KR20210117230A - Apparatus for Inference of sleeping status using Patch type Electrode - Google Patents

Abstract

The present invention relates to a method for determining a sleep state using a biosignal measuring device, wherein an objective of the present invention is to provide the method for determining the sleep state using the biosignal measuring device that measures, by the biosignal measuring device, the biometric information in a state stably attached to the skin of the human body, and distinguishes a sleep state of the subject using the measured biometric information. The method for determining the sleep state comprises: a first process; a second process; a third process; a fourth process; and a sixth process.

Description

Apparatus for Inference of sleeping status using Patch type Electrode

The present invention relates to a method for determining a sleep state using a biosignal measuring device, and more particularly, measuring biometric information in a state in which the biosignal measuring device is stably attached to the skin of a human body, and using the measured biometric information to obtain a subject It relates to a sleep state determination method using a biosignal measuring device to determine the sleep state of

In general, sleep is a very important factor that accounts for one-third of human life. If you slept soundly the night before, your quality of life will change the next day, and in the opposite case, your life satisfaction will drop sharply, such as being very lethargic, losing concentration due to drowsiness, and losing vitality in life.

Therefore, there is a method of measuring the electroencephalogram and using the analysis result as the main method for analyzing the quality of sleep, but the method of determining the state and quality of sleep by attaching a large number of electrodes to the head and then sleeping is common, which Various analyzes are possible, but it takes some time to attach the electrode, and even if it is properly attached, the adhesive component used for attachment is damaged when used for a long time, and there is a problem that an error may occur due to poor contact of the sensor electrode.

In addition, technology is being developed to accurately and efficiently measure various biometric information sensed in the human body in order to accurately identify the condition of the subject and provide effective treatment, or to determine whether there is an abnormality in the health of the general public and take appropriate preventive measures. .

ElectrocardioGram (ECG), one of representative biometric information, records the action current generated as the heart muscle contracts and expands due to the beating of the heart. After that, the measured current data is described as a graph.

Specifically, the action potential generated when the heart muscle contracts and relaxes by the beating of the heart causes a current transmitted from the heart to the whole body, and this current generates a potential difference depending on the location of the body. It can be detected and recorded through the surface electrode.

Such an electrocardiogram is used to confirm the presence or absence of abnormalities in the heart, and is used as a basic measurement method for diagnosing cardiac diseases such as angina pectoris, myocardial infarction, and arrhythmia.

In general, the electrode induction method used in clinical practice to measure the electrical abnormality of the heart is to measure the biopotential generated when the electrical stimulation generated in the sinus node of the heart is conducted to the left and right ventricles and left and right atria. Attach and measure.

As a measurement method using electrodes, the extremity electrode induction method and the two-electrode measurement method are mainly used.

The limb electrode induction method uses the fact that the longer the path of the line integral is electromagnetically, the larger the potential can be measured. Then, electrodes are attached to both arms and legs of the body and connected to a cardiac electrical activity measuring device with a cable to connect the electrical activity of the heart. a way to measure In the case of the extremity electrode induction method, the longer the path of the line integral, the greater the potential can be measured.

And the two-electrode measurement method is a method of measuring the electrical activity of the heart by attaching electrodes to the chest area using an elastic band. In the case of the two-electrode measurement method, there is a problem in that it is difficult to wear the elastic band on the chest for a long time due to the feeling of pressure on the chest.

In addition, there is a problem in that the quality of the measured heartbeat signal is deteriorated when the electrode is loosely attached due to a user's mistake during the initial attachment or when the humidity of the electrode is reduced due to long-term use.

Heartbeat signal measuring devices that can solve the problems that occur in the conventional device for measuring a heartbeat signal have been developed.

On the other hand, Korean Patent Publication No. 10-0731676 (registered on June 18, 2007) discloses "an electrode patch for measuring electrical activity of the heart in a mobile environment".

It consists of a circular concentric electrode unit that detects a biopotential signal, a conductive metal, an electrode support unit that supports each electrode and transmits a biopotential signal, and an electrode support unit that receives and amplifies the biopotential signal transmitted through the electrode support unit. A signal processing and transmission unit that transmits to the outside, an adhesive unit that attaches an electrode patch for measuring cardiac electrical activity to the human body, a buffer isolation unit that provides a cushioning function to improve wearing comfort when worn on the human body, and signal processing and transmission It relates to an electrode patch for measuring electrical activity of the heart in a moving environment, which includes a cover that transmits an amplified biopotential signal generated by the unit to the outside.

In the case of this technique, there is an advantage in that the cardiac electrical activity signal can be continuously monitored using a miniaturized wireless electrode patch compared to the conventional extremity electrode induction method. However, by using the wireless electrode patch, there is a problem in that it can be applied only to an electrocardiogram measuring device that can wirelessly receive the biopotential signal generated and amplified by the signal processing and transmission unit.

The present invention has been proposed to improve the problems in the prior art, and the biosignal measuring device measures biometric information while stably attached to the skin of the human body, and uses the measured biometric information to determine the sleep state of the subject. An object of the present invention is to provide a sleep state determination method using a biosignal measuring device to determine

A living body that measures the ECG signal and IMU signal from a part of the body when the subject sleeps, analyzes the measured signal, acquires biometric data, motion and posture data from a biosignal measuring device, and transmits it to a mobile device to determine the sleep state A method for determining sleep state using a signal measuring device, the biosignal measuring device comprising: a first step of acquiring an ECG signal measured through a patch-type electrode unit and an acceleration and angular velocity signal for a movement of a subject measured through an IMU sensor; a second process of calculating RRI (R-R peak interval) from the ECG signal through amplification and filtering, and calculating respiration rate, heart rate, and autonomic nervous system effect analysis result data using the RRI; a third process of determining whether to move during sleep and a sleeping posture by using the acceleration and angular velocity information obtained in the first process; a fourth process of wirelessly transmitting the respiration rate, heart rate, autonomic nervous system effect analysis result, movement status, and sleep posture determination data calculated through the second and third processes to a designated mobile device; and a sixth process in which the mobile device analyzes movement changes, posture data, and heart rate state during sleep using each data received in the fourth process, and determines whether a sleep state is present.

Here, in the second process, the respiratory rate is calculated using the RRI data to perform the first differentiation, and then a 0.1 to 0.5 Hz band filter is applied to stabilize the baseline, and ECG according to accurate intake and expiration. Extract the change in the signal, and calculate the respiration rate by counting the section in which the slope of the respiration signal is converted from negative (-) to positive (+) due to the change in the ECG signal,

In the second process, the heart rate is calculated by counting the number of RRIs per minute by analyzing the RRI data in the time domain. The heart rate variability is extracted and the autonomic nervous system effect analysis data is calculated according to the result, wherein the frequency domain is set to a VLF (Very Low Frequency) region, LF (Low Frequency) region, and HF (High Frequency) region. do.

In addition, the fifth process may include: 21 step of determining the sleep state if there is no change in the movement status and sleep posture determination data received from the mobile device for a set initial set time period; 22 step of determining whether the movement and sleep posture determination data is in a non-sleep state if there is a change during a preset initial set time and the heart rate is less than a set value compared to an average heart rate, and determining a sleep state if it decreases by more than a set value; If it is determined that the sleep state in step 21 or 22, the respiration rate is lower than the set value and is regular, step 23 of determining the state of NREM (Non-Rapid Eye Movement) sleep; When the sleep state is determined in step 21 or 22, if the respiration rate is higher than the set value and irregular, and the VLF ratio of the heart rate variability is greater than the HF ratio by comparing the calculated frequency region, REM (Rapid Eye Movement) sleep 24 step of determining the state; and determining the sleep apnea state when the respiration rate is absent for a predetermined time in step 23.

The sleep state determination method using the biosignal measuring device of the present invention calculates the movement and posture determination data of the subject through the IMU sensor while the biosignal measuring device is stably attached to the skin of the human body, and measures it through the ECG sensor The ECG signal is analyzed to measure the subject's respiration rate, heart rate, and biometric information including the autonomic nervous system effect analysis result data, and has the effect of judging the subject's sleep state using the measured biometric information.

1 is a view showing an embodiment in which a sleep state determination device using a patch-type electrode according to an embodiment of the present invention is attached to the chest of a subject;
2 is a detailed block diagram of an apparatus for determining a sleep state according to an embodiment of the present invention;
3 is a cross-sectional structural view of a sleep state determination device using a patch-type electrode according to an embodiment of the present invention;
Figure 4 is a bottom structural view of the present invention patch part.
5 is a plan view of the patch part of the present invention,
6 is a view for explaining the flexibility of the patch part of the present invention,
7 is an operation flowchart of the ECG signal processing unit in FIG. 2;
8 is a flowchart of an operation process for obtaining biometric information using each measured biosignal in FIG. 2;
9 is a flowchart of a process of determining the sleep state of a subject using biometric information obtained by the apparatus for determining a sleep state according to an embodiment of the present invention.

Hereinafter, specific embodiments of the present invention will be described in detail with reference to the accompanying drawings.

First, referring to FIGS. 1 and 2 , the apparatus for determining sleep state using a patch-type electrode according to an embodiment of the present invention analyzes ECG signals and IMU signals collected from a body part of a subject to analyze biometric data, motion and posture data A bio-signal measuring device 100 for obtaining Consists of a mobile device 131 that determines the sleep state of the examinee using data, motion and posture data, and a server 132 that stores the sleep state data of the examinee transmitted from the mobile device 131 and converts it into a database do.

Referring to FIG. 3 , the biosignal measuring apparatus 100 includes an ECG signal processing unit 101 that obtains biometric data by filtering and analyzing the ECG signal measured from the patch unit 110 , and acceleration and angular velocity of the subject. An IMU sensor 103 that measures The MCU 104 for calculating the respiration rate, heart rate, and autonomic nervous system effect analysis results from the bio data received from 101) and receiving movement status and sleeping posture data from the IMU signal processing unit 103 during sleep; A wireless communication unit 105 that transmits the respiration rate, heart rate, autonomic nervous system effect analysis result, movement status, and posture determination data of the MCU 104 through wireless communication to the mobile device 131, and the biosignal measuring device 100 It is composed of a power supply unit 106 for supplying driving power.

2 to 5, the patch part 110 is a flexible electrode part 111 of a flexible material forming a predetermined shape, the flexible electrode part 111 and the biosignal measuring device 100 is fixed by coupling. It is composed of an adhesive cloth layer 112 that surrounds and protects the outside to maintain the state.

The upper flexible electrode unit 111 includes a support film 111d made of a flexible material, three electrodes 111a to 111c for measuring electrical signals from the subject's skin at the lower end of the support film 111d, and the support film and each electrode connection part 113a to 113c for electrical connection between the respective electrodes and the biosignal measuring device 100 on the upper surface of the .

The electrode connection parts 113a to 113c are in the form of snap buttons, are electrically coupled to the biosignal measuring device 100, and are formed with metal detachable grooves to be detachable.

In addition, the support film 111d is harmless to the human body, preferably formed of a polyimide film made of a flexible material, and is configured to be disposable so that it can be easily replaced when contamination and adhesion are low.

The configuration and operation of the biosignal measuring device using the patch-type electrode configured as described above will be described in detail with reference to the accompanying FIGS. 1 to 7 as follows.

First, the biosignal measuring apparatus 100 according to the present invention is coupled to the patch unit 110 and attached to the lower left chest of the subject. (See Fig. 1)

The lower left chest of the subject not only minimizes the influence on the movement of the subject's hand, but also allows easier measurement by comparing the ECG signal to other regions.

On the other hand, a silicone tape, a biosignal measuring device 100 and an attachment cloth 112 that can cover the support film 111 are used at the bottom for easy attachment to the human body, and the attachment cloth 112 is a flexible span material. It is composed of , which increases the adhesion to body movement, and minimizes the motion noise factor during ECG measurement. (See Fig. 5)

In addition, the support film 111 has a thin structure with a width of 3.5 mm between the electrode parts 111a to 111c so that it can be easily bent even in an irregular shape of the human body.

The electrode parts 111a to 111c may be encapsulated with an electrolyte gel to facilitate ECG signal measurement.

A detailed operation for obtaining a biosignal of the biosignal measuring apparatus 100 will be described with reference to FIGS. 6 and 7 .

First, the biosignal measuring device 100 attached to the body part of the subject using the patch unit 110 starts to measure the ECG signal from the electrode units 111a to 111c, and at the same time, the IMU sensor 102 Measure the motion (acceleration/angular velocity) signal.

The signal measured through the electrode units 111a to 111c is amplified and filtered by the ECG signal processing unit 101 . Signal filtering is ECG data (raw data), RRI (R-R peak interval) is detected through high pass (0.5 Hz) and low pass filtering (40 Hz).

As such, the final RRI data is calculated by estimating the RRI data using interpolation so that the RRI data falls within the average standard (0.4 to 1.3 s).

After performing the first differentiation using the calculated RRI data, a 0.1~0.5Hz band filter is applied to stabilize the baseline to extract changes in the ECG signal according to accurate inspiration and expiration, and the respiratory rate is The respiration rate is calculated by counting the section in which the slope of the respiration signal changes from negative (-) to positive (+). (See Fig. 8)

In addition, the heart rate is calculated by counting the number of RRIs per minute by analyzing the RRI data in a time domain.

The RRI data is extracted through frequency domain analysis of sampling at the same interval on the time axis. At this time, 0.04 Hz or less is set as VLF region, 0,04 to 0.14 Hz is LF region, and 0.15 to 0.4 Hz is set to HF region. do.

On the other hand, the IMU data input through the IMU sensor 102 is input to the IMU signal processing unit 103 to determine whether to turn over and sleep posture during sleep by using the acceleration and angular velocity information.

9 is a flowchart of a sleep state determination process according to an embodiment of the present invention. The respiration rate, heart rate, autonomic nervous system effect analysis result, and movement status and posture determination data calculated through the detailed description of FIGS. 7 and 8 are shown above. It is transmitted wirelessly to the mobile device 131, and the mobile device 131 determines the sleep state of the examinee through the installed sleep state determination application.

That is, when the subject attaches the biosignal measuring device 100 to a part of the body and starts driving, the biosignal measuring device 100 processes the ECG signals collected from the respective electrode units 111a to 111c through a signal processing process. Respiratory rate, heart rate, autonomic nervous system effect analysis result data is calculated, and it is transmitted to the mobile device 131 .

At the same time, the acceleration/angular velocity data measured from the IMU sensor 102 is transmitted to the mobile device 131 by calculating the movement and posture data of the subject through the IMU signal processing unit and the MCU 104 .

The mobile device 131 checks the movement data (changes in 3-axis acceleration data) and posture data for the transmitted initially set time (about 15 minutes), and if there is no movement change in the lying state, it returns to the sleeping state. It is determined, and even if there is a change in movement, the transmitted heart rate state is checked.

At this time, if the mobile device 130 is determined to be in a non-sleep state even after a set initial setting time (about 15 minutes), it plays the set music to help sleep, and when it is determined that the transition from the non-sleep state to the sleep state is performed, playback Decrease the volume of the music being played at a certain rate and then end it.

After the above sleep state, the respiration rate is continuously checked, and if the respiration rate is low and regular, it is judged as NREM (Non-Rapid Eye Movement) sleep state. (Rapid Eye Movement) It is judged by the state of sleep.

If the respiration rate is not detected for more than a set time (10 seconds), it is determined as sleep apnea, and if the transmitted apnea signal is repeated 5 times or more, it is determined as an initial sleep apnea and alerts through the mobile device 130 It outputs a sound to induce waking from sleep.

Data is collected by repeatedly performing sleep state determination until it changes from a sleep state to a non-sleep state.

In addition, when changing from a sleep state to a non-sleep state, data is transmitted to the server 132 that manages the sleep state of the examinee and converted into a database.

In addition, by using the acceleration and angular velocity data using the IMU data, it is determined whether the sleeping posture and tossing and turning, etc. are used, and this is used as an index for evaluating the sleep state together with the ECG data.

And, although specific embodiments of the present invention have been described and illustrated above, it is obvious that the sleep state determination method using the biosignal measuring device of the present invention can be variously modified and implemented by those skilled in the art.

However, such modified embodiments should not be individually understood from the spirit or scope of the present invention, and such modified embodiments should be included within the appended claims of the present invention.

100: bio-signal measuring device 101: ECG signal processing unit
102: IMU sensor 103: IMU signal processing unit
104: MCU 105: wireless communication unit
106: power unit 110: patch unit
111: flexible electrode part 111a~111c: electrode part
111d: support film 113a~113c: electrode connection part
131: mobile device 132: server

Claims (6)

A living body that measures the ECG signal and IMU signal from a part of the body when the subject sleeps, analyzes the measured signal, acquires biometric data, motion and posture data from the biosignal measuring device, and transmits it to a mobile device to determine the sleep state In the sleep state determination method using a signal measuring device,
The biosignal measuring apparatus includes: a first process of obtaining an ECG signal measured through the patch-type electrode unit and an acceleration and angular velocity signal for the movement of the subject measured through an IMU sensor;
a second process of calculating RR peak interval (RRI) from the ECG signal through amplification and filtering, and calculating respiration rate, heart rate, and autonomic nervous system effect analysis result data using the RRI;
a third process of determining whether to move during sleep and a sleeping posture by using the acceleration and angular velocity information obtained in the first process;
a fourth process of wirelessly transmitting the respiration rate, heart rate, autonomic nervous system effect analysis result, movement status, and sleep posture determination data calculated through the second and third processes to a designated mobile device; and
and a sixth process of the mobile device analyzing movement changes, posture data, and heart rate state during sleep using each data received in the fourth process, and determining whether the mobile device is in a sleep state; A method for determining sleep state using a device. According to claim 1,
RRI data calculation in the second process includes: 11 steps of detecting RRI (RR peak interval) through high-pass and low-pass filtering of raw data of the ECG signal; and
and 12 steps of calculating the final RRI data by estimating the RRI data using interpolation so that the RRI falls within the average standard. 3. The method of claim 2,
In the second process, the respiration rate is calculated using the RRI data to perform the first differentiation, and then a 0.1 to 0.5 Hz band filter is applied to stabilize the baseline. extract change,
A sleep state determination method using a biosignal measuring device, characterized in that the respiration rate is calculated by counting the section in which the slope of the respiration signal is converted from negative (-) to positive (+) due to the change in the ECG signal. According to claim 1,
In the second process, the heart rate is calculated by analyzing the RRI data in a time domain and counting the number of RRIs per minute,
The autonomic nervous system effect analysis data extracts the heart rate variability through frequency domain analysis of sampling the RRI data at the same interval on the time axis, and calculates the autonomic nervous system effect analysis data according to the result,
The sleep state determination method using a biosignal measuring device, characterized in that the frequency domain is set to a very low frequency (VLF) area, a low frequency (LF) area, and a high frequency (HF) area. 5. The method of claim 4,
The fifth process is a 21 step of determining the sleep state if there is no change in the movement status and sleep posture determination data received from the mobile device for a set initial set time period;
22 step of determining whether the movement and sleep posture determination data is in a non-sleep state if there is a change during a preset initial set time and the heart rate is less than a set value compared to an average heart rate, and determining a sleep state if it decreases by more than a set value;
If it is determined that the sleep state in step 21 or 22, the respiration rate is lower than a set value and is regular, step 23 of determining a non-rapid eye movement (NREM) sleep state;
When the sleep state is determined in step 21 or 22, if the respiration rate is higher than the set value and irregular, and the VLF ratio of the heart rate variability is greater than the HF ratio by comparing the calculated frequency region, REM (Rapid Eye Movement) sleep 24 step of determining the state; and
In step 23, when the respiration rate is absent for a certain period of time, determining the sleep apnea state. 6. The method of claim 5,
When it is determined in step 21 or 22 that the non-sleep state is determined for the initial set time, the set music to help sleep is played, and when the non-sleep state is converted to the sleep state, the volume of the music being played is reduced at a constant rate A sleep state determination method using a biosignal measuring device, characterized in that it further comprises the step of terminating the sleep state.

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