Calorie consumption measurement method, wearable device and computer storage medium

Abstract

The present invention provides a calorie consumption measurement method, a wearable device and a computer storage medium, wherein the calorie consumption measurement method comprises: obtaining acceleration data generated by an acceleration sensor; determining the user's exercise intensity and walking steps according to the acceleration data; obtaining the working mode of a PPG sensor, wherein the working mode of the PPG sensor comprises a daily monitoring mode and a sports monitoring mode; in response to the PPG sensor being in the daily monitoring mode, determining the user's consumed calories according to at least one of the walking steps, the user's weight and the user's basal metabolic rate and the exercise intensity; in response to the PPG sensor being in the sports monitoring mode, determining the user's real-time heart rate and the heart rate interval in which the real-time heart rate is located according to the PPG signal, and determining the user's consumed calories according to the heart rate interval and the exercise intensity. The wearable device can adopt different calorie consumption measurement methods according to the working mode of the PPG sensor, thereby improving the measurement accuracy.

Description

Technical Field

[0001] The present invention relates to the field of wearable devices, and more specifically, to a calorie consumption measurement method, a wearable device and a computer storage medium. Background Art

[0002] Active calories refer to the calories consumed by the human body due to different individual activities in addition to basic metabolism. They are the main indicator of the intensity of daily human activity. The current method of measuring calories is mainly to use professional equipment to test the body's oxygen consumption and carbon dioxide exhalation to directly calculate the calorie consumption value. The direct measurement method has expensive equipment, complicated testing procedures, and requires wearing a closed professional helmet for a long time, resulting in poor human comfort.

[0003] In the prior art, there are methods for calculating calorie consumption through wearable devices. For example, calorie consumption can be estimated through personal information, heart rate information monitored by wearable devices, and human activity information. However, due to the high power consumption of physiological monitoring sensors (such as PPG sensors), wearable devices will not turn on the physiological monitoring sensors for a long time. When measuring calorie consumption, existing wearable devices use the same standard regardless of whether the physiological monitoring sensors are turned on, resulting in poor measurement accuracy of calorie consumption. Moreover, during the intermittent opening process of the PPG (Photoplethysmography) sensor, the PPG sensor is often affected by ambient light, user posture, etc., resulting in poor reliability of the heart rate value obtained, which causes large errors in the calculation of calorie consumption and makes it impossible to obtain a more accurate value. Summary of the invention

[0004] The purpose of the embodiments of the present invention is to provide a calorie consumption measurement method, a wearable device and a computer storage medium, the purpose of which is to solve the problem of poor measurement accuracy of wearable devices when measuring calorie consumption in the prior art.

[0005] In a first aspect, an embodiment of the present application provides a calorie consumption measurement method, which is applied to a wearable device including an acceleration sensor and a PPG sensor, including:

[0006] Obtain acceleration data generated by the acceleration sensor;

[0007] Determine the user's exercise intensity and walking steps based on acceleration data;

[0008] Get the working mode of the PPG sensor. The working modes of the PPG sensor include daily monitoring mode and sports monitoring mode. In daily monitoring mode, the PPG sensor is turned on at intervals, and in sports monitoring mode, the PPG sensor is turned on continuously.

[0009] In response to the PPG sensor being in the daily monitoring mode, determining the calories consumed by the user according to the number of steps walked, at least one of the user's weight and the user's basal metabolic rate, and the exercise intensity;

[0010] In response to the PPG sensor being in exercise monitoring mode, the user's real-time heart rate and the heart rate range in which the real-time heart rate is located are determined based on the PPG signal, and the calories consumed by the user are determined based on the heart rate range and exercise intensity.

[0011] According to the first aspect of the present disclosure, the calories consumed by the user are determined based on at least one of the number of steps walked, the user's weight and the user's basal metabolic rate and the intensity of exercise, which also includes: obtaining the user's basic information; determining the basal metabolic rate based on the basic information.

[0012] According to a first aspect of the present disclosure, determining a user's real-time heart rate and a heart rate interval in which the real-time heart rate is located according to a PPG signal includes:

[0013] Get the user's resting heart rate;

[0014] Determine the user's maximum heart rate based on basic information;

[0015] Determine the heart rate thresholds for each heart rate zone of the user based on the resting heart rate and maximum heart rate;

[0016] The heart rate zone in which the real-time heart rate belongs is determined according to the real-time heart rate.

[0017] According to a first aspect of the present disclosure, determining the user's exercise intensity based on acceleration data includes: determining acceleration amplitude based on the acceleration data; and determining the user's exercise intensity based on a preconfigured association relationship between acceleration amplitude and exercise intensity.

[0018] According to a first aspect of the present disclosure, determining the calories consumed by a user according to at least one of the number of steps walked, the user's weight, and the user's basal metabolic rate and the exercise intensity specifically includes:

[0019] Normalizing the exercise intensity at multiple time points within a preset time period to obtain a normalized value;

[0020] If the normalized value is lower than a first preset threshold, determining the calories consumed by the user based on the exercise intensity and the basal metabolic rate;

[0021] If the normalized value is not lower than the first preset threshold value and the number of steps is not 0, the calories consumed by the user are determined based on the exercise intensity, the number of steps and the basal metabolic rate;

[0022] If the normalized value is not lower than the first preset threshold and the number of steps is 0, the calories consumed by the user are determined based on the exercise intensity and weight.

[0023] According to the first aspect of the present disclosure, the calories consumed by the user are determined based on the heart rate range and the exercise intensity, and then the method also includes: obtaining the user's current exercise time; and compensating the calories based on the exercise intensity and the exercise time.

[0024] According to the first aspect of the present disclosure, calories are compensated according to exercise intensity and exercise duration, including: when the exercise intensity is greater than or equal to a second preset threshold, and the exercise duration exceeds a preset time threshold, calories are compensated according to a preconfigured compensation factor, wherein the compensation factor is configured to increase as the exercise time increases.

[0025] According to a first aspect of the present disclosure, the calories consumed by the user are determined according to the heart rate range and the exercise intensity, and then the method further includes:

[0026] Determine the heart rate change based on the real-time heart rate, and compensate calories based on the heart rate change. The compensation formula is:

[0027]

[0028] Among them, Cur_kcal represents the current calories, cur_HR represents the heart rate value at the current moment; pre_HR represents the heart rate value at the previous moment.

[0029] In a second aspect, an embodiment of the present application provides a wearable device, including a processor, a memory, an acceleration sensor, and a PPG sensor, wherein the memory stores a computer program that can be run on the processor, and the processor implements the steps of the above method when executing the computer program.

[0030] In a third aspect, an embodiment of the present application provides a computer storage medium, which stores a computer program, and is characterized in that the computer program implements the steps of the above method when executed by a processor.

[0031] In an embodiment of the present application, a calorie consumption measurement method includes: determining a user's first exercise intensity and walking steps according to acceleration data generated by an acceleration sensor; determining a user's real-time heart rate and a heart rate interval in which the real-time heart rate is located according to a signal from a PPG sensor; obtaining a working mode of the PPG sensor, the working mode of the PPG sensor including a daily monitoring mode and a sports monitoring mode; if the PPG sensor is in the daily monitoring mode, determining the calories consumed by the user according to at least one of the walking steps, the user's weight, and the user's basal metabolic rate and the first exercise intensity; if the PPG sensor is in the sports monitoring mode, determining the calories consumed by the user according to the heart rate interval and the first exercise intensity. The wearable device can use different calorie consumption measurement methods according to the working mode of the PPG sensor. When the PPG sensor is turned on at intervals, the calories consumed by the user are determined based on at least one of the walking steps, the user's weight, and the user's basal metabolic rate and the first exercise intensity, and the use of the less reliable heart rate value is abandoned, thereby improving the measurement accuracy of calorie consumption. BRIEF DESCRIPTION OF THE DRAWINGS

[0032] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative labor.

[0033] Figure 1 A block diagram of a wearable device provided by an embodiment of the present application is shown;

[0034] Figure 2 is a flow chart of a calorie measurement method provided in an embodiment of the present application;

[0035] Figure 3 is a flow chart of a method for determining calories in a daily monitoring mode provided by an embodiment of the present application;

[0036] Figure 4 This is a flow chart of another calorie measurement method provided in an embodiment of the present application. DETAILED DESCRIPTION

[0037] The following will be combined with the accompanying drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Generally, the components of the embodiments of the present invention described and shown in the drawings here can be arranged and designed in various different configurations.

[0038] Therefore, the following detailed description of the embodiments of the present invention provided in the accompanying drawings is not intended to limit the scope of the invention claimed for protection, but merely represents selected embodiments of the present invention. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without making creative work are within the scope of protection of the present invention.

[0039] In addition, in the description of the present specification and the appended claims, relational terms such as the terms "first" and "second" and the like are used only to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations. For example, the first medal may be referred to as the second medal. Those skilled in the art should also understand that the terms "including", "having" when used in this specification specify the presence of features, wholes, steps, operations, elements and / or parts, but do not exclude one or more other features, wholes, steps, operations, elements, parts and / or combinations thereof. The terms "if" and "if" may be interpreted to mean "when..." or "in response to" depending on the context.

[0040] Since calorie consumption is strongly correlated with human activities, heart rate, weight and other factors, existing wearable devices usually use the heart rate obtained by the PPG sensor to participate in the calculation of calorie consumption. Taking power consumption into consideration, the PPG sensor will not be turned on continuously during the user's daily heart rate tracking, but will be turned on at intervals. For example, the PPG sensor will be turned on every 10 minutes until the user's heart rate can be calculated and then turned off. When the wearable device detects that the user is exercising or the user actively selects exercise monitoring on the wearable device, the wearable device will continue to turn on the PPG sensor. During the intermittent activation of the PPG sensor, the PPG sensor is often affected by ambient light, user posture, etc., resulting in poor reliability of the heart rate value obtained, and it takes a long time to generate a heart rate value, which causes large errors in the calculation of calorie consumption and makes it impossible to obtain a more accurate value.

[0041] The basic idea of ​​the present invention is: when the PPG sensor is turned on at intervals, the wearable device mainly measures calories based on the user's exercise intensity, the number of steps the user walks, the weight, and the basal metabolic rate; when the PPG sensor is turned on continuously, the wearable device measures calories based on the user's heart rate range and exercise intensity. The wearable device can use different calorie consumption measurement methods according to the working mode of the PPG sensor. In particular, when the PPG sensor is turned on at intervals, the heart rate value with poor reliability is not used for calorie calculation, thereby improving the measurement accuracy of calorie consumption.

[0042] Figure 1A block diagram of a wearable device for implementing a calorie consumption measurement method is shown. The wearable device 100 includes but is not limited to a mobile phone, a tablet computer, a laptop computer, an ultra-mobile personal computer, a netbook, a personal digital assistant, etc. The wearable device may include one or more processors 101, a memory 102, a communication module 103, a sensor module 104, a display screen 105, an audio module 106, a speaker 107, a microphone 108, a camera module 109, a motor 110, a button 111, an indicator 112, a battery 113, a power management module 114, etc. These components may communicate via one or more communication buses or signal lines.

[0043] The processor 101 is the final execution unit for information processing and program running, and can run an operating system or application program to execute various functional applications and data processing of the wearable device 100. The processor 101 may include one or more processing units, for example: the processor 101 may include a central processing unit (CPU), a graphics processing unit (GPU), an image signal processor 100 (Image Signal Processing, ISP), a sensor hub processor or a communication processor (Central Processor, CP) application processor (Application Processor, AP), etc. In some embodiments, the processor 101 may include one or more interfaces. The interface is used to couple a peripheral device to the processor 101 to transmit instructions or data between the processor 101 and the peripheral device.

[0044] The memory 102 can be used to store computer executable program codes, and the executable program codes include instructions. The memory 102 may include a program storage area and a data storage area. Among them, the program storage area may store an operating system, at least one application required for a function (such as an application related to sports health management), etc. The data storage area may store data created during the use of the wearable device 100, such as the user's personal information, which may include age, height, weight, gender, etc., and may store the user's exercise parameters and physiological parameters for each exercise, such as the number of steps, stride, pace, exercise type, exercise duration, heart rate, blood pressure, blood oxygen, etc. The memory may include a high-speed random access memory, and may also include a non-volatile memory, such as at least one disk storage device, a flash memory device, a universal flash storage (UFS), etc.

[0045] The communication module 103 can support the wearable device 100 to communicate with the network and other devices (for example, communicate with the wearable device) through wireless communication technology. The communication module 103 converts electrical signals into electromagnetic signals for transmission, or converts received electromagnetic signals into electrical signals. The communication module 103 includes: an antenna, an RF transceiver, one or more amplifiers, a tuner, an oscillator, a digital signal processor, a codec chipset, and the like. The communication module 103 of the wearable device 100 may include one or more of a cellular mobile communication module, a short-range wireless communication module, a wireless Internet module, and a location information module.

[0046] The sensor module 104 is used to measure physical quantities or detect the operating state of the wearable device. The sensor 104 may include an acceleration sensor 104A, a gyroscope sensor 104B, an air pressure sensor 104C, a magnetic sensor 104D, a biosensor 104E, a proximity sensor 104F, an ambient light sensor 104G, a touch sensor 104H, etc. The sensor module 104 may also include a control circuit for controlling one or more sensors included in the sensor module 104.

[0047] Among them, the acceleration sensor 104A can detect the acceleration magnitude of the wearable device 100 in various directions. When the wearable device 100 is stationary, the magnitude and direction of gravity can be detected. In some embodiments, the acceleration sensor 104A can also be used to identify the posture of the wearable device 100 to calculate the number of steps of the user during exercise. The acceleration sensor 104A can be combined with the gyroscope sensor 104B to monitor the user's stride, step frequency and pace during exercise.

[0048] The gyroscope sensor 104B can be used to determine the motion posture of the wearable device 100. In some embodiments, the angular velocity of the wearable device 100 around three axes (i.e., x, y, and z axes) can be determined by the gyroscope sensor 104B. In some embodiments, the acceleration sensor 104A can be used in conjunction with the gyroscope sensor 104B to jointly identify the user's motion, such as identifying the user's motion type, the start and end of the user's motion.

[0049] The air pressure sensor 104C is used to measure air pressure. In some embodiments, the wearable device 100 calculates the altitude through the air pressure value measured by the air pressure sensor 104C to assist positioning and navigation.

[0050] The magnetic sensor 104D includes a Hall sensor, a magnetometer, etc., and can be used to determine the user's position.

[0051] The PPG sensor 104E is used to measure the user's physiological parameters. For example, the wearable device 100 can obtain the user's PPG signal through the PPG sensor 104E to calculate the user's heart rate or blood oxygen saturation and other information. In some embodiments, the wearable device 100 may also include other physiological sensors for measuring the user's physiological production, such as a fingerprint sensor, an electrocardiogram sensor, etc. The wearable device 100 may also obtain the user's heart rate based on the electrocardiogram sensor.

[0052] The proximity sensor 104F is used to detect the presence of an object near the wearable device 100 without any physical contact. In some embodiments, the proximity sensor 104F may include a light emitting diode and a light detector.

[0053] The ambient light sensor 104G is used to sense the ambient light brightness. In some embodiments, the wearable device 100 can adaptively adjust the display brightness according to the perceived ambient light brightness to reduce power consumption. In some embodiments, the ambient light sensor 104G can also cooperate with the proximity sensor 104F to detect whether the wearable device 100 is in a pocket to prevent accidental touch.

[0054] The touch sensor 104H is used to detect a touch operation on or near the touch sensor 104H, and is also called a “touch control device.” The touch sensor 104H can be disposed on the display screen 105 , and the touch sensor 104H and the display screen 105 form a touch screen.

[0055] The display screen 105 is used to display a graphical user interface (UI), which may include graphics, text, icons, videos, and any combination thereof. The display screen 105 may be a liquid crystal display (LCD), an organic light-emitting diode (OLED) display, and the like. When the display screen 105 is a touch display screen, the display screen 105 can collect a touch signal on or above the surface of the display screen 105, and input the touch signal as a control signal to the processor 101.

[0056] The audio module 106, the speaker 107, and the microphone 108 provide audio functions between the user and the wearable device 100, such as listening to music or making calls. The audio module 106 converts the received audio data into an electrical signal and sends it to the speaker 107, which converts the electrical signal into sound; or the microphone 108 converts the sound into an electrical signal and sends it to the audio module 106, which then converts the audio electrical signal into audio data.

[0057] The camera module 109 is used to capture still images or videos. The camera module 109 may include an image sensor, an image signal processor (ISP), and a digital signal processor (DSP). The image sensor converts the optical signal into an electrical signal, the image signal processor converts the electrical signal into a digital image signal, and the digital signal processor converts the digital image signal into an image signal in a standard format (RGB, YUV). The image sensor may be a charge coupled device (CCD) or a complementary metal-oxide-semiconductor (CMOS).

[0058] The motor 110 can convert electrical signals into mechanical vibrations to produce vibration effects. The motor 110 can be used for vibration prompts of incoming calls and messages, and can also be used for touch vibration feedback.

[0059] The buttons 111 include a power button, a volume button, etc. The buttons 111 may be mechanical buttons (physical buttons) or touch buttons.

[0060] The indicator 112 is used to indicate the status of the wearable device 100, for example, to indicate the charging status, power change, and can also be used to indicate messages, missed calls, notifications, etc.

[0061] The battery 113 is used to provide power to various components of the wearable device 100. The power management module 114 is used to manage the charge and discharge of the battery, and monitor parameters such as battery capacity, battery cycle number, battery health status (whether it is leaking, impedance, voltage, current and temperature). In some embodiments, the power management module 114 can charge the wearable device 100 via wired or wireless means.

[0062] It should be understood that in some embodiments, the wearable device 100 may be composed of one or more of the aforementioned components, and the wearable device 100 may include more or fewer components than shown, or combine certain components, or split certain components, or arrange the components differently. The components shown in the figure may be implemented in hardware, software, or a combination of software and hardware.

[0063] Figure 2 is a flow chart of a calorie consumption measurement method provided in an embodiment of the present application. Figure 1 The wearable device shown is implemented. The method includes:

[0064] S201, obtaining acceleration data generated by an acceleration sensor.

[0065] S203: Determine the user's exercise intensity and walking steps according to the acceleration data. The wearable device may pre-configure the association between exercise intensity and acceleration characteristics, and when the acceleration data is acquired, determine the corresponding exercise intensity according to the acceleration characteristics.

[0066] In some embodiments, the acceleration amplitude can be determined based on the acceleration data, and the user's exercise intensity can be determined based on a pre-configured association between the acceleration amplitude and the exercise intensity. The wearable device can pre-set multiple exercise intensities, each of which corresponds to a different acceleration amplitude threshold range. When the acceleration data is acquired, the acceleration amplitude is determined based on the acceleration data, and the exercise intensity is determined based on the acceleration amplitude.

[0067] In some embodiments, the user's exercise intensity can also be determined based on the acceleration change within a preset time period. The wearable device pre-configures multiple relationships between exercise intensity and acceleration change, and each exercise intensity corresponds to a different acceleration change threshold range. When the acceleration data is acquired, the difference between the acceleration data at the current time point and the acceleration data before the preset time is determined to determine the acceleration change, and then the user's exercise intensity is determined based on the acceleration change. Those skilled in the art can also use other acceleration features to determine the user's exercise intensity, such as determining the user's exercise intensity based on instantaneous momentum, the sum of momentum within a preset time period, the sum of the amplitudes of the three-axis acceleration data, etc.

[0068] The acceleration data may be used to determine the number of steps a user is walking by using a step counting method in the prior art. This step counting method is not the focus of the present invention and will not be described in detail herein.

[0069] S203, obtaining a working mode of the PPG sensor, the working modes of the PPG sensor including a daily monitoring mode and a sports monitoring mode. In the daily monitoring mode, the PPG sensor is turned on at intervals, and in the sports monitoring mode, the PPG sensor is turned on continuously.

[0070] In some embodiments, the PPG sensor can enter the motion monitoring mode based on the user's choice to monitor a certain type of motion, or can enter the motion monitoring mode based on the wearable device detecting that the user is exercising. In the motion monitoring mode, the light-emitting module of the PPG sensor continuously emits light at a preset frequency, and the acquisition module of the PPG sensor continuously acquires the reflection signal of the user's skin at a preset sampling frequency to generate a PPG signal. In the daily monitoring mode, the PPG sensor is turned on according to a pre-configured time, for example, every 5 minutes or 10 minutes, to obtain the user's physiological information. After obtaining the user's physiological information, the PPG sensor is turned off.

[0071] S204, in response to the PPG sensor being in daily monitoring mode, determining the calories consumed by the user according to the number of steps walked, at least one of the user's weight and the user's basal metabolic rate, and the exercise intensity.

[0072] In some embodiments, the wearable device can obtain basic information of the user, such as gender, age, height, weight, etc., and determine the basal metabolic rate (BMR) based on the basic information. For example, the BMR can be calculated based on weight as recommended by FAQ / WHO, as shown in Table 1:

[0073] Table 1. Calculation formula of BRM

[0074] Age (years) Male (Kcal / d) Female (Kcal / d) 0～ 60.9×W-54 61.0×W-51 3 22.4×W+495 22.5×W+499 10 17.5×W+651 12.2×W+746 18 15.3×W+679 14.7×W+496 30 11.6×W+879 8.7×W+829 60 13.5×W+487 10.5×W+596

[0075] In Table 1, the unit of BMR can be kilocalories per day (Kcal / d) or megajoules per day (MJ / d); W represents body weight in kilograms (kg).

[0076] Optionally, the calories consumed by the user are determined based on at least one of the number of steps taken, the user's weight and the user's basal metabolic rate and the exercise intensity, specifically including: normalizing the exercise intensity at multiple time points within a preset time period to obtain a normalized value; if the normalized value is lower than a first preset threshold, the calories consumed by the user are determined based on the exercise intensity and the basal metabolic rate; if the normalized value is not lower than the first preset threshold and the number of steps is not 0, the calories consumed by the user are determined based on the exercise intensity, the number of steps and the basal metabolic rate. For details, please refer to Figure 3 .

[0077] S205, in response to the PPG sensor being in exercise monitoring mode, determining the user's real-time heart rate and the heart rate range in which the real-time heart rate is located according to the PPG signal, and determining the calories consumed by the user according to the heart rate range and the exercise intensity.

[0078] Specifically, the PPG sensor can emit light to the user and receive light reflected from the user's skin. The absorption of light by muscles, bones, veins and other connecting tissues is basically unchanged (provided that there is no significant movement of the measurement site), but due to the flow of blood in the blood vessels, the absorption of light naturally changes. When we convert light into electrical signals, the signals obtained can be divided into direct current (DC) signals and alternating current (AC) signals, precisely because the absorption of light by blood changes while the absorption of light by other tissues remains basically unchanged. Extracting the AC signal can reflect the characteristics of blood flow and determine the user's heart rate.

[0079] The user's heart rate zone can be determined based on the maximum heart rate percentage or the reserve heart rate percentage. The maximum heart rate percentage only uses the maximum heart rate to determine the heart rate zone during training. The reserve heart rate percentage requires determining the maximum heart rate and resting heart rate to calculate the reserve heart rate (reserve heart rate = maximum heart rate - resting heart rate), and finally using the reserve heart rate to determine the heart rate zone.

[0080] Optionally, determining the user's real-time heart rate and the heart rate range in which the real-time heart rate is located based on the PPG signal includes: obtaining the user's resting heart rate; determining the user's maximum heart rate based on basic information; determining the heart rate thresholds of each heart rate range of the user based on the resting heart rate and the maximum heart rate; and determining the heart rate range in which the real-time heart rate is located based on the real-time heart rate. The formula for determining the heart rate range in which the real-time heart rate is located is as follows:

[0081]

[0082] In formula 1, HR_range represents the heart rate range of the real-time heart rate, HR max Indicates the user's maximum heart rate, which can be calculated by the difference between 220 and the user's age. HR indicates the real-time heart rate, and RHR indicates the resting heart rate. The resting heart rate can be measured when the user is at rest (such as sleeping) and stored in the wearable device.

[0083] The meaning of each heart rate zone in which the real-time heart rate is located is shown in Table 2:

[0084] Table 2 Meaning of each heart rate interval where the real-time heart rate is located

[0085] HR_range Heart rate zones [0,0.2] Physical limit consumption [0.2,0.45] Highly effective fat burning [0.45,0.6] Aerobic activity [0.6,0.75] Warm-up phase ≥0.75 Comfort and relaxation

[0086] Optionally, the following formula may be used to determine the calories consumed by the user based on the heart rate zone and exercise intensity:

[0087] Cur_kcal=a*HR_range+b*Level……(Formula 2)

[0088] In formula 2, Cur_kcal represents the calories currently consumed by the user, HR_range represents the current heart rate range of the user, and Level represents the exercise intensity. Parameters a and b are obtained by performing piecewise linear fitting on the calories measured by a high-precision calorie measuring device according to different exercise types and genders.

[0089] In this embodiment, when the PPG sensor is turned on at intervals, the wearable device mainly measures calories based on the user's exercise intensity, the number of steps the user walks, the user's weight, and the basal metabolic rate; when the PPG sensor is turned on continuously, the wearable device measures calories based on the user's heart rate range and exercise intensity. The wearable device can use different calorie consumption measurement methods according to the working mode of the PPG sensor. In particular, when the PPG sensor is turned on at intervals, the heart rate value with poor reliability is not used for calorie calculation, thereby improving the measurement accuracy of calorie consumption.

[0090] Optionally, the calories consumed by the user are determined based on the heart rate range and exercise intensity, and then the following steps are included: obtaining the user's current exercise time; compensating the calories based on the exercise intensity and exercise time. When the exercise intensity is greater than or equal to the second preset threshold, and the exercise time exceeds the preset time threshold, the calories are compensated based on a pre-configured compensation factor, wherein the compensation factor is configured to increase with the increase in exercise time. After the user exercises for a long time, maintaining a certain exercise frequency, the heart rate range may tend to stabilize, but the user's exercise intensity has not decreased. Therefore, compensation needs to be made based on the exercise time and exercise intensity, thereby improving the accuracy of calorie measurement. Exemplarily, based on the exercise intensity and exercise time, the compensation formula for the current calories is as follows:

[0091]

[0092] In formula 3, Cur_kcal represents the current calories, Level represents the current exercise intensity, and c represents the compensation factor. The compensation factor range is the result of the statistics in different time periods. When the current exercise intensity is greater than or equal to 3, the calories need to be compensated according to the compensation factor if the exercise time exceeds the preset time. For example, if the exercise time is greater than 5 minutes, the compensation factor can be 0.02; if the exercise time is greater than 12 minutes, the compensation factor can be 0.1; if the exercise time is greater than 20 minutes, the compensation factor can be 0.15; if the exercise time is greater than 35 minutes, the compensation factor can be 0.2.

[0093] Optionally, the calories consumed by the user are determined according to the heart rate range and the exercise intensity, and then the method further includes: determining the heart rate change according to the real-time heart rate, and compensating the calories according to the heart rate change, and the compensation formula is:

[0094]

[0095] In formula 4, Cur_kcal represents the current calories, cur_HR represents the heart rate value at the current moment, and pre_HR represents the heart rate value at the previous moment. Since heart rate has a strong correlation with calories, compensating calories through real-time heart rate can make the calorie change rate correlated with heart rate changes, thereby improving the progress of calorie measurement.

[0096] In such Figure 2 Based on the shown embodiment, Figure 3 1 is a flow chart of a method for determining calories in a daily monitoring mode provided by an embodiment of the present application. Figure 3 As shown, the above step S204 can be implemented by the following steps:

[0097] S301, normalize the exercise intensity at multiple time points within a preset time period to obtain a normalized value. The normalized value represents the overall exercise intensity of the user within the preset time period, and different calorie consumption calculation methods are used based on the overall exercise intensity within the preset time period. When the overall exercise intensity is low, calorie calculation is performed based on the normalized value and the basal metabolic rate of the human body. When the overall exercise intensity is high, if there are steps (indicating that the user has walked or run), the calories consumed by the user within the preset time period are determined based on the user's steps, the normalized value and the user's basal metabolic rate; if there are no steps (indicating that the user has exercised in situ), the calories consumed by the user within the preset time period are determined based on the normalized value and the user's weight.

[0098] For example, the exercise intensity within 1 minute can be normalized to obtain a normalized value. The acceleration amplitude of the acceleration sensor per second can be calculated first, and the acceleration amplitude calculation formula is as follows:

[0099]

[0100] In formula 5, AMP represents the acceleration amplitude, x, y, and z represent the three axes of the acceleration sensor, and max(ACC i ) indicates the maximum acceleration of a certain axis, min(ACC i ) represents the minimum acceleration of an axis.

[0101] Then, based on the acceleration amplitude per second, the corresponding exercise intensity per second is determined. In some embodiments, the association between exercise intensity and acceleration amplitude threshold range can be pre-stored in the wearable device, as shown in Table 3. After determining the acceleration amplitude per second, the exercise intensity for a certain second is determined by looking up the table.

[0102] Table 3 Correspondence between exercise intensity level and acceleration amplitude

[0103] Exercise intensity level AMP (acceleration amplitude) 0 AMP is less than or equal to a 1 AMP is greater than b and less than or equal to c 2 AMP is greater than c and less than or equal to d 3 AMP is greater than d

[0104] In Table 3, a, b, c, and d represent different acceleration amplitude thresholds. The threshold range of acceleration amplitude at different exercise intensity levels can be pre-configured with different values ​​according to the working mode of the PPG sensor, and can also be pre-configured according to the different exercise types selected by the user on the wearable device. The exercise intensity level is not limited to the 4 levels in the above table, and can also be set to 3, 5, 6, or other more or fewer levels. In some instances, the acceleration amplitude thresholds corresponding to each exercise intensity level of the PPG sensor in the daily monitoring mode can be configured. Among them, the acceleration amplitude threshold x can be set to the average value of the acceleration amplitude when the user is working normally or resting, such as 10; the acceleration amplitude threshold z can be set to the average value of the acceleration amplitude when the user is walking, such as 50; the acceleration amplitude threshold m can be set to the average value of the acceleration amplitude when the user is walking fast, such as 120.

[0105] After the exercise intensity per second within one minute is determined, the exercise intensity per second within one minute may be normalized based on the following formula to obtain a normalized value.

[0106]

[0107] In Formula 6, Level_min represents the normalized value of exercise intensity within 1 minute, Level(i) represents the first exercise intensity in a certain second, and Max(Level) represents the maximum exercise intensity.

[0108] The preset time period cannot be set too long or too short. If it is too long, the data will not be fine enough, and if it is too short, frequent calculations will be required, which will increase the energy consumption of the device. Therefore, the preset time period is preferably 1 to 5 minutes, and preferably an integer multiple of 1 minute.

[0109] S302: If the normalized value is lower than a first preset threshold, the calories consumed by the user are determined based on the exercise intensity and the basal metabolic rate. The first preset threshold is an empirical value, which can be obtained by fitting according to the calorie value measured by an accurate calorie measuring device.

[0110] Exemplarily, the formula for determining the calories consumed by the user based on the exercise intensity and the basal metabolic rate is as follows:

[0111] kcal_1=Level_min*bmr……(Formula 7)

[0112] In Formula 7, kcal_1 represents the calories consumed by the user, Level_min represents the normalized value of the exercise intensity within 1 minute, and bmr represents the basal metabolic rate of the user. The unit of the basal metabolic rate is kcal / min (kilocalories per minute).

[0113] S303: If the normalized value is not lower than the first preset threshold value and the number of steps is not 0, the calories consumed by the user are determined based on the exercise intensity, the number of steps, and the basal metabolic rate. For example, the formula for determining the calories consumed by the user based on the exercise intensity and the basal metabolic rate is as follows:

[0114] kcal_2=Level_min*bmr*step_param......(Formula 8)

[0115] In Formula 8, kcal_2 represents the calories consumed by the user, level_min represents the normalized value of the exercise intensity within 1 minute, bmr represents the basal metabolic rate of the user, and step_param represents the number of steps walked.

[0116] S304: If the normalized value is not lower than the first preset threshold and the number of steps is 0, the calories consumed by the user are determined based on the exercise intensity and the weight. For example, the formula for determining the calories consumed by the user based on the exercise intensity and the weight is as follows:

[0117] kcal_3=Level_min*weight_param……(Formula 9)

[0118] In Formula 9, kcal_3 represents the calories consumed by the user, Level_min represents the normalized value of the exercise intensity within 1 minute, and weight_param represents the number of steps per body weight.

[0119] In this embodiment, when the PPG sensor interval is turned on, the wearable device mainly measures calories based on the user's exercise intensity and the user's walking steps, weight and basal metabolic rate. And based on the different overall exercise intensities within the preset time period, different calorie consumption calculation methods are adopted. When the overall exercise intensity is low, calorie calculation is performed based on the normalized value and the human body's basal metabolic rate. When the overall exercise intensity is high, if there are steps (indicating that the user has walked or run), the calories consumed by the user in the preset time period are determined based on the user's steps, normalized value and user's basal metabolic rate; if there are no steps (indicating that the user has exercised in situ), the calories consumed by the user in the preset time period are determined based on the normalized value and the user's weight. Thereby, the measurement accuracy of calorie consumption is improved.

[0120] Figure 4 is a flow chart of another calorie measurement method provided by an embodiment of the present application. Figure 1 The wearable device 100 shown implements the process including:

[0121] S402, obtaining basic information of the user. The basic information includes: gender, age, height, weight, etc. The user can directly input the basic information on the wearable device; or the mobile communication device associated with the wearable device can transmit the basic information to the wearable device.

[0122] S404, determining the basal metabolic rate and the maximum heart rate according to the basic information. The method for determining the basal metabolic rate can refer to Table 1. The maximum heart rate can be calculated by the difference between 220 and the user's age.

[0123] S406: Obtain the user's resting heart rate. The resting heart rate can be measured by the wearable device when the user is in a resting state (such as sitting or sleeping) and stored in the wearable device.

[0124] S408, acquiring acceleration data.

[0125] S410, determine the user's exercise intensity and walking steps. The wearable device can pre-configure the association between exercise intensity and acceleration characteristics, and when the acceleration data is obtained, the exercise intensity is determined based on the acceleration characteristics. The acceleration characteristics can be acceleration amplitude, based on instantaneous momentum, the sum of momentum within a preset time period, the sum of amplitudes of three-axis acceleration data, etc. The walking steps can be determined by a pedometer algorithm, and the pedometer algorithm can refer to the prior art.

[0126] S412, obtaining the working mode of the PPG sensor. The working modes of the PPG sensor include a daily monitoring mode and a sports monitoring mode. In the daily monitoring mode, the PPG sensor is turned on at intervals, and in the sports monitoring mode, the PPG sensor is turned on continuously.

[0127] S414, determine whether it is a motion monitoring mode. If so, proceed to step S416, otherwise proceed to step S424.

[0128] S416, determining the user's real-time heart rate and the heart rate interval in which the real-time heart rate is located according to the PPG signal. The heart rate interval in which the real-time heart rate is located is determined as shown in Formula 1.

[0129] S418, determining the calories consumed by the user according to the heart rate range and the exercise intensity. Please refer to Formula 2.

[0130] S420, compensate calories according to exercise intensity and exercise duration. Specifically, the wearable device can obtain the user's current exercise duration; compensate calories according to the exercise intensity and exercise duration. When the exercise intensity is greater than or equal to a preset threshold, and the exercise duration exceeds a preset time threshold, the calories are compensated according to a pre-configured compensation factor, wherein the compensation factor is configured to increase as the exercise time increases. Formula 3 can be used to determine the calories consumed by the user based on the heart rate range and exercise intensity.

[0131] S422, compensating calories according to the change in heart rate. Since heart rate is strongly correlated with calories, compensating calories by real-time heart rate can make the calorie change rate correlated with heart rate change, thereby improving the progress of calorie measurement. For the specific compensation formula, please refer to Formula 4.

[0132] S424, normalize the exercise intensity at multiple time points within the preset time period to obtain a normalized value. The normalized value represents the overall exercise intensity of the user within the preset time period, and different calorie consumption calculation methods are used based on the overall exercise intensity within the preset time period. When the overall exercise intensity is low, the calories are calculated based on the normalized value and the basal metabolic rate of the human body. When the overall exercise intensity is high, if there are steps (indicating that the user has walked or run), the calories consumed by the user within the preset time period are determined based on the user's steps, the normalized value and the user's basal metabolic rate; if there are no steps (indicating that the user has exercised in situ), the calories consumed by the user within the preset time period are determined based on the normalized value and the user's weight. The formula for the normalization process can refer to Formula 6.

[0133] S426, determine whether the normalized value is lower than a first preset threshold value. If so, proceed to S428, otherwise proceed to S430.

[0134] S428, determining the calories consumed by the user based on the exercise intensity and the basal metabolic rate. The specific calculation method can refer to Formula 7.

[0135] S430, determine whether the step number is 0. If so, proceed to S434, otherwise proceed to S432.

[0136] S432, determining the calories consumed by the user based on the exercise intensity, the number of steps and the basal metabolic rate. The specific calculation method can refer to Formula 8.

[0137] S434, determining the calories consumed by the user based on the exercise intensity and weight. The specific calculation method can refer to Formula 9.

[0138] Those skilled in the art should understand that the above method is only an exemplary description, and the order of each step does not constitute a limitation of the present invention.

[0139] The exemplary embodiment of the present application further provides a computer storage medium, which includes computer instructions. When the computer instructions are executed on a communication terminal, the electronic device executes part or all of the steps of the above-mentioned medal management method.

[0140] In several embodiments provided in the present application, it should be understood that the disclosed devices and methods can also be implemented in other ways. The device embodiments described above are merely schematic. For example, the flowcharts and block diagrams in the accompanying drawings show the possible architecture, functions and operations of the devices, methods and computer program products according to multiple embodiments of the present invention. In this regard, each box in the flowchart or block diagram can represent a module, a program segment or a part of the code, and a part of the module, program segment or code contains one or more executable instructions for implementing the specified logical functions. It should also be noted that in some alternative implementations, the functions marked in the box can also occur in a different order from the order marked in the accompanying drawings. For example, two consecutive boxes can actually be executed substantially in parallel, and they can sometimes be executed in the opposite order, depending on the functions involved. It should also be noted that each box in the block diagram and / or flowchart, and the combination of boxes in the block diagram and / or flowchart can be implemented with a dedicated hardware-based system that performs a specified function or action, or can be implemented with a combination of dedicated hardware and computer instructions.

[0141] If the function is implemented in the form of a software function module and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, or the part that contributes to the prior art or the part of the technical solution, can be embodied in the form of a software product. The computer software product is stored in a storage medium and includes several instructions for a computer device to perform all or part of the steps of the various embodiments of the present invention. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), disk or optical disk and other media that can store program codes.

[0142] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. For those skilled in the art, the present invention may have various modifications and variations. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention shall be included in the protection scope of the present invention.

Claims

1. A calorie consumption measurement method, applied to a wearable device including an acceleration sensor and a PPG sensor, It is characterized in that include: Obtain acceleration data generated by the acceleration sensor; Determine the user's exercise intensity and walking steps according to the acceleration data; Acquire a working mode of a PPG sensor, wherein the working modes of the PPG sensor include a daily monitoring mode and a sports monitoring mode, wherein the PPG sensor is turned on at intervals in the daily monitoring mode and the PPG sensor is turned on continuously in the sports monitoring mode; In response to the PPG sensor being in a daily monitoring mode, determining the calories consumed by the user according to at least one of the number of steps walked, the user's weight and the user's basal metabolic rate and the exercise intensity; In response to the PPG sensor being in a sports monitoring mode, determining a user's real-time heart rate and a heart rate interval in which the real-time heart rate is located according to a PPG signal, and determining calories consumed by the user according to the heart rate interval and the sports intensity; Determining the calories consumed by the user according to at least one of the number of steps, the user's weight, and the user's basal metabolic rate and the exercise intensity specifically includes: Normalizing the exercise intensity at multiple time points within a preset time period to obtain a normalized value; If the normalized value is lower than a first preset threshold, determining the calories consumed by the user based on the exercise intensity and the basal metabolic rate; If the normalized value is not lower than a first preset threshold value and the number of walking steps is not 0, determining the calories consumed by the user based on the exercise intensity, the number of walking steps and the basal metabolic rate; If the normalized value is not lower than the first preset threshold and the number of walking steps is 0, the calories consumed by the user are determined based on the exercise intensity and the weight.

2. The calorie consumption measurement method according to claim 1, It is characterized in that The method further includes determining the calories consumed by the user according to at least one of the number of steps, the weight of the user, and the basal metabolic rate of the user and the exercise intensity, wherein: Get basic information of the user; The basal metabolic rate is determined according to the basic information.

3. The calorie consumption measurement method according to claim 2, It is characterized in that Determining the user's real-time heart rate and the heart rate interval in which the real-time heart rate is located according to the PPG signal includes: Get the user's resting heart rate; determining the user's maximum heart rate based on the basic information; Determine the heart rate thresholds of each heart rate interval of the user according to the resting heart rate and the maximum heart rate; The heart rate interval in which the real-time heart rate belongs is determined according to the real-time heart rate.

4. The calorie consumption measurement method according to claim 1, It is characterized in that Determining the user's exercise intensity according to the acceleration data includes: determining an acceleration amplitude based on the acceleration data; The user's exercise intensity is determined according to the pre-configured association relationship between the acceleration amplitude and the exercise intensity.

5. The calorie consumption measurement method according to any one of claims 1 to 4, It is characterized in that The method further includes determining the calories consumed by the user according to the heart rate interval and the exercise intensity, and then: Get the user's current exercise duration; The calories are compensated according to the exercise intensity and the exercise duration.

6. The calorie consumption measurement method according to claim 5, It is characterized in that The calories are compensated according to the exercise intensity and the exercise duration, including: When the exercise intensity is greater than or equal to a second preset threshold and the exercise duration exceeds a preset time threshold, the calories are compensated according to a preconfigured compensation factor, wherein the compensation factor is configured to increase as the exercise time increases.

7. The calorie consumption measurement method according to any one of claims 1 to 4, It is characterized in that The method further includes determining the calories consumed by the user according to the heart rate interval and the exercise intensity, and then: The heart rate change is determined according to the real-time heart rate, and the calories are compensated according to the heart rate change. The compensation formula is: , in, Indicates the current calories, Indicates the heart rate value at the current moment; Indicates the heart rate value at the previous moment.

8. A wearable device comprising a processor, a memory, an acceleration sensor and a PPG sensor, It is characterized in that The memory stores a computer program that can be run on the processor, and the processor implements the steps of the method according to any one of claims 1 to 6 when executing the computer program.

9. A computer storage medium storing a computer program. It is characterized in that When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 6 are implemented.

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