Wearable device wearing state detection method and device, and wearable device

Abstract

Embodiments of the present application provide a wearable device wearing state detection method and device and a wearable device. The method comprises obtaining pulse wave sampling data of at least two consecutive heartbeat cycles, wherein the pulse wave sampling data of each heartbeat cycle comprises a plurality of pulse wave sampling signals; obtaining a first signal set composed of pulse wave sampling signals satisfying a first preset condition and a second signal set composed of pulse wave sampling signals satisfying a second preset condition in a plurality of heartbeat cycles; and determining whether the wearable device is in a wearing state according to the first signal set and the second signal set. In this way, whether the pulse wave sampling data of a plurality of heartbeat cycles is periodic pulse wave signal data can be determined according to the first signal set and the second signal set of at least two consecutive heartbeat cycles, and then whether the wearable device is in a wearing state can be determined. This can solve the problem of not being conducive to improving detection accuracy, and has the effect of improving wearing state detection accuracy.

Description

Technical Field

[0001] This application relates to the field of electronic equipment technology, specifically to a method, apparatus, and wearable device for detecting the wearing status of a wearable device. Background Technology

[0002] With the continuous advancement of technology, wearable devices, such as smartwatches, wristbands, and smart earphones, are no longer limited to functions like checking time, timing, and step counting. As people pay more attention to their health, some wearable devices have added health monitoring functions, such as heart rate monitoring, allowing users to understand their health status anytime without going to the hospital, bringing great convenience to daily life. During the use of wearable devices, it is necessary to detect their wearing status. When the wearable device is worn, it enters measurement mode to ensure the normal operation of various functions, such as heart rate and blood oxygen monitoring; when the wearable device is not worn, it enters low-power mode to disable various timed monitoring functions, thereby reducing the device's power consumption and extending the usage time on a single charge.

[0003] The first existing method for detecting wearing status uses an infrared light source to detect distance and determine whether the wearable device is being worn. However, this method cannot distinguish whether the object approaching the wearable device is the target wearing area or another part of the human body, which is not conducive to improving the detection accuracy. The second existing method for detecting wearing status uses a PPG signal (PhotoPlethysmoGraph) measurement light source to detect object occlusion. It determines whether the wearable device is being worn by checking whether an object is detected. However, this method cannot distinguish whether the occluding object is the target wearing area, another part of the human body, or a non-human body, which is also not conducive to improving the detection accuracy. Summary of the Invention

[0004] In view of the above problems, this application provides a method, apparatus and wearable device for detecting the wearing status of a wearable device to solve the above technical problems.

[0005] In a first aspect, embodiments of this application provide a method for detecting the wearing status of a wearable device, including:

[0006] Acquire pulse wave sampling data for at least two consecutive heartbeat cycles, wherein the pulse wave sampling data for each heartbeat cycle includes multiple pulse wave sampling signals acquired at a first sampling frequency;

[0007] For multiple heartbeat cycles, a first signal set composed of pulse wave sampling signals that satisfy a first preset condition and a second signal set composed of pulse wave sampling signals that satisfy a second preset condition are obtained in each heartbeat cycle.

[0008] Whether the wearable device is in a wearing state is determined based on the first signal set and the second signal set of each heartbeat cycle.

[0009] Optionally, determining whether the wearable device is in a wearing state based on the first signal set and the second signal set of each heartbeat cycle includes:

[0010] If the first difference in each heartbeat cycle is less than a first preset threshold, then the wearable device is determined to be in a wearing state, wherein the first difference is the difference between the number of all pulse wave sampled signals in the first signal set and the number of all pulse wave sampled signals in the second signal set in the corresponding heartbeat cycle.

[0011] Optionally, determining whether the wearable device is in a wearing state based on the first signal set and the second signal set of each heartbeat cycle includes:

[0012] If the first difference in each heartbeat cycle is less than the first preset threshold and the second and third differences in each two adjacent heartbeat cycles are less than the second preset threshold, then the wearable device is determined to be in a wearing state. The second difference is the difference in the number of pulse wave sampling signals in all the first signal sets in two adjacent heartbeat cycles, and the third difference is the difference in the number of pulse wave sampling signals in all the second signal sets in two adjacent heartbeat cycles.

[0013] Optionally, determining whether the wearable device is in a wearing state based on the first signal set and the second signal set of each heartbeat cycle further includes:

[0014] If the first difference of any of the heartbeat cycles is greater than or equal to the first preset threshold, then it is determined that the wearable device is in an unworn state, and the pulse wave sampling signal is acquired at the first sampling frequency, and the ambient light signal is acquired.

[0015] When the pulse wave sampling signal is greater than the first signal threshold and the ambient light signal is less than the second signal threshold, the step of acquiring pulse wave sampling data for at least two consecutive heartbeat cycles continues.

[0016] Optionally, acquiring the pulse wave sampling signal at the first sampling frequency and acquiring the ambient light signal includes:

[0017] The pulse wave sampling signal is acquired at the first sampling frequency until a first preset time has elapsed;

[0018] Acquire the ambient light signal.

[0019] Optionally, the step of acquiring a first signal set composed of pulse wave sampling signals satisfying a first preset condition and a second signal set composed of pulse wave sampling signals satisfying a second preset condition for multiple heartbeat cycles includes:

[0020] The maximum and minimum values ​​of the plurality of pulse wave sampling signals for each heartbeat cycle are obtained respectively;

[0021] A first signal value corresponding to the heartbeat cycle is determined based on the maximum value and the first coefficient, and a second signal value corresponding to the heartbeat cycle is determined based on the minimum value and the second coefficient.

[0022] Obtain the first signal set composed of the pulse wave sampled signals that are greater than the first signal value in the heartbeat cycle;

[0023] The second signal set is obtained, which consists of the pulse wave sampling signals that are less than the second signal value in the heartbeat cycle.

[0024] Optionally, before acquiring, for multiple heartbeat cycles, a first signal set composed of pulse wave sampling signals satisfying a first preset condition and a second signal set composed of pulse wave sampling signals satisfying a second preset condition, the method further includes:

[0025] Determine whether the pulse wave sampling data of the heartbeat cycle meets the wearing status detection conditions.

[0026] Optionally, determining whether the pulse wave sampling data of the heartbeat cycle meets the wearing status detection conditions includes:

[0027] Obtain the average signal value of the plurality of pulse wave sampling signals of the heartbeat cycle;

[0028] The average value and standard deviation of the signal mean corresponding to multiple heartbeat cycles are obtained respectively, and the first signal range is determined based on the average value and standard deviation;

[0029] When the average signal value of all heartbeat cycles is within the first signal range, it is determined that the pulse wave sampling data of the heartbeat cycle meets the wearing status detection conditions.

[0030] Optionally, determining whether the pulse wave sampling data of the heartbeat cycle meets the wearing status detection conditions further includes:

[0031] When the mean value of the signal in any of the heartbeat cycles is not within the first signal range, it is determined that the pulse wave sampling data of the heartbeat cycle does not meet the wearing status detection conditions.

[0032] Continue with the steps to acquire pulse wave sampling data for at least two consecutive heartbeat cycles.

[0033] Optionally, before acquiring pulse wave sampling data for at least two consecutive heartbeat cycles, the method further includes:

[0034] The pulse wave sampling signal is acquired at the second sampling frequency to acquire the ambient light signal;

[0035] When the pulse wave sampling signal is greater than a first signal threshold and the ambient light signal is less than a second signal threshold, the sampling frequency of the pulse wave sampling signal is adjusted to the first sampling frequency, wherein the second sampling frequency is less than the first sampling frequency.

[0036] Optionally, after determining whether the wearable device is in a wearing state based on the first signal set and the second signal set of each heartbeat cycle, the method further includes:

[0037] When it is determined that the wearable device is in a wearing state, the sampling frequency of the pulse wave sampling signal is adjusted to a third sampling frequency, wherein the third sampling frequency is greater than the first sampling frequency.

[0038] Optionally, after adjusting the sampling frequency of the pulse wave sampling signal to the third sampling frequency, the method further includes:

[0039] The pulse wave sampling signal is acquired at the third sampling frequency to acquire the ambient light signal;

[0040] When the pulse wave sampling signal is less than the third signal threshold or the ambient light signal is greater than the fourth signal threshold, it is determined that the wearable device is not being worn, and the sampling frequency of the pulse wave sampling signal is adjusted to the second sampling frequency.

[0041] Secondly, embodiments of this application also provide a wearable device for detecting the wearing status of a wearable device, comprising:

[0042] The acquisition module is used to acquire pulse wave sampling data for at least two consecutive heartbeat cycles, wherein the pulse wave sampling data for each heartbeat cycle includes multiple pulse wave sampling signals acquired at a first sampling frequency.

[0043] The analysis module is used to acquire, for multiple heartbeat cycles, a first signal set composed of pulse wave sampling signals that satisfy a first preset condition and a second signal set composed of pulse wave sampling signals that satisfy a second preset condition.

[0044] The detection module is used to determine the wearing status of the wearable device based on the first signal set and the second signal set of each heartbeat cycle.

[0045] Thirdly, embodiments of this application also provide a wearable device, including: a processor and a memory coupled to the processor, the memory storing program instructions executable by the processor; when the processor executes the program instructions stored in the memory, it implements the above-described method for detecting the wearing status of the wearable device.

[0046] The wearable device wearing status detection method, apparatus, and wearable device provided in this application acquire pulse wave sampling data for at least two consecutive heartbeat cycles. Each heartbeat cycle pulse wave sampling data includes multiple pulse wave sampling signals acquired at a first sampling frequency. A first signal set consisting of pulse wave sampling signals satisfying a first preset condition and a second signal set consisting of pulse wave sampling signals satisfying a second preset condition are acquired from the multiple heartbeat cycles. The wearable device is determined to be in a wearing state based on the first signal set and the second signal set from the multiple heartbeat cycles. Through this method, the pulse wave sampling data for multiple heartbeat cycles can be determined to be periodic pulse wave signal data based on the first signal set and the second signal set from at least two consecutive heartbeat cycles, thereby determining whether the wearable device is in a wearing state. This solves the problem of hindering the improvement of detection accuracy and has the effect of improving the accuracy of wearing status detection.

[0047] These or other aspects of this application will become more apparent in the following description of the embodiments. Attached Figure Description

[0048] To more clearly illustrate the technical solutions in the embodiments of this application, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0049] Figure 1 The illustration shows an application scenario of the wear status detection method for wearable devices provided in this application embodiment.

[0050] Figure 2A schematic flowchart of the wear status detection method for wearable devices provided in an embodiment of this application is shown.

[0051] Figure 3 This diagram illustrates the signal intensity changes of the pulse wave signal during a heartbeat cycle.

[0052] Figure 4 A schematic diagram of the wear status detection device for wearable devices provided in an embodiment of this application is shown.

[0053] Figure 5 A schematic diagram of the structure of a wearable device provided in an embodiment of this application is shown. Detailed Implementation

[0054] The embodiments of this application are described in detail below. Examples of the embodiments are shown in the accompanying drawings, wherein the same or similar reference numerals denote the same or similar elements or elements having the same or similar functions throughout. The embodiments described below with reference to the accompanying drawings are exemplary and are only used to explain this application, and should not be construed as limiting this application.

[0055] To enable those skilled in the art to better understand the solutions of this application, the technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only a part of the embodiments of this application, and not all of them. All other embodiments obtained by those skilled in the art based on the embodiments of this application without creative effort are within the scope of protection of this application.

[0056] In the embodiments of this application, it should be noted that, in this document, relational terms such as first and second are used only to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations.

[0057] Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes said element.

[0058] In the description of the embodiments in this application, the words "example" or "for example" are used to indicate exemplification, illustration, or description. Any embodiment or design described as "example" or "for example" in the embodiments of this application is not to be construed as being more preferred or having more advantages than another embodiment or design. The use of the words "example" or "for example" is intended to present relative concepts in a clear manner.

[0059] Furthermore, in the embodiments of this application, "multiple" refers to two or more. Therefore, in the embodiments of this application, "multiple" can also be understood as "at least two". "At least one" can be understood as one or more, such as one, two, or more. For example, including at least one means including one, two, or more, and is not limited to which ones are included. For example, including at least one of A, B, and C, then it could include A, B, C, A and B, A and C, B and C, or A and B and C.

[0060] It should be noted that in the embodiments of this application, "and / or" describes the relationship between associated objects, indicating that there can be three relationships. For example, A and / or B can represent: A existing alone, A and B existing simultaneously, or B existing alone. In addition, the character " / ", unless otherwise specified, generally indicates that the associated objects before and after it are in an "or" relationship.

[0061] It should be noted that in the embodiments of this application, "connection" can be understood as electrical connection. The connection between two electrical components can be a direct or indirect connection between the two electrical components. For example, the connection between A and B can be a direct connection between A and B, or an indirect connection between A and B through one or more other electrical components.

[0062] The main principle of PPG (Photoplethysmography) signal measurement of biometrics such as heart rate and blood oxygen saturation is that LED (Light-emitting diode) light is shone onto the skin, and the light reflected back from the skin tissue is received by the photosensitive module and converted into an electrical signal. This signal is then converted into a digital signal by an analog-to-digital converter, and further calculations are performed based on the digital signal.

[0063] The heartbeat cycle mentioned in this application is also known as the cardiac cycle, which refers to the process that the cardiovascular system goes through from the start of one heartbeat to the start of the next heartbeat. It is the time required for the heart to complete one contraction and relaxation.

[0064] Please see Figure 1 As shown, the wear status detection method for wearable devices of this application can be applied to, for example... Figure 1The wearable device 400 shown includes an optical signal sensor 100, which comprises an LED light source 10 and a photodiode (PD) 20, with a photosensitive path 30 formed between the LED light source 10 and the photodiode 20. When a user wears the wearable device 400, it is in a wearing state and fits against the user's target area (e.g., wrist or ear canal). The collected pulse wave sampling signal exhibits periodic changes, and at this time, the pulse wave sampling signal is a PPG signal. When the wearable device 400 is placed, it fits against the object being placed, and the collected pulse wave sampling signal does not exhibit periodic changes.

[0065] Please see Figure 2 The diagram shown is a schematic flowchart of a method for detecting the wearing status of a wearable device according to an embodiment of this application. It should be noted that if substantially the same result is obtained, the method of this application is not necessarily identical. Figure 2 The illustrated process sequence is limited. In this embodiment, the method for detecting the wearing status of the wearable device includes the following steps:

[0066] S11, acquire pulse wave sampling data for at least two consecutive heartbeat cycles, wherein the pulse wave sampling data for each heartbeat cycle includes multiple pulse wave sampling signals acquired at a first sampling frequency;

[0067] Each heartbeat cycle is set as a preset time window. Within each preset time window, multiple pulse wave sampling signals are acquired by the optical signal sensor 100 at a first sampling frequency. These multiple pulse wave sampling signals are the pulse wave sampling data for the corresponding heartbeat cycle. At least two consecutive heartbeat cycles correspond to at least two preset time windows that are consecutive in time and do not interact.

[0068] In one optional implementation, since a normal person's heart rate is generally 60-100 beats per minute, the heart rate cycle can be determined to be 0.8-1.0 seconds. All pulse wave sampling signals from a preset time interval can be acquired, with the preset time corresponding to at least two heart rate cycles. These pulse wave sampling signals are then divided into pulse wave sampling data corresponding to each heart rate cycle.

[0069] S12, for multiple heartbeat cycles, acquire a first signal set composed of pulse wave sampling signals that meet the first preset condition and a second signal set composed of pulse wave sampling signals that meet the second preset condition in each heartbeat cycle;

[0070] Please refer to Figure 3The diagram shows a pulse wave of a heartbeat cycle. A complete pulse wave has undulating peaks and troughs. The first preset condition corresponds to the peak segment of the pulse wave, and the second preset condition corresponds to the trough segment of the pulse wave. The first signal set corresponds to multiple pulse wave sampling signals in the peak segment, and the second signal set corresponds to multiple pulse wave sampling signals in the trough segment.

[0071] In this embodiment, the pulse wave sampling data of all heartbeat cycles obtained in step S11 can be extracted into the first signal set and the second signal set. Alternatively, a first number of consecutive heartbeat cycles can be selected from all heartbeat cycles obtained in step S11 and the first signal set and the second signal set can be extracted respectively. The first number can be determined according to actual needs or experience. For example, it can be determined as follows: the duration corresponding to the first number of consecutive heartbeat cycles is greater than or equal to the first preset duration. The first number can be determined according to the first preset duration and the duration of the heartbeat cycle.

[0072] S13, determine whether the wearable device is being worn based on the first signal set and the second signal set of each heartbeat cycle;

[0073] Specifically, based on the first set of signals used to characterize the peak segment of the pulse wave and the second set of signals used to characterize the trough segment of the pulse wave in each heartbeat cycle, it can be determined whether the pulse wave sampling data of the corresponding heartbeat cycle conforms to the characteristics of the pulse wave to determine whether the pulse wave sampling data is collected from a living body, and thus determine whether the wearable device is in a wearing state.

[0074] In this embodiment, based on the first signal set and the second signal set of at least two consecutive heartbeat cycles, it can be determined whether the pulse wave sampling data of multiple heartbeat cycles is periodic pulse wave signal data, thereby determining whether the wearable device is in a wearing state. This can solve the problem of not being able to improve the detection accuracy and has the effect of improving the accuracy of wearing state detection.

[0075] In some implementations, step S13 specifically includes the following steps:

[0076] S131, if the first difference in each heartbeat cycle is less than the first preset threshold, then the wearable device is determined to be in a wearing state, wherein the first difference is the difference between the number of pulse wave sampling signals in the first signal set and the number of pulse wave sampling signals in the second signal set in the corresponding heartbeat cycle.

[0077] In this embodiment, the number of pulse wave sampling signals in the first signal set is used to characterize the duration of the corresponding peak segment in the corresponding heartbeat cycle, the number of pulse wave sampling signals in the second signal set is used to characterize the duration of the corresponding trough segment in the corresponding heartbeat cycle, and the first difference is used to characterize the difference between the duration of the peak segment and the trough segment in the corresponding heartbeat cycle. For periodic signal data, the first difference is relatively stable. If the first difference of each heartbeat cycle is less than the first preset threshold, it indicates that the pulse wave sampling data of at least two consecutive heartbeat cycles obtained are data collected from a living organism.

[0078] In this embodiment, the first difference is used as the periodic feature data of the corresponding heartbeat cycle for judgment, which can improve the speed and accuracy of judging the wearing status.

[0079] In some implementations, step S13 further includes the following steps:

[0080] S132, if the first difference of any heartbeat cycle is greater than or equal to the first preset threshold, then it is determined that the wearable device is in an unworn state, and the pulse wave sampling signal is acquired at the first sampling frequency, and the ambient light signal is acquired.

[0081] Specifically, when the first difference of any heartbeat cycle is greater than or equal to the first preset threshold, the wearable device is in an unworn state. At this time, sampling continues at the first sampling frequency to obtain the pulse wave sampling signal for the next round of wearing status detection. At the same time, the ambient light signal is acquired to determine whether the LED light source is blocked.

[0082] In some implementations, pulse wave sampling signals are acquired at a first sampling frequency until a first preset duration has elapsed, at which point ambient light signals are acquired. In this implementation, sampling continues at the first sampling frequency for a first preset duration to acquire a sufficient number of pulse wave sampling signals for the next round of wearing status detection. Assuming that data from N heartbeat cycles is required for wearing status detection, where N is an integer greater than or equal to 2, and the first preset duration is greater than or equal to the product of N and the heartbeat cycle,...

[0083] S133, when the pulse wave sampling signal is greater than the first signal threshold and the ambient light signal is less than the second signal threshold, continue to execute the step of acquiring pulse wave sampling data for at least two consecutive heartbeat cycles;

[0084] If the pulse wave sampling signal is greater than the first signal threshold, it is determined that the pulse wave sampling signal intensity is sufficiently large. If the ambient light signal is less than the second signal threshold, it is determined that the LED light source of the wearable device is still blocked. At this time, the wearable device may be close to the human body or blocked by other objects. When both the pulse wave sampling signal is greater than the first signal threshold and the ambient light signal is less than the second signal threshold, the wearable device is likely to be close to the human body, that is, the wearable device is likely to be worn. Step S11, which involves obtaining pulse wave sampling data for at least two consecutive heartbeat cycles, can be executed. The pulse wave sampling data for at least two consecutive heartbeat cycles obtained is the data collected in step S132.

[0085] In some implementations, the pulse wave sampling data of at least two consecutive heartbeat cycles are data collected within a first preset duration.

[0086] In some implementations, to improve the accuracy of detection, in addition to judging the periodic characteristics of each heartbeat cycle, the difference between two adjacent heartbeat cycles can also be judged. Step S13 specifically includes the following steps:

[0087] S131' If the first difference of each heartbeat cycle is less than the first preset threshold and the second and third differences of each two adjacent heartbeat cycles are less than the second preset threshold, then the wearable device is determined to be in a wearing state. The second difference is the difference in the number of pulse wave sampling signals in the first signal set of two adjacent heartbeat cycles, and the third difference is the difference in the number of pulse wave sampling signals in the second signal set of two adjacent heartbeat cycles.

[0088] The second difference is used to characterize the difference in duration of the peak segment of two adjacent heartbeat cycles, and the third difference is used to characterize the difference in duration of the trough segment of two adjacent heartbeat cycles. If the second difference is less than the second preset threshold and the third difference is less than the second preset threshold, it indicates that the duration of the peak segment and the duration of the trough segment of two adjacent heartbeat cycles are relatively close, and the fluctuation of the pulse wave sampling data of at least two consecutive heartbeat cycles is not large.

[0089] In this embodiment, the first difference is specifically described in step S131, and will not be repeated here.

[0090] In this embodiment, in addition to the first difference, the second and third differences between two adjacent heartbeat cycles are also used as judgment conditions, which further improves the accuracy of wearing status detection.

[0091] In some implementations, step S12 specifically includes the following steps:

[0092] S121, respectively obtain the maximum and minimum values ​​of multiple pulse wave sampling signals in each heartbeat cycle;

[0093] During the heartbeat cycle, the signal strength of the pulse wave sampling signal changes as follows: Figure 3 The changes are shown. For each heartbeat cycle, the maximum value in the pulse wave sample signal corresponds to the peak value ( Figure 3 Point A in the middle, the minimum value in the pulse wave sampling signal corresponds to Figure 3 The middle line is L.

[0094] S122, determine the first signal value corresponding to the heartbeat cycle based on the maximum value and the first coefficient, and determine the second signal value corresponding to the heartbeat cycle based on the minimum value and the second coefficient;

[0095] The first and second coefficients can be set based on empirical values. The range from the first signal value to the maximum value corresponds to the peak segment, and the range from the minimum value to the second signal value corresponds to the trough segment. As one implementation method, the first coefficient can be greater than 0.5 and less than 1, and the second coefficient can be greater than 1 and less than 1.5. For example, the first coefficient can be 0.85 and the second coefficient can be 1.17.

[0096] S123, acquire the first signal set composed of pulse wave sampling signals that are greater than the first signal value in the heartbeat cycle;

[0097] Among them, the range from the first signal value to the maximum value corresponds to the peak segment, that is, the peak segment corresponding to the first signal set.

[0098] S124, acquire the second signal set composed of pulse wave sampling signals that are less than the second signal value in the heartbeat cycle;

[0099] Among them, the trough segment corresponds to the range from the minimum value to the second signal value, that is, the trough segment corresponds to the second signal set.

[0100] In this embodiment, the lower limit of the peak segment is determined based on the first coefficient and the maximum value determined by experience, and the upper limit of the trough segment is determined based on the second coefficient and the minimum value determined by experience. The first signal set better reflects the characteristics of the peak segment and the second signal set better reflects the characteristics of the trough segment, which can further improve the accuracy of wearing status detection.

[0101] In some implementations, the following steps are included after step S11 and before step S12:

[0102] S21, determine whether the pulse wave sampling data of the heartbeat cycle meets the wearing status detection conditions.

[0103] If the wearing status detection conditions are met, proceed to step S12; if the wearing status detection conditions are not met, proceed to step S11 to reacquire a new round of multiple pulse wave sampling data.

[0104] In some implementations, step S21 may include the following steps:

[0105] S211, acquire the signal average of multiple pulse wave sampling signals during the heartbeat cycle;

[0106] Specifically, for each heartbeat cycle, the average signal value of multiple pulse wave sampling signals is calculated.

[0107] S212, obtain the average value and standard deviation of the signal mean of multiple heartbeat cycles respectively, and determine the first signal range based on the average value and standard deviation;

[0108] The lower limit of the first signal range is the difference between the mean and the standard deviation, and the upper limit of the first signal range is the sum of the mean and the standard deviation.

[0109] S213, when the average signal value of the heartbeat cycle is within the first signal range, it is determined that the pulse wave sampling data of the heartbeat cycle meets the wearing status detection conditions;

[0110] The first signal range is determined based on the average and standard deviation of the signal mean values ​​for all heartbeat cycles. When the signal mean values ​​for all heartbeat cycles fall within the first signal range, it indicates that the differences between the signal mean values ​​for all heartbeat cycles are small, and the signal mean values ​​for all heartbeat cycles are relatively concentrated. If the signal mean value for each heartbeat cycle falls within the first signal range, then the pulse wave sampling data obtained in step S11 is determined to meet the wearing status detection conditions.

[0111] In this embodiment, determining whether the data meets the wearing status detection conditions before detecting the wearing status can improve the accuracy of wearing status detection, while avoiding the detection of wearing status for data that does not meet the wearing status detection conditions, reducing the occupation of system resources and helping to reduce power consumption.

[0112] In some implementations, after step S213, the following steps are also included:

[0113] S214, when the signal mean of any heartbeat cycle is not within the first signal range, it is determined that the pulse wave sampling data of the heartbeat cycle does not meet the wearing status detection conditions;

[0114] S215, continue with the step of acquiring pulse wave sampling data for at least two consecutive heartbeat cycles.

[0115] In this embodiment, if the average signal value of at least one heartbeat cycle is not within the first signal range, it is determined that the data collected in step S11 does not meet the wearing status detection conditions, and step S11 needs to be executed again to collect pulse wave sampling data of at least two consecutive heartbeat cycles in a new round.

[0116] In one implementation, the following steps are included before step S11:

[0117] S101, acquire pulse wave sampling signal at second sampling frequency, acquire ambient light signal;

[0118] In determining whether a wearable device is being worn, it can first be determined whether the wearable device is being blocked; after determining that the wearable device is being blocked, it can then be determined whether the wearable device is being worn. Therefore, in step S101, a pulse wave sampling signal can be acquired at a second sampling frequency, and the ambient light signal received by the photodiode when the LED light source is turned off can also be acquired. The second sampling frequency is lower than the first sampling frequency; that is, before determining that the wearable device is being blocked, sampling can be performed at a relatively low frequency to reduce power consumption.

[0119] S102, when the pulse wave sampling signal is greater than the first signal threshold and the ambient light signal is less than the second signal threshold, the sampling frequency of the pulse wave sampling signal is adjusted to the first sampling frequency.

[0120] If the pulse wave sampling signal is greater than the first signal threshold and the ambient light signal is less than the second signal threshold, then the wearable device is determined to be in an occluded state.

[0121] In this embodiment, when the wearable device is not being worn, sampling is performed at a second frequency to first determine whether the wearable device is being blocked; after determining that the wearable device is being blocked, sampling is performed at a first frequency to detect whether the wearable device is being worn; by using different sampling frequencies, the power consumption of the wearable device is reduced, and the battery life on a single charge is increased.

[0122] In one implementation, in step S102, if each pulse wave sampling signal is greater than a first signal threshold and each ambient light signal is less than a second signal threshold within a second preset time period, it is determined that the wearable device is in an occluded state. To further determine whether it is in a wearing state, rather than being occluded by a non-living object, the sampling frequency of the pulse wave sampling signal can be adjusted to the first sampling frequency. In this implementation, a non-living object refers to an object other than the human body, such as the wearable device being placed on a desk and obscured by the desktop; or the wearable device being placed inside a handbag and obscured by the bag's lining. In this implementation, the sampling time can be accumulated to a second preset time period. Within the second preset time period, if the pulse wave sampling signal is continuously greater than the first signal threshold and the ambient light signal is less than the second signal threshold, it can be determined that the wearable device is in an occluded state, and the sampling frequency is adjusted to the first sampling frequency to begin wearing state detection, further improving the accuracy of occlusion state detection.

[0123] In one implementation, the following steps are included after step S13:

[0124] S14, When it is determined that the wearable device is in the wearing state, the sampling frequency of the pulse wave sampling signal is adjusted to the third sampling frequency;

[0125] Once it is confirmed that the wearable device is in a wearing state, the wearable device enters normal working mode and adjusts the sampling frequency to the third sampling frequency to measure heart rate or blood oxygen saturation. The third sampling frequency is greater than the first sampling frequency.

[0126] In one implementation, the following steps are included after step S14:

[0127] S15, acquire pulse wave sampling signal at the third sampling frequency, acquire ambient light signal;

[0128] S16, when the pulse wave sampling signal is less than the third signal threshold or the ambient light signal is greater than the fourth signal threshold, it is determined that the wearable device is not being worn, and the sampling frequency of the pulse wave sampling signal is adjusted to the second sampling frequency.

[0129] In this embodiment, when the wearable device is in the wearing state, it is determined whether the wearable device is in the unwearing state based on the pulse wave sampling signal and the ambient light signal. When the pulse wave sampling signal is less than the third signal threshold, the wearable device cannot collect a qualified pulse wave sampling signal, indicating whether the wearable device is in the unwearing state. When the ambient light signal is greater than the fourth signal threshold, the wearable device is in the unobstructed state, indicating whether the wearable device is in the unwearing state.

[0130] like Figure 4As shown, one embodiment of this application provides a wearable device for detecting the wearing status of a wearable device. Please refer to [link to relevant documentation]. Figure 4 As shown, the wearable device's wearing status detection device 40 includes: an acquisition module 41, an analysis module 42, and a detection module 43. The acquisition module 41 is used to acquire pulse wave sampling data for at least two consecutive heartbeat cycles, wherein the pulse wave sampling data for each heartbeat cycle includes multiple pulse wave sampling signals acquired at a first sampling frequency. The analysis module 42 is used to acquire, for multiple heartbeat cycles, a first signal set composed of pulse wave sampling signals that meet a first preset condition and a second signal set composed of pulse wave sampling signals that meet a second preset condition. The detection module 43 is used to determine the wearing status of the wearable device based on the first signal set and the second signal set for each heartbeat cycle.

[0131] In one implementation, the detection module 43 is further configured to: determine that the wearable device is in a wearing state if the first difference in each heartbeat cycle is less than a first preset threshold, wherein the first difference is the difference between the number of all pulse wave sampling signals in the first signal set and the number of all pulse wave sampling signals in the second signal set in the corresponding heartbeat cycle.

[0132] In one implementation, the detection module 43 is further configured to: determine that the wearable device is in a wearing state if the first difference of each heartbeat cycle is less than a first preset threshold and the second and third differences of each two adjacent heartbeat cycles are less than a second preset threshold, wherein the second difference is the difference in the number of all pulse wave sampling signals in the first signal set of two adjacent heartbeat cycles, and the third difference is the difference in the number of all pulse wave sampling signals in the second signal set of two adjacent heartbeat cycles.

[0133] In one implementation, the detection module 43 is further configured to: determine that the wearable device is in an unworn state if the first difference of any heartbeat cycle is greater than or equal to a first preset threshold, acquire a pulse wave sampling signal at a first sampling frequency, and acquire an ambient light signal; when the pulse wave sampling signal is greater than a first signal threshold and the ambient light signal is less than a second signal threshold, continue to execute the step of acquiring pulse wave sampling data for at least two consecutive heartbeat cycles.

[0134] In one implementation, the detection module 43 is also used to: acquire a pulse wave sampling signal at a first sampling frequency until a first preset time has elapsed; and acquire an ambient light signal.

[0135] In one implementation, the analysis module 42 is further configured to: acquire the maximum and minimum values ​​of multiple pulse wave sampling signals in each heartbeat cycle; determine the first signal value of the corresponding heartbeat cycle based on the maximum value and a first coefficient, and determine the second signal value of the corresponding heartbeat cycle based on the minimum value and a second coefficient; acquire a first signal set composed of pulse wave sampling signals greater than the first signal value in the heartbeat cycle; and acquire a second signal set composed of pulse wave sampling signals less than the second signal value in the heartbeat cycle.

[0136] As one implementation, the analysis module 42 is also used to: determine whether the pulse wave sampling data of the heartbeat cycle meets the wearing status detection conditions.

[0137] In one implementation, the analysis module 42 is further configured to: acquire the signal mean of multiple pulse wave sampling signals of the heartbeat cycle; acquire the average value and standard deviation of the signal mean corresponding to multiple heartbeat cycles respectively, and determine a first signal range based on the average value and standard deviation; when the signal mean of all heartbeat cycles is within the first signal range, determine that the pulse wave sampling data of the heartbeat cycle meets the wearing status detection conditions.

[0138] In one implementation, the analysis module 42 is further configured to: determine that the pulse wave sampling data of the heartbeat cycle does not meet the wearing status detection conditions when the signal mean of any heartbeat cycle is not within the first signal range; and continue to execute the step of acquiring pulse wave sampling data of at least two consecutive heartbeat cycles.

[0139] In one implementation, the acquisition module 41 is further configured to: acquire a pulse wave sampling signal at a second sampling frequency and acquire an ambient light signal; when the pulse wave sampling signal is greater than a first signal threshold and the ambient light signal is less than a second signal threshold, adjust the sampling frequency of the pulse wave sampling signal to a first sampling frequency, wherein the second sampling frequency is less than the first sampling frequency.

[0140] In one implementation, the detection module 43 is further configured to: when it is determined that the wearable device is in a wearing state, adjust the sampling frequency of the pulse wave sampling signal to a third sampling frequency, wherein the third sampling frequency is greater than the first sampling frequency.

[0141] In one implementation, the detection module 43 is also used to: acquire a pulse wave sampling signal at a third sampling frequency and acquire an ambient light signal; when the pulse wave sampling signal is less than a third signal threshold or the ambient light signal is greater than a fourth signal threshold, determine that the wearable device is in an unworn state and adjust the sampling frequency of the pulse wave sampling signal to a second sampling frequency.

[0142] In this embodiment, based on the first signal set and the second signal set of at least two consecutive heartbeat cycles, it can be determined whether the pulse wave sampling data of multiple heartbeat cycles is periodic pulse wave signal data, thereby determining whether the wearable device is in a wearing state. This can solve the problem of not being able to improve the detection accuracy and has the effect of improving the accuracy of wearing state detection.

[0143] Figure 5 This is a schematic diagram of the structure of a wearable device according to an embodiment of this application. Figure 5 As shown, the wearable device 50 includes a processor 51 and a memory 52 coupled to the processor 51.

[0144] The memory 52 stores program instructions for implementing the wear status detection method of the wearable device in any of the above embodiments.

[0145] The processor 51 is used to execute program instructions stored in the memory 52 to detect the wearing status of the wearable device.

[0146] The processor 51 can also be referred to as a CPU (Central Processing Unit). The processor 51 may be an integrated circuit chip with signal processing capabilities. The processor 51 can also be a general-purpose processor, a digital signal processor (DSP), an application-specific integrated circuit (ASIC), a field-programmable gate array (FPGA), or other programmable logic devices, discrete gate or transistor logic devices, or discrete hardware components. A general-purpose processor can be a microprocessor or any conventional processor.

[0147] In this embodiment, wearable devices include, but are not limited to, smartwatches, smart bracelets, smart headphones, and neck massagers. In this wearable device, based on a first signal set and a second signal set from at least two consecutive heartbeat cycles, it is possible to determine whether pulse wave sampling data from multiple heartbeat cycles are periodic pulse wave signal data, thereby determining whether the wearable device is in a wearing state. This solves the problem of hindering the improvement of detection accuracy and has the effect of improving the accuracy of wearing state detection.

[0148] The above are merely preferred embodiments of this application and are not intended to limit this application in any way. Although this application has disclosed preferred embodiments as above, it is not intended to limit this application. Any person skilled in the art can make some modifications or alterations to the above-disclosed technical content to create equivalent embodiments without departing from the scope of the technical solution of this application. Any simple modifications, equivalent changes and alterations made to the above embodiments based on the technical essence of this application without departing from the scope of the technical solution of this application shall still fall within the scope of the technical solution of this application.

Claims

1. A method for detecting the wearing status of a wearable device, characterized in that, include: Acquire pulse wave sampling data for at least two consecutive heartbeat cycles, wherein the pulse wave sampling data for each heartbeat cycle includes multiple pulse wave sampling signals acquired at a first sampling frequency; For multiple heartbeat cycles, obtaining a first signal set composed of pulse wave sampling signals that satisfy a first preset condition and a second signal set composed of pulse wave sampling signals that satisfy a second preset condition in each heartbeat cycle specifically includes: obtaining the maximum value and minimum value among the multiple pulse wave sampling signals in each heartbeat cycle; determining a first signal value corresponding to the heartbeat cycle based on the maximum value and a first coefficient, and determining a second signal value corresponding to the heartbeat cycle based on the minimum value and a second coefficient; obtaining the first signal set composed of pulse wave sampling signals in the heartbeat cycle that are greater than the first signal value; and obtaining the second signal set composed of pulse wave sampling signals in the heartbeat cycle that are less than the second signal value. Determining whether the wearable device is in a wearing state based on the first signal set and the second signal set of each heartbeat cycle specifically includes: if the first difference of each heartbeat cycle is less than a first preset threshold, then the wearable device is determined to be in a wearing state, wherein the first difference is the difference between the number of all pulse wave sampling signals in the first signal set and the number of all pulse wave sampling signals in the second signal set in the corresponding heartbeat cycle. 2.The method of claim 1, wherein, Determining whether the wearable device is in a wearing state based on the first signal set and the second signal set of each heartbeat cycle includes: If the first difference in each heartbeat cycle is less than the first preset threshold and the second and third differences in each two adjacent heartbeat cycles are less than the second preset threshold, then the wearable device is determined to be in a wearing state. The second difference is the difference in the number of all pulse wave sampling signals in the first signal set of two adjacent heartbeat cycles, and the third difference is the difference in the number of all pulse wave sampling signals in the second signal set of two adjacent heartbeat cycles. 3.The method of claim 1, wherein, The step of determining whether the wearable device is in a wearing state based on the first signal set and the second signal set of each heartbeat cycle further includes: If the first difference of any of the heartbeat cycles is greater than or equal to the first preset threshold, then it is determined that the wearable device is in an unworn state, and the pulse wave sampling signal is acquired at the first sampling frequency, and the ambient light signal is acquired. When the pulse wave sampling signal is greater than the first signal threshold and the ambient light signal is less than the second signal threshold, the step of acquiring pulse wave sampling data for at least two consecutive heartbeat cycles continues. 4.The method of claim 3, wherein, Acquiring the pulse wave sampling signal at the first sampling frequency and acquiring the ambient light signal includes: The pulse wave sampling signal is acquired at the first sampling frequency until a first preset time has elapsed; Acquire the ambient light signal. 5.The method of claim 1, wherein, Before acquiring, for multiple heartbeat cycles, a first signal set composed of pulse wave sampling signals satisfying a first preset condition and a second signal set composed of pulse wave sampling signals satisfying a second preset condition, the method further includes: Determine whether the pulse wave sampling data of the heartbeat cycle meets the wearing status detection conditions. 6.The method of claim 5, wherein, Determining whether the pulse wave sampling data of the heartbeat cycle meets the wearing status detection conditions includes: Obtain the average signal value of the plurality of pulse wave sampling signals of the heartbeat cycle; The average value and standard deviation of the signal mean corresponding to multiple heartbeat cycles are obtained respectively, and the first signal range is determined based on the average value and standard deviation; When the average signal value of all heartbeat cycles is within the first signal range, it is determined that the pulse wave sampling data of the heartbeat cycle meets the wearing status detection conditions. 7.The method of claim 6, wherein, The step of determining whether the pulse wave sampling data of the heartbeat cycle meets the wearing status detection conditions also includes: When the mean value of the signal in any of the heartbeat cycles is not within the first signal range, it is determined that the pulse wave sampling data of the heartbeat cycle does not meet the wearing status detection conditions. Continue with the steps to acquire pulse wave sampling data for at least two consecutive heartbeat cycles. 8.The method of claim 1, wherein, Before acquiring pulse wave sampling data for at least two consecutive heartbeat cycles, the method further includes: The pulse wave sampling signal is acquired at the second sampling frequency to acquire the ambient light signal; When the pulse wave sampling signal is greater than a first signal threshold and the ambient light signal is less than a second signal threshold, the sampling frequency of the pulse wave sampling signal is adjusted to the first sampling frequency, wherein the second sampling frequency is less than the first sampling frequency. 9.The method of claim 1, wherein, After determining whether the wearable device is in a wearing state based on the first signal set and the second signal set of each heartbeat cycle, the method further includes: When it is determined that the wearable device is in a wearing state, the sampling frequency of the pulse wave sampling signal is adjusted to a third sampling frequency, wherein the third sampling frequency is greater than the first sampling frequency. 10.The method of claim 9, wherein, After adjusting the sampling frequency of the pulse wave sampling signal to the third sampling frequency, the method further includes: The pulse wave sampling signal is acquired at the third sampling frequency to acquire the ambient light signal; When the pulse wave sampling signal is less than the third signal threshold or the ambient light signal is greater than the fourth signal threshold, it is determined that the wearable device is not being worn, and the sampling frequency of the pulse wave sampling signal is adjusted to the second sampling frequency.

11. A wearable device for detecting the wearing status of a wearable device, characterized in that, include: The acquisition module is used to acquire pulse wave sampling data for at least two consecutive heartbeat cycles, wherein the pulse wave sampling data for each heartbeat cycle includes multiple pulse wave sampling signals acquired at a first sampling frequency. The analysis module is configured to, for multiple heartbeat cycles, acquire a first signal set composed of pulse wave sampling signals that satisfy a first preset condition and a second signal set composed of pulse wave sampling signals that satisfy a second preset condition in each heartbeat cycle; the analysis module is further configured to acquire the maximum value and the minimum value among the multiple pulse wave sampling signals in each heartbeat cycle; determine a first signal value corresponding to the heartbeat cycle based on the maximum value and a first coefficient, and determine a second signal value corresponding to the heartbeat cycle based on the minimum value and a second coefficient; acquire the first signal set composed of pulse wave sampling signals in the heartbeat cycle that are greater than the first signal value; and acquire the second signal set composed of pulse wave sampling signals in the heartbeat cycle that are less than the second signal value. The detection module is configured to determine the wearing state of the wearable device based on the first signal set and the second signal set for each heartbeat cycle; the detection module is further configured to determine that the wearable device is in a wearing state if the first difference for each heartbeat cycle is less than a first preset threshold, wherein the first difference is the difference between the number of all pulse wave sampling signals in the first signal set and the number of all pulse wave sampling signals in the second signal set in the corresponding heartbeat cycle.

12. A wearable device, comprising: include: A processor, and a memory coupled to the processor, the memory storing program instructions executable by the processor; When the processor executes the program instructions stored in the memory, it implements the wearing status detection method of the wearable device as described in any one of claims 1 to 10.

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