WO2017119638A1

WO2017119638A1 - Real-time sleep disorder monitoring apparatus

Info

Publication number: WO2017119638A1
Application number: PCT/KR2016/014979
Authority: WO
Inventors: 원용관
Original assignee: 전남대학교산학협력단
Priority date: 2016-01-08
Filing date: 2016-12-21
Publication date: 2017-07-13

Abstract

The present invention relates to a real-time sleep disorder monitoring apparatus comprising: a main terminal body formed in a band form so as to be worn around the neck of a user; a sensor unit for detecting biometric data including breathing signals while the user wearing the main terminal body sleeps; a stimulus generation unit capable of applying a stimulus to the user wearing the main terminal body; and a terminal control unit for controlling the stimulus generation unit such that the stimulus is applied to the user if the biometric data detected by the sensor unit corresponds to a set stimulus application condition. Configured as such, the real-time sleep disorder monitoring apparatus, which is worn around the neck, can overcome disadvantages such as wearing inconvenience, which is caused by the many wires conventional polysomnography (PSG) devices have, and high costs resulting from the required absolute involvement of an expert, can particularly induce immediate escape from a critical sleep disorder through real-time monitoring during sleep, and thus provides the advantage of preventing a serious accident.

Description

Real-time sleep disorder monitoring device

The present invention relates to a real-time sleep disorder monitoring apparatus, and more particularly, to a real-time sleep disorder monitoring apparatus that can apply a sleep escape stimulation in case of emergency while real-time monitoring of the factors related to sleep disorders.

Sleep disorders include breathing disorders such as snoring and apnea, blood oxygen deficiency, heartbeat abnormalities, decreased blood flow, rapid eye movement (REM), teeth grinding, jaw clenching, muscle stiffness, It is caused by factors such as frequent torsion, which causes sleep quality and fatigue even after sufficient sleep time.If long-term symptoms persist, heart disease, lung disease, vascular disease, brain damage, Significantly increases the likelihood of dementia, rheumatoid arthritis, depression, loss of libido, sudden death and diabetes.

Respiratory disturbances during sleep include snoring and apnea, and the air passages are narrowed due to relaxation of the throat and surrounding muscles, causing the snoring to inhale or exhale by vibrating the soft parts around when air flows through this area. Severe obstruction of the air passages can cause apnea, which makes breathing difficult.

Blood oxygen saturation (SpO ₂ ) represents the oxygen binding ratio of hemoglobin, and low oxygen saturation, low oxygen, causes serious problems in the central nervous system and cardiovascular system. In particular, one of the main causes of hypoxia during sleep is a respiratory disorder (especially apnea), which is treated as an important factor in monitoring and determining sleep disorders along with respiratory analysis.

Heart beat abnormalities can lead to a decrease in the functioning of various organs due to poor blood supply to the body, and in particular, serious situations such as a heart attack can be directly related to death. Surveillance is absolutely necessary.

Although it does not cause a serious situation during sleep, other sleep disorders, such as rapid eye movement (REM), teething, jaw clenching, muscle stiffness in the arms and lower limbs, and frequent overturning are also treated as sleep disturbance factors. Lose.

Conventionally, portable or wearable sleep respiratory monitoring devices have been presented in various shapes such as beds, pillows, dolls, and the like, and a respiratory state monitoring function using a smart phone is also presented, but a respiratory state monitoring device is analyzed based on sound information. Due to the nature of the device and the position of the sleeper, there is a problem that a large difference in surveillance performance occurs.

Conventional wearable oxygen saturation (SpO ₂ ) inspection device is measured by using the visible and infrared wavelengths are mainly provided in the form worn on the fingertips, and recently has been provided as a function mounted on a smart phone or smart watch, but during sleep It is not suitable for the purpose of wearing, it is difficult to cope with the emergency situation in real time.

Conventional wearable heart rate monitoring device is a mainstream attachable electrocardiogram device that detects electrical signals related to cardiac activity, and can monitor the heart condition including heart rate in real time by analyzing the measured electrical signals, heart The measurement of only the beat rate can be obtained from the oxygen saturation measurement signal.

Other disturbance factors related to muscle activity in specific areas, such as eye movements, bruising, jaw clenching, and muscle stiffness, are measured and analyzed by EMG measurement principles. Can be measured and analyzed by the sensor.

The most common technology and apparatus for measuring sleep disorder-related factors are integrated with polysomnography (PSG), and comprehensively measure various factors related to sleep disorders. However, the device may be disturbed by the complicated measurement cable connected to the sleeper's body, which makes it difficult to diagnose the natural state.

Recently, a wireless sleep polygraph (PSG) has been provided to overcome these drawbacks, but basically the sleep polygraph (PSG) has to be dealt with by a specialist, hospitalized and has a high cost. In addition, since only basic data is collected and stored during sleep and later analyzed by an expert, it is only a one-time diagnosis, and there is a disadvantage in that it is not possible to monitor and determine a sleep disorder in real time during sleep, and thus cannot cope with an emergency during sleep.

This eliminates the inconvenience of wearing during sleep, makes it easy for non-professionals to use, diagnoses without being admitted to the hospital, and provides accurate and effective monitoring of sleep disorders that can be dealt with immediately in case of emergencies due to disorders during sleep. There is a need for an apparatus and method for the same.

[Preceding technical literature]

(Patent Document 1) Korean Unexamined Patent Publication No. 10-2013-0140595

(Patent Document 2) Korean Unexamined Patent Publication No. 10-2007-0048201

(Patent Document 3) Korean Unexamined Patent Publication No. 10-2007-0084901

(Patent Document 4) U.S. Patent US 7,559,903 B2

The present invention has been made to improve the above problems, eliminating the inconvenience of wearing, can also be used by non-professional, can diagnose sleep disorders without being hospitalized, performance deterioration according to the position and posture of the sleeper The purpose of the present invention is to provide a band-type real-time sleep disorder monitoring device that can be worn on the neck that can deal with a crisis immediately.

In order to achieve the above object, the real-time sleep disorder monitoring device according to the present invention comprises a terminal body formed in a band form so as to be worn on the user's neck; A sensor unit for measuring biometric information including a breathing signal during sleep of a user wearing the terminal body; A stimulus generator for applying a stimulus to a user wearing the terminal body; A terminal control unit which analyzes the biometric information collected by the sensor unit and controls the stimulus generating unit so that a stimulus is applied to the user if the analysis result corresponds to a set stimulus application condition; and a biosignal, its analysis result and stimulus control information, etc. It comprises a terminal storage unit for storing.

In addition, a terminal communication unit for transmitting and receiving data with an external device provided separately from the terminal body; is provided.

The terminal controller may include: a signal processor configured to control preprocessing and storage of the biosignal collected by the sensor unit; an information analyzer configured to analyze the biosignal; and an analysis result of the biosignal and a setting condition of a user Sleep state analysis unit for determining whether the sleep disorder occurs; and Stimulation control unit for controlling the stimulation generating unit in accordance with the determination result of the sleep state analysis unit.

The external device may communicate with the terminal communication unit to receive biometric information and transmit stimulus control information; and a server storage unit to store biosignals, analysis results thereof, and stimulus control information. And a server control unit for generating stimulus control information when the analysis result corresponds to a set stimulus application condition, and an information display unit for producing and providing various types of processed information using data stored in the server storage unit.

According to an embodiment of the present invention, the sensor unit, the stimulus generating unit, the terminal communication unit, the terminal control unit, the terminal storage unit and their detailed configuration functions are all mounted on the terminal body.

According to another embodiment of the present invention, only the central control function of the sensor unit, the stimulus generating unit, the terminal communication unit, and the terminal control unit is mounted on the terminal body, and the signal processing unit, information analysis unit, sleep state analysis unit, and stimulation control unit of the terminal control unit And a storage function of the terminal storage unit is provided in an external device installed separately from the terminal body. That is, the biological information collected by the sensor unit mounted on the terminal body is transmitted to the external device through the terminal communication unit, stored and analyzed, and the stimulus generating unit generates the stimulus according to the stimulus control information received through the terminal communication unit.

The sensor unit is mounted on the inner surface of the main body worn on the user's neck, the breathing signal detection sensor for detecting the user's breathing signal is installed so as to face or contact the user's neck; An oxygen saturation sensor for detecting oxygen saturation in the blood of the user wearing the main body; Electrocardiogram sensor for detecting the electrical activity of the heart of the user wearing the body; preferably includes.

More preferably, the oxygen saturation sensor is applied to be formed on the ear of the user.

In addition, the sensor unit, the jaw muscle conduction sensor for detecting the activity of the user's jaw muscles, the eye conduction sensor for detecting the movement of the user's eye, the arm muscle conduction sensor for detecting the activity of the arm muscles, the activity of the lower extremity muscles At least one or more of the lower extremity EMG sensor, and a motion sensor for measuring body movements and posture information during sleep.

The stimulus generating unit may include at least one of an electrical stimulation unit applying an electrical stimulus, a vibration stimulating unit applying a vibration, and a warning sound unit generating a warning sound.

In addition, the information analysis unit analyzes the signal collected by the respiratory signal detection sensor to determine the respiratory state; and by analyzing the signal collected by the oxygen saturation sensor to calculate the blood oxygen saturation and heart rate Oxygen saturation signal analysis unit; and ECG signal analysis unit for determining the abnormality of the heart by analyzing the electrocardiogram signals collected by the ECG sensor; and the eye movement, bifurcation, this evil by analyzing the signals collected from the EMG sensors EMG signal analysis unit for extracting information on the stiffness of the bite, arm and leg muscles; and a motion signal analysis unit for extracting the motion and posture information of the body during sleep by analyzing the signals collected by the motion sensor .

In addition, the breathing signal analysis unit is provided with a breathing state classifier for discriminating the breathing signal of the user wearing the terminal body to any one of the normal breathing, snoring breathing, apnea, the breathing state classifier is the terminal body Average ratio values, which are relative ratios of average values of power spectrums calculated from each of a plurality of frequency subbands set in a frequency domain of a respiratory signal detected by a user wearing a, and extracted from each of the subbands The type of breathing is determined on the basis of the standard deviation ratio values, which are the relative ratios of the standard deviation values of the calculated power spectrum.

According to the real-time sleep disorder monitoring device worn on the neck according to the present invention, the disadvantages such as the inconvenience of wearing by the many lines of the existing sleep polygraph (PSG) and the expensive cost according to the absolute involvement needs of professionals In particular, real-time monitoring during sleep can induce immediate escape from emergency sleep disorders, which provides the advantage of preventing serious accidents.

In addition, the real-time sleep disorder monitoring device according to the present invention is mounted so that the respiratory signal sensor is in close proximity or contact with the neck, and the respiratory type is based on the relative ratio values of the mean values and standard deviation values of the power spectrum for the respiratory signal By applying the breathing classifier to classify, it is possible to obtain a breathing state determination result that is independent of the change in the intensity of the breathing signal (sound) and is resistant to noise.

1 is a view showing a state in which a real-time sleep disorder monitoring device is mounted on a user, according to an embodiment of the present invention,

FIG. 2 is a block diagram illustrating components of a sleep disorder monitoring device implemented as an example of FIG. 1 and an association therebetween.

3 is a flowchart illustrating an implementation process of a respiratory state classifier mounted in the sleep state monitoring device of FIG. 1;

4 is a flowchart illustrating a real-time respiratory state classification process by the respiratory state classifier obtained by the process illustrated in FIG. 3 and mounted on the respiratory signal signal analysis unit of the information analysis unit of FIG. 2;

FIG. 5 is a view illustrating a sleep state analyzer determining whether sleep disorder occurs in FIG. 2;

6 is a block diagram showing the components of the sleep disorder monitoring apparatus implemented in real time according to another embodiment of the present invention and the connection therebetween.

[Description of the code]

10: terminal body 100: sensor unit

180: stimulation generating unit 210: terminal control unit

230: terminal storage unit 250: terminal communication unit

300: external device

Hereinafter, a real-time sleep disorder monitoring apparatus according to a preferred embodiment of the present invention with reference to the accompanying drawings will be described in more detail.

1 is a view showing a state in which a real-time sleep disorder monitoring device is mounted on a user according to an embodiment of the present invention, Figure 2 shows the major components of the sleep disorder monitoring device of Figure 1 and the relationship between them It is a block diagram.

1 and 2, the real-time sleep disorder monitoring device 1 according to the present invention is the terminal body 10, the sensor unit 100, the terminal storage unit 220, the terminal control unit 210 and the stimulation generator It is composed of 180, it may further include a terminal communication unit 250.

The terminal body 10 is a band form that can be worn on the user's neck, and is provided with a fastening portion such as a loop or a Velcro tape at both ends so that the terminal body 10 can be adjusted in accordance with the length of the neck of the user to be closed in the form of a closed track.

The terminal body 10 is composed of some sensors of the sensor unit 100, the terminal storage unit 220, the terminal control unit 210 and the stimulus generating unit 180, the power supply battery (not shown) and operation A switch (not shown) capable of on / off operation is provided, and a terminal communication unit 250 may be further provided as necessary.

The sensor unit 100 is a breathing signal detection sensor 110, oxygen saturation sensor 120, electrocardiogram sensor 130, in order to measure a variety of biological signals including the breathing signal during sleep of the user wearing the terminal body 10, The EMG sensor 140 and the motion sensor 150 are provided.

The respiratory signal detection sensor 110 is mounted on the inner surface of the terminal body 10 worn on the user's neck so as to face or contact the user's neck in proximity, and is a sensor that detects a sound signal due to the user's breath. For example, a piezoelectric sensor may be used to measure vibrations caused by sound.

When the respiratory signal detection sensor 110 is mounted on the inner surface of the terminal body 10, the area for receiving a sound signal is limited to the neck area of the user, thereby significantly reducing the inflow of external noise, thereby improving the respiratory signal measurement efficiency. In particular, the use of a unidirectional microphone makes the effect more obvious.

Oxygen saturation sensor 120 is a sensor for measuring the oxygen saturation in the blood of the user wearing the terminal body 10, two light emitting elements for emitting red light (for example 660nm) and infrared light (for example 940nm) and light In the embodiment of the present invention, the same type of sensor and the same measuring method as those widely used in pulse oximetery, which are generally applied to the fingertips, can be applied. It is preferable to apply a type (adhesive or tong type) that can be attached to the earlobe close to the band-type terminal body 10.

In addition, the oxygen saturation sensor 120 may be used to measure the heart rate, it is possible to obtain the heart rate by analyzing the periodicity of any one of the two signals collected by the oxygen saturation sensor 120.

ECG sensor 130 is a sensor for measuring the potential change occurring during the relaxation and contraction of the heart muscle of the user wearing the terminal body 10, the patch-type electrode that can be attached to the skin attached to the body and these terminal body ( 10), the number of electrodes used and the attachment location can be determined in consideration of the desired quality level for the ECG signal. In this case, for convenience of wearing, a plurality of ECG sensors 130 may be connected to one relay device for integrated control, and the relay device may be constructed to communicate wirelessly with the terminal body 10.

EMG sensor 140 is a device for measuring the electrical physiological changes generated in the muscle fiber membrane by attaching an electrode to the skin, non-invasive method, EMG signal is used to measure and analyze the activity of the muscle, in the present invention the movement of the tongue , EMG sensor 141 attached to detect the activity of muscles around the jaw to monitor teeth grinding and clenching, and eye conduction attached to the muscles around the eyes to monitor eye movement. A sensor 142, an arm muscle conduction sensor 143 for monitoring the activity of the arm muscles, and a lower leg muscle conduction sensor 144 for monitoring the activity of the lower extremity muscle are applied.

The method of measuring the EMG sensors 140 used is basically the same, but the number of sensors to be applied for each measurement part, the characteristics of the applied electricity, the signal analysis method, and the like are different. In addition, in consideration of the distance between the terminal body 10, the lower extremity EMG sensor 144 is preferably connected to the terminal body 10 wirelessly, the arm muscle conduction sensor 143 also wirelessly with the terminal body 10 Of course, it can be built to be connected.

The motion sensor 150 collects body motion information during sleep, and is provided in the terminal body 10. As a representative example, a gyro sensor and an acceleration sensor may be applied.

The signal collected by the motion sensor 150 is used to extract the information of the wearer's back and sleeping posture during sleep.

The stimulus generating unit 180 applies a stimulus capable of inducing a posture change or escaping from the surface to the user wearing the terminal body 10, the electrical stimulating unit 182 for applying an electrical stimulus, and applying vibration to the user. At least one of the vibration stimulator 184 and the sound stimulator 186 for generating sound.

In addition, the type and intensity of the applied magnetic poles are preferably constructed to be determined by the magnetic pole control unit 219 of the terminal controller 210.

In addition, the stimulus generating unit 180 may be separated from the terminal body 10 and attached to the user's body, and may be connected to the terminal control unit 210 by wire or wirelessly.

The terminal storage unit 220 is a device that stores all the information to be recorded, including the biometric information collected from the sensor unit 100, the terminal storage device 230 such as the terminal body 10 built-in or removable memory card 230 It is desirable to construct a structure that applies).

The terminal controller 210 is mounted on the terminal body 10 as a central control device for controlling the cooperative operation of the functions performed by the components of the present invention, and preprocessing the bio-signal collected by the sensor unit 100. And a signal processor 211 for controlling the storage; and an information analyzer 212 for analyzing the biological signal; and a sleep state analyzer for determining whether a sleep disorder occurs by comprehensively analyzing the analysis result and the user's setting condition ( And a stimulus controller 219 for controlling the stimulus generator 180 according to the judgment of the sleep state analyzer 218.

The signal processor 211 performs preprocessing such as noise reduction and normalization on the signals collected by the sensor unit 100 and stores the signals in the terminal storage device 230 of the terminal storage unit 220.

The information analysis unit 212 is a respiratory signal analysis unit 213 for determining the respiratory state by analyzing the signals collected by the respiratory signal detection sensor 110; and by analyzing the signals collected by the oxygen saturation sensor 120 Oxygen saturation signal analysis unit 214 for calculating blood oxygen saturation and heart rate; and ECG signal analysis unit 215 for determining the abnormality of the heart by analyzing ECG signals collected by ECG sensor 140; and EMG sensor EMG signal analysis unit 216 for analyzing the signals collected from the 140 to extract information about eye movements, limbs, teeth cleavage, stiffness of the arm and leg muscles; and collected by the motion sensor 150 And a motion signal analyzer 217 for analyzing the signal and extracting body motion and posture information during sleep.

The respiratory signal analysis unit 213 includes a respiratory state classifier 213a that determines the respiratory state as one of normal breathing, snoring breathing, and apnea, and provides an apnea-hypopnea index (AHI). Calculate and determine if respiratory disorders occur.

The respiratory state classifier 213a includes an average ratio value that is a relative ratio of average values of power spectrums calculated from each of a plurality of frequency subbands of a respiratory signal detected from a user wearing the terminal body 10, and The type of breath is determined based on the standard deviation ratio values, which are the relative proportions of the standard deviation values of the power spectrum calculated from each of the stations.

Here, the respiratory state classifier 213a is implemented by software in advance by a separate and independent process as shown in FIG. 3, and the implemented respiratory state classifier 213a is the respiratory signal analysis unit 213 of the terminal controller 210. ) Is used to classify a user's respiratory state and determine a breathing disorder in real time by a process as illustrated in FIG. 4.

Hereinafter, an implementation process of the respiratory state classifier 213a will be described with reference to FIG. 3.

First, using the breathing signal detection sensor 110 of the terminal body 10 of the sleep disorder monitoring device 1 collects the breathing signal during sleep from the unspecified majority, and breathing for each breathing period by the auditory examination of the person The type (normal breath, Cocoy, apnea) is indexed and stored in the database (S10).

Next is a signal input for extracting one time segment (T _i ) to be analyzed from a number of signals stored in the database (S10), for example, a signal piece of 100 ms length and inputting it to the respiratory signal analysis unit 213. Step S110, Fourier transform step S120 for converting the input signal to the frequency domain, and N subbands of the frequency domain signal obtained as a result of the Fourier transform (eg, N = 4). A calculation step (S130) of calculating average ratio values of the average values of the power spectrum and the relative ratios thereof, and standard deviation ratio values of the standard deviations of the power spectrum and the relative ratios thereof, and the calculated average ratio values Respiratory state classifier through the classifier learning step (S140) which repeats the learning process so that the true value of the respiratory type for a known signal fragment is output by indexing the values and the standard deviation ratio values. 213a is implemented.

Here, the calculating step (S130) is the average calculation step (S133) for obtaining the average value of the power spectrum of each subband, and the average ratio calculation step (S133) for obtaining the relative ratios between the N average values obtained in the average calculation step (S131). ).

In addition, the calculation step (S130) is a standard deviation calculation step (S135) for obtaining the standard deviation value of each power spectrum for the same subbands, and between the N standard deviation values obtained in the standard deviation calculation step (S135) A standard deviation ratio calculation step (S137) of calculating relative ratios is performed.

For example, when the first subband 50 to 240 Hz, the second subband 400 to 680 Hz, the third subband 800 to 960 Hz, and the fourth subband 1200 to 1600 Hz (N = 4), The number of standard deviation ratio values is 6 by ₄ C ₂ = 6. Therefore, accurately determine the true value (normal breathing, snoring or apnea) for a particular time slice (T _i) is known in advance by the index (index) of time slices (T _i) that when the total is 12 ratio values are input obtained from To perform the process of learning the respiratory state classifier 213a.

This repetition by the signals of the respiratory status classifier implementation infinitely many times a piece of (213a) (T _i) being to implement a more accurate respiratory status classifier (213a).

In addition, the number and frequency range of the subbands applied for respiratory signal type determination in the respiratory state classifier 213a are not limited to the examples, and the sampling rate and the accuracy of the discrimination applied to the digitization process of the signal are illustrated. This may vary depending on how the subbands contain a large amount of information for improvement.

In addition, the respiratory state classifier 213a that can be applied to the present invention may be any of the classifiers commonly known in mathematics, statistics, or artificial intelligence (eg, crystal trees, regression, Bayesian classifiers, fuzzy, neural networks, etc.). Although it is not specified here, a difference in the accuracy of the learning method and the discrimination may occur according to the selected classifier.

The respiratory state classifier 213a, which is implemented in software through such a learning process and mounted on the terminal control unit 210 as an application program, is based on the respiratory type based on the relative ratio values of the average values of the power spectrum and the standard deviation values for the respiratory signals. By classifying, we can obtain the results of respiratory state determination that is independent of the change in the intensity of the respiratory signal and is resistant to noise.

Hereinafter, the respiratory state classification process for the respiratory signal input in real time by applying the respiratory state classifier 213a implemented by FIG. 3 will be described with reference to FIG. 4.

The respiratory state classifier 213a implemented through the learning process shown in FIG. 3 is mounted on the respiratory signal analysis unit 213 of the terminal control unit 210 and is in real time according to the process illustrated in FIG. 4. Snoring, or apnea), this process is similar to the classifier implementation process of Figure 3 but the breathing signal obtained in real time from the user wearing the terminal body 10 instead of the breathing signal stored in the database (S10) signal input It is provided in step S110, in the respiratory state classifier step (S240) is determined by the respiratory state classifier 213a to determine the type of breathing. In this case, intermediate processes such as the signal input step S110, the Fourier transform step S120, and the calculation step S130 are the same as those in FIG. 3.

This real-time breathing state classification process is carried out for the time pieces continuously input, the breathing signal analysis unit 213 performs the breathing state determination step (S310) shown in Figure 5 based on the respiratory state information accumulated for a certain time Analyzing whether a respiratory disorder occurs for a certain time duration (for example, 10 seconds), and performing the AHI calculation step (E100) to calculate the apnea and low respiratory index (AHI).

At this time, the determination of whether apnea is generated by the respiratory state determination step (S310) and the calculation of apnea and low respiratory index (AHI) by the AHI calculation step (E100) is performed by a professional institution (eg, ACP, American College of Physicians or It is preferable to follow the standards recognized by AASM (American Academy of Sleep Medicine). For example, if apnea is maintained for 10 seconds or more, it is determined that apnea occurs and the number of apneas generated during an hour is defined as an AHI value.

On the other hand, the terminal control unit 210 is a sleep state and sleep disorder by the sleep state analysis unit 218 by using the analysis results of the biometric information collected from the remaining sensors of the sensor unit 100 as well as the breathing state determination information. It is constructed to judge the occurrence.

The oxygen saturation signal analysis unit 214 analyzes the signal measured by the oxygen saturation sensor 120 to calculate blood oxygen saturation and heart rate. The signal collected by the oxygen saturation sensor 120 represents the light absorption of two different wavelengths (red light and infrared light) obtained by passing or reflecting blood of the body, and the ratio of the pulsating component obtained from the two light absorption The method of obtaining oxygen saturation in blood by non-invasive method is generally applied. More specifically, red light is more absorbed by deoxygenated hemoglobin (Hb), which is not bound to oxygen, and infrared light is more absorbed by oxygenated hemoglobin (HbO2), which is bound to oxygen. Calculate oxygen saturation in the blood according to Equation 1 below using the absorbance.

In addition, the oxygen saturation signal analysis unit 214 calculates a heart rate value by detecting the periodicity of any one of the two light absorption signals, and the number of times the oxygen saturation in blood per hour is lowered to 3% or less of the reference value. It may be configured to perform the ODI calculation step (E200) for calculating the oxygen desaturation index (ODI, defined as).

The electrocardiogram signal analysis unit 215 may be constructed to detect cardiac diseases such as myocardial disease, reflux disease, arrhythmia, etc. by analyzing and interpreting the electrocardiogram signal collected from the electrocardiogram sensor 130. However, according to an analysis and interpretation method of the waveforms between the P, Q, R, S, and T points of the ECG, which are widely known, they may be implemented to detect an emergency symptom and a heart disease. In addition, the heart rate may be calculated using the periodicity of the waveform.

The EMG signal analyzing unit 216 analyzes and acquires signals obtained from the jaw EMG sensor 141, the ocular conductivity sensor 142, the EMG sensor 143, and the EMG sensor 144 constituting the EMG sensor 140. It may be configured to be interpreted, and may be embodied by an analysis and interpretation method of EMG for each site, which is not specific to the present invention but is generally known.

The motion signal analysis unit 217 extracts information about the body's overturning and posture during sleep based on the signals collected from the motion sensor 150. In the present invention, a method of analyzing and interpreting the motion signal is not specified, but may be implemented by a conventionally known method according to the attachment position and the purpose of the motion sensor 150.

The sleep state analysis unit 218 comprehensively analyzes the results collected by the various sensors of the sensor unit 100 and analyzed for each signal by the information analyzer 212 to determine whether a sleep disorder occurs and a sleep stage. Can be constructed to This integrated decision is based on recognized standard criteria, but the criteria may be adjusted according to the choice of the implementer and the user.

Hereinafter, an example of a sleep disorder occurrence and a sleep stage determination by the sleep state stones 218 will be described with reference to FIG. 5.

The sleep state analyzer 218 analyzes the oxygen saturation signal signal from the breathing signal analyzer 213 for information on a respiratory state, a respiratory disorder, and AHI for a predetermined time duration (for example, 10 seconds). Real-time oxygen saturation value, heart rate and ODI information from the unit 214; information on heart abnormality signs and heart rate from the ECG signal analyzer 215; eye movement information, splitting, and the like from the EMG signal analyzer 216. Information about the clenching information, the rigidity of the arm and the leg, and the like; information about the body torsion and posture from the motion signal analyzer 150;

Subsequently, the sleep state analyzer 218 determines whether or not the sleep disorder occurs and the type of the disorder based on a criterion generally applied by the input information or a criterion set by the operator or the user.

If the result determined by the sleep state analyzer 218 corresponds to the stimulus application condition set by the operator or the user, the stimulus controller 219 may include the electrical stimulator 182 and the vibration stimulator 184. And stimulus control information (stimulus applied, stimulus type, stimulus intensity) so that at least one of the sound stimulators 186 can be operated. The stimulus application condition may be set in various rules according to the type and emergency of sleep disorders, and the type and intensity of stimuli applied according to each condition may be applied differently.

As an example of application of the stimulus, when the determination result is simply snoring that continues for a long time, the vibration stimulation unit 184 is operated to apply a one-step vibration suitable for the degree of inducing posture change while maintaining the sleeping state. Of course, the electrical stimulation unit 182 may be operated to apply the fine electrical stimulation.

In another stimulus application example, if apnea is maintained for 10 seconds and blood oxygen saturation is determined to be less than 85%, a vibratory stimulus of considerable intensity is applied by the vibratory stimulator 184, and nonetheless the sleep disorder is eliminated within a certain time. If not, the electrical stimulation unit 182 is driven to apply a significant level of electrical stimulation that can escape from the water surface.

In another example, when it is determined that the heart rate and the intensity of the electrocardiogram signal are significantly lowered, the sound stimulator 186 is driven to generate a strong sound having a perceivable intensity.

Alternatively, pre-establish a list of scores for each type of disability and level of disability that may occur, add the scores of disabilities generated at a specific time to assess risk levels, and determine whether they are irritating according to the level. And a stimulus control unit 219 to determine the type of stimulus and the intensity of the stimulus.

The stimulus applying condition set in the stimulus control unit 219 may be set in various manners other than the exemplary condition described above.

In addition, the information related to the generation of the stimulus may be stored in the terminal storage unit 220 may be used for history management.

The terminal communication unit 250 is a device selectively mounted on the terminal body 10 and provides a communication means for transmitting and receiving data with the outside of the terminal body 10.

In another embodiment of the present invention, the terminal body 10 with the capacity of the same battery in a manner that is constructed to mitigate the computational processing burden of the terminal body 110 required for the processing and analysis of the biological signal and the sleep state analysis. The long operation time of, the configuration of the terminal body 10 is very simplified, and the analysis speed is provided with the advantage of being very high. An example thereof will be described with reference to FIG. 6. Elements that perform the same function as in the drawings of the foregoing embodiment are denoted by the same reference numerals.

Referring to FIG. 6, all of the analysis and calculation functions of the terminal controller 210 of the terminal body 10 shown in FIG. 2 are mounted as the same function in the server controller 320 of the external device 300, and the terminal controller 210 is included. Performs only a central control function for the cooperative operation of the components of the terminal body (10). In addition, the terminal storage device 230 shown in FIG. 2 may not be included in the terminal body 10.

The external device 300 is a server communication unit 310 for performing a wired or wireless communication with the terminal communication unit 250 of the terminal body 10; and the linked operation of the functions performed by the components of the external device 300 The server controller 320 performs the same analysis and calculation functions of the central controller device and the terminal controller 210 to control the control unit; and all information to be recorded, including biometric information collected from the sensor unit 100. It includes a server storage unit 330 to be stored; and an information display unit 340 for providing a means of viewing and reporting the stored information.

The signals collected by the sensor unit 100 are transmitted to the server communication unit 310 through the terminal communication unit 250, stored in the server storage unit 330, and analyzed by the server control unit 320. In this case, the signal analysis function performed by the server controller 320 is the same as the function of the terminal controller 210.

The stimulus control information finally obtained by the stimulus control unit 219 of the server control unit 320 is transmitted to the terminal body 10 through the server communication unit 310 and a stimulus is applied by the stimulus generating unit 180.

The server storage unit 330 stores in the server storage device 335 all information to be recorded, including the biosignal and its analysis information, sleep disorder occurrence, and stimulus control information.

The information display unit 340 is built to provide reports and historical information including graphs, tables, and numerical values using data from the server storage unit 330, and these reports and historical information may be used to receive expert analysis. Can be.

According to the real-time sleep disorder monitoring device 1 described above, it is possible to induce immediate escape from an emergency sleep disorder through the convenience of wearing, and real-time monitoring during sleep provides an advantage of preventing a serious accident.

In addition, the real-time sleep disorder monitoring device 1 according to the present invention is equipped with a breathing signal detection sensor 110 to be in close contact or contact with the neck inside the band-type terminal body 10 to be worn on the neck to prevent external noise inflow By minimizing the classification of breaths based on the mean values of the power spectrum and the relative ratios of the standard deviations to the breathing signals, it is possible to obtain a breathing state determination result that is independent of changes in the intensity of the breathing signals and is resistant to noise.

In addition, the present invention functions the terminal control unit 210 or the server control unit 320, the computer program for determining whether the breathing signal detected by the breathing signal detection sensor 110 is normal breathing, snoring breathing or apnea Can provide more.

The computer program may further include average ratio values, which are relative ratios of average values of power spectrums calculated from each of a plurality of frequency subbands set in the frequency domain, and power spectrums calculated from each of the frequency subbands. The type of breath is determined on the basis of the standard deviation ratio values, which are the relative proportions of the standard deviation values of.

Since the detailed determination method has been described above with reference to FIG. 4, it will be omitted.

In addition, the computer program may be stored and provided in a separate recording medium, and the recording medium may be those specially designed and configured for the present invention or be known and available to those skilled in the computer software field. .

For example, the recording medium may be magnetic media such as hard disks, floppy disks and magnetic tape, optical recording media such as CDs and DVDs, magnetic-optical recording media capable of both magnetic and optical recording, ROM, RAM, flash memory. Etc. may be a hardware device specifically configured to store and execute program instructions, alone or in combination.

In addition, the computer program may be a program consisting of program instructions, local data files, local data structures, and the like, alone or in combination, and may be executed by a computer using an interpreter as well as machine code such as produced by a compiler. It can be a program written in high-level language code.

The present invention may further provide a computer device in which the computer program is stored to determine the type of breathing. The computer device is a computer device of a broad scope including not only a general personal computer but also an embedded system and a smart device.

The present invention may further provide a server computer device having a storage medium in which the computer program is stored and a communication medium capable of transmitting the computer program stored in the storage medium to a client computer device via a communication network.

That is, the client computer device may download the computer program from the server computer device and perform a breath type determination.

The real-time sleep disorder detection apparatus of the present invention can be utilized in the medical field because the user can immediately escape from the sleep disorder in the event of an emergency while seriously monitoring the factors associated with the sleep disorder to perform serious accident prevention.

Claims

A terminal body formed in a band shape to be worn on a user's neck;

A sensor unit for measuring biometric information including a breathing signal during sleep of a user wearing the terminal body;

A stimulus generator for applying a stimulus to a user wearing the terminal body;

And a terminal controller configured to control the stimulus generator so that the stimulus is applied to the user when the biometric information collected by the sensor corresponds to a set stimulus application condition.
The method of claim 1, wherein the terminal control unit

Analyze the biological information collected from the sensor unit, and if the analysis result corresponds to the set stimulus application condition is configured to control the stimulus generating unit so that the stimulus is applied to the user,

And a terminal storage unit configured to store biometric information collected from the sensor unit, analysis results thereof, and stimulus control information.
The apparatus of claim 1, further comprising a terminal communication unit configured to transmit biometric information collected from the sensor unit to an external device provided separately from the terminal body, and to receive stimulus control information from the external device.

The external device

A server communication unit which communicates with the terminal communication unit to receive biometric information and transmits stimulus control information to the terminal communication unit; and

A server storage unit for storing the biometric information received through the server communication unit, analysis results thereof, and stimulus control information; and

A server controller which analyzes the biometric information and generates stimulus control information when the analysis result corresponds to a set stimulus application condition; and

And an information display unit for producing and providing processed information of a set type using the data stored in the server storage unit.
According to claim 2 or 3, wherein the sensor unit

A breathing signal detecting sensor mounted on an inner surface of the terminal body worn on the user's neck so as to face or contact the neck of the user and detecting a breathing signal of the user;

An oxygen saturation sensor for detecting oxygen saturation in the blood of the user wearing the terminal body;

Real-time sleep disorder monitoring device comprising a; electrocardiogram sensor for detecting the electrical activity of the heart of the user wearing the terminal body.
The apparatus of claim 4, wherein the oxygen saturation sensor is formed to be worn on the ear of a user.
The method of claim 4, wherein the sensor unit

Jaw EMG sensor to detect the activity of the mandible lower jaw muscles, Eye conduction sensor to detect the movement of the user's eye, Arm EMG sensor to detect the activity of the arm muscles, Lower limb EMG to detect the activity of the lower extremity muscles And at least one or more of a sensor and a motion sensor for detecting body motion and posture information during sleep.
The method of claim 1, wherein the stimulation generating unit

And an electrical stimulation unit for applying an electrical stimulus, a vibration stimulation unit for applying a vibration, and a sound stimulation unit for generating sound.
The method of claim 6, wherein the terminal control unit or the server control unit

A signal processor for controlling preprocessing and storage of the biosignal collected by the sensor unit; and

An information analyzer for analyzing the bio-signals; and

A sleep state analysis unit which determines whether a sleep disorder occurs by comprehensively analyzing a result of analyzing the biosignal and a user's setting condition; and

And a stimulus controller for controlling the stimulus generator according to the determination result of the sleep state analyzer.
The method of claim 8, wherein the information analysis unit

Respiratory signal analysis unit for determining the respiratory state by analyzing the signal collected by the respiratory signal detection sensor; And

Oxygen saturation signal analysis unit for calculating the blood oxygen saturation degree and heart rate by analyzing the signal collected by the oxygen saturation sensor; And

An electrocardiogram signal analysis unit for determining an abnormality of the heart by analyzing the electrocardiogram signal collected by the electrocardiogram sensor; and

EMG signal analysis unit for extracting information on the movement of the eye movements, splitting, teeth cleavage, arm and leg muscles by analyzing the signals collected from the EMG sensors; And

And a motion signal analysis unit for analyzing the signals collected by the motion sensor and extracting motion and posture information of the body during sleep.
The method of claim 9, wherein the respiratory signal analysis unit

There is provided a respiratory state classifier that determines the type of respiration by any one of the normal breathing, snoring breathing, apnea as the breathing signal of the user wearing the terminal body,

The respiratory state classifier

Average ratio values, which are relative ratios of average values of power spectrums calculated from each of a plurality of frequency subbands set in a frequency domain, with respect to a breathing signal detected from a user wearing the terminal body, and calculated from each of the frequency subbands. And a respiratory type is determined based on standard deviation ratio values which are relative ratios of the standard deviation values of the power spectrum.
A computer program stored in a medium for determining whether a breathing signal detected from a user wearing the terminal body is normal breathing, snoring breathing or apnea by acting as a terminal control unit of a real-time sleep disorder detecting device according to claim 1,

The computer program comprises average ratio values which are relative ratios of average values of power spectrums calculated from each of a plurality of frequency subbands set in the frequency domain with respect to the respiration signal, and a standard of power spectrums calculated from each of the frequency subbands. A computer program stored in a medium, characterized in that the type of respiration is determined based on standard deviation ratio values, which are relative ratios of deviation values.
A computer device in which the computer program of claim 11 is stored.
The method of claim 12,

The computer device receives a user's breathing signal from the real-time sleep disorder monitoring device through a communication network, and functions by the computer program to determine whether the breathing signal is normal breathing, snoring breathing or apnea. .
A storage medium storing the computer program of claim 10; And

And a communication medium capable of transmitting the computer program stored in the storage medium to a client computer device via a communication network.