KR101333511B1 - Novel Method to detect Ventilatory-threshold in real-time - Google Patents

Abstract

The present invention can be measured while minimizing the restraint of the exerciser, using the heart rate reflecting the current physical condition of the exerciser, monitoring the exerciser's body information during the exercise and detecting the ventilation threshold time point in real time during the exercise, The present invention relates to a method for detecting a real time ventilation threshold point by monitoring heart rate changes.
The present invention provides a method for detecting a ventilation threshold time point while a subject is wearing an electrocardiogram electrode and exercising, detecting an R point that is the highest point in an electrocardiogram every cycle, and the previous window time in seconds from the R point. A heart rate averaging step for detecting a ventilation threshold time point, by detecting the number of RR intervals during the second period, and obtaining an average heart rate for the window time in seconds; Determining whether the heart rate average for the second window time, which is obtained in the heart rate averaging step for detecting the ventilation threshold time point, is greater than the preset baseline, and if it is larger than the reference line, the time of the heart rate average for the current second window time. Determining a threshold threshold candidate for determining a threshold threshold time; If, as a result of the ventilation threshold timing step, three of the five consecutive heart rate inputs are not greater than the baseline value, the baseline is multiplied by 0.95, that is, the baseline value is reduced to 0.95 times, and the heart rate for the current second window time A baseline readjustment step of determining an average time as a candidate for a ventilation threshold time point; If three out of five consecutive heart rate input is greater than the baseline value, determining the ventilation threshold time point to determine the ventilation threshold time candidate as the ventilation threshold time point; characterized in that it comprises a.

Description

{Novel Method to detect Ventilatory-threshold in real-time} by monitoring heart rate change

 The present invention relates to a method for detecting a real-time ventilation threshold time point by monitoring a change in heart rate, and more particularly, to measure while minimizing the restraint of the exerciser, and using the heart rate reflecting the exerciser's current physical condition, The present invention relates to a real-time ventilation threshold detection method through monitoring the heart rate change, which monitors body information and detects the ventilation threshold time in real time during exercise.

 During exercise, lactic acid and hydrogen ions (H +) in the muscle produced by glycolysis increase the concentration of hydrogen ions in the blood, and the produced lactic acid combines with hydrogen atoms to produce carbon dioxide. Increasing the partial pressure stimulates the respiratory control center and thus increases ventilation. In addition, as exercise intensity increases, peripheral chemical receptors are stimulated according to metabolic acid poisoning caused by increased hydrogen ion concentration, and thus the ventilation amount is greatly increased beyond the proportional relationship with the increase rate of carbon dioxide. The level of oxygen uptake or exercise intensity at the time of these metabolic acid poisoning events and changes related to respiratory gas exchange is called the ventilation threshold.

 Ventilation threshold is an objective and representative indicator for evaluating an individual's exercise ability, and by reducing the amount of exercise before a certain level of intensity that is not appropriate for an individual's fitness level according to the ventilation threshold, excessive exercise is prevented in advance and an appropriate amount of exercise Can be induced to perform

Physiological indicators for detecting ventilation thresholds are typically ventilation (Ventilation, VE), oxygen consumption (VO ₂ ), carbon dioxide production (VCO ₂ ), maximum oxygen uptake (VO ₂ max), etc. By using the physiological indicators can be measured by the breathing gas analyzer during exercise. Although this is a non-invasive method, it is necessary to wear a gas mask connected to the breathing gas analyzer during exercise, so that it may provide the athlete with restraint or discomfort and discomfort. In addition, respiratory gas analysis is limited in space because it is only possible in laboratory environments where expensive equipment is installed.

In order to minimize the restraint of the exerciser during exercise, many methods for determining the ventilation threshold time point using the heart rate without a gas respiratory analyzer have been studied. If you end more than once to know the result, there is a disadvantage that can not be detected during exercise.

Representative methods for measuring the ventilation threshold point include the Visual, V-slope, D-max, Cumulative summation (CUSUM), and Combined method. Existing methods can determine the ventilation threshold time using physiological indicators such as respiratory gas data measured during exercise time after the exercise load test performed by the exerciser.

1 is an explanatory diagram for explaining a conventional ventilation threshold time determination method.

In the case of the visual method, during the exercise load test, the carbon dioxide emissions (or ventilation) show a linear increase in parallel with the oxygen uptake. Thereafter, a point where carbon dioxide emission (or ventilation amount) rapidly increases compared to oxygen intake amount is generally referred to as the ventilation threshold, and is based on a graph of oxygen intake-carbon dioxide emission (or oxygen intake-ventilation amount) after the exercise is over. 3 or more experts make visual judgments.

In the case of the V-slope method, it is one of the most commonly used methods for determining the ventilation threshold time point. After the exercise was over, the observer visually determined a sharp break point on the graph of carbon dioxide emissions-oxygen uptake, and then based on this reference point, each linear regression analysis of carbon dioxide emissions for previous and subsequent oxygen uptake. Determine the regression line through and determine the intersection of these two regression lines as the ventilation threshold point.

In the case of the D-max method, after the exercise, a third-order polynomial curve is calculated and applied to the change of carbon dioxide emission (or ventilation) with respect to oxygen intake by using the Least square method (Polynomial curve fitting). . Then, the point in the curve that is farthest from the curve perpendicular to the straight line connecting the start and end points of the third-order polynomial curve is detected and determined as the ventilation threshold time point.

In the case of the cumulative summation (CUSUM) method, the ventilation threshold point is determined by focusing on the absolute amount of change over time, not the change in the physiological indicators detected during exercise. That is, the CUSUM method uses a method in which an observer visually determines a ventilation threshold time point in a graph in which the absolute value of a continuous difference in physiological parameters with time is successively added to a past value.

In the combined method, the CUSUM method and the D-max method are properly mixed to detect the ventilation threshold time point, and a third-order polynomial curve is applied to a graph in which absolute values of continuous differences in physiological indicators over time are accumulated (Polynomial). The curve fitting method is used to determine the timing of the ventilation thresholds.

These methods use physiological indicators such as respiratory gas analysis and heart rate to determine ventilation threshold points based on data obtained only after the workout is over. In addition, physiological indicators detected during exercise leave room for subjectivity intervention because the viewer visually judges.

In addition, the athlete must complete at least one exercise load test to know the timing of the ventilation threshold of the individual, which induces the athlete to digest the exercise amount beyond the individual's exercise ability. There is a possibility of adverse effects.

That is, among these methods, the Visual and V-slope CUSUM methods are not objective because the subjectivity of the observer is involved in determining the ventilation threshold point. The disadvantage is that the ventilation threshold can only be detected afterwards.

Therefore, a method for determining a real-time ventilation threshold point during exercise, which can overcome the fundamental limitations of existing methods, and can present an exercise amount and exercise regimen to allow an athlete to perform an exercise suitable for an individual's exercise ability, is required.

 Therefore, in order to supplement the limitations of existing methods for determining the ventilation threshold time point, the present invention utilizes a heart rate that can be measured while minimizing the constraint of the exerciser and reflects the exerciser's current physical condition, thereby the exerciser's body during exercise. We propose a method to monitor the information and to detect the ventilation threshold in real time during exercise.

In the present invention, by using the heart rate as a physiological indicator for determining the ventilation threshold time point in real time, unlike the physiological index acquisition method according to the wearing of the gas mask to minimize the restraint of the athlete.

 The problem to be solved by the present invention can be measured while minimizing the restraint of the exerciser, using the heart rate reflecting the current body state of the exerciser, monitoring the body information of the exerciser during exercise based on the ventilation in real time during the exercise It is to provide a real-time ventilation threshold point detection method by monitoring the heart rate change that can detect the threshold point.

The present invention provides a method for detecting a ventilation threshold time while a subject is wearing an electrocardiogram electrode and exercising, and after the exercise apparatus starts exercising, the heart rate average value in 15 seconds during the initial measurement time in minutes. And calculating a heart rate average for initial straight line setting to obtain a minimum value. The slope (Slop) and the y-intercept (Initial _{y -intercept} ) are calculated using the heart rate average value HRmean and the minimum value HRmin obtained in the heart rate averaging step, but the slope _Slop is

(However, Time _HRmean -Time _HRmin , which is △ Time, is the initial measurement time in minutes)

Is obtained by the initial _y-intercept

(Time is the time at the minimum value (HRmin))

A slope and intercept calculation step obtained by; And an initial straight line setting step of determining an initial straight line VTy using the slope value and the y-intercept value obtained in the slope calculation step.

Using the slope value (Slop) and the y-intercept value (Initial _{y - intercept} ) of the initial straight line setting step, the _{y - intercept} value (VT _{y - intercept} ) of the baseline is a regression equation of male and female, that is,

It is obtained by, and the baseline setting step of determining the reference line using the slope value (Slop) of the initial straight line setting step, the y-intercept value (VT _{y - intercept} ) of the reference line;

In addition, the present invention is a method for detecting the ventilation threshold time point while the subject is wearing the electrocardiogram electrode and exercising, detecting the R point that is the highest point in the electrocardiogram every cycle, during the predetermined second window time Calculating a heart rate average, and calculating a heart rate average for detecting a ventilation threshold time point; Determining whether the heart rate average for the second window time, which is obtained in the heart rate averaging step for detecting the ventilation threshold time point, is greater than the preset baseline, and if it is larger than the reference line, the time of the heart rate average for the current second window time. Characterized in that it comprises ;; the ventilation threshold time candidate determination step of determining the ventilation threshold time candidate.

According to the present invention, as a result of the determination of the ventilation threshold time point, if three out of five consecutive heart rate input values are not larger than the baseline value, the baseline is multiplied by 0.95, that is, the baseline value is reduced to 0.95 times, and the current window time in seconds A baseline readjustment step of determining the time of the heart rate mean during the ventilation threshold time candidate; If three out of five consecutive heart rate input is greater than the baseline value, the ventilation threshold time point determination step of determining the ventilation threshold time candidate as the ventilation threshold time point; further includes.

The initial designated measurement time in minutes is 3 minutes, and the window time in seconds is 15 seconds.

According to an aspect of the present invention, there is provided a system for detecting a ventilation threshold time point, comprising: an electrocardiogram electrode unit including a reference electrode for measuring electrocardiogram and electrodes for measuring signals; An exercise device configured to exercise the user by mounting the ECG electrode; An ECG signal preprocessor for amplifying the ECG signal detected by the ECG electrode unit, removing noise, and converting the ECG signal into a digital signal; From the electrocardiogram signal received from the electrocardiogram signal preprocessing unit, the R point which is the highest point of the electrocardiogram is detected every cycle, the heart rate average for the preset second window time is obtained, and the heart rate average for the second window time is set to the preset reference line. And a ventilation threshold time point determination processing unit configured to determine a greater than the reference line and determine a greater than the baseline, as a ventilation threshold time point candidate, for a current heart rate average time during the current second unit window time.

The present invention provides a system for detecting a ventilation threshold time point, comprising: an electrocardiogram electrode unit including a reference electrode for measuring an electrocardiogram and electrodes for measuring a signal; An exercise device configured to exercise the user by mounting the ECG electrode; An ECG signal preprocessor for amplifying the ECG signal detected by the ECG electrode unit, removing noise, and converting the ECG signal into a digital signal; From the ECG signal received from the ECG signal preprocessor, the heart rate average value (HRmean) and minimum value (HRmin) for 15 seconds are obtained during the initial measurement time in minutes, and the average heart rate (HRmean) and minimum value (HRmin) are obtained. Calculate the slope (Slop) and y-intercept (Initial _{y - intercept} ), but the slope (Slop)

(However, Time _HRmean -Time _HRmin , which is △ Time, is the initial measurement time in minutes)

Is obtained by the initial _y-intercept

(Time is the time at the minimum value (HRmin))

And the slope value (Slop) and y-intercept value (Initial _{y - intercept} ), the y-intercept value (VT _{y - intercept} ) of the baseline is a regression equation of male and female, that is,

And a ventilation threshold time determining operation processor for obtaining a reference line for determining a ventilation threshold time point using a slope value Slop and a y-intercept value VT _{y - intercept of} the reference line. .

The present invention is a treadmill exercise load test protocol, the subject is made to detect the ventilation threshold time point during exercise by the Modified Balke protocol.

 According to the real-time ventilation threshold time detection method through the monitoring of the heart rate change of the present invention, it is possible to measure while minimizing the restraint of the athlete, and monitor the physical information of the athlete during exercise by using the heart rate reflecting the current physical condition of the athlete. Based on this, the ventilation threshold time can be detected in real time during the exercise.

That is, the present invention obtains a ventilation threshold point in real time during exercise, but uses heart rate as a physiological indicator for determining the ventilation threshold point in real time. Minimize the feeling.

As a result of the test for this method, it is possible to replace the existing methods and determine the ventilation threshold time point in real time by showing the results correlated with the ventilation threshold determined by the existing methods.

In the present invention, the exerciser can manage the health by evaluating the exercise ability of the individual exercisers according to the ventilation threshold time point evaluated in real time during the exercise and present the exercise amount and exercise prescription accordingly to perform the exercise suitable for the individual's physical ability Induce.

1 is an explanatory diagram for explaining a conventional ventilation threshold time determination method.
2 is a schematic diagram for schematically illustrating a system for detecting a real time ventilation threshold time point through monitoring of a heart rate change of the present invention.
3 is a flowchart for detecting a ventilation threshold time point in the calculation processor of FIG. 2.
Figure 4 is an example of a graph showing the average heart rate of 15 seconds interval in the heart rate average calculation step for the initial straight line setting of the present invention.
Figure 4 is an example of a graph showing the average heart rate of 15 seconds interval in the heart rate average operation step for the initial straight line setting of the present invention (HR vs Time graph).
FIG. 5 is a graph in which an initial straight line is applied to a graph showing an average heart rate of the 15 second interval of FIG. 4.
FIG. 6 is a graph in which a baseline is applied to a graph showing an average heart rate of the 15 second interval of FIG. 5.
FIG. 7 is a graph illustrating a ventilation threshold time point in a graph showing an average heart rate of the 15 second interval of FIG. 6.
8 is an explanatory diagram for explaining an exercise test experiment environment for comparing and analyzing a real-time ventilation threshold time point detection method according to a heart rate change and a method detected by a conventional gas breathing analyzer.
9 is an explanatory diagram for explaining a Modified Balke protocol as a treadmill motion load test protocol.
10 is a graph showing the results of statistical analysis of experimental results comparing the detection method of the real-time ventilation threshold time point and the method detected by the conventional gas breathing analyzer through the monitoring of the heart rate change of the present invention.

 Ventilation threshold refers to the level of oxygen uptake or exercise intensity at the time of exercise related metabolic acid poisoning and changes in respiratory gas exchange.

Conventionally, wearing an oxygen mask and exercising to measure the ventilation threshold, by detecting the oxygen intake and carbon dioxide emissions with a gas breathing analyzer, to determine the regression line through each linear regression analysis for the carbon dioxide emissions to the oxygen intake, The intersection of the two regression lines is determined as the ventilation threshold point.

In the present invention, in order to measure the ventilation threshold, an ECG electrode is mounted, a movement is performed, and a ventilation threshold point is determined by a predetermined algorithm of the present invention from the detected ECG signal.

First, a real-time ventilation threshold time point detection method through monitoring the heart rate change of the present invention will be described, and then the real-time ventilation threshold time point detection method through the monitoring of the heart rate change of the present invention is compared with the method detected by a conventional gas breathing analyzer. Analyze

Hereinafter, a method of detecting a real time ventilation threshold time point by monitoring a change in heart rate according to an exemplary embodiment of the present invention will be described in detail with reference to the accompanying drawings.

Figure 2 is a schematic diagram for explaining the system for detecting the real-time ventilation threshold time point through monitoring the heart rate change of the present invention, the electrocardiogram electrode unit 100, electrocardiogram preprocessor 200, arithmetic processing unit 300, output A portion 400 is included.

The electrocardiogram electrode part 100 is an electrode for detecting an electrocardiogram, and includes a reference electrode and signal measuring electrodes. The examinee attaches an electrocardiogram electrode and exercises on a treadmill or the like.

The electrocardiogram preprocessor 200 includes a preamplifier (not shown), a filter (not shown), and an A / D converter (not shown) to amplify the ECG signal detected by the ECG electrode unit 100 and to generate noise. Removes and converts it to a digital signal.

The calculation processing unit 300 detects the ventilation threshold time point by analyzing the ECG signal received from the ECG preprocessor 200 by an algorithm described below.

The output unit 400 outputs an output signal received from the arithmetic processing unit 300, for example, a heartbeat signal, a ventilation threshold (VT) time point, and the like.

3 is a flowchart for detecting a ventilation threshold time point in the calculation processor of FIG. 2.

Ventilation threshold time point detection of the present invention includes the initial straight line setting step, the baseline setting step to find the ventilation threshold (VT) time point, the ventilation threshold (VT) time point determination step sequentially.

First, the initial straight line setting step is as follows.

In the heart rate averaging step for initial straight line setting, after an exercise device such as a treadmill starts exercising (S100), the number of R points (beats, heart rates) (or RR intervals (ie, heart rate)) for 15 seconds is determined. Detecting and obtaining an average (S110).

That is, the R point (beat, heart rate), which is the highest point in each period of the ECG, is detected, and the RR interval, which is the distance from the R point to the next R point, is detected, and the number of R points (or RR intervals) for 15 seconds is detected. Is detected and the average heart rate in 15 seconds is obtained. Here, for example, if the average heart rate between 1 and 15 seconds is calculated, then the average heart rate is measured as the average heart rate between 16 and 30 seconds in 30 seconds.

Figure 4 is an example of a graph showing the average heart rate of 15 seconds interval in the heart rate average operation step for the initial straight line setting of the present invention (HR vs Time graph). Although the window time for the average in FIG. 3 is 15 seconds, this is not intended to limit the present invention, which can be used within 8 to 20 seconds.

In step 3 of determining whether the initial specified measurement time has elapsed, when the 3 minutes have not elapsed, the operation returns to the heart rate averaging step S110 (S120). In this way, the average, maximum, and minimum values of the heart rate during the first three minutes of exercise can be obtained. Here, the initial specified measurement time is 3 minutes, but this is not intended to limit the present invention, which can be used within 2 to 5 minutes.

In the step of calculating the slope, the slope and the y-intercept are calculated using the average value, the maximum value, and the minimum value of the heart rate (S130).

Here, for convenience of description, the 'average heart rate' measured at intervals of 15 seconds is referred to as 'heart rate' below.

The mean value of heart rate during the first 3 minutes of exercise refers to the _mean value (HR _mean ) of heart rates updated every 15 seconds. For example, since the heart rate is measured at 15 second intervals, it is generally expected to obtain approximately four heart rate data in one minute, and approximately three or so data of approximately twelve in three minutes. Here it will be determined an average value _(mean HR) of heart rate.

The minimum value represents the smallest value of approximately 12 heart rates for 3 minutes and is expressed as HR _min hereinafter. In the same vein, the maximum value HR _max is obtained.

In the equation of a linear function such as y = ax + b, y is HR, a is slope, b is y intercept, x is time (Time in _HR , ie Time _HR ), and Time _HRmean is The time taken to reach the average heart rate, Time _HRmin is the time taken to reach the minimum value of the heart rate.

HR _mean = _Slop × Time _HRmean + Y intercept

HR _min = _Slop × Time _HRmin + Y intercept

Here, the slope Slop is equal to Equation 1.

△ Time _HRmean -Time _{HRmin, which} is △ Time, is fixed at 3 minutes for convenience because the slope is determined based on the heart rate during the 3 minutes of exercise.

Since the initial Y intercept is HR _min = _Slop x Time _HRmin + Y intercept, Y intercept = HR _{min -Slop} × Time _HRmin . Therefore, the initial Y intercept Y _init is expressed by Equation 2.

Where the initial Y _intercept is expressed as Y _init or Initial _{y - intercept} .

In the initial straight line setting step, the initial straight line VTy is determined using the slope value and the y-intercept value obtained in the slope calculation step S130 (S140). FIG. 5 is a graph in which an initial straight line is applied to a graph showing an average heart rate of the 15 second interval of FIG. 4. That is, FIG. 5 is an HR vs Time graph (initial line is blue line) to which an initial straight line is applied.

The following describes the baseline setting step.

As the baseline setting step, calculate the y-intercept value of the baseline by using the slope value and the y-intercept value of the initial straight line setting step and apply a regression equation, and calculate the slope value of the initial straight line setting step and the y-intercept of the baseline y-intercept calculation step. The reference line is determined using the intercept value (S150).

That is, the y-intercept value VT _y-intercept of the baseline is represented by a regression equation of male and female as shown in Equation 3.

여기서, age는 나이를 말하며, smoking은 흡연여부를 나타내는 값(예로, 비흡연시는 0, 흡연시는 1)을 말한다.

Here, age refers to age, and smoking refers to a value indicating smoking (for example, 0 for non-smoking and 1 for smoking).

In Equation 3, a significant parameter was detected through statistical analysis, and linear regression analysis was performed using the same, thereby deriving the following equation. Where Initial _y-intercept is the initial Y _-intercept .

Here, the reference line is determined using the slope value Slop obtained in the slope calculation step S130 and the y-intercept value VT _{y - intercept} of the reference line. Here, the reference line means that the initial straight line and the inclination are the same and only the Y-intercept is different, that is, the initial straight line such that b is changed to b 'at y = ax + b is translated in the y-axis.

FIG. 6 is a graph in which a baseline is applied to a graph showing an average heart rate of the 15 second interval of FIG. 5. That is, FIG. 6 is an HR vs Time graph to which a reference line is applied (a reference line is a green line).

The following describes the ventilation threshold time detection step.

As a heart rate averaging step for detecting a ventilation threshold time point, while detecting an R point (beat, heart rate), which is the highest point in the ECG every cycle, a heart rate average of 15 seconds is obtained (S155).

In the heart rate and baseline comparison step, it is determined whether the heart rate average of 15 seconds obtained in the heart rate averaging step for detecting the ventilation threshold time point is greater than the reference line obtained in the baseline setting step (S160), and if it is smaller than or equal to the baseline, the ventilation threshold time point The operation returns to heart rate averaging step S155 for detection.

In the ventilation threshold time point determination step, the current time of the heart rate average of 15 seconds, that is, the current time is determined as the ventilation threshold time point candidate (S170). That is, if the heart rate and the baseline comparison step (S160) is the next step, if the heart rate average of 15 seconds obtained in the heart rate averaging step for detecting the ventilation threshold time point is larger than the reference line obtained in the baseline setting step, that is, the reference line When a heart rate value higher than the heart rate is detected, the time at that time is determined as a candidate candidate for the ventilation threshold (S170). Here, the candidate for the ventilation threshold time point refers to a starting point for conducting a test for detecting the ventilation threshold time point.

In the ventilation threshold point determination step, after the ventilation threshold point candidate determination step, it is determined whether three out of five consecutive heart rate averages are greater than the reference line value (S180). In other words, it is determined whether the heart rate value that is larger than the baseline value in the heart rate average is 60% or more.

In the baseline readjustment step, if the result of the ventilation threshold time determination step (S180), if three of five consecutive heart rate input is not greater than the baseline value, multiply the baseline by 0.95, that is, reduce the baseline value to 0.95 times (S175) ), The process returns to the ventilation threshold time candidate determination step (S170).

In the determination of the ventilation threshold time point, as a result of the ventilation threshold time determination step (S180), if three out of five consecutive heart rate inputs are larger than the baseline value, that is, the heart rate value that is continuously larger than the baseline value in the heart rate mean If more than 60% is detected, the ventilation threshold time candidate is determined as the ventilation threshold time point (S190), and the exercise of the exercise equipment is terminated (S200). FIG. 7 is a graph illustrating a ventilation threshold time point in a graph showing an average heart rate of the 15 second interval of FIG. 6. That is, FIG. 7 is an HR vs Time graph in which the ventilation threshold time point is determined (the ventilation threshold time point is a red line).

Next, a comparison between the real-time ventilation threshold detection method and the method detected by the conventional gas breathing analyzer by monitoring the heart rate change of the present invention.

FIG. 8 is an explanatory diagram for explaining a test environment for an exercise test for comparing and analyzing a real-time ventilation threshold time point detection method according to a heart rate change and a method detected by a conventional gas respiratory analyzer. Same as the table.

Experiments for this were carried out in the following order.

First, a medical history survey (a questionnaire and a consent form) was conducted. Here, the questionnaire was examined for exercise status, eating habits, drugs, psychological status, past and present diseases.

Secondly, a body composition analysis test was performed. Here, subcutaneous fat, obesity, BMI, and BMR indices of the body parts were measured.

Third, ECG electrode mounting and gas analyzer mask were worn and data were acquired in the resting state.

Electrocardiogram measurements were performed using the 12-channel electrocardiograph electrodes, which were measured by Lead I, Lead II, Lead III, aVR, aVF, aVL, V1, V2, V3, V4, V5, and V6.

Subjects wore gas analyzer masks to obtain VO2, METS, VCO2, VE, RER, Vt, FEO2, FECO2, HR, TM, AcKcal.

Third, ECG electrode mounting and gas analyzer mask were worn.

The electrocardiogram electrode was mounted to obtain measurement results of Lead I, Lead II, Lead III, aVR, aVF, aVL, V1, V2, V3, V4, V5, and V6 in the ECG measurement method using the 12-channel electrocardiograph electrode.

Third, the subject wore a gas analyzer mask, and obtained VO2, METS, VCO2, VE, RER, Vt, FEO2, FECO2, HR, TM, and AcKcal.

Fourth, taking a rest while wearing an ECG electrode and wearing a gas analyzer mask. Here, the resting state refers to a state of sitting in a chair, that is, data is acquired while sitting in a chair.

Fifth, data is acquired during warm-up after resting state. At this time, the speed of the treadmill is 1.9Km / h.

Sixth, the subject's VO ₂ max was measured for 10-25 minutes in accordance with the Modified Balke Protocol. The Balke Protocol uses a treadmill speed of 2.0 to 3.3 mph and ramps up to 2-3% every 2-3 minutes. 9 is an explanatory diagram for explaining a Modified Balke protocol as a treadmill motion load test protocol.

Seventh, as a cool down process, the speed of treadmill is 1.9Km / h and data is measured.

Eighth, finish the exercise test.

In this experiment, the exercise termination condition is as follows.

 If at least two of the following conditions are met during a workout, go to cool-down mode.

First, despite the constant increase in exercise load, the heart rate does not increase any more, or the subject's heart rate during exercise reaches 15 beats smaller than the maximum heart rate predicted by age (maximum heart rate-15 beats).

Second, the respiratory exchange ratio (RER) is greater than or equal to 1.10.

Third, the oxygen intake (VO2) does not increase any more even when the exercise load increases.

Fourth, the subject himself requested to stop the exercise test due to physical fatigue or arbitrary judgment.

Fifth, RPE, which is one of the subjective indicators of maximal movement, is over 17 (RPE: Rating of perceived exertion).

Through the experimental results, a comparison between the ventilation threshold determined by the real-time ventilation threshold point detection method through monitoring the heart rate change of the present invention and the detection threshold determined by the conventional gas respiratory analyzer was performed. Indicated. Therefore, the real-time ventilation threshold time detection method through monitoring the heart rate change of the present invention can replace the conventional gas respiratory analyzer detection method and can determine the ventilation threshold time point in real time.

Table 1 is a result of statistical analysis of the experimental results comparing the detection method of the real-time ventilation threshold point through the monitoring of the heart rate change of the present invention and the method detected by the conventional gas breathing analyzer.

Measured VT in Table 1 represents the average of the VT points automatically measured after the end of the exercise from the conventional gas breathing analyzer, Estimated VT is a VT point measured through the real-time ventilation threshold point detection method through monitoring the heart rate change of the present invention Statistical analysis showed significant results.

FIG. 10 is a graph illustrating experimental results comparing a method of detecting a real-time ventilation threshold time point and a method detected by a conventional gas respiratory analyzer through monitoring a heart rate change of the present invention. That is, Table 1 is a graph. It is shown.

As described above, the present invention has been described in connection with specific embodiments of the present invention. However, the present invention is not limited thereto and the scope of the present invention is not the described embodiments, but the claims and their equivalents. Must be determined by

DESCRIPTION OF SYMBOLS 100 ECG electrode part 200 ECG preprocessing part 300 Computation processing part 400 Output part

Claims (16)

In the method for detecting the ventilation threshold time point while the subject is wearing the ECG electrode and exercising,
A heart rate averaging step for initial straight line setting, wherein after the exercise device starts to exercise, the heart rate average value and minimum value of 15 seconds are calculated during the initial measurement time in minutes;
Using the average heart rate (HRmean) and the minimum heart rate (HRmin) obtained in the heart rate averaging step, the slope and _y-intercept are calculated.
Slop is

(However, △ Time is the initial measurement time in minutes, which is 3 minutes.)
Obtained by
Initial _y-intercept

(Time is the time at the minimum value (HRmin))
A slope and intercept calculation step obtained by;
An initial straight line setting step of determining an initial straight line (VTy) using the slope value and the y-intercept value obtained in the slope calculation step;
Method for detecting a ventilation threshold time point characterized in that it comprises a. The method of claim 1,
Using the slope value (Slop) and the y-intercept value (Initial _y-intercept ) of the initial straight line setting step, the _y-intercept value (VT _y-intercept ) of the baseline is a regression equation of male and female, that is,

(However, age is the age of the subject, smoking is a value indicating whether the subject is smoking, 0 for non-smoking, 1 for smoking)
Saved by
A baseline setting step of determining a reference line using a slope value Slop of the initial straight line setting step and a _y-intercept value VT _y-intercept of the reference line;
Method for detecting a ventilation threshold time point further comprises. In the method for detecting the ventilation threshold time point while the subject is wearing the ECG electrode and exercising,
A heart rate averaging step for detecting a ventilation threshold time point by detecting an R point which is the highest point in each ECG, and obtaining an average heart rate for a predetermined second window time;
Determining whether the heart rate average for the second window time, which is obtained in the heart rate averaging step for detecting the ventilation threshold time point, is greater than the preset baseline, and if it is larger than the reference line, the time of the heart rate average for the current second window time. Determining a threshold threshold candidate for determining a threshold threshold time;
Method for detecting a ventilation threshold time point, characterized in that consisting of. The method of claim 3, wherein
After the ventilation threshold time point candidate determining step, determining whether three out of five consecutive heart rate averages are greater than the baseline value;
If, as a result of the ventilation threshold timing step, three of the five consecutive heart rate inputs are not greater than the baseline value, the baseline is multiplied by 0.95, that is, the baseline value is reduced to 0.95 times, and the heart rate for the current second window time A baseline readjustment step of determining an average time as a candidate for a ventilation threshold time point;
A ventilation threshold time point determining step of determining a ventilation threshold time point candidate as a ventilation threshold time point if three out of five consecutive five of the input heart rate averages are larger than the baseline value;
Method for detecting a ventilation threshold time point further comprising. The method of claim 1, wherein
And the initial specified measurement time in minutes is three minutes. 3. The method of claim 2,
A heart rate averaging step for detecting a ventilation threshold time point, after detecting the R point, which is the highest point in the electrocardiogram every cycle, to obtain a heart rate average for a preset second window time;
Determining whether the heart rate average for the second window time, which is obtained in the heart rate averaging step for detecting the ventilation threshold time point, is greater than the baseline, and if greater than the reference line, ventilates the time of the heart rate average for the current second window time. A ventilation threshold time candidate determination step of determining the threshold time candidate;
Method for detecting a ventilation threshold time point further comprises. The method according to claim 6,
After the ventilation threshold time point candidate determining step, determining whether three out of five consecutive heart rate averages are greater than the baseline value;
As a result of the ventilation threshold timing step, if three of the five consecutive heart rate inputs are not greater than the baseline value, the baseline is multiplied by 0.95, i.e., the baseline value is reduced to 0.95 times, during the current second window time. A baseline readjustment step of determining a time of the heart rate average as a candidate candidate for the ventilation threshold;
A ventilation threshold time point determining step of determining a ventilation threshold time point candidate as a ventilation threshold time point if three out of five consecutive five of the input heart rate averages are larger than the baseline value;
Method for detecting a ventilation threshold time point further comprising. The method according to any one of claims 3 or 4 or 6 or 7,
And said window time in seconds is 15 seconds. In the system for detecting the ventilation threshold time point,
An electrocardiogram electrode unit including a reference electrode for measuring an electrocardiogram and a signal measuring electrode;
An exercise device configured to exercise the user by mounting the ECG electrode;
An ECG signal preprocessor for amplifying the ECG signal detected by the ECG electrode unit, removing noise, and converting the ECG signal into a digital signal;
From the electrocardiogram signal received from the electrocardiogram signal preprocessing unit, the R point which is the highest point of the electrocardiogram is detected every cycle, the heart rate average for the preset second window time is obtained, and the heart rate average for the second window time is set to the preset reference line. A ventilation threshold time point determination processing unit configured to determine whether the threshold is greater than the reference line, and determine a time of the heart rate average for the current second window time as a candidate for the ventilation threshold time point;
System for detecting a ventilation threshold time point comprising a. 10. The method of claim 9,
The ventilation threshold time point determination processing unit,
From the electrocardiogram signal received from the electrocardiogram signal preprocessor, the heart rate average value HRmean and the minimum value HRmin in units of 15 seconds are calculated during the initial measurement time in minutes.
Using the average heart rate (HRmean) and minimum value (HRmin) to calculate the slope (Slop) and y-intercept (Initial _y-intercept ),
Slop is

(However, △ Time is the initial measurement time in minutes, which is 3 minutes.)
Obtained by
Initial _y-intercept

(Time is the time at the minimum value (HRmin))
Obtained by
Using the slope value Slop and the y-intercept value, the _y-intercept value VT _{y-intercept of the} baseline is a regression equation of male and female, that is,

(However, age is the age of the subject, smoking is a value indicating whether the subject is smoking, 0 for non-smoking, 1 for smoking)
Saved by
A system for detecting a ventilation threshold time point, wherein the baseline is determined using a slope value (Slop) and a _y-intercept value (VT _y-intercept ) of the baseline. In the system for detecting the ventilation threshold time point,
An electrocardiogram electrode unit including a reference electrode for measuring an electrocardiogram and a signal measuring electrode;
An exercise device configured to exercise the user by mounting the ECG electrode;
An ECG signal preprocessor for amplifying the ECG signal detected by the ECG electrode unit, removing noise, and converting the ECG signal into a digital signal;
From the electrocardiogram signal received from the electrocardiogram signal preprocessor, the heart rate average value HRmean and the minimum value HRmin in units of 15 seconds are calculated during the initial measurement time in minutes.
Using the average heart rate (HRmean) and minimum value (HRmin) to calculate the slope (Slop) and y-intercept (Initial _y-intercept ),
Slop is

(However, △ Time is the initial measurement time in minutes, which is 3 minutes.)
Obtained by
Initial _y-intercept

(Time is the time at the minimum value (HRmin))
Obtained by
Using the slope value Slop and the y-intercept value, the _y-intercept value VT _{y-intercept of the} baseline is a regression equation of male and female, that is,

(However, age is the age of the subject, smoking is a value indicating whether the subject is smoking, 0 for non-smoking, 1 for smoking)
Saved by
A ventilation threshold time point determination processing unit obtaining a reference line for determining a ventilation threshold time point using a slope value Slop and a _y-intercept value VT _{y-intercept of} the reference line;
System for detecting a ventilation threshold time point comprising a. The method of claim 11, wherein
The ventilation threshold time point determination processing unit,
From the ECG signal received from the ECG signal preprocessing unit, the heart rate average for the window time in seconds is determined, and the heart rate average for the window time in seconds is determined to be greater than a preset reference line. A system for detecting a ventilation threshold time point, wherein the time of the heart rate average for the window time unit in seconds is determined as the ventilation threshold time point candidate. 13. The method according to any one of claims 9 to 12,
A system for detecting a ventilation threshold time point, wherein the window time in seconds is 15 seconds. 13. The method according to any one of claims 10 to 12,
A system for detecting a ventilation threshold time point, wherein an initial specified measurement time in minutes is 3 minutes. 8. The method according to any one of claims 1 to 7,
A method for detecting a ventilation threshold time point, wherein a subject is configured to detect a ventilation threshold time point during a workout according to a modified balke protocol as a treadmill exercise load test protocol. 13. The method according to any one of claims 9 to 12,
A system for detecting a ventilation threshold time point, wherein a subject is configured to detect a ventilation threshold time point during a workout according to a modified balke protocol as a treadmill exercise load test protocol.

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