CN112205973A

CN112205973A - Intelligent wearable device-based cardiopulmonary endurance measurement method and system

Info

Publication number: CN112205973A
Application number: CN202011096062.9A
Authority: CN
Inventors: 高理升; 李关东; 叶玉琪; 王艺桦; 张瑞骐; 马祖长; 许杨; 王涛; 王辉; 李云龙; 胡天骄; 孙怡宁; 杨先军; 陈焱焱; 周旭; 孙少明
Original assignee: Hefei Institutes of Physical Science of CAS
Current assignee: Hefei Institutes of Physical Science of CAS
Priority date: 2020-10-14
Filing date: 2020-10-14
Publication date: 2021-01-12
Anticipated expiration: 2040-10-14
Also published as: CN112205973B

Abstract

The invention provides a cardio-pulmonary endurance measuring method and system based on intelligent wearable equipment, wherein the method comprises the steps of collecting the resting heart rate of a user before an experiment by utilizing the intelligent wearable equipment; and acquiring real-time heart rate and walking speed in the test process, calculating according to a PCI index formula to obtain quantitative indexes, and measuring and evaluating the heart-lung endurance. The system based on the measurement method comprises the following steps: the sensor data acquisition module is used for acquiring the real-time heart rate and the walking speed of the user in the test; the intelligent wearable device system control module is used for data processing, timing reminding and communication data analysis; a wireless communication module; and the user terminal processing module is used for calculating and evaluating the cardiopulmonary endurance and displaying data. The indexes of the intelligent wearable device do not need strict experimental protocols, the device automatically detects the motion state of the user, the data is real and effective, the cost of manual guidance and measurement in the cardiopulmonary endurance test project can be reduced, the functions of the intelligent wearable device are further expanded, and the practicability of the intelligent wearable device is improved.

Description

Intelligent wearable device-based cardiopulmonary endurance measurement method and system

Technical Field

The invention relates to the field of cardiopulmonary endurance measurement, in particular to a cardiopulmonary endurance measurement method and system based on intelligent wearable equipment.

Background

The heart and lung endurance comprehensively reflects the capability of human body to take, transport and utilize oxygen, and relates to the functions of heart pumping blood, lung oxygen uptake and gas exchange, the efficiency of blood circulation system carrying oxygen to all parts of the body, and the function of muscle and other tissues to utilize oxygen. The measurement of the cardiopulmonary endurance has important significance for the subject to know the physical condition of the subject and guide the body-building training.

The professional cardiopulmonary endurance test method comprises the steps that a subject performs extreme exercise on exercise equipment, a breathing mask continuously monitors the content and the flow rate of breathing gas, and the maximum oxygen uptake (VO) of the subject is obtained through calculation_2Max) And evaluating the heart and lung endurance. Simple cardiorespiratory endurance measurement methods include step test, 6-minute walking, Cooper twelve-minute running, fixed-distance running, and the like. The professional test method has high accuracy, but needs professional instruments, is complex to operate, and has injury risk when a subject performs extreme sports. The simple test method needs manual guidance and cannot be automatically realized.

Disclosure of Invention

In order to solve the technical problems, the invention provides a cardio-pulmonary endurance measurement method and system based on intelligent wearable equipment, which are used for conveniently and quickly realizing the cardio-pulmonary endurance measurement function in step tests and 6-minute walking test projects.

The invention provides a cardio-pulmonary endurance measuring method and system based on intelligent wearable equipment, which can automatically guide a user to perform a step test and a 6-minute walking test, and arrange the monitored exercise heart rate and walking speed into a physiological consumption index PCI to evaluate the cardio-pulmonary endurance level of the user. Compared with the independent judgment index in the traditional test, the PCI index is suitable for various test types, the burden of a breath test method is avoided, a brand-new method for evaluating the cardio-pulmonary endurance level is added compared with other test equipment, the cardio-pulmonary endurance is measured by the aid of the intelligent wearable equipment, the self-measurement of the testee is facilitated, and reference is provided for the testee to know the physical ability condition of the testee.

The technical scheme of the invention is as follows: a heart and lung endurance measurement method based on intelligent wearable equipment comprises the following steps:

step 1, logging in an APP of a user;

step 2, selecting a test item type from the APP, wherein the item type comprises a step test and a 6-minute walking test;

step 3, before the test is formally started, the user keeps a rest state, and the intelligent wearable device automatically starts to acquire the rest heart rate of the user;

step 4, clicking a starting exercise option to formally start a test after the preparation is finished, providing an instruction for the user action by the intelligent wearable device and the APP according to the requirement of the item type, and monitoring whether the user timely completes the action according to the requirement;

step 5, collecting exercise heart rate and walking speed data of a user in the test process;

and 6, calculating according to a PCI index formula to obtain a quantitative index, and comparing the quantitative index with a reference standard to realize measurement and evaluation of the cardiopulmonary endurance.

Further, in step 2, when the user selects the step test item, the method specifically includes:

under the prompt of the APP, the user normally wears the intelligent wearable device on the wrist, and meanwhile selects and confirms the left-hand or right-hand wearable device in the APP; the resting state is kept before the formal test is started, and the resting heart rate of the user is automatically measured after the intelligent wearable device detects that the user enters the stable resting state; after the preparation is finished, clicking the starting exercise option to formally start a step testing link; the intelligent wearable device performs short vibration prompt at the frequency of once every 0.5 second in the movement process, the user performs one step of action each time the user vibrates, each step of action device can detect whether the user completes the step-up and step-down action in time according to the requirement, and each 4 steps of action is a complete step-up and step-down action; after the exercise starts, the intelligent wearable equipment immediately counts time and collects exercise heart rate and walking speed; after completing the repeated actions for 3 minutes, the equipment sends out long vibration to prompt the end of the exercise, and the heart rate measurement of the last 10 seconds is waited; data acquisition finishes the back, sends data to APP through the bluetooth, and APP calculates and obtains the PCI index, compares with reference standard at last, makes the aassessment to user's cardiopulmonary endurance level.

Further, in the step 2, when the user selects the 6-minute walking test item, the method specifically includes:

under the prompt of the APP, the user normally wears the intelligent wearable device on the wrist; the resting state is kept before the formal test is started, and the resting heart rate of the user can be automatically measured after the intelligent wearable device detects that the user enters the stable resting state; after the preparation is finished, clicking the starting exercise option to formally start a 6-minute walking test link; after walking begins, the user walks directly in a running platform or a corridor; the intelligent wearable equipment is used for timing and collecting the exercise heart rate and the walking speed; after walking for 6 minutes, the equipment sends out long vibration to prompt the end of exercise, and the heart rate measurement of the last 10 seconds is waited; data acquisition finishes the back, sends data to APP through the bluetooth, and APP calculates and obtains the PCI index, compares with reference standard at last, makes the aassessment to user's cardiopulmonary endurance level.

Further, in step 5, intelligence wearing equipment will gather a heart rate in every 10 seconds in 2 minutes under the quiescent condition, and the average value of 12 heart rates is taken as the quiescent heart rate, and in the motion process equipment respectively in the 30 seconds after the motion begins, in the last 60 seconds of motion and in the 10 seconds that the motion was finished after the motion three time quantum gather heart rate average value, and meanwhile the walking speed of user is recorded in step to equipment.

Further, in the step 6, the PCI index specifically means: the parameters for evaluating the human body motion ability in the walking state have certain linear relation with the oxygen uptake. The subject is in a resting state, after the heart rate is stabilized, counting is carried out every 10 seconds within 2 minutes, and the average value of the 12 heart rates is taken as resting HR; then moving for 6 minutes at walking speed (walking speed), respectively recording the unsteady state heart rate (the mean value of the heart rates after 30s of movement start), the steady state heart rate (the mean value of the heart rates after the last 60s of movement) and the heart rates after movement (the mean value of the heart rates after the movement), representing the exercise heart rate (walking HR) by the mean value of the three heart rates, obtaining a conclusion through repeated tests and data analysis, wherein a certain linear relation exists between the ratio of the difference value of the resting heart rate and the walking heart rate of a human body to the walking speed and the maximum oxygen uptake amount, and providing a calculation formula of a physiological consumption index:

the indirect cardiopulmonary function testing method based on the physiological consumption index can substantially and truly reflect the cardiopulmonary endurance level of a subject no matter whether the walking heart rate is the unsteady state heart rate, the steady state heart rate or the heart rate after exercise. In order to reduce the influence caused by the deviation of one state detection value, the average value of the non-steady state heart rate, the steady state heart rate and the exercise heart rate is calculated to be used as the exercise heart rate.

According to another aspect of the present invention, a cardiopulmonary endurance measurement system based on an intelligent wearable device is provided, including:

the sensor data acquisition module is used for acquiring data of heart rate and walking speed by a sensor;

the intelligent wearable equipment system control module is used for processing, timing reminding, motion state monitoring and analyzing communication data acquired by the sensor;

the wireless communication module is used for realizing a Bluetooth wireless communication function between the intelligent wearable device and the mobile phone terminal;

and the user terminal processing module is used for calculating the quantitative index, evaluating the calculation result and displaying data.

Further, in the process of performing a step test and a 6-minute walking test, the intelligent wearable device system control module sends out vibration in a designated test link to prompt a user to start or end or execute actions according to a certain beat. The intelligent wearable device simultaneously monitors the motion state of the user, and ensures that the user completes actions according to requirements, so that the collected data can more accurately reflect the real level of the user in each state, and the obtained PCI index is more real and effective.

Further, the user terminal processing module is configured to:

setting user information and setting motion parameters;

playing guidance audio and timing reminding;

processing the exercise data, calculating a PCI index and assessing the cardio-pulmonary endurance;

displaying the measurement result in a software interface;

and storing data, namely storing user information and measurement data.

Further, when the step test and the 6-minute walking test are carried out, the user terminal processing module controls the intelligent wearable device indicator lamp to emit light through Bluetooth communication, or the screen of the intelligent wearable device displays the current motion, so that the effect of prompting the user is achieved.

Further, in the process of performing a step test and a 6-minute walking test, the terminal APP broadcasts the specified action to be executed in the current link, and the user follows the instruction to complete the specified action.

Further, the terminal APP performs timing according to fixed time specified by the test, and reminds the user that the action stage is completed when timing starts and ends.

Further, the terminal APP provides an interface supporting display of the two cardiopulmonary endurance test items, the PCI index is calculated according to the heart rate and the walking distance information received from the intelligent wearable device, the PCI index is compared with a reference standard to evaluate, and finally the interface of the test measurement result is displayed.

Further, the user terminal processing module processes the exercise data by using the cardiopulmonary endurance measurement method of any one of claims 1 to 5, and performs a cardiopulmonary endurance evaluation for a step test and a 6-minute walk test.

Further, the terminal APP stores the personal information added by the user and the measurement result obtained after the movement in a classified manner.

Has the advantages that:

the cardio-pulmonary endurance measuring method and system based on the intelligent wearable device can make up for the defects of the prior art, heart rate and walking speed data are collected through the sensor on the intelligent wearable device, the reality and accuracy of the collected data are ensured through the motion detection function, and the quantitative index is calculated by using the method provided by the invention, so that the cardio-pulmonary endurance measuring function is conveniently and quickly realized. The method uses the quantitative index PCI index without a strict experimental protocol, is theoretically suitable for various different types of cardiopulmonary endurance test items, and can automatically complete the measurement work in the exercise process only by wearing intelligent wearable equipment, thereby reducing the cost of manual guidance and measurement in the cardiopulmonary endurance test items.

Drawings

Fig. 1 is a flow chart of a cardiopulmonary endurance measurement method based on an intelligent wearable device provided by the invention;

FIG. 2 is a schematic diagram of the calibration of an acceleration sensor coordinate system in a bracelet according to the present invention;

FIG. 3 is a flow chart of a step test based on an intelligent wearable device provided by the invention;

fig. 4 is a flowchart of detecting a resting state of a user by using the intelligent wearable device provided by the invention;

FIG. 5 is a schematic diagram of an intelligent wearable device detecting a step test action provided by the invention;

FIG. 6 is a flow chart of a method for testing steps of the intelligent wearable device provided by the invention;

FIG. 7 is a flow chart of a 6-minute walking test based on an intelligent wearable device provided by the invention;

fig. 8 is a structural diagram of a cardiopulmonary endurance measurement system based on an intelligent wearable device provided by the invention.

Detailed Description

The technical solutions in the embodiments of the present invention will be described clearly and completely with reference to the accompanying drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, rather than all embodiments, and all other embodiments obtained by a person skilled in the art based on the embodiments of the present invention belong to the protection scope of the present invention without creative efforts.

The invention provides a cardiopulmonary endurance measurement method and system based on intelligent wearable equipment, which are used for conveniently and quickly realizing the cardiopulmonary endurance measurement function. The method and the system are based on the same technical conception, and because the principle of solving the problems of the method and the system is similar, the implementation of the system and the method can be mutually referred, and repeated parts are not repeated.

In the embodiment of the invention, the intelligent wearable equipment is portable intelligent equipment. The device is at least built-in with a heart rate sensor, a triaxial acceleration sensor, or the device can also be connected with an externally deployed sensor module. Some examples of smart wearable devices are: smart phones, smart watches, smart bracelets, smart glasses, and other sports accessories or wearable accessories, and the like, which are not limited herein.

According to one embodiment of the invention, a cardiopulmonary endurance measurement method based on intelligent wearable equipment is provided; as shown in fig. 1, a flowchart of a cardiopulmonary endurance measurement method based on an intelligent wearable device is provided, in the method, a user selects a test type in a mobile phone APP, and the APP provides two test types: bench test and 6 minute walk test. Normally wear intelligent wearing equipment on the wrist under APP's suggestion, keep the rest state, equipment detects and judges can begin to gather the rest rhythm of the heart automatically after for the rest state. After beginning the experiment, the user follows the instruction of APP and accomplishes the regulation action, constantly gathers user's real-time rhythm of the heart at this in-process intelligence wearing equipment, acquires the rate of motion, monitors user's motion state simultaneously, supervises the user and accomplishes the action as required, and after whole experiment, cell-phone APP carries out calculation processing with the data that receive, obtains quantization index PCI index, compares with reference standard afterwards, realizes the aassessment measurement to this user's cardiopulmonary endurance level.

Further, the method is mainly applicable to the following application scenarios: bench test and 6 minute walk test. These two tests differ in their implementation.

First, the step test, the 6-minute walk test, and the PCI index are explained to facilitate understanding by those skilled in the art.

The step test is simply that the left leg and the right leg are alternately stepped on the steps to test the adaptation level of the cardiopulmonary function. During testing, a subject stands vertically in front of the steps and moves up and down according to a certain beat. The user has to step up and down each time every 2 seconds, 30 times per minute for 3 minutes. A complete up-down step process comprises the following steps: firstly, one foot steps on the steps, then the other foot steps on the steps, the two legs are straightened, then the foot steps of the steps are stepped on, and finally the other foot steps are stepped on. When the user needs to do the tests by turns with the left leg and the right leg, the upper body and the two legs must be straightened after going up and down the steps each time, and the knees cannot be bent. After the repeated actions are finished, the user sits on the chair immediately and statically, and records that the exercise is stopped for 1 minute to 1 minute and a half minute,

To represent the transformation from the geodetic coordinate system e to the carrier coordinate system b. The third column of the rotation matrix is actually the description of the z-axis unit vector in system b. And the transposition of the rotation matrix

Third row vector [ c ]₁₃ c₂₃ c₃₃]I.e. the original rotation matrix

The third column of vectors. Therefore, the temperature of the molten metal is controlled,

i.e. the description of the e-system z-axis direction unit vector, i.e. the gravity vector g, in the b-system. Meanwhile, the description of the gravity vector (or the vector in the opposite direction) in the b system is the values of the three directions measured by the three-axis acceleration sensor. Thus, it is possible to provide

The third row vector is actually the output vector of the acceleration sensor, which is the key of the attitude calculation.

Fig. 3 is a step test flow chart based on the intelligent wearable device provided by the invention, and the whole test flow includes the following steps:

step S1: the user clicks a step test item in a mobile phone APP, the user normally wears the intelligent wearable device on the wrist under the prompt of the APP, meanwhile, the user clicks and confirms that the device is worn by the left hand or the right hand in the APP, and after the preparation is finished, a starting option is clicked to start a test link;

step S2: under the prompt of the APP, the user should keep a resting state before the formal test is started, the intelligent wearable device automatically starts to measure the resting heart rate of the user, and meanwhile, the APP explains the action to be executed by the formal test to the user;

step S3: in the process of a rest state, after the heart rate of a user is stable, the intelligent wearable device collects the heart rate every 10 seconds within 2 minutes, the average value of the heart rates of 12 times is taken as the rest heart rate, after the measurement is finished, the APP can prompt the completion of the measurement work in the stage, after the user finishes the preparation, the user clicks a starting exercise option to formally start a step test link, the APP sends out voice, and the device sends out long vibration to indicate that an exercise stage starts;

step S4: the intelligent wearable device performs short vibration prompt at the frequency of once every 0.5 second in the movement process, the user should perform one-step action by vibration every time, complete step-up and step-down actions are performed every 4 steps, and the device monitors whether the user completes the actions according to the requirements or not in real time;

step S5: after the exercise starts, timing is started immediately by the intelligent wearable device, heart rate mean values are collected in three time periods of 30 seconds after the exercise starts, 60 seconds after the exercise finishes and 10 seconds after the exercise finishes respectively, meanwhile, the intelligent wearable device can synchronously record the walking speed of a user, and step tests are fixed in action frequency, so that the difference of actual speed measurement values in each test is not large;

step S6: the APP reminds the user of preparing for finishing 15 seconds before the stage is finished, after 3 minutes of repeated actions are finished, the intelligent wearable device sends out long vibration to prompt the user to finish the movement, and the user sits down statically according to the APP prompt;

step S7: data acquisition finishes, sends data to APP through the bluetooth, and APP rethread foretell PCI computational formula obtains the PCI index, compares with reference standard at last, obtains and shows user's cardiopulmonary endurance level grade on the cell-phone.

Further, fig. 4 is a flowchart of detecting the resting state of the user by the intelligent wearable device provided by the present invention, soIn the step S2, the intelligent wearable device automatically detects the resting state of the user, and the specific method is as follows: the user should satisfy three conditions when in a resting state: user inactivity, low heart rate, less fluctuation in heart rate variation. These three conditions can be measured and determined by the tri-axial accelerometer and heart rate sensor, respectively. First, the acceleration value measured by the three-axis accelerometer is a ═ { ax, ay, az }, and when the user is in an inactive state, the accelerations in the three axes should all be close to 0, so that the combined acceleration is the sum of the accelerations

However, considering that the sensor may drift, a threshold value is set to ε, if the acceleration is combined

Then the time is determined to be inactive. The user can not necessarily acquire the true resting heart rate in an inactive state, the reason is related to the psychological activity of the user during testing, when the user is in nervous and excited emotion during testing, the heart rate change fluctuation is large, and even if the user keeps sitting still, the acquired heart rate is not the resting heart rate of the user. Therefore, when heart rate data HR acquired by a heart rate sensor is less than or equal to Ε, and Δ HR is less than or equal to δ, the user in the time period is determined to be in a resting state, wherein the Ε is a set heart rate threshold value, the threshold value is determined by characteristics such as age, gender, life habits and the like, the average of 75 times per minute is about the adult heart rate in the resting state, and the fluctuation range of the normal adult heart rate is 60-100 times per minute. When in an excited state, the heart rate is obviously increased and exceeds the range, and the data can be used as a threshold reference value; delta is a heart rate fluctuation threshold, which is related to a maximum heart rate threshold, and the value is suggested as a percentage of the maximum heart rate. In summary, an appropriate time interval T1 is set, during which the acceleration, if any, is measured continuously

Constant, continuous measurement of the heart rate HR<≦ Ε and heart rate fluctuation Δ HR<If δ is always true, thenAnd judging that the user enters a stable resting state, and indicating that the work of continuously acquiring resting heart rate can be started. On the contrary, when above-mentioned condition can not satisfy in T1 completely, then indicate that this user does not enter stable resting state for a while, gather resting heart rate data this moment and will be inaccurate, APP suggestion user keeps resting state and carries out deep breathing simultaneously and alleviates the mood, and original data and timing are abandoned to intelligent wearing equipment, the detection of a new round of T1 time is restarted.

Further, the intelligent wearable device monitors the resting state of the user while collecting the resting heart rate in the step S3, and the specific method thereof is as follows: during the two-minute acquisition process, the triaxial accelerometer continuously measures the triaxial acceleration data

The time indicates that the user is not in a resting state at the moment, and the heart rate fluctuation brought along with the resting state affects the accuracy of the measurement result. In the heart rate collected every 10 seconds, if the heart rate HR collected is the same as the heart rate HR collected>E or Δ HR>Delta, indicating that the user is now excited, the heart rate collected is not the true resting heart rate and the data should be discarded. In summary, setting a suitable time interval T2, T2 suggests that the time interval may be 10 seconds in synchronization with the heart rate acquisition if the resultant acceleration is detected during that time interval

Or the heart rate HR acquired during the period>eAE or heart rate fluctuation Δ HR>If delta, judging that the current time period of the user is not in a stable resting state, prompting the user to keep the resting state and simultaneously performing deep breathing to relieve emotion by the APP, and discarding data in the time period by the intelligent wearable device; if the user is judged not to enter the stable rest state within n T2 time periods, the intelligent wearable device discards all the collected data and returns to the step S2 to restart the detection of the rest state, and the value of n is determined according to the test condition and suggests that the reference value is 3.

Further, the intelligent wearable device monitors whether the user completes the action as required in real time in step S4, and the specific method includes:

when a user normally wears the intelligent wearable device on the wrist and the arm naturally hangs down, the carrier coordinate system b rotates 90 degrees anticlockwise around the X axis relative to the reference coordinate system e, when the user goes up and down steps, the intelligent wearable device swings up and down along with the arm, and the movement process can be regarded as rotation movement around the Z axis.

The rotation matrix for a known rotation φ about the X-axis is represented as:

the rotation matrix around the Z-axis by ψ is expressed as:

the rotation matrix in the X-Z rotation order is then represented as:

the third row vector is the projection of the gravity vector g in the carrier coordinate system. The output of the acceleration sensor is a ═ ax, ay, az ═ sin (ψ) × sin (Φ), sin (Φ) × cos (ψ), cos (Φ) }, where Φ is-90 °, so that the value of ψ can be calculated by collecting the X-axis and Y-axis output quantities of the acceleration sensor. In practice, during the step descending process, the data directly output by the accelerometer cannot accurately calculate the angle of rotation around the Z axis because the motion of the body in the front-back and up-down directions generates additional acceleration, and therefore, the acceleration generated by the body motion needs to be calculated so as to be removed from the sensor data when the angle is calculated.

Fig. 5 is a schematic diagram of step testing actions of the intelligent wearable device provided by the invention, and the four-step actions of the step testing can be divided into two processes: an upper step and a lower step; each process can be divided into two stages. For the stair climbing process: in the first stage, the left leg is stepped up, the left arm swings backwards, the right arm swings forwards, and the gravity center of the body does not rise; in the second stage, the gravity center of the body begins to rise, the right leg also ascends the step, the left arm swings forwards, and the right arm swings backwards. For the following step procedure: in the first stage, the left leg firstly goes down the step, the gravity center of the body also descends, the left arm swings backwards, and the right arm swings forwards; in the second stage, the right leg also goes down the step, at the moment, the gravity center of the body does not descend any more, the left arm swings forwards, and the right arm swings backwards.

Taking a left arm wearing intelligent wearing equipment as an example, the arms swing backwards in the first stage of the upper step and the first stage of the lower step, and in the first stage of the lower step, in addition to the acceleration generated by the swinging of the arms, the acceleration generated by the backward movement of the gravity center of the body is also arranged in the X-axis direction, and the acceleration generated by the descending of the gravity center of the body is also arranged in the Y-axis direction; the arms swing forwards in the second stage of the upper step and the second stage of the lower step, and in the second stage of the upper step, the acceleration generated by the swinging of the arms, the acceleration generated by the forward movement of the gravity center of the body and the acceleration generated by the descending of the gravity center of the body are added in the X-axis direction and the Y-axis direction.

According to the analysis, X-axis acceleration data measured by the intelligent wearable equipment in the first stage of the upper step is recorded as

The acceleration of the arm swinging backwards on the X axis is denoted as a_x'; the measured Y-axis acceleration data of the apparatus is recorded as

The acceleration of the arm swing on the Y axis is denoted as a_y. Then the equation is listed according to the analysis:

recording X-axis acceleration data measured by intelligent wearable equipment at second stage of climbing steps

Addition of arm swinging forward on X axisThe speed is denoted as a_xAcceleration due to forward movement of body center of gravity is recorded

The measured Y-axis acceleration data of the apparatus is recorded as

The acceleration due to the rise of the body's center of gravity is recorded as

Then the equation is listed according to the analysis:

recording X-axis acceleration data measured by intelligent wearable equipment at first stage of lower step

The acceleration caused by the backward shift of the body's center of gravity is recorded as

The measured Y-axis acceleration data of the device are respectively recorded as

The acceleration due to the lowering of the body's centre of gravity is recorded as

Then the equation is listed according to the analysis:

recording X-axis acceleration data measured by intelligent wearable equipment at second stage of lower step

The measured Y-axis acceleration data of the apparatus is recorded as

Then the equation is listed according to the analysis:

the above equation is combined to calculate: acceleration of upper step body gravity center forward movement

Acceleration of body center of gravity rise

Acceleration of downward step body center of gravity backward movement

Acceleration of lowering of body center of gravity

For the first stage of the upper step and the second stage of the lower step, the data acquired by the three-axis acceleration sensor can be directly used for attitude calculation, and the acceleration generated by the body weight center change in the data needs to be subtracted in the second stage of the upper step and the first stage of the lower step to be used for attitude calculation.

The method comprises the steps that an arm naturally hangs down to serve as a reference of an angle of a swing arm, the arm swings forwards to serve as the positive direction of the angle, a fixed upper limit threshold and a fixed lower limit threshold are set according to collected angle changes, the arm swings backwards to enable an angle psi to be gradually reduced in the first stage of an upper step and the first stage of a lower step, and the arm continues to descend to pass through the lower limit threshold after reaching a zero reference after being lower than the upper limit threshold; and in the second stage of the upper step and the second stage of the lower step, the arm swings forwards to enable the angle psi to be gradually increased, and after the angle psi is higher than the lower limit threshold value, the arm continuously rises to pass through the upper limit threshold value after reaching the zero reference.

Fig. 6 is a flowchart of a testing method for detecting steps of an intelligent wearable device provided by the present invention, when the intelligent wearable device is in a corresponding stage, the system will firstly analyze and judge the change process of the swing arm angle, specifically, detect and judge the action of the stage according to the change direction of the angle, whether the angle passes through the upper and lower threshold values and the sequence, and if the change process requirement of the swing arm angle corresponding to the stage cannot be met, judge that the user cannot complete the action in the stage as required in time. After the arm swing angle condition is met, corresponding threshold values are set aiming at the acceleration change of the body gravity center, the system can judge the action of the user in the corresponding stage by combining the change of the body gravity center acceleration, specifically, in the second stage of the upper step, the acceleration generated by the forward movement and the rising of the body gravity center is respectively larger than the respective set threshold values, and the system can judge the action of the upper step only after the condition is met; in the first stage of the downstairs, the absolute values of the acceleration generated by the backward movement and the descending of the gravity center of the body are respectively larger than the respective set threshold values, and the system can judge the downstairs movement only after the condition is met. Taking four stages as an action period, and when more than two stages in the action period are judged to be not in accordance with the action by the system, the action period is considered to be not in accordance with the requirement, and the system sends out a prompt to remind a user to test according to the requirement; and when the test is judged to be not satisfactory in k continuous periods, stopping the test, and restarting to execute the step S4, wherein the motion data of the test is also discarded, and the value of k is determined according to the test condition, and the recommended reference value is 3. When the right arm wears the intelligent wearing equipment for testing, the swing arm direction is opposite to that of the left arm in each stage, but no difference exists in the change of the body gravity center, so that the acceleration calculation method generated by the change of the body gravity center is the same as that of the left arm. When the first stage of the upper step and the first stage of the lower step are carried out, the arm swings forwards to enable the angle psi to be gradually increased, and after the angle psi is higher than the lower limit threshold value, the arm continuously rises to pass through the upper limit threshold value after reaching the zero reference; and in the second stage of the upper step and the second stage of the lower step, the arm swings backwards to enable the angle psi to be gradually reduced, and after the angle psi is lower than the upper limit threshold value, the arm continues to descend to pass through the lower limit threshold value after reaching the zero reference. Therefore, the judgment process of the swing arm angle in the right arm wearing condition is opposite to that of the left arm, and the body gravity center acceleration judgment is not different.

Fig. 7 is a flowchart of a 6-minute walking test based on an intelligent wearable device, where the whole test flow includes the following steps:

step S1: the user clicks a 6-minute walking test item in the mobile phone APP, and the user normally wears the intelligent wearable device on the wrist under the prompt of the APP;

step S2: under the prompt of the APP, the user should keep a rest state for at least 10 minutes before the formal test is started, and the APP reminds the user that the rest heart rate is to be detected and explains the action to be executed by the formal test to the user;

step S3: in the process of a rest state, after the heart rate of a user is stable, the intelligent wearable device collects the heart rate every 10 seconds within 2 minutes, the average value of the heart rates of 12 times is taken as the rest heart rate, the APP can prompt the completion of the measurement work in the stage after the measurement is finished, a user clicks a starting exercise option to formally start a walking test link after the preparation of the user is finished, and the intelligent wearable device sends long vibration to indicate that a walking stage starts;

step S4: after walking starts, the user directly walks in a running platform or a corridor, the intelligent wearable device starts timing, heart rate mean values are collected in three time periods of 30 seconds after the start of movement, 60 seconds after the last movement and 10 seconds after the end of movement respectively, and meanwhile the intelligent wearable device synchronously records the walking speed of the user;

step S5: timing when the APP starts a walking test, reminding a user of preparing for finishing in advance for 15 seconds, after walking for 6 minutes, simultaneously sending long vibration by the APP voice broadcast and the intelligent wearable equipment to remind the user of finishing walking, standing, and waiting for the last 10 seconds of heart rate measurement;

step S6: data acquisition finishes, sends data to APP through the bluetooth, and APP rethread foretell PCI computational formula obtains the PCI index, compares with reference standard at last, obtains and shows user's cardiopulmonary endurance level grade on the cell-phone.

Further, fig. 4 is a flowchart of detecting the resting state of the user by the intelligent wearable device provided by the present invention, and the specific method of automatically detecting the resting state of the user by the intelligent wearable device in step S2 includes: the user should satisfy three conditions when in a resting state: user inactivity, low heart rate, less fluctuation in heart rate variation. These three conditions may be defined by a three-axis accelerometerAnd heart rate sensors measure and make decisions. First, the acceleration value measured by the three-axis accelerometer is a ═ { ax, ay, az }, and when the user is in an inactive state, the accelerations in the three axes should all be close to 0, so that the combined acceleration is the sum of the accelerations

Constant, continuous measurement of the heart rate HR<Angle and heart rate fluctuation Δ HR<If δ is always true, the user is judged to enter a stable resting state, which indicates that the work of continuously acquiring the resting heart rate can be started. On the contrary, when the above condition is not completely satisfied in T1, it indicates that the user has not entered a stable resting state, and at this time, the collection of resting heart rate data will be inaccurate, aPP prompts the user to keep a resting state and simultaneously carry out deep breathing to relieve emotion, and the intelligent wearable device discards original data and timing and restarts a new round of T1 time detection.

Or the heart rate HR acquired during the period>eAE or heart rate fluctuation Δ HR>If delta, judging that the current time period of the user is not in a stable resting state, prompting the user to keep the resting state and simultaneously performing deep breathing to relieve emotion by the APP, and discarding data in the time period by the intelligent wearable device; if the user is judged not to enter the stable rest state within n T2 time periods, the intelligent wearable device discards all the collected data and returns to the step S2 to restart the detection of the rest state, and the value of n is determined according to the test condition and suggests that the reference value is 3. It should be noted that the above embodiments only exemplify some application scenarios, but those skilled in the art should understand that the present invention is not limited to the described application scenarios, because the test indexes and methods can be applied to other application scenarios with the same function according to the present invention, and the related scenarios are not necessarily required by the present invention.

According to another embodiment of the present invention, as shown in fig. 8, a structure diagram of a cardiopulmonary endurance measurement system based on an intelligent wearable device provided by the present invention includes:

Furthermore, the sensor data acquisition module performs software filtering on data, performs data interaction with a communication interface of a central processing unit chip of the intelligent wearable device through the sensor, reads sensor information in real time, and performs filtering processing on the acquired data;

the intelligent wearable device system control module controls the intelligent wearable device to match with data acquisition and vibration reminding functions within a specified time period in the test process so as to meet the test requirements;

the intelligent wearable device system control module can control the intelligent wearable device to emit vibration to prompt the user to start and end or execute actions according to a certain beat when the intelligent wearable device is in a specified test ring;

the intelligent wearable device bracelet system control module can continuously monitor the motion state of a user in the process of testing the user, and ensures that the user completes actions according to requirements, so that the collected data can accurately reflect the real level of the user in each state, and the obtained PCI index is more real and effective.

The wireless communication module is used for packaging the processed data in the intelligent wearable device and wirelessly communicating with the intelligent mobile phone through a Bluetooth wireless protocol to realize data interaction with the mobile phone end; the Bluetooth communication function with the intelligent wearable equipment is realized by calling API service provided by a Bluetooth official party, and data interaction with the equipment is realized;

further, the user terminal processing module is configured to:

setting user information and setting motion parameters;

playing guidance audio and timing reminding;

displaying the measurement result in a software interface;

and storing data, namely storing user information and measurement data.

User terminal processing module through bluetooth communication control intelligence wearing equipment pilot lamp state and screen display module, because part old-fashioned wearing equipment is not equipped with the display screen, only has the pilot lamp, consequently for most intelligent wearing equipment on the adaptation market, can control this type of equipment pilot lamp and send bright representation equipment and be in the detection state. For the intelligent wearable device equipped with the display screen, the screen of the device displays the current ongoing movement so as to prompt the user.

The user information setting and motion parameter setting module is used for providing a function of adding personal related information of a user and realizing the login verification function of the APP; certain motion parameters can be set, such as motion time and the like;

playing guidance audio, timing and reminding a module, controlling a terminal APP to broadcast a specified action to be executed in a current link in a user test process, controlling the terminal APP to time according to fixed time specified by a test after the user follows the specified action, and reminding the user that the action stage is finished when the time is started and finished;

the exercise data are processed, a PCI index and cardiopulmonary endurance evaluation module is calculated, a quantitative index PCI index is calculated according to the heart rate and walking speed data received from the intelligent wearable equipment, and meanwhile, the heart rate and walking speed data are compared with a reference standard to evaluate the cardiopulmonary endurance;

a measurement result module is displayed in a software interface, and an interface of the measurement result of the test is displayed on a terminal APP;

and the data storage module is used for storing user information and measurement data and storing personal information added by a user and measurement results obtained after movement in a classified manner.

It should be noted that, for simplicity of description, the above-mentioned method embodiments or examples are described as a series of acts or combination of acts, but those skilled in the art will recognize that the present invention is not limited by the order of acts described, as some steps may occur in other orders or concurrently in accordance with the invention. Further, those skilled in the art should also appreciate that the embodiments or examples described in this specification are presently preferred, and that the acts and modules illustrated are not necessarily required to practice the invention.

The above description is only for the preferred embodiment of the present invention, but the scope of the present invention is not limited thereto, and any person skilled in the art should be considered to be within the technical scope of the present invention, and the technical solutions and the inventive concepts thereof according to the present invention should be equivalent or changed within the scope of the present invention.

Claims

1. A heart and lung endurance measurement method based on intelligent wearable equipment comprises the following steps:

step 1, logging in an APP of a user;

2. The cardiopulmonary endurance measurement method based on intelligent wearable device according to claim 1, wherein in step 2, when the user selects a step test item, the method specifically includes:

3. The cardiopulmonary endurance measurement method based on intelligent wearable device according to claim 1, where in the step 2, when the user selects a 6-minute walking test item, the method specifically includes:

4. The cardiopulmonary endurance measurement method based on an intelligent wearable device according to claim 1, wherein in the step 5, the intelligent wearable device in a resting state collects the heart rate every 10 seconds within 2 minutes, an average value of 12 heart rates is taken as the resting heart rate, and during exercise, the device collects the heart rate average values in three time periods, namely 30 seconds after the exercise starts, 60 seconds after the exercise ends and 10 seconds after the exercise ends, and simultaneously the device synchronously records the walking speed of the user.

5. The cardiopulmonary endurance measurement method based on intelligent wearable device according to claim 1, wherein in step 6, the PCI index means specifically: the parameters for evaluating the human body exercise capacity in a walking state have a certain linear relation with oxygen uptake, a subject is in a resting state, after the heart rate is stable, counting is carried out every 10 seconds within 2 minutes, and the average value of 12 heart rates is taken as resting HR; then, moving for 6 minutes at walking speed, respectively recording the unstable state heart rate, namely the mean value of the heart rates 30s after the start of movement, the stable state heart rate, namely the mean value of the heart rates 60s after the last movement and the heart rate after the movement, namely the mean value of the heart rates 10s after the movement, representing the moving heart rate walking HR by the mean values of the three heart rates, and providing a calculation formula of the physiological consumption index:

6. the cardiopulmonary endurance measurement method based on intelligent wearable device according to claim 1, wherein in step 3, the automatic start of collecting the resting heart rate of the user by the intelligent wearable device includes:

the user should satisfy three conditions when in a resting state: user inactivity, heart rate below a threshold, heart rate variation fluctuation less than a threshold; the three conditions are measured and judged by a triaxial accelerometer and a heart rate sensor respectively;

first, the acceleration value measured by the three-axis accelerometer is a ═ { ax, ay, az }, and when the user is in an inactive state, the accelerations in the three axes should all be close to 0, so that the combined acceleration is the sum of the accelerations

Considering that the sensor will drift, a threshold value is set to epsilon, if acceleration is combined

Then the time is determined to be inactive; when the heart rate data HR acquired by the heart rate sensor is less than or equal to AE and meanwhile the Delta HR is less than or equal to Delta, determining that the user in the time slot is in a resting state, wherein the AE is a set heart rate threshold; delta is the heart rate fluctuation threshold, and a time interval T1 is set during which the acceleration is continuously measured if the combined acceleration is continuously measured

Constant, continuous measurement of the heart rate HR<≦ Ε and heart rate fluctuation Δ HR<If the value is not more than δ, judging that the user enters a stable resting state, and indicating that the user can start to continuously acquire resting heart rate; on the contrary, when above-mentioned condition can not satisfy in T1 completely, then indicate that this user does not enter stable resting state for a while, gather resting heart rate data this moment and will be inaccurate, APP suggestion user keeps resting state and carries out deep breathing simultaneously and alleviates the mood, and original data and timing are abandoned to intelligent wearing equipment, the detection of a new round of T1 time is restarted.

7. The cardiopulmonary endurance measurement method based on intelligent wearable device according to claim 1, wherein in step 4, it is monitored whether the user completes the action in time as required, and specifically includes:

recording X-axis acceleration data measured by intelligent wearable equipment at first stage of going up step

The acceleration generated in the X-axis by swinging the arm backward is recorded as a'_x(ii) a The measured Y-axis acceleration data of the apparatus is recorded as

The acceleration of the arm swing on the Y axis is denoted as a_y(ii) a Then the equation is listed according to the analysis:

The acceleration of the arm swinging forward on the X axis is denoted as a_xAcceleration due to forward movement of body center of gravity is recorded

The measured Y-axis acceleration data of the apparatus is recorded as

The acceleration due to the rise of the body's center of gravity is recorded as

Then the equation is listed according to the analysis:

Then the equation is listed according to the analysis:

The measured Y-axis acceleration data of the apparatus is recorded as

Then the equation is listed according to the analysis:

Acceleration of body center of gravity rise

Acceleration of downward step body center of gravity backward movement

Acceleration of lowering of body center of gravity

For the first stage of the upper step and the second stage of the lower step, the data acquired by the three-axis acceleration sensor can be directly used for attitude calculation, and the acceleration generated by the body weight center change in the data needs to be subtracted for attitude calculation in the second stage of the upper step and the first stage of the lower step.

8. The cardiopulmonary endurance measurement method based on intelligent wearable device according to claim 1, wherein in step 4, it is monitored whether the user completes the action in time as required, further comprising:

when the swing arm angle is in a corresponding stage, the system firstly analyzes and judges the change process of the swing arm angle, specifically, the change direction of the angle, whether the change process passes through upper and lower limit thresholds and the action of the stage is detected and judged through the sequence, if the change process requirement of the swing arm angle corresponding to the stage cannot be met, the user is judged that the action of the stage cannot be completed as required in time; after the arm swing angle condition is met, corresponding threshold values are set aiming at the acceleration change of the body gravity center, the system can judge the action of the user in the corresponding stage by combining the change of the body gravity center acceleration, specifically, in the second stage of the upper step, the acceleration generated by the forward movement and the rising of the body gravity center is respectively larger than the respective set threshold values, and the system can judge the action of the upper step only after the condition is met; in the first stage of descending steps, the absolute values of the acceleration generated by the backward movement and the descending of the gravity center of the body are respectively greater than the respective set threshold values, and the system can judge the motion of descending steps only after the condition is met; taking four stages as an action period, and when more than two stages in the action period are judged to be not in accordance with the action by the system, the action period is considered to be not in accordance with the requirement, and the system sends out a prompt to remind a user to test according to the requirement; and when the test is judged to be not satisfactory in k continuous periods, stopping the test, and restarting to execute the step 4, wherein the motion data of the test is also discarded.

9. The utility model provides a heart lung endurance measurement system based on intelligence wearing equipment which characterized in that includes:

10. The system for measuring the cardiopulmonary endurance based on the intelligent wearable device according to claim 9, wherein in the process of performing the step test and the 6-minute walk test, the system control module of the intelligent wearable device sends out a vibration in a designated test link to prompt the user to start, end or execute an action according to a certain beat; intelligent wearing equipment is simultaneously.

11. The cardiopulmonary endurance measurement system based on intelligent wearable device of claim 10, wherein motion state monitoring, monitoring user motion state, ensuring that the user performs actions as required includes:

The acceleration of the arm swing on the Y axis is recorded asa_y(ii) a Then the equation is listed according to the analysis:

The measured Y-axis acceleration data of the apparatus is recorded as

The acceleration due to the rise of the body's center of gravity is recorded as

Then the equation is listed according to the analysis:

Then the equation is listed according to the analysis:

The measured Y-axis acceleration data of the apparatus is recorded as

Then the equation is listed according to the analysis:

Acceleration of body center of gravity rise

Acceleration of downward step body center of gravity backward movement

Acceleration of lowering of body center of gravity

12. The cardiopulmonary endurance measurement system based on intelligent wearable device of claim 10, wherein motion state monitoring, monitoring user motion state, ensuring that user accomplishes action as required, further comprises:

when the swing arm angle is in a corresponding stage, the system firstly analyzes and judges the change process of the swing arm angle, specifically, the change direction of the angle, whether the change process passes through upper and lower limit thresholds and the action of the stage is detected and judged through the sequence, if the change process requirement of the swing arm angle corresponding to the stage cannot be met, the user is judged that the action of the stage cannot be completed as required in time; after the arm swing angle condition is met, corresponding threshold values are set aiming at the acceleration change of the body gravity center, the system can judge the action of the user in the corresponding stage by combining the change of the body gravity center acceleration, specifically, in the second stage of the upper step, the acceleration generated by the forward movement and the rising of the body gravity center is respectively larger than the respective set threshold values, and the system can judge the action of the upper step only after the condition is met; in the first stage of descending steps, the absolute values of the acceleration generated by the backward movement and the descending of the gravity center of the body are respectively greater than the respective set threshold values, and the system can judge the motion of descending steps only after the condition is met; taking four stages as an action period, and when more than two stages in the action period are judged to be not in accordance with the action by the system, the action period is considered to be not in accordance with the requirement, and the system sends out a prompt to remind a user to test according to the requirement; and when the test is judged to be not satisfactory in k continuous periods, stopping the test, restarting the test, and discarding the motion data of the test.

13. The cardiopulmonary endurance measurement system based on intelligent wearable device of claim 9, wherein the user terminal processing module is configured to:

setting user information and setting motion parameters;

playing guidance audio and timing reminding;

displaying the measurement result in a software interface;

and storing data, namely storing user information and measurement data.

14. The system for measuring the cardiopulmonary endurance based on the intelligent wearable device according to claim 9, wherein in the process of performing the step test and the 6-minute walk test, the user terminal processing module controls the intelligent wearable device indicator lamp to emit light through bluetooth communication, or the intelligent wearable device screen displays the current ongoing movement, so as to prompt the user;

the terminal APP broadcasts the specified action to be executed in the current link, and the user follows the instruction to complete the specified action; timing according to the fixed time specified by the test, and reminding the user that the action stage is finished when the timing is started and ended;

terminal APP provides the interface that supports to show above-mentioned two kinds of cardiopulmonary endurance test projects, calculates the PCI index according to the rhythm of the heart and the walking distance information that receive from intelligent wearing equipment simultaneously.