KR20180075832A - Method and Apparatus for Monitoring Sleep State - Google Patents

Abstract

Provided is a method for monitoring a sleep state, which determines a sleep state of a user by using biological signals. The method uses a contactless measuring device near the user without attaching the measuring device to a body of the user to enhance convenience. The method for monitoring the sleep state performed by an apparatus for monitoring the sleep state comprises the steps of: obtaining original biological signals including a first biological signal indicating a heartbeat state of the user, and a second biological signal indicating a breathing state of the user; extracting the first biological signal and the second biological signal from the original biological signals by using a frequency of each biological signal; determining at least one reference biological signal used in determining the sleep state of the user between the first biological signal and the second biological signal; measuring a signal cycle shown in the reference biological signal; and determining the sleep state of the user by using the signal cycle.

Description

TECHNICAL FIELD [0001] The present invention relates to a sleep state monitoring method and apparatus,

The present invention relates to a sleep state monitoring method and apparatus. More particularly, the present invention relates to a sleep state monitoring method and apparatus for determining a sleep state of a user by using a living body signal and detecting a sleeping breathing disorder occurring during sleeping.

During sleep, all the organs of the brain and the body enter the resting state and improve the quality of life by decomposing various fatigue substances accumulated during the daytime. Although the importance of sleep is not so great, many people in the modern world suffer from sleep disturbances such as poor sleep quality or sleep apnea symptoms.

In order to solve the sleep disorder, the task of judging the state of sleep should be preceded. The most objective and accurate method of determining sleep status is polysomnography (PSG). Sleep polyvalence tests measure various physiological signals such as the electroencephalogram (EEG), electromyogram (EMG), electrocardiogram (ECG), oxygen saturation, chest and abdominal motion, respiration, And the sleep state of the user. For example, it is possible to judge from the above-described bio-signals by the sleeping polyvalent test how many steps of sleep apnea, arrhythmia, rapid eye movement, and non-rapid eye movement (Non-REM) .

However, the sleeping polyvalence test is costly to the user because it uses a large number of specialized apparatuses for measuring the above-mentioned bio-signals, and it is troublesome to sleep in the sleeping room of the hospital. In addition, since a plurality of contact type measuring devices must be attached to the user's body, it is inconvenient to the user and it may be difficult to diagnose the usual sleep state.

Accordingly, there is a need for a sleep state monitoring method and apparatus that can more easily determine a sleep state of a user without attaching a physical restraint measuring device to a user in terms of user convenience and cost reduction.

Korea Patent Publication No. 2010-0022706

SUMMARY OF THE INVENTION It is an object of the present invention to provide a sleep state measuring method and apparatus capable of determining a sleep state of a user without attaching a separate measuring device to a user's body.

It is another object of the present invention to provide a sleep state measurement method and apparatus capable of determining whether a sleeping user causes a sleeping breathing disorder.

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

According to another aspect of the present invention, there is provided a sleep state monitoring method performed by a sleep state monitoring apparatus, the sleep state monitoring method comprising: a first biometric signal indicating a heartbeat state of a user; Acquiring an original biometric signal including a second biometric signal indicating a breathing state, extracting the first biometric signal and the second biometric signal from the original biometric signal using the frequency of each biometric signal, Determining at least one reference bio-electrical signal to be used for determining the sleep state of the user from among the one bio-electrical signal and the second bio-electrical signal, measuring a signal period represented by the reference bio-electrical signal, And determining a sleep state of the user.

According to another aspect of the present invention, there is provided a sleep state monitoring method performed by a sleep state monitoring apparatus, the sleep state monitoring apparatus comprising: Acquiring a first biological signal indicative of a breathing state of a sleeping user and a second biological signal indicative of a snoring state of the user, using the change in the first biological signal, Analyzing a correlation between the first bio-signal and the second bio-signal when it is determined that the respiratory disturbance state of the user is maintained for a predetermined period of time; Determining a sleeping breathing disorder symptom of the user using the analysis result; It can hamhal.

According to another aspect of the present invention, there is provided a sleep state monitoring apparatus including at least one processor, a network interface, a memory for loading a computer program executed by the processor, Wherein the computer program comprises: an operation of acquiring an original biometric signal including a first biometric signal indicating a heartbeat state of a user and a second biometric signal indicating a respiration state of the user; An operation of extracting the first living body signal and the second living body signal from the original living body signal using at least one of the first living body signal and the second living body signal, An operation for determining a biological signal, By using the operation period, and the signal for measuring the signal cycle shown in the call may include the operation of determining a sleep state of the user.

According to another aspect of the present invention, there is provided a sleep state monitoring apparatus including at least one processor, a network interface, a memory for loading a computer program executed by the processor, Wherein the computer program further comprises: acquiring a first biological signal indicative of a breathing state of a sleeping user and a second biological signal indicative of a snoring state of the user; Determining whether the respiratory disturbance state of the user is maintained for a preset period of time; determining whether the respiratory disturbance state of the user is maintained for a predetermined period of time; And an operation for analyzing the correlation between the phase It may include an operation for determining a sleep breathing disorder of the user by using the analysis result of the relation.

According to still another aspect of the present invention, there is provided a computer program product for causing a computer to function as: a first biometric signal indicating a heartbeat state of a user; a second biometric signal indicating a breathing state of the user; Extracting the first bio-signal and the second bio-signal from the original bio-signal using the frequency of each bio-signal, extracting the first bio-signal and the second bio- Determining at least one reference bio-electrical signal to be used for determining a sleep state of the user, measuring a signal period represented by the reference bio-electrical signal, and determining a sleep state of the user using the signal period May be stored in the recording medium.

According to another aspect of the present invention, there is provided a computer program for use in a computer system, the computer program causing a computer to function as: a first biometric signal indicating a breathing state of a sleeping user; Determining whether the respiratory disturbance state of the user is maintained for a predetermined period of time using the change of the first bio-signal, determining whether the respiratory disturbance state of the user is maintained for a predetermined period of time Analyzing a correlation between the first bio-signal and the second bio-signal, and determining a symptom of the user's sleep-disordered breathing using the analysis result of the correlation, Lt; / RTI >

According to the present invention, the user's convenience can be improved by judging the user's sleeping state or sleeping breathing trouble by using the non-contact type measuring device installed around the user without attaching the measuring device to the user's body.

In addition, the cost of the user can be minimized by judging the user's sleep state or sleeping breathing trouble using a low-cost measuring device.

Further, there is an effect that the accuracy of sleep state determination is improved by determining a sleep state and a sleep phase of a user by combining a plurality of sleep state determination algorithms.

In addition, by detecting both the snoring and the vital signs indicating the breathing state, the obstructive sleep apnea and the central sleep apnea can be accurately discriminated by detecting the sleep apnea.

Also, by controlling the operation of the PAP (Positive Airway Pressure) (PAP) according to whether the sleeping breathing fault is detected and the user's sleeping phase, a good quality sleep can be provided to the user.

The effects of the present invention are not limited to the effects mentioned above, and other effects not mentioned can be clearly understood to those of ordinary skill in the art from the following description.

1 is a configuration diagram of a sleep state monitoring system according to an embodiment of the present invention.
2 to 3 are functional block diagrams of a sleep state monitoring apparatus according to another embodiment of the present invention.
4 is a hardware block diagram of a sleep state monitoring apparatus according to another embodiment of the present invention.
5 is a flowchart of a sleep state monitoring method according to another embodiment of the present invention.
6A to 6D are diagrams for explaining a step of separating a heartbeat signal and a respiration signal and measuring a signal period.
7 to 8 are diagrams for explaining a method of determining a sleep state using a heartbeat signal, which may be referred to in some embodiments of the present invention.
Figure 9 is a flow diagram of a method for determining a sleep state using a breathing signal, which may be referenced in some embodiments of the present invention.
10 to 11 are diagrams for explaining a method of determining a sleep state using a heartbeat signal and a breathing signal, which may be referred to in some embodiments of the present invention.
12 is a diagram for explaining a method of determining a sleep state using a moving signal, which may be referred to in some embodiments of the present invention.
FIGS. 13 to 14 are diagrams for explaining a sleep breathing disorder determination method according to another embodiment of the present invention.
Figure 15 is a flowchart of a method for controlling the operation of a PAP in accordance with a user's sleep apnea symptoms and breathing conditions, which may be referred to in some embodiments of the present invention.
16A and 16B are exemplary views of a user interface for displaying a user's sleep record.
17 is a configuration diagram of a sleep state monitoring system interlocked with an IoT (Internet of Things) system according to an embodiment of the present invention.

Hereinafter, preferred embodiments of the present invention will be described in detail with reference to the accompanying drawings. BRIEF DESCRIPTION OF THE DRAWINGS The advantages and features of the present invention, and the manner of achieving them, will be apparent from and elucidated with reference to the embodiments described hereinafter in conjunction with the accompanying drawings. The present invention may, however, be embodied in many different forms and should not be construed as being limited to the embodiments set forth herein. Rather, these embodiments are provided so that this disclosure will be thorough and complete, and will fully convey the concept of the invention to those skilled in the art. Is provided to fully convey the scope of the invention to those skilled in the art, and the invention is only defined by the scope of the claims. Like reference numerals refer to like elements throughout the specification.

Unless defined otherwise, all terms (including technical and scientific terms) used herein may be used in a sense that is commonly understood by one of ordinary skill in the art to which this invention belongs. Also, commonly used predefined terms are not ideally or excessively interpreted unless explicitly defined otherwise. The terminology used herein is for the purpose of illustrating embodiments and is not intended to be limiting of the present invention. In the present specification, the singular form includes plural forms unless otherwise specified in the specification.

It is noted that the terms "comprises" and / or "comprising" used in the specification are intended to be inclusive in a manner similar to the components, steps, operations, and / Or additions.

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

1 is a configuration diagram of a sleep state monitoring system 10 according to an embodiment of the present invention.

Referring to FIG. 1, the sleep state monitoring system 10 monitors and manages a user's overall sleep state, such as measuring a user's sleep state using a user's bio-signal, and detecting a sleeping breath disorder.

The sleep state monitoring system 10 may include a living body signal measuring apparatus 100, a sleep state monitoring apparatus 300, and a sleep management server 500. However, it is needless to say that the sleep state monitoring system 10 shown in FIG. 1 is only a preferred embodiment for achieving the object of the present invention, and that some components may be added or deleted as needed.

The bio-signal measuring device 100 is a device for measuring a bio-signal indicating a user's breathing state, snoring sound, and heartbeat state. However, the present invention is not limited thereto, and various kinds of bio-signals required for judging the user's sleeping state can be measured.

The bio-signal measuring apparatus 100 may be, for example, a device that senses the pressure of the blood flow, detects movement of the chest, detects movement of the abdomen, and electrically converts the bio-signal through a change in voltage, have. In addition, the bio-signal measuring apparatus 100 may measure the user's bio-signal using an optical or RF (Radio Frequency) signal. That is, as is well known in the art, an optical or RF signal transmitted from the bio-signal measuring apparatus 100 passes through the skin of the user and is reflected or scattered by the living tissue, The user's bio-signal can be measured

According to an embodiment of the present invention, the bio-signal measuring apparatus 100 may be a sensor for simultaneously measuring a heartbeat state, a breathing state, and a motion state of a user, and the sensor may be a pressure sensor, a vibration sensor, And the like, but are not limited thereto.

According to the embodiment of the present invention, the living body signal measuring apparatus 100 is positioned on a mattress top 100a, a mattress bottom 100b, a bed leg 100c, a pillow bottom 100d, etc., And may be fixed with a clip on the pillow or bed. That is, the bio-signal measuring device is a non-contact type measuring device that is not directly attached to a body part of a user's head, chest, or the like. Therefore, the convenience of the user can be improved as compared with the contact type measuring device.

The living body signal measuring apparatus 100 transmits the measured user's living body signal to the sleep state monitoring apparatus 300 via the network. At this time, the analog signal measured by the bio-signal measuring apparatus 100 is transmitted as it is, and signal processing such as digital signal conversion, filtering, and amplification can be performed in the sleep state monitoring apparatus 300, May be transmitted after the signal processing is performed, which is merely a difference in implementation method.

The network is a concept that includes both wired and wireless networks. The network may be implemented as any kind of wired / wireless network such as a local area network (LAN), a wide area network (WAN), a mobile radio communication network,

The living body signal measuring apparatus 100 and the sleep state monitoring apparatus 300 may be connected to a wireless LAN (WLAN), a Bluetooth, a UWB (Ultra Wide Band), an IrDA Association, IEEE1394, etc.), a wired / wireless communication module, and the like.

Next, the sleep state monitoring apparatus 300 determines the sleep state of the user using the bio-signal of the user obtained from the bio-signal measuring apparatus 100 and detects the sleep disordered breathing (SDB) State monitoring device. Herein, the computing device includes a notebook, a desktop, a laptop, and the like, and may include all kinds of handheld-based devices such as a smart phone and the like. However, the present invention is not limited thereto, and may include all kinds of devices having a computing function and a communication function.

For example, the sleep state monitoring apparatus 300 may include a living body signal (hereinafter, referred to as a "first living body signal") indicating a heartbeat state of a user and a living body signal indicating a user's breathing state (Hereinafter, referred to as a 'third living body signal') indicating the user's sleeping state, or a symptom of a sleeping breathing disorder occurring in a user who is asleep using the second living body signal and a living body signal indicating the user's snoring sound Can be detected. A detailed description of how the sleep state monitoring apparatus 300 determines the sleep state of the user and how to detect a sleeping breath disorder will be described later with reference to Figs. 5 to 15. Fig.

The sleep state monitoring device 300 may include a user interface to provide the user with a sleep recording of the monitored user in a user-friendly manner. The user interface will be briefly described below with reference to the example shown in Fig.

Next, the sleep management server 500 is a computing device for receiving, storing, and analyzing sleep recording data including sleep state of the user and occurrence of sleeping breathing trouble from the sleep state monitoring apparatus 300. The sleep management server 500 may analyze the sleep recording data to calculate a sleep quality improvement method or provide a variety of sleep management services in cooperation with an IoT (Internet of Things) system or the like. An example of providing a sleep management service in cooperation with the IoT system will be described later with reference to FIG.

1, the sleep management server 500 and the sleep state monitoring apparatus 300 are shown as physically independent apparatuses. However, according to the embodiment, the sleep management server and the sleep state monitoring apparatus are different from each other May be implemented in the form of logic.

In addition, the functions of the bio-signal measuring apparatus 100 and the sleep state monitoring apparatus 300 may be implemented in various manners. For example, both the function of measuring the user's bio-signal and the function of monitoring the sleep state are all performed in the first apparatus, the second apparatus receives the user's sleep state information from the first apparatus, Or the like.

The sleep state monitoring system 10 according to an embodiment of the present invention has been described with reference to FIG. Next, the operation and configuration of the sleep state monitoring apparatus 300 according to another embodiment of the present invention will be described with reference to FIGS. 2 to 4. FIG.

FIGS. 2 to 3 are functional block diagrams of the sleep state monitoring apparatus 300. FIG.

Referring to FIG. 2, the sleep state monitoring apparatus 300 may include a sensor unit 310, a communication unit 330, an output unit 350, and a controller 390. However, only the components related to the embodiment of the present invention are shown in Fig. Accordingly, it will be appreciated by those skilled in the art that other general-purpose components may be included in addition to those shown in FIG.

Referring to each component, the sensor unit 310 measures a user's biomedical signal. For example, the sensor unit 310 may include a built-in microphone for measuring a snoring sound of a sleeping user. That is, the sleeping state monitoring apparatus 300 can further measure the living body signal through the sensor unit 310 in addition to the living body signal of the user obtained from the living body signal measuring apparatus 100. However, the sensor unit may be omitted depending on the implementation of the sleep state monitoring apparatus 300. [

The input unit 330 receives various input signals including a selection input of the user using the sleep state monitoring apparatus 300. For example, the input unit 330 may include, but is not limited to, a touch screen, a keyboard, and a mouse.

The communication unit 350 may include a wired Internet module, a mobile communication module, or a wireless communication module for transmitting and receiving a user's biometric signal from the living body signal measuring device 100.

The output unit 370 displays the sleep record including the sleep state of the user through the user interface or outputs an alarm sound for waking up the sleeping user. The output unit may include, for example, a monitor, a screen, and a speaker, but is not limited thereto.

The controller 390 controls the overall operation of each configuration of the sleep state monitoring apparatus 300. The control unit 390 may be configured to include a CPU (Central Processing Unit), an MPU (Micro Processor Unit), an MCU (Micro Controller Unit), or any type of processor well known in the art. In addition, the controller 390 may perform operations on at least one application or program for executing a method according to embodiments of the present invention to be described later.

Next, detailed functional blocks included in the controller 390 will be described with reference to FIGS. 3A to 3B. FIG.

Referring to FIG. 3A, the controller 390 may include a sleep state determination unit 391 and a sleeping breathing fault detection unit 393. However, only the components related to the embodiment of the present invention are shown in Fig. Accordingly, those skilled in the art will recognize that other general-purpose components may be included in addition to those shown in FIG. 3A.

The sleep state determination unit 391 determines the sleep state of the user. More specifically, the sleep state determination unit 391 determines whether or not the user is awake, the sleeping phase of the user, and the like. Herein, the sleeping step may mean four stages of sleeping steps which are well known in the art. That is, the sleeping step may mean a Rapid Eye Movement (REM) sleeping phase and a non-REM sleeping phase, and the Nemem sleeping phase may be subdivided into three sleeping phases, 2 sleep stages may refer to shallow sleep stages and 3 sleep stages may refer to deep sleep stages.

3B, the sleep state determination unit includes a living body signal extraction unit 391a, a heartbeat measurement unit 391b, a breath measurement unit 391c, and a sleep state determination unit 391b. 391d.

When a signal including a plurality of biological signals such as a first biological signal and a second biological signal is received, the biological signal extracting unit 391a extracts the first biological signal and the second biological signal based on the frequency, 2 Biological signals are separated and extracted. A method of separating the first and second bio-signals from the bio-signal extracting unit will be further described with reference to an example shown in Figs. 6A to 6B.

The heartbeat measurement unit 391b measures the bioindex such as a heart rate, a heartbeat period, a change in a heartbeat period, and a deviation in a heartbeat period using the first living body signal. For example, the heartbeat measuring unit may detect a peak or a valley of a first biological signal for a predetermined time, determine the number of the peak or valleys as a heart rate, and determine a peak or a peak or a peak or valley between the valley and the valley The time interval is determined as a heartbeat period, and the deviation of the heartbeat period indicating the degree of change of the heartbeat period can be measured. A method for measuring the heartbeat period of the heartbeat measuring unit will be further described with reference to an example shown in FIG. 6C.

The respiration measuring unit 391c measures the bioindex such as the respiration rate, the respiratory cycle, the change of the respiratory cycle, and the deviation of the respiratory cycle using the second bio-signal. For example, the respiration measuring unit may detect peaks and valleys of the second bio-signal for a preset time, determine the number of peaks or valleys as the number of breaths, and determine the time interval between peaks and peaks or between the valley and the valley as a breathing cycle And the deviation of the respiratory cycle indicating the degree of change of the respiratory cycle can be measured. The method of measuring the breathing cycle of the respiration measuring unit will be described later with reference to the example shown in FIG. 6D.

Meanwhile, although not shown in FIG. 3B, according to the embodiment, the sleep state determination unit 391 may further include a motion measurement unit (not shown). The motion measuring unit may measure a user's motion from a motion signal indicating a motion state of the user (hereinafter referred to as a 'fourth living body signal'). The fourth bio-signal can be extracted from the bio-signal extracting unit 391a, and a method of measuring the movement of the user by the motion measuring unit will be described later with reference to FIG.

The sleeping state determination unit 391d determines the sleep state of the user by using at least one biometric index among the biometric index related to the heartbeat measured by the heartbeat measuring unit 391b and the breath index measured by the breath measuring unit 391c . Alternatively, the sleep state determiner 391d may determine the sleep state of the user by considering the biological index related to the movement of the user measured by the motion measuring unit (not shown). Details of how the sleep state determining unit determines the sleep state of the user will be described later with reference to FIGS. 7 to 12. FIG.

Referring again to FIG. 3A, the sleeping breathing detection unit 393 detects a sleeping breathing disorder symptom that may appear to a sleeping user. More specifically, the sleeping breathing fault detecting unit 393 detects the obstructive sleep apnea (OSA) using the correlation between the second living body signal indicating the breathing state and the third living body signal indicating the snoring state. And Central Sleep Apnea ('CSA'). In addition, the sleeping breathing fault detecting unit 393 can accurately detect the OSA and the CSA by using the second and third bio-signals. Here, it should be noted that the OSA and the CSA include not only sleep apnea but also respiratory disturbance due to sleep hypoventilation. A detailed description of how the sleeping breathing fault detecting unit detects a sleeping breathing disorder will be described later with reference to FIG. 13 to FIG.

Meanwhile, when the sleep state monitoring apparatus 300 is implemented as a PAP or when the sleep state monitoring apparatus and the PAP are interlocked, the sleep state monitoring apparatus may further include a PAP controller (not shown).

The PAP control unit sends a control signal for operating the PAP when a sleeping breath disorder is detected. In addition, a control signal for controlling the pressure of the PAP is sent according to the sleeping phase or the breathing state of the user. That is, the PAP controller controls the PAP according to the occurrence of the sleeping breathing disorder and the breathing state of the user, thereby helping the user to sleep and improving the therapeutic effect of the sleeping disorder. A detailed description of the operation algorithm of the PAP control unit will be described later with reference to FIG.

In addition, when the sleep state monitoring system 10 is interlocked with the IoT system 700, the sleep state monitoring apparatus 300 controls the IoT devices included in the IoT system on the basis of the user's sleep state, And an event processing unit (not shown) for performing an event. The event processor may control the IoT devices according to the sleep state and the sleep phase condition of the predetermined user to provide various sleep management services to the user. Various embodiments of the sleep management service will be described later with reference to FIG.

Each of the components shown in FIGS. 2 to 3 described above may mean software or hardware such as an FPGA (Field Programmable Gate Array) or an ASIC (Application-Specific Integrated Circuit). However, the components are not limited to software or hardware, and may be configured to be addressable storage media, and configured to execute one or more processors. The functions provided in the components may be implemented by a more detailed component, or may be implemented by a single component that performs a specific function by combining a plurality of components.

Next, a hardware configuration diagram of the sleep state monitoring apparatus 300 according to another embodiment of the present invention will be described with reference to FIG.

4, the sleep state monitoring apparatus 300 includes one or more processors 301, a bus 305, a network interface 307, a memory 301 for loading a computer program executed by the processor 301 303 and a storage 309 for storing sleep state monitoring software 309a. 4, only the components related to the embodiment of the present invention are shown. Accordingly, those skilled in the art will recognize that other general-purpose components may be included in addition to those shown in FIG.

The processor 301 controls the overall operation of each configuration of the sleep state monitoring apparatus 300. The processor 301 may be configured to include a Central Processing Unit (CPU), a Micro Processor Unit (MPU), a Micro Controller Unit (MCU), or any type of processor well known in the art. The processor 301 may also perform operations on at least one application or program to perform the method according to embodiments of the present invention. The sleep state monitoring apparatus 300 may include one or more processors.

The memory 303 stores various data, commands and / or information. The memory 303 may load one or more programs 309a from the storage 309 to perform the sleep state monitoring method according to embodiments of the present invention. RAM is shown as an example of the memory 303 in Fig.

The bus 305 provides the inter-component communication function of the sleep state monitoring apparatus 300. The bus 305 may be implemented as various types of buses such as an address bus, a data bus, and a control bus.

The network interface 307 supports wired / wireless Internet communication of the sleep state monitoring apparatus 300. In addition, the network interface 307 may support various communication methods other than Internet communication. To this end, the network interface 307 may comprise a communication module well known in the art.

The network interface 307 can receive various biometric signals of the user from the bio-signal measuring apparatus 100 shown in FIG. 1, for example, via a network.

The storage 309 may non-temporarily store the one or more programs 309a. Sleep state monitoring software 309a is illustrated in Figure 4 as an example of the one or more programs.

The storage 309 may be a nonvolatile memory such as a ROM (Read Only Memory), an EPROM (Erasable Programmable ROM), an EEPROM (Electrically Erasable Programmable ROM), a flash memory, etc., a hard disk, a removable disk, And any form of computer-readable recording medium known in the art.

The sleep state monitoring software 309a may perform a sleep state monitoring method for determining a sleep state of a user based on a user's bio-signal obtained according to an embodiment of the present invention or for detecting a sleep breathing disorder.

In detail, the sleep state monitoring software 309a is loaded into the memory 303 and is controlled by the one or more processors 301 to generate a first living body signal indicating a heartbeat state of the user and a second living body signal An operation of extracting the first biometric signal and the second biometric signal from the original biometric signal using the frequency of each biometric signal, an operation of extracting the first biometric signal and the second biometric signal from the original biometric signal, A determination unit configured to determine at least one reference bio-electrical signal to be used for determining a sleep state of the user, an operation to measure a signal period represented by the reference bio-electrical signal, and a sleep state of the user using the signal period Operation can be performed.

The sleep state monitoring software 309a may also be loaded into the memory 303 and used by one or more processors 301 to generate a first biological signal indicative of the user's breathing state and a second biological signal indicative of the user's snoring state, An operation for acquiring a biological signal, an operation for determining whether the user's respiratory disturbance state continues for a preset time period using the change of the first biological signal, determining whether the user's respiratory disturbance state continues for a preset time An operation of analyzing a correlation between the first bio-signal and the second bio-signal, and an operation of determining the user's sleep breathing disorder symptom using the correlation analysis result.

Up to now, the operation and configuration of the sleep state monitoring apparatus 300 according to the embodiment of the present invention have been described with reference to FIGS. 2 to 4. FIG. Next, a sleep state monitoring method according to another embodiment of the present invention will be described with reference to FIGS. 5 to 13. FIG. Hereinafter, each step of the sleep state monitoring method according to the embodiment of the present invention is assumed to be performed by the sleep state monitoring apparatus 300. It should be noted, however, that the subject of each operation included in the sleep state monitoring method may be omitted for convenience of explanation. In addition, each step of the sleep state monitoring method described below may be an operation performed in the sleep state monitoring apparatus 300 by the sleep state monitoring software 309a being executed by the processor 301. [

A sleep state monitoring method according to an embodiment of the present invention includes a sleep state determination method for determining a sleep state of a user and a sleeping breathing disorder detection method for detecting a sleeping breathing disorder. First, the sleep state determining method will be described with reference to FIGS. 5 to 12. FIG.

5 is a flowchart of a method of determining a sleep state.

Referring to FIG. 5, the sleep state monitoring apparatus 300 acquires an original bio-signal including a first bio-signal indicating a heartbeat state of a user and a second bio-signal indicating a respiration state of the user (S100). As described above, the sleep state monitoring apparatus 300 receives the first living body signal and the second living body signal from the living body signal measuring apparatus 100 located in the vicinity of the user's bed, Can be obtained.

Next, the sleep state monitoring apparatus 300 separates the first bio-signal and the second bio-signal from the original bio-signal based on the obtained frequency of the bio-signal (S110). For example, the sleep state monitoring apparatus can separate the first and second bio-signals using an FFT (Fast Fourier Transform) algorithm. However, it is not so limited, and one or more algorithms well known in the art may be used to separate the biosignals based on frequency.

More specifically, considering that the heartbeat of a person is faster than breathing, the sleep state monitoring apparatus 300 determines a relatively high-frequency radio-frequency bio-signal as a first bio-signal indicating a heartbeat state, The low-frequency bio-signal is determined to be the second bio-signal indicative of the breathing state (S120, S140).

Alternatively, the original biometric signal can be separated into a plurality of biometric signals based on the frequency, and the first biometric signal and the second biometric signal can be extracted from the plurality of biometric signals using the heartbeat frequency and the respiratory frequency of a predetermined person . However, in the case where the first bio-signal and the second bio-signal are obtained separately according to the embodiment, the above-described separation steps (S110, S120, S140) may be omitted.

Next, the sleep state monitoring apparatus 300 determines at least one reference bio-electrical signal to be used for determining the sleep state of the user from among the first bio-signal and the second bio-signal, and determines a signal cycle represented by the reference bio- . For example, in the case where the reference bio-electrical signal is determined as the first biological signal, the heartbeat period is measured in the first bio-signal (S130). When the reference biological signal is determined as the second biological signal, The period is measured (S150). That is, according to the embodiment of the present invention, even if any one of the first and second bio-signals is given, the sleep state of the user can be determined.

Next, the sleep state monitoring apparatus 300 determines the sleep state of the user using the determined signal period of the reference bio-signal (S160). A concrete algorithm for determining the sleep state of the user will be described later with reference to FIGS. 7 to 11. FIG.

Up to now, a sleep state monitoring method according to an embodiment of the present invention has been described with reference to FIG. However, it should be understood that the above-described sleep state monitoring method is a preferred embodiment for attaining the object of the present invention, and that some steps may be added or deleted as needed.

Next, in order to facilitate understanding, steps S110 to S150 for separating the living body signal and measuring the heartbeat period and the respiratory period with reference to the bio-signals illustrated in Figs. 6A to 6D will be described in detail. In the graphs shown in FIGS. 6A to 6D, the x-axis means time, and the y-axis means an a.u (arbitrary unit) in which the amplitude of the signal is adjusted in units of ratios.

6A illustrates an original biometric signal 510 including a first biometric signal and a second biometric signal. 6A, an original biological signal 510 is a signal obtained by converting an analog signal output from the biological signal measurement apparatus 100 into an analog signal through an ADC (Analog-Digital Converter) Quot; means a bio-signal including the " According to an implementation method, the original bio-signal may be a signal in which a signal processing process such as filtering and amplification is further performed.

Next, FIG. 6B illustrates the first biometric signal 511 and the second biometric signal 513 extracted from the original biometric signal 510. 6B, a first living body signal 511 having a relatively high frequency and a human heartbeat frequency from the original living body signal 510, a second living body signal 513 having a relatively low frequency and a human breathing frequency, Is extracted. As described above, the first and second bio-signals may be separated using algorithms well known in the art, such as FFT.

Next, FIG. 6C is a diagram for explaining a method of measuring the heartbeat period in the first living body signal 511 indicating the heartbeat state. In the figure, the inverted triangle indicates the peak point of the signal.

Referring to FIG. 6C, the sleep state monitoring apparatus 300 may detect a peak 511a or a valley of the first living body signal 511 to measure a heartbeat period in the first living body signal 511. In order to detect a peak 511a of the signal, the sleep state monitoring device 300 may utilize one or more peak detection algorithms that are well known in the art. For reference, only the detection of the peak of the signal and the detection of the heartbeat period is shown in this figure, but it should be noted that this is merely an example for measuring the heartbeat period. That is, according to another embodiment of the present invention, it is also possible to measure the heartbeat period by detecting the valley of the signal and measuring the period between the valleys.

When the peak 511a is detected in the first living body signal 511, the sleep state monitoring apparatus 300 can measure a heartbeat period by calculating a time interval between peaks.

Next, FIG. 6D is a diagram for explaining a method of measuring the respiratory cycle in the second living body signal 513 indicating the breathing state. In the figure, the inverted triangle indicates the peak point of the signal.

Referring to FIG. 6D, the sleep state monitoring apparatus 300 detects a peak 513a in the second biological signal 513 in the same manner as the method of measuring the heartbeat period, and detects a time interval 513b between the plurality of detected peak points To measure the respiratory cycle. And a description thereof will be omitted in order to exclude redundant description.

Up to now, steps (S110 to S150) for separating a living body signal and measuring a heartbeat period and a respiratory period have been described with reference to FIGS. 6A to 6D. Next, a detailed algorithm of the sleep state determination step S160, which can be referred to in some embodiments of the present invention, will be described with reference to FIGS.

7 to 8 are diagrams for explaining a method of determining a sleep state using a first living body signal indicating a heartbeat state (hereinafter referred to as a "first sleep state determination algorithm"). FIG. 7 is a flowchart of the first sleep state determination algorithm, and FIG. 8 is a graph showing a change of a heartbeat period into a frequency domain. In the graph, the x-axis means frequency and the y-axis means PSD (Power Spectrum Density).

Referring to FIGS. 7 and 8, the sleep state monitoring apparatus 300 calculates a change in a heartbeat period to determine a sleep state and converts it into a frequency domain (S161a, S161b). Here, the change of the heartbeat period may mean, for example, heart rate variability (HRV), and an algorithm such as FFT may be used to convert the change of the heartbeat period into the frequency domain.

For reference, the reason for converting the changes in the heart rate measured in the time domain into the frequency domain is that a specific frequency band of heart rate variability reflects the action of sympathetic nerves and parasympathetic nerves. In other words, through the frequency analysis, the degree of activation of parasympathetic nerves associated with the sympathetic nerve and the relaxed state associated with the excited state can be grasped and the user's sleep state can be judged.

Next, the sleep state monitoring apparatus 300 calculates an area occupied by a high frequency band (hereinafter, referred to as 'HF') and a low frequency band (hereinafter referred to as 'LF') in the frequency domain S161c). Here, the LF band 523 represents the influence of the sympathetic nerve in the frequency band between 0.04 and 0.15 Hz, and the HF band 525 influences the parasympathetic nerve in the frequency band between 0.15 and 0.4 Hz. That is, the widths of the LF band 523 and the HF band 525 can be understood as indicating the degree of activation of the sympathetic nerve and the degree of activation of the parasympathetic nerve, respectively.

Next, the sleep state monitoring apparatus 300 compares the ratio (LF / HF) of the widths of the LF band 523 and the HF band 525 to a preset threshold value (S161d) (Step S161f). Here, the ratio (LF / HF) of the width can be understood as an index indicating the balance of the autonomic nervous system, and the greater the ratio of the width of the LF band 523, the more active the sympathetic nervous system in the autonomic nervous system It can be seen that the user's state is closer to the arousal state. In contrast, as the width ratio of the HF band 525 increases, the sleep state monitoring apparatus 300 determines that the user is close to the sleep state (S161e).

Up to now, the first sleep state determination algorithm for determining the sleep state of the user by using the first living body signal indicating the heartbeat state has been described. Next, referring to FIG. 9, an algorithm for determining a user's sleep state based on a second bio-signal indicating a breathing state (hereinafter referred to as a second sleep determination algorithm) will be described.

9 is a flowchart of a second sleep determination algorithm.

Referring to FIG. 9, the sleep state monitoring apparatus 300 calculates a deviation with respect to the respiration period measured in the previous step S150 (S163a). The deviation with respect to the respiratory cycle can be understood as an index indicating the instability of respiration. The deviation for the respiratory cycle may be, for example, but is not limited to, standard deviation.

The sleep state monitoring apparatus 300 compares the calculated deviation value with a predetermined threshold value (S163b), and if the deviation value is equal to or greater than a predetermined threshold value, determines that the user is awake (S163d). Also, in the opposite case, the sleep state monitoring apparatus 300 determines the state of the user as a sleep state (163c). That is, the sleep state monitoring apparatus 300 determines that the user is in the sleep state when the respiration of the user is stable.

Up to now, the second sleep state determination algorithm for determining the sleep state of the user by using the second bio-signal indicating the breath state has been described. Next, an algorithm (hereinafter referred to as a third sleep surface determination algorithm) for determining the sleep state of the user by using the correlation between the first and second bio-signals will be described with reference to FIGS. 10 to 11. FIG.

10 is a flowchart of a third sleep determination algorithm.

10, the sleep state monitoring apparatus 300 analyzes a period of a heartbeat interval measured in the first living body signal and a respiration period measured in the second living body signal to determine whether the two periods are synchronized with each other (S165a ). Specifically, the sleep state monitoring apparatus 300 can determine that the periods of the two signals are synchronized with each other when the difference between the phase of the heartbeat interval and the phase of the respiration cycle is small in the time domain.

According to the implementation method, the sleep state monitoring apparatus 300 can calculate a result indicating the degree of synchronization between the period of the heartbeat interval and the respiratory cycle, and when the resultant value is equal to or less than the predetermined threshold value, Can be determined.

If the sleep period monitoring apparatus 300 synchronizes the periods of the heartbeat intervals and the respiration periods, the sleep state is determined (S165b, S165d). If the sleep state is not synchronized, the sleep state monitoring apparatus 300 determines that the user is awake (S165b, S165c).

This is because the amount of oxygen inhaled into the body, which varies with respiration, affects the heartbeat, so that when the other elements are not intervened, the respiratory cycle and the heartbeat interval cycle are synchronized with each other. In other words, when the sympathetic nerve is activated, many other elements are intervening in the living body, so that synchronization does not occur. When the parasympathetic nerves are activated, the human body is stabilized and the intervention of other elements is not so great. The sleep state is determined using a feature that is well synchronized.

For example, a bio-signal of a user in a sleep state can be shown as in Fig. 11, the interval between the second living body signal 531 indicating the breathing state and the heartbeat 533 measured in the first living body signal shows that the phases of the respiratory cycle and the heartbeat interval of about 4 seconds are substantially coincident with each other Can be seen. This is because, as described above, the parasympathetic nerves are activated and the cycle of the respiratory cycle and the heartbeat interval are synchronized.

The first to third sleep state determination algorithms that can be used for determining the sleep state of the user have been described. As described above, the sleep state monitoring apparatus 300 determines the sleep state of the user by selectively using any one of the first sleep state determination algorithm to the third sleep state determination algorithm according to the type of the bio-signal to be obtained .

If both the first and second bio-signals are acquired, the sleep state monitoring apparatus 300 may perform a first sleep state determination algorithm to a third sleep state determination algorithm in various ways .

For example, when combining the first to third sleep state determination algorithms on the basis of probability, the sleep state monitoring apparatus 300 may be configured such that, when two or more sleep state determination algorithms output a user state to a sleep state The user's state can be determined to be in the sleep state. Alternatively, the sleep state monitoring apparatus 300 may calculate a final result value using a weighted sum, an arithmetic mean, a weighted average, and the like for at least one of the result values of the first to third sleep state determination algorithms And if the final result value is equal to or greater than a predetermined threshold value, the user can be determined to be in a sleep state or awake state. Here, the result value means a value used for determining the state of the user as a sleep state or awake state in each sleep state determination algorithm.

Further, according to an embodiment of the present invention, the first sleep state determination algorithm to the third sleep state determination algorithm may be used to determine a sleep phase of the user. For example, if the result value of each sleep state determination algorithm is determined to be awake when the result value is equal to or greater than the predetermined first threshold value, and if the result is equal to or greater than the first threshold value and equal to or greater than the predetermined second threshold value, , And can be determined in the same manner as a first-stage sleep state, a second-stage sleep state, and the like depending on the magnitude of the result value. The level of granularity of the sleeping step may vary depending on the implementation method.

Alternatively, the sleep state monitoring apparatus 300 may calculate a final result value using a weighted sum, an arithmetic mean, a weighted average, and the like for at least one of the result values of the first to third sleep state determination algorithms And determine the sleeping phase of the user by comparing the final result value with a preset threshold value.

In this case, when the final result value is calculated using a weighted sum or a weighted average, the weight used for the weighted sum or the weighted average may be determined using one or more machine learning models well known in the art. For example, the machine learning model may be a linear regression model, an artificial neural network model, or the like, and a data set accumulated through a sleep polygraph inspection using a learning data set used for machine learning Can be used. That is, the sleep state monitoring apparatus 300 can accurately determine the sleep phase of the user by using the weight determined through the machine learning. The linear regression model and the artificial neural network model are machine learning models widely known in the art, and a description thereof will be omitted.

Meanwhile, according to another embodiment of the present invention, the sleep state monitoring apparatus 300 can further determine the sleep state of the user by using the fourth bio-signal indicating the user's movement state. Hereinafter, an embodiment in which the sleep state of the user is determined by further considering the fourth bio-electrical signal will be described with reference to FIG.

For example, when the original biometric signal includes a first biometric signal indicating a user's heartbeat state, a second biometric signal indicating a user's breathing state, and a fourth biometric signal indicating a user's motion state, The controller 300 first extracts the fourth living body signal and separates the first living body signal and the second living body signal from the remaining signals. The fourth bio-signal is much stronger than the other bio-signals, so it is efficient to extract the fourth bio-signal first, and it is difficult to extract the first and second bio-signals in a state in which the fourth bio-signal is included .

Next, the sleep state monitoring apparatus 300 measures the movement of the user from the fourth living body signal indicating the movement state. This will be described with reference to the fourth living body signal 535 shown in Fig.

Referring to FIG. 12, the sleep state monitoring apparatus 300 may determine that there is movement when a signal exceeding a preset threshold value continuously appears at a predetermined interval or more. Specifically, the sleep state monitoring apparatus 300 detects a peak point of a predetermined threshold value or more in the fourth bio-signal and calculates a time interval of the detected peak point.

For example, when the detection time of the first peak point is 2:00:00, the detection time of the second peak point is 2:02:00, and the detection time of the third peak point is 2:04:00, A time interval (e ⁱ ) between the first peak point and the second peak point and a time interval (e ^{i + 1} ) between the second peak point and the third peak point are calculated. Next, the sleep state monitoring apparatus 300 compares each time interval (e ⁱ , e ^{i + 1} ) with a threshold time of toss. If the time interval e ⁱ , e ^{i + 1} is greater than or equal to the predetermined time interval, the sleep state monitoring apparatus 300 may determine that the user has been moved during the time interval e ⁱ , e ^{i + 1} . In such a case, the heart rate and respiratory rate measurement may not be performed in the interval corresponding to the time interval (e ⁱ , e ^{i + 1} ).

The reason for determining that there is a movement of the user only when the time interval is equal to or longer than a predetermined time interval is because a short variation of one motion signal is highly likely to be noise generated in the sensor.

When the user's motion state is measured, the sleep state monitoring apparatus 300 can determine the sleep state of the user in consideration of the motion state of the user. For example, when the motion of the user is severe, the user can determine that the user is close to the awake state.

However, when the sleep state of the user is measured only by the movement, the accuracy of the judgment is lowered, so that the sleep state monitoring apparatus 300 can preferably use the user's movement state as a secondary element. For example, in determining the sleep state of the user through the first to third sleep state determination algorithms described above, the sleep state of the user can be determined by further considering the measured motion state.

Specifically, the sleep state monitoring apparatus 300 may include a weighted sum of at least one of the results of the first to third sleep state determination algorithms and a measurement value indicating the measured motion state, an arithmetic average, Weighted average, etc., and the final resultant value is compared with the predetermined threshold value to determine the user's sleeping state or sleeping phase.

Up to now, a method of determining the sleep state of the user has been described with reference to Figs. 5 to 12. Fig. According to the above-described method, the sleep state monitoring apparatus 300 can improve the accuracy of the user's sleep state and sleep phase judgment by considering a plurality of bio-signals and combining a plurality of sleep state determination algorithms.

Next, a description will be given of a method for detecting a sleeping breathing fault included in a sleeping state monitoring method with reference to FIGS. 13 to 14. FIG.

First, the problem of the conventional sleep breathing disturbance detection method will be briefly described. The conventional detection method is to detect the sleep breathing disorder based on the user's breathing state, or to use the OSA of the sleeping breathing trouble using the snoring sound of the user . Conventional detection methods for detecting sleeping breathing disorders based on respiratory conditions can not distinguish between OSA and CSA treatment methods but can not detect them. Conventional detection methods using snoring sounds can not detect CSA, and OSA There is a problem that the accuracy of detection is also lowered.

In order to solve such a problem, the sleep apnea detection method according to the present invention correctly detects the OSA and the CSA based on the correlation between the second bio-signal indicating the breathing state and the third bio-signal indicating the snoring state . Hereinafter, a method for detecting sleep apnea according to the present invention will be described in detail.

13 is a flowchart of a sleep state monitoring method.

Referring to FIG. 13, the sleep state monitoring apparatus 300 acquires a second living body signal indicating a breathing state and a third living body signal indicating a snoring state (S200). The second and third living body signals can be received and obtained from the living body signal measuring apparatus 100. According to the embodiment, the third living body signals can be obtained through a measuring device such as a microphone built in the sleep state monitoring apparatus 300 You can also get it directly.

Next, the sleep state monitoring apparatus 300 determines whether the sleep breathing disorder state such as apnea or hypothermia continues for a predetermined time or longer by using the second bio-signal (S210). For example, when the change in the second living body signal according to the breathing cycle does not occur over a predetermined period of time, or the intensity of the breathing signal is less than or equal to a preset threshold value, the sleeping state monitoring apparatus 300 generates sleeping breathing disorder symptoms It can be judged.

In a case where the sleep-disordered breathing state continues for a predetermined time or more, the sleep state monitoring apparatus 300 analyzes a correlation between the second bio-signal and the third bio-signal (S230). For example, the sleep state monitoring apparatus 300 may perform a correlation analysis by calculating a correlation coefficient between the second bio-signal and the third bio-signal. For example, the sleep state monitoring apparatus 300 may calculate a cross correlation coefficient to obtain a degree of a cross correlation between the second bio-signal and the third bio-signal . However, the present invention is not limited to this, and various types of correlation analysis techniques can be used.

The reason for analyzing the correlation between the second bio-signal and the third bio-signal is that there is a high probability that the snoring occurs in the OSA when the cause of the snoring is caused by the user's breathing. In other words, if the snoring occurs according to the breathing of the sleeping user and the snoring stops when the sleeping user stops breathing, the user may be experiencing OSA symptoms.

To further facilitate understanding, the graphs shown in Figs. 14A to 14D will be described. 14A shows a second bio-signal 541 and a third bio-signal 543, FIG. 14B is an enlarged view of a part of the graph of FIG. 14A, FIG. 14C shows a graph of OSA symptoms, 14d shows a graph of CSA symptoms.

Referring to FIG. 14B, it can be seen that a snoring sound is generated in the inspiration phase in which the user breathes. Specifically, breathing swinging (545) occurs during the inspiration and snoring occurs, resulting in a similar pattern in both biological signals. That is, in such a case, a correlation appears between the second bio-signal and the third bio-signal. 14B, since the snoring of the user is caused by the breathing of the user, it is more preferable that the snoring state of the user is measured using only the third bio-signal, It may be more accurate to measure the snoring status of the user by using more correlations. In other words, if the correlation between the second bio-signal and the third bio-signal is utilized according to the present invention, not only can the OSA and the CSA be detected separately, but also the snoring state of the user can be accurately measured.

Next, if the OSA symptom shown in FIG. 14C is observed, the respiratory disorder symptoms in which the respiration change does not occur in the second bio-signal 547, and the third bio-signal 549 ). That is, when there is breathing, snoring occurs, and a correlation appears between the second bio-signal 547 and the third bio-signal 549. On the contrary, in the bio-signal for the CSA symptom shown in FIG. 14D, although the respiratory disorder symptoms appear in the second bio-signal 547, no change occurs in the third bio-signal 549, Able to know. Accordingly, the OSA and the CSA can be accurately discriminated by analyzing the correlation between the second bio-signal and the third bio-signal.

Referring again to FIG. 13, when the sleep state monitoring apparatus 300 determines that there is a correlation (S240), it is determined that the OSA symptom occurs in the sleep breathing disorder (S260). For example, the sleep state monitoring apparatus 300 can determine that the OSA symptom occurs when the calculated correlation coefficient value is equal to or greater than a predetermined threshold value. However, according to the algorithm used for the correlation analysis, it may be determined that the OSA has occurred when the threshold value is less than a preset threshold value. In the opposite case, the sleeping state monitoring apparatus 300 determines that the CSA symptom occurs to the sleeping user (S250).

Up to now, a method for detecting sleeping breathing disorders has been described with reference to Figs. 13 to 14. Fig. According to the above-described method, the OSA and the CSA can be accurately discriminated and compared with the conventional detection method. Further, the correlation between the second bio-signal indicating the breathing state and the third bio-signal indicating the snoring state can be used to accurately measure the snoring state of the user, thereby further improving the accuracy of OSA detection . It should be noted that the above-described sleep breathing disturbance detection method is a preferred embodiment for attaining the object of the present invention, and that some steps may be added or deleted as needed.

According to another embodiment of the present invention, when the sleep state monitoring method is implemented in the PAP, it can be used to appropriately control the PAP to improve the user's sleeping and sleeping disorder treatment effect. For example, the sleep state monitoring apparatus 300 may be implemented as a PAP or the sleep state monitoring apparatus according to the present invention may be used to control the PAP by the sleep state monitoring apparatus 300 controlling the PAP through the network.

Briefly describing the PAP for ease of understanding, PAP is a device used to treat sleeping breathing disorders, and is a device that carries air to the airway through a specially designed mask. More specifically, the CPAP (Continuous PAP) of the PAP is a device for preventing sleeping breathing trouble by applying pressure to the nose and mouth to open the upper airway. However, since the CPAP applies a constant fixed pressure without consideration of the user's breathing state, the user's breathing is made inconvenient and the compliance is greatly reduced. That is, since the conventional CPAP operates at a constant pressure regardless of the user's sleeping phase, the treatment effect is lowered and the user's breathing is disturbed. Therefore, it is necessary to control the CPAP appropriately.

On the other hand, Bi-PAP uses internal sensors to measure whether the user's breathing state is in the inspiratory or exhalation state and adjusts the positive pressure and the negative pressure accordingly. However, since the sensor is built in Bi-PAP, This also can not provide comfortable breathing to the user.

Hereinafter, a method of controlling the PAP operation according to the sleep state and the sleeping phase of the user will be briefly described with reference to FIGS. 15A to 15B. FIG.

Referring to FIG. 15A, the sleep state monitoring apparatus 300 detects a sleeping breathing disorder using a second living body signal indicating a breathing state and a third living body signal indicating a snoring state (S300). Step S300 corresponds to the above-described sleeping breathing fault detection method, and a description thereof will be omitted.

When the sleeping breathing disorder is detected (S310), the sleeping state monitoring apparatus 300 transmits a control signal for operating the PAP to operate the PAP (S320). More specifically, when the OSA is detected during the sleeping breathing disorder, the sleep state monitoring apparatus 300 may transmit a control signal for operating the PAP.

Next, the sleep state monitoring apparatus 300 measures the user's sleep state or respiration state in real time (S330). For example, the sleep state monitoring apparatus 300 may measure the sleep state or sleep phase of the user according to the method shown in FIG. 5, or may measure the breathing state of the user from the second living body signal.

Next, the sleep state monitoring apparatus 300 transmits a control signal for controlling the pressure of the PAP according to the sleeping phase or the breathing state of the user (S340). For example, the sleep state monitoring device 300 may monitor the user ' s sleep phase and control the pressure of the PAP to change accordingly as the sleep phase of the user changes. Thus, by appropriately controlling the pressure of the PAP in accordance with the sleeping phase, it can assist the user in sleeping.

Further, as shown in FIG. 15B, a control signal for controlling the pressure of the PAP to positive pressure is transmitted at the time of inspiration using the user's breathing state from the second bio-electrical signal, and a control signal for controlling the pressure at the time of exhalation is transmitted The pressure of the PAP can be controlled. Alternatively, the pressure of the PAP may be adjusted appropriately according to the user's sleeping phase.

Up to now, a method of controlling the operation of the PAP according to sleep apnea has been briefly described with reference to Figs. 15A to 15B. According to the above-described method, the operation of the PAP is automatically controlled according to the detection of the sleeping breathing fault and the breathing state of the user, thereby providing the user with a good quality sleeping surface.

Next, the user interface provided by the sleep state monitoring apparatus 300 will be briefly described with reference to Figs. 16A to 16B.

16A to 16B are exemplary views of a user interface showing sleep information of a user.

Referring to FIG. 16A, the user interface provided by the sleep state monitoring apparatus 300 includes a first region 551 showing graphical sleep phase information for intuitively showing the sleep information of the user, And a second area 553 for providing information.

The user can grasp the information such as the number and time of the RAM sleeping step, the number of times of the sleeping step of the NEMEM, and the time at a glance through the graph shown in the first area 551, and thus the approximate quality of sleeping can be grasped .

In addition, the user can obtain information on the quality of sleep (efficiency) calculated on the basis of the sleep history, the sleep time, the sleep time, the sleep time during the sleep time, and the awake time based on the summary information shown in the second area 553 . In the second area, the sleep time, the RAM sleep time, the sleep time and the deep sleep time ratio, the user's sleep time, the first sleep time, the first RAM sleep time, And summary information such as time can be displayed.

In addition, the sleep state monitoring apparatus 300 may provide the user with information on the user's sleep record in a more intuitive form such as the user interface shown in FIG. 16B.

In summary, the sleep state monitoring apparatus 300 can provide a user with a user interface for sleep recording, and the user can intuitively grasp information about his sleep state, sleep quality, etc. through the user interface .

17, an example of a sleep management service provided in conjunction with the IoT system 700 according to another embodiment of the present invention will be described.

Referring to FIG. 17, the sleep state monitoring system 10 may provide various sleep management services in cooperation with the IoT system 700.

For example, if the sleep state monitoring device 300 determines that the user is entering a sleep state, the IoT system 700 may turn off the lighting device that is on and control the volume of the audio device being played back to gradually decrease , It is possible to automatically switch to music that is useful for sleeping and to be reproduced. In addition, if it is determined that the user is in the sleep state, the power of the audio apparatus can be turned off to stop the operation.

When it is determined that the user is awake in the vicinity of the rising time, the IoT system 700 can turn on the electric lamp, turn on the power of the audio device to reproduce music, operate the coffee machine Can be provided.

In addition, when an emergency such as a sleeping breathing disorder occurs continuously during a sleep, a service for automatically notifying the emergency room can be provided. In the case of a user having a sleeping disorder, the sleep record of the user can be periodically To the service provider.

In addition, the user may be provided with a personalized sleep management service by setting a service to be provided according to conditions related to the sleep state or the sleeping phase. For example, when entering a sleeping state, various personalized sleep management services can be provided by setting various services according to conditions such as the first non-sleep step, the last sleep sleep step, and the like.

For example, when the user is lying on a bed (awake), the IoT system (700) automatically darkens the lighting device and, when entering the sleeping state, extinguishes the lighting device in the bedroom, The power of the apparatus that is generated can be turned off. In addition, when the user enters the sleeping step of the Nemes, the temperature of the heating device is adjusted to a predetermined first temperature, and when the REM level at the dawn time is more than the preset time or the number of times, The heating cost can be reduced by adjusting the temperature to a predetermined second temperature. At this time, it is preferable that the first temperature is set to a temperature lower than the pre-adjustment temperature, and the second temperature is set to a temperature higher than the pre-adjustment temperature.

As another example, if a user who was asleep before the wake-up time wakes up in the bed (awake state) and heads to the toilet, the IoT system 700 will illuminate the bedroom lighting system with a very low brightness or brightness, It is possible to prevent the user from being awakened in the sleeping state while preventing the danger during going. In addition, the IoT system 700 sounds an alarm when the user enters the sleep state of the RAM before or after the alarm time set by the user, does not sound an alarm when the user is awake before or after the alarm time set by the user, To provide a service that helps regular sleep.

The concepts of the invention described above with reference to Figures 5 to 17 can be implemented in computer readable code on a computer readable medium. The computer readable recording medium may be, for example, a removable recording medium (CD, DVD, Blu-ray disk, USB storage device, removable hard disk) . The computer program recorded on the computer-readable recording medium may be transmitted to another computing device via a network such as the Internet and installed in the other computing device, thereby being used in the other computing device.

Although the operations are shown in the specific order in the figures, it should be understood that the operations need not necessarily be performed in the particular order shown or in a sequential order, or that all of the illustrated operations must be performed to achieve the desired result. In certain situations, multitasking and parallel processing may be advantageous. Moreover, the separation of the various configurations in the above-described embodiments should not be understood as such a separation being necessary, and the described program components and systems may generally be integrated together into a single software product or packaged into multiple software products .

While the present invention has been described in connection with what is presently considered to be practical exemplary embodiments, it is to be understood that the invention is not limited to the disclosed embodiments, but, on the contrary, You will understand. It is therefore to be understood that the above-described embodiments are illustrative in all aspects and not restrictive.

Claims (16)

A sleep state monitoring method performed by a sleep state monitoring apparatus,
Acquiring an original biometric signal including a first biometric signal indicating a heartbeat state of a user and a second biometric signal indicating a breathing state of the user;
Extracting the first biometric signal and the second biometric signal from the original biometric signal using the frequency of each biometric signal;
Determining at least one reference biological signal used for determining a sleep state of the user from among the first biological signal and the second biological signal;
Measuring a signal period appearing in the reference bio-signal; And
And determining a sleep state of the user using the signal period.
How to monitor sleep status. The method according to claim 1,
Wherein the determining of the at least one reference bio-
And determining the first biological signal as the reference biological signal,
Wherein the step of determining the user sleep state comprises:
Converting a change in the signal period measured in the reference bio-electrical signal into a frequency domain;
Calculating a width of a first area occupied by the high frequency component signal in the frequency domain and a width of a second area occupied by the low frequency component signal; And
And determining that the sleep state of the user is awake when the ratio of the width of the first area to the width of the second area is equal to or greater than a preset threshold value.
How to monitor sleep status. The method according to claim 1,
Wherein the determining of the at least one reference bio-
And determining the second bio-signal as the reference bio-signal,
Wherein the step of determining the sleep state of the user comprises:
Calculating a deviation of the signal period measured in the second bio-signal;
Determining a state of awake when the deviation of the signal period measured in the second bio-signal is equal to or greater than a preset threshold value;
How to monitor sleep status. The method according to claim 1,
Wherein the determining of the at least one reference bio-
And determining the first bio-signal and the second bio-signal as the reference bio-signal,
Wherein the step of determining the sleep state of the user comprises:
Calculating a result indicating a degree of synchronization between a period of the time interval of the first biometric signal and a period of the second biometric signal; And
And determining that the output value is awake if the output value is equal to or less than a preset threshold value.
How to monitor sleep status. The method according to claim 1,
Wherein the determining of the at least one reference bio-
And determining the first bio-signal and the second bio-signal as the reference bio-signal,
The step of determining the sleep state of the user comprises:
Calculating a first result value indicating a ratio of an area occupied by the high-frequency component signal and the low-frequency component signal included in the first living body signal in the frequency domain;
Calculating a second result value indicating a deviation of the signal period measured in the second bio-signal;
Calculating a third result value indicating a degree of synchronization between a period of the time interval of the first biometric signal and a period of the second biometric signal; And
And determining a sleep state of the user using at least one of the first resultant value, the second resultant value, and the third resultant value.
How to monitor sleep status. 6. The method of claim 5,
Calculating a weighted sum of at least one of the first resultant value, the second resultant value, and the third resultant value; And
Further comprising: comparing the weighted sum with a predetermined threshold value to determine a sleeping phase of the user;
How to monitor sleep status. A sleep state monitoring method performed by a sleep state monitoring apparatus,
Obtaining a first biological signal indicative of a breathing state of a sleeping user and a second biological signal indicative of a snoring state of the user;
Determining whether the respiratory disturbance state of the user is maintained for a predetermined time using the change of the first bio-signal;
Analyzing a correlation between the first bio-signal and the second bio-signal when it is determined that the respiratory disturbance state of the user is maintained for a preset time period; And
And determining a symptom of a sleeping breath disorder of the user using the correlation analysis result.
How to monitor sleep status. 8. The method of claim 7,
Wherein the step of determining the user's sleeping breathing disturbance symptom comprises:
Determining a sleeping breath symptom of the user as an OSA (Obstructive sleep apnea) when there is a correlation between the first biological signal and the second biological signal as a result of the correlation analysis;
How to monitor sleep status. 8. The method of claim 7,
If it is determined that the breathing fault state of the user is maintained for the predetermined time,
Further comprising transmitting a control signal to operate a PAP (Positive Airway Pressure)
How to monitor sleep status. 8. The method of claim 7,
Measuring a breathing state of the user using the first bio-signal; And
Further comprising sending a control signal to control the pressure of the PAP according to the breathing state of the user,
How to monitor sleep status. 11. The method of claim 10,
The step of transmitting a control signal for controlling the pressure of the PAP includes:
And transmitting a control signal for controlling the pressure of the PAP to a positive pressure when the breathing state of the user is in an intake state.
How to monitor sleep status. 8. The method of claim 7,
Determining a sleeping phase of the user; And
Further comprising sending a control signal to adjust the pressure of the PAP according to the sleep phase of the user,
How to monitor sleep status. One or more processors;
Network interface;
A memory for loading a computer program executed by the processor; And
And a storage for storing the computer program,
The computer program comprising:
Obtaining an original bio-electrical signal including a first bio-signal indicating a heartbeat state of a user and a second bio-signal indicating a respiration state of the user;
An operation of extracting the first bio-signal and the second bio-signal from the original bio-signal using the frequency of each bio-signal;
Determining at least one reference bio-electrical signal to be used for determining the sleep state of the user out of the first bio-signal and the second bio-signal;
An operation of measuring a signal period appearing in the reference bio-signal; And
And determining the sleep state of the user using the signal period.
Sleep state monitoring device .. One or more processors;
Network interface;
A memory for loading a computer program executed by the processor; And
And a storage for storing the computer program,
The computer program comprising:
Obtaining a first biological signal indicative of a breathing state of a sleeping user and a second biological signal indicative of a snoring state of the user;
Determining whether the respiratory disturbance state of the user is maintained for a predetermined period of time using the change of the first living body signal;
Analyzing a correlation between the first biometric signal and the second biometric signal when it is determined that the respiratory disturbance state of the user is maintained for a predetermined period of time; And
And an operation of determining the symptom of sleeping breathing disorder of the user using the correlation analysis result.
Sleep state monitoring device. In combination with the computing device,
Acquiring an original biometric signal including a first biometric signal indicating a heartbeat state of a user and a second biometric signal indicating a breathing state of the user;
Extracting the first biometric signal and the second biometric signal from the original biometric signal using the frequency of each biometric signal;
Determining at least one reference biological signal used for determining a sleep state of the user from among the first biological signal and the second biological signal;
Measuring a signal period appearing in the reference bio-signal; And
The method comprising the steps of: determining a sleep state of the user using the signal period;
Computer program. In combination with the computing device,
Obtaining a first biological signal indicative of a breathing state of a sleeping user and a second biological signal indicative of a snoring state of the user;
Determining whether the respiratory disturbance state of the user is maintained for a predetermined time using the change of the first bio-signal;
Analyzing a correlation between the first bio-signal and the second bio-signal when it is determined that the respiratory disturbance state of the user is maintained for a preset time period; And
And a step of determining a symptom of sleeping breathing disorder of the user by using the analysis result of the correlation,
Computer program.

Images