the smartwatch determines that the difference between the maximum and minimum values is greater than 2*106 (e.g., the difference between the maximum and minimum values is 3*106), and the number of absolute differences between adjacent data points greater than 6*104 is greater than 240 (e.g., the number of absolute differences between adjacent data points greater than 6*104 is 280), then the smartwatch determines that the user is wearing the smartwatch in a loose-wearing state.
[0153] In another possible scenario, if the smartwatch determines that the difference between the maximum and minimum values of the data collected by the optical heart rate sensor is greater than or equal to the difference threshold, and the smartwatch determines that the number of adjacent data with absolute differences greater than the first threshold is less than or equal to the second threshold, then the smartwatch determines that the current wearing state is either a tight wearing state or a normal wearing state.
[0154] As an example, if the smartwatch determines that the difference between the maximum and minimum values is greater than 2*106 (e.g., the difference between the maximum and minimum values is 3*106), and the number of absolute differences between adjacent data points greater than 6*104 is less than 240 (e.g., the number of absolute differences between adjacent data points greater than 6*104 is 180), then the smartwatch determines that the user is wearing the smartwatch in a tight-fitting state or a normal-fitting state.
[0155] It should be noted that the description of the smartwatch determining the tightness of the user's wear based on data collected by the optical heart rate sensor is merely an illustrative example and is not intended to limit the scope of the invention. For instance, the smartwatch could also determine the tightness of the user's wear based on data collected by at least one of the following sensors: a pressure sensor, an accelerometer, a temperature sensor, and a gyroscope. This embodiment of the invention does not limit the scope of the invention.
[0156] In practical applications, after the smartwatch indicates that the wearing status is loose, the user can manually adjust the tightness of the smartwatch strap.
[0157] In practical applications, after the smartwatch prompts the user that the wearing condition is loose, and the user confirms the adjustment, the smartwatch automatically adjusts the tightness according to its current operating mode. That is, in this embodiment, the smartwatch strap can be an automatically retractable strap. For the same user, the wrist circumference is fixed. The smartwatch controls the wearing condition by controlling the degree of retraction of the strap, thus automatically adjusting the tightness. This eliminates the need for manual adjustment of the strap, simplifying the user experience and improving user satisfaction.
[0158] The optimal tightness for a smartwatch varies depending on its operating mode. For example, in sports mode, the optimal tightness is determined by a first parameter; in normal mode, it's determined by a second parameter; and in sleep mode, it's determined by a third parameter. The first parameter is less than the second, and the second is less than the third.
[0159] It's important to explain that when a smartwatch is in sleep mode, it needs to be worn relatively loosely on the wrist to ensure sleep quality and freedom of movement. Conversely, during exercise, it needs to be worn more tightly to prevent slipping. Therefore, when the smartwatch is in different modes, it automatically adjusts the strap tightness differently depending on whether it's in a loose or relaxed position.
[0160] As an example, such as Figure 8As shown, assuming the smartwatch's wristband is made of a flexible material with an automatic stretching function, once the smartwatch determines that the user is currently wearing it in a loose wearing state, the smartwatch can automatically adjust the tightness of the wristband according to the current working mode.
[0161] In summary, in this embodiment, during the user's wearing of the smartwatch, the smartwatch determines the user's wearing status based on data collected by the optical heart rate sensor. When the smartwatch determines the wearing status is loose, it promptly prompts the user to adjust the tightness of the smartwatch. This avoids the problem of the smartwatch monitoring the user's heart rate being too low or too high due to the user wearing the smartwatch too loosely, thus improving the accuracy of the smartwatch's heart rate monitoring.
[0162] like Figure 9 As shown, Figure 9 This is a schematic diagram of a wearable device provided in an embodiment of this application. The wearable device can be a smartwatch, a smart bracelet, or something similar. Specifically, the wearable device may include: a touchscreen 901, which includes a touch sensor 906 and a display screen 907; one or more processors 902; a memory 903; one or more application programs (not shown); and one or more computer programs 904. These components can be connected via one or more communication buses 905. The one or more computer programs 904 are stored in the memory 903 and configured to be executed by the one or more processors 902. The one or more computer programs 904 include instructions that can be used to perform the relevant steps in the above embodiments.
[0163] It is understood that the aforementioned wearable devices, etc., include hardware structures and / or software modules corresponding to perform each function in order to achieve the above-mentioned functions. Those skilled in the art should readily recognize that, based on the units and algorithm steps of the various examples described in conjunction with the embodiments disclosed herein, the embodiments of this application can be implemented in hardware or a combination of hardware and computer software. Whether a function is executed in hardware or by computer software driving hardware depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of the embodiments of this invention.
[0164] This application embodiment can divide the wearable device and the like into functional modules according to the above method examples. For example, each function can be divided into its own functional module, or two or more functions can be integrated into one processing module. The integrated module can be implemented in hardware or as a software functional module. It should be noted that the module division in this embodiment is illustrative and only represents one logical functional division; other division methods may be used in actual implementation.
[0165] When each functional module is divided according to its corresponding function, the wearable device involved in the above embodiments can be illustrated as follows: the wearable device may include a display unit, a transmission unit, and a processing unit, etc. It should be noted that all relevant content of each step involved in the above method embodiments can be referenced from the functional description of the corresponding functional module, and will not be repeated here.
[0166] This application also provides a wearable device, including one or more processors and one or more memories. The one or more memories are coupled to the one or more processors, and the one or more memories are used to store computer program code, including computer instructions. When the one or more processors execute the computer instructions, the wearable device performs the aforementioned method steps to implement the wearing state detection method in the above embodiments.
[0167] Embodiments of this application also provide a computer-readable storage medium storing computer instructions. When the computer instructions are executed on a wearable device, the wearable device performs the aforementioned method steps to implement the wearing state detection method in the above embodiments.
[0168] Embodiments of this application also provide a computer program product, which includes computer instructions that, when executed on a wearable device, cause the wearable device to perform the aforementioned method steps to implement the wearing state detection method in the above embodiments.
[0169] In addition, embodiments of this application also provide an apparatus, which may specifically be a chip, component or module. The apparatus may include a connected processor and a memory; wherein the memory is used to store computer execution instructions. When the apparatus is running, the processor may execute the computer execution instructions stored in the memory to cause the apparatus to perform the wearing state detection method performed by the wearable device in the above method embodiments.
[0170] In this embodiment, the wearable device, computer-readable storage medium, computer program product or apparatus are all used to execute the corresponding methods provided above. Therefore, the beneficial effects they can achieve can be referred to the beneficial effects in the corresponding methods provided above, and will not be repeated here.
[0171] Through the above description of the embodiments, those skilled in the art will clearly understand that, for the sake of convenience and brevity, only the division of the above functional modules is used as an example. In practical applications, the above functions can be assigned to different functional modules as needed, that is, the internal structure of the device can be divided into different functional modules to complete all or part of the functions described above. The specific working process of the system, device, and unit described above can be referred to the corresponding process in the foregoing method embodiments, and will not be repeated here.
[0172] In the embodiments of this application, the functional units can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or as a software functional unit.
[0173] If the integrated unit is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solutions of the embodiments of this application, essentially, or the parts that contribute to the prior art, or all or part of the technical solutions, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) or processor to execute all or part of the steps of the methods described in the various embodiments of this application. The aforementioned storage medium includes various media capable of storing program code, such as flash memory, portable hard disk, read-only memory, random access memory, magnetic disk, or optical disk.
[0174] The above description is merely a specific embodiment of this application, but the scope of protection of this application is not limited thereto. Any changes or substitutions within the technical scope disclosed in this application should be included within the scope of protection of this application. Therefore, the scope of protection of this application should be determined by the scope of the claims.
Claims
1. A method for detecting the wearing status of a wearable device, characterized in that, The method includes: The wearable device collects multiple target data points from the wearer according to a preset collection period; the target data points are used to characterize the wearer's heart rate. The wearable device determines the absolute value of the difference between adjacent target data in the plurality of target data, and determines the number of first absolute values among the absolute values, wherein the adjacent target data are data collected at adjacent times, and the first absolute value is greater than a first threshold; If the number is greater than the first threshold, the wearable device determines the wearing state as a loose wearing state.
2. The method according to claim 1, characterized in that, The method further includes: If the wearable device determines that the number is less than or equal to the first threshold number, then the wearable device determines the wearing state as either a tight-fitting state or a normal-fitting state.
3. The method according to claim 1, characterized in that, The method further includes: The wearable device determines the difference between the maximum and minimum values among the plurality of target data; If the wearable device determines that the difference between the maximum and minimum values is greater than a difference threshold, and the number of such differences is greater than a second threshold, then the wearable device determines that the wearing state is a loose wearing state; the second threshold is less than the first threshold. If the wearable device determines that the difference between the maximum and minimum values is greater than the difference threshold, and the number is less than or equal to the second number threshold, then the wearable device determines the wearing state as a tight wearing state or a normal wearing state.
4. The method according to claim 3, characterized in that, After the wearable device determines the difference between the maximum and minimum values among the plurality of target data, the method further includes: If the wearable device determines that the difference between the maximum and minimum values is less than or equal to the difference threshold, and the number of values is greater than the first number threshold, then the wearable device determines that the wearing state is a loose wearing state. If the wearable device determines that the difference between the maximum and minimum values is less than or equal to the difference threshold, and the number of values is less than or equal to the first number threshold, then the wearable device determines that the wearing state is a tight wearing state or a normal wearing state.
5. The method according to any one of claims 1-4, characterized in that, After the wearable device determines that the wearing state is a loose wearing state, the method further includes: The wearable device prompts the user to adjust the wearing status using at least one prompting method within a first preset time period; the at least one prompting method includes: voice prompt, vibration prompt, sound and light prompt, or display prompt information.
6. The method according to claim 5, characterized in that, After the wearable device prompts the user to adjust the wearing status using at least one prompting method within a first preset time period, the method further includes: If the wearable device does not receive the first operation from the user within the second preset time period, the wearable device determines whether the number of prompts has reached the threshold; the first operation is the user adjusting the wearing state from the loose wearing state to the tight wearing state or the normal wearing state. If the wearable device determines that the number of prompts is less than the number threshold, then after a third preset time period, the wearable device will again determine the wearing status of the wearable device based on the multiple target data collected from the wearer.
7. The method according to claim 5, characterized in that, After the wearable device prompts the user to adjust the wearing status using at least one prompting method within a first preset time period, the method further includes: The wearable device responds to the first operation of the wearer and determines whether the wearing state changes from a loose wearing state to a tight wearing state or a normal wearing state.
8. The method according to any one of claims 1-4, characterized in that, The wearable device collects multiple target data points from the wearer according to a preset collection period, including: The wearable device collects target data from the wearer during exercise according to a preset sampling period.
9. The method according to claim 8, characterized in that, After the wearable device determines that the wearing state is a loose wearing state, the method further includes: If the wearable device receives the first operation from the user within a second preset time period, the wearable device will no longer prompt the user to adjust the wearing status during this exercise.
10. The method according to any one of claims 1-4, characterized in that, After the wearable device determines that the wearing state is a loose wearing state, the method further includes: The wearable device automatically adjusts the tightness of the fit.
11. The method according to any one of claims 1-4, characterized in that, The target data is data collected by an optical heart rate sensor.
12. A wearable device, characterized in that, include: A touchscreen, comprising a touch sensor and a display screen; One or more processors; Memory; The memory stores one or more computer programs, the one or more computer programs including instructions that, when executed by the wearable device, cause the wearable device to perform the wearing state detection method as described in any one of claims 1-11.
13. A computer-readable storage medium storing instructions, characterized in that, When the instruction is executed on the wearable device, the wearable device performs the wearing state detection method as described in any one of claims 1-11.
14. A computer program product, characterized in that, The computer program product includes computer instructions that, when executed on a wearable device, cause the wearable device to perform the method for detecting the wearing state as described in any one of claims 1-11.