CN117958802A

CN117958802A - Walking test method and device and electronic equipment

Info

Publication number: CN117958802A
Application number: CN202211301584.7A
Authority: CN
Inventors: 崔雨琦; 陈文娟; 李靖; 王伟; 郭建华; 臧振飞; 陈玉梅
Original assignee: Huawei Technologies Co Ltd
Current assignee: Huawei Technologies Co Ltd
Priority date: 2022-10-24
Filing date: 2022-10-24
Publication date: 2024-05-03

Abstract

The embodiment of the application provides a walking test method, which comprises the following steps: determining a walking distance predicted value of the user according to the motion data of the user and the motion type of the user; determining a compensation distance according to the motion type and the motion intensity of the user, wherein the motion data, the motion type and the motion intensity correspond to a first motion process of the user; a first walking distance of the user is then determined based on the walking distance prediction value and the compensation distance. The method can actively initiate the walking test when the test condition is met, and can combine the exercise intensity, the exercise type and the like of the user to obtain the walking test result of the user, so that the test frequency can be improved, the health level of the user can be better monitored, the accuracy of the test result can be improved, and the use experience of the user is further improved.

Description

Walking test method and device and electronic equipment

Technical Field

The embodiment of the application relates to the field of health monitoring, and more particularly relates to a walking test method, a walking test device and electronic equipment.

Background

Cardiovascular diseases and respiratory diseases are two major factors threatening the health of people in China, and chronic cardiovascular diseases and respiratory diseases are usually accompanied by the reduction of exercise tolerance, so that accurate assessment of the heart and lung functions and exercise tolerance of patients in exercise state is very important.

Disclosure of Invention

The application provides a walking test method, a walking test device and electronic equipment. According to the method, the walking test can be actively initiated when the test condition is met, the walking test result of the user can be obtained by combining comprehensive analysis and calculation of the exercise intensity, the exercise type, the crowd to which the user belongs and the like of the user, the test frequency can be improved, the monitoring of the health level of the user can be better realized, the accuracy of the test result can be improved, and the use experience of the user is further improved.

In a first aspect, a method of walk testing is provided, the method comprising: determining a walking distance predicted value of the user according to the motion data of the user and the motion type of the user; determining a compensation distance according to the motion type and the motion intensity, wherein the motion data, the motion type and the motion intensity of the user correspond to a first motion process of the user; a first walking distance of the user is determined based on the walking distance prediction value and the compensation distance.

Optionally, the motion data of the user includes one or more of step frequency, gait, speed and distance, and in addition, the motion data of the user may also include other data related to motion, which is not limited in this application.

Optionally, the type of exercise of the user may include one or more of walking, running, riding, stair climbing, swimming, and other exercise-related types, which the present application is not limited to.

Alternatively, the walk test may be a 6-minute walk test, and if Q (Q is greater than or equal to 1 and Q is not equal to 6) appears in the future, the walk test may also be a Q-minute walk test.

According to the embodiment of the application, the walking test can be initiated actively without sense when the test condition is met, the test frequency can be improved, and the monitoring of the health level of the user can be better realized; the walking test result of the user (the test result is compensated according to the exercise intensity and the exercise type) can be obtained by comprehensively analyzing and calculating the exercise intensity and the exercise type of the user, the accuracy of the test result can be improved, and the method supports the tests under different exercise types, has wide application scenes, and can improve the use experience of the user.

With reference to the first aspect, in a possible implementation manner, the method further includes: collecting motion data of a user and physiological data of the user in a first motion process of the user; determining a motion type of the user according to the motion data; the intensity of the user's movement is determined from the movement type and the physiological data.

Optionally, the physiological data of the user includes one or more of heart rate, blood oxygen and blood pressure, and in addition, the physiological data of the user may also include other data related to physiology, which is not limited in the present application.

With reference to the first aspect, in one possible implementation manner, determining the exercise intensity of the user according to the exercise type and the physiological data of the user includes: determining a maximum heart rate of the user according to the basic information of the user; correcting the maximum heart rate according to resting physiological data of the user; determining a motion intensity judgment threshold according to the motion type of the user and the corrected maximum heart rate; and determining the exercise intensity of the user according to the physiological data of the user and the exercise intensity judgment threshold.

Optionally, the basic information of the user includes one or more of age, height and weight, and in addition, the basic information of the user may also include other physiological information of the user, which is not limited by the present application.

Alternatively, the maximum heart rate of the user may be determined according to the basic information of the user, and may be determined according to the age of the user, specifically: maximum heart rate of user = 220-age of user.

Specifically, the exercise intensity judgment thresholds corresponding to different exercise types are different, firstly, the exercise intensity judgment threshold corresponding to the exercise type is required to be determined according to the exercise type of the user, and then the exercise physiological data of the user is compared with the exercise intensity judgment threshold, so that the exercise intensity of the user is determined.

Wherein, optionally, the exercise intensity judging threshold value comprises a first threshold value and a second threshold value, and when the exercise physiological data of the user is smaller than the first threshold value, the exercise intensity of the user is determined to be low (can also be described as a first intensity); when the exercise physiological data of the user is greater than or equal to a first threshold value and less than a second threshold value, determining the exercise intensity of the user as medium intensity (also can be described as second intensity); when the motor physiological data of the user is greater than or equal to the second threshold, the motor intensity of the user is determined to be high intensity (which may also be described as a third intensity).

According to the embodiment of the application, the exercise intensity of the user can be comprehensively determined according to the basic information, exercise type, exercise data and physiological data of the user, and different exercise intensity judgment thresholds are established for different exercise types in the process, so that the determined exercise intensity has higher credibility, and further, the walking distance output value obtained after the walking distance predicted value is compensated according to the exercise intensity is more accurate.

With reference to the first aspect, in one possible implementation manner, determining a first walking distance of the user according to the walking distance predicted value and the compensation distance includes: and obtaining the first walking distance of the user by summing the walking distance predicted value and the compensation distance.

Optionally, the walking distance prediction value coefficient is recorded as a, the compensation distance coefficient is recorded as b, or the product of the walking distance prediction value and the coefficient a and the product of the compensation distance and the coefficient b can be calculated respectively, and then the two products are summed to obtain the first walking distance of the user.

With reference to the first aspect, in a possible implementation manner, the method further includes: acquiring N walking distances of a user, wherein the N walking distances are in one-to-one correspondence with N movement processes of the user, and the N walking distances comprise the first walking distances; and determining the walking distance output value of the user according to the N walking distances and the resting physiological data of the user, wherein the resting physiological data of the user is physiological data of the user in a non-motion state.

Optionally, the physiological data of the user can be divided into exercise physiological data and resting physiological data according to the exercise state of the user, wherein the exercise physiological data refers to physiological data of the user in the exercise state (such as walking, running, swimming, etc.); resting physiological data refers to physiological data of a user in a non-exercise state (e.g., sitting, lying, etc.).

Wherein, the one-to-one correspondence of the N walking distances and the N movement processes of the user means that: each exercise course of the user obtains a walking distance of the user (the obtained method is as described in the first aspect), and then the N exercise courses of the user obtain N walking distances of the user, so that the N walking distances are in one-to-one correspondence with the N exercise courses of the user.

The walking distance output value of the user refers to a walking test result finally displayed to the user. Optionally, the walking distance output value may be displayed to the user in a chart manner, may be displayed to the user in a data manner, may be transmitted to the user in a voice broadcast manner, or may be combined in a plurality of display manners, which is not limited in the present application.

In the embodiment of the application, the integrated analysis is carried out on a plurality of walking distances corresponding to a plurality of movement processes of the user, and the result after the integrated analysis is corrected according to the rest physiological parameters of the user, so that the accuracy of the walking distance output value can be further improved.

With reference to the first aspect, in one possible implementation manner, determining a walking distance output value of the user according to the N walking distances and resting physiological data of the user includes: determining the crowd of the user according to the resting physiological data of the user; determining walking distance distribution conditions corresponding to the user according to the crowd to which the user belongs; respectively calculating weight values of the N walking distances according to the N walking distances and walking distance distribution conditions corresponding to the user; and determining the walking distance output value of the user according to the N walking distances and the weight values of the N walking distances.

Optionally, the group to which the user belongs includes one or more of a young healthy group, a middle-aged and elderly healthy group, a young sub-healthy group, a middle-aged and elderly sub-healthy group, a heart function abnormal group, and a lung function abnormal group, and in addition, the group to which the user belongs may also include other groups, which is not limited in the application.

Optionally, the characterization parameters of the walking distance distribution condition corresponding to the crowd to which the user belongs are mean and variance.

In one example, taking a six-minute walking test as an example, determining that the user is a middle-aged and elderly person according to resting physiological data of the user in a period of time, further obtaining a six-minute walking distance distribution condition of the middle-aged and elderly person as a mean value m, a variance σm, and constructing a gaussian function according to the mean value and the variance:

wherein x is any one of the N six-minute walking distances of the user; f (x) is the integration weight.

The larger the value of the I x-m I is, the farther the x distance average value is, the less reliable the corresponding six-minute walking distance is represented, and the smaller the integration weight is.

Optionally, the N six-minute walking distances of the user are multiplied by the respective integrated weights, and then the sum is divided by the sum of the integrated weights of the N six-minute walking distances of the user, so that the six-minute walking distance output value of the user can be obtained.

In one example, the 4 six-minute walking distances of the user are a1, a2, a3, a4, respectively, and the integration weights of the 4 six-minute walking distances of the user are b1, b2, b3, b4, respectively, then the six-minute walking distance output value of the user is:

According to the embodiment of the application, the prediction result weight deviating from the baseline of the crowd can be reduced by dividing the crowd and calculating the integrated weight, so that the prediction accuracy is improved; according to the method, the influence caused by a plurality of single walking distances of the user and different crowds to which the user belongs is considered, so that abnormal data can be effectively filtered, and the accuracy of a prediction result is improved.

With reference to the first aspect, in one possible implementation manner, the method further includes: and prompting the user to start a six-minute walk test when the effective exercise data of the user are not detected for M consecutive days.

Alternatively, the user is reminded to start a six-minute walk test through terminal equipment (such as a mobile phone and the like) carried by the user; the user can be reminded to start a six-minute walk test through a wearable device (e.g., watch, bracelet, etc.) worn by the user. The reminding mode can be vibration reminding, voice reminding, barrage character reminding and combination of a plurality of reminding modes, and the application is not limited to the above.

The valid motion data of the user may refer to motion data that may be used to perform a six-minute walk test, among other things.

According to the embodiment of the application, when the effective motion data of the user is not detected for a long time, the user can be reminded of the motion, the motion frequency of the user can be improved to a certain extent, and the use experience of the user can be improved.

With reference to the first aspect, in one possible implementation manner, the method further includes: when a user actively initiates a six-minute walk test through a mobile phone, if the mobile phone of the user is connected with the wearable device, the six-minute walk test is performed on the wearable device side; if the mobile phone of the user is not connected with the wearable device, six-minute walking test is performed on the mobile phone side.

In the embodiment of the application, six-minute walking test is initiated through the mobile phone side, so that the threshold of the test condition can be reduced, and more users can participate in the 6-minute walking test; in addition, the method can also realize that the mobile phone is combined with the wearable equipment for testing, so that the use experience of a user is further improved.

With reference to the first aspect, in one possible implementation manner, the method further includes: when the user actively initiates a six-minute walk test through the wearable device, performing the six-minute walk test on the wearable device side; if the wearable device is connected with the mobile phone of the user, after the six-minute walk test is completed, the six-minute walk test result is synchronized to the mobile phone.

According to the embodiment of the application, six-minute walking test can be initiated through the wearing equipment side, the mobile phone can be combined with the wearing equipment to perform the test, and the measurement record of the wearing equipment side can be synchronized to the mobile phone, so that the measurement record can be stored for a long time, and a user can observe the change (improvement or deterioration) of the self-movement capacity through looking up the history record, so that the use experience of the user is further improved.

With reference to the first aspect, in one possible implementation manner, the method further includes: and reminding the user of walking along the straight line when detecting that the walking track of the user deviates from the straight line.

Optionally, the user can be reminded to walk along the straight line through terminal equipment (such as a mobile phone and the like) carried by the user; the user can be reminded to walk along the straight line through a wearing device (such as a watch, a bracelet and the like) worn by the user. The reminding mode can be vibration reminding, voice reminding, barrage character reminding and combination of a plurality of reminding modes, and the application is not limited to the above.

In the embodiment of the application, when the movement track of the user is detected to deviate from the straight line, the user is reminded to move along the straight line as much as possible when the accuracy of the final test result is possibly influenced, so that the accuracy of the test result can be improved to a certain extent.

With reference to the first aspect, in one possible implementation manner, the method further includes: and when the six-minute walk test is finished, displaying a six-minute walk test report on a display screen of the mobile phone or the wearable device of the user.

Optionally, the six-minute walk test report includes one or more of a data section, a chart section, an interpretation section, and a advice section. Wherein, optionally, the data part comprises the data of the height, weight, body mass index, age, average step frequency, average step speed, gait stability, walking distance and the like of the user; the chart part comprises a comparison chart between the six-minute walking distance of the user and the historical test result, the same person and the standard value of the user; the interpretation part comprises interpretation of the test result of the user; the advice section includes health advice for the user.

In the embodiment of the application, the 6-minute walking test result report of the user can be interpreted, so that the user can clearly know whether each index of the user is normal or not, and know the difference between the exercise capacity of the user and the standard value of the same person, and the user can clearly know the current exercise capacity positioning of the user; and scientific guidance opinions can be provided for the user according to the evaluation results.

With reference to the first aspect, in one possible implementation manner, the method further includes: and reminding the user whether to start the six-minute walking test or not when detecting that the current movement of the user meets the condition of the six-minute walking test.

Wherein, alternatively, the conditions of the six-minute walk test may be: the user's walking track is on a straight line, and the user's current physiological data does not belong to the following cases: heart rate >180 or blood oxygenation <90% or low pressure >100 or high pressure >180.

Alternatively, the user can be reminded of whether to start a six-minute walk test through terminal equipment (such as a mobile phone and the like) carried by the user; it may also be to alert the user whether to turn on a six-minute walk test by means of a wearable device (e.g., watch, bracelet, etc.) worn by the user. The reminding mode can be vibration reminding, voice reminding, barrage character reminding and combination of a plurality of reminding modes, and the application is not limited to the above.

Optionally, the reminder page is associated with a control "start", which when clicked by the user enters a six minute walk test phase.

It should be understood that the six-minute walk test described above may also be replaced with a Q (Q is greater than or equal to 1 and Q is not equal to 6) minute walk test.

According to the embodiment of the application, when the user is detected to meet the 6-minute walking test condition, the user is reminded whether to start the test, the movement frequency of the user can be improved to a certain extent, and the use experience of the user can be improved.

In a second aspect, there is provided an apparatus for walk testing, the apparatus comprising: the distance prediction module is used for determining a walking distance predicted value of the user according to the motion data of the user and the motion type of the user; the distance prediction module is further used for determining a compensation distance according to the motion type and the motion intensity of the user, wherein the motion data, the motion type and the motion intensity of the user correspond to a first motion process of the user; the distance prediction module is further configured to determine a first walking distance of the user according to the walking distance prediction value and the compensation distance.

With reference to the second aspect, in a possible implementation manner, the apparatus further includes: the data acquisition module is used for acquiring the motion data of the user and the physiological data of the user in the first motion process of the user; the distance prediction module is also used for determining the motion type of the user according to the motion data; and the intensity determining module is used for determining the exercise intensity of the user according to the exercise type and the physiological data of the user.

With reference to the second aspect, in one possible implementation manner, the intensity determining module is specifically configured to: determining a maximum heart rate of the user according to the basic information of the user; correcting the maximum heart rate according to resting physiological data of the user; determining a motion intensity judgment threshold according to the motion type of the user and the corrected maximum heart rate; and determining the exercise intensity of the user according to the physiological data and the exercise intensity judging threshold.

Optionally, the intensity determination module determines the maximum heart rate of the user according to the basic information of the user, which may be that the intensity determination module determines the maximum heart rate according to the age of the user, specifically may be that: maximum heart rate of user = 220-age of user.

Specifically, the exercise intensity judgment thresholds corresponding to different exercise types are different, and the intensity determination module is required to determine the exercise intensity judgment threshold corresponding to the exercise type according to the exercise type of the user, and then compare the exercise physiological data of the user with the exercise intensity judgment threshold, so as to determine the exercise intensity of the user.

Wherein, optionally, the exercise intensity judgment threshold value comprises a first threshold value and a second threshold value, and when the exercise physiological data of the user is smaller than the first threshold value, the intensity determination module determines that the exercise intensity of the user is low intensity (can also be described as first intensity); when the exercise physiological data of the user is greater than or equal to a first threshold value and less than a second threshold value, the intensity determination module determines the exercise intensity of the user as a medium intensity (which may also be described as a second intensity); when the motor physiological data of the user is greater than or equal to the second threshold, the intensity determination module determines that the motor intensity of the user is high intensity (which may also be described as a third intensity).

In the embodiment of the application, the intensity determination module can comprehensively determine the exercise intensity of the user according to the basic information, exercise type, exercise data and physiological data of the user, and different exercise intensity judgment thresholds are established for different exercise types in the process, so that the determined exercise intensity has higher credibility, and further, the walking distance output value obtained after the distance prediction value is compensated according to the exercise intensity is more accurate.

With reference to the second aspect, in one possible implementation manner, the distance prediction module is specifically configured to: and obtaining the first walking distance of the user by summing the walking distance predicted value and the compensation distance.

Optionally, the walking distance prediction value coefficient is recorded as a, the compensation distance coefficient is recorded as b, or the distance prediction module calculates to obtain the product of the walking distance prediction value and the coefficient a and the product of the compensation distance and the coefficient b, and then sums the two products to obtain the first walking distance of the user.

With reference to the second aspect, in a possible implementation manner, the apparatus further includes: the result integration module is used for acquiring N walking distances of the user, wherein the N walking distances are in one-to-one correspondence with N movement processes of the user, and the N walking distances comprise the first walking distance; the result integrating module is further used for determining walking distance output values of the user according to the N walking distances and resting physiological data of the user, wherein the resting physiological data are physiological data in a non-motion state.

With reference to the second aspect, in one possible implementation manner, the result integration module is specifically configured to: determining the crowd of the user according to the resting physiological data of the user; determining walking distance distribution conditions corresponding to the user according to the crowd to which the user belongs; respectively calculating weight values of the N walking distances according to the N walking distances and walking distance distribution conditions corresponding to the user; and determining the walking distance output value of the user according to the N walking distances and the weight values of the N walking distances.

In one example, taking a six-minute walking test as an example, the result integration module determines that the user is a middle-aged and elderly person according to resting physiological data of the user in a period of time, further obtains that the six-minute walking distance distribution condition of the middle-aged and elderly person is a mean value m and a variance σm, and the result integration module can construct a gaussian function according to the mean value and the variance:

Optionally, the result integrating module multiplies the N six-minute walking distances of the user by the respective integrated weights, and then sums the multiplied integrated weights, and divides the multiplied integrated weights by the N six-minute walking distances of the user, thereby obtaining the six-minute walking distance output value of the user.

In the embodiment of the application, the result integration module can reduce the predicted result weight deviating from the baseline of the crowd by dividing the crowd and calculating the integrated weight, thereby improving the prediction accuracy; according to the method, the influence caused by a plurality of single six-minute walking distances of the user and different crowds to which the user belongs is considered, so that abnormal data can be effectively filtered, and the accuracy of a prediction result is improved.

With reference to the second aspect, in a possible implementation manner, the apparatus further includes: and the reminding module is used for reminding the user to start a six-minute walking test when the effective movement data of the user are not detected in M consecutive days.

Optionally, the reminding module may remind the user to start the six-minute walk test through a terminal device (such as a mobile phone) carried by the user; the user can be reminded to start a six-minute walk test through a wearable device (e.g., watch, bracelet, etc.) worn by the user. The reminding mode can be vibration reminding, voice reminding, barrage character reminding and combination of a plurality of reminding modes, and the application is not limited to the above.

According to the embodiment of the application, the reminding module can remind the user of the movement when the effective movement data of the user are not detected for a long time, so that the movement frequency of the user can be improved to a certain extent, and the use experience of the user can be improved.

With reference to the second aspect, in a possible implementation manner, the apparatus further includes: and the information synchronization module is used for realizing information synchronization between the mobile phone and the wearable equipment when the mobile phone of the user and the wearable equipment are connected.

According to the embodiment of the application, the information synchronization between the mobile phone and the wearable device can be realized through the information synchronization module, so that the measurement record at the wearable device side can be synchronized to the mobile phone, the measurement record can be stored for a long time, and a user can observe the change (improvement or deterioration) of the self-movement capability through looking up the history record, so that the use experience of the user is further improved.

With reference to the second aspect, in one possible implementation manner, the reminding module is further configured to: when the walking track of the user is detected to deviate from the straight line, the user is reminded to walk along the straight line.

Optionally, the reminding module may remind the user to walk along a straight line through a terminal device (such as a mobile phone) carried by the user; the user can be reminded to walk along the straight line through a wearing device (such as a watch, a bracelet and the like) worn by the user. The reminding mode can be vibration reminding, voice reminding, barrage character reminding and combination of a plurality of reminding modes, and the application is not limited to the above.

In the embodiment of the application, when the movement track of the user is detected to deviate from the straight line and possibly influence the accuracy of the final test result, the reminding module reminds the user to move along the straight line as much as possible, so that the accuracy of the test result can be improved to a certain extent.

With reference to the second aspect, in a possible implementation manner, the apparatus further includes: and the result presentation module is used for displaying a six-minute walking test report on a display screen of a mobile phone or a wearable device of the user when the six-minute walking test is finished.

With reference to the second aspect, in one possible implementation manner, the reminding module is further configured to: and reminding the user whether to start the six-minute walking test or not when detecting that the current movement of the user meets the condition of the six-minute walking test.

Optionally, the reminding module may remind the user whether to start the six-minute walk test through a terminal device (such as a mobile phone) carried by the user; it may also be to alert the user whether to turn on a six-minute walk test by means of a wearable device (e.g., watch, bracelet, etc.) worn by the user. The reminding mode can be vibration reminding, voice reminding, barrage character reminding and combination of a plurality of reminding modes, and the application is not limited to the above.

According to the embodiment of the application, the reminding module can remind the user whether to start the test when detecting that the user meets the 6-minute walking test condition, so that the movement frequency of the user can be improved to a certain extent, and the use experience of the user can be improved.

In a third aspect, there is provided a method of determining walking distance, the method comprising: acquiring first motion data in a first motion period; acquiring a first motion type in the first motion period; determining a first distance measurement value corresponding to the first movement period according to the first movement data and the first movement type; determining a first distance compensation value according to the first motion type and the motion intensity in the first motion period; and determining the walking distance corresponding to the first movement period according to the first distance measurement value and the first distance compensation value.

Optionally, the exercise data includes one or more of step frequency, gait, speed, distance, and other exercise related data, which is not limited in this regard.

Optionally, the exercise type may include one or more of walking, running, riding, climbing stairs, swimming, and other exercise-related types, which the present application is not limited to.

Alternatively, the distance determining method is applied to a 6-minute walk test, and if Q (Q is greater than or equal to 1 and Q is not equal to 6) is present in the future, the distance determining method may also be applied to a Q-minute walk test.

According to the embodiment of the application, the walking distance can be actively and noninductively measured when the test condition is met, the frequency of measurement can be improved, and the health level of the user can be better monitored; the walking measurement result of the user (the measurement result is compensated according to the exercise intensity and the exercise type) can be obtained by comprehensively analyzing and calculating the exercise intensity and the exercise type of the user, the accuracy of the measurement result can be improved, and the method supports the test under different exercise types, has wide application scenes, and can improve the use experience of the user.

With reference to the third aspect, in one possible implementation manner, the method further includes: acquiring the first motion data and first physiological data during the first motion period; determining the first motion type from the first motion data; and determining the exercise intensity corresponding to the first exercise period according to the first exercise type and the first physiological data.

Optionally, the physiological data includes one or more of heart rate, blood oxygen and blood pressure, and in addition, the physiological data may also include other data related to physiology, which is not limited in this application.

With reference to the third aspect, in a possible implementation manner, determining, according to the first exercise type and the first physiological data, an exercise intensity corresponding to the first exercise period includes: determining a maximum heart rate of the user according to the basic information of the user; correcting the maximum heart rate according to resting physiological data of the user; determining a motion intensity judgment threshold according to the first motion type and the corrected maximum heart rate; the exercise intensity is determined based on the first physiological data and the exercise intensity determination threshold.

With reference to the third aspect, in one possible implementation manner, determining a walking distance corresponding to the first exercise period according to the first distance measurement value and the first distance compensation value includes: and obtaining the walking distance corresponding to the first exercise period by summing the first distance measurement value and the first distance compensation value.

Alternatively, the coefficient of the first distance measurement value is denoted as a, the coefficient of the first distance compensation value is denoted as b, or the product of the first distance measurement value and the coefficient a and the product of the first distance compensation value and the coefficient b may be calculated respectively, and then the two products are summed to obtain the walking distance corresponding to the first exercise period.

With reference to the third aspect, in one possible implementation manner, the method further includes: acquiring N walking distances of a user, wherein the N walking distances are in one-to-one correspondence with N movement periods of the user, and the N walking distances comprise walking distances corresponding to the first movement periods; and determining the walking distance output value of the user according to the N walking distances and the resting physiological data of the user, wherein the resting physiological data of the user is physiological data of the user in a non-motion state.

Wherein, the one-to-one correspondence of the N walking distances and the N movement periods of the user means that: each exercise process of the user obtains a walking distance of the user (the obtained method is as described in the first aspect), and then the N exercise periods of the user obtain N walking distances of the user, so the N walking distances are in one-to-one correspondence with the N exercise periods of the user.

The walking distance output value of the user refers to the walking distance measurement result finally displayed to the user. Optionally, the walking distance output value may be displayed to the user in a chart manner, may be displayed to the user in a data manner, may be transmitted to the user in a voice broadcast manner, or may be combined in a plurality of display manners, which is not limited in the present application.

In the embodiment of the application, the integrated analysis is carried out on a plurality of walking distances corresponding to a plurality of movement periods of the user, and the result after the integrated analysis is corrected according to the rest physiological parameters of the user, so that the accuracy of the walking distance output value can be further improved.

With reference to the third aspect, in one possible implementation manner, determining a walking distance output value of the user according to the N walking distances and resting physiological data of the user includes: determining the crowd of the user according to the resting physiological data of the user; determining walking distance distribution conditions corresponding to the user according to the crowd to which the user belongs; respectively calculating weight values of the N walking distances according to the N walking distances and walking distance distribution conditions corresponding to the user; and determining the walking distance output value of the user according to the N walking distances and the weight values of the N walking distances.

In one example, the 4 six-minute walking distances of the user are a1, a2, a3, a4, respectively, and the integration weights of the 4 six-minute walking distances of the user are b1, b2, b3, b4, respectively, then the six-minute walking distance output value of the user is:/>

With reference to the third aspect, in one possible implementation manner, the method further includes: and prompting the user to start a six-minute walk test when the effective exercise data of the user are not detected for M consecutive days.

With reference to the third aspect, in one possible implementation manner, the method further includes: when a user actively initiates a six-minute walk test through a mobile phone, if the mobile phone of the user is connected with the wearable device, the six-minute walk test is performed on the wearable device side; if the mobile phone of the user is not connected with the wearable device, six-minute walking test is performed on the mobile phone side.

With reference to the third aspect, in one possible implementation manner, the method further includes: when the user actively initiates a six-minute walk test through the wearable device, performing the six-minute walk test on the wearable device side; if the wearable device is connected with the mobile phone of the user, after the six-minute walk test is completed, the six-minute walk test result is synchronized to the mobile phone.

With reference to the third aspect, in one possible implementation manner, the method further includes: and reminding the user of walking along the straight line when detecting that the walking track of the user deviates from the straight line.

With reference to the third aspect, in one possible implementation manner, the method further includes: and when the six-minute walk test is finished, displaying a six-minute walk test report on a display screen of the mobile phone or the wearable device of the user.

With reference to the third aspect, in one possible implementation manner, the method further includes: and reminding the user whether to start the six-minute walking test or not when detecting that the current movement of the user meets the condition of the six-minute walking test.

In a fourth aspect, an electronic device is provided, the electronic device comprising a memory for storing computer program code and a processor for executing the computer program code stored in the memory to implement the method of the first aspect or any one of the possible implementations of the first aspect.

In a fifth aspect, there is provided a chip having instructions stored therein which, when run on a device, cause the chip to perform the method of the first aspect or any one of the possible implementations of the first aspect.

In a sixth aspect, a computer readable storage medium is provided, in which a computer program or instructions is stored which, when executed, implement the method of the first aspect or any one of the possible implementations of the first aspect.

In a seventh aspect, a computer program product is provided which, when run on an electronic device, causes the electronic device to perform the method of the first aspect or any of the possible implementations of the first aspect.

Drawings

Fig. 1 is a schematic structural diagram of an electronic device according to an embodiment of the present application;

FIG. 2 is a block diagram of a software architecture of an electronic device according to an embodiment of the present application;

FIG. 3 is a six minute walk test method;

FIG. 4 is yet another six minute walk test method;

FIG. 5 is a schematic flow chart of a method of six-minute walk testing provided by an embodiment of the present application;

FIG. 6 is a schematic flow chart of yet another method of six-minute walk testing provided by an embodiment of the present application;

FIG. 7 is a schematic flow chart diagram of a method for determining the exercise intensity of a user provided by an embodiment of the present application;

FIG. 8 is a schematic flow chart of a method for determining a six-minute walking distance output value according to an embodiment of the present application;

FIG. 9 is a diagram of a display interface corresponding to a six-minute walking distance output value of a user according to an embodiment of the present application;

FIG. 10 is a schematic diagram of an interface for reminding a user to perform a six-minute walking distance test according to an embodiment of the present application;

FIG. 11 is a schematic flow chart of yet another six-minute walk distance test method provided by an embodiment of the present application;

FIG. 12 is a schematic flow chart of yet another six-minute walk distance test method provided by an embodiment of the present application;

FIG. 13 is a schematic flow chart of another six-minute walk distance test method provided by an embodiment of the present application;

FIG. 14 is a schematic flow chart of yet another six-minute walk distance test method provided by an embodiment of the present application;

FIG. 15 is a schematic flow chart of a method for intelligently reminding to start 6-minute walk test provided by an embodiment of the application;

fig. 16 is a schematic diagram of a start page corresponding to a 6-minute walk test process performed on a wearable device side according to an embodiment of the present application;

Fig. 17 is a schematic diagram of an interface display of a start test failure or a test termination caused by failing to meet a test condition corresponding to a 6-minute walk test process performed on a wearable device side according to an embodiment of the present application;

fig. 18 is a schematic diagram of interface display when a walking track of a user is detected to deviate from a straight line in a 6-minute walking test process performed on a wearable device side according to an embodiment of the present application;

Fig. 19 is an interface display schematic diagram of a whole-minute reminder corresponding to a 6-minute walk test process performed on a wearable device side according to an embodiment of the present application;

fig. 20 is a schematic diagram of an interface display of a whole minute reminder corresponding to a 6-minute walk test process performed on a wearable device side according to another embodiment of the present application;

Fig. 21 is a schematic diagram of interface display at the end of a test corresponding to a 6-minute walk test procedure performed on a wearable device side according to an embodiment of the present application;

FIG. 22 is a schematic diagram of an interface display for intelligently reminding a user to start a 6-minute walk test according to an embodiment of the present application;

FIG. 23 is a schematic flow chart of yet another six-minute walk distance test method provided by an embodiment of the present application;

Fig. 24 is a schematic diagram of a start page corresponding to a 6-minute walk test process performed on a mobile phone side according to an embodiment of the present application;

fig. 25 is a schematic diagram of an interface display of a whole minute reminder corresponding to a 6-minute walk test process performed on a mobile phone side according to an embodiment of the present application;

fig. 26 is a schematic diagram showing an interface at the end of a test corresponding to a 6-minute walk test procedure performed on a mobile phone side according to an embodiment of the present application;

Fig. 27 is a schematic diagram of an interface display when a user walking track deviation from a straight line is detected corresponding to a 6-minute walking test process performed on a mobile phone side according to an embodiment of the present application;

FIG. 28 is a diagram showing a 6-minute walk test results interface provided by an embodiment of the present application;

FIG. 29 is a diagram showing an interactive interface for 6-minute walk test results provided by an embodiment of the present application;

FIG. 30 is a schematic diagram of functional modules of a six-minute walk test apparatus according to an embodiment of the present application;

fig. 31 is a schematic functional block diagram of another six-minute walk test apparatus according to an embodiment of the present application.

Detailed Description

The technical scheme of the application will be described below with reference to the accompanying drawings. It will be apparent that the described embodiments are only some, but not all, embodiments of the application.

The technical solutions in the embodiments of the present application will be described below with reference to the accompanying drawings in the embodiments of the present application. Wherein, in the description of the embodiments of the present application, unless otherwise indicated, "/" means or, for example, a/B may represent a or B; "and/or" herein is merely an association relationship describing an association object, and means that three relationships may exist, for example, a and/or B may mean: a exists alone, A and B exist together, and B exists alone. In addition, in the description of the embodiments of the present application, "plural" or "plurality" means two or more than two.

The terms "first" and "second" are used below for descriptive purposes only and are not to be construed as indicating or implying relative importance or implicitly indicating the number of technical features indicated. Thus, a feature defining "a first" or "a second" may explicitly or implicitly include one or more such feature. In the description of the present embodiment, unless otherwise specified, the meaning of "plurality" is two or more.

The method provided by the embodiment of the application can be applied to electronic equipment such as mobile phones, tablet computers, wearable equipment, vehicle-mounted equipment, augmented reality (augmented reality, AR)/Virtual Reality (VR) equipment, notebook computers, ultra-mobile personal computer (UMPC), netbooks, personal digital assistants (personal DIGITAL ASSISTANT, PDA) and the like, and the embodiment of the application does not limit the specific type of the electronic equipment.

By way of example, fig. 1 shows a schematic diagram of an electronic device 100. The electronic device 100 may include a processor 110, an external memory interface 120, an internal memory 121, a universal serial bus (universal serial bus, USB) interface 130, a charge management module 140, a power management module 141, a battery 142, an antenna 1, an antenna 2, a mobile communication module 150, a wireless communication module 160, an audio module 170, a speaker 170A, a receiver 170B, a microphone 170C, an ear-piece interface 170D, a sensor module 180, keys 190, a motor 191, an indicator 192, a camera 193, a display 194, and a user identification (subscriber identification module, SIM) card interface 195, etc. The sensor module 180 may include a pressure sensor 180A, a gyro sensor 180B, an air pressure sensor 180C, a magnetic sensor 180D, an acceleration sensor 180E, a distance sensor 180F, a proximity sensor 180G, a fingerprint sensor 180H, a temperature sensor 180J, a touch sensor 180K, an ambient light sensor 180L, a bone conduction sensor 180M, and the like.

It should be understood that the illustrated structure of the embodiment of the present application does not constitute a specific limitation on the electronic device 100. In other embodiments of the application, electronic device 100 may include more or fewer components than shown, or certain components may be combined, or certain components may be split, or different arrangements of components. The illustrated components may be implemented in hardware, software, or a combination of software and hardware.

The processor 110 may include one or more processing units, such as: the processor 110 may include an application processor (application processor, AP), a modem processor, a graphics processor (graphics processing unit, GPU), an image signal processor (IMAGE SIGNAL processor, ISP), a controller, a memory, a video codec, a digital signal processor (DIGITAL SIGNAL processor, DSP), a baseband processor, and/or a neural Network Processor (NPU), etc. Wherein the different processing units may be separate devices or may be integrated in one or more processors.

The controller may be a neural hub and a command center of the electronic device 100, among others. The controller can generate operation control signals according to the instruction operation codes and the time sequence signals to finish the control of instruction fetching and instruction execution.

A memory may also be provided in the processor 110 for storing instructions and data. In some embodiments, the memory in the processor 110 is a cache memory. The memory may hold instructions or data that the processor 110 has just used or recycled. If the processor 110 needs to reuse the instruction or data, it can be called directly from the memory. Repeated accesses are avoided and the latency of the processor 110 is reduced, thereby improving the efficiency of the system.

In some embodiments, the processor 110 may include one or more interfaces. The interfaces may include an integrated circuit (inter-INTEGRATED CIRCUIT, I2C) interface, an integrated circuit built-in audio (inter-INTEGRATED CIRCUIT SOUND, I2S) interface, a pulse code modulation (pulse code modulation, PCM) interface, a universal asynchronous receiver transmitter (universal asynchronous receiver/transmitter, UART) interface, a mobile industry processor interface (mobile industry processor interface, MIPI), a general-purpose input/output (GPIO) interface, a subscriber identity module (subscriber identity module, SIM) interface, and/or a universal serial bus (universal serial bus, USB) interface, among others.

The I2C interface is a bi-directional synchronous serial bus comprising a serial data line (SERIAL DATA LINE, SDA) and a serial clock line (derail clock line, SCL). In some embodiments, the processor 110 may contain multiple sets of I2C buses. The processor 110 may be coupled to the touch sensor 180K, charger, flash, camera 193, etc., respectively, through different I2C bus interfaces. For example: the processor 110 may be coupled to the touch sensor 180K through an I2C interface, such that the processor 110 communicates with the touch sensor 180K through an I2C bus interface to implement a touch function of the electronic device 100.

The I2S interface may be used for audio communication. In some embodiments, the processor 110 may contain multiple sets of I2S buses. The processor 110 may be coupled to the audio module 170 via an I2S bus to enable communication between the processor 110 and the audio module 170. In some embodiments, the audio module 170 may transmit an audio signal to the wireless communication module 160 through the I2S interface, to implement a function of answering a call through the bluetooth headset.

PCM interfaces may also be used for audio communication to sample, quantize and encode analog signals. In some embodiments, the audio module 170 and the wireless communication module 160 may be coupled through a PCM bus interface. In some embodiments, the audio module 170 may also transmit audio signals to the wireless communication module 160 through the PCM interface to implement a function of answering a call through the bluetooth headset. Both the I2S interface and the PCM interface may be used for audio communication.

The UART interface is a universal serial data bus for asynchronous communications. The bus may be a bi-directional communication bus. It converts the data to be transmitted between serial communication and parallel communication. In some embodiments, a UART interface is typically used to connect the processor 110 with the wireless communication module 160. For example: the processor 110 communicates with a bluetooth module in the wireless communication module 160 through a UART interface to implement a bluetooth function. In some embodiments, the audio module 170 may transmit an audio signal to the wireless communication module 160 through a UART interface, to implement a function of playing music through a bluetooth headset.

The MIPI interface may be used to connect the processor 110 to peripheral devices such as a display 194, a camera 193, and the like. The MIPI interfaces include camera serial interfaces (CAMERA SERIAL INTERFACE, CSI), display serial interfaces (DISPLAY SERIAL INTERFACE, DSI), and the like. In some embodiments, processor 110 and camera 193 communicate through a CSI interface to implement the photographing functions of electronic device 100. The processor 110 and the display 194 communicate via a DSI interface to implement the display functionality of the electronic device 100.

The GPIO interface may be configured by software. The GPIO interface may be configured as a control signal or as a data signal. In some embodiments, a GPIO interface may be used to connect the processor 110 with the camera 193, the display 194, the wireless communication module 160, the audio module 170, the sensor module 180, and the like. The GPIO interface may also be configured as an I2C interface, an I2S interface, a UART interface, an MIPI interface, etc.

The USB interface 130 is an interface conforming to the USB standard specification, and may specifically be a Mini USB interface, a Micro USB interface, a USB Type C interface, or the like. The USB interface 130 may be used to connect a charger to charge the electronic device 100, and may also be used to transfer data between the electronic device 100 and a peripheral device. And can also be used for connecting with a headset, and playing audio through the headset. The interface may also be used to connect other electronic devices, such as AR devices, etc.

It should be understood that the interfacing relationship between the modules illustrated in the embodiments of the present application is only illustrative, and is not meant to limit the structure of the electronic device 100. In other embodiments of the present application, the electronic device 100 may also employ different interfacing manners in the above embodiments, or a combination of multiple interfacing manners.

The charge management module 140 is configured to receive a charge input from a charger. The charger can be a wireless charger or a wired charger. In some wired charging embodiments, the charge management module 140 may receive a charging input of a wired charger through the USB interface 130. In some wireless charging embodiments, the charge management module 140 may receive wireless charging input through a wireless charging coil of the electronic device 100. The charging management module 140 may also supply power to the electronic device through the power management module 141 while charging the battery 142.

The power management module 141 is used for connecting the battery 142, and the charge management module 140 and the processor 110. The power management module 141 receives input from the battery 142 and/or the charge management module 140 and provides power to the processor 110, the internal memory 121, the external memory, the display 194, the camera 193, the wireless communication module 160, and the like. The power management module 141 may also be configured to monitor battery capacity, battery cycle number, battery health (leakage, impedance) and other parameters. In other embodiments, the power management module 141 may also be provided in the processor 110. In other embodiments, the power management module 141 and the charge management module 140 may be disposed in the same device.

The wireless communication function of the electronic device 100 may be implemented by the antenna 1, the antenna 2, the mobile communication module 150, the wireless communication module 160, a modem processor, a baseband processor, and the like.

The antennas 1 and 2 are used for transmitting and receiving electromagnetic wave signals. Each antenna in the electronic device 100 may be used to cover a single or multiple communication bands. Different antennas may also be multiplexed to improve the utilization of the antennas. For example: the antenna 1 may be multiplexed into a diversity antenna of a wireless local area network. In other embodiments, the antenna may be used in conjunction with a tuning switch.

The mobile communication module 150 may provide a solution for wireless communication including 2G/3G/4G/5G, etc., applied to the electronic device 100. The mobile communication module 150 may include at least one filter, switch, power amplifier, low noise amplifier (low noise amplifier, LNA), etc. The mobile communication module 150 may receive electromagnetic waves from the antenna 1, perform processes such as filtering, amplifying, and the like on the received electromagnetic waves, and transmit the processed electromagnetic waves to the modem processor for demodulation. The mobile communication module 150 can amplify the signal modulated by the modem processor, and convert the signal into electromagnetic waves through the antenna 1 to radiate. In some embodiments, at least some of the functional modules of the mobile communication module 150 may be disposed in the processor 110. In some embodiments, at least some of the functional modules of the mobile communication module 150 may be provided in the same device as at least some of the modules of the processor 110.

The modem processor may include a modulator and a demodulator. The modulator is used for modulating the low-frequency baseband signal to be transmitted into a medium-high frequency signal. The demodulator is used for demodulating the received electromagnetic wave signal into a low-frequency baseband signal. The demodulator then transmits the demodulated low frequency baseband signal to the baseband processor for processing. The low frequency baseband signal is processed by the baseband processor and then transferred to the application processor. The application processor outputs sound signals through an audio device (not limited to the speaker 170A, the receiver 170B, etc.), or displays images or video through the display screen 194. In some embodiments, the modem processor may be a stand-alone device. In other embodiments, the modem processor may be provided in the same device as the mobile communication module 150 or other functional module, independent of the processor 110.

The wireless communication module 160 may provide solutions for wireless communication including wireless local area network (wireless local area networks, WLAN) (e.g., wireless fidelity (WIRELESS FIDELITY, wi-Fi) network), bluetooth (BT), global navigation satellite system (global navigation SATELLITE SYSTEM, GNSS), frequency modulation (frequency modulation, FM), near field communication (NEAR FIELD communication, NFC), infrared (IR), etc., applied to the electronic device 100. The wireless communication module 160 may be one or more devices that integrate at least one communication processing module. The wireless communication module 160 receives electromagnetic waves via the antenna 2, modulates the electromagnetic wave signals, filters the electromagnetic wave signals, and transmits the processed signals to the processor 110. The wireless communication module 160 may also receive a signal to be transmitted from the processor 110, frequency modulate it, amplify it, and convert it to electromagnetic waves for radiation via the antenna 2.

In some embodiments, antenna 1 and mobile communication module 150 of electronic device 100 are coupled, and antenna 2 and wireless communication module 160 are coupled, such that electronic device 100 may communicate with a network and other devices through wireless communication techniques. The wireless communication techniques can include the Global System for Mobile communications (global system for mobile communications, GSM), general packet radio service (GENERAL PACKET radio service, GPRS), code division multiple access (code division multiple access, CDMA), wideband code division multiple access (wideband code division multiple access, WCDMA), time division code division multiple access (time-division code division multiple access, TD-SCDMA), long term evolution (long term evolution, LTE), BT, GNSS, WLAN, NFC, FM, and/or IR techniques, among others. The GNSS may include a global satellite positioning system (global positioning system, GPS), a global navigation satellite system (global navigation SATELLITE SYSTEM, GLONASS), a beidou satellite navigation system (beidou navigation SATELLITE SYSTEM, BDS), a quasi zenith satellite system (quasi-zenith SATELLITE SYSTEM, QZSS) and/or a satellite based augmentation system (SATELLITE BASED AUGMENTATION SYSTEMS, SBAS).

The electronic device 100 implements display functions through a GPU, a display screen 194, an application processor, and the like. The GPU is a microprocessor for image processing, and is connected to the display 194 and the application processor. The GPU is used to perform mathematical and geometric calculations for graphics rendering. Processor 110 may include one or more GPUs that execute program instructions to generate or change display information.

The display screen 194 is used to display images, videos, and the like. The display 194 includes a display panel. The display panel may employ a Liquid Crystal Display (LCD) CRYSTAL DISPLAY, an organic light-emitting diode (OLED), an active-matrix organic LIGHT EMITTING diode (AMOLED), a flexible light-emitting diode (FLED), miniled, microLed, micro-oLed, a quantum dot LIGHT EMITTING diode (QLED), or the like. In some embodiments, the electronic device 100 may include 1 or N display screens 194, N being a positive integer greater than 1.

The electronic device 100 may implement photographing functions through an ISP, a camera 193, a video codec, a GPU, a display screen 194, an application processor, and the like.

The ISP is used to process data fed back by the camera 193. For example, when photographing, the shutter is opened, light is transmitted to the camera photosensitive element through the lens, the optical signal is converted into an electric signal, and the camera photosensitive element transmits the electric signal to the ISP for processing and is converted into an image visible to naked eyes. ISP can also optimize the noise, brightness and skin color of the image. The ISP can also optimize parameters such as exposure, color temperature and the like of a shooting scene. In some embodiments, the ISP may be provided in the camera 193.

The camera 193 is used to capture still images or video. The object generates an optical image through the lens and projects the optical image onto the photosensitive element. The photosensitive element may be a charge coupled device (charge coupled device, CCD) or a Complementary Metal Oxide Semiconductor (CMOS) phototransistor. The photosensitive element converts the optical signal into an electrical signal, which is then transferred to the ISP to be converted into a digital image signal. The ISP outputs the digital image signal to the DSP for processing. The DSP converts the digital image signal into an image signal in a standard RGB, YUV, or the like format. In some embodiments, electronic device 100 may include 1 or N cameras 193, N being a positive integer greater than 1.

The digital signal processor is used for processing digital signals, and can process other digital signals besides digital image signals. For example, when the electronic device 100 selects a frequency bin, the digital signal processor is used to fourier transform the frequency bin energy, or the like.

Video codecs are used to compress or decompress digital video. The electronic device 100 may support one or more video codecs. In this way, the electronic device 100 may play or record video in a variety of encoding formats, such as: dynamic picture experts group (moving picture experts group, MPEG) 1, MPEG2, MPEG3, MPEG4, etc.

The NPU is a neural-network (NN) computing processor, and can rapidly process input information by referencing a biological neural network structure, for example, referencing a transmission mode between human brain neurons, and can also continuously perform self-learning. Applications such as intelligent awareness of the electronic device 100 may be implemented through the NPU, for example: image recognition, face recognition, speech recognition, text understanding, etc.

The external memory interface 120 may be used to connect an external memory card, such as a Micro SD card, to enable expansion of the memory capabilities of the electronic device 100. The external memory card communicates with the processor 110 through an external memory interface 120 to implement data storage functions. For example, files such as music, video, etc. are stored in an external memory card.

The internal memory 121 may be used to store computer executable program code including instructions. The processor 110 executes various functional applications of the electronic device 100 and data processing by executing instructions stored in the internal memory 121. The internal memory 121 may include a storage program area and a storage data area. The storage program area may store an App (such as a sound playing function, an image playing function, etc.) and the like required for at least one function of the operating system. The storage data area may store data created during use of the electronic device 100 (e.g., audio data, phonebook, etc.), and so on. In addition, the internal memory 121 may include a high-speed random access memory, and may further include a nonvolatile memory such as at least one magnetic disk storage device, a flash memory device, a universal flash memory (universal flash storage, UFS), and the like.

The electronic device 100 may implement audio functions through an audio module 170, a speaker 170A, a receiver 170B, a microphone 170C, an earphone interface 170D, an application processor, and the like. Such as music playing, recording, etc.

The audio module 170 is used to convert digital audio information into an analog audio signal output and also to convert an analog audio input into a digital audio signal. The audio module 170 may also be used to encode and decode audio signals. In some embodiments, the audio module 170 may be disposed in the processor 110, or a portion of the functional modules of the audio module 170 may be disposed in the processor 110.

The speaker 170A, also referred to as a "horn," is used to convert audio electrical signals into sound signals. The electronic device 100 may listen to music, or to hands-free conversations, through the speaker 170A.

A receiver 170B, also referred to as a "earpiece", is used to convert the audio electrical signal into a sound signal. When electronic device 100 is answering a telephone call or voice message, voice may be received by placing receiver 170B in close proximity to the human ear.

Microphone 170C, also referred to as a "microphone" or "microphone", is used to convert sound signals into electrical signals. When making a call or transmitting voice information, the user can sound near the microphone 170C through the mouth, inputting a sound signal to the microphone 170C. The electronic device 100 may be provided with at least one microphone 170C. In other embodiments, the electronic device 100 may be provided with two microphones 170C, and may implement a noise reduction function in addition to collecting sound signals. In other embodiments, the electronic device 100 may also be provided with three, four, or more microphones 170C to enable collection of sound signals, noise reduction, identification of sound sources, directional recording functions, etc.

The earphone interface 170D is used to connect a wired earphone. The headset interface 170D may be a USB interface 130 or a 3.5mm open mobile electronic device platform (open mobile terminal platform, OMTP) standard interface, a american cellular telecommunications industry association (cellular telecommunications industry association of the USA, CTIA) standard interface.

The pressure sensor 180A is used to sense a pressure signal, and may convert the pressure signal into an electrical signal. In some embodiments, the pressure sensor 180A may be disposed on the display screen 194. The pressure sensor 180A is of various types, such as a resistive pressure sensor, an inductive pressure sensor, a capacitive pressure sensor, and the like. The capacitive pressure sensor may be a capacitive pressure sensor comprising at least two parallel plates with conductive material. The capacitance between the electrodes changes when a force is applied to the pressure sensor 180A. The electronic device 100 determines the strength of the pressure from the change in capacitance. When a touch operation is applied to the display screen 194, the electronic apparatus 100 detects the touch operation intensity according to the pressure sensor 180A. The electronic device 100 may also calculate the location of the touch based on the detection signal of the pressure sensor 180A. In some embodiments, touch operations that act on the same touch location, but at different touch operation strengths, may correspond to different operation instructions. For example: and executing an instruction for checking the short message when the touch operation with the touch operation intensity smaller than the first pressure threshold acts on the short message application icon. And executing an instruction for newly creating the short message when the touch operation with the touch operation intensity being greater than or equal to the first pressure threshold acts on the short message application icon.

The gyro sensor 180B may be used to determine a motion gesture of the electronic device 100. In some embodiments, the angular velocity of electronic device 100 about three axes (i.e., x, y, and z axes) may be determined by gyro sensor 180B. The gyro sensor 180B may be used for photographing anti-shake. For example, when the shutter is pressed, the gyro sensor 180B detects the shake angle of the electronic device 100, calculates the distance to be compensated by the lens module according to the angle, and makes the lens counteract the shake of the electronic device 100 through the reverse motion, so as to realize anti-shake. The gyro sensor 180B may also be used for navigating, somatosensory game scenes.

The air pressure sensor 180C is used to measure air pressure. In some embodiments, electronic device 100 calculates altitude from barometric pressure values measured by barometric pressure sensor 180C, aiding in positioning and navigation.

The magnetic sensor 180D includes a hall sensor. The electronic device 100 may detect the opening and closing of the flip cover using the magnetic sensor 180D. In some embodiments, when the electronic device 100 is a flip machine, the electronic device 100 may detect the opening and closing of the flip according to the magnetic sensor 180D. And then according to the detected opening and closing state of the leather sheath or the opening and closing state of the flip, the characteristics of automatic unlocking of the flip and the like are set.

The acceleration sensor 180E may detect the magnitude of acceleration of the electronic device 100 in various directions (typically three axes). The magnitude and direction of gravity may be detected when the electronic device 100 is stationary. The electronic equipment gesture recognition method can also be used for recognizing the gesture of the electronic equipment, and is applied to horizontal and vertical screen switching, pedometers and other applications.

A distance sensor 180F for measuring a distance. The electronic device 100 may measure the distance by infrared or laser. In some embodiments, the electronic device 100 may range using the distance sensor 180F to achieve quick focus.

The proximity light sensor 180G may include, for example, a Light Emitting Diode (LED) and a light detector, such as a photodiode. The light emitting diode may be an infrared light emitting diode. The electronic device 100 emits infrared light outward through the light emitting diode. The electronic device 100 detects infrared reflected light from nearby objects using a photodiode. When sufficient reflected light is detected, it may be determined that there is an object in the vicinity of the electronic device 100. When insufficient reflected light is detected, the electronic device 100 may determine that there is no object in the vicinity of the electronic device 100. The electronic device 100 can detect that the user holds the electronic device 100 close to the ear by using the proximity light sensor 180G, so as to automatically extinguish the screen for the purpose of saving power. The proximity light sensor 180G may also be used in holster mode, pocket mode to automatically unlock and lock the screen.

The ambient light sensor 180L is used to sense ambient light level. The electronic device 100 may adaptively adjust the brightness of the display 194 based on the perceived ambient light level. The ambient light sensor 180L may also be used to automatically adjust white balance when taking a photograph. Ambient light sensor 180L may also cooperate with proximity light sensor 180G to detect whether electronic device 100 is in a pocket to prevent false touches.

The fingerprint sensor 180H is used to collect a fingerprint. The electronic device 100 may utilize the collected fingerprint feature to unlock the fingerprint, access the application lock, photograph the fingerprint, answer the incoming call, etc.

The temperature sensor 180J is for detecting temperature. In some embodiments, the electronic device 100 performs a temperature processing strategy using the temperature detected by the temperature sensor 180J. For example, when the temperature reported by temperature sensor 180J exceeds a threshold, electronic device 100 performs a reduction in the performance of a processor located in the vicinity of temperature sensor 180J in order to reduce power consumption to implement thermal protection. In other embodiments, when the temperature is below another threshold, the electronic device 100 heats the battery 142 to avoid the low temperature causing the electronic device 100 to be abnormally shut down. In other embodiments, when the temperature is below a further threshold, the electronic device 100 performs boosting of the output voltage of the battery 142 to avoid abnormal shutdown caused by low temperatures.

The touch sensor 180K, also referred to as a "touch panel". The touch sensor 180K may be disposed on the display screen 194, and the touch sensor 180K and the display screen 194 form a touch screen, which is also called a "touch screen". The touch sensor 180K is for detecting a touch operation acting thereon or thereabout. The touch sensor may communicate the detected touch operation to the application processor to determine the touch event type. Visual output related to touch operations may be provided through the display 194. In other embodiments, the touch sensor 180K may also be disposed on the surface of the electronic device 100 at a different location than the display 194.

The bone conduction sensor 180M may acquire a vibration signal. In some embodiments, bone conduction sensor 180M may acquire a vibration signal of a human vocal tract vibrating bone pieces. The bone conduction sensor 180M may also contact the pulse of the human body to receive the blood pressure pulsation signal. In some embodiments, bone conduction sensor 180M may also be provided in a headset, in combination with an osteoinductive headset. The audio module 170 may analyze the voice signal based on the vibration signal of the sound portion vibration bone block obtained by the bone conduction sensor 180M, so as to implement a voice function. The application processor may analyze the heart rate information based on the blood pressure beat signal acquired by the bone conduction sensor 180M, so as to implement a heart rate detection function.

The keys 190 include a power-on key, a volume key, etc. The keys 190 may be mechanical keys. Or may be a touch key. The electronic device 100 may receive key inputs, generating key signal inputs related to user settings and function controls of the electronic device 100.

The motor 191 may generate a vibration cue. The motor 191 may be used for incoming call vibration alerting as well as for touch vibration feedback. For example, touch operations acting on different applications (e.g., photographing, audio playing, etc.) may correspond to different vibration feedback effects. The motor 191 may also correspond to different vibration feedback effects by touching different areas of the display screen 194. Different application scenarios (such as time reminding, receiving information, alarm clock, game, etc.) can also correspond to different vibration feedback effects. The touch vibration feedback effect may also support customization.

The indicator 192 may be an indicator light, may be used to indicate a state of charge, a change in charge, a message indicating a missed call, a notification, etc.

The SIM card interface 195 is used to connect a SIM card. The SIM card may be inserted into the SIM card interface 195, or removed from the SIM card interface 195 to enable contact and separation with the electronic device 100. The electronic device 100 may support 1 or N SIM card interfaces, N being a positive integer greater than 1. The SIM card interface 195 may support Nano SIM cards, micro SIM cards, and the like. The same SIM card interface 195 may be used to insert multiple cards simultaneously. The types of the plurality of cards may be the same or different. The SIM card interface 195 may also be compatible with different types of SIM cards. The SIM card interface 195 may also be compatible with external memory cards. The electronic device 100 interacts with the network through the SIM card to realize functions such as communication and data communication. In some embodiments, the electronic device 100 employs an embedded SIM (eSIM) card, namely: an embedded SIM card. The eSIM card can be embedded in the electronic device 100 and cannot be separated from the electronic device 100.

It should be appreciated that the phone cards in embodiments of the present application include, but are not limited to, SIM cards, eSIM cards, universal subscriber identity cards (universal subscriber identity module, USIM), universal integrated phone cards (universal integrated circuit card, UICC), and the like.

The software system of the electronic device 100 may employ a layered architecture, an event driven architecture, a microkernel architecture, a microservice architecture, or a cloud architecture. In the embodiment of the application, taking an Android system with a layered architecture as an example, a software structure of the electronic device 100 is illustrated.

Fig. 2 is a software configuration block diagram of the electronic device 100 according to the embodiment of the present application. The layered architecture divides the software into several layers, each with distinct roles and branches. The layers communicate with each other through a software interface. In some embodiments, the Android system is divided into four layers, from top to bottom, an application layer, an application framework layer, an Zhuoyun rows (Android runtime) and system libraries, and a kernel layer, respectively. The application layer may include a series of application packages.

As shown in fig. 2, the application package may include applications for cameras, gallery, calendar, phone calls, maps, navigation, WLAN, bluetooth, music, video, short messages, etc.

The application framework layer provides an application programming interface (application programming interface, API) and programming framework for the application of the application layer. The application framework layer includes a number of predefined functions.

As shown in FIG. 2, the application framework layer may include a window manager, a content provider, a view system, a telephony manager, a resource manager, a notification manager, and the like.

The window manager is used for managing window programs. The window manager can acquire the size of the display screen, judge whether a status bar exists, lock the screen, intercept the screen and the like.

The content provider is used to store and retrieve data and make such data accessible to applications. The data may include video, images, audio, calls made and received, browsing history and bookmarks, phonebooks, etc.

The view system includes visual controls, such as controls to display text, controls to display pictures, and the like. The view system may be used to build applications. The display interface may be composed of one or more views. For example, a display interface including a text message notification icon may include a view displaying text and a view displaying a picture.

The telephony manager is used to provide the communication functions of the electronic device 100. Such as the management of call status (including on, hung-up, etc.).

The resource manager provides various resources for the application program, such as localization strings, icons, pictures, layout files, video files, and the like.

The notification manager allows the application to display notification information in a status bar, can be used to communicate notification type messages, can automatically disappear after a short dwell, and does not require user interaction. Such as notification manager is used to inform that the download is complete, message alerts, etc. The notification manager may also be a notification in the form of a chart or scroll bar text that appears on the system top status bar, such as a notification of a background running application, or a notification that appears on the screen in the form of a dialog window. For example, a text message is prompted in a status bar, a prompt tone is emitted, the electronic device vibrates, and an indicator light blinks, etc.

Android run time includes a core library and virtual machines. Android runtime is responsible for scheduling and management of the android system.

The core library consists of two parts: one part is a function which needs to be called by java language, and the other part is a core library of android.

The application layer and the application framework layer run in a virtual machine. The virtual machine executes java files of the application program layer and the application program framework layer as binary files. The virtual machine is used for executing the functions of object life cycle management, stack management, thread management, security and exception management, garbage collection and the like.

The system library may include a plurality of functional modules. For example: surface manager (surface manager), media library (media library), three-dimensional graphics processing library (e.g., openGL ES), 2D graphics engine (e.g., SGL), etc.

The surface manager is used to manage the display subsystem and provides a fusion of 2D and 3D layers for multiple applications.

Media libraries support a variety of commonly used audio, video format playback and recording, still image files, and the like. The media library may support a variety of audio and video encoding formats, such as MPEG4, h.264, MP3, AAC, AMR, JPG, PNG, etc.

The three-dimensional graphic processing library is used for realizing three-dimensional graphic drawing, image rendering, synthesis, layer processing and the like.

The 2D graphics engine is a drawing engine for 2D drawing.

The kernel layer is a layer between hardware and software. The inner core layer at least comprises a display driver, a camera driver, an audio driver and a sensor driver.

It should be understood that the technical scheme in the embodiment of the application can be used in Android, IOS, hong Meng and other systems.

The technical terms related to the application are described in detail below:

1. Six minute walk test (6-minute walk test,6 MWT)

The 6MWT result is an important indicator for evaluating the athletic ability of the user. The 6MWT is a distance that the patient walks at the fastest speed that the patient can withstand in 6 minutes, with the patient taking a hiking motion. Therefore, the exercise endurance of a test patient is detected, the 6MWT result can reflect the cardiopulmonary function state of the subject, and the whole body function state of the subject, such as exercise capacity, cardiopulmonary function, bone, muscle function, nutrition level and the like, can be comprehensively estimated, and is also an important content for life quality estimation; particularly useful for chronic pulmonary diseases, such as: chronic Obstructive Pulmonary Disease (COPD), bronchial asthma, pulmonary interstitial fibrosis, etc.; and cardiovascular diseases such as hypertension, coronary heart disease, cardiomyopathy, pulmonary hypertension, heart failure, etc.

The longer the walking distance, the more healthy the cardiovascular, respiratory and muscular functions, the 6MWT results may also reflect the subject's ability to perform daily activities, and the six minute walking distance may be increased by improving physical fitness and mobility.

The application scene of the embodiment of the application can be a scene that a user adopts terminal equipment or wearable equipment to perform six-minute walking test.

Currently, the six-minute walk test method commonly used in clinic is an in-hospital test. In a specific test, a straight corridor with the length of 15-30 m and the passing of few people is needed to be selected for six-minute walking experiments in a hospital, a mark is made every 3m, and the turning points at two ends can be marked by cones; the test equipment needed in the test process comprises: at least one chair (placed at one end of the test path), dyspnea meter and subjective fatigue meter, sphygmomanometer, oximeter, stopwatch, oxygen, call for help telephone, portable oxygen supplementing device, and tablet with report meter and pen; the subject needs to wear comfortable clothing before testing and avoid eating as much as possible within one hour before testing; before the experiment starts, the subject needs to rest on a chair for 5-10 minutes near the starting point, and check heart rate, blood pressure, blood oxygen and the like to finish the dyspnea scoring, and introduce the test process and notice to the subject; during the test, the subject is required to walk the longest distance as full as possible, while the tester is speaking a standard prompt phrase with a uniform speech rate and a peace of mind (e.g., prompt "do you very well, test still 5 minutes | when the test is going to 1 minute, prompt" do you very well, test already half | when the test is going to 3 minutes, prompt "please you stay in place | when the test is going to 6 minutes, prompt" please you stay in place | ") to prompt the rest of the time and encourage the subject; after the experiment is finished, heart rate, blood pressure and blood oxygen indexes of the subjects are recorded, and a dyspnea scale and a subjective fatigue scale (also a Borg subjective fatigue scoring scale) are filled in to evaluate the dyspnea and the fatigue degree of the subjects.

In the method, a subject needs to carry out a 6-minute walking test with the help of a tester (such as a professional medical staff), the blood pressure of the subject needs to be measured by a blood pressure meter before and after walking, and after the test is finished, the tester manually measures the walking distance of the subject through a measuring tool. The operation flow of the test method is complex and time-consuming; the test process depends on professional testers, and the testee cannot independently carry out walking tests after discharge and cannot independently and self-evaluate the physical state; in addition, the method needs to use professional measuring equipment and sites, and the deviation of measuring results can be caused by factors such as different sites and encouragement words, so that the popularization of six-minute walking tests in a hospital is poor, the inspection rate is low, and a large number of missed diagnosis is easy to cause.

Fig. 3 illustrates yet another six minute walk test method, as shown in fig. 3, the method 300 comprising:

s301: the user initiates a six minute walk test through the wearable device.

S302: the wearable device measures the user's walking data and physiological parameters over 6 minutes.

Wherein the walking data comprises walking distance, walking step number and the like; physiological parameters include heart rate, blood oxygen, etc.

S303: and analyzing and outputting six-minute walking test results.

The method is based on active measurement of the wearable equipment, and the testing process needs active initiation by a user, so that the equipment cannot be initiated autonomously, and the use experience of the user is poor; and the output test result does not consider factors such as the crowd to which the user belongs, and the accuracy of the test result is poor.

Fig. 4 illustrates yet another six minute walk test method, as shown in fig. 4, the method 400 comprising:

s401: historical walking data of the user is collected.

The user wears the wearable device for a long time, and the historical walking data of the user is automatically calculated in the background through sensors such as an accelerometer, a gyroscope and a GPS.

The walking data includes the number of walking steps, walking distance, walking speed, and the like.

S402: and measuring and calculating and outputting the six-minute walking maximum distance of the user according to the historical walking data of the user.

The method is based on the non-sensing measurement of the wearable equipment, only evaluates according to the existing walking data, does not consider physiological parameters of the user in the process, and also does not consider the possible influence of the exercise intensity and exercise type of the user on the test result, so that the accuracy of the finally obtained test result is low; in addition, the method cannot realize active initiation of measurement, and the estimated walking distance is inaccurate.

Therefore, the existing six-minute walking test method has the problems that the accuracy of test results is low and the use experience of users is affected.

In view of this, the embodiment of the application provides a walking test method, in which a device can actively initiate a walking test when a test condition is satisfied, and can calculate a walking test result of a user by combining with comprehensive analysis of the exercise intensity, exercise type, crowd to which the user belongs, and the like of the user, so that the frequency of the test can be improved, the monitoring of the health level of the user can be better realized, the accuracy of the test result can be improved, and the use experience of the user can be further improved.

The terminology used in the following examples is for the purpose of describing particular embodiments only and is not intended to be limiting of the application. As used in the specification of the application and the appended claims, the singular forms "a," "an," "the," and "the" are intended to include, for example, "one or more" such forms of expression, unless the context clearly indicates to the contrary. It should also be understood that in the following embodiments of the present application, "at least one", "one or more" means one, two or more than two. The term "and/or" is used to describe an association relationship of associated objects, meaning that there may be three relationships; for example, a and/or B may represent: a alone, a and B together, and B alone, wherein A, B may be singular or plural. The character "/" generally indicates that the context-dependent object is an "or" relationship.

Reference in the specification to "one embodiment" or "some embodiments" or the like means that a particular feature, structure, or characteristic described in connection with the embodiment is included in one or more embodiments of the application. Thus, appearances of the phrases "one embodiment," "some embodiments," "another embodiment," "other embodiments," and the like in the specification are not necessarily all referring to the same embodiment, but mean "one or more, but not all, embodiments" unless expressly specified otherwise. The terms "comprising," "including," "having," and variations thereof mean "including but not limited to," unless expressly specified otherwise.

Note that: while the six-minute walk test is taken as an example in the embodiment of the present application, this does not limit the scope of the present application in any way, and if Q (Q is 1 or more and Q is not 6) minute walk test occurs in the future, the walk test may be Q minute walk test. For example: if an eight minute walk test is used to assess the health status of a person in the future, then the eight minute walk test related methods and apparatus are also within the scope of the present application.

Illustratively, FIG. 5 shows a schematic flow chart of a method 500 for six-minute walk testing provided by an embodiment of the present application. As shown in fig. 5, the method 500 includes:

S501: motion data and physiological data of a user are collected during a first motion of the user.

The first movement process takes the state that the user is detected to be in movement as a starting point, and takes the state that the user is detected to be in movement as an ending point. It can be understood that: since the user's motion state and non-motion state are alternately present, the user may have a plurality of motion processes.

Additionally, optionally, the motion data corresponding to different motion types may differ, for example: when the exercise type is walking, the corresponding exercise data may be walking distance, number of steps, pace, calories, etc.; when the sport type is swimming, the corresponding sport data may be swimming distance, calories, etc.; when the movement type is stair climbing, the corresponding movement data may be climbing height, speed, calories, etc.; when the sport type is riding, the corresponding sport data may be riding distance, speed, calories, and the like.

Optionally, the physiological data of the user includes resting physiological data and exercise physiological data, wherein the resting physiological data refers to physiological data when the user is in a non-exercise state, and the exercise physiological data refers to physiological data when the user is in an exercise state.

Optionally, the physiological parameters of the user (e.g. one minute physiological parameters are recorded every ten minutes) are periodically recorded by a photoplethysmogram (PPG) sensor, while the user motion data is monitored in real time based on an acceleration (accelerometer, ACC) sensor, a gyroscope or a global positioning system (global positioning system, GPS) sensor, etc., and when the current user is determined to be in motion state (a first motion process is started) according to the motion data, the physiological data and the motion data of the user are started to be monitored and collected in real time, and the real-time monitoring and collecting process is continued until the first motion process is ended.

S502: and determining the motion type of the user according to the motion data of the user in the first motion process.

Wherein optionally the type of movement of the user comprises one or more of walking, running, riding, stair climbing, swimming, and further the type of movement of the user may comprise other types related to movement, without limitation of the application.

It should be understood that: step S501 and step S502 are optional steps.

S503: and determining a six-minute walking distance predicted value corresponding to the first movement process according to the movement type and the movement data of the user.

Specifically, the distance prediction methods (also called distance prediction sub-modules) corresponding to different motion types are different, and it is first required to determine the distance prediction method corresponding to the first motion process according to the motion type (also called distance prediction sub-module corresponding to the first motion process), and then further determine the six-minute walking distance prediction value corresponding to the first motion process according to the distance prediction method corresponding to the first motion process (or the distance prediction sub-module corresponding to the first motion process) and the motion data.

It should be understood that: the algorithm converts the 6-minute walking distance according to the motion data, and the method for converting the motion data corresponding to different motion types into the 6-minute walking distance is different, but the 6-minute walking distance obtained by the motion data corresponding to different motion types is consistent for the same user, because the 6-minute walking distance reflects the motion capability of the same user, and the motion capability of the user is consistent when the user performs different types of motions.

S504: the exercise intensity of the user is determined according to the exercise type of the user and the physiological data of the user.

Specifically, the exercise intensity judgment thresholds corresponding to different exercise types are different, firstly, the exercise intensity judgment threshold corresponding to the first exercise process (also referred to as the exercise type) is required to be determined according to the exercise type of the user, and then physiological data of the user is compared with the exercise intensity judgment threshold, so that the exercise intensity of the user is determined.

Wherein the exercise intensity judgment threshold value comprises a first threshold value and a second threshold value, and when the physiological data of the user is smaller than the first threshold value, the exercise intensity of the user is determined to be low (the exercise intensity can also be described as the first intensity); when the physiological data of the user is greater than or equal to a first threshold value and less than a second threshold value, determining that the exercise intensity of the user is medium intensity (which can also be described as second intensity); when the physiological data of the user is greater than or equal to the second threshold, the intensity of the motion of the user is determined to be high intensity (which may also be described as a third intensity).

Alternatively, the intensity of the movement of the user may be a continuous value between 0 and 100%, for example, a heart rate, and the current intensity of movement may be considered to be 80% when the current heart rate reaches 80% of the maximum heart rate (for example: 220-the age of the user).

Optionally, in this step, the physiological data of the user includes resting physiological data of the user and exercise physiological data corresponding to the first exercise session.

Alternatively, the intensity of movement is related to the person's sense of movement and may be described by an index such as subjective feeling or heart rate. Subjective experiences include rapid breathing, shortness of breath, sweating, speaking a few words, and the like, which require stopping breathing. Heart rate dividing exercise intensity may be determined by whether the exercise has reached a certain proportion of the maximum heart rate.

It should be understood that: step S504 is an optional step.

S505: and determining the compensation distance according to the motion intensity and the motion type of the user.

It should be understood that: under the condition that the motion types are the same, the compensation values corresponding to different motion intensities are different. Specifically, it can be understood that: the low intensity motion compensation value is relatively large and the high intensity compensation value is relatively small.

S506: and determining the first six-minute walking distance of the user according to the six-minute walking distance predicted value and the compensation distance corresponding to the first movement process.

Specifically, the compensation distance is added to the predicted six-minute walking distance value corresponding to the first exercise process, so as to obtain the first six-minute walking distance of the user.

In the embodiment of the application, the equipment can actively initiate six-minute walking test without sense when the test condition is met, and the test frequency can be improved so as to better realize the monitoring of the health level of the user; the method can be used for comprehensively analyzing and calculating the walking six-minute test result of the user by combining the exercise intensity and the exercise type of the user (compensating the test result according to the exercise intensity and the exercise type), and can improve the accuracy of the test result.

In connection with the embodiment of fig. 5, fig. 6 illustratively shows a schematic flow chart of a method 600 of a further six-minute walk test provided by an embodiment of the present application. As shown in fig. 6, the method 600 includes:

S601: the N six-minute walking distances of the user are integrated, and the N six-minute walking distances are in one-to-one correspondence with the N exercise processes of the user.

Wherein the N six minute walking distances of the user include a first six minute walking distance of the user.

The explanation of the first six-minute walking distance of the user and the acquisition method are described in detail in the embodiment shown in fig. 5, and are not repeated here for brevity.

In addition, explanation and acquisition methods of each of the N six-minute walking distances of the user are the same as those of the first six-minute walking distance, and are not described here again for brevity.

S602: and determining the six-minute walking distance output value of the user according to the N six-minute walking distances and the resting physiological data of the user.

In the embodiment of the application, the integrated analysis is carried out on a plurality of six-minute walking distances corresponding to a plurality of movement processes of the user, and the result after the integrated analysis is corrected according to the rest physiological parameters of the user, so that the accuracy of the six-minute walking distance output value can be further improved.

To more clearly understand the process of determining the exercise intensity, fig. 7 is an exemplary flowchart illustrating a method 700 for determining the exercise intensity of a user according to an embodiment of the present application. As shown in fig. 7, the method 700 includes:

s701: the maximum heart rate of the user is determined according to the basic information of the user.

Optionally, the maximum heart rate of the user = 220-the age of the user.

S702: the maximum heart rate is corrected based on the resting physiological data of the user.

Since the physical states of the users of the same age are also different, the maximum heart rate of the user obtained in step S701 needs to be corrected according to the resting physiological parameters of the user over a period of time.

S703: and determining a motion intensity judgment threshold according to the motion type of the user and the corrected maximum heart rate.

Specifically, the exercise intensity judgment thresholds corresponding to different exercise types are different, and the exercise intensity judgment threshold corresponding to the first exercise process (also referred to as the exercise type) is firstly determined according to the exercise type of the user, so that the exercise physiological data of the user is conveniently compared with the exercise intensity judgment threshold, and the exercise intensity of the user is determined.

The motion strength judging threshold value comprises a first threshold value and a second threshold value.

Optionally, when the exercise type of the user is running, the first threshold is heart rate=60, and the second threshold is heart rate=80; when the movement type of the user is swimming, the first threshold is heart rate=70, and the second threshold is heart rate=90; furthermore, it should be understood that: the values of the first threshold and the second threshold are not absolute and can be adjusted according to actual conditions.

S704: and determining the exercise intensity of the user according to the exercise intensity judging threshold and the exercise physiological data of the user.

Specifically, the exercise physiological data of the user is compared with an exercise intensity judgment threshold value, so that the exercise intensity of the user is determined.

Optionally, when the exercise type of the user is running, if the exercise heart rate of the user is less than 60, determining the exercise intensity of the user to be low intensity (which may also be described as a first intensity); if the exercise physiological data of the user is greater than or equal to 60 and less than 80, determining the exercise intensity of the user as a medium intensity (which can also be described as a second intensity); if the user's motor physiological data is greater than or equal to 80, the user's motor intensity is determined to be high (which may also be described as a third intensity).

Optionally, when the exercise type of the user is swimming, if the exercise heart rate of the user is less than 70, determining the exercise intensity of the user to be low intensity (which may also be described as a first intensity); if the exercise physiological data of the user is greater than or equal to 70 and less than 90, determining the exercise intensity of the user as a medium intensity (which can also be described as a second intensity); if the user's motor physiological data is greater than or equal to 90, the user's motor intensity is determined to be high (which may also be described as a third intensity).

According to the embodiment of the application, the exercise intensity of the user can be comprehensively determined according to the basic information, exercise type, exercise data and physiological data of the user, and different exercise intensity judgment thresholds are established for different exercise types in the process, so that the determined exercise intensity has higher credibility, and further, the six-minute walking distance output value obtained after the six-minute distance predicted value is compensated according to the exercise intensity is more accurate.

To more clearly understand the determination process of the six-minute walking distance output value, fig. 8 is an exemplary flowchart illustrating a method 800 for determining the six-minute walking distance output value according to an embodiment of the present application. As shown in fig. 8, the method 800 includes:

s801: and determining the crowd to which the user belongs according to the resting physiological data of the user.

The explanation of the resting physiological data of the user has been described in detail in the embodiment shown in fig. 5, and is not described herein for brevity.

S802: and determining six-minute walking distance distribution conditions corresponding to the user according to the crowd to which the user belongs.

Optionally, the characterization parameters of the six-minute walking distance distribution condition corresponding to the crowd to which the user belongs are mean and variance.

S803: and respectively calculating the weight values of the N six-minute walking distances of the user according to the N six-minute walking distances of the user and the six-minute walking distance distribution situation corresponding to the user.

In one example, the user is determined to be middle-aged and elderly people according to resting physiological data of the user in a period of time, the six-minute walking distance distribution condition of the middle-aged and elderly people is further obtained to be a mean value m meters, a variance sigma meters, and a gaussian function can be constructed according to the mean value and the variance:

S804: and determining six-minute walking distance output values according to the N six-minute walking distances and the weight values of the user.

According to the embodiment of the application, the prediction result weight deviating from the baseline of the crowd can be reduced by dividing the crowd and calculating the integrated weight, so that the prediction accuracy is improved; according to the method, the influence caused by a plurality of single six-minute walking distances of the user and different crowds to which the user belongs is considered, so that abnormal data can be effectively filtered, and the accuracy of a prediction result is improved.

Fig. 9 is a diagram illustrating a display interface corresponding to a six-minute walking distance output value of a user according to an embodiment of the present application.

As shown in fig. 9, a line graph of the six-minute walking distance prediction result (i.e., the six-minute walking distance output value described in the embodiment shown in fig. 5 to 8) of the user over a period of time is displayed on the display screen of the apparatus. According to the line graph, a user can intuitively know the current prediction result and the comparison condition between the current prediction result and the previous prediction result; meanwhile, historical motion data of the user is displayed below a display screen of the device, each piece of historical motion data comprises motion time, motion type (such as fast walking and running) of the user, various motion data (such as walking distance/running distance, walking speed/running speed, motion heart rate and the like) and a six-minute walking distance prediction result of the user, and the user can view the historical motion data; in addition, the user may actively delete a piece of historical motion data if the piece of historical motion data is perceived as inaccurate or if the piece of historical motion data is not desired to be displayed.

Optionally, the device may refer to a terminal device such as a mobile phone, or may refer to a wearable device such as a watch or a bracelet.

It should be understood that: fig. 9 is a schematic diagram of an interface display of six-minute walking distance output values according to an embodiment of the present application, and the display interface may also have multiple forms, which is not limited in this application.

Exemplary, fig. 10 is a schematic diagram of an interface display for reminding a user to perform a six-minute walking distance test according to an embodiment of the present application.

Optionally, when the user turns on the sensorless amount, but no valid athletic data is detected for a long period of time, a pop-up window 1001 may be displayed on the display screen of the device 1000 to encourage the user to perform an outdoor sport.

Alternatively, the text content of the popup 1001 may be: no effective sports data of you are detected for a long time, for your physical health, you are recommended to do outdoor sports-!

Optionally, the user opening the sensorless measurement means that the user opens the six-minute walk test function, specifically, the user may open the six-minute walk test function by setting the device, or the user may quickly open the six-minute walk test function by using the status bar of the device, and in addition, the user may open or close the six-minute walk test function by other manners, such as voice control, etc., which is not limited in this application.

In the embodiment of the application, the equipment can remind the user of the movement when the effective movement data of the user is not detected for a long time, so that the movement frequency of the user can be improved to a certain extent, and the use experience of the user can be improved.

Illustratively, fig. 11 shows a schematic flow chart of yet another six-minute walking distance testing method 1100 provided by an embodiment of the present application. As shown in fig. 11, the method 1100 includes:

S1101: the mobile phone side application APP actively initiates six-minute walk test.

Optionally, when the user wishes to perform the six-minute walk test, the six-minute walk test is actively initiated by the sports health application of the mobile phone, or may be initiated by the setup of the mobile phone, the entry of the status bar, etc., which is not limited by the present application.

Alternatively, the mobile phone in this embodiment may be replaced with any terminal device (e.g., tablet, notebook, etc.).

S1102: determining whether the mobile phone is connected with the wearable device, if so, executing step S1103; if not, step S1104 is performed.

The mobile phone is connected with the wearable device, and can be in wired connection with the wearable device or in wireless connection (in the forms of Bluetooth, WIFI and the like).

The wearable device is in a user wearing state.

S1103: starting the wearable device side application to perform six-minute walk test, and further executing step S1105.

When the mobile phone and the wearable device are determined to be connected, the wearable device side automatically starts six-minute walking test.

S1104: the mobile phone side application is started for six-minute walk test, and step S1107 is further executed.

When the mobile phone is determined to be not connected with the wearable device, the mobile phone side automatically starts six-minute walking test.

S1105: physiological data and motion data of a user are collected.

Optionally, after the six-minute walking test is started, the physiological parameters of the user may be monitored and collected in real time by a photoplethysmogram (PPG) sensor, while the motion data of the user is monitored and collected in real time based on an acceleration (accelerometer, ACC) sensor, a gyroscope, or a global positioning system (global positioning system, GPS) sensor, etc., and the real-time monitoring and collecting process is continued until the six-minute walking test is ended.

Alternatively, in this embodiment, the timing is started when the user starts the six-minute walk test, and the test is ended after 6 minutes. The physiological data and the exercise data of the user acquired are the physiological data and the exercise data of the user within the 6-minute time period.

S1106: and outputting six-minute walking test results according to the physiological data and the exercise data of the user.

Optionally, in this step, the method for outputting the six-minute walking test result according to the physiological data and the exercise data of the user is the same as the method for determining the six-minute walking distance output value of the user in the embodiment shown in fig. 5 to 8, and for brevity, will not be described herein.

The six-minute walk test result may also be described as a six-minute walk distance output value, or the six-minute walk test result may include a six-minute walk distance output value.

S1107: motion data of a user is collected.

The motion data description about the user has been described in detail in step S1105, and is not described here again for brevity.

Alternatively, in this embodiment, the timing is started when the user starts the six-minute walk test, and the test is ended after 6 minutes. The collected motion data of the user is the motion data of the user in the period of 6 minutes.

S1108: and outputting a six-minute walking test result according to the movement data of the user.

In the embodiment of the application, a user can independently start a 6-minute walking test on a terminal device (such as a mobile phone and the like), monitor exercise physiological data and exercise data of the user such as heart rate, blood pressure, blood oxygen and the like in real time after the starting test, and display or voice broadcast a six-minute walking test result of the user on a display screen of the terminal device and/or a display screen of a wearable device after the 6-minute walking test is finished, and the process can be independently completed by the user. When the terminal equipment is not connected with the wearable equipment, the mobile phone can also support 6-minute walking test, and a user only needs to initiate on the mobile phone, so that the threshold of test conditions can be reduced, and more users can participate in the 6-minute walking test; in addition, the method can realize that the mobile phone is combined with the wearable equipment to carry out the test, and the measurement record at the side of the wearable equipment can be synchronized to the mobile phone, so that the measurement record can be stored for a long time, and a user can observe the change (improvement or deterioration) of the self-movement capacity through looking up the history record, so that the use experience of the user is further improved.

In parallel with the embodiment of fig. 11, fig. 12 illustrates a schematic flow chart of yet another six-minute walking distance testing method 1200 provided by an embodiment of the present application. As shown in fig. 12, the method 1200 includes:

s1201: the wearable device side application APP actively initiates a six-minute walk test.

Optionally, when the user wishes to perform the six-minute walk test, the six-minute walk test is actively initiated by the sports health application of the wearable device, or may be initiated by an entry such as a setting of the wearable device, which is not limited by the present application.

S1202: and starting the wearable device side application to perform six-minute walking test.

S1203: physiological data and motion data of a user are collected.

The description of this step is the same as that of step S1105 in the embodiment shown in fig. 11, and for brevity, the description is omitted here.

S1204: and outputting six-minute walking test results according to the physiological data and the exercise data of the user.

S1205: if the wearable device is connected with the mobile phone, the physiological data, the movement data and the six-minute walking test result of the user are synchronized to the mobile phone.

The wearable device is connected with the mobile phone, and can be in wired connection with the mobile phone or in wireless connection (in the forms of Bluetooth, WIFI and the like).

In the embodiment of the application, a user can independently start a 6-minute walking test on the wearing equipment side, monitor the exercise physiological data and the exercise data such as heart rate, blood pressure, blood oxygen and the like of the user in real time after the starting test, and display or voice broadcast the six-minute walking test result of the user on the display screen of the terminal equipment connected with the user and/or the display screen of the wearing equipment after the 6-minute walking test is finished.

Illustratively, based on the embodiment shown in fig. 12, fig. 13 shows a schematic flowchart of a method 1300 for testing a six-minute walking distance according to an embodiment of the present application. The method 1300 is applicable to a scenario where a user wears a wearable device, as shown in fig. 13, the method 1300 includes:

S1301: the wearable device side application APP actively initiates a six-minute walk test.

The description of this step is the same as that of step S1201 in the embodiment shown in fig. 12, and for brevity, the description is omitted here.

S1302: and starting the wearable device side application to perform six-minute walking test, and collecting the initial heart rate, the initial blood oxygen and the initial blood pressure of the user.

The method for collecting the initial heart rate, the initial blood oxygen and the initial blood pressure of the user is described in detail in the embodiment shown in fig. 5, and is not described herein for brevity.

S1303: judging whether the physiological data of the user meets the following conditions: heart rate/initial heart rate >180 or blood oxygenation/initial blood oxygenation <90% or low pressure/initial low pressure >100 or high pressure/initial high pressure >180. If so, indicating that the physical state of the user does not meet the test conditions, and is not suitable for 6-minute walking test, and forcibly ending the test (or starting the test to fail); if not, it is indicated that the physical state of the user satisfies the test condition, and the 6-minute walk test can be performed, and the step S1304 is further performed.

Optionally, when the test condition is satisfied, the wearable device performs vibration reminding and voice synchronous broadcasting: "please walk on a flat road in a straight line for 6 minutes" and show the user's awareness on the corresponding start page of the display screen of the wearable device, and after the user reads the user's awareness through the page, autonomously start the 6 minute walk test.

Optionally, when the test condition is not satisfied, the wearable device performs vibration reminding and voice synchronous broadcasting: "your current heart rate: XX, blood pressure: XX, blood oxygen: XX, failing to meet the 6-minute walking test condition, please open the test after resting, and display the corresponding prompt text on the display screen of the wearable device and end the test.

S1304: the exercise physiological data and the exercise data of the user are monitored in real time.

Wherein, optionally, the wearing equipment monitors and collects the motion physiological data and the motion data of the user in real time.

The explanation and collection of the exercise physiological data and the exercise data of the user are described in detail in the embodiment shown in fig. 5, and are not repeated herein for brevity.

It should be understood that: after the start of the test is successful, the timing is started for 6 minutes, and step S1303 is performed in a loop during the timing for 6 minutes, and if the physiological data of the user satisfies the above conditions (heart rate/initial heart rate >180 or blood oxygen/initial blood oxygen <90% or low pressure/initial low pressure >100 or high pressure/initial high pressure > 180) during the test, the test is terminated immediately.

S1305: when 1 minute after the start of the test (namely when the countdown of 6 minutes is to 5 minutes), the wearable device carries out vibration reminding, synchronously broadcasts relevant reminding contents through voice, and synchronously displays the relevant reminding contents on a display screen of the wearable device.

Optionally, the voice prompt is dynamically broadcasted according to the heart rate range of the user within 1 minute.

Optionally, based on physiological data and motion data such as heart rate, blood oxygen, blood pressure, step frequency, speed, distance and the like of the whole minute of the user acquired by the wearable device, reminding the user of the current walking live condition.

Optionally, the reminding mode may be: vibration reminding for whole minutes; and (3) synchronous voice broadcasting: "you have walked for 1 minute, distance: XXm, current speed: XX, heart rate: XX, blood oxygen, blood pressure: XX, please refuel "; and displaying the real-time data and the corresponding prompt information on a display screen of the wearable device. The wearable device carries out vibration reminding, synchronously broadcasts relevant reminding contents through voice, and synchronously displays the relevant reminding contents on a display screen of the wearable device.

S1306: and determining whether the walking track of the user is on a straight line, and if not, reminding the user to walk along the straight line in a best effort mode.

Optionally, based on the walking path of the user in the walking process collected by the wearable device, judging whether the sampling position point is on a straight line, and if not, reminding the user to walk along the straight line as much as possible.

Optionally, the reminding mode may be: the wearing equipment carries out vibration reminding; and synchronously broadcasting the voice: "please walk best along straight line"; and synchronously displaying the related reminding content on a display screen of the wearable device.

Alternatively, this step S1306 is not a one-time step, but is performed repeatedly in a loop during the 6-minute walk test.

S1307: and at the nth minute (namely, when the time of 6 minutes is counted down to (6-n) minutes) after the start of the test, the wearable device carries out vibration reminding, synchronously broadcasts relevant reminding contents through voice, and synchronously displays the relevant reminding contents on a display screen of the wearable device.

Optionally, in the nth minute, based on physiological data and motion data such as heart rate, blood oxygen, blood pressure, step frequency, speed, distance and the like of the whole minute of the user acquired by the wearable device, the real-time heart rate of the user, the distance contrast (Sn-1) between the current minute Duan Juli (Sn) and the last minute is extracted, and further dynamic reminding is carried out. Specifically, firstly, judging a heart rate interval of a user, and sequentially extracting corresponding content reminding users from a first voice and text reminding content library according to whether Sn and Sn-1 are compared to rise or fall. The first voice and text reminding content library is shown in table 1.

TABLE 1

Optionally, the reminding mode may be: vibration reminding for whole minutes; and (3) synchronous voice broadcasting: you have moved for n minutes, distance: XXm, current speed: XX, which is a drop/rise compared to the previous minute, XXX (determined by the first speech and text alert content library, speech and text dynamically adapted); and displaying the real-time physiological data, the motion data and the corresponding prompt information on a display screen of the wearable device.

Optionally, if the wearable device is connected to a terminal device (such as a mobile phone, etc.), the real-time physiological data, the motion data and the corresponding prompt information can be synchronously displayed on the display screen of the terminal device.

S1308: the six-minute walk test ends.

Optionally, after the test is finished in the 6 th minute, the wearable device carries out vibration reminding; the voice synchronous broadcasting walking test result may be, for example: 6 minutes walking test has ended, you walk distance 6 minutes: XXm slightly up/down compared to the last walk test result (not first 6 minutes walk test); and displaying the six-minute walk test result on a display screen of the wearable device.

Alternatively, if the wearable device is connected to a terminal device (such as a mobile phone, etc.), six-minute walk test results may be synchronously displayed on a display screen of the terminal device.

According to the embodiment of the application, a user can actively initiate six-minute walking test through the wearable device, and the walking distance is automatically calculated after the test is finished, so that a doctor is not required to measure, and the portable walking device is easy to use; in the walking test process, the user acquires physiological data such as heart rate, blood oxygen and blood oxygen of the user through the wearable equipment, and interacts with the user in real time based on the physiological data, so that the user is scientifically guided to walk farther along a straight line as much as possible, the accuracy of a 6-minute walking test result can be improved, and meanwhile, the risk of the user in the walking process can be reduced; the method does not depend on the assistance of medical staff in a hospital, monitors physiological data such as heart rate, blood oxygen, blood pressure and the like of the user in real time in the walking process, does not need a plurality of equipment to cooperate with experiments, greatly reduces operation complexity, enlarges the user population walking for 6 minutes, and improves user experience.

Illustratively, fig. 14 shows a schematic flow chart of a method 1400 for testing a six-minute walking distance according to an embodiment of the present application, based on the embodiment shown in fig. 11. The method 1400 is applicable to a scenario where a user is wearing a wearable device, as shown in fig. 14, the method 1400 includes:

S1401: the mobile phone side application APP actively initiates six-minute walk test.

The description of this step is the same as that of step S1101 in the embodiment shown in fig. 11, and is not repeated here for brevity.

S1402: and starting the wearable device side application to perform six-minute walking test, and collecting the initial heart rate, the initial blood oxygen and the initial blood pressure of the user.

S1403: judging whether the physiological data of the user meets the following conditions: heart rate/initial heart rate >180 or blood oxygenation/initial blood oxygenation <90% or low pressure/initial low pressure >100 or high pressure/initial high pressure >180. If so, indicating that the physical state of the user does not meet the test conditions, and is not suitable for 6-minute walking test, and forcibly ending the test (or starting the test to fail); if not, it is indicated that the physical state of the user satisfies the test condition, and the 6-minute walk test is performed, and the step S1404 is further performed.

S1404: and monitoring the exercise physiological data and the exercise data of the user in real time, and synchronizing the exercise physiological data and the exercise data to the mobile phone side.

Optionally, the wearable device monitors and collects the motion physiological data and the motion data of the user in real time, and synchronizes the collected motion physiological data and the motion data of the user to the mobile phone side in real time.

It should be understood that: after the start of the test is successful, the timing is started for 6 minutes, and step S1403 is performed in a loop during the timing for 6 minutes, and if the physiological data of the user satisfies the above condition (heart rate/initial heart rate >180 or blood oxygen/initial blood oxygen <90% or low pressure/initial low pressure >100 or high pressure/initial high pressure > 180) during the test, the test is terminated immediately.

S1405: when the test is started for 1 minute (namely, when the time is counted down to 5 minutes for 6 minutes), the wearable device carries out vibration reminding, synchronously broadcasts relevant reminding contents through voice, and synchronously displays the relevant reminding contents on a display screen of the mobile phone.

Optionally, the reminding mode may be: vibration reminding for whole minutes; and (3) synchronous voice broadcasting: "you have walked for 1 minute, distance: XXm, current speed: XX, heart rate: XX, blood oxygen, blood pressure: XX, please refuel "; and displaying the real-time data and the corresponding prompt information on a display screen of the mobile phone. Namely: the wearable device carries out vibration reminding, synchronously broadcasts relevant reminding contents through voice, and synchronously displays the relevant reminding contents on a display screen of the mobile phone.

S1406: and determining whether the walking track of the user is on a straight line, and if not, reminding the user to walk along the straight line in a best effort mode.

Optionally, the reminding mode may be: the wearing equipment carries out vibration reminding; and synchronously broadcasting the voice: "please walk best along straight line"; and synchronously displaying related reminding contents on a display screen of the mobile phone.

Alternatively, this step S1406 is not a one-time step, but is performed repeatedly in a loop during the 6-minute walk test.

S1407: and when the test starts at the nth minute (namely, when the time is counted down from 6 minutes to (6-n) minutes), the wearable device carries out vibration reminding, synchronously broadcasts relevant reminding contents through voice, and synchronously displays the relevant reminding contents on a display screen of the mobile phone.

Optionally, in the nth minute, based on physiological data and motion data such as heart rate, blood oxygen, blood pressure, step frequency, speed, distance and the like of the whole minute of the user acquired by the wearable device, the real-time heart rate of the user, the distance contrast (Sn-1) between the current minute Duan Juli (Sn) and the last minute is extracted, and further dynamic reminding is carried out. Specifically, firstly, judging a heart rate interval of a user, and sequentially extracting corresponding content reminding users from a first voice and text reminding content library according to whether Sn and Sn-1 are compared to rise or fall. The first voice and text reminding content library is shown in the table 1.

Optionally, the reminding mode may be: vibration reminding for whole minutes; and (3) synchronous voice broadcasting: you have moved for n minutes, distance: XXm, current speed: XX, which is a drop/rise compared to the previous minute, XXX (determined by the first speech and text alert content library, speech and text dynamically adapted); and displaying real-time physiological data, motion data and corresponding prompt information on a display screen of the mobile phone.

S1408: the six-minute walk test ends.

Optionally, after the test is finished in the 6 th minute, the wearable device carries out vibration reminding; the voice synchronous broadcasting walking test result may be, for example: 6 minutes walking test has ended, you walk distance 6 minutes: XXm slightly up/down compared to the last walk test result (not first 6 minutes walk test); and displaying the six-minute walk test result on the display screen of the mobile phone.

In the embodiment of the application, a user can actively initiate a six-minute walking test through the mobile phone, when the mobile phone is connected with the wearable device, the wearable device starts the 6-minute walking test, and the walking distance is automatically calculated after the test is finished, so that a doctor is not required to measure, and the mobile phone is portable and easy to use; in the walking test process, the user acquires physiological data such as heart rate, blood oxygen and blood oxygen of the user through the wearable equipment, and interacts with the user in real time based on the physiological data, so that the user is scientifically guided to walk farther along a straight line as much as possible, the accuracy of a 6-minute walking test result can be improved, and meanwhile, the risk of the user in the walking process can be reduced; the method does not depend on the assistance of medical staff in a hospital, monitors physiological data such as heart rate, blood oxygen, blood pressure and the like of the user in real time in the walking process, does not need a plurality of equipment to cooperate with experiments, greatly reduces operation complexity, enlarges the user population walking for 6 minutes, and improves user experience.

Illustratively, fig. 15 shows a schematic flowchart of a method 1500 for intelligently reminding to start a 6-minute walk test according to an embodiment of the application. The method 1500 is applicable to a scenario where a user wears a wearable device and is in a walking state, as shown in fig. 15, the method 1500 includes:

s1501: the wearable device side application monitors the user's 3 minute walking track, heart rate, blood oxygen, and blood pressure.

S1502: whether the walking track of the user is on a straight line is determined, if so, step S1503 is further executed.

The method for determining whether the walking track of the user is on the straight line is described in detail in the embodiments shown in fig. 13 and 14, and is not described herein for brevity.

S1503: judging whether the physiological data of the user meets the following conditions: heart rate >180 or blood oxygenation <90% or low pressure >100 or high pressure/initial high pressure >180. If not, it is indicated that the physical state of the user satisfies the test condition, and the 6-minute walk test is performed, and the step S1504 is continued.

S1504: the user is prompted as to whether he would like to turn on the six minute walk test.

Optionally, the prompting method may be that the wearable device performs vibration prompting; and synchronously broadcasting the voice: "detected you are on straight walking, ask you if you are willing to turn on the six-minute walk test"; and synchronously displaying related reminding contents on a display screen of the mobile phone.

S1505: after the user triggers the starting process, the wearable device starts a six-minute walk test.

The following test procedure may be the test procedure described in the embodiment shown in any of fig. 5 to 14.

Hereinafter, an interface display diagram involved in a 6-minute walk test performed on the wearable device side will be described with reference to fig. 16 to 22 by way of example.

Fig. 16 is a schematic diagram of a start page corresponding to a 6-minute walking test process performed on a wearable device side according to an embodiment of the present application.

As shown in fig. 16, when the test condition is satisfied, the wearable device performs vibration alert and voice synchronous broadcast: "please walk on a flat road in a straight line for 6 minutes" and display the user's awareness on the corresponding actuation page of the display screen of the wearable device, and after the user reads the user's awareness through the page, automatically initiate a 6-minute walk test through the actuation control below the page.

For example, fig. 17 is a schematic diagram showing an interface display of a start test failure or a test termination caused by failing to meet a test condition corresponding to a 6-minute walk test process performed on a wearable device side according to an embodiment of the present application.

As shown in fig. 17, when the test condition is not satisfied, the wearable device performs vibration alert and voice synchronous broadcast: "your current heart rate: XX, blood pressure: XX, blood oxygen: XX, failing to meet the 6-minute walking test condition, please start the test after resting, and display the corresponding prompt text and abnormal index data on the display screen of the wearable device, and end the test.

Fig. 18 is a schematic diagram of interface display when a user walking track is detected to deviate from a straight line, corresponding to a 6-minute walking test process performed on a wearable device side according to an embodiment of the present application.

As shown in fig. 18, when the wearable device detects that the walking track of the user deviates from the straight line, the wearable device carries out vibration reminding; and synchronously broadcasting the voice: "please walk best along straight line"; real-time physiological data and motion data of a user and corresponding barrage characters are synchronously displayed on a display screen of the wearable device: "please walk best along straight line".

Fig. 19 and fig. 20 are schematic interface display diagrams of a whole-minute reminder corresponding to a 6-minute walking test process performed on a wearable device side according to an embodiment of the present application.

As shown in fig. 19, when the wearable device detects that the user walks for 3 minutes in a countdown manner for 6 minutes, the wearable device performs vibration reminding; and synchronously broadcasting the voice: "you have moved 3 minutes, distance: 200m, current speed: 1 meter per second, please continue to struggle "; real-time physiological data and motion data of a user and corresponding barrage characters are synchronously displayed on a display screen of the wearable device: "please continue to struggle".

As shown in fig. 20, when the wearable device detects that the user walks for 3 minutes in a countdown manner for 6 minutes, the wearable device carries out vibration reminding; and synchronously broadcasting the voice: "you have moved 3 minutes, distance: 150m, current speed: 1 meter per second, please control the breathing well, if there is discomfort to rest "; real-time physiological data and motion data of a user and corresponding barrage characters are synchronously displayed on a display screen of the wearable device: please control the breathing well, if there is discomfort, please rest.

The specific prompts in the embodiment of fig. 19 and 20 described above are related to the real-time physiological data and the exercise data of the user, and the specific prompts may be determined according to the first voice and text prompt library (table 1) described in the embodiment of fig. 13 described above.

Fig. 21 is a schematic diagram of interface display at the end of a test corresponding to a 6-minute walking test procedure performed on a wearable device side according to an embodiment of the present application.

As shown in fig. 21, when the wearable device detects that the test is finished, the wearable device performs vibration reminding; and synchronously broadcasting the voice: "6 minutes walk test has ended, please note rest, you walk distance 6 minutes: XXm, slightly lifting/lowering (not first 6 minutes walking test) compared with the previous walking test; and synchronously displaying test result data of the user on a display screen of the wearable device.

The test result data comprise data of average step frequency, average step speed, average heart rate, heart rate range, blood oxygen range, blood pressure range, gait stability, walking distance and the like of the user.

Exemplary, fig. 22 shows an interface display schematic diagram for intelligently reminding a user to start a 6-minute walk test according to an embodiment of the present application.

As shown in fig. 22, when the user wears the wearable device and the user is in a walking state, if the user is detected to satisfy the condition of the 6-minute walking test, a reminding word is displayed on the display screen of the wearable device: "you have detected that you are walking in a straight line, ask you if you are willing to open a 6-minute walk test", the display page is associated with a control "start" and a control "cancel", and the user can confirm that 6-minute walk test is open by clicking the control "start"; the user can also confirm that the 6 minute walk test is not turned on by clicking the control "cancel".

Alternatively, if the user does not make a selection within a certain time, the display interface is automatically exited.

Alternatively, when the user opens the 6-minute walk test through the mobile phone side and the mobile phone establishes a connection with the wearable device, the display interfaces shown in fig. 16 to 22 are displayed on the display screen of the mobile phone, and the display interfaces shown in fig. 16 to 22 may also be displayed on the display screen of the wearable device.

Optionally, when the user opens the 6-minute walk test through the wearable device side and the mobile phone establishes a connection with the wearable device, the display interfaces shown in fig. 16 to 22 are displayed on the display screen of the wearable device, and the display interfaces shown in fig. 16 to 22 may also be displayed on the display screen of the mobile phone.

Optionally, when the user opens the 6-minute walk test through the wearable device side and the mobile phone and the wearable device are not connected, the display interface shown in fig. 16 to 22 is displayed on the display screen of the wearable device.

Illustratively, fig. 23 shows a schematic flow chart of a further six-minute walking distance testing method 2300 provided by an embodiment of the application, based on the embodiment shown in fig. 11. The method 2300 is applicable to a scenario where the user is not wearing a wearable device, as shown in fig. 23, the method 2300 includes:

S2301: the mobile phone side application APP actively initiates six-minute walk test.

S2302: and the mobile phone side monitors the motion data of the user in real time.

The explanation and collection of the motion data of the user are described in detail in the embodiment shown in fig. 5, and are not repeated herein for brevity.

S2303: when the test is started for 1 minute (namely, when the time is counted down to 5 minutes for 6 minutes), the mobile phone carries out vibration reminding, relevant reminding contents are synchronously broadcasted through voice, and the relevant reminding contents are synchronously displayed on a display screen of the mobile phone.

Optionally, reminding the user of the current walking live condition based on the motion data of the whole minute of the user, such as the step frequency, the speed, the distance and the like acquired by the mobile phone.

Optionally, the reminding mode may be: vibration reminding for whole minutes; and (3) synchronous voice broadcasting: "you have walked for 1 minute, distance: XXm, current speed: XX, please refuel "; and displaying the real-time data and the corresponding prompt information on a display screen of the mobile phone.

S2304: and determining whether the walking track of the user is on a straight line, and if not, reminding the user to walk along the straight line in a best effort mode.

Optionally, based on the walking path of the mobile phone acquisition user walking process, judging whether the sampling position point is on a straight line, and if not, reminding the user to walk along the straight line as much as possible.

Optionally, the reminding mode may be: the mobile phone carries out vibration reminding; and synchronously broadcasting the voice: "please walk best along straight line"; and synchronously displaying related reminding contents on a display screen of the mobile phone.

Alternatively, this step S2304 is not a one-time step, but is performed repeatedly in a loop during the 6-minute walk test.

S2305: and at the nth minute (namely, when the time from 6 minutes to (6-n) minutes) after the start of the test, the mobile phone carries out vibration reminding, synchronously broadcasts relevant reminding contents by voice, and synchronously displays the relevant reminding contents on a display screen of the mobile phone.

Optionally, in the nth minute, based on the motion data of the whole minute of the user, such as the step frequency, the speed, the distance and the like, collected by the mobile phone, the distance between the current minute Duan Juli (Sn) and the last minute is compared (Sn-1), so that dynamic reminding is further performed. Specifically, according to whether the Sn-1 contrast rises or falls, corresponding content reminding users are sequentially extracted from the second voice and text reminding content library. The second voice and text reminding content library is shown in table 2.

TABLE 2

Optionally, the reminding mode may be: vibration reminding for whole minutes; and (3) synchronous voice broadcasting: you have moved for n minutes, distance: XXm, current speed: XX, which is a drop/rise compared to the previous minute, XXX (determined by the second speech and text alert content library, speech and text dynamically adapted); and displaying real-time motion data and corresponding prompt information on a display screen of the mobile phone.

S2306: the six-minute walk test ends.

Optionally, after the test is finished in the 6 th minute, the mobile phone carries out vibration reminding; the voice synchronous broadcasting walking test result may be, for example: 6 minutes walking test has ended, you walk distance 6 minutes: XXm slightly up/down compared to the last walk test result (not first 6 minutes walk test); and displaying the six-minute walk test result on the display screen of the mobile phone.

In the embodiment of the application, the user can actively initiate six-minute walking test through the mobile phone, and the walking distance is automatically calculated after the test is finished, so that the operation is more convenient; in addition, in the walking process, the user interacts with the user in real time through the motion data such as the distance, the speed, the path and the like acquired by the mobile phone, so that the user is guided to walk along a straight line, the user is encouraged to walk farther as much as possible, and the walking distance of the user for 6 minutes is reflected more truly. According to the method, the user can independently initiate the 6-minute walking test based on the mobile phone, the wearing equipment scene is not relied on, the cost of purchasing the wearing equipment by the user is greatly reduced, and meanwhile, the participation group of the 6-minute walking test is further enlarged.

Hereinafter, an interface display diagram involved in a 6-minute walk test performed on a mobile phone side (a non-connected wearing rate) will be described with reference to fig. 24 to 27.

Fig. 24 is a schematic diagram of a start page corresponding to a 6-minute walk test procedure performed on a mobile phone side according to an embodiment of the present application.

As shown in fig. 24, before the test is started, the mobile phone performs vibration reminding and voice synchronous broadcasting: "please walk along straight line for 6 minutes on flat road", and display user's notice on the corresponding start page of the display screen of the mobile phone, after the user reads the user's notice through the page, start 6 minutes walk test independently through the start control under the page.

Fig. 25 is an exemplary diagram showing an interface display of a whole-minute reminder corresponding to a 6-minute walk test procedure performed on a mobile phone side according to an embodiment of the present application.

As shown in fig. 25, when the mobile phone detects that the user walks for 3 minutes in a countdown manner for 6 minutes, the mobile phone carries out vibration reminding; and synchronously broadcasting the voice: "you have moved 3 minutes, distance: 200m, current speed: 1 meter per second, please refuel "; the display screen of the mobile phone synchronously displays real-time motion data of the user and corresponding barrage characters: "please refuel".

The specific prompt content in the embodiment shown in fig. 25 is related to the real-time motion data of the user, and the specific prompt content may be determined according to the second voice and text prompt content library (table 2) described in the embodiment shown in fig. 23.

Fig. 26 is a schematic diagram illustrating an interface display at the end of a test corresponding to a 6-minute walk test procedure performed on a mobile phone side according to an embodiment of the present application.

As shown in fig. 26, when the mobile phone detects that the test is finished, the mobile phone carries out vibration reminding; and synchronously broadcasting the voice: "6 minutes walk test has ended, please note rest, you walk distance 6 minutes: XXm, slightly lifting/lowering (not first 6 minutes walking test) compared with the previous walking test; and synchronously displaying test result data of the user on a display screen of the mobile phone.

The test result data comprise data such as average stride frequency, average pace speed, gait stability, walking distance and the like of the user.

Fig. 27 is a schematic diagram of an interface display when a user walking track is detected to deviate from a straight line corresponding to a 6-minute walking test process performed on a mobile phone side according to an embodiment of the present application.

As shown in fig. 27, when the mobile phone detects that the walking track of the user deviates from a straight line, the mobile phone carries out vibration reminding; and synchronously broadcasting the voice: "please walk best along straight line"; the display screen of the mobile phone synchronously displays real-time motion data of the user and corresponding barrage characters: "please walk best along straight line".

Illustratively, FIG. 28 shows a 6-minute walk test result interface display provided by an embodiment of the present application.

As shown in fig. 28, the six-minute walk test result includes various exercise data and physiological data analysis tables of the user and exercise capacity analysis comparison charts of the user.

Specifically, the index item includes basic information of the user, including height, weight, body mass index, age, and the abnormality index is indicated upward or downward by an arrow; the index items also include exercise data and physiological data of the user in the walking test, including distance, average step number, average step frequency, average heart rate, average blood oxygen, systolic pressure maximum/minimum value, diastolic pressure maximum/minimum value, gait stability, and the abnormality index is represented by an arrow upward or downward.

Meanwhile, the walking distance of the user is compared with the standard value of the same person, and the current exercise capacity state of the user is estimated.

And according to the interpretation and exercise performance evaluation of the 6-minute result, a suggestion of user rationality is given.

Alternatively, normal people walk a distance >450m for 6 minutes; when walking distance is less than 150m in 6 minutes, the exercise capacity is severely reduced; when the walking distance is 150-300m in 6 minutes, the exercise ability is moderately reduced; at walking distances greater than 300m and less than 450m for 6 minutes, exercise ability was slightly impaired.

Exemplary, fig. 29 shows a display diagram of a 6-minute walk test result interactive interface provided by an embodiment of the present application.

As shown in fig. 29, 6-minute walking distances can be ranked among friends, the friends can know each other's 6-minute walking distances, and can praise each other, the user can be encouraged to enhance the activity ability, the 6-minute walking distance can be improved, the 6-minute walking interactivity can be enhanced, and the user is encouraged to participate in the 6-minute walking test more.

It should be understood that: the above embodiments may be implemented alone or in combination, for example: any of the embodiments shown in fig. 5-8 may be incorporated into the step of six-minute walking distance determination in any of the embodiments shown in fig. 11-15.

Fig. 30 is a schematic functional block diagram of an apparatus 3000 for six-minute walk test according to an embodiment of the present application, corresponding to the embodiments shown in fig. 5 and 6. As shown in fig. 30, the apparatus 3000 includes:

The data acquisition module 3010 is used for acquiring motion data and physiological data of the user in the first motion process of the user.

Optionally, the data acquisition module 3010 periodically records the physiological parameters of the user (e.g., records a physiological parameter every ten minutes) through a photoplethysmogram (PPG) sensor, while the data acquisition module 3010 monitors the user motion data in real time based on an acceleration (accelerometer, ACC) sensor, a gyroscope, or a global positioning system (global positioning system, GPS) and the like, and when the data acquisition module 3010 determines that the current user is in motion (starts the first motion process) according to the motion data, starts to monitor and acquire the physiological data and the motion data of the user in real time, and the real-time monitoring and acquisition process is continued until the first motion process ends.

The distance prediction module 3020 is configured to determine a motion type of the user according to the motion data of the user during the first motion process.

The distance prediction module 3020 is further configured to determine a six-minute walking distance predicted value corresponding to the first exercise process according to the exercise type and the exercise data of the user.

Specifically, the distance prediction module 3020 needs to determine, according to the motion type, a distance prediction method (also referred to as a distance prediction sub-module) corresponding to the first motion process first, and further determine, according to the distance prediction method (or the distance prediction sub-module corresponding to the first motion process) corresponding to the first motion process and the motion data, a six-minute walking distance prediction value corresponding to the first motion process.

The intensity determining module 3030 is configured to determine the exercise intensity of the user according to the exercise type of the user and the physiological data of the user.

Specifically, the exercise intensity judgment threshold values corresponding to different exercise types are different, and the intensity determination module 3030 needs to determine the exercise intensity judgment threshold value corresponding to the first exercise process (that is, the exercise type) according to the exercise type of the user first, and then compare the physiological data of the user with the exercise intensity judgment threshold value, so as to determine the exercise intensity of the user.

Wherein the exercise intensity judgment threshold includes a first threshold and a second threshold, and when the physiological data of the user is smaller than the first threshold, the intensity determining module 3030 determines the exercise intensity of the user as low intensity (may also be described as the first intensity); when the physiological data of the user is greater than or equal to the first threshold and less than the second threshold, the intensity determination module 3030 determines the intensity of the motion of the user to be a medium intensity (which may also be described as a second intensity); when the physiological data of the user is greater than or equal to the second threshold, the intensity determination module 3030 determines the intensity of the motion of the user to be high intensity (which may also be described as a third intensity).

The distance prediction module 3020 is further configured to determine the compensation distance according to the motion intensity and the motion type of the user.

The distance prediction module 3020 is further configured to determine a first six-minute walking distance of the user according to the six-minute walking distance predicted value and the compensation distance corresponding to the first exercise process.

Specifically, the distance prediction module 3020 adds the compensation distance to the six-minute walking distance prediction value corresponding to the first motion process to obtain the first six-minute walking distance of the user.

Optionally, the apparatus 3000 may further include:

The result integrating module 3040 is used for integrating N six-minute walking distances of the user, and the N six-minute walking distances are in one-to-one correspondence with N movement processes of the user.

The result integration module 3040 is further configured to determine a six-minute walking distance output value of the user according to the N six-minute walking distances and the resting physiological data of the user.

Optionally, the apparatus 3000 further comprises a reminding module for reminding the user to start the six-minute walk test when no valid movement data of the user is detected for M consecutive days.

Optionally, the apparatus 3000 further includes an information synchronization module, configured to implement information synchronization between the mobile phone and the wearable device when the mobile phone and the wearable device of the user are connected.

Optionally, the apparatus 3000 further comprises a result presenting module for displaying a six-minute walk test report on a display screen of the user's mobile phone or the wearable device when the six-minute walk test is ended.

Among them, the data acquisition module 3010 and the intensity determination module 3030 are optional modules.

In the embodiment of the application, the equipment can actively initiate six-minute walking test when the test condition is met, and the test frequency can be improved so as to better realize the monitoring of the health level of the user; the walking six-minute test result (the test result is compensated according to the exercise intensity and the exercise type) of the user can be obtained by comprehensively analyzing and calculating the exercise intensity and the exercise type of the user, the accuracy of the test result can be improved, and the method supports the tests under different exercise types, has wide application scenes, and can improve the use experience of the user; and the integrated analysis can be carried out on a plurality of six-minute walking distances corresponding to a plurality of exercise processes of the user, and the result after the integrated analysis is corrected according to the rest physiological parameters of the user, so that the accuracy of the six-minute walking distance output value can be further improved.

Fig. 31 is a schematic functional block diagram of another six-minute walk test apparatus 3100 according to an embodiment of the application, corresponding to the embodiment shown in fig. 11 and 12. As shown in fig. 31, the apparatus 3100 includes:

the data acquisition module 3110 is configured to acquire motion data and physiological data of the user.

The man-machine interaction module 3120 is configured to implement information interaction between the user and the device.

The result presentation module 3130 is configured to display a six-minute walking test report on a display screen of a mobile phone or a wearable device of the user when the six-minute walking test is ended.

The embodiment of the present application further provides an electronic device, which includes a memory for storing computer program code and a processor for executing the computer program code stored in the memory, so as to implement the method of any one of the embodiments shown in fig. 5to 29.

One or more of the modules or units described herein may be implemented in software, hardware, or a combination of both. When any of the above modules or units are implemented in software, the software exists in the form of computer program instructions and is stored in a memory, a processor can be used to execute the program instructions and implement the above method flows. The processor may include, but is not limited to, at least one of: a central processing unit (central processing unit, CPU), microprocessor, digital Signal Processor (DSP), microcontroller (microcontroller unit, MCU), or artificial intelligence processor, each of which may include one or more cores for executing software instructions to perform operations or processes. The processor may be built into a SoC (system on a chip) or an application specific integrated circuit (application specificintegrated circuit, ASIC), or may be a stand-alone semiconductor chip. The processor may further include necessary hardware accelerators, such as field programmable gate arrays (field programmable GATE ARRAY, FPGAs), PLDs (programmable logic devices), or logic circuits implementing dedicated logic operations, in addition to the cores for executing software instructions for operation or processing.

When the modules or units described herein are implemented in hardware, the hardware may be any one or any combination of a CPU, microprocessor, DSP, MCU, artificial intelligence processor, ASIC, soC, FPGA, PLD, special purpose digital circuitry, hardware accelerator, or non-integrated discrete device that may run the necessary software or that is independent of the software to perform the above method flows.

When the modules or units described herein are implemented in software, they may be implemented in whole or in part in the form of a computer program product. The computer program product includes one or more computer instructions. When loaded and executed on a computer, produces a flow or function in accordance with embodiments of the present invention, in whole or in part. The computer may be a general purpose computer, a special purpose computer, a computer network, or other programmable apparatus. The computer instructions may be stored in or transmitted from one computer-readable storage medium to another, for example, by wired (e.g., coaxial cable, optical fiber, digital Subscriber Line (DSL)), or wireless (e.g., infrared, wireless, microwave, etc.). The computer readable storage medium may be any available medium that can be accessed by a computer or a data storage device such as a server, data center, etc. that contains an integration of one or more available media. The usable medium may be a magnetic medium (e.g., floppy disk, hard disk, tape), an optical medium (e.g., DVD), or a semiconductor medium (e.g., solid state disk (solid statedisk, SSD)), etc.

Those of ordinary skill in the art will appreciate that the elements and method steps of the examples described in connection with the embodiments disclosed herein can be implemented as electronic hardware, or as a combination of computer software and electronic hardware. Whether such functionality is implemented as hardware or software depends upon the particular application and design constraints imposed on the solution. Skilled artisans may implement the described functionality in varying ways for each particular application, but such implementation decisions should not be interpreted as causing a departure from the scope of the present application.

It will be clear to those skilled in the art that, for convenience and brevity of description, specific working procedures of the above-described systems, apparatuses and units may refer to corresponding procedures in the foregoing method embodiments, and are not repeated herein.

In the several embodiments provided by the present application, it should be understood that the disclosed systems, devices, and methods may be implemented in other manners. For example, the apparatus embodiments described above are merely illustrative, e.g., the division of the units is merely a logical function division, and there may be additional divisions when actually implemented, e.g., multiple units or components may be combined or integrated into another system, or some features may be omitted or not performed. Alternatively, the coupling or direct coupling or communication connection shown or discussed with each other may be an indirect coupling or communication connection via some interfaces, devices or units, which may be in electrical, mechanical or other form.

The units described as separate units may or may not be physically separate, and units shown as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

In addition, each functional unit in the embodiments of the present application may be integrated in one processing unit, or each unit may exist alone physically, or two or more units may be integrated in one unit.

The functions, if implemented in the form of software functional units and sold or used as a stand-alone product, may be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present application may be embodied essentially or in a part contributing to the prior art or in a part of the technical solution, in the form of a software product stored in a storage medium, comprising several instructions for causing a computer device (which may be a personal computer, a server, a network device, etc.) to perform all or part of the steps of the method according to the embodiments of the present application. And the aforementioned storage medium includes: a U-disk, a removable hard disk, a read-only memory (ROM), a random access memory (random access memory, RAM), a magnetic disk, or an optical disk, or other various media capable of storing program codes.

The foregoing is merely illustrative of the present application, and the present application is not limited thereto, and any person skilled in the art will readily recognize that variations or substitutions are within the scope of the present application. Therefore, the protection scope of the present application shall be subject to the protection scope of the claims.

Claims

1. A method of walking testing, the method comprising:

Determining a walking distance predicted value of a user according to the motion data of the user and the motion type of the user;

determining a compensation distance according to the motion type and the motion intensity of the user, wherein the motion data, the motion type and the motion intensity correspond to a first motion process of the user;

and determining a first walking distance of the user according to the walking distance predicted value and the compensation distance.

2. The method according to claim 1, wherein the method further comprises:

collecting the movement data and physiological data of the user during a first movement of the user;

Determining the motion type of the user according to the motion data;

And determining the exercise intensity of the user according to the exercise type and the physiological data.

3. The method of claim 2, wherein said determining the intensity of motion of the user from the type of motion and the physiological data comprises:

Determining a maximum heart rate of the user according to the basic information of the user;

Correcting the maximum heart rate according to resting physiological data of the user;

Determining a motion intensity judgment threshold according to the motion type of the user and the corrected maximum heart rate;

and determining the exercise intensity of the user according to the physiological data and the exercise intensity judging threshold.

4. A method according to any one of claims 1 to 3, wherein said determining a first walking distance of the user from the walking distance prediction value and the compensation distance comprises:

and obtaining the first walking distance of the user by summing the walking distance predicted value and the compensation distance.

5. The method according to any one of claims 1 to 4, further comprising:

Acquiring N walking distances of the user, wherein the N walking distances correspond to N movement processes of the user one by one, and the N walking distances comprise the first walking distance;

And determining walking distance output values of the user according to the N walking distances and resting physiological data of the user, wherein the resting physiological data are physiological data in a non-motion state.

6. The method of claim 5, wherein said determining the walking distance output value of the user from the N walking distances and the resting physiological data of the user comprises:

determining the crowd of the user according to the resting physiological data of the user;

Determining walking distance distribution conditions corresponding to the user according to the crowd to which the user belongs;

Respectively calculating weight values of the N walking distances according to the N walking distances and walking distance distribution conditions corresponding to the user;

and determining the walking distance output value of the user according to the N walking distances and the weight values of the N walking distances.

7. The method of any one of claims 1 to 6, wherein the walking test is a six-minute walking test.

8. The method of claim 7, wherein the method further comprises:

And prompting the user to start the six-minute walk test when the effective movement data of the user are not detected for M consecutive days.

9. The method according to claim 7 or 8, characterized in that the method further comprises:

When the user actively initiates the six-minute walk test through the cell phone,

If the mobile phone is connected with the wearable device, performing the six-minute walk test on the wearable device side;

and if the mobile phone is not connected with the wearable equipment, performing the six-minute walking test on the mobile phone side.

10. The method according to claim 7 or 8, characterized in that the method further comprises:

when the user actively initiates the six-minute walk test through the wearable device, performing the six-minute walk test on the wearable device side;

and if the wearable equipment is connected with the mobile phone, synchronizing the six-minute walking test result to the mobile phone after completing the six-minute walking test.

11. The method according to any one of claims 7 to 10, further comprising:

and reminding the user of walking along the straight line when detecting that the walking track of the user deviates from the straight line.

12. The method according to any one of claims 7 to 11, further comprising:

And when the six-minute walk test is finished, displaying a six-minute walk test report on a display screen of the mobile phone or the wearable device of the user.

13. The method of any one of claims 1 to 12, wherein the motion data comprises one or more of stride frequency, gait, speed, distance.

14. The method of any one of claims 1 to 13, wherein the physiological data comprises one or more of heart rate, blood oxygen, blood pressure.

15. The method of any one of claims 1 to 14, wherein the type of exercise comprises one or more of walking, running, riding, stair climbing, swimming.

16. An apparatus for walk testing, the apparatus comprising:

the distance prediction module is used for determining a walking distance predicted value of the user according to the motion data of the user and the motion type of the user;

The distance prediction module is further used for determining a compensation distance according to the motion type and the motion intensity of the user, and the motion data, the motion type and the motion intensity are corresponding to a first motion process of the user;

The distance prediction module is further configured to determine a first walking distance of the user according to the walking distance prediction value and the compensation distance.

17. The apparatus of claim 16, wherein the apparatus further comprises:

the data acquisition module is used for acquiring the motion data and the physiological data of the user in the first motion process of the user;

The distance prediction module is further used for determining the motion type of the user according to the motion data;

And the intensity determining module is used for determining the exercise intensity of the user according to the exercise type and the physiological data.

18. The apparatus of claim 17, wherein the intensity determination module is specifically configured to:

19. The apparatus according to any one of claims 16 to 18, wherein the distance prediction module is specifically configured to:

20. The apparatus according to any one of claims 16 to 19, further comprising:

The result integration module is used for acquiring N walking distances of the user, the N walking distances are in one-to-one correspondence with N movement processes of the user, and the N walking distances comprise the first walking distance;

The result integration module is further used for determining walking distance output values of the user according to the N walking distances and resting physiological data of the user, wherein the resting physiological data are physiological data in a non-motion state.

21. The apparatus of claim 20, wherein the result integration module is specifically configured to:

22. The apparatus of any one of claims 16 to 21, wherein the walk test is a six minute walk test.

23. The apparatus of claim 22, wherein the apparatus further comprises:

and the reminding module is used for reminding the user to start the six-minute walking test when the effective movement data of the user are not detected in M continuous days.

24. The apparatus according to claim 22 or 23, characterized in that the apparatus further comprises:

and the information synchronization module is used for realizing information synchronization between the mobile phone and the wearable equipment when the mobile phone of the user and the wearable equipment are connected.

25. The apparatus of any one of claims 22 to 24, wherein the reminder module is further for:

26. The apparatus according to any one of claims 22 to 25, further comprising:

And the result presentation module is used for displaying a six-minute walking test report on a display screen of the mobile phone or the wearable device of the user when the six-minute walking test is finished.

27. The apparatus of any one of claims 16 to 26, wherein the motion data comprises one or more of stride frequency, gait, speed, distance.

28. The apparatus of any one of claims 16 to 27, wherein the physiological data comprises one or more of heart rate, blood oxygen, blood pressure.

29. The apparatus of any one of claims 16 to 28, wherein the type of movement comprises one or more of walking, running, riding, stair climbing, swimming.

30. An electronic device, comprising:

one or more processors;

One or more memories;

And one or more computer programs, wherein the one or more computer programs are stored in the one or more memories, the one or more computer programs comprising instructions, which when executed by the one or more processors, cause the electronic device to perform the method of any of claims 1-15.

31. A computer readable storage medium, characterized in that the storage medium has stored therein a program or instructions which, when executed, implement the method of any one of claims 1 to 15.

32. A chip having instructions stored therein which, when executed on a device, cause the chip to perform the method of any of claims 1 to 15.