KR101850803B1 - Method for measuring low power heart rate using PPG signal, and recording medium thereof - Google Patents

Abstract

A low-power heart rate measuring method using a PPG signal of the present invention comprises the steps of: multiplying a value obtained by subtracting a first threshold value from a currently measured data measurement value (n) by a value obtained by subtracting the first threshold value from a subsequently measured data measurement value (n+1), and determining whether a result of the multiplication is a negative value, which is a value smaller than 0; when the result is a negative value, determining a currently measured time n and a subsequently measured time n+1 as a measurement range, and obtaining a maximum value (n) within the measurement range; when the maximum value (n) is greater than a second threshold value, recognizing the same as a maximum value, and when the maximum value (n) is smaller than the second threshold value, not recognizing the same as a maximum value; performing the maximum value recognizing process for a predetermined measurement time, and after the measurement time, calculating time values, which are measurement time intervals between the recognized maximum values; calculating an average value obtained by averaging the time values; and calculating a heart rate by using the average value. According to the present invention, a heart rate can be measured more accurately and quickly in a blood flow rate measuring apparatus using an LED and a photodiode.

Description

BACKGROUND OF THE INVENTION 1. Field of the Invention [0001] The present invention relates to a method of measuring a low power heart rate using a PPG signal,

The present invention relates to an algorithm for processing a blood flow signal measured in a heart rate measurement process, and more particularly, to an algorithm for converting an optical blood flow rate according to a body part into a PPG (PhotoPlethysmoGraphy) signal to indicate the heart rate.

Heart rate is the most basic information of human health information. It can monitor body change through heart rate monitoring in a situation where interest in recent health is continuously increasing. In addition, due to the arrival of the Internet of Things, the heart rate measuring device can be miniaturized and implemented with low power, and it is possible to easily monitor the heart rate even in normal times.

In recent years, with the development of the object Internet sensor, the blood flow is measured by using the LED and the photodiode photodetector, and the heart rate can be easily detected by touching part of the body such as the finger, ear, and cuff. However, such a wearable sensor using the Internet is cumbersome to wear and carry, the algorithm of the measurement process is inaccurate, and the measurement time is long.

FIG. 1 is a view showing an operation principle in which a conventional optical blood flow rate is indicated by a PPG signal. That is, FIG. 1 shows an example of a conventional PPG (PhotoPlethysmoGraphy) signal measurement.

Referring to FIG. 1, in the body tissue that receives light from the LED light source, light is absorbed into the bloodstream of the artery through the vein, and the blood flow is changed every time the pulse is run. At this time, The amount of light coming out also changes. This light change can be detected by a photodiode and represented by a voltage change. It can be expressed as a voltage graph, and the beats per minute (BPM) can be measured.

FIG. 2 is a view showing a principle of measuring a heart rate using data obtained by measuring a PPG signal using a conventional gradient method. FIG. 3 shows a principle of measuring a heart rate using data obtained by measuring a PPG signal using a conventional maximum value Fig.

FIG. 2 and FIG. 3 are diagrams schematically showing, in a graph, an algorithm for processing data measured by the conventional PPG method.

The data measured by the PPG method comes out as a curve having a curvature. FIG. 2 is a method of obtaining the slope of the convex portion of the graph and averaging the time intervals of the gradient to obtain the heart rate per minute. In the method of FIG. 3, the peak value of the convex portion is obtained and the time interval of each maximum value is averaged to obtain the heart rate per minute.

In Fig. 2, a plurality of convex points may appear in the graph due to the movement of the body or trembling during the measurement of noise or PPG. In such a case, there is a disadvantage that the error value becomes large and the reliability becomes poor when the heart rate per minute (BPM) is measured.

Also, FIG. 3 similarly shows that a convex point is not formed uniformly by noise, and when a plurality of points appear, the error value becomes large when the heart rate per minute (BPM) is measured and the reliability becomes poor.

Korea Patent No. 10-0859981

SUMMARY OF THE INVENTION It is an object of the present invention to provide a method for accurately and quickly measuring heart rate in a blood flow measuring apparatus using an LED and a photodiode.

It is another object of the present invention to provide a method for minimizing the influence of noise on a measurement signal and widening a measurement range to more widely measure the heart rate.

The objects of the present invention are not limited to the above-mentioned objects, and other objects not mentioned can be clearly understood by those skilled in the art from the following description.

In order to achieve the above object, there is provided a heart rate measuring method for measuring blood flow using an LED (Light Emitting Diode) and a photodiode according to a first order algorithm of the present invention, Multiplying a value obtained by subtracting the first threshold value from the measured value n and a value obtained by subtracting the next measured data measurement value n + 1 from the first threshold value, and determining whether the value is a negative value that is a value less than 0; (N) within the measurement range is determined as the measurement range, and the maximum value (n) is recognized as the maximum value when the maximum value (n) is larger than the second threshold value The maximum value recognition process is performed for a predetermined measurement time, and after the measurement time, the measurement time interval between the recognized maximum values By using a step of calculating the median, the method comprising: calculating an average value by averaging the time value and the average value includes the step of calculating the heart rate.

In calculating the heart rate, the heart rate per minute (BPM) can be calculated by dividing 60 by the average value.

In a method of measuring a heart rate in a heart rate measuring apparatus for measuring a blood flow volume using an LED (Light Emitting Diode) and a photodiode according to a second-order algorithm of the present invention, the data measured value n currently measured in the heart rate measuring apparatus Multiplying a value obtained by subtracting the first threshold value from a value obtained by subtracting the next measured data measurement value n + 1 from the first threshold value and determining whether the value is a negative value that is a value less than 0; (N) within the measurement range is determined as the measurement range, and if the maximum value (n) is larger than the second threshold value, it is recognized as the maximum value, and if the maximum value (n) is smaller than the second threshold value (N + 1) minus the third threshold value and the next measured data measurement value (n + 2) to the third measured value (n + 2) Multiply the subtracted value by 0 Determining whether a current time n + 1 and a next time n + 2 are determined as a measurement range and obtaining a minimum value n within the measurement range, if the current value is a negative value; Recognizing the minimum value as a minimum value when the minimum value n is less than the fourth threshold value and not recognizing the minimum value as a minimum value when the minimum value is larger than the fourth threshold value; performing the maximum value recognition process and the minimum value recognition process for a predetermined measurement time, Calculating a measurement time interval between measurement time intervals and minimum values between recognized maximum values, calculating an average value obtained by averaging measurement time intervals between the measurement time intervals and the minimum values between the maximum values, And calculating the heart rate using the average value.

In calculating the heart rate, the heart rate per minute (BPM) can be calculated by dividing 60 by the average value.

According to the present invention, in the blood flow measuring apparatus using the LED and the photodiode, the heart rate can be more accurately and quickly measured.

Further, according to the present invention, it is possible to minimize the influence of noise on the measurement signal and widen the measurement range, so that the heart rate can be measured more widely.

Further, the present invention can more easily apply the algorithm applied to the PPG sensor in a wearable apparatus and an Internet of Things (IoT) apparatus, and can more accurately measure the heart rate value per minute in a shorter time It is expected.

FIG. 1 is a view showing an operation principle in which a conventional optical blood flow rate is indicated by a PPG signal.
2 is a diagram illustrating a principle of measuring heart rate using data obtained by measuring a PPG signal using a conventional slanting method.
FIG. 3 is a diagram illustrating a principle of measuring a heart rate using data obtained by measuring a PPG signal using a conventional maximum value.
FIG. 4 is a diagram illustrating a principle of measuring a heart rate using a maximum value in a range in a first-order algorithm proposed in the present invention.
5 is a flowchart briefly showing a primary algorithm proposed in the present invention.
FIG. 6 shows the mean and standard deviation of the Gaussian distributions obtained by comparing the first order algorithm of the present invention with the conventional method of FIG.
FIG. 7 is a diagram illustrating a principle of measuring a heart rate using a maximum value and a minimum value within a range in the second algorithm of the present invention. FIG.
FIG. 8 is a flowchart briefly showing a second-order algorithm proposed by the present invention.
9 is an average and standard deviation of a Gaussian distribution comparing 100 measured values by comparing the first and second algorithms of the present invention.
FIG. 10 is a diagram illustrating an optical blood flow measured at the neck using a first-order algorithm and a second-order algorithm of the present invention. FIG.

While the invention is susceptible to various modifications and alternative forms, specific embodiments thereof are shown by way of example in the drawings and will herein be described in detail. It should be understood, however, that the invention is not intended to be limited to the particular embodiments, but includes all modifications, equivalents, and alternatives falling within the spirit and scope of the invention.

The terminology used in this application is used only to describe a specific embodiment and is not intended to limit the invention. The singular expressions include plural expressions unless the context clearly dictates otherwise. In the present application, the terms "comprises" or "having" and the like are used to specify that there is a feature, a number, a step, an operation, an element, a component or a combination thereof described in the specification, But do not preclude the presence or addition of one or more other features, integers, steps, operations, elements, components, or combinations thereof.

Unless defined otherwise, all terms used herein, including technical or scientific terms, have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs. Terms such as those defined in commonly used dictionaries are to be interpreted as having a meaning consistent with the contextual meaning of the related art and are to be interpreted in an ideal or overly formal sense unless expressly defined in the present application Do not.

In the following description of the present invention with reference to the accompanying drawings, the same components are denoted by the same reference numerals regardless of the reference numerals, and redundant explanations thereof will be omitted. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS Hereinafter, exemplary embodiments of the present invention will be described in detail with reference to the accompanying drawings. In the following description, well-known functions or constructions are not described in detail since they would obscure the invention in unnecessary detail.

The present invention relates to a method of measuring heart rate in a heart rate measuring apparatus for measuring a blood flow volume using an LED (Light Emitting Diode) and a photodiode.

The heart rate measuring method of the present invention is composed of a kind of algorithm, which can be executed in a control unit of a computer or a central processing unit (CPU).

FIG. 4 is a diagram illustrating a principle of measuring a heart rate using a maximum value in a range in a first-order algorithm proposed in the present invention, and FIG. 5 is a flowchart briefly showing a first-order algorithm proposed in the present invention.

In FIG. 4, the present invention is different from the conventional method in that the range is determined by a user-defined threshold value. By specifying this range, the maximum value can be obtained more accurately and the error of the BPM measurement value can be reduced because the maximum value does not measure a value lower than the threshold value.

5, a value obtained by subtracting a first threshold value from a data measurement value n currently measured in a heart rate measuring apparatus and a value obtained by subtracting a first threshold value from a next measured data measurement value n + 1, It is determined whether the value is a negative value that is a smaller value (S501). That is, a point at which a negative value appears is a point passing through the first threshold value.

If it is a negative value, the current measured time n and the next measured time n + 1 are set in the range, and the maximum value n in this range is obtained (S503).

If the maximum value n is larger than the second threshold value, it is recognized as the maximum value (S505 and S507). If the maximum value n is smaller than the second threshold value, the waveform distortion is regarded as noise and is not recognized as the maximum value (S505 and S509).

Then, the maximum value recognition process is performed for a predetermined measurement time (S511), and a time value, which is a measurement time interval between the maximum values recognized after the measurement time, is calculated (S513). For example, it is possible to set the measurement time for measurement for 60 seconds, and the measurement time can be arbitrarily set according to the embodiment.

Then, an average value obtained by averaging the time values is calculated (S515).

Then, the heart rate is calculated using the average value (S517). In the case of heart rate per minute, it is obtained by dividing 60 by the average value.

FIG. 6 shows the mean and standard deviation of the Gaussian distributions obtained by comparing the first order algorithm of the present invention with the conventional method of FIG.

In FIG. 6, the left graph is a graph in which two algorithms are compared and a heart rate value is a normal distribution value when green light is used. In the right graph, two algorithm values are compared when using infrared rays, .

As can be seen from the table shown in FIG. 6, it can be seen that the average value and the standard deviation value of the heart rate can be represented by 100 times, respectively, and the standard deviation is improved by 61.4% from 29.96 to 11.54 when using infrared rays. Also, when green light is used, it can be confirmed that it is improved by 58.5% from 75.67 to 31.34. The reduction of the standard deviation means that the first algorithm proposed in the present invention can more accurately measure the heart rate than the conventional measurement algorithm of FIG. 3, since it means that the standard deviation is measured more closely to the value to be measured in terms of accuracy .

The PPG method has a lot of changes in heart rate per minute according to the measurement time. On the other hand, in order to miniaturize the IoT sensor of the PPG related device and to minimize the power consumption, there is a limitation on the battery capacity and the device size to supply power . In order to achieve this, the measurement time should be measured as short as possible. If the measurement time is too short, the maximum amount of sample to be measured is too small to measure incorrect heart rate per minute. In order to compensate for this and to double the data samples, the present invention proposes a second order algorithm as shown in FIGS. 7 and 8.

FIG. 7 is a diagram illustrating a principle of measuring a heart rate using a maximum value and a minimum value within a range in the second-order algorithm of the present invention, and FIG. 8 is a flowchart briefly showing a second-order algorithm proposed in the present invention.

As shown in FIG. 7, the second-order algorithm proposed in the present invention measures the minimum value smaller than the threshold value in comparison with the first-order algorithm, thereby doubling the sample.

FIG. 8 is a flowchart briefly showing a second-order algorithm proposed by the present invention.

8, a value obtained by subtracting a first threshold value from a data measurement value n currently measured by a heart rate measuring apparatus and a value obtained by subtracting a first threshold value from a next measured data measurement value n + 1, It is determined whether the value is a negative value which is a smaller value (S801). That is, a point at which a negative value appears is a point passing through the first threshold value.

If it is a negative value, the current measured time n and the next measured time n + 1 are set in the range, and the maximum value n in this range is obtained (S803).

If the maximum value n is greater than the second threshold value, it is recognized as the maximum value (S805 and S807). If the maximum value n is smaller than the second threshold value, the waveform distortion is reported as noise and is not recognized as the maximum value (S805 and S809).

Next, a value obtained by subtracting the third threshold value from the data measurement value (n + 1) currently measured by the heart rate measuring device and a value obtained by subtracting the third threshold value from the next measured data measurement value (n + 2) Is a negative value (S811). That is, the point at which the negative value comes out is the point passing the third threshold value.

If it is a negative value, the currently measured time n + 1 and the next measured time n + 2 are set in the range, and the minimum value n in this range is obtained (S813).

If the minimum value is smaller than the fourth threshold value, it is recognized as the minimum value (S815, S817). If the minimum value is larger than the fourth threshold value, the waveform distortion is regarded as noise and is not recognized as the minimum value (S815 and S819).

In this manner, the maximum value recognition process and the minimum value recognition process are performed for a predetermined measurement time (S821), and the measurement time interval between the maximum values recognized after the measurement time and the measurement time interval between the minimum values are calculated (S823) . For example, it is possible to set the measurement time for measurement for 60 seconds, and the measurement time can be arbitrarily set according to the embodiment.

Then, an average value obtained by averaging the measurement time intervals between the maximum values and the measurement time intervals between the minimum values is calculated (S825).

Then, the heart rate is calculated using the average value (S827). In the case of heart rate per minute, it is obtained by dividing 60 by the average value.

As described above, in the second-order algorithm of the present invention, as in the first-order algorithm, first, the range is divided to obtain the maximum value, the next is the minimum value of the predetermined range, then the maximum value of the next convex point, Go ahead. In this way, we can obtain the time interval of the maximum value and the minimum value of the minimum value, and by dividing the mean value by 60, the heart rate per minute (BPM) can be obtained. Assuming that this second-order algorithm measures the same time, it can obtain twice the sample value compared with the conventional method, so that it can obtain more accurate BPM value per minute, and when compared with the same data sample, There is an advantage that it can be reduced.

9 is a graph and a graph showing an average and a standard deviation of a Gaussian distribution comparing 100 measured values by comparing the first and second algorithms of the present invention.

Referring to FIG. 9, when comparing the heart rates using two algorithms using only infrared rays, the heart rate averages are 105.54 and 104.8, respectively, while the standard deviation is 12.3% reduced from 11.54 to 10.11. Thus, it can be seen that the heart rate values calculated through the secondary algorithm of the present invention are measured closer to the average. It can be seen that the sample value of the second-order algorithm is twice as accurate as the sample value of the first-order algorithm, so that it can be measured more accurately and quickly.

FIG. 10 is a diagram illustrating an optical blood flow measured at the neck using a first-order algorithm and a second-order algorithm of the present invention. FIG.

10 is a graph comparing the accuracy of the heart rate per minute (BPM) and the ability to perform extensive measurements when the algorithm proposed in the present invention is applied.

In the embodiment of FIG. 10, measurements were made using infrared rays on the neck, and measurements were made on all the A, B, C, D, and E sites.

The left graph is a graph showing the average value and the standard deviation of the heart rate per minute measured by the conventional algorithm, and the graph on the right side is a graph of each area measured by applying the first algorithm and the second algorithm.

The y-axis (standard deviation) value of the right graph is 30 or less as compared to the left graph, and the average heart rate range is further collected in the right graph as compared with the left graph. This means that when the heart rate per minute is measured by applying the algorithm proposed in the present invention, it can be measured with higher reliability and further extended to the range of the A portion. Therefore, it can be seen that in the measurement range, the algorithm proposed in the present invention can be expanded much more than when the conventional algorithm is applied.

As described above, according to the present invention, it is possible to easily apply the algorithm applied to the PPG sensor in the wearable device and the IoT device, and by using the first-order algorithm and the second-order algorithm processing method proposed by the present invention, More accurate heart rate (BPM) values can be measured. In addition, when the algorithm proposed in the present invention is used for a measurement site, the measurement can be made wider than that using the existing algorithm. In addition, the second algorithm of the present invention is advantageous in that the heart rate can be measured rapidly even in a very small sensor having a limited power consumption and size.

Meanwhile, the heart rate measuring method according to the embodiment of the present invention can be implemented as a computer-readable code on a computer-readable recording medium. A computer-readable recording medium includes all kinds of recording apparatuses in which data that can be read by a computer system is stored.

For example, the computer-readable recording medium includes a ROM, a RAM, a CD-ROM, a magnetic tape, a hard disk, a floppy disk, a removable storage device, a nonvolatile memory, , Optical data storage devices, and the like.

In addition, the computer readable recording medium may be distributed and executed in a computer system connected to a computer communication network, and may be stored and executed as a code readable in a distributed manner. In addition, functional programs, codes, and code segments for implementing the present invention can be easily inferred by programmers of the technical field to which the present invention belongs.

While the present invention has been described with reference to several preferred embodiments, these embodiments are illustrative and not restrictive. It will be understood by those skilled in the art that various changes and modifications may be made therein without departing from the spirit of the invention and the scope of the appended claims.

Claims (5)

In a method of measuring a heart rate in a heart rate measuring apparatus for measuring a blood flow volume using an LED (Light Emitting Diode) and a photodiode,
Multiplying a value obtained by subtracting a first threshold value from a data measurement value n currently measured in the heart rate measuring apparatus and a value obtained by subtracting a first threshold value from a next measured data measurement value n + 1, Judging whether or not it is in a first state;
If the value n is a negative value, the present measurement time n and the next measurement time n + 1 are defined as the measurement range, and the maximum value (n) within the measurement range is obtained;
Recognizing the maximum value n as a maximum value if the maximum value n is greater than a second threshold value and not recognizing the maximum value as a maximum value if the maximum value n is less than the second threshold value;
Performing the maximum value recognition process for a predetermined measurement time and calculating a time value that is a measurement time interval between the recognized maximum values after the measurement time;
Calculating an average value obtained by averaging the time values; And
And calculating a heart rate using the average value.
The method according to claim 1,
In the step of calculating the heart rate,
And calculating a heart rate per minute (BPM) by dividing the heart rate (60) by the average value.
In a method of measuring a heart rate in a heart rate measuring apparatus for measuring a blood flow volume using an LED (Light Emitting Diode) and a photodiode,
Multiplying a value obtained by subtracting a first threshold value from a data measurement value n currently measured in the heart rate measuring apparatus and a value obtained by subtracting a first threshold value from a next measured data measurement value n + 1, Judging whether or not it is in a first state;
If the value n is a negative value, the present measurement time n and the next measurement time n + 1 are defined as the measurement range, and the maximum value (n) within the measurement range is obtained;
Recognizing the maximum value n as a maximum value if the maximum value n is greater than a second threshold value and not recognizing the maximum value as a maximum value if the maximum value n is less than the second threshold value;
(N + 1) obtained by subtracting the third threshold value from the next data measured value (n + 2) by multiplying a value obtained by subtracting the third threshold value from the data measured value Determining whether the value is a negative value;
If the value is a negative value, the current measurement time n + 1 and the next measurement time n + 2 are defined as the measurement range, and the minimum value (n) within the measurement range is obtained;
Recognizing the minimum value as a minimum value if the minimum value n is smaller than the fourth threshold value and not recognizing the minimum value as a minimum value if the minimum value is larger than the fourth threshold value;
Performing the maximum value recognition process and the minimum value recognition process for a predetermined measurement time and calculating a measurement time interval between the measurement time interval and the minimum value between the recognized maximum values after the measurement time;
Calculating a mean value of a measurement time interval between the maximum values and a measurement time interval between the minimum values; And
And calculating a heart rate using the average value.
The method of claim 3,
In the step of calculating the heart rate,
And calculating a heart rate per minute (BPM) by dividing the heart rate (60) by the average value.
A computer-readable recording medium having recorded thereon a program capable of executing a method according to any one of claims 1 to 4 by a computer.

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