WO2019019489A1

WO2019019489A1 - Exercise guidance method and apparatus, and intelligent wearable device

Info

Publication number: WO2019019489A1
Application number: PCT/CN2017/111398
Authority: WO
Inventors: 韩浩瀚
Original assignee: 深圳市沃特沃德股份有限公司
Priority date: 2017-07-24
Filing date: 2017-11-16
Publication date: 2019-01-31
Also published as: CN107590358B; CN107590358A

Abstract

Disclosed is an exercise guidance method, comprising the following steps: obtaining a basic heart rate and a heart rate variability index of a user; calculating a health index of the user according to the basic heart rate and the heart rate variability index, and calculating a fatigue index of the user according to the basic heart rate; and providing exercise guidance for the user according to the health index and the fatigue index so that the exercise intensity of the user matches with body state, to prevent harming the body caused by too high exercise intensity, and therefore, the user experience is improved.

Description

Motion guidance device, device and smart wearable device

Technical field

The present invention relates to the field of electronic technology, and in particular to a motion guiding device, device and smart wearable device.

Background technique

With the improvement of living standards, people pay more attention to physical health, more and more people participate in sports and fitness activities, and smart wearable devices such as smart bracelets and smart watches that provide reference information for sports have also emerged. During the exercise process, if the user's exercise intensity is too large and does not match the user's physical state, it may cause damage to the user's body, so the user needs to get corresponding exercise guidance.

However, the current smart wearable device can only provide information such as the number of exercise steps, heart rate, energy consumption, etc., and can not provide personalized exercise guidance according to the specific situation of the user, and the utility and the degree of intelligence are low.

Summary of the invention

The main object of the present invention is to provide a motion guiding method, device and smart wearing device, which are intended to provide exercise guidance for the user, and improve the practicality and intelligence.

To achieve the above objective, an embodiment of the present invention provides a motion guiding method, where the method includes the following steps:

Obtain the user's basal heart rate and heart rate variability index;

Calculating a health index of the user according to the basal heart rate and the heart rate variability index, and calculating a fatigue index of the user according to the basal heart rate;

The user is provided with exercise guidance based on the health index and the fatigue index.

The invention also provides a motion guiding device, the device comprising:

An acquisition module for obtaining a user's basal heart rate and heart rate variability index;

a calculation module, configured to calculate a health index of the user according to the basic heart rate and the heart rate variability index, and calculate a fatigue index of the user according to the basal heart rate;

A guidance module for providing exercise guidance to the user based on the health index and the fatigue index.

Embodiments of the present invention also provide a smart wearable device including a memory, a processor, and at least one application stored in the memory and configured to be executed by the processor, the application being configured to use To perform the aforementioned exercise guidance method.

A motion guiding method provided by an embodiment of the present invention calculates a user's health index and a fatigue index according to a basic heart rate and a heart rate variability index by acquiring a user's basal heart rate and heart rate variability index, thereby making the user according to the health index and the fatigue index. Personalized exercise guidance is provided to match the user's exercise intensity with the physical state, prevent the exercise intensity from being too large and cause damage to the body, improve the practicality and intelligence of the smart wearable device, and improve the user experience.

DRAWINGS

1 is a flow chart of an embodiment of a motion guiding method of the present invention;

2 is a specific flowchart of a step of calculating a user's health index according to a basic heart rate and a heart rate variability index according to an embodiment of the present invention;

3 is a specific flow chart of steps for providing exercise guidance to a user according to a health index and a fatigue index according to an embodiment of the present invention;

4 is a motion intensity type selection dialog box in an embodiment of the present invention;

4a is a comparison table of exercise intensity type and heart rate intensity in an embodiment of the present invention;

Figure 5 is a block diagram showing a first embodiment of the motion guiding device of the present invention;

Figure 6 is a block diagram of the computing module of Figure 5;

Figure 7 is a block diagram of the health index calculation unit of Figure 6;

Figure 8 is a block diagram of the fatigue index calculation unit of Figure 6;

Figure 9 is a block diagram of the instruction module of Figure 5;

Figure 10 is a block diagram showing a second embodiment of the exercise instructing device of the present invention;

11 is a block diagram of a computing module of FIG. 10;

Figure 12 is a block diagram showing the psychological pressure index calculation unit of Figure 11;

Figure 13 is a block diagram of the motion amount statistics unit of Figure 12;

Figure 14 is a block diagram of the suggested module of Figure 10;

Figure 15 is a block diagram of the motion suggesting unit of Figure 14.

The implementation, functional features, and advantages of the present invention will be further described in conjunction with the embodiments.

Detailed ways

It is understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention.

The motion guidance method and device of the embodiments of the present invention are mainly applied to smart wearable devices such as smart watches and smart wristbands, and can of course be applied to other terminal devices, which is not limited by the present invention. The following is a detailed description of the application to the smart wearable device.

Referring to Figure 1, an embodiment of a motion guidance method of the present invention is presented. The method includes the following steps:

S11. Obtain a user's basal heart rate and heart rate variability index.

S12. Calculate the user's health index according to the basal heart rate and the heart rate variability index, and calculate the user's fatigue index according to the basal heart rate.

S13. Provide exercise guidance to the user according to the health index and the fatigue index.

The basal heart rate generally refers to the resting heart rate when waking up in the morning. It is generally considered that the basal heart rate is slow and uniform is a good performance of health, and the basal heart rate is too fast, or the sudden change in heart rate means excessive fatigue or disease ridden. The Heart Rate Variability Index (HRVI) can be used to indicate sympathetic and parasympathetic tone and is important for cardiovascular and cranial nerve health.

In step S11, the smart wearable device detects the user's basal heart rate through the heart rate sensor and counts the heart rate variability index. In a specific implementation, the smart wearable device can determine the wake-up time of the user by using the sleep monitoring function, and calculate the standard deviation by collecting 200 samples of the RR interval at a preset frequency (such as 1 Hz) in accordance with the HRV mode of the heart rate sensor, and the calculation will be performed. The result was used as a heart rate variability index. The average heart rate measured over a certain period of time (eg, within one minute) is averaged as the basal heart rate. When determining the sleep time, the smart wearable device can use the acceleration sensor to match the user's set sleep time and wake-up time for accurate judgment.

Optionally, the smart wearable device can take real-time heart rate data (ie, the currently detected heart rate data) within a certain period of time (eg, within half an hour) before the user wakes up, and calculate the basic heart rate of the day, and then for a period of time (eg, The basal heart rate data of the day of the tenth day is subjected to median filtering processing, and the processing result is taken as the basal heart rate of the user.

In step S12, the smart wearable device evaluates the user's fatigue index according to the basic heart rate, and evaluates the user's health index according to the basic heart rate and the heart rate variability index.

In the embodiment of the present invention, the smart wearable device calculates the user according to the basic heart rate and the heart rate variability index. The specific process of the health index is shown in Figure 2, including the following steps:

S121. Normalize the heart rate variability index by using the basic heart rate, and substitute the processing result into the first statistical regression formula to calculate the first index.

Specifically, the smart wearable device utilizes a normalized formula:

Normalize the heart rate variability index, where hb is the basal heart rate and hi is the heart rate variability index.

The result of the heart rate variability index is the normalized heart rate variability index. Then, the smart wearable device will

Substituting x: α ₁ = 0.0000147x ^{3 -} 0.002303456x ² + 0.09017484x in the first statistical regression formula, the first index α _{1 is} calculated.

It should be understood that the foregoing normalization formula and statistical regression formula are merely illustrative and not exclusive, and those skilled in the art may use other normalization formulas and statistical regression formulas for calculation according to actual needs.

S122: Normalize the basic heart rate by using the gender and age of the user, and substitute the processing result into the second statistical regression formula to calculate the second index.

Specifically, the smart wearable device utilizes a normalized formula:

Normalize the basal heart rate, where a is age, k is the gender compensation coefficient, and hb is the basal heart rate.

To normalize the basal heart rate, that is, the processing result of the basal heart rate. Then, the smart wearable device will

Substituting into the first statistical regression formula

The second index α _{2 is} calculated. Generally, when the user is an adult male, k takes 0, when the user is an adult female, k takes 10, and when the user is a child (such as under 13), k takes 0.

S123. The product of the first index and the second index is used as a health index.

The smart wearable device substitutes the first index α ₁ and the second index α ₂ into the formula: α=α ₁ *α ₂ , and calculates the user's health index α.

In other embodiments, the smart wearable device may also calculate the heartbeat cycle of the user through the heart rate sensor, and then calculate the health index of the user according to the basal heart rate, the heart rate variability index, and the heartbeat cycle. For example, according to the formula: I=(100-hb)*hi/p, the user's body mass index I is calculated, and the body mass index is taken as the user's health index. Among them, hb is the basal heart rate, hi is the heart rate variability index, and p is the heart rate cycle.

In other embodiments, after calculating the user's body mass index I, the smart wearable device further calculates the user's fitness index U according to the formula: U=2*I*hb/hn-1, and uses the fitness index as the user. Health index. Among them, hn is the current real-time heart rate, hb is the basal heart rate, and I is the body mass index.

It can be understood by those skilled in the art that, in addition to this, other calculation formulas can be used to calculate the health index of the user according to the basal heart rate and the heart rate variability index, which will not be enumerated in the present invention.

In the embodiment of the present invention, the smart wearable device calculates the fatigue index of the user by first counting the time t after the user's real-time heart rate is restored to n times of the basic heart rate after the end of the exercise, and the value of n can be determined according to actual needs, preferably Take a value in the range of 1-1.5 and then substitute the time t into the formula:

The user's fatigue index γ is calculated.

For example, the smart wearable device defines the end of exercise by using the motion discriminating function of the acceleration sensor, and the real-time heart rate of the user after the end of the statistical exercise is restored to a time t within 1.25 times of the basal heart rate, and then the time t is substituted into the above formula to calculate the fatigue index γ.

Optionally, the smart wearable device counts the median of the basal heart rate in the most recent period (eg, 90 days), and determines whether the basal heart rate of the most recent D day (eg, 2-5 days, preferably 3 days) exceeds the median preset. The value (such as 5-15 units, preferably 10 units), if the median preset value is exceeded, determines that the user is excessively fatigued and can prompt the user to be excessively tired.

After the smart wearable device calculates the user's health index and fatigue index, the health index and/or fatigue index can be output for the user's reference, for example, by displaying the health index and/or the fatigue index through the display screen.

In step S13, the smart wearable device provides the user with exercise guidance according to the user's health index and the fatigue index, so that the user's exercise intensity matches the physical condition of the user. Optionally, the sports instruction reference table is stored in the smart wearable device, and the exercise guide reference table includes different health indexes and fatigue indexes corresponding to different exercise instructions.

In the embodiment of the present invention, the specific process for the smart wearable device to provide the user with the motion guidance according to the user's health index and the fatigue index is as shown in FIG. 3, and includes the following steps:

S131. Calculate a theoretical maximum heart rate according to the age of the user.

The smart wearable device can calculate the theoretical maximum heart rate Η _max of the user according to the empirical formula: Η _max = 205.8-0.685*a, where a is the age.

In other embodiments, the age of the user may also be subtracted from 205 or 220 as the user's maximum heart rate.

S132. Correcting the theoretical maximum heart rate by using the health index to obtain a corrected maximum heart rate.

Smart wearable devices can be based on the formula:

Calculate the corrected maximum heart rate

Where α is the health index.

S133. Calculate an upper limit value of the exercise heart rate according to the corrected maximum heart rate and the fatigue index.

Smart wearable devices can be based on the formula:

Calculate the upper limit of exercise heart rate

Where γ is the fatigue index,

To correct the maximum heart rate.

S134. Provide motion guidance according to the upper limit of the exercise heart rate.

Optionally, the smart wearable device may directly output the user's exercise heart rate upper limit value and corresponding motion guidance, so that the user adjusts the exercise intensity according to the exercise heart rate upper limit value.

Specifically, the smart wearable device pops up a selection dialog box (as shown in FIG. 4a), and when receiving the user selected exercise intensity type, searches for a corresponding maximum heart rate intensity percentage in the pre-stored comparison table (FIG. 4b) according to the user selected exercise intensity type. (ie, the percentage of the upper limit of the exercise heart rate, hereinafter referred to as the maximum heart rate intensity%); then multiply the upper limit of the exercise heart rate by the percentage of the highest heart rate intensity to calculate the heart rate guidance range that matches the user's motion and display it on the display screen.

For example, if the smart wearable device receives the type of exercise intensity selected by the user as a light fat burning exercise, and the upper limit value of the output user's exercise heart rate is 190, then the highest heart rate intensity is known in the pre-stored comparison table according to the lightweight fat burning exercise. For 50-60%, the operating heart rate guide range: 190*(50-60%)=95-114, the smart wearable device will display the heart rate guidance range of 95-114, and the user needs to maintain the real-time heart rate during the exercise. Between 95-114.

Optionally, the smart wearable device can also detect the real-time heart rate of the user in real time or time during the user's motion, and determine whether the real-time heart rate is within the heart rate guidance range, and if the real-time heart rate is not in the range of the heart rate, the user is alerted. In other embodiments, the real heart rate is divided by the upper limit of the exercise heart rate to obtain the highest heart rate intensity %, and the pre-stored comparison table is used to analyze the current exercise intensity type corresponding to the highest heart rate intensity %, and output the current exercise intensity. Type, such as voice announcements and/or display the current type of exercise intensity.

Alternatively, when the smart wearable device detects excessive fatigue of the user, the user may be advised not to perform the exercise of the intensity above the fat burning exercise.

Further, the smart wearable device can also count the amount of exercise of the user in the past preset time (such as within the past 60 minutes), and normalize the current real-time heart rate of the user by using the exercise amount to obtain a normalized real-time heart rate, and then The user's psychological stress index is calculated based on the normalized real-time heart rate. Optionally, the smart wearable device can output a psychological stress index for the user to refer to, such as displaying a psychological stress index through the display screen.

In a specific implementation, the smart wearable device can count the modulus of the acceleration data of the acceleration sensor within a preset time period (eg, within the past 60 minutes).

Where x, y, and z are acceleration data of the acceleration sensor in the x-axis, y-axis, and z-axis directions. Then calculate the ratio of the modulus length of the acceleration data to the gravity G

The standard deviation is the amount of exercise that the user has in the past preset time period.

Then, the smart wearable device can count the average of the real-time heart rate in the current period of time (such as within one minute), and use the average value as the current real-time heart rate of the user. And use the formula:

Normalize the real-time heart rate, where m is the amount of exercise and hr is the real-time heart rate.

Normalized real-time heart rate.

Finally, smart wearable devices can take advantage of the formula:

Calculating the user's psychological stress index s, where hb is the basal heart rate,

For normalized real-time heart rate.

Further, the smart wearable device can also calculate the user's exercise index according to the psychological stress index and the fatigue index, and provide the user with motion suggestions according to the exercise index, such as suggesting the user to exercise or not. The exercise index is positively correlated with the degree of exercise, that is, the higher the exercise index, the more the user is recommended to move, and the less the user is recommended.

In specific implementation, the smart wearable device can calculate the user's exercise index χ using the formula: χ=s*(1-γ), where γ is the fatigue index and s is the psychological stress index.

Smart wearable devices can classify motion recommendations into two levels: user motion is not recommended and user motion is recommended, and motion recommendations can be divided into three levels: user motion is not recommended, user motion is recommended, and user motion is strongly recommended. Sports recommendations are divided into more than three levels. The smart wearable device can display the level of the user's motion and suggest the user's movement in the form of text on the display screen or voice broadcast, and strongly recommend the user's level of motion as a kind of time alarm, vibration, text display, icon display, etc. Or a variety of remind users to exercise.

For example, the smart wearable device compares the motion index with the first threshold and the second threshold, and when the motion index is less than or equal to the first threshold, displays “not recommended user motion” on the display screen; when the motion index is between the first threshold When the second threshold is used, the “recommended user motion” is displayed on the display screen; when the motion index is greater than or equal to the second threshold, the user is strongly recommended to move, that is, in the manner of timed alarm, vibration, text display, icon display, etc. One or more of the reminders of the user's movement. The first threshold is smaller than the second threshold, and the first threshold and the second threshold may be set according to actual needs. For example, the first threshold may be set to 0.2-0.4 (if set to 0.3), and the second threshold may be set to 0.6-0.8. (if set Set to 0.7).

In other embodiments, only one third threshold may be set. When the motion index is less than or equal to the third threshold, user motion is not recommended; when the motion index is greater than the third threshold, user motion is recommended.

The exercise guidance method of the embodiment of the invention obtains the user's basic heart rate and heart rate variability index, calculates the user's health index and the fatigue index according to the basal heart rate and the heart rate variability index, thereby providing the user with personalized information according to the health index and the fatigue index. The exercise guidance makes the user's exercise intensity match the physical state, prevents the exercise intensity from being too large and causes harm to the body, improves the practicality and intelligence of the smart wearable device, and improves the user experience.

Referring to FIG. 5, a first embodiment of the motion guiding device of the present invention is provided. The device includes an obtaining module 10, a calculating module 20, and a guiding module 30, wherein: the obtaining module 10 is configured to acquire a basic heart rate and a heart rate variability index of the user; The calculating module 20 is configured to calculate a health index of the user according to the basic heart rate and the heart rate variability index, and calculate a fatigue index of the user according to the basic heart rate; and a guiding module 30, configured to provide the user with motion guidance according to the health index and the fatigue index.

The acquisition module 10 detects the user's basal heart rate through a heart rate sensor and counts the heart rate variability index. In a specific implementation, the acquiring module 10 may determine the wake-up time of the user by using the sleep monitoring function, and calculate the standard deviation by collecting 200 samples of the RR interval at a preset frequency (such as 1 Hz) according to the HRV mode of the heart rate sensor, and the calculation will be performed. The result was used as a heart rate variability index. The average heart rate measured over a certain period of time (eg, within one minute) is averaged as the basal heart rate. When determining the sleep time, the acquisition module 10 can utilize the acceleration sensor to match the sleep time and the wake-up time set by the user for accurate judgment.

Optionally, the obtaining module 10 may take real-time heart rate data (ie, the currently detected heart rate data) within a certain period of time (eg, within half an hour) before the user wakes up, and calculate the basic heart rate of the day, and then for a period of time (eg, The basal heart rate data of the day of the tenth day is subjected to median filtering processing, and the processing result is taken as the basal heart rate of the user.

The calculation module 20, as shown in FIG. 6, includes a health index calculation unit 21 and a fatigue index calculation unit 22.

As shown in FIG. 7, the health index calculation unit 21 includes a first index calculation unit 211, a second index calculation unit 212, and a product calculation unit 213, in which:

The first index calculation unit 211 is configured to perform normalization processing on the heart rate variability index by using the basal heart rate, and substitute the processing result into the first statistical regression formula to calculate the first index.

Specifically, the first index calculation unit 211 utilizes a normalization formula:

The result of the heart rate variability index is the normalized heart rate variability index. Then, the first index calculation unit 211 will

The second index calculation unit 212 is configured to perform normalization processing on the basic heart rate by using the gender and age of the user, and substitute the processing result into the second statistical regression formula to calculate the second index.

Specifically, the second index calculation unit 212 uses the normalization formula:

To normalize the basal heart rate, that is, the processing result of the basal heart rate. Then, the second index calculation unit 212 will

Substituting into the first statistical regression formula

The product calculation unit 213 is configured to use the product of the first index and the second index as the health index.

The product calculation unit 213 substitutes the first index α ₁ and the second index α ₂ into the formula: α = α ₁ * α ₂ , and calculates the user's health index α.

In other embodiments, the health index calculation unit 21 may also calculate the heart cycle of the user through the heart rate sensor, and then calculate the health index of the user according to the basic heart rate, the heart rate variability index, and the heart cycle. For example, according to the formula: I=(100-hb)*hi/p, the user's body mass index I is calculated, and the body mass index is taken as the user's health index. Among them, hb is the basal heart rate, hi is the heart rate variability index, and p is the heart rate cycle.

In other embodiments, after calculating the body mass index I of the user, the health index calculation unit 21 further calculates the user's fitness index U according to the formula: U=2*I*hb/hn-1, and calculates the fitness index. As a user's health index. Among them, hn is the current real-time heart rate, hb is the basal heart rate, and I is the body mass index.

As shown in FIG. 8, the fatigue index calculation unit 22 includes a time statistics unit 221 and a result calculation unit 222, in which:

Time statistics unit 221: used to count the time t after the user's real-time heart rate is restored to within n times of the basal heart rate after the end of the exercise.

The value of n can be determined according to actual needs, and is preferably in the range of 1-1.5. For example, the time statistic unit 221 defines the end of the exercise using the motion discrimination function of the acceleration sensor, and the time t of the user's real-time heart rate after the end of the statistical exercise is restored to within 1.25 times the basal heart rate.

The result calculation unit 222 is configured to calculate the fatigue index of the user according to the time t.

The result calculation unit 222 can substitute the time t into the formula:

The user's fatigue index γ is calculated.

Optionally, the fatigue index calculation unit 22 counts the median of the basal heart rate in the most recent period (eg, 90 days), and determines whether the basal heart rate of the most recent D day (eg, 2-5 days, preferably 3 days) exceeds the median. The preset value (such as 5-15 units, preferably 10 units), if the median preset value is exceeded, determines that the user is excessively fatigued and can prompt the user to be excessively tired.

After calculating the user's health index and fatigue index, the calculation module 20 may output a health index and/or a fatigue index for the user's reference, such as displaying the health index and/or the fatigue index through the display screen.

The guidance module 30, as shown in FIG. 9, includes a maximum heart rate calculation unit 31, a maximum heart rate correction unit 32, a exercise heart rate calculation unit 33, and a motion guidance unit 34, wherein:

The maximum heart rate calculation unit 31 is configured to calculate the theoretical maximum heart rate of the user according to the age of the user.

The maximum heart rate calculation unit 31 can calculate the theoretical maximum heart rate Η _max of the user according to the empirical formula: Η _max = 205.8 - 0.685 * a, where a is the age.

The maximum heart rate correction unit 32 is configured to correct the theoretical maximum heart rate using the health index to obtain a corrected maximum heart rate.

The maximum heart rate correction unit 32 can be based on the formula:

Calculate the corrected maximum heart rate

Where α is the health index.

Exercise heart rate calculation unit 33: for correcting the maximum heart rate and the fatigue index to calculate the exercise heart rate Limit.

The exercise heart rate calculation unit 33 can according to the formula:

Calculate the upper limit of exercise heart rate

Where γ is the fatigue index,

To correct the maximum heart rate.

The motion guiding unit 34 is configured to provide motion guidance according to the user's exercise heart rate upper limit value.

Optionally, the motion guiding unit 34 may directly output the user's exercise heart rate upper limit value and its corresponding motion guidance, so that the user adjusts the exercise intensity according to the exercise heart rate upper limit value.

Specifically, the motion guiding unit 34 includes an ejecting unit, a receiving unit, a searching unit, an arithmetic unit, and a display unit. The pop-up unit is configured to pop up a selection dialog box (as shown in FIG. 4a); the receiving unit is configured to receive the type of motion intensity selected by the user, and the searching unit is configured to search for a corresponding correspondence table (FIG. 4b) according to the type of exercise intensity selected by the user. The percentage of the highest heart rate intensity (ie, the percentage of the upper limit of the exercise heart rate, hereinafter referred to as the maximum heart rate intensity %); the arithmetic unit is used to multiply the upper limit of the exercise heart rate by the percentage of the highest heart rate intensity to calculate a range of guiding heart rate in accordance with the user's motion, the display unit Used to display the guided heart rate range on the display.

For example, the receiving unit receives the light fat burning motion selected by the user, and the motion guiding unit 34 outputs the upper limit of the exercise heart rate of the user, and the searching unit searches for the highest heart rate intensity % in the pre-stored comparison table according to the lightweight fat burning motion. 50-60%: The calculation unit can calculate the heart rate guide range is 190*(50-60%)=95-114, and the display unit displays 95-114 on the display screen, so the user needs to maintain the real-time heart rate during the exercise. Between 95-114.

Optionally, the motion guiding unit 34 may further include a heart rate detecting unit, a heart rate determining unit, and a reminding unit, wherein the heart rate detecting unit is configured to detect the real-time heart rate of the user in real time or timing during the user's motion, and the heart rate determining unit is configured to determine the real-time. Whether the heart rate is within the heart rate guidance, the reminder unit is used to alert the user when the real-time heart rate is not in the range of the heart rate. In other embodiments, the motion guiding unit 34, the intensity calculating unit, the analyzing unit, the output unit, and the intensity calculating unit are configured to obtain the highest heart rate intensity % according to the real-time heart rate divided by the exercise heart rate upper limit value, and the analyzing unit is configured to use the pre-stored comparison table according to the pre-stored comparison table. The current intensity type corresponding to the current maximum heart rate intensity % is analyzed, and the output unit is used to output the current exercise intensity type, such as voice announcement and/or display current exercise intensity type.

Alternatively, when the fatigue index calculation unit 22 detects excessive fatigue of the user, the exercise instruction unit 34 may suggest that the user does not perform the exercise of the intensity above the fat burning exercise.

The exercise guiding device of the embodiment of the invention obtains the user's basic heart rate and heart rate variability index, calculates the user's health index and the fatigue index according to the basal heart rate and the heart rate variability index, thereby providing the user with personalized information according to the health index and the fatigue index. Exercise guidance, making the user's movement stronger The degree is matched with the physical state to prevent the exercise intensity from being too large and causing harm to the body, which improves the practicality and intelligence of the smart wearable device and improves the user experience.

Further, as shown in FIG. 10, in a second embodiment of the inventive exercise instructing device, the device further includes a suggestion module 40 for providing motion suggestions to the user.

At this time, the calculation module 20, as shown in FIG. 11, further includes a psychological stress index calculation unit 23 for calculating a psychological stress index of the user.

As shown in FIG. 12, the psychological stress index calculation unit 23 includes an exercise amount statistical unit 231, a normalization processing unit 232, and a pressure calculation unit 233, in which:

The exercise amount statistics unit 231 is configured to count the amount of exercise of the user within a preset time period (such as within the past 60 minutes).

As shown in FIG. 13, the motion amount statistics unit 231 includes a modulus length statistic unit 2311 and a standard deviation calculation unit 2312, wherein: the modulo length statistic unit 2311 is configured to calculate the modulo of the acceleration data within a preset time period (eg, within the past 60 minutes). long

Where x, y, z are acceleration data of the acceleration sensor x-axis, y-axis, and z-axis directions; the standard deviation calculation unit 2312 is configured to calculate the ratio of the modulus length of the acceleration data to the gravity G

The normalization processing unit 232 is configured to normalize the current real-time heart rate of the user by using the amount of exercise to obtain a normalized real-time heart rate.

The normalization processing unit 232 can count the average of the real-time heart rates over the current period of time (eg, within one minute), and use the average as the current real-time heart rate of the user. And use the formula:

Normalized real-time heart rate.

The pressure calculation unit 233 is configured to calculate a psychological stress index of the user according to the basic heart rate and the normalized real-time information.

The pressure calculation unit 233 can utilize the formula:

For normalized real-time heart rate.

Optionally, after calculating the psychological stress index, the calculation module 20 may output a psychological stress index for the user to refer to, for example, displaying a psychological stress index through a display screen.

The suggestion module 40, as shown in FIG. 14, includes a motion index calculation unit 41 and a motion suggestion unit 42, wherein:

The exercise index calculation unit 41 is configured to calculate a user's exercise index based on the psychological stress index and the fatigue index.

The exercise index calculation unit 41 can calculate the user's exercise index χ using the formula: χ=s*(1-γ), where γ is the fatigue index and s is the psychological stress index.

The motion suggesting unit 42 is configured to provide a motion suggestion to the user according to the motion index, such as suggesting that the user exercise or not. The exercise index is positively correlated with the degree of exercise, that is, the higher the exercise index, the more the user is recommended to move, and the less the user is recommended.

The motion suggestion unit 42 can divide the motion suggestions into two levels: the user motion is not recommended and the user motion is suggested, and the motion suggestions can be divided into three levels: user motion is not recommended, user motion is recommended, and user motion is strongly recommended, and Divide the exercise recommendations into more than three levels. The motion suggesting unit 42 may display the level of not suggesting the user's motion and suggesting the user's motion to be displayed on the display screen or the voice broadcast in a text form, and the level of the user's motion is strongly recommended to be one of a timing alarm, a vibration, a text display, an icon display, and the like. Kind or more to remind users.

In an optional embodiment, the motion suggesting unit 42 includes a comparing unit 421, a first suggesting unit 422, a second suggesting unit 423, and a third suggesting unit 424, as shown in FIG. 15, wherein: the comparing unit 421 is configured to compare a size of the motion index and the first threshold and the second threshold; a first suggesting unit 422, configured to display “not recommending user motion” on the display screen when the motion index is less than or equal to the first threshold; the second suggesting unit 423, For displaying the “recommended user motion” on the display screen when the motion index is between the first threshold and the second threshold; the third suggesting unit 424 is configured to strongly recommend when the motion index is greater than or equal to the second threshold User movement, that is, one or more of the methods of timed alarm, vibration, text display, icon display, etc., reminds the user to exercise.

The first threshold is smaller than the second threshold, and the first threshold and the second threshold may be set according to actual needs. For example, the first threshold may be set to 0.2-0.4 (if set to 0.3), and the second threshold may be set to 0.6-0.8. (if set to 0.7).

In other embodiments, only one third threshold may be set. When the motion index is less than or equal to the third threshold, the motion suggesting unit 42 does not recommend user motion; when the motion index is greater than the third threshold, the motion suggesting unit 42 suggests the user motion.

In this embodiment, the user's psychological stress index is further calculated, and the user is provided with motion suggestions according to the psychological stress index, thereby further improving the practicability and intelligence of the smart wearable device and improving the user experience.

The motion guiding method and device of the embodiment of the present invention, without changing the hardware of the existing product, By fully analyzing and synthesizing the user's activity information and physiological information, the index information of the health index and the fatigue index psychological stress index is given, and the user is provided with real-time fitness data monitoring, and provides sports guidance and exercise for the user accordingly. It is recommended to improve the practicality and intelligence of smart wearable devices.

The present invention also contemplates a smart wearable device that includes a memory, a processor, and at least one application stored in the memory and configured to be executed by the processor, the application being configured to execute a motion coaching method. The exercise guiding method comprises the steps of: obtaining a user's basal heart rate and a heart rate variability index; calculating a user's health index according to the basal heart rate and the heart rate variability index, and calculating a user's fatigue index according to the basal heart rate; according to the health index and the fatigue index Provide sports guidance for users. The motion guiding method described in this embodiment is the motion guiding method involved in the foregoing embodiment of the present invention, and details are not described herein again.

The smart wearable device of the embodiment of the present invention calculates the user's health index and the fatigue index according to the basic heart rate and the heart rate variability index by acquiring the user's basal heart rate and heart rate variability index, thereby providing the user with personalized information according to the health index and the fatigue index. The exercise guidance makes the user's exercise intensity match the physical state, prevents the exercise intensity from being too large and causes harm to the body, improves the practicality and intelligence of the smart wearable device, and improves the user experience.

Those skilled in the art will appreciate that the present invention includes apparatus that is directed to performing one or more of the operations described herein. These devices may be specially designed and manufactured for the required purposes, or may also include known devices in a general purpose computer. These devices have computer programs stored therein that are selectively activated or reconfigured. Such computer programs may be stored in a device (eg, computer) readable medium or in any type of medium suitable for storing electronic instructions and coupled to a bus, respectively, including but not limited to any Types of disks (including floppy disks, hard disks, optical disks, CD-ROMs, and magneto-optical disks), ROM (Read-Only Memory), RAM (Random Access Memory), and EPROM (Erasable Programmable Read-Only Memory, Erasable programmable read-only memory, EEPROM (Electrically Erasable Programmable Read-Only Memory), flash memory, magnetic card or light card. That is, a readable medium includes any medium that is stored or transmitted by a device (eg, a computer) in a readable form.

The above is only the preferred embodiment of the present invention, and is not intended to limit the scope of the invention, and the equivalent structure or equivalent process transformations made by the description of the invention and the drawings are directly or indirectly applied to other related The technical field is equally included in the scope of patent protection of the present invention.

Claims

A motion guiding method, comprising the steps of:

Obtain the user's basal heart rate and heart rate variability index;

Calculating a health index of the user according to the basal heart rate and the heart rate variability index, and calculating a fatigue index of the user according to the basal heart rate;

The user is provided with exercise guidance based on the health index and the fatigue index.
The exercise guiding method according to claim 1, wherein the calculating the health index of the user according to the basal heart rate and the heart rate variability index comprises:

Normalizing the heart rate variability index by using the basal heart rate, and substituting the processing result into the first statistical regression formula to calculate a first index;

The basic heart rate is normalized by using the gender and age of the user, and the processing result is substituted into the second statistical regression formula to calculate the second index;

The product of the first index and the second index is taken as the health index.
The exercise guidance method according to claim 1, wherein the method further comprises:

Count the amount of exercise the user has in the past preset time period;

Normalizing the current real-time heart rate of the user by using the amount of exercise to obtain a normalized real-time heart rate;

Using formula
Calculate the user's psychological stress index, where hb is the basal heart rate,
For normalized real-time heart rate, s is the psychological stress index.
The exercise guidance method according to claim 3, wherein the method further comprises:

The exercise index is calculated by the formula χ=s*(1-γ), where γ is the fatigue index, s is the psychological stress index, and χ is the exercise index;

The user is provided with a motion recommendation based on the athletic index.
The exercise guiding method according to claim 3, wherein the step of counting the amount of exercise of the user in the past preset time period comprises:

Counting the modulus length of the acceleration data in the past preset time period;

The standard deviation of the ratio of the modulus length to the gravity of the acceleration data is calculated, and the calculation result is used as the amount of motion of the user in the past preset time period.
The exercise guiding method according to claim 2, wherein the step of normalizing the heart rate variability index according to the basal heart rate comprises:

Using formula
Normalizing the heart rate variability index, wherein hb is the basal heart rate and hi is the heart rate variability index.
The result of processing the heart rate variability index.
The exercise guidance method according to claim 2, wherein the first statistical regression formula is:

α 1 =0.0000147x 3 -0.002303456x 2 +0.09017484x, wherein α 1 is the first index, and the processing result of the heart rate variability index is substituted into x.
The exercise guiding method according to claim 1, wherein the calculating the fatigue index of the user according to the basic heart rate comprises:

The time t after the user's real-time heart rate is restored to within n times of the basal heart rate after the end of the statistical exercise;

The user's fatigue index is calculated by substituting the time t into the formula γ=1-e -t+120/60 , where γ is the fatigue index.
The exercise guidance method according to claim 8, wherein n has a value ranging from 1 to 1.5.
The exercise guidance method according to claim 1, wherein the step of providing exercise guidance to the user based on the health index and the fatigue index comprises:

Calculate the theoretical maximum heart rate of the user according to the age of the user;

Correcting the theoretical maximum heart rate by using the health index to obtain a corrected maximum heart rate;

According to the formula
Calculate the upper limit of the exercise heart rate, where γ is the fatigue index,
To correct the maximum heart rate,
To run the upper heart rate limit;

The exercise guidance is provided to the user according to the upper limit of the exercise heart rate.
A motion guiding device, comprising:

An acquisition module for obtaining a user's basal heart rate and heart rate variability index;

a calculation module, configured to calculate a health index of the user according to the basic heart rate and the heart rate variability index, and calculate a fatigue index of the user according to the basal heart rate;

A guidance module for providing exercise guidance to the user based on the health index and the fatigue index.
The exercise instructing device according to claim 11, wherein the calculation module comprises a health index calculation unit, and the health index calculation unit comprises:

a first index calculation unit, configured to normalize the heart rate variability index by using the basal heart rate, and substitute the processing result into the first statistical regression formula to calculate a first index;

a second index calculation unit for returning the basic heart rate by using the gender and age of the user The processing is performed, and the processing result is substituted into the second statistical regression formula to calculate the second index;

a product calculation unit for using a product of the first index and the second index as the health index.
The exercise instructing device according to claim 11, wherein the calculation module further comprises a psychological stress index calculation unit, wherein the psychological stress index calculation unit comprises:

The exercise amount statistics unit is configured to count the amount of exercise of the user in the past preset time period;

a normalization processing unit, configured to normalize the current real-time heart rate of the user by using the amount of exercise, to obtain a normalized real-time heart rate;

Pressure calculation unit for using formulas
Calculate the user's psychological stress index, where hb is the basal heart rate,
For normalized real-time heart rate, s is the psychological stress index.
The motion guiding device according to claim 13, wherein the device further comprises a suggestion module, the suggesting module comprising:

The exercise index calculation unit is configured to calculate the exercise index by using the formula χ=s*(1-γ), wherein γ is a fatigue index, s is a psychological stress index, and χ is a sports index;

a motion suggesting unit for providing motion suggestions to the user based on the motion index.
The exercise instruction device according to claim 13, wherein the exercise amount statistics unit comprises:

a modulus length statistical unit for counting the modulus length of the acceleration data in the past preset duration;

The standard deviation calculation unit is configured to calculate a standard deviation of a ratio of a modulus length of the acceleration data to a gravity, and use the calculation result as the amount of motion of the user within a preset preset time period.
The exercise instructing device according to claim 12, wherein said first index calculating unit is configured to:

Using formula
Normalizing the heart rate variability index, wherein hb is the basal heart rate and hi is the heart rate variability index.
The result of processing the heart rate variability index.
The exercise instructing device according to claim 12, wherein said first statistical regression formula is:

α 1 =0.0000147x 3 -0.002303456x 2 +0.09017484x, wherein α 1 is the first index, and the processing result of the heart rate variability index is substituted into x.
The exercise instructing device according to claim 11, wherein the second index calculating unit is configured to:

Using formula
Normalizing the basal heart rate, wherein a is age, k is a gender compensation coefficient, and hb is a basal heart rate,
The result of the processing of the heart rate.
The exercise instructing device according to claim 11, wherein the calculation module comprises a fatigue index calculation unit, and the fatigue index calculation unit comprises:

a time statistics unit, configured to count the time t after the user's real-time heart rate is restored to within n times of the basal heart rate after the end of the exercise;

The result calculation unit is configured to calculate the fatigue index of the user by substituting the time t into the formula γ=1-e −t+120/60 , wherein γ is a fatigue index.
A smart wearable device comprising a memory, a processor and at least one application stored in the memory and configured to be executed by the processor, wherein the application is configured to execute a right The exercise instruction method described in claim 1.