Heart rate detection method and wearable device

Abstract

The present disclosure provides a heart rate detection method and a wearable device, wherein the method includes: obtaining a first reflected light signal and a second reflected light signal; wherein the first reflected light signal is obtained by reflecting the first light signal from a target object whose heart rate is to be measured, and the second reflected light signal is obtained by reflecting the second light signal from the target object; the wavelength of the first light signal is smaller than the wavelength of the second light signal; converting the first reflected light signal from the time domain to the frequency domain to obtain a first frequency domain signal; converting the second reflected light signal from the time domain to the frequency domain to obtain a second frequency domain signal; determining a noise signal based on a first energy difference between the first frequency domain signal and the second frequency domain signal; and performing noise reduction processing on the first frequency domain signal according to the noise signal to obtain a heart rate signal of the target object.

Description

Technical Field

[0001] The present disclosure relates to the field of electronic technology, and in particular to a heart rate detection method and a wearable device. Background Art

[0002] Heart rate detection is a fundamental function of wearable devices. Wearable devices can measure heart rate using technologies such as photoplethysmography (PPG). However, this method is susceptible to contamination from ambient noise and motion interference, resulting in inaccurate heart rate information. Summary of the Invention

[0003] The present disclosure provides a heart rate detection method and a wearable device.

[0004] According to a first aspect of an embodiment of the present disclosure, a heart rate detection method is provided, the method comprising: acquiring a first reflected light signal and a second reflected light signal; wherein, the first reflected light signal is obtained by reflecting the first light signal from a target object for measuring the heart rate, and the second reflected light signal is obtained by reflecting the second light signal from the target object; the wavelength of the first light signal is smaller than the wavelength of the second light signal; performing a time domain to frequency domain conversion on the first reflected light signal to obtain a first frequency domain signal; performing a time domain to frequency domain conversion on the second reflected light signal to obtain a second frequency domain signal; determining a noise signal based on a first energy difference between the first frequency domain signal and the second frequency domain signal; and performing a noise reduction process on the first frequency domain signal according to the noise signal to obtain a heart rate signal of the target object.

[0005] In some optional embodiments, the first optical signal is green light, and the second optical signal is red light or infrared light.

[0006] In some optional embodiments, determining the noise signal based on the first energy difference between the first frequency domain signal and the second frequency domain signal includes: determining that the first frequency domain signal or the second frequency domain signal is a noise signal when the first energy difference is less than a preset first threshold; or determining that the second frequency domain signal is a noise signal when the first energy difference is greater than or equal to the first threshold and less than or equal to a second threshold; wherein the second threshold is greater than the first threshold; or determining that the noise signal is zero when the first energy difference is greater than the second threshold.

[0007] In some optional embodiments, before performing noise reduction processing on the first frequency domain signal according to the noise signal to obtain the heart rate signal of the target object, it also includes: when the noise signal is divided into at least two window signals, based on the noise signal in the previous window signal, performing weighted processing on the noise signal in the current window signal.

[0008] In some optional embodiments, before converting the first reflected light signal from the time domain to the frequency domain to obtain a first frequency domain signal; and converting the second reflected light signal from the time domain to the frequency domain to obtain a second frequency domain signal, the method further includes: performing at least one of the following processing on the reflected light signal: high-pass filtering processing, normalization processing; wherein the reflected light signal includes the first reflected light signal or the second reflected light signal.

[0009] In some optional embodiments, before determining the noise signal based on the first energy difference between the first frequency domain signal and the second frequency domain signal, the method further includes: performing sliding average processing on the first frequency domain signal and the second frequency domain signal respectively.

[0010] In some optional embodiments, before determining the noise signal based on the first energy difference between the first frequency domain signal and the second frequency domain signal, it also includes: when the frequency domain signal is divided into at least two window signals, based on the frequency domain signal in the previous window signal, weighted processing is performed on the frequency domain signal in the current window signal; wherein the frequency domain signal includes the first frequency domain signal or the second frequency domain signal.

[0011] In some optional embodiments, the denoising process is performed on the first frequency domain signal according to the noise signal to obtain the heart rate signal of the target object, including: determining a second energy difference according to the first frequency domain signal and the second frequency domain signal; determining gain data according to the second energy difference and the noise signal; and determining the heart rate signal of the target object according to the first frequency domain signal based on the gain data.

[0012] According to a second aspect of an embodiment of the present disclosure, a heart rate detection device is provided, comprising: a reflected light signal acquisition module for acquiring a first reflected light signal and a second reflected light signal; wherein the first reflected light signal is obtained by reflecting the first light signal from a target object for measuring the heart rate, and the second reflected light signal is obtained by reflecting the second light signal from the target object; the wavelength of the first light signal is smaller than the wavelength of the second light signal; a frequency domain conversion module for performing time domain to frequency domain conversion on the first reflected light signal to obtain a first frequency domain signal; and performing time domain to frequency domain conversion on the second reflected light signal to obtain a second frequency domain signal; a noise signal determination module for determining a noise signal based on a first energy difference between the first frequency domain signal and the second frequency domain signal; and a noise reduction processing module for performing noise reduction processing on the first frequency domain signal according to the noise signal to obtain a heart rate signal of the target object.

[0013] In some optional embodiments, the first optical signal is green light, and the second optical signal is red light or infrared light.

[0014] In some optional embodiments, the noise signal determination module, when used to determine the noise signal based on the first energy difference between the first frequency domain signal and the second frequency domain signal, includes: when the first energy difference is less than a preset first threshold, determining that the first frequency domain signal or the second frequency domain signal is a noise signal; or, when the first energy difference is greater than or equal to the first threshold and less than or equal to a second threshold, determining that the second frequency domain signal is a noise signal; wherein the second threshold is greater than the first threshold; or, when the first energy difference is greater than the second threshold, determining that the noise signal is zero.

[0015] In some optional embodiments, the device further includes: a noise signal weighted processing module for performing weighted processing on the noise signal in the current window signal based on the noise signal in the previous window signal when the noise signal is divided into at least two window signals.

[0016] In some optional embodiments, the device further includes: a reflected light signal processing module, configured to perform at least one of the following processing on the reflected light signal: high-pass filtering processing, normalization processing; wherein the reflected light signal includes the first reflected light signal or the second reflected light signal.

[0017] In some optional embodiments, the apparatus further includes: a sliding average processing module, configured to perform sliding average processing on the first frequency domain signal and the second frequency domain signal respectively.

[0018] In some optional embodiments, the device also includes: a frequency domain signal weighted processing module, which is used to perform weighted processing on the frequency domain signal in the current window signal based on the frequency domain signal in the previous window signal when the frequency domain signal is divided into at least two window signals; wherein the frequency domain signal includes the first frequency domain signal or the second frequency domain signal.

[0019] In some optional embodiments, the noise reduction processing module, when used to perform noise reduction processing on the first frequency domain signal based on the noise signal to obtain the heart rate signal of the target object, includes: determining a second energy difference based on the first frequency domain signal and the second frequency domain signal; determining gain data based on the second energy difference and the noise signal; and determining the heart rate signal of the target object based on the first frequency domain signal based on the gain data.

[0020] According to a third aspect of an embodiment of the present disclosure, a wearable device is provided, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein when the processor executes the program, the heart rate detection method described in any one of the first aspects is implemented.

[0021] According to a fourth aspect of an embodiment of the present disclosure, a computer-readable storage medium is provided, on which a computer program is stored. When the program is executed by a processor, the heart rate detection method described in any one of the first aspects is implemented.

[0022] According to a fifth aspect of an embodiment of the present disclosure, a computer program product is provided, comprising a computer program, which, when executed by a processor, implements the heart rate detection method described in any one of the first aspects.

[0023] In the disclosed embodiment, after acquiring the first and second reflected light signals, the acquired reflected light signals are converted from the time domain to the frequency domain to obtain corresponding first and second frequency domain signals. This allows the determination of a noise signal based on a first energy difference between the first and second frequency domain signals. The first frequency domain signal is then subjected to noise reduction processing based on the noise signal to obtain the target subject's heart rate signal. This heart rate detection method does not rely on the ACC signal as a reference for noise reduction processing of the acquired first reflected light signal. Instead, noise reduction processing of the first frequency domain signal is performed based on the energy difference between the first and second frequency domain signals, resulting in more accurate heart rate information.

[0024] It is to be understood that both the foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of the disclosure. BRIEF DESCRIPTION OF THE DRAWINGS

[0025] The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the present disclosure and, together with the description, serve to explain the principles of the present disclosure.

[0026] Figure 1 is a flow chart showing a heart rate detection method according to an exemplary embodiment;

[0027] Figure 2 is a flowchart showing a noise reduction process according to an exemplary embodiment;

[0028] Figure 3 is a time-frequency diagram without noise reduction processing according to an exemplary embodiment;

[0029] Figure 4 is a time-frequency diagram after noise reduction processing according to an exemplary embodiment;

[0030] Figure 5 is a schematic diagram of a heart rate detection device according to an exemplary embodiment;

[0031] Figure 6 is a schematic diagram of another heart rate detection device according to an exemplary embodiment;

[0032] Figure 7 The figure is a schematic structural diagram of a wearable device according to an exemplary embodiment. DETAILED DESCRIPTION

[0033] Exemplary embodiments will be described in detail herein, with examples illustrated in the accompanying drawings. In the following description, when referring to the drawings, identical numerals in different figures represent identical or similar elements, unless otherwise indicated. The specific aspects described in the following exemplary embodiments are not intended to be exhaustive and should not be construed as representing all possible implementations consistent with the present disclosure. Rather, they are merely examples of apparatus and methods consistent with certain aspects of the present disclosure, as detailed in the appended claims.

[0034] The terms used in this disclosure are for the purpose of describing specific embodiments only and are not intended to limit the disclosure. As used in this disclosure and the appended claims, the singular forms "a," "an," "the," and "the" are intended to include the plural forms as well, unless the context clearly indicates otherwise. It should also be understood that the term "and / or" as used herein refers to and encompasses any and all possible combinations of one or more of the associated listed items.

[0035] It should be understood that although the terms first, second, third, etc. may be used in this disclosure to describe various information, such information should not be limited to these terms. These terms are only used to distinguish information of the same type from each other. For example, without departing from the scope of this disclosure, first information may also be referred to as second information, and similarly, second information may also be referred to as first information. Depending on the context, the word "if" as used herein may be interpreted as "at the time of" or "when" or "in response to determining."

[0036] Heart rate detection is one of the most important features for wearable device users. In related heart rate detection technologies, wearable devices use LEDs to illuminate the subject's skin and calculate heart rate by detecting changes in the reflected light (PPG signal). This heart rate detection method is susceptible to environmental noise, motion interference, and other factors, resulting in inaccurate heart rate information.

[0037] In related technologies, to calculate more accurate heart rate information, the collected PPG signal needs to be subjected to noise reduction processing to reduce the impact of environmental noise and motion interference on heart rate calculation. Two common processing methods are used: one that processes time-domain data, such as adaptive filtering, and the other that processes frequency-domain data, such as spectral subtraction. Both methods use accelerometer information (ACC signal) as a reference to perform noise reduction on the received PPG signal.

[0038] However, when using the ACC signal as a reference to perform noise reduction on the PPG signal, ideal noise reduction effects cannot be achieved in many cases. Schemes that process time-domain data generally have a better noise reduction effect on PPG signals generated by periodic motion, but have a poorer noise reduction effect on PPG signals generated by non-periodic motion or short motion duration. Schemes that process frequency-domain data can only achieve a better noise reduction effect when the frequency energy distribution of the ACC signal and the PPG signal are consistent. However, due to the hardware accuracy of the accelerometer, the ACC signal cannot always maintain the same frequency energy distribution as the PPG signal, and thus cannot achieve a good noise reduction effect on the PPG signal.

[0039] Based on the above, the present disclosure provides a heart rate detection method. After obtaining the first reflected light signal and the second reflected light signal, the obtained reflected light signal is converted from the time domain to the frequency domain to obtain the corresponding first frequency domain signal and the second frequency domain signal, so that the noise signal can be determined based on the first energy difference between the first frequency domain signal and the second frequency domain signal, and then the first frequency domain signal is denoised according to the noise signal to obtain the heart rate signal of the target object.

[0040] In this heart rate detection method, the noise reduction processing of the acquired first reflected light signal is not performed relying on the ACC signal as a reference. Instead, the noise reduction processing of the first frequency domain signal is performed based on the energy difference between the first frequency domain signal and the second frequency domain signal, thereby obtaining more accurate heart rate information.

[0041] In order to make the heart rate detection method provided by the present disclosure clearer, the execution process of the solution provided by the present disclosure is described in detail below with reference to the accompanying drawings and specific embodiments.

[0042] See also Figure 1 , Figure 1 FIG. 1 is a flow chart of a heart rate detection method according to an embodiment of the present disclosure. Figure 1 As shown, the process includes:

[0043] Step 101, obtaining a first reflected light signal and a second reflected light signal; wherein, the first reflected light signal is obtained by the target object whose heart rate is to be measured reflecting the first light signal, and the second reflected light signal is obtained by the target object reflecting the second light signal; the wavelength of the first light signal is smaller than the wavelength of the second light signal.

[0044] In an embodiment of the present disclosure, a first light signal and a second light signal can be sent to a target object whose heart rate is to be measured, and the wavelength of the first light signal is smaller than the wavelength of the second light signal. In one possible implementation, the first light signal and the second light signal can be sent to the target object at the same time. Since the wavelengths of the first light signal and the second light signal are different, the depths at which the first light signal and the second light signal penetrate the skin are different, so that the collected first reflected light signal and the second reflected light signal are subject to different degrees of motion interference, and noise reduction processing of the first reflected light signal can be implemented based on this feature. In some optional embodiments, the first light signal is green light, and the second light signal is red light or infrared light.

[0045] For example, the first light signal is green light, and the second light signal is red light. This step can include sending a green light signal to the skin of the human subject whose heart rate is to be measured, and obtaining a first reflected light signal reflected from the green light signal; and sending a red light signal to the skin of the human subject whose heart rate is to be measured, and obtaining a second reflected light signal reflected from the red light signal. In one possible implementation, the first and second reflected light signals can be obtained simultaneously. Either the first or second reflected light signal can be a PPG signal.

[0046] Step 102: Convert the first reflected light signal from the time domain to the frequency domain to obtain a first frequency domain signal; and convert the second reflected light signal from the time domain to the frequency domain to obtain a second frequency domain signal.

[0047] The first reflected light signal and the second reflected light signal acquired in step 101 are time domain data. In this step, the time domain data can be converted into corresponding frequency domain data to obtain corresponding first frequency domain signals and second frequency domain signals. There are various methods for converting the time domain data into frequency domain data, and this embodiment does not limit the specific conversion method.

[0048] For example, a Fourier transform can be performed on the time domain data, and then a modulus calculation can be performed on the Fourier transform result to ultimately obtain frequency domain data. For example, using green light as the first optical signal and red light as the second optical signal, a green light PPG signal reflected from the green light can be collected as the first reflected optical signal, and a red light PPG signal reflected from the red light can be collected as the second reflected optical signal. In this step, a Fourier transform can be performed on the collected green light PPG signal to obtain the spectrum data corresponding to the green light PPG signal, denoted as F-Green; and a Fourier transform can be performed on the collected red light PPG signal to obtain the spectrum data corresponding to the red light PPG signal, denoted as F-Red. Since the Fourier transform result is in imaginary form, a modulus calculation can be performed on the Fourier transform result, namely, calculating the modulus of F-Green and denoting it as P-Green; and calculating the modulus of F-Red and denoting it as P-Red. P-Green can be considered the first frequency domain signal in this step, and P-Red can be considered the second frequency domain signal in this step.

[0049] In some optional embodiments, before converting the first reflected light signal from the time domain to the frequency domain to obtain a first frequency domain signal; and converting the second reflected light signal from the time domain to the frequency domain to obtain a second frequency domain signal, the method further includes: performing at least one of the following processing on the reflected light signal: high-pass filtering processing, normalization processing; wherein the reflected light signal includes the first reflected light signal or the second reflected light signal.

[0050] In the above optional embodiment, the reflected light signal may be subjected to high-pass filtering before being converted into a frequency domain signal. For example, the first transmitted light signal in the reflected light signal may be subjected to high-pass filtering with a step frequency of 0.5 Hz to remove the influence of the baseline in the first reflected light signal. Similarly, the second reflected light signal may be subjected to high-pass filtering to remove the influence of the baseline in the second reflected light signal.

[0051] In the above optional embodiment, the reflected light signal may be normalized before being converted into a frequency domain signal. Because the first reflected light signal and the second reflected light signal differ in intensity, to avoid poor noise reduction due to inconsistent energy ranges, this embodiment may perform normalization on each of the first and second reflected light signals. The method of normalization is not specifically limited.

[0052] For example, the normalization of the first reflected light signal is described as follows. For example, a square operation can be performed on each point X in the first reflected light signal to obtain the energy V corresponding to the point, and then the energy V can be updated by referring to an exponential decaying method. The energy V at any point can be updated according to the following formula:

[0053] V new =alpha*V old +(1-alpha)*V

[0054] Among them, V new is the updated energy; V old is the energy of the adjacent previous point; alpha is the preset update weight; V is the energy of the current point to be updated.

[0055] After the energy V is updated, X can be divided by V. new The square root of x new , x new This is the result of the normalization process of X. It should be noted that the above normalization process is only for illustrative purposes and does not constitute a specific limitation.

[0056] Step 103: Determine a noise signal based on a first energy difference between the first frequency domain signal and the second frequency domain signal.

[0057] In this step, a first energy difference value can be determined based on the energy difference between the first frequency domain signal and the second frequency domain signal, and a noise signal (denoted as P-NN) can be further determined based on the first energy difference value. The first energy difference value is used to represent the energy difference between the first frequency domain signal and the second frequency domain signal. It is understood that there are multiple specific processes for determining the first energy difference value, and a specific one is described below as an example.

[0058] For example, P-Red can be subtracted from P-Green, and the result divided by the sum of P-Green and P-Red at the frequency point to obtain a first energy difference. Thus, the noise signal P-NN can be determined based on the magnitude of the first energy difference.

[0059] In some optional embodiments, determining the noise signal based on the first energy difference between the first frequency domain signal and the second frequency domain signal includes: determining that the first frequency domain signal or the second frequency domain signal is a noise signal when the first energy difference is less than a preset first threshold; or determining that the second frequency domain signal is a noise signal when the first energy difference is greater than or equal to the first threshold and less than or equal to a second threshold; wherein the second threshold is greater than the first threshold; or determining that the noise signal is zero when the first energy difference is greater than the second threshold.

[0060] In the above optional embodiment, a first threshold and a second threshold may be pre-set, and the first threshold may be less than the second threshold. The specific values ​​of the first and second thresholds may be obtained based on experimental data or empirical values, and are not limited in this embodiment. After the first and second thresholds are set, in the above embodiment, the noise signal may be further determined by determining the relationship between the first energy difference and the threshold.

[0061] When the first energy difference is less than the first threshold, it indicates that both the first frequency domain signal and the second frequency domain signal contain only a background noise signal. In this case, the noise signal P-NN can be determined as the first frequency domain signal or the second frequency domain signal. When the first energy difference is greater than or equal to the first threshold and less than or equal to the second threshold, it indicates that both the first frequency domain signal and the second frequency domain signal contain a motion interference signal. In this case, the second frequency domain signal can be determined as the noise signal P-NN. When the first energy difference is greater than the second threshold, it indicates that the first frequency domain signal does not contain a noise signal. In this case, the noise signal P-NN can be determined as zero.

[0062] In some optional embodiments, before determining the noise signal based on the first energy difference between the first frequency domain signal and the second frequency domain signal, the method further includes: performing sliding average processing on the first frequency domain signal and the second frequency domain signal respectively.

[0063] In the above optional embodiment, before determining the first energy difference based on the first frequency domain signal and the second frequency domain signal, a moving average process may be performed on each of the first frequency domain signal and the second frequency domain signal to remove the effects of signal mutations. For example, a moving average process may be performed on each of P-Green and P-Red to obtain SP-Green and SP-Red, respectively.

[0064] In some optional embodiments, before determining the noise signal based on the first energy difference between the first frequency domain signal and the second frequency domain signal, it also includes: when the frequency domain signal is divided into at least two window signals, based on the frequency domain signal in the previous window signal, weighted processing is performed on the frequency domain signal in the current window signal; wherein the frequency domain signal includes the first frequency domain signal or the second frequency domain signal.

[0065] In the above optional embodiment, the frequency domain signal can be pre-windowed to obtain at least two window signals. For example, frequency domain data obtained by converting time domain data of a fixed duration can be used as a window signal. After obtaining at least two window signals, the frequency domain signal at any point in the current window can be weighted based on the frequency domain signal in the previous window signal to update the frequency domain signal in the current window, thereby preventing calculation distortion caused by excessive signal variation between different window signals.

[0066] The specific method for weighting the frequency domain signal in the current window signal is not limited and is described below as an example. For example, the frequency domain signal of any frequency point X1 in the current window signal is: SP-Green1; the frequency point corresponding to frequency point X1 in the previous window signal is X2, and the frequency domain signal of frequency point X2 is: SP-Green2. The weight value of the current window signal can be pre-set to α, and the frequency domain signal SP-Green1 of frequency point X1 in the current window signal can be updated to: α*SP-Green1+(1-α)*SP-Green2.

[0067] Step 104: Perform noise reduction processing on the first frequency domain signal according to the noise signal to obtain a heart rate signal of the target object.

[0068] In the disclosed embodiment, the first reflected light signal is used as the primary signal, and the second reflected light signal is used as the reference signal. Therefore, after determining the noise signal, this step can perform noise reduction processing on the first reflected light signal, which serves as the primary signal, based on the determined noise signal to obtain the target subject's heart rate signal.

[0069] In some optional embodiments, before performing noise reduction processing on the first frequency domain signal according to the noise signal to obtain the heart rate signal of the target object, it also includes: when the noise signal is divided into at least two window signals, based on the noise signal in the previous window signal, performing weighted processing on the noise signal in the current window signal.

[0070] In the above optional embodiment, the noise signal may be pre-windowed to obtain at least two window signals. Furthermore, the noise signal in the current window signal may be weighted based on the noise signal in the previous window signal to prevent excessive variation in noise signals between different window signals, which may cause computational distortion. The specific process of weighting the noise signal may be referenced to the description of weighting the frequency domain signal, and will not be further elaborated herein.

[0071] In some optional embodiments, such as Figure 2 As shown, the specific implementation of step 104 may include the following steps:

[0072] Step 201: Determine a second energy difference according to the first frequency domain signal and the second frequency domain signal.

[0073] In this embodiment, the second energy difference is used to represent the energy difference between the first frequency domain signal and the second frequency domain signal. Taking P-Green as the first frequency domain signal and P-Red as the second frequency domain signal as an example, this step can calculate the energy difference on the spectrum by subtracting P-Red from P-Green (negative numbers are set to zero), obtaining the second energy difference and recording it as P-Diff.

[0074] Step 202: Determine gain data according to the second energy difference and the noise signal.

[0075] The gain data is used to represent the proportion of the effective heart rate signal in the first frequency domain data. Specifically, the gain data can be obtained by dividing the second energy difference value P-Diff by the sum of the second energy difference value P-Diff and the noise signal P-NN and recorded as G.

[0076] Step 203: Determine the heart rate signal of the target object according to the first frequency domain signal based on the gain data.

[0077] After obtaining the gain data G, this step can perform a dot product between the gain data G and the first frequency domain signal P-Green to obtain a filtered signal spectrum as the target subject's heart rate signal. This allows for more accurate calculation of the target subject's heart rate information based on the obtained heart rate signal.

[0078] In the heart rate detection process of the disclosed embodiment, the ACC signal is not used as a reference. Instead, the second frequency domain signal is used as a reference signal for noise reduction of the first frequency domain signal. The noise signal is determined based on the energy difference between the two frequency domain signals, ultimately achieving noise reduction of the first frequency domain signal. This approach can reduce the influence of noise such as environmental noise and motion interference on the first frequency domain signal, thereby detecting more accurate heart rate information.

[0079] This heart rate detection method does not rely on the ACC signal as a reference, effectively reducing noise generated by both periodic and non-periodic motion. Furthermore, by using a second reflected light signal instead of the accelerometer signal as a reference, this method is no longer limited by the frequency energy distribution of the ACC signal and the PPG signal being consistent or strongly correlated. Furthermore, while the ACC signal becomes increasingly weak during non-periodic motion, the second reflected light signal remains unaffected by the varying conditions.

[0080] For more intuitive and specific effects, please refer to Figure 3 、 Figure 4 The time-frequency diagram shown in Figure 1 is as follows. Figure 3 This is a time-frequency diagram directly drawn based on the first reflected light signal without being processed according to the heart rate detection method provided by the present disclosure. Figure 4 This is a time-frequency plot based on the first reflected light signal after noise reduction, processed according to the heart rate detection method provided in this disclosure. In both figures, the ordinate represents energy value, and the abscissa represents different moments. The white highlights in the figures represent the corresponding heart rate information or interfering noise. Both figures use 150 seconds as the boundary, with periods before 150 seconds corresponding to non-periodic motion and periods after 150 seconds corresponding to periodic walking and running.

[0081] Figure 4 Compared to Figure 3 It can be clearly confirmed that the heart rate detection method provided by the present invention can achieve very obvious effects in both periodic and non-periodic motions, effectively suppressing noise signals, thereby more accurately calculating the heart rate information of the target object.

[0082] Figure 5 As shown, the present disclosure provides a heart rate detection device that can perform the heart rate detection method of any embodiment of the present disclosure. The device may include a reflected light signal acquisition module 501, a frequency domain conversion module 502, a noise signal determination module 503, and a noise reduction processing module 504.

[0083] A reflected light signal acquisition module 501 is configured to acquire a first reflected light signal and a second reflected light signal; wherein the first reflected light signal is obtained by reflecting the first light signal from the target object whose heart rate is to be measured, and the second reflected light signal is obtained by reflecting the second light signal from the target object; and the wavelength of the first light signal is smaller than the wavelength of the second light signal.

[0084] The frequency domain conversion module 502 is configured to convert the first reflected light signal from the time domain to the frequency domain to obtain a first frequency domain signal; and convert the second reflected light signal from the time domain to the frequency domain to obtain a second frequency domain signal;

[0085] A noise signal determining module 503 is configured to determine a noise signal based on a first energy difference between the first frequency domain signal and the second frequency domain signal;

[0086] The noise reduction processing module 504 is configured to perform noise reduction processing on the first frequency domain signal according to the noise signal to obtain a heart rate signal of the target object.

[0087] Optionally, the first optical signal is green light, and the second optical signal is red light or infrared light.

[0088] Optionally, the noise signal determination module 503, when used to determine the noise signal based on the first energy difference between the first frequency domain signal and the second frequency domain signal, includes: when the first energy difference is less than a preset first threshold, determining that the first frequency domain signal or the second frequency domain signal is a noise signal; or, when the first energy difference is greater than or equal to the first threshold and less than or equal to a second threshold, determining that the second frequency domain signal is a noise signal; wherein the second threshold is greater than the first threshold; or, when the first energy difference is greater than the second threshold, determining that the noise signal is zero.

[0089] Alternatively, as Figure 6 As shown, the device also includes: a reflected light signal processing module 601, which is used to perform at least one of the following processing on the reflected light signal: high-pass filtering processing, normalization processing; wherein, the reflected light signal includes the first reflected light signal or the second reflected light signal.

[0090] Alternatively, as Figure 6 As shown, the apparatus further includes: a sliding average processing module 602, configured to perform sliding average processing on the first frequency domain signal and the second frequency domain signal respectively.

[0091] Alternatively, as Figure 6 As shown, the device also includes: a frequency domain signal weighted processing module 603, which is used to perform weighted processing on the frequency domain signal in the current window signal based on the frequency domain signal in the previous window signal when the frequency domain signal is divided into at least two window signals; wherein the frequency domain signal includes the first frequency domain signal or the second frequency domain signal.

[0092] Optionally, the noise reduction processing module 504, when used to perform noise reduction processing on the first frequency domain signal based on the noise signal to obtain the heart rate signal of the target object, includes: determining a second energy difference based on the first frequency domain signal and the second frequency domain signal; determining gain data based on the second energy difference and the noise signal; and determining the heart rate signal of the target object based on the first frequency domain signal based on the gain data.

[0093] Alternatively, as Figure 6 As shown, the apparatus further includes: a noise signal weighted processing module 604 for performing weighted processing on the noise signal in the current window signal based on the noise signal in the previous window signal when the noise signal is divided into at least two window signals.

[0094] For the device embodiments, since they basically correspond to the method embodiments, the relevant parts can be referred to the partial description of the method embodiments. The device embodiments described above are merely illustrative, wherein the units described as separate components may or may not be physically separated, and the components displayed as units may or may not be physical units, that is, they may be located in one place, or they may be distributed on multiple network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of at least one embodiment of the present disclosure. A person of ordinary skill in the art can understand and implement the present invention without paying any creative work.

[0095] The present disclosure also provides a wearable device, including a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the program, the heart rate detection method of any embodiment of the present disclosure can be implemented.

[0096] Figure 7 FIG1 shows a more specific hardware structure diagram of a wearable device provided by an embodiment of the present disclosure. The device may include: a processor 1010, a memory 1020, an input / output interface 1030, a communication interface 1040, and a bus 1050. The processor 1010, the memory 1020, the input / output interface 1030, and the communication interface 1040 are connected to each other within the device via the bus 1050.

[0097] The processor 1010 can be implemented using a general-purpose CPU (Central Processing Unit), a microprocessor, an application-specific integrated circuit (ASIC), or one or more integrated circuits, and is used to execute relevant programs to implement the technical solutions provided in the embodiments of this specification.

[0098] The memory 1020 can be implemented in the form of ROM (Read Only Memory), RAM (Random Access Memory), static storage devices, dynamic storage devices, etc. The memory 1020 can store an operating system and other application programs. When the technical solutions provided in the embodiments of this specification are implemented through software or firmware, the relevant program code is stored in the memory 1020 and is called and executed by the processor 1010.

[0099] The input / output interface 1030 is used to connect input / output modules to implement information input and output. The input / output modules can be configured as components within the device (not shown in the figure) or can be externally connected to the device to provide corresponding functions. Input devices may include a keyboard, mouse, touch screen, microphone, various sensors, etc., and output devices may include a display, speaker, vibrator, indicator light, etc.

[0100] The communication interface 1040 is used to connect to a communication module (not shown) to enable communication between the device and other devices. The communication module can communicate via a wired method (such as USB, network cable, etc.) or a wireless method (such as mobile network, WiFi, Bluetooth, etc.).

[0101] The bus 1050 comprises a path for transmitting information between the various components of the device (eg, the processor 1010 , the memory 1020 , the input / output interface 1030 , and the communication interface 1040 ).

[0102] It should be noted that although the above device only shows the processor 1010, the memory 1020, the input / output interface 1030, the communication interface 1040, and the bus 1050, in a specific implementation, the device may also include other components necessary for normal operation. In addition, it will be understood by those skilled in the art that the above device may only include the components necessary to implement the embodiments of this specification, and does not necessarily include all the components shown in the figure.

[0103] The present disclosure also provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, can implement the heart rate detection method of any embodiment of the present disclosure.

[0104] The non-transitory computer-readable storage medium may be a ROM, a random access memory (RAM), a CD-ROM, a magnetic tape, a floppy disk, an optical data storage device, etc., and the present disclosure is not limited thereto.

[0105] In some optional embodiments, the present disclosure provides a computer program product comprising computer-readable code. When the computer-readable code is executed on a device, a processor in the device executes instructions for implementing the heart rate detection method provided in any of the above embodiments. The computer program product may be implemented in hardware, software, or a combination thereof.

[0106] Other embodiments of the present disclosure will readily occur to those skilled in the art after considering the specification and practicing the inventions claimed herein. This disclosure is intended to cover any variations, uses, or adaptations of the present disclosure that follow the general principles of the present disclosure and include common knowledge or customary techniques in the art not claimed herein. The description and examples are to be considered as exemplary only, with the true scope and spirit of the present disclosure being indicated by the following claims.

[0107] It should be understood that the present disclosure is not limited to the exact structures that have been described above and shown in the drawings, and that various modifications and changes can be made without departing from the scope thereof. The scope of the present disclosure is limited only by the appended claims.

[0108] The above description is only a preferred embodiment of the present disclosure and is not intended to limit the present disclosure. Any modifications, equivalent replacements, improvements, etc. made within the spirit and principles of the present disclosure should be included in the scope of protection of the present disclosure.

Claims

1. A heart rate detection method, characterized in that: The method comprises: Acquire a first reflected light signal and a second reflected light signal; wherein the first reflected light signal is obtained by reflecting the first light signal from the target object whose heart rate is to be measured, and the second reflected light signal is obtained by reflecting the second light signal from the target object; and the wavelength of the first light signal is smaller than the wavelength of the second light signal; Converting the first reflected light signal from the time domain to the frequency domain to obtain a first frequency domain signal; Converting the second reflected light signal from the time domain to the frequency domain to obtain a second frequency domain signal; Determine a noise signal based on a first energy difference between the first frequency domain signal and the second frequency domain signal, wherein the noise signal is the first frequency domain signal, the second frequency domain signal, or zero; According to the noise signal, noise reduction processing is performed on the first frequency domain signal to obtain the heart rate signal of the target object.

2. The method according to claim 1, characterized in that The first optical signal is green light, and the second optical signal is red light or infrared light.

3. The method according to claim 1, characterized in that The determining of the noise signal based on the first energy difference between the first frequency domain signal and the second frequency domain signal includes: A noise signal is determined by comparing a first energy difference between the first frequency domain signal and the second frequency domain signal with at least one preset threshold.

4. The method according to claim 1, wherein The determining of the noise signal based on the first energy difference between the first frequency domain signal and the second frequency domain signal includes at least one of the following: When the first energy difference is less than a preset first threshold, determining that the first frequency domain signal or the second frequency domain signal is a noise signal; When the first energy difference is greater than or equal to the first threshold and less than or equal to a second threshold, determining that the second frequency domain signal is a noise signal; wherein the second threshold is greater than the first threshold; When the first energy difference is greater than the second threshold, the noise signal is determined to be zero.

5. The method according to claim 1, wherein Before performing noise reduction processing on the first frequency domain signal according to the noise signal to obtain the heart rate signal of the target object, the method further includes: In the case where the noise signal is divided into at least two window signals, weighted processing is performed on the noise signal in the current window signal based on the noise signal in the previous window signal to obtain the updated noise signal in the current window.

6. The method according to claim 1, characterized in that Before converting the first reflected light signal from the time domain to the frequency domain to obtain a first frequency domain signal; and converting the second reflected light signal from the time domain to the frequency domain to obtain a second frequency domain signal, the method further includes: At least one of the following processing is performed on the reflected light signal: high-pass filtering processing, normalization processing; wherein the reflected light signal includes the first reflected light signal or the second reflected light signal.

7. The method according to claim 1, characterized in that Before determining the noise signal based on the first energy difference between the first frequency domain signal and the second frequency domain signal, the method further includes: Perform sliding average processing on the first frequency domain signal and the second frequency domain signal respectively.

8. The method according to claim 1, characterized in that Before determining the noise signal based on the first energy difference between the first frequency domain signal and the second frequency domain signal, the method further includes: When the frequency domain signal is divided into at least two window signals, the frequency domain signal in the current window signal is weighted based on the frequency domain signal in the previous window signal to obtain an updated frequency domain signal in the current window signal; wherein the frequency domain signal includes the first frequency domain signal or the second frequency domain signal.

9. The method according to any one of claims 1 to 8, characterized in that The step of performing noise reduction processing on the first frequency domain signal according to the noise signal to obtain the heart rate signal of the target object includes: determining a second energy difference according to the first frequency domain signal and the second frequency domain signal; determining gain data according to the second energy difference and the noise signal; Based on the gain data, a heart rate signal of the target object is determined according to the first frequency domain signal.

10. A heart rate detection device, characterized in that: The device comprises: a reflected light signal acquisition module, configured to acquire a first reflected light signal and a second reflected light signal; wherein the first reflected light signal is obtained by the target object whose heart rate is to be measured reflecting the first light signal, and the second reflected light signal is obtained by the target object reflecting the second light signal; and the wavelength of the first light signal is smaller than the wavelength of the second light signal; a frequency domain conversion module, configured to convert the first reflected light signal from the time domain to the frequency domain to obtain a first frequency domain signal; and convert the second reflected light signal from the time domain to the frequency domain to obtain a second frequency domain signal; a noise signal determining module, configured to determine a noise signal based on a first energy difference between the first frequency domain signal and the second frequency domain signal, wherein the noise signal is the first frequency domain signal, the second frequency domain signal, or zero; The noise reduction processing module is used to perform noise reduction processing on the first frequency domain signal according to the noise signal to obtain the heart rate signal of the target object.

11. The device according to claim 10, characterized in that The first optical signal is green light, and the second optical signal is red light or infrared light.

12. The device according to claim 10, characterized in that The noise signal determination module, when used to determine the noise signal based on the first energy difference between the first frequency domain signal and the second frequency domain signal, includes: A noise signal is determined by comparing a first energy difference between the first frequency domain signal and the second frequency domain signal with at least one preset threshold.

13. The device according to claim 10, characterized in that The noise signal determination module, when used to determine the noise signal based on the first energy difference between the first frequency domain signal and the second frequency domain signal, includes at least one of the following: When the first energy difference is less than a preset first threshold, determining that the first frequency domain signal or the second frequency domain signal is a noise signal; When the first energy difference is greater than or equal to the first threshold and less than or equal to a second threshold, determining that the second frequency domain signal is a noise signal; wherein the second threshold is greater than the first threshold; When the first energy difference is greater than the second threshold, the noise signal is determined to be zero.

14. The device according to claim 10, characterized in that The device further comprises: The noise signal weighted processing module is used to perform weighted processing on the noise signal in the current window signal based on the noise signal in the previous window signal when the noise signal is divided into at least two window signals, so as to obtain the updated noise signal in the current window.

15. The device according to claim 10, characterized in that The device further comprises: The reflected light signal processing module is used to perform at least one of the following processing on the reflected light signal: high-pass filtering processing, normalization processing; wherein the reflected light signal includes the first reflected light signal or the second reflected light signal.

16. The device according to claim 10, characterized in that The device further comprises: The sliding average processing module is used to perform sliding average processing on the first frequency domain signal and the second frequency domain signal respectively.

17. The device according to claim 10, characterized in that The device further comprises: A frequency domain signal weighted processing module is used to perform weighted processing on the frequency domain signal in the current window signal based on the frequency domain signal in the previous window signal when the frequency domain signal is divided into at least two window signals, so as to obtain an updated frequency domain signal in the current window signal; wherein the frequency domain signal includes the first frequency domain signal or the second frequency domain signal.

18. The device according to any one of claims 10 to 17, characterized in that The noise reduction processing module, when used to perform noise reduction processing on the first frequency domain signal according to the noise signal to obtain the heart rate signal of the target object, includes: determining a second energy difference according to the first frequency domain signal and the second frequency domain signal; determining gain data according to the second energy difference and the noise signal; Based on the gain data, a heart rate signal of the target object is determined according to the first frequency domain signal.

19. A wearable device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein: When the processor executes the program, the method according to any one of claims 1 to 9 is implemented.

20. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the program is executed by a processor, the method according to any one of claims 1 to 9 is implemented.

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