Electrocardiograph device and body abnormality detection method using same

Abstract

An electrocardiograph device comprises: a body position determination unit for determining the body position of a body; an electrocardiogram measurement unit which can measure the heart rate variability of the body according to the body position; a storage unit for storing first data related to the heart rate variability in a normal state of the body for each body position; a control unit for controlling the body position determination unit and the electrocardiogram measurement unit to extract second data related to the heart rate variability for a specific body position by providing driving signals to the body position determination unit and the electrocardiogram measurement unit when a specific event occurs; and a comparator which generates comparison data comparing the first data for the specific body position obtained from the storage unit and the second data obtained from the electrocardiogram measurement unit. Accordingly, the amount of change in the heart rate variability can be calculated on the basis of the same body position.

Description

Electrocardiograph device and method for detecting physical abnormalities using the same

[0001] Embodiments of the present invention relate to an electrocardiogram (ECG) device and a method for detecting physical abnormalities using the same. More specifically, embodiments of the present invention relate to an ECG device that measures heart rate variability (HRV) and a method for detecting physical abnormalities using the HRV.

[0002] Heart rate variability (HRV) is one of the measurements used to evaluate the activity of the heart's autonomic nervous system. Key indicators of HRV include low frequency (LF) and very low frequency (VLF), which indicate sympathetic nervous system activity; high frequency (HF), which indicates parasympathetic nervous system activity; the LF / HF ratio; RR interval (RR), standard deviation of RR intervals (SDRR), and total power (TP). These indicators are collectively referred to as heart rate variability, and are used to measure and interpret changes in heart rate due to the activity of the heart's autonomic nervous system.

[0003] In general, healthy people have high heart rate variability and stable heart activity, whereas people under stress or physical strain may have low heart rate variability.

[0004] To evaluate heart rate variability, indicators such as LF, HF, and TP, which are obtained by extracting the time interval between each heartbeat from the electrocardiogram information and calculating the signal intensity in the frequency domain through Fourier transform, and the standard deviation value (SDRR) of the time between electrocardiogram RR peaks of adjacent heartbeats can be used as indicators.

[0005] TP is defined as the sum of power values ​​obtained from the VLF, LF, and HF frequency bands. That is, TP = VLF power + LF power + HF power. Here, LF (Low Frequency) and HF (High Frequency) are indicators of the frequency domain primarily used in measuring heart rate variability.

[0006] That is, LF represents heart rate variability in the frequency range of 0.04-0.15 Hz and may be primarily related to sympathetic nerve activity. On the other hand, HF represents heart rate variability in the frequency range of 0.15-0.4 Hz and is primarily related to parasympathetic nerve activity and breathing.

[0007] Here, the autonomic nervous system, comprised of the sympathetic and parasympathetic nerves, influences cardiac regulation and other bodily functions. The sympathetic nervous system is activated in stressful situations, triggering responses such as increased heart rate and elevated blood pressure. Conversely, the parasympathetic nervous system is activated in resting states and contributes to decreased heart rate and lowered blood pressure.

[0008] Meanwhile, the LF / HF ratio, which is the ratio of LF to HF, is used to assess the relative activity of the sympathetic and parasympathetic nervous systems. A higher LF / HF ratio indicates greater sympathetic nervous system activity and may indicate stress or psychological tension. Conversely, a lower LF / HF ratio indicates greater parasympathetic nervous system activity and may indicate a state of stability or relaxation.

[0009] Additionally, RR represents the adjacent RR intervals in an electrocardiogram composed of PQRST waveforms and is the most fundamental indicator in measuring heart rate variability. The RR interval represents the time interval between successive contractions and relaxations of the heart. The RR interval is a value that can directly measure heartbeat variability and is used as one parameter of heart rate variability.

[0010] The standard deviation of RR intervals (SDRR) provides an intuitive indicator of the variability of RR intervals, indicating the degree of heart rate-to-beat variability. Higher SDRR values ​​indicate greater heart rate variability and greater autonomic nervous system (ANS) flexibility. For example, low SDRR values ​​observed during pain may indicate reduced heart rate variability and stiffer ANS function, which can be used as indicators of increased pain perception and consequently reduced ANS pain tolerance.

[0011] The standard deviation of normal-to-normal intervals (SDNN) represents the standard deviation of all normal RR intervals, excluding abnormal or abnormal heart rates. It reflects short-term and long-term heart rate variability and provides a measure of overall autonomic nervous system activity. Similar to SDRR, low SDNN values ​​suggest reduced heart rate variability and impaired autonomic nervous system regulation, which can be used as a marker for a higher level of pain perception in the subject.

[0012] Analysis of heart rate variability in pain assessment involves comparing values ​​obtained during pain-inducing stimuli or across individuals with different pain levels. Typically, individuals with acute or chronic pain exhibit reduced heart rate variability (lower SDRR and SDNN) compared to those without pain. However, pain perception and heart rate variability can be influenced by various factors, including psychological state, medication, and individual differences. Therefore, when using heart rate variability as a pain assessment tool, it should be interpreted in conjunction with other clinical assessments.

[0013] Although heart rate variability alone cannot clearly assess pain intensity, it can be used as a complementary tool to assess pain-related autonomic regulation. Integrating heart rate variability analysis with self-report measures and clinical assessments can provide a more comprehensive understanding of the pain experience.

[0014] Measurement and analysis technologies related to heart rate variability and the autonomic nervous system are widely used in health monitoring, stress management, and exercise physiology research. Analyzing an individual's heart rate variability patterns can help assess and improve stress levels, tension levels, and potential health risks. Furthermore, monitoring exercise training and recovery can be used to optimize exercise outcomes.

[0015] Meanwhile, in order to measure heart rate variability, first, statistical data on the interval between heartbeat signals and a time-series electrocardiogram curve are derived, with time as the x-axis and the magnitude of the electrocardiogram as the y-axis. Then, the time-series electrocardiogram curve can be interpreted based on information in the frequency domain, which is constructed by Fourier transforming the frequency as the x-axis and the signal intensity (power) as the y-axis.

[0016] At this time, any factor that can potentially affect heart rate can cause changes in heart rate variability. Factors related to cardiac output, the heart's most important function, include gravity, changes in body position that alter the amount of gravitational force felt by blood vessels, and body rotation, which can alter cardiac output.

[0017] Here, postural changes trigger vascular reflexes that impede upright venous return, leading to a decrease in cardiac output. Factors that induce changes in pleural fluid volume, cardiac volume, blood pressure, and hemodynamics are closely related to postural changes.

[0018] In 2010, researchers such as Romei compared five different tilt positions: sitting upright, tilting the upper body at 80°, 65°, and 40°, and leaning against the backrest. They found that as the lumbar tilt gradually increased, chest movement and expiratory volume gradually decreased.

[0019] Figure 1 is a diagram to explain the difference in blood pressure in veins according to the posture of the human body.

[0020] Referring to Figure 1, when lying down, the difference in venous blood pressure between the heart, brain, and other body organs is only 8 mmHg, but when an adult of 180 cm tall stands up, the difference in venous blood pressure between the head and feet is 131 mmHg, which is more than 16 times that of when lying down.

[0021] Furthermore, changes in upper body inclination also affect venous blood pressure gradients throughout the body, affecting cardiac output and electrocardiogram (ECG). The subject's posture is also a key factor in determining the gravitational influence on cardiac output pressure gradients.

[0022] Meanwhile, the volume of the thoracic cavity increases during inspiration, and the negative pressure within the thoracic cavity increases during inspiration, increasing the venous blood flowing into the heart and increasing the preload of the heart, which increases the cardiac output, affecting the electrocardiogram.

[0023] Conversely, when the volume of the thoracic cavity decreases during expiration, the venous blood flow to the heart decreases, and the decrease in cardiac preload leads to a decrease in cardiac output.

[0024] At this time, since changes in posture also contribute to changes in intrathoracic preload and volume, the influence of posture must be considered to accurately measure heart rate variability.

[0025] Figure 2 is a graph showing RR values ​​in supine and standing positions.

[0026] Referring to Figure 2, according to “Heart Rate Asymmetry Analysis During Head-Up Tilt Test in Healthy Men” published in Frontiers in Physiology on April 13, 2021, the distribution of RR values ​​in the supine and tilted states shows different distributions, as shown in [Figure 3]. When the supine position is raised 75 degrees while maintaining the supine position, the interbeat interval increases from 1,100 ms to 800 ms.

[0027] Additionally, the standard deviation values ​​of RR data are larger in the supine position, which shows a completely irregular distribution, and smaller in the standing position.

[0028] Therefore, the problem of heart rate variability varying depending on the body's position can arise. Furthermore, because heart rate variability varies from person to person, data related to normal conditions may be required for each patient. Furthermore, for certain diseases, measuring heart rate variability in a specific position can improve diagnostic accuracy.

[0029] Heart rate variability (HRV) is one of the measurements used to evaluate the activity of the heart's autonomic nervous system. Key indicators of HRV include low frequency (LF) and very low frequency (VLF), which indicate sympathetic nervous system activity; high frequency (HF), which indicates parasympathetic nervous system activity; the LF / HF ratio; RR interval (RR), standard deviation of RR intervals (SDRR), and total power (TP). These indicators are collectively referred to as heart rate variability, and are used to measure and interpret changes in heart rate due to the activity of the heart's autonomic nervous system.

[0030] In general, healthy people have high heart rate variability and stable heart activity, whereas people under stress or physical strain may have low heart rate variability.

[0031] To evaluate heart rate variability, indicators such as LF, HF, and TP, which are obtained by extracting the time interval between each heartbeat from the electrocardiogram information and calculating the signal intensity in the frequency domain through Fourier transform, and the standard deviation value (SDRR) of the time between electrocardiogram RR peaks of adjacent heartbeats can be used as indicators.

[0032] TP is defined as the sum of power values ​​obtained from the VLF, LF, and HF frequency bands. That is, TP = VLF power + LF power + HF power. Here, LF (Low Frequency) and HF (High Frequency) are indicators of the frequency domain primarily used in measuring heart rate variability.

[0033] That is, LF represents heart rate variability in the frequency range of 0.04-0.15 Hz and may be primarily related to sympathetic nerve activity. On the other hand, HF represents heart rate variability in the frequency range of 0.15-0.4 Hz and is primarily related to parasympathetic nerve activity and breathing.

[0034] Here, the autonomic nervous system, comprised of the sympathetic and parasympathetic nerves, influences cardiac regulation and other bodily functions. The sympathetic nervous system is activated in stressful situations, triggering responses such as increased heart rate and elevated blood pressure. Conversely, the parasympathetic nervous system is activated in resting states and contributes to decreased heart rate and lowered blood pressure.

[0035] Meanwhile, the LF / HF ratio, which is the ratio of LF to HF, is used to assess the relative activity of the sympathetic and parasympathetic nervous systems. A higher LF / HF ratio indicates greater sympathetic nervous system activity and may indicate stress or psychological tension. Conversely, a lower LF / HF ratio indicates greater parasympathetic nervous system activity and may indicate a state of stability or relaxation.

[0036] Additionally, RR represents the adjacent RR intervals in an electrocardiogram composed of PQRST waveforms and is the most fundamental indicator in measuring heart rate variability. The RR interval represents the time interval between successive contractions and relaxations of the heart. The RR interval is a value that can directly measure heartbeat variability and is used as one parameter of heart rate variability.

[0037] The standard deviation of RR intervals (SDRR) provides an intuitive indicator of the variability of RR intervals, indicating the degree of heart rate-to-beat variability. Higher SDRR values ​​indicate greater heart rate variability and greater autonomic nervous system (ANS) flexibility. For example, low SDRR values ​​observed during pain may indicate reduced heart rate variability and stiffer ANS function, which can be used as indicators of increased pain perception and consequently reduced ANS pain tolerance.

[0038] The standard deviation of normal-to-normal intervals (SDNN) represents the standard deviation of all normal RR intervals, excluding abnormal or abnormal heart rates. It reflects short-term and long-term heart rate variability and provides a measure of overall autonomic nervous system activity. Similar to SDRR, low SDNN values ​​suggest reduced heart rate variability and impaired autonomic nervous system regulation, which can be used as a marker for a higher level of pain perception in the subject.

[0039] Analysis of heart rate variability in pain assessment involves comparing values ​​obtained during pain-inducing stimuli or across individuals with different pain levels. Typically, individuals with acute or chronic pain exhibit reduced heart rate variability (lower SDRR and SDNN) compared to those without pain. However, pain perception and heart rate variability can be influenced by various factors, including psychological state, medication, and individual differences. Therefore, when using heart rate variability as a pain assessment tool, it should be interpreted in conjunction with other clinical assessments.

[0040] Although heart rate variability alone cannot clearly assess pain intensity, it can be used as a complementary tool to assess pain-related autonomic regulation. Integrating heart rate variability analysis with self-report measures and clinical assessments can provide a more comprehensive understanding of the pain experience.

[0041] Measurement and analysis technologies related to heart rate variability and the autonomic nervous system are widely used in health monitoring, stress management, and exercise physiology research. Analyzing an individual's heart rate variability patterns can help assess and improve stress levels, tension levels, and potential health risks. Furthermore, monitoring exercise training and recovery can be used to optimize exercise outcomes.

[0042] Meanwhile, in order to measure heart rate variability, first, statistical data on the interval between heartbeat signals and a time-series electrocardiogram curve are derived, with time as the x-axis and the magnitude of the electrocardiogram as the y-axis. Then, the time-series electrocardiogram curve can be interpreted based on information in the frequency domain, which is constructed by Fourier transforming the frequency as the x-axis and the signal intensity (power) as the y-axis.

[0043] At this time, any factor that can potentially affect heart rate can cause changes in heart rate variability. Factors related to cardiac output, the heart's most important function, include gravity, changes in body position that alter the amount of gravitational force felt by blood vessels, and body rotation, which can alter cardiac output.

[0044] Here, postural changes trigger vascular reflexes that impede upright venous return, leading to a decrease in cardiac output. Factors that induce changes in pleural fluid volume, cardiac volume, blood pressure, and hemodynamics are closely related to postural changes.

[0045] In 2010, researchers such as Romei compared five different tilt positions: sitting upright, tilting the upper body at 80°, 65°, and 40°, and leaning against the backrest. They found that as the lumbar tilt gradually increased, chest movement and expiratory volume gradually decreased.

[0046] Figure 1 is a diagram to explain the difference in blood pressure in veins according to the posture of the human body.

[0047] Referring to Figure 1, when lying down, the difference in venous blood pressure between the heart, brain, and other body organs is only 8 mmHg, but when an adult of 180 cm tall stands up, the difference in venous blood pressure between the head and feet is 131 mmHg, which is more than 16 times that of when lying down.

[0048] Furthermore, changes in upper body inclination also affect venous blood pressure gradients throughout the body, affecting cardiac output and electrocardiogram (ECG). The subject's posture is also a key factor in determining the gravitational influence on cardiac output pressure gradients.

[0049] Meanwhile, the volume of the thoracic cavity increases during inspiration, and the negative pressure within the thoracic cavity increases during inspiration, increasing the venous blood flowing into the heart and increasing the preload of the heart, which increases the cardiac output, affecting the electrocardiogram.

[0050] Conversely, when the volume of the thoracic cavity decreases during expiration, the venous blood flow to the heart decreases, and the decrease in cardiac preload leads to a decrease in cardiac output.

[0051] At this time, since changes in posture also contribute to changes in intrathoracic preload and volume, the influence of posture must be considered to accurately measure heart rate variability.

[0052] Figure 2 is a graph showing RR values ​​in supine and standing positions.

[0053] Referring to Figure 2, according to “Heart Rate Asymmetry Analysis During Head-Up Tilt Test in Healthy Men” published in Frontiers in Physiology on April 13, 2021, the distribution of RR values ​​in the supine and tilted states shows different distributions, as shown in [Figure 3]. When the supine position is raised 75 degrees while maintaining the supine position, the interbeat interval increases from 1,100 ms to 800 ms.

[0054] Additionally, the standard deviation values ​​of RR data are larger in the supine position, which shows a completely irregular distribution, and smaller in the standing position.

[0055] Therefore, the problem of heart rate variability varying depending on the body's position can arise. Furthermore, because heart rate variability varies from person to person, data related to normal conditions may be required for each patient. Furthermore, for certain diseases, measuring heart rate variability in a specific position can improve diagnostic accuracy.

[0056] An electrocardiogram device according to embodiments of the present invention includes a body position determination unit for determining a body position, an electrocardiogram measurement unit capable of measuring heart rate variability of the body according to the body position, a storage unit for storing first data related to the heart rate variability in a normal state of the body according to the body position, a control unit for controlling the body position determination unit and the electrocardiogram measurement unit to extract second data related to heart rate variability for a specific body position by providing a driving signal to the body position determination unit and the electrocardiogram measurement unit when a specific event occurs, and a comparator for generating comparison data by comparing first data for the specific body position obtained from the storage unit and second data obtained from the electrocardiogram measurement unit with each other.

[0057] In one embodiment of the present invention, the body position determination unit includes a sensor that calculates acceleration or angular velocity for each of three directions by defining the opposite direction of gravity as the Z-axis direction and the frontal view direction in a standing state of the body as the X-axis direction, a calibrator that calculates inclination values ​​of the sensor for each of the three directions using the acceleration or angular velocity, a calibrator that corrects the inclination values ​​of the sensor by using the inclination value of the sensor itself that changes according to the attachment position of the sensor when the body is standing, thereby calculating corrected sensor inclination values, and a determinator that specifies the body position from the corrected sensor inclination values, and the body position determination unit may be attached to a pentagonal cuboid space defined by the inside of a pentagon connecting the pectoralis major tips of the left and right sides of the body, the deltoid tips of both shoulders, and the chin.

[0058] In one embodiment of the present invention, each of the first and second data related to the heart rate variability may include a Standard Deviation of RR intervals (SDRR) or Standard Deviation of Normal-to-Normal intervals (SDNN) value.

[0059] In one embodiment of the present invention, the control unit may be provided to select a specific body position necessary to determine a disease related to an expected abnormality of the body.

[0060] In a method for detecting a body abnormality using heart rate variability according to embodiments of the present invention, the body position is determined by attaching the device to the inside of a pentagonal cuboid space of the body, and the heart rate variability when the body is in a normal state according to the body position is measured. Thereafter, first data related to the heart rate variability for each body position is stored. When a specific event occurs, second data related to the heart rate variability for a specific body position is extracted, and first data and second data for the specific body position are compared to each other to generate data.

[0061] An electrocardiogram device according to an embodiment of the present invention can improve reliability of heart rate variability by comparing first data related to heart rate variability by body position in a normal state and second data related to heart rate variability of a specific body position when a specific event occurs, assuming the same body position.

[0062] Furthermore, since the first data related to the normal heart rate variability of an individual human body is secured in advance, changes in the individual heart rate variability can be effectively confirmed.

[0063] Figure 1 is a diagram to explain the difference in blood pressure in veins according to the posture of the human body.

[0064] Figure 2 is a graph showing RR values ​​in supine and standing positions.

[0065] FIG. 3 is a block diagram illustrating an electrocardiogram device according to one embodiment of the present invention.

[0066] Fig. 4 is a photograph defining the X-axis direction, Y-axis direction, Z-axis direction, and pentagonal cube coexistence space based on the standing state of a human body to which the body position determination unit of Fig. 3 is attached.

[0067] Figure 5 is a flowchart for explaining the method by which the body position measuring unit of Figure 3 determines the body position.

[0068] Figure 6 is an azimuth coordinate system for explaining a method of calculating a sensor's inclination value using acceleration measurement values.

[0069] Figure 7 is a graph showing data on SDRR by body position.

[0070] Figure 8 is a graph showing changes in RR intervals by body position.

[0071] FIG. 9 is a flowchart for explaining a method for detecting a physical abnormality according to embodiments of the present invention.

[0072] Hereinafter, embodiments of the present invention will be described in detail with reference to the attached drawings. The present invention can be modified in various ways and can take various forms, and thus specific embodiments are illustrated in the drawings and described in detail in the text. However, this is not intended to limit the present invention to a specific disclosed form, but it should be understood that all modifications, equivalents, and substitutes included in the spirit and technical scope of the present invention are included. In describing each drawing, similar reference numerals are used to indicate similar components. In the attached drawings, the dimensions of structures are shown larger than actual size to ensure clarity of the present invention.

[0073] While terms like "first" and "second" may be used to describe various components, these components should not be limited by these terms. These terms are used solely to distinguish one component from another. For example, without departing from the scope of the present invention, a first component could be referred to as a "second component," and similarly, a second component could also be referred to as a "first component."

[0074] The terminology used in this application is only used to describe specific embodiments and is not intended to limit the present invention. The singular expression includes the plural expression unless the context clearly indicates otherwise. In this application, it should be understood that the terms "comprise" or "have" indicate the presence of a feature, number, step, operation, component, part, or combination thereof described in the specification, but do not preclude the possibility of the presence or addition of one or more other features, numbers, steps, operations, components, parts, or combinations thereof.

[0075] Unless otherwise defined, 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 pertains. Terms defined in commonly used dictionaries should be interpreted as having a meaning consistent with their meaning in the context of the relevant technology, and will not be interpreted in an idealized or overly formal sense unless explicitly defined herein.

[0076] Fig. 3 is a block diagram illustrating an electrocardiograph device according to one embodiment of the present invention. Fig. 4 is a photograph defining the X-axis direction, the Y-axis direction, the Z-axis direction, and the pentagonal cubic space based on the standing state of a human body to which the body position determination unit of Fig. 3 is attached. Fig. 5 is a flowchart illustrating a method for the body position measurement unit of Fig. 3 to determine the body position. Fig. 6 is an azimuth coordinate system for explaining a method for calculating the inclination value of a sensor using acceleration measurement values.

[0077] Referring to FIGS. 3 to 6, an electrocardiogram device (10) according to one embodiment of the present invention includes a body position determination unit (110), an electrocardiogram measurement unit (120), a storage unit (150), a control unit (160), and a comparator (170). The electrocardiogram device (10) is a device that can measure the electrocardiogram of a body in a normal state and an abnormal state, respectively, and provide data that can help determine whether the body is abnormal.

[0078] The above-mentioned body position determination unit (110) determines the body position. The body position determination unit (110) determines the body position at the time of electrocardiogram measurement, thereby enabling the electrocardiogram device (10) to generate data regarding heart rate variability by body position.

[0079] Referring again to FIGS. 3 to 6, the body position determination unit (110) according to embodiments of the present invention includes a sensor, a calibrator, a calibrator, and a determinator.

[0080] The above sensor calculates acceleration or angular velocity for each of the three axes, with the Z-axis direction being the opposite direction of gravity and the X-axis direction being the frontal view direction in the normal standing state of the body. The normal standing state is defined as a state in which the body is standing in a direction perpendicular to the ground.

[0081] The above calculator calculates the inclination values ​​of the sensor for each of the three-axis directions using the acceleration or angular velocity.

[0082] The above calibrator calculates corrected sensor inclination values ​​by correcting the inclination values ​​of the sensor using the inclination value of the sensor itself, which changes depending on the attachment position of the sensor when the body is standing.

[0083] The above determinator determines the body position of the human body from the corrected sensor inclination values. At this time, the pentagonal cuboid space can be defined as the interior of a pentagon connecting the pectoralis major on both sides of the human body, the deltoid muscles on both shoulders, and the chin.

[0084] Hereinafter, the operation of the body position determination unit will be described with reference to Fig. 5.

[0085] First, acceleration or angular velocity is calculated using a sensor attached inside the pentagonal cube space (P; see Fig. 4) of the human body (S110).

[0086] At this time, the pentagonal cuboid space (P) is defined as the interior of a pentagon connecting the tips of the pectoralis major muscles on both sides of the human body, the tips of the deltoid muscles on both shoulders, and the chin. In particular, the sensor can be attached to the anterior part of the mediastinum of the human body.

[0087] This ensures that the sensor is not pressed against the body when the patient is lying down, preventing discomfort to the user. Furthermore, it facilitates the identification of the supine, semi-sitting (Fowler's), and semi-Fowler's positions, which are frequently used in medical diagnosis. Furthermore, it becomes possible to determine whether the right or left side is more likely to reduce the burden of sleep apnea.

[0088] The above sensor may be, for example, an acceleration sensor or a gyro sensor. In the case of the acceleration sensor, acceleration can be measured, and in the case of the gyro sensor, angular velocity can be measured.

[0089] The human body positions are broadly classified into 12 types, including supine, prone, lateral, dorsolateral, lithotomy, knee-chest, Sims, Fowler, semi-Fowler, Trendelberg, modified Trendelberg, and jackknife positions.

[0090] In relation to the above human body position, the examination area and application situation of the human body can be organized as shown in Table 1 below.

[0091] At this time, the inclination values ​​of the sensor for each of the three-axis directions constituting the local coordinate system are calculated using the acceleration or angular velocity (S120).

[0092] Here, if the sensor is an acceleration sensor, the acceleration in the x-axis direction is α x , the acceleration in the z-axis direction is α z , is defined as , and the acceleration in the y-axis direction is α y is represented as . Here, the x-axis, y-axis, and z-axis constitute the local coordinate system of the sensor. In addition, the acceleration in the y-axis direction (α y ) satisfies mathematical expressions 1 and 2 below.

[0093]

[0094]

[0095] That is, the sensor is constantly detecting a gravitational acceleration of 9.8 m / s^2 toward the center of the Earth, i.e., in the direction of gravity. This is because, when the sensor is attached to the chest of a standing human body, and the human body to which the sensor is attached is in a normal standing state, an acceleration of 9.8 m / s^2 is applied in the negative direction of the Z-axis, which is opposite to the direction of gravity.

[0096] Therefore, when using an acceleration sensor, the vector sum of the gravitational acceleration values ​​in each of the x-axis, y-axis, and z-axis directions is always 1G (9.8m / sec) in magnitude when there is no movement of the human body. 2 ) and the direction is a vector in the (-) Z-axis direction that constitutes the absolute coordinate system. That is, α of the stationary accelerometer x , α Y , α z The magnitude of the vector sum (the square root of the sum of the squares of the three values) always converges to the value 9.8.

[0097] Figure 6 is an azimuth coordinate system for explaining a method of calculating a sensor's inclination value using acceleration measurement values.

[0098] Referring to FIG. 6, the acceleration measurement values ​​for each of the x-axis direction, y-axis direction, and z-axis direction are defined as a vector R, and the inclination values ​​of the sensor itself are defined by the following mathematical expression 3.

[0099] Mathematical formula 3

[0100] θ xr = arccos(R x / R), θ yr = arccos(R y / R), θ zr = arccos(R z / R)

[0101] Here, θ xr , θ yr and θ zr is the inclination of the sensor itself along the x-axis, y-axis, and z-axis directions, respectively, and R x , R y and R z Each is the magnitude of vector R in each direction, where R is the magnitude of vector R.

[0102] Next, the sensor's own inclination value (θ) changes depending on the attachment location of the sensor. xr , θ yr and θ zr ) to derive corrected sensor inclination values ​​by correcting the inclination values ​​of the sensor (S130). The corrected sensor inclination values ​​correspond to sensor inclination values ​​for the X-axis direction, Y-axis direction, and Z-axis direction constituting the absolute coordinate system.

[0103] Here, the Z-axis direction and the X-axis direction can be specified as absolute directions. Furthermore, the Y-axis direction can be defined as a direction that generates the Z-axis direction through a vector product with the X-axis direction. At this time, the X-axis direction, the Y-axis direction, and the Z-axis direction constitute an absolute coordinate system.

[0104] To this end, the z-axis direction, which is the local coordinate system of the sensor itself that changes depending on the attachment location of the sensor, can be corrected to match the (+)Z-axis direction, which is the opposite direction of gravity.

[0105] For example, the sensor inclination value with respect to the z-axis direction, which constitutes the local coordinate system of the sensor itself, can be rotated counterclockwise by 60 to 70° to match the (+) Z-axis direction. The 60 to 70° corresponds to the inclination of a typical adult's chest with respect to the (+) Z-axis direction, which is the direction opposite to gravity.

[0106] Thereafter, the patient's body position is determined from the above-mentioned corrected sensor inclination values ​​(S140).

[0107] The above body position determination unit (110) can measure heart rate variability by body position for the human body in a normal state using an electrocardiogram measurement unit.

[0108] The electrocardiogram measurement unit (120) can measure the heart rate variability of the body according to the body position. At this time, the body may be in a normal state. The normal state refers to a state in which no abnormality is present or is not recognized in the body.

[0109] That is, the electrocardiogram measurement unit (120) can measure the heart rate variability of a normal body according to body position.

[0110] The above electrocardiogram measurement unit (120) may include an electrode pad, a pressure sensor, a tester, and a controller.

[0111] The above electrocardiogram measuring device (100) includes an electrode pad, a pressure sensor (P), an electrocardiogram tester (T), and a controller (G).

[0112] The above electrode pads can be brought into contact with the limbs of the human body.

[0113] Each of the above electrode pads can be connected to the electrocardiogram tester (T) through at least four wires. At this time, the four wires can be connected to a microprocessor included in the electrocardiogram tester (T).

[0114] The pressure sensor (P) is positioned inside each of the electrode pads. The pressure sensor (P) detects the pressure applied to each of the electrode pads. The pressure sensor (P) may include, for example, a film-type pressure sensor such as a load cell.

[0115] The above film-type pressure sensor (P) generally has a measurement range of 0 to 10 kg and a minimum pressure resolution of 1.5 g / 0.0000762 V.

[0116] The above pressure sensor (P) is placed when the human body is lying supine on the bed and the limbs are in contact with the electrode pad. At this time, the pressure sensor (P) placed inside the electrode pad (120) can detect the applied pressure.

[0117] Accordingly, the pressure sensor (P) can detect whether the limbs and electrode pads are in contact with each other. Furthermore, the pressure sensor (P) may have a pressure value that varies depending on the elasticity of the mat and the body's lying position. However, this inevitably reduces the reliability of the electrocardiogram values ​​measured for the body. In other words, the pressure sensor (P) can only determine whether the vibration stability of the limbs being contacted is stable.

[0118] An electrocardiogram tester (T) is electrically connected to each of the electrode pads. The electrocardiogram tester (T) can obtain various electrocardiogram values ​​depending on the interconnection relationship between the electrode pads.

[0119] Meanwhile, aVR is a potential that measures the right arm as the (+) pole, and the voltage of the right arm is measured against it by connecting the left arm and left foot. aVL is a potential that measures the left arm as the (+) pole, and the voltage of the left arm is measured against it by connecting the right arm and left foot. aVF is a potential that measures the left foot as the (+) pole, and the voltage of the left leg is measured against it by connecting the right arm and left arm. At this time, the right leg is used as a ground electrode in all of the above measurements. Thus, the electrocardiogram measuring device according to the present invention can implement 6-lead measurement.

[0120] The controller (G) uses the pressure data transmitted from the pressure sensor (p) to ensure that the human body is in a stable state and then generates a test start signal for the electrocardiogram tester (T). In other words, the controller (G) allows the electrocardiogram tester (T) to begin testing only after confirming that the human body is in a stable state. Therefore, the reliability of the electrocardiogram-related data obtained by the electrocardiogram tester (T) can be ensured.

[0121] Accordingly, the electrocardiogram measurement unit (120) can measure the heart rate variability of a normal body according to body position.

[0122] The storage unit (150) stores first data related to the heart rate variability for each body position. The storage unit (150) may include, for example, a database.

[0123] Figure 7 is a graph showing data on heart rate variability by body position.

[0124] Referring to Fig. 7, data for calculating heart rate variability (SDRR, SDNN, RR, LF power, HF power, LF / HF Ratio) is recorded together with the electrocardiogram and the body position when the electrocardiogram is measured, and data for one of the positions A to F (or other multiple positions) is used in a database that records electrocardiograms by body position.

[0125] Performing ECG measurements by body position in this manner can reduce errors in heart rate variability measurements caused by different body positions. This eliminates the influence of body position changes, which directly affect cardiac output and ECG patterns, which determine heart rate variability.

[0126] Figure 8 is a graph showing changes in RR intervals by body position.

[0127] Referring to Figures 2 and 8, A is supine, B is standing walking, C is Fowler's position, and D is semi-Fowler's position, and the changes in RR values ​​in each position / posture are shown. In the case of B, it is intuitively shown that the pulse rate and pulse interval and the range of the peak's vertical change are reduced compared to other positions, and thus the standard deviation of the RR value (SDRR) is reduced.

[0128] The control unit (160) provides a driving signal to the body position determination unit and the electrocardiogram measurement unit when a specific event occurs, thereby controlling the body position determination unit (110) and the electrocardiogram measurement unit (120) to extract second data related to heart rate variability for a specific body position.

[0129] At this time, the event corresponds to a case where an abnormality is recognized in a specific part of the body or a diagnosis of an abnormality in the body is required.

[0130] That is, the control unit (160) provides a driving signal to the body position determination unit and the electrocardiogram measurement unit when necessary to extract second data related to heart rate variability for a specific body position.

[0131] The above comparator (170) generates comparison data by comparing the first data and the second data for the specific body position obtained from the storage unit (150).

[0132] In addition, the comparator (170) can determine that the comparison data, which is the difference between the first and second data values, is abnormal if it exceeds a reference value, for example, 5%.

[0133] The electrocardiogram device (10) may include, in each of the first and second data related to the heart rate variability of the electrocardiogram, a Standard Deviation of RR intervals (SDRR) or a Standard Deviation of Normal-to-Normal intervals (SDNN) value. As a result, the electrocardiogram device (10) may secure more reliable data on whether there is an abnormality in the body.

[0134] In one embodiment of the present invention, the control unit (160) may enable selection of a specific body position necessary to determine a disease related to an expected abnormality of the body.

[0135] For example, in the case of Brugada syndrome (BrS), heart rate variability values ​​measured in the right-sided supine position can be helpful in making an accurate diagnosis.

[0136] An electrocardiogram device (10) according to an embodiment of the present invention can improve the reliability of heart rate variability by comparing first data related to heart rate variability by body position in a normal state with second data related to heart rate variability of a specific body position when a specific event occurs, assuming the same body position.

[0137] Furthermore, since the first data related to the normal heart rate variability of an individual human body is secured in advance, changes in the individual heart rate variability can be effectively confirmed.

[0138] FIG. 9 is a flowchart illustrating a method for detecting a physical abnormality according to embodiments of the present invention. The method for detecting a physical abnormality can be implemented using the electrocardiogram device illustrated in FIG. 3.

[0139] The body position is determined by attaching it to the inside of the pentagonal cuboid space (P, see Fig. 4) of the body (S210). At this time, the pentagonal cuboid space is defined as the interior of a pentagon connecting the apices of the pectoralis major on the left and right sides of the patient, the apices of the deltoid muscles on both shoulders, and the chin. In particular, the sensor can be attached to the anterior part of the patient's mediastinum.

[0140] Next, the heart rate variability is measured when the body is in a normal state according to the above-mentioned posture (S220).

[0141] Thereafter, first data related to the heart rate variability for each body position is stored (S230).

[0142] After determining whether a specific event has occurred (S240), second data related to heart rate variability for a specific body position is extracted (S250). An event refers to a case where an abnormality is detected in a specific body part or a diagnosis of a physical abnormality is required.

[0143] Comparison data is generated by comparing the first data and the second data for the specific body position (S260). That is, the first data and the second data for the same specific body position are compared. Therefore, the reliability of the comparison data can be improved.

[0144] Meanwhile, since the first data related to the normal heart rate variability of an individual human body is secured in advance, changes in the individual heart rate variability can be precisely identified.

[0145] A device according to embodiments of the present invention may include a processor, a memory for storing and executing program data, permanent storage such as a disk drive, a communication port for communicating with an external device, a user interface device such as a touch panel, a key, a button, etc. Methods implemented as software modules or algorithms may be stored on a computer-readable recording medium as computer-readable codes or program instructions executable on the processor. Here, the computer-readable recording medium includes a magnetic storage medium (e.g., read-only memory (ROM), random-access memory (RAM), floppy disk, hard disk, etc.) and an optical reading medium (e.g., CD-ROM, DVD: Digital Versatile Disc)). The computer-readable recording medium may be distributed to computer systems connected through a network, so that the computer-readable code may be stored and executed in a distributed manner. The medium may be readable by a computer, stored in a memory, and executed by a processor.

[0146] Embodiments of the present invention may be represented by functional block configurations and various processing steps. These functional blocks may be implemented by various hardware and / or software components that perform specific functions. For example, embodiments may employ integrated circuit components, such as memory, processing, logic, and look-up tables, that may perform various functions under the control of one or more microprocessors or other control devices. Similarly, embodiments may be implemented in a programming or scripting language, such as C, C++, Java, or an assembler, including various algorithms implemented as a combination of data structures, processes, routines, or other programming components. Functional aspects may be implemented as algorithms that execute on one or more processors. Furthermore, embodiments may employ conventional techniques for electronic configuration, signal processing, and / or data processing. Terms such as "mechanism," "element," "means," and "composition" can be used broadly and are not limited to mechanical or physical structures. These terms can also encompass a series of software routines, such as those associated with a processor.

[0147] Embodiments of the present invention relate to an electrocardiogram device for measuring heart rate variability (HRV) and a body abnormality detection method capable of detecting abnormalities in the body using the heart rate variability, and can be applied to fields such as the medical industry and the sports industry.

[0148] The present invention has been described above, focusing on preferred embodiments thereof. Those skilled in the art will appreciate that the present invention can be implemented in modified forms without departing from its essential characteristics. Therefore, the disclosed embodiments should be considered illustrative rather than limiting. The scope of the present invention is set forth in the claims, not the foregoing description, and all differences within the scope equivalent thereto should be construed as being encompassed by the present invention.

Claims

1. Body position judgment unit that judges the body position; An electrocardiogram measuring unit capable of measuring the heart rate variability of the body according to the above-mentioned body position; A storage unit that stores first data related to the heart rate variability in the normal state of the body for each body position; A control unit that provides a driving signal to the body position determination unit and the electrocardiogram measurement unit when a specific event occurs, thereby controlling the body position determination unit and the electrocardiogram measurement unit to extract second data related to heart rate variability for a specific body position; and An electrocardiogram device including a comparator that compares first data for the specific body position obtained from the storage unit and second data obtained from the electrocardiogram measurement unit to generate comparison data.

2. In the first paragraph, the position determination unit, A sensor that calculates acceleration or angular velocity for each of the three axes, with the opposite direction of gravity defined as the Z-axis direction and the frontal view direction of the body in a standing state defined as the X-axis direction; A calculator that calculates the inclination values ​​of the sensor for each of the three-axis directions using the acceleration or angular velocity; A calibrator that calculates corrected sensor inclination values ​​by correcting the inclination values ​​of the sensor using the inclination value of the sensor itself that changes depending on the attachment location of the sensor when the body is standing; and A determinator for determining the body position from the above-mentioned corrected sensor inclination values; An electrocardiograph device characterized in that the above-mentioned body position determination unit is attached to a pentagonal cube-shaped space defined by the inside of a pentagon connecting the tips of the pectoralis major muscles on the left and right sides of the body, the tips of the deltoid muscles on both shoulders, and the chin.

3. An electrocardiograph device according to claim 1, wherein each of the first and second data related to the heart rate variability includes a Standard Deviation of RR intervals (SDRR) or Standard Deviation of Normal-to-Normal intervals (SDNN) value.

4. An electrocardiograph device according to claim 1, characterized in that the control unit is provided to select a specific body position necessary to determine a disease related to an expected abnormality of the body.

5. A step of determining the body's position by attaching it to the inside of the body's pentagonal cube space; A step of measuring heart rate variability when the body is in a normal state according to the above posture; A step of storing first data related to the heart rate variability for each body position; A step of extracting second data related to heart rate variability for a specific body position when a specific event occurs; and A method for detecting a physical abnormality using heart rate variability, comprising the step of generating data by comparing first data and second data for the specific body position.

6. A method for detecting a body abnormality, characterized in that in the fifth paragraph, each of the first and second data related to the heart rate variability includes a Standard Deviation of RR intervals (SDRR) or Standard Deviation of Normal-to-Normal intervals (SDNN) value.

7. A method for detecting a body abnormality, characterized in that in the fifth paragraph, the step of extracting the second data can select a specific body position necessary for determining a disease related to an expected abnormality of the body.

8. A method for detecting a body abnormality in the fifth paragraph, characterized in that the pentagonal cube-shaped space is defined as the interior of a pentagon connecting the tips of the pectoralis major muscles on the left and right sides of the body, the tips of the deltoid muscles on both shoulders, and the chin.

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