KR101503604B1 - Wearable type System for realtime monitoring blood pressure estimation and Method for controlling the same - Google Patents

Abstract

The present invention relates to a wearable system for monitoring blood-pressure estimation in real time and to a control method of the same, wherein the wearable system is equipped with a measuring electrode and a display part in a main body having a human-wearable shape and can continuously monitor blood pressure using a non-invasive method in a ubiquitous environment. The wearable system has a sensor module which includes: a first electrode prepared on the inner surface of the main body having a human-wearable shape, and touching a human body when worn by a user; and a second electrode prepared on the outer surface of the main body. The wearable system measures the electrocardiogram (ECG) signal, photoplethysmography (PPG) signal, and saturation of peripheral oxygen (SpO_2) signal of the human body.

Description

[0001] WATER-BASED REAL-TIME Blood Pressure Estimation Monitoring System and Control Method [0002]

The present invention relates to real-time blood pressure estimation using multiple bio-signals. More specifically, the present invention relates to a method and apparatus for measuring blood pressure continuously by applying a non-invasive method in a ubiquitous environment, To a wearable real-time blood pressure estimation monitoring system and a control method thereof.

Recently, the rapid development of science and technology has improved the quality of life of the whole human being, and many changes have occurred in the medical environment. In past hospitals, medical images such as X-ray, CT, and fMRI were taken and it was possible to read the images only after several hours or several days.

However, after a medical image was taken 10 years ago, a Picture Archive Communication System (PACS) was introduced, which allows images to be transmitted to a monitor screen of a radiologist and then read out immediately.

Also, many ubiquitous healthcare-related medical devices that can confirm their blood sugar and blood pressure at any time without going to a hospital are widely used, and blood glucose patients or hypertension patients use them in their own homes or offices.

Hypertension is a major cause of cardiovascular disease and is also a major cause of stroke. Hypertension is costing the world $ 300 billion a year in medical costs. It is reported that 25% of adults around the world as well as Korea are hypertensive, and 1 in 3 Americans are hypertensive.

In Korea, 30% of adults over 30 years belong to the high - risk group, and the prevalence of hypertension increases with age. The prevalence of hypertension is about 50% in adults over 60 years of age.

In order to inform the risk of hypertension in a shorter time, we need a system that continuously measures blood pressure and informs it in real time.

Various types of studies have been attempted to reduce the mortality due to hypertension.

One of them is to measure the blood pressure in real time by inserting the blood pressure measurement sensor into the pulmonary artery of the patients with chronic heart disease and then transmit it to the primary care physician using the wireless communication to monitor the patient's pulmonary artery blood pressure change pattern (U_Health; ubiquitous healthcare), which delivers prescriptions to patients, has been proposed to dramatically reduce the number of times patients are required to enter the hospital.

In clinical practice, a method of measuring blood pressure by inserting a catheter into an arterial blood vessel is one of the methods of measuring invasive blood pressure. However, this method can measure blood pressure continuously and accurately, but it is performed only when it is absolutely necessary due to the difficulty of operation, the risk of arterial injury, and infection.

Therefore, a system for real-time measurement of blood pressure in a non-invasive manner without inserting a sensor for blood pressure measurement into arterial blood vessels has been continuously studied.

Also, blood pressure was monitored in ubiquitous environment, and blood pressure was adjusted by biofeedback to measured blood pressure.

For example, when a patient is alerted to signs of hypertension due to anxiety and stress, the patient is notified of the risk of hypertension, and the patient is able to adjust his or her own blood pressure drop by switching to a biofeedback or stable state.

In particular, in order to receive emergency treatment within a short time, it is necessary to provide a system that continuously measures the blood pressure and informs it in real time in order to inform the risk of hypertension in a shorter time.

It is difficult to measure the blood pressure continuously by attaching a cuff to the arm. It is impossible to measure your own blood pressure when you work or relax, unless someone measures your blood pressure or you do not operate your blood pressure monitor yourself.

Therefore, a device that measures blood pressure at all times is needed. In addition, when the blood pressure reaches the danger level, it is monitored quickly and feedback is provided to the patient to prevent and manage hypertension by the patient himself

Is required.

As such, there is a need to develop a new monitoring system capable of continuously monitoring blood pressure in a non-invasive manner in a ubiquitous environment and managing blood pressure without relying on drugs.

In order to solve the problem of the conventional blood pressure monitoring system, the present invention is equipped with a measurement electrode and a display unit in a body of a wearable form for monitoring the blood pressure continuously by applying a non-invasive method in a ubiquitous environment A real-time blood-pressure monitoring system and method.

The present invention relates to a sensor module for measuring the electrocardiogram (ECG), photoelectric pulse wave (PPG) and oxygen saturation (SpO ₂ ) signals of a human body, And a wearable real-time blood pressure estimation monitoring system and method in which a gate module that receives biometrics signal data wirelessly transmitted from a sensor module and transmits the biometrics signal data to the Internet using IPv4 or IPv6 based TCP / IP communication is provided in the main body. .

The present invention relates to a sensor module for measuring the electrocardiogram (ECG), photoelectric pulse wave (PPG) and oxygen saturation (SpO ₂ ) signals of a human body, And a signal analysis processor for analyzing a signal, a monitor for a screen output and an alarm, and a method for monitoring and monitoring a wearable real-time blood pressure.

The present invention measures the ECG, PPG and SpO ₂ vital signs, calculates the pulse transit time using the ECG, the PPG signal, the ECG and the SpO ₂ signal, estimates the blood pressure and continuously monitors the blood pressure A real-time blood-pressure monitoring system and method.

The present invention provides an apparatus and method for monitoring and measuring bio-signals, which is capable of maintaining stable power supply and transmitting or receiving measured bio-signals using wireless communication, The present invention aims to provide a blood pressure management system which can be carried in a ubiquitous health and mobile healthcare environment and is easy to use by being transmitted to an internet environment by wireless communication.

The present invention provides a WBAN-based platform capable of supporting existing TCP / IP communication based on IPv4 as well as being able to operate without restriction even in an IPv6 environment. Through this, hypertensive patients continuously monitor their blood pressure, The present invention provides a wearable real-time blood pressure estimation monitoring system and method that can be managed before stroke and prevent normal hypertension in normal people.

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 attain the above object, a wearable real-time blood pressure estimation monitoring system according to the present invention comprises: a first electrode formed on an inner surface of a body having a wearable form to be in contact with a human body, (ECG), photoelectric pulse wave (PPG), and oxygen saturation (SpO ₂ ) signals of the human body.

Here, the body having a wearable form is further provided with a display screen for displaying the result of the measurement and analysis of the measured signal.

The systolic blood pressure, the diastolic blood pressure, and the pulse are displayed on the display screen, and the graph of the change of the ECG signal and the PPG signal can be displayed. The display contents and the display style can be displayed by the display mode and the display contents selection buttons And is displayed by being changed.

The display screen provided on the main body having the human-wearable form becomes the second electrode, and the human body is brought into contact with the display screen when the living body signal is measured.

The main body having a human-wearable shape further includes an electrode connection terminal for connecting other electrodes for measuring a living body signal.

The measurement electrode module is connected to the electrode connection terminal to measure PPG and SPO ₂ signals. The measurement electrode module includes a red LED having a wavelength of 660 nm, an infrared ray having a wavelength of 940 nm An LED is configured, and a photodiode is configured in the light receiving portion.

In addition, the main body having a human-wearable form may further include a measurement electrode module in which a red LED having a wavelength of 660 nm and an infrared LED having a wavelength of 940 nm are formed in the light emitting portion and a photodiode is formed in the light receiving portion.

In order to accomplish the above objects, the present invention provides a wearable real-time blood pressure estimation and monitoring system, comprising: a first electrode formed on a rear surface of a main body, which is an inner surface of a wrist; and a second electrode, A sensor module for measuring the electrocardiogram (ECG), the photoelectric pulse wave (PPG), and the oxygen saturation (SpO ₂ ) signals of the human body through a digital conversion and wirelessly transmitting the signals, Or a gate module for transmitting to the Internet using IPv6-based TCP / IP communication.

Here, a monitoring system for analyzing bio-signal data received through the gate module and estimating blood pressure in real time to perform screen output and data storage, and a monitoring system for simultaneously supporting IPv4 and IPv6 environments, address registration, and Serial to Peripheral Interface ) Initialization and hardware reset operation, an auto-configuration process for IPv6 and IPv4 after hardware reset, and a dual-stack driver for performing a loopback operation to determine an operation mode according to the state of a received or transmitted packet ; ≪ / RTI >

According to still another aspect of the present invention, there is provided a wearable real-time blood pressure estimation monitoring system comprising: a first electrode formed on a back surface of a main body which is an inner surface of a wrist; (ECG) measured by the sensor module, and a sensor module for measuring an electrocardiogram (ECG), a photoelectrical pulse wave (PPG) and an oxygen saturation (SpO ₂ ) A signal analysis processor for analyzing a photoelectric pulse wave (PPG) and an oxygen saturation (SpO ₂ ) signals to estimate a blood pressure in real time, and a monitoring system for screen output and alarm according to an analysis result of the signal analysis processor, A sensor module, a signal analysis processor, and a monitoring system are built in the main body.

The sensor module includes a sensor unit for processing biological signals measured in the body, a digital measurement system for quantizing and converting the analog signals measured by the sensor unit into digital signals, And a Bluetooth communication unit for wirelessly transmitting the data.

In order to achieve the above object, a method of controlling a wearable real-time blood pressure estimation monitoring system according to the present invention is a method for estimating a blood pressure after calculating a pulse transit time using an ECG, a PPG signal, and an SpO ₂ signal A first electrode formed on a back surface of a wearable body which is an inner surface when wrist is worn, and an ECG and PPG signal measured through a second electrode formed on the front surface of a wearable body which is an outer surface when wrist is worn A step of classifying the ECG data by a setting unit after waiting for setting a threshold value used for peak analysis, a step of calculating a first peak value by a peak analysis algorithm using the divided data, ; further comprising: after extracting the first Peak values by applying the same method to extract in succession the following: Peak value, and stores the extracted time information (t1, t2); the RR interval Is the time difference between the two Peak point - to calculate the (t2 t1) identifying the number of sampling data size moving window of the PPG signal (Moving window size) comprising: reflected on; negative of the PPG data existing between the RR interval ECG data Extracting a peak (Negative Peak) and a positive peak from time information ( TN ) and ( TP ) using vertex analysis, extracting time information ( t1 ) of the peak point of the first ECG and And calculating PTT = ( T1 - t1 ) which is the first PTT time information using the time information T1 = ( TN + TP ) / 2 at the midpoint between the S point and the P point.

Here, the PTT is a time difference from the R peak of the ECG waveform to the peak of the PPG measured in the peripheral blood vessel, and a peak of one PPG signal necessarily exists between the R peak of the first ECG signal and the R peak of the second ECG signal .

In order to achieve the above object, a control method of a wearable real-time blood pressure estimation monitoring system according to the present invention is a method for estimating real-time systolic blood pressure using an ECG, a PPG signal and an SpO ₂ signal, The PPG signal and the SpO ₂ signal are measured through the first electrode formed on the rear surface of the main body of the wrist and the second electrode formed on the front surface of the wearable body which is the outer surface when wrist is worn, ( IRAC ) by an infrared light source, a DC component ( IRDC ) by an infrared light source, and an AC component by a red light source ( REDAC ) , Storing DC component ( REDDC ) data by a red light source for a preset time and calculating an average value thereof at a set time interval; calculating IRAC , IRDC , RED AC , REDDC Storing the ECG data, as measured by the output SpO ₂ value, the extracted PTT values, real-time, each arranged in the corresponding registers, the method comprising using an average value of the data operation once the SpO ₂ value in real time in one second; Save and after performing the above steps repeatedly for 53 seconds results to 53rd stored SpO ₂ value SpO ₂ [k53], 9 beonjjae stored PTT value PTT [j9], the first stored ECG value ECG [i1] value And calculating the real-time systolic blood pressure (SYS BP) by applying SpO ₂ [ k53 ], PTT [ j9 ], and ECG [ i1 ] information to the systolic blood pressure estimation model.

Here, the calculated real-time systolic blood pressure SYS BP is stored again as the blood pressure information SYS BP [ x1 ] and notified to the user when the calculated real time systolic blood pressure SYS BP is 20 mmHg or more than the reference blood pressure of the user (reference SYS BP).

And the calculated IRAC, IRDC, REDAC, REDDC The step of calculating the SpO ₂ value in real time using the average value of the data is a step of calculating the amount of change in the AC component and the DC component by the red light source and the infrared light source

으로 연산하는 것을 특징으로 한다.

.

According to still another aspect of the present invention, there is provided a method for controlling a wearable real-time blood pressure estimation system, comprising the steps of: sensing a real-time diastolic blood pressure using a PTT signal and an SpO ₂ signal; The ECG, the PPG signal, and the SpO ₂ signal are measured through the first electrode formed on the rear surface and the second electrode formed on the front surface of the wearable body that is the outer surface when the wrist is worn, and a threshold value for the vertex analysis is set ( IRAC ) by an infrared light source, a DC component ( IRDC ) by an infrared light source, an AC component ( REDAC ) by a red light source, storing the DC components of the red light source (REDDC) data for a set period of time and calculating an average value by setting a time interval; calculated IRAC, IRDC, REDAC, RE DDC The step of using the average value of the data operation once the SpO ₂ value in real time in one second; 31, the above steps; step for storing the SpO ₂ value and the extracted PTT value calculated in the previous step in each array to the register after the in early performed repeatedly stores the result 31st stored SpO ₂ value (SpO ₂ [k31]) and first stored PTT value (PTT [j1]) the step of extracting; stored for 10 seconds after the SpO ₂ [ k31 - 40 ] and PTT [ j1 - 10 ] data using the interval averaging formula; calculating Rj (t) and Rk (t) ; And calculating a real diastolic blood pressure (DIA BP) by applying a diastolic blood pressure estimation model to Rj (t) and Rk (t) information.

Here, the calculated real-time diastolic blood pressure (DIA BP) is stored again as the blood pressure information DIA BP [ y1 ] and notified to the user when it is 20 mmHg or less than the reference blood pressure of the user (reference DIA BP).

The wearable real-time blood pressure estimation and monitoring system and its control method according to the present invention have the following effects.

First, the blood pressure can be continuously monitored and transmitted by applying a non-invasive method in a ubiquitous environment using measurement electrodes provided on the front and back surfaces of the wearable body without a separate electrode configuration.

Second, blood pressure can be estimated by simultaneously measuring electrocardiogram (ECG), photoelectrical pulse wave (PPG), and oxygen saturation (SpO ₂ ) signals among various bio-signals generated in the human body.

Third, the power supply can be stably maintained, and the measured bio-signals can be transmitted or received using wireless communication, thereby enhancing the convenience of carrying and using.

Fourth, since the measured data is transmitted to the Internet environment by wireless communication, it is possible to implement a blood pressure management system which is portable in a ubiquitous health and mobile healthcare environment and is easy to use.

Fifth, it provides WBAN-based platform that supports TCP / IP communication based on IPv4 as well as IPv6 without any restrictions.

Sixth, patients with hypertension can be continuously monitored for blood pressure and managed before the risk, and normal people can also prevent daily hypertension.

1 is a block diagram illustrating a healthcare process using a wireless human body sensor network (WBSN)
FIGS. 2A and 2B are diagrams showing a configuration of a wearable real-time blood pressure estimation monitoring system according to the first and second embodiments of the present invention
FIGS. 3A to 3C are views showing a blood pressure estimation using a wearable real-time blood pressure estimation monitoring system according to the present invention;
4 is a detailed block diagram of a hardware block of a wearable real-time blood pressure estimation monitoring system
5 is a sensor configuration diagram for measuring an ECG signal
6 is a block diagram of the PPG sensor module
7 is a block diagram of the SpO ₂ sensor module
8 is a block diagram of a software module for monitoring multiple biological signals
9A is a detailed configuration diagram of a PC-based monitoring system
9B shows a configuration diagram of a web-based monitoring system
10 is a flowchart showing the operation of the IPv4 / IPv6 dual stack driver
11 is a flowchart showing an initialization process for driving the dual stack driver
12 is a flowchart showing an automatic configuration process
13 is a flowchart showing an operation procedure of the UDP mode for loopback
14 is a flowchart showing an operation procedure of the TCP server mode for loopback
15 is a flowchart showing the operation sequence of the TCP client mode for loopback
16 is a flowchart for real time PTT calculation according to the present invention;
17 is a flowchart for real-time systolic blood pressure estimation according to the present invention
18 is a flowchart for real-time diastolic blood pressure estimation according to the present invention;

Hereinafter, a preferred embodiment of a wearable real-time blood pressure estimation monitoring system and a control method thereof according to the present invention will be described in detail.

The features and advantages of the wearable real-time blood pressure estimation monitoring system and control method thereof according to the present invention will be apparent from the following detailed description of each embodiment.

FIG. 1 is a configuration diagram illustrating a healthcare process using a wireless human body sensor network (WBSN), and FIGS. 2A and 2B are block diagrams of a wearable real-time blood pressure estimation and monitoring system according to the first and second embodiments of the present invention.

U_Health, which uses bio-signals generated from the human body, transmits the data by applying the wireless communication method, and monitors the transmitted bio-signals to diagnose the disease and change the trend, has been continuously carried out.

As shown in FIG. 1, a technique of attaching a sensor to various parts of a human body to measure a living body signal and applying it to a USN is called a Wireless Body Sensor Network (WBSN).

The present invention relates to a sensor module and a sensor module which are equipped with measuring electrodes on the front and back surfaces of a wearable body and measure and digitally convert electrocardiogram (ECG), photoelectric pulse wave (PPG) and oxygen saturation (SpO ₂ ) The present invention includes a technology structure in which a gate module for receiving biometric signal data wirelessly transmitted from a module and transmitting the biometric signal data to the Internet using IPv4 or IPv6 based TCP / IP communication is embedded in a wearable main body.

The present invention relates to a sensor module for measuring the electrocardiogram (ECG), photoelectric pulse wave (PPG), and oxygen saturation (SpO ₂ ) signals of a human body, A signal analysis processor for analysis, a screen output and a monitoring system for alarming are built into the wearable body.

The present invention includes a WBSN construction technique that is easy to connect to the Internet, and has a weak vulnerability to security while implementing WBSN capable of supporting IPv6 based on reliable TCP / IP.

The present invention relates to an electrocardiogram (ECG), a photoplethysmography (PPG), an oxygen saturation (SpO), and a blood oxygen saturation ₂ ; Saturation of Peripheral Oxygen) signals at the same time.

Electrocardiogram (ECG) is a waveform consisting of a vector sum of action potentials generated by a special excitatory & conductive system of the heart. In other words, in the case of the SA node (sinoatrial node), atrioventricular node (AV node), His bundle, bundle branch, furkinje fibers, The vector sum signal of the action potential is a signal measured from an electrode attached to the outside of the body.

In general, the ECG signal is acquired using the standard limb lead method using four electrodes.

And photoelectrically pulse wave (PPG) refers to a pulse wave signal measured in peripheral blood vessels when blood ejected during ventricular systole is delivered to peripheral blood vessels. The optical properties of the biotissue are used to measure the PPG signal.

That is, a PPG sensor capable of measuring a pulse wave signal at a location where peripheral blood vessels of the fingertip and a toe are distributed is a biological signal obtained by converting the change in blood flow, which is the volume change of the peripheral blood vessel, into a change in light amount.

In general, the correlation between PPG and ECG signals is analyzed without using only PPG signal, and the pulse transit time (PTT) or the pulse wave velocity (PWV) is extracted and used for diagnosis of cardiovascular diseases have. To do this, the PPG signal is second-differentiated to obtain the feature points, and then the time interval with the apex (R wave) of the ECG signal is measured.

The PTT and PWV signals extracted in this way are analyzed and used for the status of blood vessels, arteriosclerosis, diagnosis of peripheral circulatory disorders.

Blood oxygen saturation (SpO ₂ ) is a biological signal that indicates the content of oxygen present in hemoglobin among various constituents of blood.

Most of the bio-signal measurement utilities running on the WBSN base are based on locally running applications. Since the vital signal itself is vast, it is very difficult to implement it in a form that can be used by a plurality of users at the same time in real time on the web base.

Accordingly, the present invention configures the system so that it can be applied to large-scale data analysis that operates in a web-based environment.

As shown in FIG. 2A, the wearable real-time blood pressure estimation and monitoring system according to the first embodiment of the present invention is configured by dividing a system for measuring and transmitting multiple bio-signals into a hardware block and a software block.

The hardware block includes a sensor module 20 and a gateway module 30 and a wearable body having measurement electrodes on the front and back surfaces. And a module (gateway module) 30 is embedded therein.

The software block includes a PC-based, smartphone-based, web-based monitoring system 40 and a TCP / IP driver 50 having a dual IPv4 / IPv6 stack, and a socket program.

2B, the wearable-type real-time blood-pressure-estimation monitoring system according to the second embodiment of the present invention includes measurement electrodes on the front and rear surfaces of a wearable body, electrocardiogram (ECG) and photoelectrical pulse wave (PPG) , it is incorporated in the body of type a signal analysis processor, a monitoring system for the screen output and alarm for the wireless transmission module and the sensors to the signal analysis by measuring the oxygen saturation (SpO ₂₎ digital signal converted wear.

In the wearable real-time blood pressure estimation and monitoring system according to the first and second embodiments of the present invention, the electrodes constituting the main body constitute a first electrode for measuring a living body signal on the back surface (inner surface when wrist is worn) A second electrode for measuring a living body signal is formed on the front surface of the main body (an outer surface when the wrist is worn), and the third and fourth electrodes necessary for measurement are connected to the main body.

Of course, it is natural that the third and fourth electrodes necessary for the measurement may be constituted by making contact portions different from the front surface of the main body (the outer surface when the wrist is worn).

FIGS. 3A to 3C are views illustrating bio-signal measurement for estimating a blood pressure using the wearable real-time blood pressure estimation monitoring system according to the present invention.

FIG. 3A shows a state in which a wearable real-time blood pressure estimation monitoring system according to the present invention is worn on a human body. FIG. 3 shows a state in which a screen A is formed on the front surface of the body and a living body signal is measured on the rear surface A second electrode C for measuring a living body signal is formed on the front surface of the main body (an outer surface when wrist is worn), and a main body is worn on the first electrode B of the user (ECG) of the human body is measured by bringing the other finger into contact with the second electrode (C).

Here, the first electrode B for measuring a living body signal is formed on the rear surface of the main body (the inner surface when the wrist is worn), the second electrode C is formed on the screen A, So that the ECG can be measured.

In this case, the screen A preferably comprises a touch panel.

FIG. 3B is a graph showing the relationship between the photoplethysmogram (PPG) and the oxygen saturation (SpO ₂ ) signals using a photosensor for measuring the amount of light passing through the peripheral blood vessels at the fingertips or toes using a red light source Fig.

The first method is a transmissive type and is connected to the connection terminal E1 of the main body and measures a photoplethysmogram (PPG) and an oxygen saturation (SpO ₂ ) signal using a measuring terminal E 2 fitted to the fingertip .

Here, the measurement terminal E2 is composed of a red LED having a wavelength of 660 nm and an infrared LED having a wavelength of 940 nm, and an optical module having a photodiode and a photo transistor shall.

The second method is a reflection type, which is composed of a 660 nm red LED (D1), a 940 nm infrared LED (D2), a photo diode and a photo transistor (D3).

FIG. 3c is a view showing a screen configuration when measuring a living body signal for blood pressure estimation using the wearable real-time blood pressure estimation monitoring system according to the present invention.

The wearable real-time blood pressure estimation monitoring system according to the present invention can display systolic blood pressure (F1), diastolic blood pressure (F2), and pulse (F3) on the screen.

It is also possible to display a change graph of the ECG signal G1 and the PPG signal G2 and such display content and display style can be changed and displayed by the display mode and the display content selection buttons H1 and H2 .

The wearable real-time blood pressure estimation and monitoring system according to the present invention may include a WiFi or Bluetooth module in the body, and may transmit the measured bio-signal and analysis result data to an external server.

The wearable real-time blood pressure estimation monitoring system according to the present invention can estimate the blood pressure using only the measured ECG signal. The blood pressure can be estimated by measuring the time interval (RR interval) of the apex (R wave) of the ECG signal It is also possible.

In addition, the RR interval of the ECG signal can be used to distinguish the excited state from the stable state. The time series data in the time domain can be divided into a power spectrum of the frequency domain by applying a Fast Fourier Transform (FFT) It can be converted into density (PSD: Power Spectrum Density) to diagnose emotional changes and stress.

The detailed construction of the wearable real-time blood pressure estimation and monitoring system according to the present invention will now be described.

4 is a detailed block diagram of a hardware block of a wearable real-time blood pressure estimation monitoring system.

The hardware block of the wearable real-time blood pressure estimation monitoring system for measuring multiple bio-signals includes a sensor module 20 and a gateway module 30.

Here, the sensor module 20 includes a sensor unit 21 for processing biological signals measured in the body, a digital measurement system 22 for quantizing the analog signals measured by the sensor unit 21 and converting the quantized analog signals into digital signals, And a Bluetooth communication unit 23 for wirelessly transmitting the signal measured by the digital measurement system 22.

The sensor module 20 measures ECG, PPG, and SpO ₂ signals to measure multiple bio-signals, processes them, and transmits them through a Bluetooth wireless communication method.

Since the ECG, PPG, and SpO ₂ signals have different characteristics such as frequency range and amplitude, and gain bandwidth (GB), they must be separately processed. The main characteristics of ECG, PPG and SpO ₂ signals are shown in Table 1.

For ECG statue rejection to attenuate the noise; required (CMRR Common Mode Rejection Ratio) circuit and, SpO ₂ will need a timing circuit that can was irradiated with red light and infrared light sources one by one, and if the ECG differential amplifier (differential amplifier) circuit.

The biometric signals obtained by the sensor module are transmitted to the gateway using Bluetooth. The gateway module receives biometrics signals through Bluetooth communication, and then transmits them to the Internet using TCP / IP communication based on IPv4 or IPv6.

5 is a sensor configuration diagram for measuring an ECG signal.

The ECG signal should be amplified by detecting the potential difference between the signals generated from the electrodes attached to various parts of the human body. To this end, a circuit capable of acquiring an ECG signal is constructed using a differential amplifier.

The ECG signal acquisition circuit according to the present invention has the following features.

First, a notch filter circuit for eliminating 60 Hz noise, which is a power supply noise mixed into the ECG signal, and a common mode rejection circuit for eliminating ripple noise mixed in a ± 15 V DC voltage, CMRR (Common Mode Rejection Ratio) circuit.

The CMRR circuit serves to remove noise mixed into the ECG electrode based on the signal r (t) measured at the right leg corresponding to the reference signal.

ECG signal is applied to the present invention because Lead Ⅱ signal s (t) is a signal obtained from the ECG electrodes attached to the right wrist, g (t) is the ECG signal attached to the left leg, r (t) is the ground electrode Which is obtained from an ECG electrode attached to the right leg.

Second, a circuit is constructed by including a differential amplifier in order to more accurately detect the potential difference between the ECG electrodes. To obtain the ECG signal more accurately, it should have a high CMRR ratio and high input impedance

In the embodiment of the present invention, the differential amplifier circuit is designed to be amplified 10 times, and it is driven at a low power, and the CMRR is 120 dB and the input impedance (10 GΩ and 2 pF in parallel) It is desirable to design it.

Third, in order to configure the ECG signal through the differential amplification circuit and the CMRR circuit to meet the characteristics of the ECG signal mentioned in Table 1, a high-pass filter for passing a signal of 0.1 Hz or higher and a signal of 50 Hz or less are passed Is designed to pass through a low-pass filter.

Fourth, the ECG signal passed through the high-pass filter and the low-pass filter is amplified 100 times and transmitted to the ADC (analog to digital converter).

Therefore, the total amplification ratio of the ECG signal in the ECG sensor module is amplified 10 times in the differential amplifier and then amplified 100 times in the operational amplifier by the series of processes, so that it is amplified 1,000 times in total, and the final GB is configured to be 40 dB do.

And Fig. 6 is a configuration diagram of the PPG sensor module.

The sensor used to measure the PPG signal is a sensor capable of simultaneously measuring PPG and SpO _{2. The} light emitting part includes an infrared LED having a wavelength of 940 nm and a red LED having a wavelength of 660 nm. A photodiode .

The PPG signal can be detected by the photodiode so that only the red light signal is continuously emitted from the TP320 sensor attached to the right finger.

An operational amplifier circuit is constructed so that the PPG signal detected by the TP320 sensor is 10 times as high as the voltage gain. The amplified signal is transmitted to a high-pass filter which passes a signal of 0.1 Hz or more, Pass filter.

The filtered signal is again inverted through the op amp to detect the PPG signal. Since the operational amplifier circuit is designed so that the voltage gain is 50 times through the second operational amplifier, the total voltage gain of the PPG sensor module is amplified 500 times in total, and the final GB is configured to be 25 dB.

Since the direct current component and the ac component coexist in the PPG signal P (t) obtained by the above process, in order to obtain the necessary PPG signal, the DC component should be removed and only the AC component should be extracted. To this end, an AC coupling circuit is formed which can extract only the AC component from the signal P (t) .

And Fig. 7 is a configuration diagram of the SpO ₂ sensor module.

A timing circuit is required to measure the SpO ₂ signal.

In this circuit, red light having a wavelength of 660 nm and infrared light having a wavelength of 940 nm are sequentially emitted one at a time and irradiated to peripheral blood vessels of a human body, and then the amount of light transmitted through the human body is detected by a photodiode.

The SpO ₂ signal passed through the timing circuit is amplified by the first operational amplifier so that the voltage gain is 10 times. The amplified signal is passed through a high-pass filter for passing a signal of 0.1 Hz or higher and a low- Pass filter.

Since the voltage gain is amplified 50 times through the operational amplifier, it is finally amplified to 500 times, and the final GB is configured to be 25 dB.

Generally, the magnitudes of the DC components represented by the red light and the infrared light are similar to each other. However, the ac component, which depends on the oxygen content in the hemoglobin, is different.

In the case of HbO ₂ , the absorptance by red light is low, but the absorptivity by infrared light is relatively high. In healthy people, it is usually between 98% and 99%, which is close to 100%.

And FIG. 8 is a configuration diagram of a software module for monitoring multiple bio-signals.

The software module for monitoring the multiple bio-signals is firstly a PC-based monitoring system 70, the second is a smartphone-based monitoring system 71 operating in a smartphone environment, the third is a web- And a dual stack driver 73 for supporting IPv4 and IPv6 environments at the same time.

9A is a detailed configuration diagram of a PC-based monitoring system.

The PC-based monitoring system consists of a signal monitoring unit for signal monitoring, a signal processing unit for signal processing, and a detection unit for signal analysis and alarm, and the data size transmitted from one channel is 16 bits.

The data size of the ADC is 12 bits, and the remaining 4 bits contain information about each channel. The ECG, PPG, and SpO ₂ signals can be distinguished through the channel information.

The screen output of the ECG, PPG, and SpO ₂ signals is configured to display data for two seconds at a time, and is stored in a text file in real time simultaneously with the screen output.

In the present invention, there are roughly two signal processing processes for analyzing multiple bio-signals.

The first signal processing process is an FFT (Fast Fourier Transform) process.

Generally, most of the biological signals consist of a series of analog signals in a time series in the time domain. When analyzing only the time series data, it is not easy to extract the parameters that can be used for diagnosis. Therefore, time series data in the time domain is converted into a frequency domain to extract more parameters and information that can be used for diagnosis.

In the PC-based software, the FFT technique is applied to optimize the verification and monitoring of the multi-bio signal acquisition system in real time.

A finite impulse response (FIR) is applied to the second signal processing.

FIR is a digital filter that can be implemented in software. It can effectively compensate for the disadvantages of analog filters implemented in hardware, and it can exhibit higher performance than hardware filters.

Therefore, in the PC-based software according to the present invention, the FIR filter is applied to optimize the verification and monitoring of the multi-bio signal acquisition system in real time.

The smartphone-based monitoring system 71 has similar characteristics to the PC-based monitoring system 70, but can be configured by omitting a module for storing multiple biological signals.

This is because the data capacity of the continuously changing bio-signals according to time is large, and therefore it is difficult to store them in a smart phone.

In addition, the real-time FFT function can be excluded, because if the real-time FFT function is included, the system often goes down in the smartphone.

Therefore, it is preferable to configure to perform only the FIR function except the real-time FFT function.

And FIG. 9B is a configuration diagram of a web-based monitoring system.

The web-based monitoring system includes a server platform, a file processing unit, and a real-time analysis unit.

It is desirable to construct a Web server and a database server so that the server environment is suitable for large-scale data analysis.

The web server is built using an event-based distributed web server that supports event-oriented asynchronous API.

The web-based monitoring system is configured to update the screen output of the ECG, PPG, and SpO ₂ signals once a second, and to configure the biometric signal information to be stored in the database server simultaneously with the screen output.

10 is a flowchart showing the operation of the IPv4 / IPv6 dual stack driver.

The IPv4 / IPv6 dual stack driver performs three steps of initialization (S1001), automatic configuration (S1002), and loopback (S1003).

11 is a flowchart showing an initialization process for driving the dual stack driver.

The initialization process of the IPv4 / IPv6 dual stack driver checks whether it belongs to the IPv4 environment or the IPv6 environment (S1101), registers the address (S1102), initializes the SPI (Serial to Peripheral Interface) (S1103) and a reset process (S1104).

Among them, SPI initialization process and H / W reset process are performed by repeatedly calling wizCheckCmdCmplth () function at the end of each socket communication.

This is because the buffer used for SPI communication and the memory used for socket communication are initialized.

12 is a flowchart showing an automatic configuration process.

The wizCheckCmdCmplth () function described above includes an auto-configuration process for IPv6 and IPv4 after H / W reset.

First, if the IPv6 address is not assigned after searching for whether it belongs to the IPv4 environment or the IPv6 environment, it is basically operated in the IPv4 environment (S1201)

Next, if it is in the IPv6 environment, it is determined whether the IPv6 address is manually assigned or whether an IPv6 address is automatically assigned (S1202)

If it is a manual IPv6 address, it immediately reflects this and enters the Main function (S1203)

However, if the IPv6 address is not manually assigned, a Link-local address is assigned (S1204)

The link-local address combines the lower 64 bits of the link-local prefix of the upper 64 bits and the lower 64 bits containing the interface ID, and performs the Duplicate Address Detection (DAD) after allocating the address.

The first process for performing the DAD is to transmit a NS (Neighbor Solicitation) packet (S1205)

When receiving an NA (Neighbor Advertisement) packet (S1206), it means that there is an address using the same address in the vicinity, so a new address is generated again and the same process is repeated.

If there is no NA packet reception within 100 ms, a Router Solicitation (RS) packet is transmitted (S1207) and a RA (Router Advertisement) packet is received (S1208)

The meaning of receiving the RA packet is the process of receiving the upper 64 bits of the prefix address for external connection of the global IPv6 address.

In this process, a global IPv6 address that is capable of external communication is allocated to the full IPv6 address by reallocating the upper 64 bit address from the router.

At this time, if RA packet is not received, it is operated only by the link local address which can communicate internally. After the global IPv6 address is allocated (S1209), the DAD process is performed again within 100 ms.

If the NA packet is not received (S1211) after transmitting the NS packet (S1210), it is determined that there is no node using the same address in the vicinity and the main function is entered.

When all of the above procedures are completed, it is confirmed that all the IPv4 or IPv6 addresses are allocated by a ping reply through a ping test.

Finally, you can confirm that the configuration is completed by using the command execution confirmation function.

13 is a flowchart showing an operation procedure of the UDP mode for loopback.

The IPv4 / IPv6 module used in the gateway requires additional settings for smooth socket communication.

A typical setting is a process of automatically setting whether the IPv4 / IPv6 module operates in a server mode or a client mode.

The IPv4 / IPv6 module should choose whether to be a server or a client for socket communication.

Choosing it is a very important step because it depends on the mode selected. Therefore, three types of loopback modes are configured in the Main function.

The Loopback performs an infinite repetition to determine which mode to operate and determines the mode of operation appropriate to the state of the packet being received or transmitted.

Loopback mode is divided into three modes: UDP loopback mode, TCP server loopback mode, and TCP client loopback mode.

First, after opening the UDP socket, it is determined whether to operate in the reception mode or the transmission mode (S1301)

At this time, you can check the status of UDP by using wizGetSocketStatus () function.

The receiving mode and the sending mode should always check internally that the socket state is UDP_OPENED.

Next, in the reception mode, the size of the received data is returned (S1302) and it is confirmed whether it is larger than 0. (S1303)

At this time, if the data size is larger than 0, the corresponding data is read (S1304)

Finally, in the transmission mode, the IP address and port of the destination are read from the IPv4 / IPv6 module used in the gateway (S1305), and the IP address and port of the destination are stored in the register of the dual stack driver (S1306)

Then, it is checked whether the socket state is UDP_OPENED internally as in the reception mode and the buffer size is checked (S1307), and the data to be transmitted is transmitted to the destination using the UDP_Send () function (S1308)

14 is a flowchart showing an operation procedure of the TCP server mode for loopback.

After performing UDP mode, the operation mode to be examined next is a case of operating in TCP Server mode and TCP Client mode when it is based on TCP communication.

In case of TCP server mode, unlike UDP mode, ACK must be transmitted in TCP server mode.

The operation procedure of the TCP Server mode is shown in FIG.

First, after the TCP socket is opened, the connection of the client is waited for (S1401)

At this time, the state of the TCP socket is changed to the Listen state (S1402)

The value of the Listen state can be checked by checking the value of TCP_LISTEN (0x01) by using wizGetSocketStatus () function.

Next, after the TCP state is normally set to the Listen state, the TCP client maintains a state of waiting for the SYN packet transmitted (S1404)

If the IPv4 / IPv6 module used in the gateway receives the SYN from the TCP client normally in the TCP listen state, it automatically sends the SYN-ACK to the client and waits for reception of the ACK from the client (S1403)

When the three-way handshaking is completed in this manner, the state of the TCP is updated from LISTEN to TCP_ESTABLISHED (S1405)

At this time, the IS_CONNECTED () function can be used to check whether the current state is TCP_ESTABLISHED.

Finally, after confirming internally that the socket state is TCP_ESTABLISHED, it is checked whether the received data size is larger than 0. (S1406) If the received data size is larger than 0, the IPv4 / IPv6 module used in the gateway reads data from the MCU. S1407)

Then, the data read from the IPv4 / IPv6 module used in the gateway is transmitted to the destination using the wizTCPSend () function (S1408), and then the TCP state is returned to the listen state again.

15 is a flowchart showing an operation procedure of the TCP client mode for loopback.

The last mode of operation after UDP mode is TCP communication based TCP Client mode.

In the operation of the TCP client mode, as shown in FIG. 15, after opening a TCP socket, a SYN packet is transmitted to connect to a server (S1501)

At this time, the SYN packet is transmitted only a maximum of 3 times, and if there is no response (SYN-ACK) from the server within 3 times, the TCP state is changed to Closed due to time-out (S1507)

Next, if a response to the SYN packet is received (S1502), an ACK is internally transmitted to the server (S1503) and the TCP state is changed to TCP_ESTABLISHED (S1504)

Finally, when the three-way handshaking is complete, the status is automatically updated to TCP_ESTABLISHED. Internally, it is confirmed that the socket state is TCP_ESTABLISHED, and it is confirmed whether the size of the received data is larger than 0. (S1505)

If the size of the received data is larger than 0, the data is read from the IPv4 / IPv6 module used in the gateway and is transmitted to the MCU (S1506)

And FIG. 16 is a flowchart for real time PTT calculation according to the present invention.

First, wait for 3 seconds to set the threshold used for peak analysis from the ECG and PPG signals. After 3 seconds have elapsed, the moving window size is set to 200 to divide the ECG data into 200 units (S1601)

The divided data is calculated by a peak analysis algorithm (S1602)

Generally, the duration of the QRS group for ECG signals is 0.08 to 0.12 seconds. Therefore, in the case of the R wave representing the peak value in the ECG data, the QRS group always exists in the interval in which the QRS group continues.

Since the ADC sampling frequency is 512Hz, about 51 sampling data corresponds to 0.1 second.

Therefore, after setting the starting point to the Max value, the next 50 sample data are compared and the largest value is converted to the peak point.

However, when there is no R wave among 50 sampling periods, the average value of the ECG data for the first 3 seconds is set as a threshold value, and only when the start point is larger than this value, it operates like a pseudo code .

Positive peak points are extracted by this operation, and negative peak points are also extracted by applying the same method.

Second, the first peak value is extracted, and then the next peak value is successively extracted by applying the same method (S1603), and the extracted time information ( t1 , t2 ) is stored (S1604)

The time difference ( t2 - t1 ) between the two peak points was calculated from the stored time information. The calculated time difference is the RR interval information of the ECG signal.

The number of sampling data corresponding to the R-R interval of the ECG calculated in the third and the second steps is obtained and reflected in the moving window size of the PPG signal (S1605).

PTT is the time difference from the Peak of the PPG measured in the peripheral blood vessels after the R peak of the ECG waveform. Therefore, there is a peak of one PPG signal between R peak of the first ECG signal and R peak of the second ECG signal.

Fourth, the negative peak and the positive peak point of the PPG data existing between the RR intervals of the ECG data are extracted as time information ( TN ) and ( TP ) using peak analysis, respectively (S1606)

And extracts the time information T1 by converting the average value of these two points.

Fifth, the first PTT time information ( t1 ), which is the time information of the peak point of the first ECG and the time information T1 = ( TN + TP ) / 2 of the midpoint between the points S and P of the PPG signal, = ( T1 - t1 ) (S1607)

Sixth, the above sequence of steps is continuously performed up to the last point of the ECG signal to be measured to calculate the PTT (S1608)

And FIG. 17 is a flowchart for real-time systolic blood pressure estimation according to the present invention.

In the present invention, an algorithm that can estimate the systolic blood pressure in real time using the ECG and SpO ₂ signals acquired from the sensor module and the PTT calculated by the PTT calculation algorithm is proposed.

As shown in FIG. 17, the real-time systolic blood pressure estimation algorithm according to the present invention first waits for 3 seconds to set a threshold value as in the peak analysis and then samples the data sampled at 512 samples per second using a sampling frequency of 128 Hz again Thereby reducing the size of the data to 1/4 (S1701)

Second, the data can be reduced to 128 pieces IRAC operation, IRDC, REDAC, REDDC After storing the data for one second, the average value is calculated at intervals of one second (S1702)

The third calculating IRAC, IRDC, REDAC, REDDC The average value of the data is applied to Equation 1 to calculate the real-time SpO ₂ value once per second (S1703)

The components of the signal obtained from the SpO ₂ optical module are divided into an AC component and a DC component.

Here, the AC component represents the amount of light absorbed by blood passing through peripheral blood vessels. And the DC component represents the amount of light absorbed by tissues such as capillaries, muscles, epidermis, and bones.

In the case of SpO2, which means blood oxygen saturation, 98 ~ 99% is a healthy general population.

That is, when there is almost no difference in the amount of change between the AC component and the DC component due to the red light source and the infrared light source, a value close to 100% appears. However, when the ratio of HbO ₂ to Hb in the blood is different, the change of SpO ₂ is apparent.

In general, when SpO ₂ is less than 95%, cognitive ability decreases. In addition, the oxygen supplied to the brain or organ is insufficient, and attention and concentration are reduced, and fatigue easily feels. Less than 90% indicates respiratory distress, and hypoxia significantly reduces memory or cognitive ability.

Fourth, the SpO ₂ value calculated in the previous step, the extracted PTT value, and the ECG data measured in real time are stored in the respective registers as an array (S1704)

Fifth, the above process is repeatedly performed for 53 seconds, and after storing the result value, the SpO ₂ value SpO ₂ [ k53 ], the ninth stored PTT value PTT [ j9 ], the first stored ECG value ECG [ i1 ] is extracted (S1705)

Sixth, the real-time systolic blood pressure SYS BP is calculated by applying SpO ₂ [ k53 ], PTT [ j9 ], and ECG [ i1 ] information to the systolic blood pressure estimation model (S1706)

The calculated real-time systolic blood pressure SYS BP is stored again as the blood pressure information SYS BP [ x1 ] (S1707) and notified to the user when it is 20 mmHg or more than the reference blood pressure (Reference SYS BP) of the user (S1708)

Eighth, the above-described series of processes are continuously performed until the final ECG is introduced to estimate the real-time systolic blood pressure (S1709)

And FIG. 18 is a flowchart for real-time diastolic blood pressure estimation according to the present invention.

As shown in FIG. 18, the real-time diastolic blood pressure estimation algorithm estimates the diastolic blood pressure using only the PTT and SpO ₂ signals without the ECG signal.

First, wait for 3 seconds to set a threshold value like the real-time systolic blood pressure estimation algorithm, and then reduce the size of the data to 1/4 by using the sampling frequency of 128 Hz again with the data sampled with 512 data per second (S1801)

Second, the data can be reduced to 128 pieces IRAC operation, IRDC, REDAC, REDDC After storing the data for 1 second, the average value is calculated at intervals of 1 second (S1802)

The third calculating IRAC, IRDC, REDAC, REDDC At the average value of the data to equation (1) is a real-time operation once the SpO ₂ value in one second. (S1803)

Fourth, the SpO ₂ value calculated in the previous step and the extracted PTT value are stored in the respective registers as an array (S1804)

Fifth, the above process is repeatedly performed for 31 seconds, the result value is stored, and the 31st stored SpO ₂ value (SpO ₂ [ k 31 ]) and the first stored PTT value PTT [ j1 ] are extracted (S1805 )

Rj (t) and Rk (t) are calculated using the interval average expression for the SpO ₂ [ k 31 -40 ] and PTT [ j 1 -10 ]

Seventh, a real diastolic blood pressure (DIA BP) is calculated by applying a diastolic blood pressure estimation model to Rj (t) and Rk (t) information (S1807)

The calculated real-time diastolic blood pressure (DIA BP) is stored again as blood pressure information DIA BP [ y1 ] (S1808) and notified to the user when the blood pressure is less than 20 mmHg below the reference blood pressure (DIA BP)

Ninth, the above-described series of steps is continuously performed until the last ECG is introduced to estimate the real-time diastolic blood pressure (S1810)

Such wearable real-time blood pressure estimation monitoring system and method according to the invention the measuring electrode being provided in the body front and rear surfaces of the wearing type, the body's electrocardiogram (ECG) and the photoelectric volume pulse wave (PPG), oxygen saturation (SpO ₂₎ signal A gate module for transmitting biometrics signal data wirelessly transmitted from the sensor module and transmitting the data to the Internet using IPv4 or IPv6 based TCP / IP communication is embedded in a wearable body will be.

In addition, such a wearable real-time blood pressure estimation monitoring system and method according to the invention the measuring electrode being provided in the body front and rear surfaces of the wearing type, the body's electrocardiogram (ECG) and the photoelectric volume pulse wave (PPG), oxygen saturation (SpO ₂ A signal analysis processor for signal analysis, and a monitoring system for screen output and alarm are incorporated in the body of the wearable type.

In addition, the power supply is stably maintained, and the measured bio-signals can be transmitted or received using the wireless communication. The measured data can be transmitted to the Internet environment So that it can be portable in a ubiquitous health and mobile healthcare environment and is convenient to use.

In addition to supporting IPv4-based TCP / IP communication, it also provides a WBAN-based platform that can operate without restrictions in IPv6 environment. Through this, hypertensive patients can monitor their blood pressure continuously And normal people are able to prevent daily hypertension.

As described above, it will be understood that the present invention is implemented in a modified form without departing from the essential characteristics of the present invention.

It is therefore to be understood that the specified embodiments are to be considered in an illustrative rather than a restrictive sense and that the scope of the invention is indicated by the appended claims rather than by the foregoing description and that all such differences falling within the scope of equivalents thereof are intended to be embraced therein It should be interpreted.

20. Sensor module 30. Gateway module
40. Monitoring system 50. Dual stack driver

Claims (18)

A system for monitoring blood pressure in real time,
main body,
A first electrode disposed on one side of the main body and contacting the human body when the main body is worn on the human body, and a second electrode disposed on a side different from the one side of the main body,
A light emitting unit connected to the sensor module and having at least one light emitting diode (LED) for generating light to be illuminated to the human body, and a photodiode PD for detecting light reflected from the human body or transmitted through the human body A measurement module including a light receiving portion having a light receiving portion,
A monitoring module for displaying information on at least one of the measured signal and the analyzed result of the measured signal,
/ RTI >
(ECG) of the human body in contact with the first electrode and the second electrode, measures a signal relating to the photoelectric pulse wave (PPG) of the human body reflected or transmitted by the sensed light , Calculates an oxygen saturation (SpO2) value based on the measured signal relating to the opto-electronic pulse wave,
Wherein the second electrode is disposed on a display screen of the monitoring module. The method according to claim 1,
Wherein at least one of the sensor module and the measurement module comprises at least one connection terminal connectable to at least one external measurement module. The method according to claim 1,
A gateway module for transmitting information on a signal measured by at least one of the sensor module and the measurement module to the outside using TCP / IP communication based on IPv4 or IPv6;
≪ / RTI > The method according to claim 1,
A processor module for analyzing the measured signal and estimating blood pressure in real time;
≪ / RTI > The method according to claim 1,
Dual Stack Driver that supports both IPv4 and IPv6 and performs initialization, automatic configuration, and loopback operations.
≪ / RTI > The method according to claim 1,
The sensor module includes:
A sensor unit for measuring the signal,
A conversion unit for converting the analog signal measured by the sensor unit into a digital signal,
A communication unit for transmitting the signal converted by the conversion unit to an external system,
/ RTI > A method for monitoring blood pressure in real time,
An electrocardiogram (ECG) measured by a sensor module including a first electrode disposed on one surface of the main body and contacting the human body when the main body is worn on the human body, and a second electrode disposed on the other surface of the main body, Extracting a first peak point and a second peak point successive from the signal relating to the first peak point,
Calculating a time interval (RR Interval) between a time point (t1) at which the first peak point appears and a point (t2) at which the second peak point appears,
A light emitting unit having at least one light emitting diode (LED) for generating light to be illuminated to the human body, and a light receiving unit having a photodiode (PD) which is generated from the light emitting unit and is reflected from the human body or senses light transmitted through the human body Extracting a positive peak point and a negative peak point appearing in the calculated time interval (RR Interval) among the signals relating to the photoelectric pulse wave (PPG) measured by the measurement module,
(T1 = (TN + TP) / 2) between a time point (TP) at which the positive peak point appears and a point at which the negative peak point appears (TN)
Determining a time interval (T1-t1) between a time point (t1) at which the first peak point appears and the time point (T1) at which the first peak point appears as a pulse transit time (PTT)
≪ / RTI > 8. The method of claim 7,
Periodically calculating an oxygen saturation value (SpO2) at a predetermined time interval with reference to a photoelectrically-induced pulse wave signal measured by the measurement module, and
Calculating systolic blood pressure (SYS BP) in real time by applying the systolic blood pressure estimation model to the periodically calculated oxygen saturation value, the determined pulse wave transmission time value, and the electrocardiogram measured in real time
≪ / RTI > 8. The method of claim 7,
Periodically calculating an oxygen saturation value (SpO2) at a predetermined time interval with reference to a photoelectrically-induced pulse wave signal measured by the measurement module, and
(T) for a predetermined time interval of the oxygen saturation value calculated periodically and an average value Rj (t) for a predetermined time interval of the determined pulse wave transmission time value, To calculate the diastolic blood pressure (DIA BP) in real time
≪ / RTI > 10. A method according to any one of claims 8 and 9,
Wherein the measured signal related to the optoelectronic pulse wave is sampled according to a predetermined sampling frequency so that the data size thereof is reduced. 10. A method according to any one of claims 8 and 9,
The AC component (ACIR) by the infrared light source, the DC component (DCIR) by the infrared light source, the AC component (ACRED) by the red light source, and the DC component (DCRED) by the red light source, Lt; / RTI >
Wherein the oxygen saturation value

≪ / RTI > 10. A method according to any one of claims 8 and 9,
If the difference between the systolic blood pressure calculated in real time and the user systolic blood pressure exceeds a predetermined level or the difference between the diastolic blood pressure calculated in real time and the user standard diastolic blood pressure exceeds a predetermined level, How to. delete delete delete delete delete delete

Images