CN108888247B - Aerobic capacity testing method, device and system and data acquisition equipment - Google Patents
Aerobic capacity testing method, device and system and data acquisition equipment Download PDFInfo
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Abstract
The invention provides an aerobic capacity testing method, device, system and data acquisition equipment, and belongs to the technical field of aerobic capacity testing. According to the aerobic capacity testing method, device and system and the data acquisition equipment, when the testing instruction is received, the wearing state of the data acquisition equipment is detected; if the wearing state of the data acquisition equipment is good, acquiring test data; from the test data, the aerobic capacity of the subject wearing the data acquisition device is determined. The test method is not required to be carried out in an exhausted state, the detection result is objective, the test of the aerobic capacity can be independently completed by a subject, and the experience degree of a user is improved.
Description
Technical Field
The invention relates to the technical field of aerobic capacity testing, in particular to an aerobic capacity testing method, device, system and data acquisition equipment.
Background
The aerobic capacity is the capacity of oxygen taken in from the outside to the inside of the body through the blood circulation and transported to the tissues such as active muscles and taken in and utilized by the tissues such as muscles in a unit time, and is the comprehensive capacity of oxygen-taking capacity, oxygen-transporting capacity and oxygen-using capacity. Aerobic capacity is the capacity of a human body to maintain movement by aerobic oxidation energy supply depending on energy substances, and reflects the cardio-pulmonary working capacity and the physical fitness level of the human body. Testing aerobic capacity, and providing information on physical function level to mobilize interest of the subject in exercise and promote participation of the subject in exercise; can help the subject to make a sports prescription and achieve good body-building effect. .
Existing methods of aerobic capacity testing typically require the subject to move to a maximum speed and maintain, i.e., a state of exhaustion, while testing. The technical identification method for judging whether the testee reaches the exhaustion state is complex, and the subjective feeling perception difference of the testee on the exhaustion is large, so that the testee is not easy to have uniform standard and is easy to have large deviation. Also, there are often various discomforts for the subject that accompany the exhaustion state when tested: moderate or severe chest pain, sudden drop in systolic blood pressure of more than 10mmhg, and neurological symptoms such as ataxia, dizziness or near syncope with other ischemic symptoms. The test experience is poor, the challenge is high, and the wide popularization is not facilitated.
Disclosure of Invention
In view of the above-mentioned problems in the prior art, the present invention provides a method, an apparatus, a system and a data collecting device for aerobic capacity test, according to which the aerobic capacity test can be independently performed by a subject without a depletion state.
In a first aspect, an embodiment of the present invention provides an aerobic capacity testing method, including:
when a test instruction is received, detecting the wearing state of the data acquisition equipment;
if the wearing state of the data acquisition equipment is good, acquiring test data;
from the test data, determining the aerobic capacity of the subject wearing the data acquisition device.
In combination with the first aspect, the embodiments of the present invention provide a first possible implementation manner of the first aspect, wherein,
a step of determining the aerobic capacity of the subject wearing the data acquisition device from the test data, comprising:
determining a maximum heart rate reference value of the subject according to the age of the subject acquired in advance;
determining a maximum speed reference value of the subject according to the maximum heart rate reference value and a pre-acquired resting heart rate of the subject; determining an actual average speed of the subject from the travel distance data; obtaining a regression function of the corresponding relation between the heart rate and the movement speed of the subject according to the parameters;
determining a predicted value of the maximum oxygen uptake according to the regression function;
determining the aerobic capacity of the subject from the predicted maximum oxygen uptake value.
In combination with the first possible implementation manner of the first aspect, the present invention provides a second possible implementation manner of the first aspect, wherein,
a step of determining the aerobic capacity of the subject from the predicted maximum oxygen uptake value, comprising:
determining whether the historical testing times are greater than or equal to the set times;
if not, taking the predicted value of the maximum oxygen uptake as the maximum oxygen uptake, and determining the aerobic capacity of the subject;
if so, determining the aerobic capacity of the subject currently measured according to the predicted maximum oxygen uptake value currently measured and the aerobic capacity of the subject measured in the designated historical test.
In combination with the second possible implementation manner of the first aspect, the present invention provides a third possible implementation manner of the first aspect, wherein,
the step of determining the aerobic capacity of the subject based on the predicted maximum oxygen uptake value currently measured and the aerobic capacity of the subject measured in the specified historical test comprises:
and smoothly updating the currently measured maximum oxygen uptake prediction value by adopting the aerobic capacity of the subject measured in the specified historical test, calculating the maximum oxygen uptake, and determining the aerobic capacity of the subject.
In combination with the first aspect, the present examples provide a fourth possible implementation manner of the first aspect, wherein,
the step of obtaining test data comprises:
receiving heart rate data within a test time period transmitted by the data acquisition equipment;
acquiring travel distance data in a test time period through a GPS module;
alternatively, the first and second electrodes may be,
receiving heart rate data and action sign data in a test time period transmitted by the data acquisition equipment;
and determining the travel distance data in the test time period according to the action sign data.
In combination with the fourth possible implementation manner of the first aspect, the present invention provides a fifth possible implementation manner of the first aspect, wherein,
the action sign data comprise swing arm amplitude and movement times; determining travel distance data within a test time period according to the action sign data, comprising:
determining the step length of the subject in the current test through the swing arm amplitude according to the corresponding relation between the swing arm amplitude and the step length measured in advance;
determining the number of steps according to the number of the movement times;
and determining travel distance data according to the step length and the step number.
In a second aspect, an embodiment of the present invention further provides an aerobic capacity testing apparatus, including:
the wearing state detection module is used for detecting the wearing state of the data acquisition equipment when receiving the test instruction;
the test data acquisition module is used for acquiring test data if the wearing state of the data acquisition equipment is good;
an aerobic capacity determination module for determining the aerobic capacity of the subject wearing the data acquisition device based on the test data.
In a third aspect, an embodiment of the present invention further provides an aerobic capacity testing system, including a processor, a memory and a data acquisition device, where the memory and the data acquisition device are connected to the processor;
the memory has stored thereon a computer program which, when executed by the processor, performs the method of any of the first aspects.
In a fourth aspect, an embodiment of the present invention further provides a data acquisition device, including a microprocessor, a heart rate data acquisition module, an action sign data acquisition module, and a communication module, which are connected to the microprocessor; the communication module is configured to perform data transmission with a processor, and the processor is configured to perform the method according to any one of the first aspect.
With reference to the fourth aspect, an embodiment of the present invention provides a first possible implementation manner of the fourth aspect, where the apparatus further includes an input module connected to the microprocessor, and configured to receive an age or a test instruction input by a user.
In a fifth aspect, the embodiment of the present invention further provides a computer-readable storage medium storing computer program instructions for implementing the above-mentioned method for testing aerobic capacity.
The embodiment of the invention has the following beneficial effects:
according to the aerobic capacity testing method, the device, the system and the data acquisition equipment provided by the embodiment of the invention, when the testing instruction is received, the wearing state of the data acquisition equipment is detected; if the wearing state of the data acquisition equipment is good, acquiring test data; from the test data, the aerobic capacity of the subject wearing the data acquisition device is determined. The test method is not required to be carried out in an exhausted state, the detection result is objective, the test of the aerobic capacity can be independently completed by a subject, and the experience degree of a user is improved.
Additional features and advantages of the invention will be set forth in the description which follows, and in part will be obvious from the description, or may be learned by practice of the invention. The objectives and other advantages of the invention will be realized and attained by the structure particularly pointed out in the written description and claims hereof as well as the appended drawings.
In order to make the aforementioned and other objects, features and advantages of the present invention comprehensible, preferred embodiments accompanied with figures are described in detail below.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, and it is obvious that the drawings in the following description are some embodiments of the present invention, and other drawings can be obtained by those skilled in the art without creative efforts.
FIG. 1 is a flow chart of a method for testing aerobic capacity according to an embodiment of the present invention;
FIG. 2 is a schematic diagram of the sensing of a three-axis accelerometer according to an embodiment of the invention;
FIG. 3 is a schematic diagram of the relationship between a three-axis accelerometer chip and a wrist wearing part according to an embodiment of the invention;
FIG. 4 is a schematic diagram of the accelerometer signals in the frequency domain during running according to an embodiment of the invention;
FIG. 5 is a block diagram of an aerobic testing apparatus according to an embodiment of the present invention;
fig. 6 is a block diagram of a data acquisition device according to an embodiment of the present invention;
fig. 7 is a block diagram of an aerobic capacity testing system according to an embodiment of the present invention.
Detailed Description
To make the objects, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings, and it is apparent that the described embodiments are some, but not all embodiments of the present invention. The components of embodiments of the present invention generally described and illustrated in the figures herein may be arranged and designed in a wide variety of different configurations. Thus, the following detailed description of the embodiments of the present invention, presented in the figures, is not intended to limit the scope of the invention, as claimed, but is merely representative of selected embodiments of the invention. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
Aiming at the problems that the conventional aerobic capacity test method needs a test subject to reach an exhausted state, and the test experience of the test subject is poor, so that the test method is not beneficial to wide popularization, the embodiment of the invention provides the aerobic capacity test method.
Example one
The present embodiment provides a method for testing aerobic capacity. The aerobic capacity reflects the Cardio-pulmonary working capacity of the human body and may also reflect the physical level of the human body, and may also be referred to as Cardio-pulmonary function or Cardio-pulmonary Fitness (CRF). Testing aerobic capacity can provide information on the level of physical function to mobilize a subject's interest in exercise and to promote participation in exercise; can help the subject to make a sports prescription and achieve good body-building effect. Maximum oxygen uptake, maximum aerobic Capacity, Physical Work Capacity (PWC), cardiovascular endurance, cardiopulmonary endurance, and the like, can all be used to indicate a person's aerobic Capacity.
This example measures the aerobic capacity of a subject by measuring the maximum oxygen uptake. The maximum oxygen intake is the maximum amount of oxygen that can be taken into active muscles and utilized by the muscles per unit time (usually, in units of minutes) when the system functions such as circulation and respiration reach the maximum level in an exhaustive exercise in which a large number of muscle groups are involved. The aerobic capacity test method of this example is an indirect test method. The indirect test method is a method in which a subject performs a subatmospheric exercise and the maximum oxygen uptake is calculated from values such as oxygen uptake, heart rate, or work reaching a certain amount. The theoretical basis is as follows: the heart rate and the load have a linear relation, when the load is maximum, the heart rate is maximum, the steady state heart rate can be measured by utilizing the movement under the steady state load, the steady state heart rate can be achieved by carrying out the subatmospheric constant power load movement for a plurality of minutes, the maximum load capacity can be predicted according to the subatmospheric load capacity, and the maximum load capacity can represent the maximum oxygen uptake, so that the cardiopulmonary capacity of the subject can be obtained.
Fig. 1 shows a flow chart of the method for testing aerobic capacity provided in this embodiment, and as shown in fig. 1, the method includes the following steps:
and S102, detecting the wearing state of the data acquisition equipment when the test instruction is received.
In conducting the aerobic capacity test, the subject is required to perform a sub-polar constant load exercise. For example, the subject can run on a relatively flat ground at a free constant speed for a test period (running time) of 10 minutes or more, and the specific running time can be selected according to the habit preferences of the user or can be a default of 12 minutes. In this example, the running for 12 minutes is described as an example.
In the test process, a user needs to wear data acquisition equipment for measuring test data such as heart rate data, distance data and sports sign data. The data acquisition device can be bracelet-shaped or a bracelet with a dial. The aerobic capacity testing method can be executed by a microprocessor of the data acquisition equipment, and the data acquisition equipment can also be connected with the mobile terminal and executed by a processor of the mobile terminal.
Taking a bracelet worn by the data acquisition device as a wrist as an example for explanation, the data acquisition device can acquire a test instruction of '12 minutes running' initiated by a user through an input module. The input module may be a touch screen, such as a capacitive touch screen, and the pressing time of the user may be determined by a capacitance change in a preset area exceeding a predetermined time. For example, a user clicks a touch screen of a bracelet to enter a test main interface of 12 minutes running, the user presses any point or designated area on the test main interface for a long time to obtain a test instruction for entering the test, and the microprocessor obtains a long pressing action of the test main interface of 12 minutes running to obtain the test instruction.
When the exercise is carried out, each sensor of the data acquisition equipment is used for acquiring corresponding signals, the exercise has different degrees of influence on the demand signals of each sensor, and the good wearing state (the sensor is worn on a flat body surface with good blood circulation, but the tightness is not too tight) can obtain better signal quality such as heart rate and exercise, and further can obtain effective test data.
After the user initiates the aerobic capacity test for 12 minutes running, the wearing state of the data acquisition device can be detected in the following two ways.
The first mode is as follows: the data acquisition equipment can be uniformly provided with a plurality of distance sensors, and if the distance value measured by each distance sensor is less than or equal to a preset distance value, the wearing state of the data acquisition equipment is determined to be good. Illustratively, two distance sensors are used for illustration, and the two distance sensors may be disposed at two ends of the bracelet, and respectively measure the distance between two parts of the bracelet and the human body. And evaluating the wearing state of the bracelet according to the distance values d1 and d2 obtained by the two distance sensors. If D1, D2 all exceed predetermined distance value D1, can think that the bracelet is not worn or wears more laxly, data acquisition equipment can send the warning to the user, the suggestion adjustment mode of wearing. If D1 or D2 is larger than the predetermined distance value D1 and the difference between D1 and D2 is larger than or equal to the predetermined distance value D2, the wearing inclination is considered, and a reminder for adjusting the wearing position is sent. And prompting to enter the test if both D1 and D2 are less than or equal to the predetermined distance value D1, or both D1 and D2 are less than or equal to the predetermined distance value D1, and the difference between D1 and D2 is less than the predetermined distance value D2, and the wearing state of the data acquisition equipment is considered to be good.
The second way is: data acquisition equipment is provided with pressure sensor including connecting the dial plate on the bracelet on the dial plate, if the pressure value that pressure sensor measured is within in the pressure range of predetermineeing, then confirms that data acquisition equipment's wearing state is good. For example, pressure sensors are arranged at four corners (or two symmetrical sides) of a square dial bottom shell, whether the pressure level of the data acquisition to the pressure sensor is consistent or not is sensed, and the data of the ranging sensor is verified and calibrated. When the pressure value measured by the pressure sensor is larger than the preset maximum pressure value, the wearing is considered to be too tight, and the user is reminded to appropriately loosen the wearing in the modes of display, vibration and the like. When the pressure value measured by the pressure sensor is smaller than the preset minimum pressure value, the wearing is considered to be too loose or not worn, and the user can be reminded to appropriately adjust the wearing mode through modes such as display, vibration and the like. When the pressure value measured by the pressure sensor is within the preset pressure range, the wearing state of the data acquisition equipment is considered to be good. The preset pressure range refers to a range between a preset minimum pressure value and a preset maximum pressure value. If a plurality of pressure sensors are arranged on the dial plate, the pressure value measured by each pressure sensor is within the preset pressure range, and the wearing state of the data acquisition equipment can be determined to be good.
And step S104, if the wearing state of the data acquisition equipment is good, acquiring test data.
The good wearing can ensure that a test signal with better quality is obtained during running, thereby ensuring the accuracy of the tested action data and the heart rate data and ensuring the accuracy of the test. And after the wearing state of the equipment is determined to be good, entering a test mode, and acquiring test data by each sensor. The microprocessor or the processor acquires signals acquired by the sensors and determines related information, such as heart rate data according to the heart rate data acquisition module, action data such as action types, action amplitudes and postures, action times and the like according to the action sign data acquisition module.
In an optional embodiment, heart rate data within a test time period transmitted by the data acquisition device may be received; and acquiring the travel distance data in the test time period through the GPS module.
In another optional embodiment, heart rate data and action sign data in a test time period transmitted by the data acquisition device can be received; and determining travel distance data in the test time period according to the action sign data. The action sign data comprise swing arm amplitude and activity times; the average step length of a subject in the current test can be determined through the swing arm amplitude according to the corresponding relation between the swing arm amplitude and the average step length which are measured in advance; determining the number of steps according to the number of activities; travel distance data is then determined based on the average step size and the number of steps.
Determining travel distance data in the test time period according to the action sign data, according to the following principle:
during running, the swing arm of a person corresponds to the motion of the legs, one swing arm corresponds to one single leg (two steps), the number of swing arms corresponds to 1/2 steps of the user, and the frequency of the swing arm corresponds to 1/2 steps. The number of steps can thus be determined from the wrist device.
Furthermore, for the same person, when the person runs, the swing arm amplitude and the step length have a fixed corresponding relationship, and the corresponding relationship conforms to the following rule: the larger the swing arm amplitude, the larger the stride, i.e., the step length. During jogging, the swing arm has small amplitude and small step length, and during fast jogging, the swing arm has large amplitude and large step length. Therefore, according to the swing arm amplitude characteristics of the upper limbs, the step length of the person during running and traveling can be relatively determined. The step size feature can be used to obtain distance data according to this relationship, i.e. distance data is obtained in steps. When a person runs and finishes a swing arm period in the same time, the larger the amplitude of the swing arm is, the higher the movement speed of the wrist is, the larger the maximum acceleration value of the wrist is, and the larger the change of the acceleration is.
When the device is used for the first time or the first few times, the travel distance data in the corresponding running time period can be acquired through the GPS module because the corresponding relationship between the swing arm amplitude and the average step length of the subject is not determined. For example, the GPS module of the bracelet itself may be used to obtain the travel distance of 12 minutes from the beginning of the timer from zero to the end of the timing. If bracelet itself does not have the GPS module, then accessible communication module is connected with mobile device, calls mobile device's GPS module through mobile device's APP, by accomplishing the distance of marcing calculation during corresponding running.
Meanwhile, at the end of each running, according to the travel distance data D _ n measured by the GPS module and the total step number C _ n in the test period, the average step length SLmean _ n in a certain stable speed time period of the subject at the time of the running is calculated to be D _ n/C _ n, and the swing arm amplitude in the certain stable speed time period is determined. The swing arm amplitude can be represented by an average amplitude Amean _ n of an acceleration change cycle of the accelerometer in a certain axial direction in a period of stable speed. And recording a group of SLmean _ n and ocean _ n data in pairing mode. The average step length SLmean _ n and the average amplitude Amean _ n can also be calculated by taking the travel distance data D _ n and the step number C _ n of partial time periods during the aerobic test, preferably, if the total test time length is 12 minutes, the travel distance data D _ n and the average amplitude Amean _ n of the wrist swing arm amplitude are taken, and the data of the last 6 minutes or the last 3 minutes of the test can also be obtained in a sectional mode. When multiple sets of data of SLmean _ n and Amean _ n are generated after multiple tests, the correspondence between SLmean _ n and Amean _ n can be generated, for example, by generating a formula SLmean _ n-k 4-Amean _ n, the corresponding value of k4 of the subject can be determined. Where k4 may take multiple values in segments.
After determining the corresponding relationship between the average step size SLmean _ n and the average amplitude mean _ n in the time period of stable speed of the subject, the segmented average step size SLmean _ n can be calculated according to the formula SLmean _ n (k 4) mean _ n by obtaining the average amplitude mean _ n during aerobic test; meanwhile, the step number of each segment is determined according to the activity times of the equipment; and then 12 minutes of travel distance data was obtained based on the average step size.
Further, the amplitude of the acceleration change period is obtained as follows: during the running process of the human body, the accelerations generated in the vertical direction and the advancing direction are approximately sinusoidal along with time, for example, only the acceleration data of the acceleration axis in the vertical direction is subjected to analysis processing such as filtering, etc., to form a curve with peak-valley characteristics, the calculation of the running step number of the subject can be realized by comparing the curve characteristics with a threshold value, etc., and the amplitude of a pair of adjacent peaks and valleys is calculated, i.e., the amplitude of one swing arm during running can be correspondingly represented (the one swing arm during running forms one period of acceleration change).
The method for acquiring the sports sign data of the wearing part by the accelerometer is as follows.
The three-axis accelerometer can detect the acceleration of 3 perpendicular axes (total 6 directions), namely the acceleration of an X axis, a Y axis and a Z axis. When the bracelet is worn on a specific part of a human body (the wrist, the three-axis accelerometer chip of the bracelet is positioned on a relatively flat part connected with the back of the hand, and the outer side surface of the wrist is called below), the track of the action can be judged according to the change of the acceleration of 3 axes during the movement of the human body, and the characteristic of the action is identified.
The identification of motion characteristics or trajectories by the accelerometer is illustrated by one arm position during running: the acceleration sensing diagram of the three-axis accelerometer chip is shown in fig. 2 with the forearm in a horizontal position and the back of the hand facing away from the sagittal plane of the human body. The positive direction of the Y axis is upward, the positive direction of the Z axis is towards the direction of the human body trunk, the acceleration of the negative direction of the Y axis is 1 g, and the acceleration of the X axis and the Z axis is 0 g. In this posture shown in fig. 3, the relationship between the three-axis accelerometer chip and the wearing part of the wrist is schematically shown, wherein the shadow plane is a plane parallel to and close to the wearing part (the outer side of the wrist), and is a vertical plane.
Fig. 4 is an acceleration signal diagram obtained by analyzing and processing (including fourier transform, filtering, etc.) the acceleration signal of the y-axis after being collected, and since a period of acceleration change (e.g., from one peak to the next peak) corresponds to a period of the swing arm, a point a in the diagram indicates a position of the peak, and a point B indicates a position of a valley adjacent to and after the point a. A. The difference between the sampled values of the two points B, i.e. the amplitude, corresponds to the amplitude of the swing arm of the subject.
Step S106, determining the aerobic capacity of the subject wearing the data acquisition device according to the test data.
When the 12-minute run test is completed, the microprocessor or processor may determine the maximum oxygen uptake of the subject, i.e., the aerobic capacity of the subject, based on the heart rate data, the physical sign data, the distance traveled data, and a predetermined formula.
Specifically, step S106 may be divided into the following two steps:
a. at the end of each test, calculating a predicted maximum oxygen uptake value of the subject, wherein the used parameters comprise: subject age [ year ], resting heart rate HR _ rest [ bpm ], median heart rate HR _ mean [ bpm ] for the plateau session (last six minutes) heart rate in this run, travel distance data D [ km ] tested here;
b. checking the test as the test for the second time, and if the test times are less than the set times, taking the predicted value of the maximum oxygen uptake as the maximum oxygen uptake to determine the aerobic capacity of the subject; and if the test times are more than or equal to the set times, determining the aerobic capacity of the subject according to the predicted value of the currently determined maximum oxygen uptake and the maximum oxygen uptake determined in the appointed historical test. For example, the maximum oxygen uptake is calculated using the predicted value of the aerobic capacity of the subject measured in the specified historical test versus the currently measured maximum oxygen uptake, and the aerobic capacity of the subject is determined. Wherein the specified historical test may be the last test or the last few tests.
The specific method process of the step a comprises the following steps:
(1) and determining the maximum heart rate reference value of the subject according to the age of the subject acquired in advance.
The maximum heart rate reference value HRmax _ ref 207-0.7 age.
(2) Determining a maximum speed reference value of the subject according to the maximum heart rate reference value and a pre-acquired resting heart rate of the subject; maximum oxygen uptake reference value VO2max _ ref k1 HRmax _ ref/HR _ rest
Wherein VO2max _ ref is a maximum oxygen uptake reference value, HR _ rest is a resting heart rate, k1 is a coefficient, k1 is an interval (12,18) with a retrievable value, and the reference preset value is 15.3.
The resting heart rate, also called the resting heart rate, refers to the number of beats per minute in a resting state of waking and inactivity. The resting heart rate corresponds to the basal metabolic level of a human body, can reflect the cardio-pulmonary function reserve capacity of the human body, and has close relation with the aerobic capacity of the human body.
(3) Determining a maximum speed reference value of the subject according to the maximum oxygen uptake reference value.
The maximum speed reference value V _ max _ ref k2 VO2max _ ref + m1
Wherein, V _ max _ ref is a maximum speed reference value, k2 is a coefficient value range (0.04,0.1), a reference preset value is 0.06153, m1 is a constant value range (0.5,1), and the reference preset value is 0.7013.
(4) From the travel distance data, the actual average speed of the subject is determined.
Actual average speed V mean 5/3.6
Wherein V _ mean is the actual average speed, and D is the distance run out by the subject at the actual test at a constant speed of 12 minutes.
(5) And respectively bringing the speed zero and the corresponding resting heart rate, the actual average speed and the corresponding median heart rate, the maximum speed reference value and the corresponding maximum heart rate reference value into a set linear regression function, and determining the characteristic coefficient of the linear regression function.
Regression relationship formula (regression function) of heart rate and speed of subject: a X + b
Preferably, the vector X in the regression function is a speed, and values [0, V _ mean, V _ max _ ref ]; the vector Y heart rate, taken as [ HR _ rest, HR _ mean, HRmax _ ref ], may determine the individual characteristic coefficients a and b of the subject. HR _ mean is the median heart rate, and may take the value of the median of the measured heart rates during the heart rate stabilization period, i.e. the midpoint of the maximum and minimum values of the measured heart rate.
(6) And determining the maximum speed predicted value of the subject according to the characteristic coefficient and the maximum heart rate reference value.
Maximum speed predicted value V _ max _ pre ═ HRmax _ ref-b)/a
Where V _ max _ ref is the maximum speed predictor and HRmax _ ref is the maximum heart rate reference for the subject.
(7) And determining a predicted value of the maximum oxygen uptake according to the predicted value of the maximum speed.
The predicted maximum oxygen uptake value VO2max _ pre ═ k 3V _ max _ pre-m 2
VO2max reflects the aerobic capacity obtained in the test, and the unit is ml/kg/min; k3 is a coefficient, and the reference preset value is 16.0966, the value range of m2 as a constant is (10, 15), and the reference preset value is 11.2877.
The values of the coefficients k1, k2, m1 and m2 in the formula are obtained according to a large number of tests of the testees (heart rate and speed during the exhaustive run are compared with the maximum oxygen uptake of a gold standard to obtain the corresponding relation of the heart rate and the speed), the larger the test sample size is, the smaller the range of the values of the coefficients or parameters of the formula tends to be, and the more accurate the calculation result tends to be for any tester. When the test device such as a bracelet is provided for a subject or the subject purchases a bracelet product for use, the developer continuously updates the data volume of the test and adjusts the value of the coefficient parameter, so that the calculation result tends to be more accurate.
In the step a, a formula of the corresponding relation among the heart rate, the exercise speed and the maximum oxygen uptake suitable for a large number of people is known, the estimation/prediction formula of the maximum oxygen uptake with personal specificity is deduced by combining the exercise speed and the heart rate performance of individuals, and the maximum oxygen uptake is calculated, so that the aerobic capacity is determined.
In step b, there are various methods for smooth update, such as using kalman filtering, RLS filtering, etc. For example, smooth update available parameters include: the predicted value of the aerobic capacity of the last N times (the specific number of N can be determined according to a specific method), all the predicted values of the aerobic capacity measured historically, the aerobic capacity value in a historical test and the like, and the speed, the heart rate and the like in the test process can be used as smoothing parameters for smoothing. For example, the current test is the Nth test, using the predicted value of aerobic capacity from the last (Nth-1 th) time, VO2max _ r [ N ] is the maximum oxygen uptake output at the Nth test, i.e., the aerobic capacity of the subject. VO2max _ pre [ N ] is the predicted value of the maximum oxygen uptake in the Nth test. Setting a preset historical test time threshold, for example, the historical test threshold is 3, the processor firstly judges whether N-1 is greater than or equal to 3, such as N-1 is greater than or equal to 3, namely when N is greater than or equal to 4,
VO2max_r[N]＝VO2max_r[N-1]*u+VO2max_pre[N]*(1-u)
e.g. N-1 < 3, i.e. when N.ltoreq.3, VO2max _ r [ N ] ═ VO2max _ pre [ N ]
In the above formula, the value range of u is [0,1], the specific value of u is related to N (the larger N, the larger u value), and related to the number of days from the last test in the current test (the longer the number of days apart from the last test, the smaller u value), and when the number of days apart from the last test is greater than a certain threshold, for example, 14 days, N can be updated and calculated from 1.
When a test of 12-minute running is performed, the heart rate gradually rises in the first 3 to 5 minutes, and then keeps a relatively stable higher level, and the HR _ mean can be a heart rate count in the last 6 minutes, a heart rate count in the last 3 minutes, and the like.
Maximum heart rate refers to the maximum level that the heart rate reaches when the oxygen consumption and heart rate cannot continue to increase at maximum load intensity as the amount of exercise increases, oxygen consumption and heart rate also increase when carrying out the exercise load. HRmax is updated if it is detected at the time of the test that the user's actual maximum heart rate exceeds HRmax. Obtaining the heart rate according to a PPG (photoplethysmography) or ECG (ECG) principle of wearable equipment, and taking the heart rate generated by each calculation as HR _ est _ n, comparing the size of HR _ est _ n with HR _ est _ n +1 to obtain a larger value, comparing the larger value with HR _ est _ n +2, comparing the obtained larger value with HR _ est _ n +2, and repeating the steps until the actual maximum value of the heart rate of a measurement period in the test is HRmax _ test. Comparing HRmax _ test to HRmax determines whether to update HRmax.
In addition, the bracelet is provided with a resting heart rate acquisition method, the microprocessor acquires an accelerometer signal and a heart rate signal, and when the resting heart rate is calculated according to the heart rate signal when the human body with small activity in a period of time is judged to be in a resting state. Preferably, the resting heart rate is the heart rate at which the person in the morning wakes from sleep for a quiet period of time (e.g., 10 minutes). When conducting aerobic capacity, the value of the resting heart rate of the last measurement, e.g. within 3 or 14 days, is used. If the bracelet has no measured resting heart rate for the first time, the default resting heart rate is used, and the default resting heart rate can be set to be 60bpm for men and 70bpm for women; simultaneously, the suggestion user measures the rest rhythm of the heart when quiet state, or wears the bracelet and measures the rest rhythm of the heart when sleeping.
It should be noted that, when the method is applied, a description can be set at the APP of the mobile device, or a description is made in a voice/text manner at the bracelet, and the user is advised to run according to the self condition, and the user does not need to be exhaustive, and the running process is kept at a constant speed as much as possible. In selecting a running route, attention is paid to reducing resistance from wind, uneven ground, removing running interruptions caused by pedestrians or other conditions during running, and preferably, running in an open and flat place, a good GPS signal can be obtained to determine the running distance.
The aerobic capacity testing method provided by the embodiment of the invention does not need to use a large amount of professional equipment or assistance of professional persons, a user can finish the test according to the description, the testing method does not need to reach an exhausted state, and the method is free from strong physical discomfort, easy to accept by the user and easy to popularize and use in a large range. According to the method, the maximum oxygen uptake formula with individual characteristics is obtained, then the maximum oxygen uptake of the individual is estimated, and the estimation value is more accurate. Furthermore, smoothing is carried out according to the historical test result of the user, so that error factors during measurement are reduced, and the test result is closer to an actual value.
The embodiment of the invention also uses the running characteristics (swing arm amplitude) of the person to calculate the step length of the person, thereby completing the distance measurement during running, and separating from the dependence on the GPS, if the equipment is provided with the GPS, the GPS can be turned off to reduce the power consumption of the equipment; if the device does not have a GPS, the distance measurement can be completed independently without using the mobile device.
Example two
In accordance with the above method embodiments, the present embodiment provides an aerobic capacity testing device, as shown in fig. 5, the device includes:
the wearing state detection module 51 is used for detecting the wearing state of the data acquisition equipment when receiving the test instruction;
a test data obtaining module 52, configured to obtain test data if the wearing state of the data acquisition device is good;
and an aerobic capacity determination module 53 for determining the aerobic capacity of the subject wearing the data acquisition device based on the test data.
The device provided by the embodiment has the same implementation principle and technical effect as the foregoing embodiment, and for the sake of brief description, reference may be made to the corresponding contents in the foregoing method embodiment for the portion of the embodiment of the device that is not mentioned.
According to the aerobic capacity testing device provided by the embodiment of the invention, when a testing instruction is received, the wearing state of the data acquisition equipment is detected; if the wearing state of the data acquisition equipment is good, acquiring test data; from the test data, the aerobic capacity of the subject wearing the data acquisition device is determined. The test method is not required to be carried out in an exhausted state, the detection result is objective, the aerobic capacity test can be independently completed by the testee, and the user experience is improved.
EXAMPLE III
The embodiment of the invention also provides data acquisition equipment, which is wearable equipment, such as a bracelet, wherein the bracelet can be provided with a dial plate. As shown in fig. 6, the data acquisition device includes a microprocessor 11, a heart rate data acquisition module 12, an action sign data acquisition module 13, a GPS module 16 and a communication module 17 connected to the microprocessor 11.
The heart rate data acquisition module 12 is used for acquiring real-time heart rate data of the subject through a body surface, and the heart rate data acquisition module 12 may include a body surface electrode or a photoelectric sensor. If the photoelectric sensor is worn on the body surface of a human body, the reflection signal of the human body to light is acquired, and the reflection signal is sent to the processor to further determine human body physiological information such as heart rate.
The motion sign data acquisition module 13 includes a motion sensor, a counter, and the like, and the motion sensor may be, but is not limited to, an accelerometer, a gyroscope, a three-axis sensor, and the like. The motion sign data acquisition module 13 is configured to acquire motion characteristics of the subject, including swing arm amplitude, and the like, so as to determine motion, posture, motion type, and the like of the human body.
The GPS module 16 is used to measure the subject's travel distance data. The GPS module 16 may download the navigation system data to determine the relevant distance.
The communication module 17 may be a wired communication module or a wireless communication module, such as a bluetooth module, an infrared module, a radio frequency module, etc., and is configured to perform data transmission with a processor of the mobile terminal.
The heart rate data acquisition module 12, the action sign data acquisition module 13 and the GPS module 16 transmit the acquired test data to the microprocessor 11. The microprocessor calculates the aerobic capacity of the subject according to the method of the first embodiment, and sends the measured aerobic capacity value to the mobile terminal through the communication module. The microprocessor 11 may adopt a single chip microcomputer, and is configured to obtain a measurement instruction of a user, send a data acquisition instruction to each module, obtain and determine relevant information of distance, time, and heart rate, determine the aerobic capacity of the user according to a built-in aerobic capacity evaluation algorithm, and output the aerobic capacity to the input/output module for the user to check.
It will be appreciated that the data acquisition device may not include a GPS module. When the data acquisition device does not include a GPS module, the heart rate data acquisition module 12 and the action sign data acquisition module 13 transmit the acquired test data to the microprocessor. And the microprocessor sends the test data to a processor of the mobile terminal through the communication module. Calculating the aerobic capacity of the subject by the method of the first embodiment by the processor of the mobile terminal in combination with the GPS data of the mobile terminal.
Optionally, the data acquisition device may further comprise a timer 14, an input module 15, a display module 18 and a storage module 19 connected to the microprocessor 11. The timer 14 is used to time during the test. The input module 15 may be a key or a touch screen, and is configured to receive age information and a test start instruction input by a user. The display module 18 may be a display screen for displaying the test status and the test result, and various prompt messages. The storage module 19 may be configured to store the information collected by each information acquisition module and the data processed by the microprocessor, such as the step number, the heart rate, the motion, the calculated aerobic capacity data, and the like, as historical data.
The data acquisition equipment can also be provided with a power module for supplying power to the equipment.
Example four
An embodiment of the present invention further provides an aerobic capacity testing system, as shown in fig. 7, the system includes: a processor 21, a memory 22 connected to the processor 21 and the data acquisition device 10. This data acquisition equipment is wearable equipment, for example bracelet, can be provided with the dial plate on the bracelet. Specifically, reference may be made to the data acquisition device in embodiment three.
The processor 21 and the memory 22 may be provided on the mobile terminal. The mobile terminal may include, but is not limited to, a smartphone, a tablet computer, and the like.
The memory 22 may be used to store software programs and modules, such as program instructions/modules corresponding to the network sequence adjustment method and apparatus in the embodiment of the present invention, and the processor 21 executes various functional applications and data processing of the mobile terminal by running the software programs and modules stored in the memory 22, such as the method for testing oxygen capacity provided in the embodiment of the present invention. The memory 22 may mainly include a storage program area and a storage data area, wherein the storage program area may store an operating system, an application program required by at least one function (such as a sound playing function, an image playing function, etc.), and the like; the storage data area may store data (such as audio data, a phonebook, etc.) created according to the use of the mobile terminal, and the like. Further, the memory 22 may include high speed random access memory, and may also include non-volatile memory, such as at least one magnetic disk storage device, flash memory device, or other volatile solid state storage device.
The processor 21 is a control center of the mobile terminal, connects various parts of the entire mobile terminal using various interfaces and lines, and performs various functions of the mobile terminal and processes data by operating or executing software programs and/or modules stored in the memory 22 and calling data stored in the memory 22, thereby performing overall monitoring of the mobile terminal. Alternatively, processor 21 may include one or more processing units; alternatively, the processor 21 may integrate an application processor, which mainly handles operating systems, user interfaces, application programs, etc., and a modem processor, which mainly handles wireless communications. It will be appreciated that the modem processor described above may not be integrated into the processor 21.
The mobile terminal can also comprise a GPS unit and a wireless communication unit, and the wireless communication unit is used for communicating with the data acquisition equipment.
The following practical application example is given: XX (woman, 28 years old) is a fitness fan, exercise is often performed, recently, he wants to know the aerobic capacity of himself, he checks that the APP end has input personal information such as sex, age and the like, then wears a fitness bracelet, clicks a bracelet interface, enters a 12-minute running page, long-time enters according to interface selection, then the bracelet displays that "please connect to the mobile phone GPS", if the mobile phone APP is not started, the bracelet interface displays that "please start the mobile phone APP", XX starts the mobile phone APP, then the bracelet displays that "3", "2", "1" (automatically starts data acquisition) countdown after being connected to the mobile phone GPS, XX starts running, and the bracelet prompts "refuel and please keep constant speed" in the running process. In the test process, the mobile phone APP is always in an open state. After running for 12 minutes, the bracelet reminds the bracelet that the test is finished and the bracelet calls for rest (automatically ending data acquisition), and the bracelet automatically exits. Then the mobile phone App outputs the test result, and XX can check the running track, the heart rate track and the test result description of the XX at the APP, wherein VO2max can be displayed to be 50.0ml/kg/min, and the aerobic capacity is excellent.
Further, embodiments of the present invention also provide a machine-readable storage medium storing machine-executable instructions that, when invoked and executed by a processor, cause the processor to implement the above-described aerobic capacity test.
The aerobic capacity testing method, the device, the system and the data acquisition equipment provided by the embodiment of the invention have the same technical characteristics, so that the same technical problems can be solved, and the same technical effect can be achieved.
It should be noted that, in the embodiments provided in the present invention, it should be understood that the disclosed system and method can be implemented in other ways. The above-described embodiments of the apparatus are merely illustrative, and for example, the division of the units is only one logical division, and there may be other divisions when actually implemented, and for example, a plurality of units or components may be combined or integrated into another system, or some features may be omitted, or not executed. The units described as separate parts may or may not be physically separate, and parts displayed 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 can be selected according to actual needs to achieve the purpose of the solution of the embodiment.
In addition, functional units in the embodiments provided by the present invention may be integrated into one processing unit, or each unit may exist alone physically, or two or more units are integrated into 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 such understanding, the technical solution of the present invention may be embodied in the form of a software product, which is stored in a storage medium and includes instructions for causing a computer device (which may be a personal computer, a server, or a network device) to execute all or part of the steps of the method according to the embodiments of the present invention. And the aforementioned storage medium includes: a U-disk, a removable hard disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a magnetic disk or an optical disk, and other various media capable of storing program codes.
Furthermore, the terms "first," "second," and "third" are used for descriptive purposes only and are not to be construed as indicating or implying relative importance.
Finally, it should be noted that: the above-mentioned embodiments are only specific embodiments of the present invention, which are used for illustrating the technical solutions of the present invention and not for limiting the same, and the protection scope of the present invention is not limited thereto, although the present invention is described in detail with reference to the foregoing embodiments, those skilled in the art should understand that: any person skilled in the art can modify or easily conceive the technical solutions described in the foregoing embodiments or equivalent substitutes for some technical features within the technical scope of the present disclosure; such modifications, changes or substitutions do not depart from the spirit and scope of the embodiments of the present invention, and they should be construed as being included therein. Therefore, the protection scope of the present invention shall be subject to the protection scope of the claims.
Claims (9)
1. An aerobic capacity test method, comprising:
when a test instruction is received, detecting the wearing state of the data acquisition equipment;
if the wearing state of the data acquisition equipment is good, acquiring test data; the test data includes: testing heart rate data and travel distance data over a time period;
determining, from the test data, an aerobic capacity of the subject wearing the data acquisition device;
a step of determining the aerobic capacity of the subject wearing the data acquisition device from the test data, comprising:
determining a maximum heart rate reference value of the subject according to the age of the subject acquired in advance;
determining a maximum speed reference value of the subject according to the maximum heart rate reference value and a pre-acquired resting heart rate of the subject; determining an actual average speed of the subject from the travel distance data; obtaining a regression function of the corresponding relation between the heart rate and the movement speed of the subject according to the parameters;
determining a predicted value of the maximum oxygen uptake according to the regression function;
determining the aerobic capacity of the subject from the predicted maximum oxygen uptake value.
2. The method of claim 1, wherein the step of determining the aerobic capacity of the subject from the predicted maximum oxygen uptake value comprises:
determining whether the historical testing times are greater than or equal to the set times;
if not, taking the currently measured maximum oxygen uptake prediction value as the maximum oxygen uptake, and determining the aerobic capacity of the subject;
if so, determining the aerobic capacity of the subject currently measured according to the predicted maximum oxygen uptake value currently measured and the aerobic capacity of the subject measured in the designated historical test.
3. The method of claim 2, wherein said step of determining the aerobic capacity of said subject based on a current predicted value of said maximum oxygen uptake and the aerobic capacity of said subject measured in a given historical test comprises:
and smoothly updating the currently measured maximum oxygen uptake prediction value by adopting the aerobic capacity of the subject measured in the specified historical test, calculating the maximum oxygen uptake, and determining the aerobic capacity of the subject.
4. The method of claim 1, wherein the step of obtaining test data comprises:
receiving heart rate data within a test time period transmitted by the data acquisition equipment;
acquiring travel distance data in a test time period through a GPS module;
alternatively, the first and second electrodes may be,
receiving heart rate data and action sign data in a test time period transmitted by the data acquisition equipment;
and determining the travel distance data in the test time period according to the action sign data.
5. The method of claim 4, wherein the motion sign data includes arm swing amplitude and number of movements; determining travel distance data within a test time period according to the action sign data, comprising:
determining the step length of the subject in the current test through the swing arm amplitude according to the corresponding relation between the swing arm amplitude and the step length measured in advance;
determining the number of steps according to the number of the movement times;
and determining travel distance data according to the step length and the step number.
6. An aerobic capacity testing device, comprising:
the wearing state detection module is used for detecting the wearing state of the data acquisition equipment when receiving the test instruction;
the test data acquisition module is used for acquiring test data if the wearing state of the data acquisition equipment is good; the test data includes: testing heart rate data and travel distance data over a time period;
an aerobic capacity determination module for determining the aerobic capacity of the subject wearing the data acquisition device based on the test data;
the aerobic capacity determination module is further used for determining a maximum heart rate reference value of the subject according to the pre-acquired age of the subject; determining a maximum speed reference value of the subject according to the maximum heart rate reference value and a pre-acquired resting heart rate of the subject; determining an actual average speed of the subject from the travel distance data; obtaining a regression function of the corresponding relation between the heart rate and the movement speed of the subject according to the parameters; determining a predicted value of the maximum oxygen uptake according to the regression function; determining the aerobic capacity of the subject from the predicted maximum oxygen uptake value.
7. An aerobic capacity testing system, which is characterized by comprising a processor, a memory and a data acquisition device, wherein the memory and the data acquisition device are connected with the processor;
the memory has stored thereon a computer program which, when executed by the processor, performs the method of any of claims 1 to 5.
8. A data acquisition device is characterized by comprising a microprocessor, a heart rate data acquisition module, an action sign data acquisition module and a communication module, wherein the heart rate data acquisition module, the action sign data acquisition module and the communication module are connected with the microprocessor; the communication module is used for data transmission with a processor, and the processor is used for executing the method according to any one of claims 1 to 5.
9. The apparatus of claim 8, further comprising an input module coupled to the microprocessor for receiving user input of age or test instructions.
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