Wearable device and heart rate tracking method and heart rate tracking device thereof

Abstract

The invention discloses a wearable device and a heart rate tracking method and a heart rate tracking device thereof, and the heart rate tracking method comprises the following steps: obtaining a photoelectric plethysmography (PPG) signal of the wearable device within a preset time; processing the PPG signal through short-time Fourier transform to obtain a frequency spectrum corresponding to the PPG signal; generating a curve cluster according to the spectrum; judging whether a curve meeting a preset condition exists in the curve cluster or not; if the curve meeting the preset condition exists, the jump heart rate is obtained according to the curve meeting the preset condition so that the heart rate can be tracked. Therefore, according to the method, through the designed heart rate jump mechanism, the correct heart rate can be tracked in time, so that the heart rate prediction precision is greatly improved.

Description

Technical Field

[0001] The present application relates to the technical field of electronic equipment, and in particular to a wearable device and a heart rate tracking method and a heart rate tracking device thereof. Background Art

[0002] As people's living standards continue to improve, wearable devices are becoming more and more popular among consumers. The heart rate tracking algorithm based on PPG (Photo Pethysmo Graphic) signals is an essential algorithm for wearable devices. Usually, the heart rate tracking algorithm searches for the current heart rate value near the heart rate of the previous moment (such as +-6BPM (Beat PerMinute, number of heart beats per minute)), but the disadvantage of this algorithm is that if the quality of the PPG signal after removing interference is not good, the predicted heart rate value will be brought to an erroneous range, and there is no way to get the real heart rate value.

[0003] Therefore, how to improve the accuracy of wearable devices in tracking heart rate is an urgent problem to be solved. Summary of the invention

[0004] The present application aims to solve at least one of the technical problems in the above-mentioned technology to a certain extent.

[0005] The embodiment of the present application proposes a heart rate tracking method for a wearable device, comprising: obtaining a photoplethysmography (PPG) signal of the wearable device within a preset time; processing the PPG signal through short-time Fourier transform to obtain a frequency spectrum corresponding to the PPG signal; generating a curve cluster according to the frequency spectrum; determining whether there is a curve meeting a preset condition in the curve cluster; if there is a curve meeting the preset condition, obtaining the heart rate according to the curve meeting the preset condition so as to track the heart rate.

[0006] According to the heart rate tracking method of the wearable device of the embodiment of the present application, the photoplethysmography (PPG) signal of the wearable device is obtained within a preset time, and the PPG signal is processed by short-time Fourier transform to obtain the spectrum corresponding to the PPG signal. Then, a curve cluster is generated according to the spectrum, and it is determined whether there is a curve that meets the preset conditions in the curve cluster. When there is a curve that meets the preset conditions, the jumping heart rate is obtained according to the curve that meets the preset conditions, so as to track the heart rate. Therefore, the method can track the correct heart rate in time by designing a heart rate jumping mechanism, thereby greatly improving the accuracy of heart rate prediction.

[0007] In some embodiments, generating a curve cluster based on the spectrum includes: performing amplitude normalization processing on the spectrum; obtaining point pairs of frequency and amplitude by searching for local peaks on the amplitude-normalized spectrum; when the current moment is greater than zero, pairing the point pairs at the current moment with the point pairs at the previous moment; if the pairing is successful, generating the curve cluster based on the two successfully paired point pairs.

[0008] In some embodiments, generating the curve cluster based on the two successfully paired point pairs includes: if the point pair at the previous moment is in the first curve, adding the point pair at the current moment to the first curve; or, if the point pair at the previous moment is not in the first curve, generating a second curve based on the point pair at the previous moment and the point pair at the current moment; and obtaining the first curve and the second curve within a preset time as the curve cluster.

[0009] In some embodiments, after obtaining the point pairs of frequency and amplitude by searching for local peaks in the spectrum after amplitude normalization, the method further includes: determining whether the amplitude of the point pairs is less than a preset amplitude; if the amplitude of the point pairs is less than the preset amplitude, deleting the point pairs with amplitudes less than the preset amplitude.

[0010] In some embodiments, determining whether there is a curve meeting a preset condition in the curve cluster includes: screening curves whose point pairs at the last moment are consistent with those at the current moment from all curves in the curve cluster, and generating a curve set; if the curve set is not empty, selecting a curve meeting the preset condition from the curve set; wherein the preset condition is that there is at least one curve in the curve set whose length exceeds a preset length, and there is no other curve within a preset frequency range whose length exceeds the preset length at a preset moment before the current moment.

[0011] In some embodiments, obtaining the beating heart rate based on the curve that meets the preset conditions in order to track the heart rate includes: selecting the longest curve from the curves that meet the preset conditions, and using the frequency of the longest curve at the last moment as the beating heart rate in order to track the heart rate.

[0012] In some embodiments, before obtaining the photoplethysmography (PPG) signal of the wearable device, it also includes: collecting an optical signal through an optical sensor; the optical signal includes a PPG signal and an acceleration signal; using a filtering algorithm, filtering the acceleration signal from the optical signal to obtain a PPG signal.

[0013] The embodiment of the present application also proposes a heart rate tracking device for a wearable device, including: an acquisition module, used to acquire a photoplethysmography (PPG) signal of the wearable device within a preset time; a processing module, used to process the PPG signal through short-time Fourier transform to obtain a spectrum corresponding to the PPG signal; a generation module, used to generate a curve cluster according to the spectrum; a judgment module, used to judge whether there is a curve that meets the preset conditions in the curve cluster; and a tracking module, used to obtain the beat heart rate according to the curve that meets the preset conditions when there is a curve that meets the preset conditions, so as to track the heart rate.

[0014] According to the heart rate tracking device of the wearable device of the embodiment of the present application, the photoplethysmography (PPG) signal of the wearable device is obtained by the acquisition module within a preset time, the processing module processes the PPG signal by short-time Fourier transform to obtain the spectrum corresponding to the PPG signal, the generation module generates a curve cluster according to the spectrum, the judgment module judges whether there is a curve that meets the preset conditions in the curve cluster, and the tracking module obtains the jumping heart rate according to the curve that meets the preset conditions when there is a curve that meets the preset conditions, so as to track the heart rate. Therefore, the device can track the correct heart rate in time through the heart rate jumping mechanism, thereby greatly improving the accuracy of heart rate prediction.

[0015] In some embodiments, the generation module includes: a processing unit for performing amplitude normalization processing on the spectrum; a search unit for obtaining point pairs of frequency and amplitude by searching for local peaks on the amplitude-normalized spectrum; a pairing unit for pairing the point pair at the current moment with the point pair at the previous moment when the current moment is greater than zero; and a first generation unit for generating the curve cluster based on the two successfully paired point pairs when the pairing is successful.

[0016] In some embodiments, the first generating unit is specifically used to: when the point pair at the previous moment is in the first curve, add the point pair at the current moment to the first curve; or, when the point pair at the previous moment is not in the first curve, generate a second curve based on the point pair at the previous moment and the point pair at the current moment; obtain the first curve and the second curve within a preset time as the curve cluster.

[0017] In some embodiments, the generation module further includes: a judgment unit, used to judge whether the amplitude of the point pair is less than a preset amplitude; and a deletion unit, used to delete the point pair with an amplitude less than the preset amplitude when the amplitude of the point pair is less than the preset amplitude.

[0018] In some embodiments, the judgment module includes: a second generation unit, used to screen out curves whose point pairs at the last moment are consistent with the point pairs at the current moment from all curves in the curve cluster, and generate a curve set; a selection unit, used to select curves that meet preset conditions from the curve set when the curve set is not empty; wherein the preset condition is that there is at least one curve in the curve set whose length exceeds the preset length, and there is no other curve within a preset frequency range at a preset moment before the current moment whose curve exceeds the preset length.

[0019] In some embodiments, the tracking module is specifically used to: select the longest curve from the curves that meet the preset conditions, and use the frequency of the longest curve at the last moment as the beating heart rate, so as to track the heart rate.

[0020] In some embodiments, the heart rate tracking device of the above-mentioned wearable device further includes: an acquisition module, used to acquire optical signals through optical sensors; the optical signals include PPG signals and acceleration signals; a filtering module, used to filter the acceleration signals from the optical signals using a filtering algorithm to obtain a PPG signal.

[0021] An embodiment of the present application also proposes a wearable device, which includes the heart rate tracking device of the wearable device mentioned above.

[0022] The wearable device of the embodiment of the present application, through the heart rate tracking device of the above-mentioned wearable device, can track the correct heart rate in time through the heart rate jump mechanism, thereby greatly improving the accuracy of heart rate prediction.

[0023] An embodiment of the present application also proposes an electronic device, comprising: a processor; and a memory for storing instructions executable by the processor; wherein the processor is configured to execute the instructions to implement the above-mentioned heart rate tracking method for a wearable device.

[0024] The electronic device of the embodiment of the present application, by executing the above-mentioned heart rate tracking method of wearable devices, can track the correct heart rate in time through the heart rate jump mechanism, thereby greatly improving the accuracy of heart rate prediction.

[0025] An embodiment of the present application also proposes a non-temporary computer-readable storage medium. When the instructions in the storage medium are executed by a processor of an electronic device, the electronic device can execute the above-mentioned heart rate tracking method for a wearable device.

[0026] The non-temporary computer-readable storage medium of the embodiment of the present application, by executing the above-mentioned heart rate tracking method of the wearable device, can track the correct heart rate in time through the heart rate jump mechanism, thereby greatly improving the accuracy of heart rate prediction. BRIEF DESCRIPTION OF THE DRAWINGS

[0027] Figure 1 is a flow chart of a heart rate tracking method for a wearable device according to an embodiment of the present application;

[0028] Figure 2 is a schematic diagram of a real heart rate and a cluster of curves according to an embodiment of the present application;

[0029] Figure 3 is a schematic diagram of a predicted heart rate obtained by a heart rate tracking algorithm of a wearable device in the related art;

[0030] Figure 4 is a schematic diagram of a predicted heart rate obtained by a heart rate tracking method for a wearable device according to an embodiment of the present application;

[0031] Figure 5 is a schematic diagram of a process of generating a curve cluster in a heart rate tracking method for a wearable device according to an embodiment of the present application;

[0032] Figure 6 is a block diagram of a heart rate tracking device for a wearable device according to an embodiment of the present application;

[0033] Figure 7 is a block diagram of a wearable device according to an embodiment of the present application;

[0034] Figure 8 It is a structural block diagram of an electronic device according to an embodiment of the present application. DETAILED DESCRIPTION

[0035] The embodiments of the present application are described in detail below, and examples of the embodiments are shown in the accompanying drawings, wherein the same or similar reference numerals throughout represent the same or similar elements or elements having the same or similar functions. The embodiments described below with reference to the accompanying drawings are exemplary and are intended to be used to explain the present application, and should not be construed as limiting the present application.

[0036] The following describes a heart rate tracking method for a wearable device, a heart rate tracking device for a wearable device, a wearable device, an electronic device, and a non-temporary computer-readable storage medium according to an embodiment of the present application in conjunction with the accompanying drawings.

[0037] Figure 1 4 is a flowchart of a heart rate tracking method for a wearable device according to an embodiment of the present application.

[0038] In an embodiment of the present application, the wearable device may be a smart watch or a smart bracelet, etc.

[0039] like Figure 1 As shown, the heart rate tracking method of the wearable device of the embodiment of the present application includes the following steps:

[0040] S101, obtaining a photoplethysmography (PPG) signal of a wearable device within a preset time.

[0041] Among them, the preset time can be set according to actual needs, for example, it can be 8 seconds. PPG is a method of shining light into the skin and measuring the light scattering caused by blood flow. The principle is: the green light emitted by the LED (Light Emitting Diode Light) in the optical sensor passes through the tissue and artery veins in the skin, and is absorbed and reflected back to the photosensitive sensor. When it is reflected back to the photosensitive sensor, the green light is attenuated to a certain extent. The absorption of green light by muscles, bones, veins and other connecting tissues is basically unchanged (provided that the measurement site does not move significantly), but blood is different. Since there is blood flowing in the artery, the absorption of light naturally changes. Then, the green light is converted into an electrical signal. It is precisely because the absorption of green light by the artery changes while the absorption of light by other tissues remains basically unchanged that the obtained signal can be divided into a DC signal and an AC signal. Finally, extracting the AC signal can reflect the characteristics of blood flow.

[0042] As an optional implementation method, before obtaining the photoplethysmography (PPG) signal of the wearable device, it also includes: collecting an optical signal through an optical sensor; the optical signal includes a PPG signal and an acceleration signal; using a filtering algorithm, filtering the acceleration signal from the optical signal to obtain a PPG signal.

[0043] In this step, PPG signals and acceleration signals are collected by optical sensors such as PPG optical modules, and motion signals such as acceleration signals are filtered out from PPG signals using relevant filtering algorithms such as RLS (Recursive least squares), and the filtered PPG signals are stored until a certain amount is reached (such as a preset time of 8 seconds).

[0044] S102, processing the PPG signal by short-time Fourier transform to obtain a frequency spectrum corresponding to the PPG signal.

[0045] In this step, a certain amount of PPG signal is subjected to short-time Fourier transform to obtain the amplitude value of a certain spectrum interval at the moment of 8 seconds.

[0046] S103, generating a curve cluster according to the frequency spectrum.

[0047] As an optional implementation method, a curve cluster is generated according to the spectrum, including: performing amplitude normalization processing on the spectrum; finding local peaks of the amplitude-normalized spectrum to obtain point pairs of frequency and amplitude; when the current moment is greater than zero, pairing the point pair at the current moment with the point pair at the previous moment; if the pairing is successful, generating a curve cluster according to the two successfully paired point pairs.

[0048] As an optional implementation method, a curve cluster is generated based on two successfully paired point pairs, including: if the point pair at the previous moment is in the first curve, the point pair at the current moment is added to the first curve; or if the point pair at the previous moment is not in the first curve, a second curve is generated based on the point pair at the previous moment and the point pair at the current moment; and the first curve and the second curve within a preset time are obtained as a curve cluster.

[0049] In this step, the amplitude of the spectrum is normalized to the maximum and minimum values, and normalized to between 0 and 1. For example, the amplitude can be normalized by dividing the maximum amplitude. Then, for the normalized amplitude, the local peak is searched to obtain the point pairs of frequency and amplitude, so that many point pairs can be obtained.

[0050] If the current time is zero, no processing is performed; if the current time is a time greater than zero, the point pair at the current time and the point pair at the previous time are paired according to the pairing condition. Among them, one implementation of the pairing condition is that the frequency of the point pair at the current time and the frequency of the point pair at the previous time differ by within 6 BPM. If the point pair at the current time and the point pair at the previous time meet the pairing condition, determine whether the point pair at the previous time is already in the first curve. If the point pair at the previous time is already in the first curve, the point pair at the current time is added to the first curve, that is, the length of the first curve is increased; if the point pair at the current time is not in a curve, the point pair at the previous time and the point pair at the current time are newly generated into a curve as the second curve. All curves generated within the preset time (including the first curve and the second curve) constitute a curve cluster.

[0051] As time goes by, steps S101-S103 are executed cyclically to obtain a growing curve cluster, such as Figure 2 As shown, it should be noted that Figure 2 Only some of the curves in the curve cluster are marked, and curves of the same thickness are also curves in the curve cluster.

[0052] In order to further improve the accuracy of heart rate prediction, after the amplitude-normalized spectrum is obtained by searching for local peaks to obtain point pairs of frequency and amplitude, the method further includes: determining whether the amplitude of the point pair is less than a preset amplitude; if the amplitude of the point pair is less than the preset amplitude, deleting the point pair with an amplitude less than the preset amplitude. The preset amplitude can be set according to actual needs, for example, it can be 0.6.

[0053] That is to say, for the normalized amplitude, after obtaining the point pairs of frequency and amplitude by searching the local peak, in order to further improve the accuracy of heart rate prediction, it is necessary to determine whether the amplitude of each point pair is less than the preset amplitude, and delete the point pair when the amplitude of the point pair is less than the preset amplitude (such as 0.6).

[0054] S104, determining whether there is a curve in the curve cluster that meets a preset condition.

[0055] S105: If there is a curve that meets the preset conditions, the heart rate is obtained according to the curve that meets the preset conditions, so as to track the heart rate.

[0056] As an optional implementation method, judging whether there is a curve that meets the preset condition in the curve cluster includes: screening all curves in the curve cluster whose point pairs at the last moment are consistent with the point pairs at the current moment, and generating a curve set; if the curve set is not empty, selecting a curve that meets the preset condition from the curve set; wherein the preset condition is that there is at least one curve in the curve set that has a length exceeding the preset length, and there is no other curve within the preset frequency range that has a length exceeding the preset length at the preset moment before the current moment. wherein the preset length, the preset frequency range and the previous preset moment can be set according to the actual situation, for example, the preset length can be 5, the preset frequency range can be 0-0.5Hz, and the previous preset moment can be the first 5 preset moments.

[0057] As an optional implementation method, the beating heart rate is obtained according to the curve that meets the preset conditions in order to track the heart rate, including: selecting the longest curve from the curves that meet the preset conditions, and using the frequency of the longest curve at the last moment as the beating heart rate in order to track the heart rate.

[0058] Generally, the heart rate tracking algorithm works as follows:

[0059] First, get the heart rate of the previous moment. For the current moment, the new heart rate is searched for 6 BPM above the heart rate of the previous moment. However, if the heart rate signal is weak, the error of heart rate tracking will be magnified. When the heart rate signal is obvious, the algorithm cannot track the heart rate correctly. For example, Figure 3 shown.

[0060] To this end, this application proposes an improved algorithm:

[0061] After obtaining the curve cluster, first select the curves whose point pairs at the last moment are consistent with the point pairs at the current moment from all the current curves in the curve cluster, and generate a curve set. Then, determine whether the curve set is empty. If the curve set is not empty, and there is a curve L with a length exceeding 5, and there are no other curves within the 0.5Hz range of the curve in the previous 5 moments. Finally, when there are multiple curves L, select the one with the longest total length, and use the frequency of this last moment as the current heart rate to jump, so as to track the heart rate, such as Figure 4 shown.

[0062] Therefore, this method designs a heart rate jump mechanism, which makes it possible to track the correct heart rate in time, thereby greatly improving the accuracy of heart rate prediction.

[0063] In order to make those skilled in the art more clearly understand steps S101-S103, Figure 5 is a schematic diagram of a process of generating a curve cluster in a heart rate tracking method for a wearable device according to an embodiment of the present application, such as Figure 5 As shown, the process of generating a curve cluster in the heart rate tracking method of the wearable device includes:

[0064] S501, PPG signal after filtering at time T.

[0065] S502, processing the PPG signal by short-time Fourier transform to obtain a frequency spectrum.

[0066] S503, normalize the amplitude of the spectrum, for example, divide the amplitude by the maximum amplitude to normalize the amplitude to between 0 and 1.

[0067] S504, searching for a local maximum value whose amplitude is greater than a preset amplitude, wherein the preset amplitude may be 0.6.

[0068] S505, compare the local maximum at time T with the local maximum at time T-1, and connect them if they meet the pairing condition. One implementation of the pairing condition is that the frequency of the current point pair and the frequency of the previous point pair differ by within 6 BPM.

[0069] S506, obtaining the spectrum peak curve before time T.

[0070] S507, continue processing the filtered PPG signal at time T+1.

[0071] After obtaining the curve cluster through steps S501-S507, first select the curves whose point pairs at the last moment are consistent with the point pairs at the current moment from all the current curves in the curve cluster, and generate a curve set. Then, determine whether the curve set is empty. If the curve set is not empty, and there is a curve L with a length exceeding 5, and there is no other curve within the 0.5Hz range of the curve in the previous 5 moments. Finally, when there are multiple curves L, select the one with the longest total length, and jump to the current heart rate with the frequency of this last moment as the current heart rate, so as to track the heart rate, such as Figure 4 shown.

[0072] In summary, according to the heart rate tracking method of the wearable device of the embodiment of the present application, the photoplethysmography (PPG) signal of the wearable device is obtained within a preset time, and the PPG signal is processed by short-time Fourier transform to obtain the spectrum corresponding to the PPG signal. Then, a curve cluster is generated according to the spectrum, and it is determined whether there is a curve that meets the preset conditions in the curve cluster. When there is a curve that meets the preset conditions, the jumping heart rate is obtained according to the curve that meets the preset conditions, so as to track the heart rate. Therefore, the method can track the correct heart rate in time by designing a heart rate jumping mechanism, thereby greatly improving the accuracy of heart rate prediction.

[0073] Figure 6 is a block diagram of a heart rate tracking device for a wearable device according to an embodiment of the present application.

[0074] like Figure 6 As shown, the heart rate tracking device 600 of the wearable device of the embodiment of the present application includes: an acquisition module 601, a processing module 602, a generation module 603, a judgment module 604 and a tracking module 605.

[0075] Among them, the acquisition module 601 is used to obtain the photoplethysmography (PPG) signal of the wearable device within a preset time. The processing module 602 is used to process the PPG signal through short-time Fourier transform to obtain the spectrum corresponding to the PPG signal. The generation module 603 is used to generate a curve cluster according to the spectrum. The judgment module 604 is used to judge whether there is a curve that meets the preset conditions in the curve cluster. The tracking module 605 is used to obtain the beat heart rate according to the curve that meets the preset conditions when there is a curve that meets the preset conditions, so as to track the heart rate.

[0076] In some embodiments, the generation module 603 includes: a processing unit, a search unit, a pairing unit and a first generation unit. The processing unit is used to perform amplitude normalization processing on the spectrum. The search unit is used to obtain point pairs of frequency and amplitude by searching for local peaks on the spectrum after amplitude normalization. The pairing unit is used to pair the point pair at the current moment with the point pair at the previous moment when the current moment is greater than zero. The first generation unit is used to generate a curve cluster based on the two successfully paired point pairs when the pairing is successful.

[0077] In some embodiments, the first generating unit is specifically used to: when the point pair at the previous moment is in the first curve, add the point pair at the current moment to the first curve; or, when the point pair at the previous moment is not in the first curve, generate a second curve based on the point pair at the previous moment and the point pair at the current moment; obtain the first curve and the second curve within a preset time as a curve cluster.

[0078] In some embodiments, the generation module 603 further includes: a judgment unit and a deletion unit. The judgment unit is used to judge whether the amplitude of the point pair is less than the preset amplitude. The deletion unit is used to delete the point pair whose amplitude is less than the preset amplitude when the amplitude of the point pair is less than the preset amplitude.

[0079] In some embodiments, the judgment module 604 includes: a second generation unit and a selection unit. The second generation unit is used to select curves whose point pairs at the last moment and the current moment are consistent from all curves in the curve cluster, and generate a curve set. The selection unit is used to select a curve that meets a preset condition from the curve set when the curve set is not empty; wherein the preset condition is that there is at least one curve in the curve set that has a length exceeding a preset length, and there is no other curve within a preset frequency range that has a length exceeding a preset length at a preset moment before the current moment.

[0080] In some embodiments, the tracking module 605 is specifically used to: select the longest curve from the curves that meet the preset conditions, and use the frequency of the longest curve at the last moment as the jumping heart rate, so as to track the heart rate.

[0081] Furthermore, the heart rate tracking device 600 of the wearable device mentioned above further includes: an acquisition module and a filtering module. The acquisition module is used to acquire an optical signal through an optical sensor, wherein the optical signal includes a PPG signal and an acceleration signal. The filtering module is used to filter the acceleration signal from the optical signal using a filtering algorithm to obtain a PPG signal.

[0082] It should be noted that for details not disclosed in the heart rate tracking device of the wearable device in the embodiment of the present application, please refer to the details disclosed in the heart rate tracking method of the wearable device in the embodiment of the present application, and the specific details will not be described here.

[0083] According to the heart rate tracking device of the wearable device of the embodiment of the present application, the photoplethysmography (PPG) signal of the wearable device is obtained by the acquisition module within a preset time, the processing module processes the PPG signal by short-time Fourier transform to obtain the spectrum corresponding to the PPG signal, the generation module generates a curve cluster according to the spectrum, the judgment module judges whether there is a curve that meets the preset conditions in the curve cluster, and the tracking module obtains the jumping heart rate according to the curve that meets the preset conditions when there is a curve that meets the preset conditions, so as to track the heart rate. Therefore, the device can track the correct heart rate in time through the heart rate jumping mechanism, thereby greatly improving the accuracy of heart rate prediction.

[0084] Figure 7 is a block diagram of a wearable device according to an embodiment of the present application. Figure 7 As shown, the wearable device 700 of the embodiment of the present application includes the heart rate tracking device 600 of the wearable device mentioned above.

[0085] The wearable device of the embodiment of the present application, through the heart rate tracking device of the above-mentioned wearable device, can track the correct heart rate in time through the heart rate jump mechanism, thereby greatly improving the accuracy of heart rate prediction.

[0086] Based on the above embodiments, the present application also proposes an electronic device, comprising: a processor; a memory for storing instructions executable by the processor; wherein the processor is configured to execute the instructions to implement the above-mentioned heart rate tracking method for the wearable device.

[0087] Figure 8 is a structural block diagram of an electronic device according to an embodiment of the present disclosure.

[0088] like Figure 8 As shown, the electronic device 800 includes: a memory 810 and a processor 820, and a bus 830 connecting different components (including the memory 810 and the processor 820).

[0089] Among them, the memory 810 is used to store the executable instructions of the processor 820; the processor 801 is configured to call and execute the executable instructions stored in the memory 802 to implement the heart rate tracking method of the wearable device proposed in the above embodiment of the present disclosure.

[0090] Bus 830 represents one or more of several types of bus structures, including a memory bus or memory controller, a peripheral bus, an accelerated graphics port, a processor or a local bus using any of a variety of bus architectures. For example, these architectures include but are not limited to Industry Standard Architecture (ISA) bus, Micro Channel Architecture (MAC) bus, Enhanced ISA bus, Video Electronics Standards Association (VESA) local bus and Peripheral Component Interconnect (PCI) bus.

[0091] The electronic device 800 typically includes a variety of electronic device readable media. These media can be any available media that can be accessed by the electronic device 800, including volatile and non-volatile media, removable and non-removable media.

[0092] The memory 810 may also include computer system readable media in the form of volatile memory, such as random access memory (RAM) 840 and / or cache memory 850. The electronic device 800 may further include other removable / non-removable, volatile / non-volatile computer system storage media. By way of example only, the storage system 860 may be used to read and write non-removable, non-volatile magnetic media ( Figure 8 not shown, usually called a "hard drive"). Although Figure 8 Not shown, a disk drive for reading and writing to a removable non-volatile disk (e.g., a "floppy disk"), and an optical disk drive for reading and writing to a removable non-volatile optical disk (e.g., a CD-ROM, a DVD-ROM, or other optical media) may be provided. In these cases, each drive may be connected to the bus 830 via one or more data medium interfaces. The memory 810 may include at least one program product having a set (e.g., at least one) of program modules that are configured to perform the functions of the various embodiments of the present disclosure.

[0093] A program / utility 880 having a set (at least one) of program modules 870 may be stored, for example, in the memory 810, such program modules 870 including, but not limited to, an operating system, one or more functions, other program modules, and program data, each of which or some combination may include an implementation of a network environment. The program modules 870 generally perform the functions and / or methods of the embodiments described in the present disclosure.

[0094] The electronic device 800 may also communicate with one or more external devices 890 (e.g., keyboard, pointing device, display 891, etc.), may also communicate with one or more devices that enable a user to interact with the electronic device 800, and / or may communicate with any device that enables the electronic device 800 to communicate with one or more other computing devices (e.g., network card, modem, etc.). Such communication may be performed via an input / output (I / O) interface 892. Furthermore, the electronic device 800 may also communicate with one or more networks (e.g., local area network (LAN), wide area network (WAN) and / or public network, such as the Internet) via a network adapter 893. As shown, the network adapter 893 communicates with other modules of the electronic device 800 via a bus 830. It should be understood that, although not shown in the figure, other hardware and / or software modules may be used in conjunction with the electronic device 800, including but not limited to: microcode, device drivers, redundant processing units, external disk drive arrays, RAID systems, tape drives, and data backup storage systems.

[0095] The processor 820 executes various functional applications and data processing by running the programs stored in the memory 810 .

[0096] It should be noted that the implementation process of the electronic device of the embodiment of the present disclosure refers to the aforementioned explanation of the method of the embodiment of the present disclosure, which will not be repeated here.

[0097] The electronic device of the embodiment of the present application, by executing the above-mentioned heart rate tracking method of wearable devices, can track the correct heart rate in time through the heart rate jump mechanism, thereby greatly improving the accuracy of heart rate prediction.

[0098] Based on the above embodiments, the present application also proposes a non-temporary computer-readable storage medium. When the instructions in the storage medium are executed by a processor of an electronic device, the electronic device can execute the above-mentioned heart rate tracking method for a wearable device.

[0099] The non-temporary computer-readable storage medium of the embodiment of the present application, by executing the above-mentioned heart rate tracking method of the wearable device, can track the correct heart rate in time through the heart rate jump mechanism, thereby greatly improving the accuracy of heart rate prediction.

[0100] Based on the above embodiments, the present application also proposes a computer program product. When the computer program is executed by a processor of an electronic device, the electronic device can execute the heart rate tracking method of the wearable device as described above.

[0101] The computer program product of the embodiment of the present application, by executing the above-mentioned heart rate tracking method for wearable devices, can track the correct heart rate in a timely manner through the heart rate jump mechanism, thereby greatly improving the accuracy of heart rate prediction.

[0102] In the description of the present application, it should be understood that the terms "center", "longitudinal", "lateral", "length", "width", "thickness", "up", "down", "front", "back", "left", "right", "vertical", "horizontal", "top", "bottom", "inside", "outside", "clockwise", "counterclockwise", "axial", "radial", "circumferential" and the like indicate orientations or positional relationships based on the orientations or positional relationships shown in the accompanying drawings, and are only for the convenience of describing the present application and simplifying the description, and do not indicate or imply that the referred device or element must have a specific orientation, be constructed and operated in a specific orientation, and therefore should not be understood as a limitation on the present application.

[0103] In addition, the terms "first" and "second" are used for descriptive purposes only and should not be understood as indicating or implying relative importance or implicitly indicating the number of the indicated technical features. Thus, a feature defined as "first" or "second" may explicitly or implicitly include one or more of the features. In the description of this application, the meaning of "plurality" is two or more, unless otherwise clearly and specifically defined.

[0104] In this application, unless otherwise clearly specified and limited, the terms "installed", "connected", "connected", "fixed" and the like should be understood in a broad sense, for example, it can be a fixed connection, a detachable connection, or an integral connection; it can be a mechanical connection or an electrical connection; it can be a direct connection or an indirect connection through an intermediate medium, it can be the internal connection of two elements or the interaction relationship between two elements. For ordinary technicians in this field, the specific meanings of the above terms in this application can be understood according to specific circumstances.

[0105] In the present application, unless otherwise clearly specified and limited, a first feature being “above” or “below” a second feature may mean that the first and second features are in direct contact, or the first and second features are in indirect contact through an intermediate medium. Moreover, a first feature being “above”, “above”, and “above” a second feature may mean that the first feature is directly above or obliquely above the second feature, or simply means that the first feature is higher in level than the second feature. A first feature being “below”, “below”, and “below” a second feature may mean that the first feature is directly below or obliquely below the second feature, or simply means that the first feature is lower in level than the second feature.

[0106] In the description of this specification, the description with reference to the terms "one embodiment", "some embodiments", "example", "specific example", or "some examples" etc. means that the specific features, structures, materials or characteristics described in conjunction with the embodiment or example are included in at least one embodiment or example of the present application. In this specification, the schematic representations of the above terms do not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described may be combined in any one or more embodiments or examples in a suitable manner. In addition, those skilled in the art may combine and combine the different embodiments or examples described in this specification and the features of the different embodiments or examples, without contradiction.

[0107] Although the embodiments of the present application have been shown and described above, it can be understood that the above embodiments are exemplary and cannot be understood as limitations on the present application. Ordinary technicians in this field can change, modify, replace and modify the above embodiments within the scope of the present application.

Claims

1. A heart rate tracking method based on a wearable device, characterized in that: include: Obtaining a photoplethysmography (PPG) signal of the wearable device within a preset time period; Processing the PPG signal to obtain a frequency spectrum corresponding to the PPG signal; According to the spectrum, at least one candidate frequency corresponding to each of at least two adjacent moments within the preset time period is obtained, wherein the amplitude corresponding to the candidate frequency in the spectrum is greater than the amplitude corresponding to at least one frequency adjacent to the candidate frequency in the spectrum; The user's heart rate is obtained according to at least one candidate frequency corresponding to each of the at least two adjacent moments.

2. The heart rate tracking method based on a wearable device as claimed in claim 1, characterized in that: The obtaining the user's heart rate according to at least one candidate frequency corresponding to each of the at least two adjacent moments includes: Obtain at least one candidate frequency curve according to at least one candidate frequency corresponding to each of the at least two adjacent moments; The user's heart rate is obtained according to the at least one candidate frequency curve.

3. The heart rate tracking method based on a wearable device as claimed in claim 2, characterized in that: The obtaining the user's heart rate according to the at least one candidate frequency curve comprises: Determine a target curve from the at least one candidate frequency curve, wherein the cutoff time of the target curve is the current time, the length of the target curve exceeds a preset length, and there is no other candidate frequency curve within the preset frequency range within the preset time range before the current time; The frequency at the cutoff moment of the target curve is used as the heart rate of the user at the current moment.

4. The heart rate tracking method based on a wearable device as claimed in claim 2, characterized in that: The obtaining at least one candidate frequency curve according to at least one candidate frequency corresponding to each of the at least two adjacent moments includes: In response to a difference between a first candidate frequency corresponding to a first moment in the at least two adjacent moments and a second candidate frequency corresponding to a moment before the first moment being within a preset difference range, a candidate frequency curve including the first candidate frequency and the second candidate frequency in the at least one candidate frequency curve is obtained.

5. The heart rate tracking method based on a wearable device as claimed in claim 1, characterized in that: The obtaining the user's heart rate according to at least one candidate frequency corresponding to each of the at least two adjacent moments includes: Pairing at least one candidate frequency corresponding to each of the at least two adjacent moments to obtain at least one candidate frequency set, wherein the candidate frequency set includes at least two successfully paired candidate frequencies corresponding to the at least two adjacent moments; A user's heart rate is determined based on the at least one candidate frequency set.

6. The heart rate tracking method based on a wearable device as claimed in claim 5, characterized in that: The pairing of at least one candidate frequency corresponding to each of the at least two adjacent moments to obtain at least one candidate frequency set includes: In response to a difference between a first candidate frequency corresponding to a first moment and a second candidate frequency corresponding to a moment before the first moment being within a preset difference range, it is determined that the first candidate frequency and the second candidate frequency are successfully paired, wherein a first candidate frequency set in the at least one candidate frequency set includes the first candidate frequency and the second candidate frequency.

7. The heart rate tracking method based on a wearable device as claimed in claim 5, characterized in that: The determining the user's heart rate according to the at least one candidate frequency set includes: Determine a target frequency set from the at least one candidate frequency set, wherein the number of candidate frequencies included in the target frequency set exceeds a preset threshold and the target frequency set includes the candidate frequency corresponding to the current moment; The user's heart rate is obtained according to the target frequency set.

8. The heart rate tracking method based on a wearable device according to any one of claims 1 to 7, characterized in that: The obtaining, according to the frequency spectrum, at least one candidate frequency corresponding to each of at least two adjacent moments in the preset time period includes: Obtaining, according to the frequency spectrum, at least one local peak corresponding to each of the at least two adjacent moments; At least one candidate frequency corresponding to each moment is obtained according to at least one local peak corresponding to each moment of the at least two adjacent moments.

9. A heart rate tracking method based on a wearable device, characterized in that: include: Obtaining a photoplethysmography (PPG) signal of the wearable device within a preset time period; Processing the PPG signal to obtain a frequency spectrum corresponding to the PPG signal; According to the spectrum, a curve cluster is obtained, wherein the curve cluster includes at least one curve, each curve in the at least one curve includes a candidate frequency at each time point in at least two adjacent time points, and an amplitude corresponding to the candidate frequency in the spectrum is greater than an amplitude corresponding to at least one frequency adjacent to the candidate frequency in the spectrum; Determining a target curve that meets a preset condition from at least one curve included in the curve cluster; The user's heart rate is determined according to the target curve.

10. The heart rate tracking method based on a wearable device according to claim 9, characterized in that: The curve cluster is obtained according to the frequency spectrum, including: Obtaining, according to the frequency spectrum, at least one candidate frequency corresponding to a current moment and at least one candidate frequency corresponding to a moment before the current moment; Performing pairing processing on at least one candidate frequency corresponding to the current moment and at least one candidate frequency corresponding to the previous moment; In response to the first candidate frequency corresponding to the current moment and the second candidate frequency corresponding to the previous moment being paired successfully, the curve cluster is obtained according to the first candidate frequency and the second candidate frequency.

11. The heart rate tracking method based on a wearable device according to claim 10, characterized in that: The step of obtaining a curve cluster according to the first candidate frequency and the second candidate frequency includes: If there is a first curve including the second candidate frequency in the original curve cluster at the current moment, the first candidate frequency is added to the first curve to obtain an updated first curve, and the curve cluster includes the updated first curve; and / or, If the first curve including the second candidate frequency does not exist in the original curve cluster at the current moment, a second curve including the first candidate frequency and the second candidate frequency is generated, and the second curve is added to the original curve cluster to obtain the curve cluster.

12. The heart rate tracking method based on a wearable device according to claim 10 or 11, characterized in that: The obtaining, according to the frequency spectrum, at least one candidate frequency corresponding to the current moment and at least one candidate frequency corresponding to a moment before the current moment includes: Obtaining, according to the frequency spectrum, at least one first local peak corresponding to the current moment and at least one second local peak corresponding to the previous moment; At least one candidate frequency corresponding to the current moment is obtained according to the at least one first local peak, and at least one candidate frequency corresponding to the previous moment is obtained according to the at least one second local peak.

13. The heart rate tracking method based on a wearable device according to claim 10 or 11, characterized in that: Before pairing the at least one candidate frequency corresponding to the current moment with the at least one candidate frequency corresponding to the previous moment, the method further includes: Determine whether the amplitude corresponding to at least one candidate frequency corresponding to the current moment is less than a preset amplitude; If there is a candidate frequency whose corresponding amplitude is smaller than the preset amplitude among the at least one candidate frequency corresponding to the current moment, the candidate frequency whose corresponding amplitude is smaller than the preset amplitude is deleted from the at least one candidate frequency corresponding to the current moment.

14. The heart rate tracking method based on a wearable device according to claim 9 or 10, characterized in that: The preset conditions include: The cut-off time of the curve is the current time; The length of the curve exceeds a preset length; Within a preset time range before the current time, no other curve exists within a preset frequency range of the curve.

15. The heart rate tracking method based on a wearable device according to claim 9 or 10, characterized in that: Determining the user's heart rate according to the target curve includes: The frequency of the cutoff moment of the target curve is used as the user's heart rate.

16. A heart rate tracking device based on a wearable device, characterized in that: include: An acquisition module is used to acquire a photoplethysmography (PPG) signal of the wearable device within a preset time period; A processing module, used for processing the PPG signal to obtain a frequency spectrum corresponding to the PPG signal; According to the spectrum, at least one candidate frequency corresponding to each of at least two adjacent moments within the preset time period is obtained, wherein the amplitude corresponding to the candidate frequency in the spectrum is greater than the amplitude corresponding to at least one frequency adjacent to the candidate frequency in the spectrum; The tracking module is used to obtain the user's heart rate according to at least one candidate frequency corresponding to each of the at least two adjacent moments.

17. The heart rate tracking device based on a wearable device as claimed in claim 16, characterized in that: The tracking module is used to: Obtain at least one candidate frequency curve based on at least one candidate frequency corresponding to each of the at least two adjacent moments; Based on the at least one candidate frequency curve, a user's heart rate is obtained.

18. The heart rate tracking device based on a wearable device as claimed in claim 17, characterized in that: The tracking module is used to: Determine a target curve from the at least one candidate frequency curve, wherein the cutoff time of the target curve is the current time, the length of the target curve exceeds a preset length, and there is no other curve within the preset frequency range within the preset time range before the current time under the target curve; The frequency at the cutoff moment of the target curve is used as the heart rate of the user at the current moment.

19. The heart rate tracking device based on a wearable device as claimed in claim 16, characterized in that: The tracking module is used to: Pairing at least one candidate frequency corresponding to each of the at least two adjacent moments to obtain at least one candidate frequency set, wherein the candidate frequency set includes at least two successfully paired candidate frequencies corresponding to the at least two adjacent moments; A user's heart rate is determined based on the at least one candidate frequency set.

20. The heart rate tracking device based on a wearable device as claimed in claim 16, characterized in that: The tracking module is used to: In response to a difference between a first candidate frequency corresponding to a first moment and a second candidate frequency corresponding to a moment before the first moment being within a preset difference range, it is determined that the first candidate frequency and the second candidate frequency are successfully paired, wherein a first candidate frequency set in the at least one candidate frequency set includes the first candidate frequency and the second candidate frequency.

21. A heart rate tracking device based on a wearable device, characterized in that: include: An acquisition module, used to acquire a photoplethysmography (PPG) signal of a wearable device within a preset time period; a processing module, configured to process the PPG signal to obtain a spectrum corresponding to the PPG signal, and obtain a curve cluster according to the spectrum, wherein the curve cluster includes at least one curve, each curve in the at least one curve includes a candidate frequency at each moment in at least two adjacent moments, and an amplitude corresponding to the candidate frequency in the spectrum is greater than an amplitude corresponding to at least one frequency adjacent to the candidate frequency in the spectrum; The tracking module is used to determine a target curve that meets a preset condition from at least one curve included in the curve cluster, and determine the user's heart rate based on the target curve.

22. The heart rate tracking device based on a wearable device as claimed in claim 21, characterized in that: The processing module is used for: Obtaining, according to the frequency spectrum, at least one candidate frequency corresponding to a current moment and at least one candidate frequency corresponding to a moment before the current moment; Performing pairing processing on at least one candidate frequency corresponding to the current moment and at least one candidate frequency corresponding to the previous moment; In response to the first candidate frequency corresponding to the current moment and the second candidate frequency corresponding to the previous moment being paired successfully, the curve cluster is obtained according to the first candidate frequency and the second candidate frequency.

23. An electronic device, characterized in that: include: processor; a memory for storing instructions executable by the processor; The processor is configured to execute the instructions to implement the heart rate tracking method based on a wearable device as described in any one of claims 1-8, or the heart rate tracking method based on a wearable device as described in any one of claims 9-15.

24. A non-transitory computer-readable storage medium, characterized in that: When the instructions in the storage medium are executed by an electronic device, the electronic device is enabled to execute the heart rate tracking method based on a wearable device as described in any one of claims 1-8, or the heart rate tracking method based on a wearable device as described in any one of claims 9-15.

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