Heart rate correction method, device, equipment, medium and product

Abstract

The embodiment of the invention provides a heart rate correction method and device, equipment, a medium and a product, and the method comprises the steps: obtaining a heart rate signal, and calculating the signal quality score of the heart rate signal and the current detection heart rate according to the heart rate signal, and taking the signal quality score and the current detection heart rate as heart rate parameters; whether the heart rate parameter meets a first condition and a second condition or not is judged, the first condition includes that the signal quality score of the heart rate signal meets a preset requirement, and the second condition includes that the difference between the current detected heart rate and the final heart rate at the last moment does not exceed a preset threshold value; and determining the current final heart rate according to the judgment result of whether the heart rate parameter meets the first condition and the second condition or not. The accuracy of heart rate detection can be improved.

Description

Technical Field

[0001] This application relates to heart rate detection technology. More specifically, it relates to a heart rate correction method, apparatus, device, medium, and product. Background Technology

[0002] As people pay increasing attention to their physical condition and health, wearable heart rate monitoring devices, such as smartwatches, are becoming more widely used. Currently, wearable heart rate monitoring devices mainly use photoplethysmography (PPG) for heart rate detection. This method involves transmitting light of a specific wavelength through biological tissue. Blood pulsation causes periodic changes in the volume of subcutaneous blood vessels, resulting in differences in the absorption spectrum. A photoelectric sensor converts these light intensity fluctuations into electrical signals, and an algorithm calculates the peak intervals of these signals to determine the heart rate.

[0003] However, wearable heart rate monitoring devices are susceptible to noise interference during high-intensity exercise. There is an urgent need for an accurate and reliable heart rate correction method. Summary of the Invention

[0004] This application provides a heart rate correction method, apparatus, device, medium, and product that can improve the accuracy of heart rate detection.

[0005] In a first aspect, embodiments of this application provide a heart rate correction method, including:

[0006] Acquire a heart rate signal, and calculate the signal quality score of the heart rate signal and the current detected heart rate based on the heart rate signal, using these as heart rate parameters;

[0007] Determine whether the heart rate parameter meets the first condition and the second condition. The first condition includes that the signal quality score of the heart rate signal reaches a preset requirement, and the second condition includes that the difference between the current detected heart rate and the final heart rate at the previous moment does not exceed a preset threshold.

[0008] The current final heart rate is determined based on the judgment results of whether the heart rate parameters meet the first and second conditions.

[0009] Optionally, the method includes:

[0010] If the heart rate parameter satisfies either the first condition or the second condition, then the current predicted heart rate is obtained;

[0011] The current predicted heart rate and the current detected heart rate are weighted and summed to obtain the current final heart rate.

[0012] Optionally, the method further includes:

[0013] If all the heart rate parameters satisfy the first condition and the second condition, then the current detected heart rate is taken as the current final heart rate.

[0014] Optionally, the method further includes:

[0015] If none of the heart rate parameters meet the first and second conditions, then the current predicted heart rate is obtained as the current final heart rate.

[0016] Optionally, before determining whether the heart rate parameter meets the first and second conditions, the method further includes:

[0017] Acquire historical accelerometer data for a first preset duration, and determine the current motion type based on the historical accelerometer data;

[0018] Based on the current motion type, determine the corresponding signal quality score threshold.

[0019] Optionally, determining whether the heart rate parameter meets the second condition includes:

[0020] If the signal quality score of the heart rate signal is greater than the signal quality score threshold corresponding to the current exercise type, then the heart rate parameter is determined to meet the second condition.

[0021] Otherwise, the heart rate parameter is determined not to meet the second condition.

[0022] Optionally, obtaining the current predicted heart rate includes:

[0023] Determine the current type of exercise;

[0024] Acquire historical exercise intensity and historical heart rate for a second preset duration under the same exercise type; acquire current accelerometer data;

[0025] Determine the current motion intensity based on the current motion type and the current accelerometer data;

[0026] The current predicted heart rate is obtained based on the current exercise type, the current exercise intensity, the historical exercise intensity, and the historical heart rate.

[0027] Optionally, before obtaining the final heart rate by weighted summation of the current predicted heart rate and the current detected heart rate, the method further includes:

[0028] The weights of predicted heart rate and detected heart rate are determined based on the signal quality score of the heart rate signal and the signal quality score threshold; wherein, the ratio of the signal quality score of the heart rate signal to the signal quality score threshold is positively correlated with the weight of the detected heart rate, and the ratio of the signal quality score of the heart rate signal to the signal quality score threshold is negatively correlated with the weight of the predicted heart rate.

[0029] Optionally, the method further includes:

[0030] If the current detected heart rate is calculated as an invalid value based on the heart rate signal, then the second condition is not met.

[0031] Secondly, embodiments of this application provide a heart rate correction device, comprising:

[0032] The acquisition module is used to acquire a heart rate signal and calculate the signal quality score of the heart rate signal and the current detected heart rate based on the heart rate signal, as heart rate parameters;

[0033] The judgment module is used to determine whether the heart rate parameter meets a first condition and a second condition. The first condition includes that the signal quality score of the heart rate signal reaches a preset requirement, and the second condition includes that the difference between the current detected heart rate and the final heart rate at the previous moment does not exceed a preset threshold.

[0034] The output module is used to determine the current final heart rate based on the judgment results of whether the heart rate parameters meet the first condition and the second condition.

[0035] Thirdly, embodiments of this application provide a heart rate detection device, including the heart rate correction device as described above.

[0036] Fourthly, embodiments of this application provide a computer-readable storage medium storing computer-executable instructions, which, when executed by a processor, implement the method described above.

[0037] Fifthly, embodiments of this application provide a computer program product, including a computer program that, when executed by a processor, implements the method described above.

[0038] The heart rate correction method, apparatus, device, medium, and product provided in this application calculate the detected heart rate based on the collected heart rate signal, and then determine whether the first and second conditions are met. The reliability of the detected heart rate is comprehensively judged from two dimensions: whether the signal quality score of the heart rate signal meets the requirements and whether the detected heart rate changes abruptly. Based on the judgment result, the current final heart rate is determined instead of directly outputting the detected heart rate. This can effectively correct the heart rate when the reliability of the detected heart rate is poor, thereby improving the accuracy and reliability of heart rate detection. Attached Figure Description

[0039] To more clearly illustrate the implementation methods in the embodiments of this application or related technologies, the accompanying drawings used in the description of the embodiments or related technologies will be briefly introduced below. Obviously, the accompanying drawings described below are some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings.

[0040] Figure 1 This is a flowchart illustrating the heart rate correction method provided in an embodiment of this application.

[0041] Figure 2 This is a flowchart illustrating another heart rate correction method provided in an embodiment of this application.

[0042] Figure 3 This is a schematic diagram of a heart rate correction device provided in this application.

[0043] Figure 4 This is a schematic diagram of the structure of an electronic device provided in an embodiment of this application. Detailed Implementation

[0044] To make the objectives, implementation methods and advantages of this application clearer, the exemplary implementation methods of this application will be clearly and completely described below with reference to the accompanying drawings of the exemplary embodiments of this application. Obviously, the described exemplary embodiments are only some embodiments of this application, and not all embodiments.

[0045] It should be noted that the brief descriptions of terms in this application are only for the convenience of understanding the embodiments described below, and are not intended to limit the embodiments of this application. Unless otherwise stated, these terms should be understood in their ordinary and common meaning.

[0046] Furthermore, the terms “comprising” and “having”, and any variations thereof, are intended to cover but not exclusively include, for example, a product or device that includes a series of components is not necessarily limited to those that are explicitly listed, but may include other components that are not explicitly listed or that are inherent to such product or device.

[0047] As people pay increasing attention to their physical condition and health, wearable heart rate monitoring devices, such as smartwatches, are becoming more widely used. Currently, wearable heart rate monitoring devices mainly use photoplethysmography (PPG) for heart rate detection. This method involves transmitting light of a specific wavelength through biological tissue. Blood pulsation causes periodic changes in the volume of subcutaneous blood vessels, resulting in differences in the absorption spectrum. A photoelectric sensor converts these light intensity fluctuations into electrical signals, and an algorithm calculates the peak intervals of these signals to determine the heart rate.

[0048] However, wearable heart rate monitoring devices are susceptible to noise interference. Taking high-intensity exercise as an example, photoelectric heart rate monitoring devices are easily affected by motion artifacts, leading to a sharp drop in signal quality; or, high-intensity exercise produces a lot of sweat, which interferes with the PPG signal acquisition device, resulting in poor signal quality; or, during exercise, there may be brief adjustments to the wearing position or the exercise posture, which may prevent the acquisition of effective signals.

[0049] Therefore, there is an urgent need for an accurate and reliable method for heart rate correction.

[0050] The heart rate correction method, apparatus, device, medium, and product provided in this application comprehensively evaluate the reliability of the detected heart rate from two aspects: whether the quality of the heart rate signal meets the requirements and whether the detected heart rate has a sudden change. If only one condition is met, the reliability of the detected heart rate is considered poor, and the weighted sum of the detected heart rate and the predicted heart rate is used as the final heart rate, thereby accurately achieving heart rate correction.

[0051] The heart rate correction method provided in the embodiments of this application will now be described in detail.

[0052] Figure 1 This is a flowchart illustrating the heart rate correction method provided in an embodiment of this application. Figure 1 As shown, the method includes:

[0053] S101. Acquire the heart rate signal. Based on the heart rate signal, calculate the signal quality score of the heart rate signal and the current detected heart rate as heart rate parameters.

[0054] Optionally, the heart rate signal refers to the signal acquired by the heart rate detection device that changes with the heartbeat, such as a PPG signal. The specific type of heart rate signal can be selected according to the actual production needs, and there are no restrictions on it here.

[0055] Optionally, when the heart rate signal is a PPG signal, the heart rate detection device illuminates the user's skin with an LED light. The user's blood pulsation causes the subcutaneous blood vessel volume to change periodically, resulting in differences in the human body's absorption spectrum. The heart rate detection device converts the light intensity fluctuations into electrical signals through a photoelectric sensor, thereby acquiring the PPG signal.

[0056] Optionally, the detected heart rate can be calculated in various ways, and there are no restrictions on which methods are used here. Below are some example methods for calculating the detected heart rate.

[0057] In one possible implementation, the original heart rate signal can be filtered to remove baseline drift and noise, and then the peaks of the heart rate signal can be identified. The corresponding detected heart rate can be calculated based on the time interval between adjacent peaks.

[0058] Among these options, an adaptive threshold can be set, and when the amplitude of the signal exceeds the threshold, it can be marked as a peak value; alternatively, the zero-crossing point of the first derivative of the signal can be marked as a peak value; or, the maximum value within a fixed window can be found as the peak value.

[0059] In one possible implementation, the heart rate signal in the time domain can be converted to the frequency domain, and the detected heart rate can be extracted by analyzing the frequency corresponding to the peak value in the frequency domain.

[0060] Optionally, the detected heart rate needs to be calculated based on heart rate signals over a period of time. Acquiring the heart rate signal can include acquiring the heart rate signal within a preset time window. For example, the time window can be set to 8 seconds.

[0061] In practical applications, the size of the time window can be selected as needed. It's understandable that a time window that is too small will result in a highly transient heart rate reading and low accuracy; a time window that is too large will result in slow real-time heart rate updates and low resolution. Therefore, it is necessary to select an appropriate time window size to improve the accuracy and reliability of heart rate detection.

[0062] Optionally, the detected heart rate is calculated based on the heart rate signal. The current detected heart rate can be calculated based on the heart rate signal within the current time window.

[0063] Optionally, the signal quality score can be used to characterize the quality of the heart rate signal.

[0064] S102. Determine whether the heart rate parameters meet the first and second conditions. The first condition includes that the signal quality score of the heart rate signal reaches the preset requirement. The second condition includes that the difference between the current detected heart rate and the final heart rate at the previous moment does not exceed the preset threshold.

[0065] Optionally, if the heart rate signal quality cannot meet the preset requirements due to noise interference, that is, if the heart rate signal quality is poor, the reliability of the detected heart rate calculated based on the heart rate signal is also poor.

[0066] Optionally, after calculating the current heart rate, it can be compared with the heart rate at the previous moment. In most cases, the heart rate will not jump dozens of times instantly, but will change gradually. For example, when a user changes from a resting state to an active state, or experiences a change in emotion, the heart rate can rise from 60 bpm to 150 bpm within tens of seconds; or, when a user calms down from an active or tense state, the heart rate can drop from 100 bpm to 60 bpm within a few minutes.

[0067] Therefore, when the difference between the current heart rate and the previous heart rate exceeds the preset threshold, it does not conform to the normal physiological state, and it can be concluded that the reliability of the current heart rate detection is poor.

[0068] S103. Determine the current final heart rate based on the judgment results of whether the heart rate parameters meet the first and second conditions.

[0069] The reliability of heart rate detection can be measured from two dimensions by combining the first and second conditions.

[0070] Optionally, the final heart rate refers to the final determined heart rate. The final heart rate is the corrected heart rate when the assessment result indicates inaccuracy in the detected heart rate.

[0071] In this embodiment, after calculating the detected heart rate based on the collected heart rate signal, it is determined whether the first and second conditions are met. The reliability of the detected heart rate is comprehensively judged from two dimensions: whether the signal quality score of the heart rate signal meets the requirements and whether the detected heart rate changes abruptly. Based on the judgment result, the current final heart rate is determined instead of directly outputting the detected heart rate. This can effectively correct the heart rate when the reliability of the detected heart rate is poor, thereby improving the accuracy and reliability of heart rate detection.

[0072] Figure 2 This is a flowchart illustrating another heart rate correction method provided in an embodiment of this application. Figure 2 As shown, in some embodiments, the current final heart rate is determined based on the judgment results of whether the heart rate parameters meet the first and second conditions, specifically including:

[0073] If the heart rate parameter satisfies either the first condition or the second condition, then obtain the current predicted heart rate.

[0074] The current predicted heart rate and the current detected heart rate are weighted and summed to obtain the current final heart rate.

[0075] Understandably, if only one of the first or second conditions is met, the current detected heart rate can be considered to have some reliability, but the reliability is low. In this case, the current detected heart rate and the current predicted heart rate can be combined to determine the final heart rate.

[0076] Optionally, predicted heart rate refers to the heart rate predicted based on certain historical data.

[0077] Optionally, the current predicted heart rate and the current detected heart rate can be weighted and summed to obtain the current final heart rate.

[0078] In one possible implementation, determining the current final heart rate based on whether the heart rate parameters satisfy the first and second conditions further includes:

[0079] If the current detected heart rate calculated based on the heart rate signal is an invalid value, then the second condition is not met.

[0080] Optionally, when the heart rate signal is severely interfered with by noise, the algorithm may be unable to calculate the heart rate based on the signal. For example, during strenuous exercise, the relative displacement between the sensor and the skin causes drastic changes in the optical path, which may result in complete overlap between the motion frequency band and the heart rate band; or, at low temperatures, blood vessels constrict, blood flow decreases, and the heart rate signal amplitude is less than the noise amplitude, all of which may prevent the detection of the heart rate. In such cases, the algorithm can directly determine that the second condition is not met, effectively avoiding the inability to perform the second condition judgment when the detection heart rate cannot be obtained, thus improving the reliability of heart rate correction.

[0081] Optionally, the first condition is to judge the reliability of the detected heart rate based on the quality of the heart rate signal, and the second condition is to judge the reliability of the detected heart rate based on the numerical value of the detected heart rate itself. Therefore, an invalid heart rate can refer to a detected heart rate that is NULL, NAN, etc., or it can refer to a detected heart rate value that is obviously unreasonable (e.g., less than 30 bpm or greater than 240 bpm).

[0082] In this embodiment, after calculating the detected heart rate based on the collected heart rate signal, it is determined whether the first and second conditions are met. The reliability of the detected heart rate is comprehensively judged from two dimensions: the quality of the heart rate signal and whether the detected heart rate changes abruptly. Furthermore, when only one of the first and second conditions is met, the detected heart rate and the predicted heart rate are weighted and summed to obtain the final output heart rate, instead of directly outputting the detected heart rate. This allows for effective correction of the heart rate when the reliability of the detected heart rate is poor, by combining the detected heart rate and the predicted heart rate, thereby improving the accuracy and reliability of heart rate detection.

[0083] like Figure 2 As shown, in some embodiments, determining the current final heart rate based on the judgment results of whether the heart rate parameters meet the first and second conditions further includes:

[0084] If all heart rate parameters meet the first and second conditions, then the current detected heart rate will be taken as the current final heart rate.

[0085] Optionally, if both the first and second conditions are met, the current detected heart rate can be considered to have high reliability. In this case, there is no need to correct the detected heart rate; the current detected heart rate can be directly used as the final heart rate, thus efficiently and accurately outputting the current heart rate.

[0086] like Figure 2 As shown, in some embodiments, the method further includes:

[0087] If neither the first nor the second condition is met, the current predicted heart rate is obtained and used as the current final heart rate.

[0088] Optionally, if neither the first nor the second condition is met, the current detected heart rate can be considered to have very low reliability. In this case, the current detected heart rate can be considered an invalid signal. Based on certain historical data, the current predicted heart rate can be obtained and used as the current final heart rate. This allows for effective and reliable heart rate correction, avoiding the output of a detected heart rate with poor reliability.

[0089] In this embodiment of the application, the reliability of the detected heart rate is divided into three cases based on whether the first section and the second condition are met, and different heart rate correction methods are selected in different cases, so as to accurately output the final determined heart rate.

[0090] The following is a detailed explanation of how to determine whether the second condition is met.

[0091] In some embodiments, before determining whether the heart rate parameters meet the first and second conditions, the method further includes:

[0092] Evaluate the signal quality score of the obtained heart rate signal;

[0093] Acquire historical accelerometer data for the first preset duration, and determine the current motion type based on the historical accelerometer data;

[0094] Based on the current motion type, determine the corresponding signal quality score threshold.

[0095] Determining whether heart rate parameters meet the second condition includes:

[0096] If the signal quality score of the heart rate signal is greater than the signal quality score threshold corresponding to the current exercise type, then the heart rate parameter is determined to meet the second condition; where different exercise types correspond to different signal quality score thresholds.

[0097] Otherwise, the heart rate parameter is determined not to meet the second condition.

[0098] In practical implementation, a signal quality score threshold can be used to measure whether the heart rate signal quality meets the requirements. The noise interference experienced by the heart rate signal varies under different exercise scenarios. For example, the signal quality score of a heart rate signal during strenuous exercise is generally lower than that during light exercise. Therefore, different signal quality score thresholds can be set for different types of exercise.

[0099] After determining the current exercise type, it is judged whether the signal quality score of the heart rate signal is greater than the signal quality score threshold corresponding to the current exercise type, thereby determining whether the heart rate parameter meets the second condition.

[0100] By combining the type of exercise to measure the quality of the heart rate signal, misjudgment can be avoided due to the influence of the type of exercise itself on the quality of the heart rate signal. This allows for an accurate determination of whether the quality of the heart rate signal meets the requirements, thereby improving the accuracy and reliability of heart rate correction.

[0101] Optionally, accelerometer data have different characteristics under different types of motion, so the corresponding type of motion can be determined based on the historical accelerometer data under the first preset duration.

[0102] In one possible implementation, historical accelerometer data can be input into a trained machine learning model (such as a decision tree, random forest, neural network, etc.) to learn and analyze the time-domain or frequency features of the historical accelerometer data, thereby determining the corresponding motion type.

[0103] It should be noted that in practical applications, the method of determining the corresponding motion type based on historical accelerometer data can be selected according to the actual production needs, and there are no restrictions on this method.

[0104] In one possible implementation, before using the weighted sum of the current predicted heart rate and the current detected heart rate as the current final heart rate, the following steps are also included:

[0105] The weights of predicted heart rate and detected heart rate are determined based on the signal quality score and signal quality score threshold of the heart rate signal.

[0106] The ratio of the signal quality score to the signal quality score threshold of the heart rate signal is positively correlated with the weight of the detected heart rate, while the ratio of the signal quality score to the signal quality score threshold of the heart rate signal is negatively correlated with the weight of the predicted heart rate.

[0107] In the specific implementation, before the weighted summation of the current predicted heart rate and the current detected heart rate, the weights of the predicted heart rate and the detected heart rate can be determined in real time based on the ratio of the signal quality score of the heart rate signal to the signal quality score threshold.

[0108] For example, if the signal quality score of the heart rate signal is less than the signal quality score threshold, when the ratio of the signal quality score to the signal quality score threshold is large, although the quality of the heart rate signal does not meet the requirements, it still has a certain degree of confidence. In this case, the weight of the predicted heart rate can be set to be less than the weight of the detected heart rate. When the ratio of the signal quality score to the current signal quality score threshold is small, the quality of the heart rate signal is very poor. In this case, the weight of the predicted heart rate can be set to be greater than the weight of the detected heart rate.

[0109] In this embodiment, the weights of predicted heart rate and detected heart rate can be adjusted in real time according to the quality of the heart rate signal. Different degrees of acceptance are applied to the predicted heart rate and detected heart rate based on different heart rate signal qualities, thereby accurately calculating the final heart rate and improving the reliability of heart rate correction.

[0110] When neither the first nor the second condition is met, a predicted heart rate needs to be used to correct the heart rate. The following is a detailed explanation of how to obtain the predicted heart rate.

[0111] In some embodiments, obtaining the current predicted heart rate includes:

[0112] Obtain historical exercise intensity and historical heart rate for a second preset duration under the same type of exercise;

[0113] Obtain the current accelerometer data;

[0114] Determine the current exercise intensity based on the current type of exercise and the current accelerometer data;

[0115] Based on the current exercise type, current exercise intensity, historical exercise intensity, and historical heart rate, the current predicted heart rate is obtained.

[0116] Optionally, the correlation between accelerometer data and motion intensity varies depending on the type of motion. Therefore, the motion intensity at a given moment can be determined based on the type of motion and the accelerometer data.

[0117] Furthermore, there is a certain correlation between exercise intensity and heart rate. For example, heart rate is relatively stable during low-intensity exercise, increases to some extent during moderate-intensity exercise, and is even higher during high-intensity exercise. As exercise intensity increases, muscle oxygen consumption increases, thus accelerating the heart rate. However, the relationship between exercise intensity and heart rate is not linear; for example, there are plateaus in the trend of heart rate changes with exercise intensity.

[0118] Therefore, historical exercise intensity and historical heart rate under the same type of exercise can be obtained, and the deep relationship between exercise intensity and heart rate under that type of exercise can be analyzed. Thus, combined with the current exercise intensity, the current predicted heart rate can be accurately predicted.

[0119] In one possible implementation, a deep learning model such as a Long Short-Term Memory Network or a Transformer model can be used to output the current predicted heart rate based on the current type of exercise, the current intensity of exercise, the historical intensity of exercise, and the historical heart rate.

[0120] The above describes the heart rate correction method provided in the embodiments of this application. This application also provides a heart rate correction device. Figure 3 This is a schematic diagram of a heart rate correction device provided in this application. Figure 3 As shown, the device 30 includes:

[0121] The acquisition module 31 is used to acquire the heart rate signal, and calculate the signal quality score of the heart rate signal and the current detected heart rate based on the heart rate signal, which are used as heart rate parameters.

[0122] The judgment module 32 is used to judge whether the heart rate parameters meet the first condition and the second condition. The first condition includes that the signal quality score of the heart rate signal reaches the preset requirement, and the second condition includes that the difference between the current detected heart rate and the final heart rate at the previous moment does not exceed the preset threshold.

[0123] Output module 33 is used to determine the current final heart rate based on the judgment results of whether the heart rate parameters meet the first and second conditions.

[0124] In practical applications, heart rate correction devices can be implemented through computer programs, such as application software; or they can be implemented as media storing relevant computer programs, such as USB flash drives or cloud drives; or they can be implemented through physical devices that integrate or install relevant computer programs, such as chips or servers.

[0125] The heart rate correction device provided in this application embodiment can execute the heart rate correction method in the above method embodiment. Its implementation principle and technical effects are similar, and will not be repeated here. It should be noted that the above... Figure 3 The division of modules shown is merely illustrative. This application does not limit the division of modules or the naming of modules.

[0126] This application also provides a heart rate detection device, including the heart rate correction device described above.

[0127] The heart rate detection device provided in this application embodiment can adopt a wrist type, armband type, chest band type, finger ring type, earband type, etc., and there is no limitation on it.

[0128] Figure 4 This is a schematic diagram of the structure of an electronic device provided in an embodiment of this application, such as... Figure 4 As shown, the electronic device includes:

[0129] The electronic device includes a processor 291 and a memory 292; it may also include a communication interface 293 and a bus 294. The processor 291, memory 292, and communication interface 293 can communicate with each other via the bus 294. The communication interface 293 can be used for information transmission. The processor 291 can invoke logical instructions stored in the memory 292 to execute the methods of the above embodiments.

[0130] Furthermore, the logic instructions in the aforementioned memory 292 can be implemented as software functional units and, when sold or used as independent products, can be stored in a computer-readable storage medium.

[0131] The memory 292, as a computer-readable storage medium, can be used to store software programs and computer-executable programs, such as program instructions / modules corresponding to the methods in the embodiments of this application. The processor 291 executes functional applications and data processing by running the software programs, instructions, and modules stored in the memory 292, thereby implementing the methods in the above-described method embodiments.

[0132] The memory 292 may include a program storage area and a data storage area. The program storage area may store the operating system and application programs required for at least one function; the data storage area may store data created based on the use of the terminal device. Furthermore, the memory 292 may include high-speed random access memory and may also include non-volatile memory.

[0133] This application also provides a computer-readable storage medium, which may include various media capable of storing program code, such as a USB flash drive, a portable hard drive, a read-only memory (ROM), a random access memory (RAM), a magnetic disk, or an optical disk. Specifically, the computer-readable storage medium stores program instructions, which are used in the methods described in the above embodiments.

[0134] This application also provides a program product including execution instructions stored in a readable storage medium. At least one control module of the heart rate detection device can read the execution instructions from the readable storage medium, and the at least one control module executes the execution instructions to cause the heart rate detection device to implement the heart rate correction methods provided in the various embodiments described above.

[0135] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of this application, and are not intended to limit them. Although this application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some or all of the technical features therein. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of this application.

[0136] For ease of explanation, the above description has been provided in conjunction with specific embodiments. However, the above exemplary discussion is not intended to be exhaustive or to limit the embodiments to the specific forms disclosed above. Various modifications and variations can be obtained based on the above teachings. The selection and description of the above embodiments are for the purpose of better explaining the principles and practical applications, thereby enabling those skilled in the art to better utilize the embodiments and various different variations of embodiments suitable for specific application considerations.

Claims

1. A heart rate correction method, characterized in that, include: Acquire a heart rate signal, and calculate the signal quality score of the heart rate signal and the current detected heart rate based on the heart rate signal, using these as heart rate parameters; Determine whether the heart rate parameter meets the first condition and the second condition. The first condition includes that the signal quality score of the heart rate signal reaches a preset requirement, and the second condition includes that the difference between the current detected heart rate and the final heart rate at the previous moment does not exceed a preset threshold. The current final heart rate is determined based on the judgment results of whether the heart rate parameters meet the first and second conditions.

2. The method according to claim 1, characterized in that, The step of determining the current final heart rate based on the judgment results of whether the heart rate parameters meet the first condition and the second condition includes: If the heart rate parameter satisfies either the first condition or the second condition, then the current predicted heart rate is obtained; The current predicted heart rate and the current detected heart rate are weighted and summed to obtain the current final heart rate.

3. The method according to claim 1, characterized in that, The step of determining the current final heart rate based on the judgment results of whether the heart rate parameters meet the first condition and the second condition includes: If all the heart rate parameters satisfy the first condition and the second condition, then the current detected heart rate is taken as the current final heart rate.

4. The method according to claim 1, characterized in that, The step of determining the current final heart rate based on the judgment results of whether the heart rate parameters meet the first condition and the second condition includes: If none of the heart rate parameters meet the first and second conditions, then the current predicted heart rate is obtained as the current final heart rate.

5. The method according to claim 2 or 4, characterized in that, The process of obtaining the current predicted heart rate includes: Determine the current type of exercise; Acquire historical exercise intensity and historical heart rate for a second preset duration under the same exercise type; acquire current accelerometer data; Determine the current motion intensity based on the current motion type and the current accelerometer data; The current predicted heart rate is obtained based on the current exercise type, the current exercise intensity, the historical exercise intensity, and the historical heart rate.

6. The method according to claim 1, characterized in that, Before determining whether the heart rate parameter meets the first and second conditions, the method further includes: Acquire historical accelerometer data for a first preset duration, and determine the current motion type based on the historical accelerometer data; Based on the current motion type, determine the corresponding signal quality score threshold.

7. The method according to claim 6, characterized in that, The determination of whether the heart rate parameter meets the second condition includes: If the signal quality score of the heart rate signal is greater than the signal quality score threshold corresponding to the current exercise type, then the heart rate parameter is determined to meet the second condition. Otherwise, the heart rate parameter is determined not to meet the second condition.

8. The method according to claim 6, characterized in that, Before obtaining the final heart rate by weighted summation of the current predicted heart rate and the current detected heart rate, the method further includes: The weights of predicted heart rate and detected heart rate are determined based on the signal quality score of the heart rate signal and the signal quality score threshold; wherein, the ratio of the signal quality score of the heart rate signal to the signal quality score threshold is positively correlated with the weight of the detected heart rate, and the ratio of the signal quality score of the heart rate signal to the signal quality score threshold is negatively correlated with the weight of the predicted heart rate.

9. The method according to any one of claims 1 to 8, characterized in that, The method further includes: If the current detected heart rate is calculated as an invalid value based on the heart rate signal, then the second condition is not met.

10. A heart rate correction device, characterized in that, include: The acquisition module is used to acquire a heart rate signal and calculate the signal quality score of the heart rate signal and the current detected heart rate based on the heart rate signal, as heart rate parameters; The judgment module is used to determine whether the heart rate parameter meets a first condition and a second condition. The first condition includes that the signal quality score of the heart rate signal reaches a preset requirement, and the second condition includes that the difference between the current detected heart rate and the final heart rate at the previous moment does not exceed a preset threshold. The output module is used to determine the current final heart rate based on the judgment results of whether the heart rate parameters meet the first condition and the second condition.

11. A wearable device, characterized in that, include: A processor, and a memory communicatively connected to the processor; The memory stores computer-executed instructions; The processor executes computer execution instructions stored in the memory to implement the method as described in any one of claims 1 to 9.

12. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores computer-executable instructions that, when executed by a processor, implement the method of any one of claims 1 to 9.

13. A computer program product, characterized in that, Includes a computer program that, when executed by a processor, implements the method of any one of claims 1 to 9.

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