KR20180042719A - Apparatus and method for analyzing respiration - Google Patents

Abstract

An apparatus for analyzing respiration is disclosed. The apparatus includes a photo-plethysmography sensing part for receiving a pulse wave of a user, removing noise, extracting a desired band signal, and digitally converting the signal; and an abnormal breathing recognition part which extracts a respiration rate signal from an optical pulse wave signal sensed by the photo-plethysmography sensing unit, calculates a current respiration rate characteristic value of the user, and compares the value with a respiration rate characteristic reference value. According to the apparatus for analyzing respiration of the present invention, sleep apnea syndrome can be effectively recognized.

Description

[0001] APPARATUS AND METHOD FOR ANALYZING RESPIRATION [0002]

The present invention relates to a respiration analyzing apparatus and method, and more particularly, to a respiration analyzing apparatus and method for detecting abnormal breathing or apnea in a sleep state.

As the quality of life increases due to the increase in income, various self-health screening methods using mobile devices such as smart bands and pads have been increasing recently. Snoring and sleep apnea, which have the greatest effect on sleep quality, cause fatigue in daily life due to inadequate oxygen supply, which reduces the efficiency of learning and work, leading to the cause of safety accidents such as industrial accidents and traffic accidents , Which can lead to cardiovascular activity and insufficient brain activity due to insufficient oxygen supply in the body.

Sleep Apnea is a phenomenon in which breathing stops temporarily during sleep. Sleep Fragmentation due to sleep apnea is caused by Excessive Daytime Sleepiness (EDS) and SpO2 (Peripheral) Capillary Oxygen Saturation). Decreased oxygen saturation leads to hypertension, arrhythmia, and in severe cases can lead to heart attack (Sudden Death), and so on.

Sleep apnea includes central apnea, which is classified as a neurological disorder that stops all respiratory effort, and obstructive apnea, which stops breathing repeatedly during sleep due to obstruction or collapse of the airway, and central obstructive sleep apnea There is a kind of mixed apnea (Mixed Apnea). Obstructive and mixed apnea wake up with breathing effort during sleep.

Sleep apnea is an electrocardiogram (ECG) for examining arrhythmias that may occur clinically as apneas, an electro-encephalogram (EEG) to distinguish the brain's sleep and arousal status, a safety (EOG) (EMG: Electro-Myogram), and the measurement of blood oxygen saturation during apnea, nasal and oral air flow to determine the types of apnea such as central or obstructive apnea, (PSG: Ploysomnography), which measures objectively the stages and functions of sleep, and the events that may occur during sleep, by measuring the movement of the abdomen and measuring the sleep posture and blood pressure.

The sleeping polygraph is a relatively accurate diagnostic method for diagnosing sleep quality, but it is expensive and requires a skilled workforce. Unlike sleep polyvalence test, which is demanded with high proficiency and price, a variety of bio-signal measuring devices such as a user's pulse have been developed due to the development of smart devices in recent years, but they are staying as devices for simple bio-signal measurement and use measured bio- Therefore, it can be said that the application service such as self-diagnosis of inexpensive sleeping is necessary in the user's familiar environment.

SUMMARY OF THE INVENTION It is an object of the present invention to provide a respiration analysis method capable of detecting sleep apnea through frequency analysis.

It is another object of the present invention to provide a respiration analyzer using the respiration analysis method.

According to an aspect of the present invention, there is provided a respiration analyzing apparatus including an optical pulse-wave-sensing unit for receiving a user's pulse wave to remove noise, extracting a signal of a required band and converting the signal into a digital signal, And an abnormal respiration detection unit for detecting abnormal respiration by comparing the respiration rate feature value of the current user with the respiratory rate feature standard value by extracting the respiration rate signal from the optical pulse signal of the pulse sensed by the pulse wave sensing unit.

Wherein the abnormal respiration detection unit obtains a respiration rate signal by performing band filtering of a respiration frequency band on the optical pulse wave and calculates a ratio of a frequency component intensity of the interest region to a frequency component intensity of the non- Thereby calculating the respiratory rate characteristic value.

Here, the region of interest according to the present invention may be a band of 0.2 Hz to 0.3 Hz, and the region of interest may be a band of 0 Hz to 0.19 Hz.

In addition, the respiratory rate characteristic reference value may be a respiration rate characteristic average value, and the respiratory characteristic average value may be set as an arithmetic average or moving average value of the respiratory rate characteristic value calculated plural times for a certain time interval for normal breathing.

If the current user's respiration is determined to be abnormal breathing, the abnormal breathing detection unit may determine the type of abnormal breathing based on the current breathing rate characteristic value.

Meanwhile, the respiration analyzing apparatus according to the present invention may take a form that can be worn on a part of the user's body, for example, a form that can be worn on the user's wrist.

In addition, the optically positive pulse-wave sensing unit may include: a sensor that generates an optical signal and senses a received optical signal reflected from a user's body; a band elimination filter that eliminates unnecessary noise bands from the sensed signal; A band pass filter that performs band pass filtering of the pulse signal band for the signal, and an analog-to-digital converter that performs a digital conversion on the filtered signal.

Detectable abnormal breathing according to the present invention includes at least one of obstructive apnea, mixed apnea, and central apnea.

The abnormal respiration detection unit may further include a recognition result output unit for outputting a recognition result of abnormal breathing.

According to another aspect of the present invention, there is provided a respiration analyzing method comprising the steps of sensing an user's pulse wave to remove noise, extracting a desired band signal and converting the signal into a digital signal, Extracting a respiration rate signal from the sensed optical pulse wave signal and frequency-converting the respiration rate signal; and calculating a respiration rate characteristic value from the frequency-converted respiration rate signal and comparing the respiration rate characteristic value with a respiration rate characteristic reference value.

Here, the respiration rate signal may be obtained by performing band filtering of the respiration frequency band with respect to the optical pulse wave signal.

In addition, the step of detecting abnormal breathing may include calculating a respiratory rate characteristic value by calculating a ratio of a frequency component intensity of a region of interest to a frequency component intensity of a non-interest region in the frequency-converted respiration rate signal .

The step of detecting the abnormal breathing may further include the step of determining the type of abnormal breathing according to the current breathing rate characteristic value if the breathing of the current user is determined to be abnormal breathing.

According to the embodiment of the present invention as described above, information or an alarm can be provided so as to promptly grasp a breathing abnormality of a user and prepare for an emergency situation.

In addition, the respiration analyzer according to the present invention is provided in a non-invasive manner in a form that can be easily mounted on a part of a user's body such as a wrist, thereby providing convenience to a user.

The apparatus and method for analyzing respiration according to the present invention can be effectively used for the determination of sleep apnea.

1 is a block diagram of a respiration signal analysis apparatus according to an embodiment of the present invention.
FIG. 2 is a configuration diagram of an optically-usable pulse-wave sensing unit according to an embodiment of the present invention.
FIG. 3 is a graph of a bio-signal response of obstructive apnea, which is one of abnormal breathing.
FIG. 4 is a graph showing a bio-signal response of central apnea, which is one of the abnormal breaths.
FIG. 5 is a graph showing the time axis of the chest breathing motion signal, respiration rate signal, and optical pulse wave signal.
6 is a graph showing an example of a frequency analysis result of a respiration rate signal according to the present invention.
7 is a graph showing another example of the frequency analysis result of the respiration rate signal according to the present invention.
8 is a schematic flowchart of a respiration analysis method according to the present invention.
FIG. 9 is a detailed flowchart of a method for deriving a reference value for use in abnormal respiration detection according to the present invention.
FIG. 10 is a detailed flowchart of the abnormal breath detection method using the frequency analysis according to the present invention.

The present invention is capable of various modifications and various embodiments, and specific embodiments are illustrated in the drawings and described in detail with reference to the drawings. It should be understood, however, that the invention is not intended to be limited to the particular embodiments, but includes all modifications, equivalents, and alternatives falling within the spirit and scope of the invention. Like reference numerals are used for like elements in describing each drawing.

The terms first, second, A, B, etc. may be used to describe various components, but the components should not be limited by the terms. The terms are used only for the purpose of distinguishing one component from another. For example, without departing from the scope of the present invention, the first component may be referred to as a second component, and similarly, the second component may also be referred to as a first component. The term "and / or" includes any combination of a plurality of related listed items or any of a plurality of related listed items.

It is to be understood that when an element is referred to as being "connected" or "connected" to another element, it may be directly connected or connected to the other element, . On the other hand, when an element is referred to as being "directly connected" or "directly connected" to another element, it should be understood that there are no other elements in between.

The terminology used in this application is used only to describe a specific embodiment and is not intended to limit the invention. The singular expressions include plural expressions unless the context clearly dictates otherwise. In the present application, the terms "comprises" or "having" and the like are used to specify that there is a feature, a number, a step, an operation, an element, a component or a combination thereof described in the specification, But do not preclude the presence or addition of one or more other features, integers, steps, operations, elements, components, or combinations thereof.

Unless defined otherwise, all terms used herein, including technical or scientific terms, have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs. Terms such as those defined in commonly used dictionaries are to be interpreted as having a meaning consistent with the contextual meaning of the related art and are to be interpreted as either ideal or overly formal in the sense of the present application Do not.

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

1 is a block diagram of a respiration signal analysis apparatus according to an embodiment of the present invention.

1, an apparatus for analyzing a respiration signal according to an exemplary embodiment of the present invention may include an optical volume pulse wave sensing unit 100, an ideal respiration recognition unit 200, and a recognition result output unit 300 have.

The optical pulse-wave-sensing unit 100 receives a user's pulse wave to remove noise, extracts a signal of a required band, and converts the signal into a digital signal, thereby sensing the optical pulse wave.

The optical pulse-wave-sensing unit 100 includes a light-emitting element and a light-receiving element, and the optical signal emitted from the light-emitting element is reflected by the wrist and sensed using the light-receiving element.

Photo-plethysmography (PPG) is a signal that measures changes in the blood component density (hemoglobin, etc.) in blood vessels according to heartbeat, using light absorption, reflection, and scattering. And the blood flow is measured using the absorption rate of light that is absorbed or reflected by the blood vessel. When the light is irradiated on the human body, the degree of transmission of light is changed by the change of the density of the blood. Since the amount of change is due to the blood flow, the pulse wave is measured using this phenomenon.

The ideal respiration recognition unit 200 calculates the respiration rate from the sensed pulse wave signal and performs the abnormal breath detection algorithm according to the present invention. Here, the apnea detection algorithm according to the present invention is based on frequency analysis.

The perceived result through the abnormal breathing recognition unit 200 is transmitted to the recognition result output unit 300. The recognition result output unit 300 may include an interface for outputting or transmitting the abnormal breathing result.

The abnormal respiration detection apparatus according to the present invention, which may include a configuration as shown in FIG. 1, extracts a respiration intensity induced variable (RIIV) signal from an optical pulse signal of the wrist to detect abnormal breathing of a user . In particular, the present invention can be effectively utilized to detect apnea of a user in a sleep state.

In the present invention, by analyzing the characteristic that the strength of the frequency component decreases in the apnea when the respiration rate is lower than that of normal breathing, which is usually 0.2 Hz to 0.3 Hz (breathing frequency 12 times / minute to 18 times / minute) Respiration or apnea.

FIG. 2 is a configuration diagram of an optically-usable pulse-wave sensing unit according to an embodiment of the present invention.

The optical pulse voltage sensing unit 100 according to an exemplary embodiment of the present invention includes optical pulse pulse sensors 160 and 110 for measuring a user's optical pulse voltage, a voltage / current conversion amplifier 120, a band elimination filter 130 A bandpass filter 140, an analog-to-digital converter (ADC) 150, and an optical output controller 170.

The optical pulse wave sensor may include a light emitting element 160 and a light receiving element 110. The light emitting element 160 may be a light emitting diode (LED), and the light receiving element 110 may be a light receiving diode . The light emitting diode generates light having a band of a certain wavelength, and examples of the wavelengths to be generated include 535 nm, 660 nm and 940 nm.

The optical pulse-wave-sensing unit 100 may further include a light-emitting diode driver for operation and control of the optical pulse-wave sensor.

Meanwhile, the optical output controller 170 plays a role of controlling the light amount of the light emitting diode, and may take the form of a digital-to-analog converter (DAC).

A signal emitted from the light emitting element and reflected from the wrist is received through the light receiving element 110 and is output in the form of a current and converted into a voltage signal through the current / voltage converter 120.

The signal output from the current / voltage converter 120 is processed through the band elimination filter 130, the band pass filter 140 and the analog-to-digital converter 150 and is transmitted to the abnormal respiration recognition unit 200.

The band elimination filter 130 removes 50 Hz or 60 Hz power frequency signals from the input signal and the bandpass filter 140 filters the input signals from approximately 50 BPM (beats per minute) It passes only the frequency band of 0.1 Hz to 1.2 Hz signal including pulse. The band-pass filtered signal is converted to a digital signal via an analog-to-digital converter (150).

The optical pulse signal converted into the digital signal is transmitted to the ideal respiration recognition unit 200 and the ideal pulse recognition method according to the present invention is performed on the transmitted optical pulse signal.

FIG. 3 is a graph of a bio-signal response of obstructive apnea, which is one of abnormal breathing.

Obstructive apnea is one of various abnormal respirations that can be detected by the respiratory signal sensing apparatus according to the present invention.

Obstructive sleep apnea (OSA) is a more common behavior than the Central Sleep Apnea (CSA) in which the diaphragm itself does not exercise and breathing is interrupted, It is a common symptom.

During sleep, the muscles of the body usually become less relaxed, and the airways become dilated, causing sleep apnea. Although many people experience temporary or intermittent symptoms of obstructive sleep apnea, fewer people experience severe chronic obstructive sleep apnea.

3, respiration accompanied by obstructive sleep apnea is repeated in a first interval 301 and a second interval 302 at an arbitrary interval, and a first interval 301, which is an abnormal breathing or apnea interval, is repeated. The signal characteristics of NAF, RC, and Abd in the second section 302 are different from those of the second section 302, which is the normal breathing section.

Here, the NAF (Nasal airflow) signal represents the nasal air flow, the Ribcage respiratory movement (RC) signal represents the thoracic respiratory motion, and the Abd (abdominal respiratory movement) signal represents the abdominal respiratory motion.

In the first section 301 of the abnormal breathing zone, respiratory movement of the chest and abdomen occurs due to the breathing motion signal of the brainstem respiration center, but air flow of the nasal cavity is blocked. In other words, in the obstructive apnea signal, the air flow in the nasal cavity is blocked although there is breathing effort in the first chest and abdomen.

FIG. 4 is a graph showing a bio-signal response of central apnea, which is one of the abnormal breaths.

The graph of FIG. 4 showing a bio-signal of central obsessive-compulsive disorder also repeats the first interval 401 and the second interval 402, which are abnormal breathing intervals, at regular intervals.

In the bio-signal response graph according to the central apnea syndrome shown in FIG. 4, it can be seen that there is no air flow of the nasal cavity and the breathing motion of the thoracic cavity and the abdominal cavity due to the non-occurrence of the breathing motion signal of the brainstem respiratory center. In other words, the signal due to central apnea is in the state of no breathing effort.

The abnormal breaths shown in FIGS. 3 and 4 are merely examples of ideal breaths to be sensed in the present invention, and the range of ideal breaths to be sensed by the present invention is not limited thereto.

FIG. 5 is a graph showing the time axis of the chest breathing motion signal, respiration rate signal, and optical pulse wave signal.

The thoracic respiratory motion signal (a) shown in FIG. 5 is a signal actually measured using a 12-minute commercial breath measurement system (BIOPAC Systems Inc. MP150, RSP100C).

5 (c) is a signal output from the optically positive pulse-wave sensing unit 100 according to the present invention, and the respiration rate signal indicated by (b) represents a respiration rate signal calculated according to the present invention .

Referring to the graph of FIG. 5, the normal breathing period 502 shows a respiration rate signal having a regular cycle and a peak-to-peak value. On the other hand, the athletic breathing signal (a) and the breathing rate signal (b) in the ideal breathing periods 501-1 and 501-2, for example, the apnea interval in which obstructive apnea occurs, It can be confirmed that the regularity of the period and the floor-bone difference value are very irregular compared to the respiratory motion signal and the respiration rate signal calculated at the normal breathing.

In the present invention, abnormal breathing such as apnea is recognized by analyzing the characteristics of the apnea interval in which the irregularity degree of the period and floor-bone difference value becomes larger than the normal breathing interval.

In the present invention, the respiration rate signal is analyzed on the frequency axis to detect abnormal breathing.

FIG. 6 is a graph showing an example of a frequency analysis result of a respiration rate signal according to the present invention, and FIG. 7 is a graph showing another example of a frequency analysis result of a respiration rate signal according to the present invention.

FIG. 6 shows frequency components for each of the normal respiration period 601 and the abnormal respiration period 602 of the respiration rate signal extracted and calculated for a predetermined time of 15 seconds.

The frequency components of the normal breathing interval and the abnormal breathing interval in the range of 0.2 Hz to 0.3 Hz in the graph of FIG. 6 indicate that the intensity of the respiration rate signal in the normal breathing interval 601 is larger than the abnormal breathing interval 602 .

FIG. 7 shows frequency analysis results of a respiration rate signal in an arbitrary 15-second time interval different from that in FIG. 6, and frequency components of the normal breathing interval 701 and the abnormal breathing interval 702 are compared. It can be seen that the intensity of the respiration rate signal in the normal breathing interval 701 is larger than that in the abnormal breathing interval 702 in the range of 0.2 Hz to 0.3 Hz.

FIG. 8 is a schematic flowchart of the respiration analysis method according to the present invention.

As shown in FIG. 8, the respiratory analysis method according to the present invention first receives optical pulse waves through a respiration analyzer worn on a wrist or the like (S810), performs band elimination and bandpass filtering on the received signals The noise signal is removed (S820). The signal thus processed is subjected to digital conversion (S830), frequency conversion is performed on the digitally converted signal, and a respiration rate signal is derived through bandpass filtering which filters only the respiration frequency component band (S840).

Here, the respiration rate signal is extracted from the sensed optical pulse wave signal, that is, the preliminary processed and digitally converted optical pulse wave signal, for the respiratory frequency component of 0.2 Hz to 0.3 Hz (12 times / minute to 18 times / minute) Pass digital filtering.

For the respiration rate signal, the frequency analysis according to the present invention is performed (S850), and it is determined whether the user's respiration is an abnormal respiration using the respiration rate characteristic value as a frequency analysis result (S860). Here, abnormal breathing includes obstructive apnea, central apnea, mixed apnea, and the like, and may include abnormal respiration of various symptoms.

If it is determined that the abnormality is an abnormal breath and if the abnormal breath is any kind of abnormality, the determination result is output (S870). As a result of the determination, the output may be displayed and provided to the user or may be transmitted to a control device separate from the respiration analysis device.

FIG. 9 is a detailed flowchart of a method for deriving a reference value for use in abnormal respiration detection according to the present invention.

What is to be derived through the method shown in FIG. 9 is a reference value used for abnormal breath detection, and therefore, the object of breathing for deriving the reference value is normal breathing. If the present invention is applied to abnormal breath detection at the time of sleep, normal breathing at this time may be normal breathing during sleeping.

Also, the reference value of FIG. 9 is compared with the respiratory rate feature value derived as a result of the frequency analysis value of the current respiration rate signal through the frequency analysis step of FIG. That is, the reference value derived from FIG. 9 is a value utilized in step 860 of FIG.

In order to derive a reference value used for abnormal breath detection, first, a variable n indicating a feature value derivation cycle is set to an initial value 1 (S900). Then, the respiratory rate feature value is extracted for an arbitrary interval Tn, for example, a time interval of 15 seconds (S910). The step S910 of extracting the respiratory rate characteristic value in the Tn section includes a step S911 of sensing the optical pulse wave, a step S912 of deriving a respiration rate signal, a step S913 of deriving a respiration rate characteristic value in the Tn section, .

Here, the step S911 of sensing the optical pulse wave includes the step S810 of receiving the optically-inductive pulse wave shown in Fig. 8, the band elimination / band-pass filtering step S820, and the digital conversion step S830 Concept. In addition, the step of deriving the respiration rate signal (S912) is performed in the same manner as the step of deriving the respiration rate signal (S840) shown in Fig.

In the step of deriving the respiration rate characteristic value S913, a predetermined number of interest frequency values and non-interest frequency values are extracted from the frequency axis of the graph as shown in FIG. 6 or 7 for the derived respiration rate signal, And calculates a respiration rate characteristic value.

The respiratory rate characteristic value according to a preferred embodiment of the present invention can be obtained by dividing the intensity of the frequency component in the 0.2 Hz to 0.3 Hz band, which is an area of interest of the present invention, And is calculated in comparison with the strength. At this time, the number of frequency components extracted from the ROI and the number of frequency components extracted from the ROI may be the same or different.

The respiratory rate characteristic values according to the present invention can be summarized as shown in Equation 1 below.

In Equation (1), Resp _fea is the respiratory rate characteristic value, and Resp _fea (f) is the intensity value at the frequency component f.

(When n = 1 il) T1 when the respiratory rate characteristic value derived from the interval, it is checked whether the preset number of times is performed by respiratory rate characteristic value calculation procedures (i. E., N _th) (S920). If the predetermined number of times has not been performed, the value of n is incremented by one (S921), and step 910 is repeated.

When respiration rate characteristic value calculation process is performed by a predetermined number of times (YES in S920), because the respiratory rate characteristic value of the N _th number as calculated and calculates the average value of these values (S930). For example, the N _th value can be set to 10 times.

Meanwhile, the average of the respiratory rate characteristic values derived through FIG. 9 is an arithmetic average, but the average value according to the present invention is not limited to the arithmetic average. In other words, the average value of the respiratory rate characteristic values according to the present invention can be obtained when the respiratory rate characteristic value calculated in real time through the execution of the abnormal breath detection method of FIG. 10 described later does not exceed the ideal respiration threshold value, It can also be used in the form of a moving average value by updating the average value in real time by reflecting on the average value calculation.

That is, although the operations shown in FIG. 9 and the operations shown in FIG. 10 are shown and described as separate operations for the sake of convenience, the arithmetic mean derivation procedure shown in FIG. 9 is modified to the moving average derivation procedure so that the two operations can be integrated have.

FIG. 10 is a detailed flowchart of the abnormal breath detection method using the frequency analysis according to the present invention.

The abnormal respiration detection method shown in FIG. 10 shows an operation procedure of detecting abnormal respiration for a user's optical pulse wave inputted in real time after the respiratory rate characteristic average value is derived through a procedure as shown in FIG.

In order to detect abnormal respiration according to the present invention, an optical pulse pulse sensing step (S1010) and a respiration rate signal derivation step (S1020) are performed on a user's optical pulse wave input in real time. Here, the optical-pulse-wave-sensing step S1010 proceeds in the same manner as the optical-volume-pulse-wave-sensing step S911 shown in FIG. That is, the optical pulse-wave sensing step S1010 includes a step S810 of receiving the optically-inactive pulse wave shown in FIG. 8, a band elimination / band-pass filtering step S820, and a digital conversion step S830 .

In addition, the step of deriving the respiration rate signal (S1020) is the same as the step of deriving the respiration rate signal described in FIG. 9 (S912) and the step of deriving the respiration rate signal described in FIG. 8 (S840).

When the respiration rate signal is derived, a respiration rate characteristic signal is derived for the current respiration rate signal by analyzing the respiration rate signal on the frequency axis (S1030). When the current respiratory rate characteristic value is derived, the ratio of the current respiratory rate characteristic value to the respiratory rate characteristic average value is calculated by comparing the respiratory rate characteristic average value calculated through the procedure shown in Fig. 9 and the current respiratory rate characteristic value at step S1040.

That is, the ratio of the respiratory rate characteristic values can be summarized as shown in Equation 2 below.

When the respiratory rate characteristic value ratio is calculated, abnormal breathing is determined according to the calculated ratio (S1050).

Specifically, when the respiratory rate characteristic value ratio is less than a predetermined threshold value, for example, less than 10%, it can be detected as an apnea state.

As described above with reference to FIG. 9, when the respiratory rate characteristic value calculated in real time does not exceed the ideal respiration reference value, the respiratory rate characteristic value is reflected in the average value calculation of FIG. 9 to update the average value in real time, The respiratory rate characteristic value derived from FIG. 10 can be utilized for calculating the moving average value in real time.

In the ideal respiration determination step (S1050), it is also possible to determine what type of abnormal breathing is abnormal breathing.

Here, the respiratory rate characteristic value ( Respfea ) May have a value from 0 to 1, and when the absorptive characteristic value is less than the central apnea threshold value, it is determined to be central apnea, and when the respiratory rate characteristic value falls within the range of the obstructive apnea threshold value, it is defined as obstructive apnea, If it is located between the apnea threshold and the central apnea threshold, it can be judged to be a mixed apnea.

For example, if said normal breathing during breathing rate characteristic value (Resp _fea) = 0.5 as an example, can be expressed as shown in Equation (3) below, the criteria for determining the type of the above breathing according to the respiratory rate characteristic value.

According to the criterion shown in Equation (3), when the respiratory rate characteristic value is close to 0, it is determined to be central apnea among the abnormal breathing, and when the respiratory rate characteristic value is less than 0.5, it is judged as obstructive apnea. For example, if it is close to 25%, it is judged as mixed apnea.

When apnea is detected according to the abnormal breathing detection method shown in FIG. 10, the apnea state and / or apnea type is displayed or transmitted to the perceived result output unit 300.

The operation of the abnormal breath sensing method according to the embodiment of the present invention can be implemented as a computer-readable program or code on a computer-readable recording medium. A computer-readable recording medium includes all kinds of recording apparatuses in which data that can be read by a computer system is stored. The computer-readable recording medium may also be distributed and distributed in a networked computer system so that a computer-readable program or code can be stored and executed in a distributed manner.

Also, the computer-readable recording medium may include a hardware device specially configured to store and execute program instructions, such as a ROM, a RAM, a flash memory, and the like. Program instructions may include machine language code such as those produced by a compiler, as well as high-level language code that may be executed by a computer using an interpreter or the like.

While some aspects of the invention have been described in the context of an apparatus, it may also represent an explanation according to a corresponding method, wherein the block or apparatus corresponds to a feature of the method step or method step. Similarly, aspects described in the context of a method may also be represented by features of the corresponding block or item or corresponding device. Some or all of the method steps may be performed (e.g., by a microprocessor, a programmable computer or a hardware device such as an electronic circuit). In some embodiments, one or more of the most important method steps may be performed by such an apparatus.

In embodiments, a programmable logic device (e.g., a field programmable gate array) may be used to perform some or all of the functions of the methods described herein. In embodiments, the field programmable gate array may operate in conjunction with a microprocessor to perform one of the methods described herein. Generally, the methods are preferably performed by some hardware device.

It will be apparent to those skilled in the art that various modifications and variations can be made in the present invention without departing from the spirit or scope of the present invention as defined by the following claims It can be understood that

100: optic volumetric pulse sensing part 200: ideal respiration recognition part
300: recognition result output unit 110: light receiving element
120: current / voltage converter 130: band elimination filter
140: band-pass filter 150: analog-to-digital converter
160: light emitting device 170: optical output controller

Claims (20)

An optical volumetric pulse-wave sensing unit for receiving a user's pulse wave to remove noise, extracting a signal of a required band, and converting the signal into a digital signal; And
And an abnormal respiration detection unit for extracting a respiration rate signal from the optical pulse wave signal sensed by the optical volume pulse wave sensing unit and calculating a respiration rate characteristic value of a current user and comparing the respiration rate characteristic value with a respiration rate characteristic reference value. The method according to claim 1,
The abnormal respiration part may include:
And acquires the respiration rate signal by performing band filtering of a respiration frequency band on the optically negative pulse wave. The method according to claim 1,
The abnormal respiration part may include:
Wherein the respiration rate characteristic value is calculated by calculating a ratio of the frequency component intensity of the ROI to the frequency component intensity of the non-ROI in the frequency-converted respiration rate signal. The method of claim 3,
Wherein the region of interest is in the 0.2 Hz to 0.3 Hz band and the uninteresting region is in the 0 Hz to 0.19 Hz band. The method according to claim 1,
Wherein the respiration rate characteristic reference value is a respiration rate characteristic average value. The method of claim 5,
The respiratory rate characteristic average value is calculated by:
Is set to an arithmetic average or a moving average value of respiratory rate characteristic values calculated a plurality of times in a predetermined time interval for normal breathing. The method according to claim 1,
The abnormal respiration part may include:
Wherein the type of ideal respiration is determined based on the current respiration rate characteristic value when the current user's respiration is determined to be abnormal breathing. The method according to claim 1,
Wherein the respiration analyzer is wearable on a part of the user's body. The method according to claim 1,
Wherein the respiration analyzer is in a form wearable on the wrist of a user. The method according to claim 1,
The optically-inactive pulse-wave sensing unit comprises:
A sensor for generating an optical signal and sensing a received optical signal reflected from a user's body;
A band elimination filter for eliminating unnecessary noise bands from the sensed signal;
A band pass filter for performing band pass filtering of a pulse signal band with respect to a signal output from the band elimination filter; And
And an analog-to-digital converter for performing a digital conversion on the filtered signal. The method according to claim 1,
Wherein the abnormal breathing comprises at least one of obstructive apnea, mixed apnea, and central apnea. The method according to claim 1,
The abnormal respiration part may include:
Further comprising a recognition result outputting section for outputting a recognition result on whether abnormal breathing has occurred. An optical volumetric pulse wave sensing step of sensing a user's pulse wave to remove noise, extracting a signal of a desired band, and converting the signal into a digital signal;
Extracting a respiration rate signal from the sensed optical pulse wave signal, and performing frequency conversion; And
Calculating a respiration rate characteristic value from the frequency-converted respiration rate signal, and comparing the respiration rate characteristic value with a respiration rate characteristic reference value, thereby detecting abnormal breathing. 14. The method of claim 13,
The respiration rate signal
And performing band filtering of a breathing frequency band on the optical pulse wave signal. 14. The method of claim 13,
Wherein the step of sensing abnormal breathing comprises:
And calculating the respiratory rate characteristic value by calculating a ratio of the frequency component intensity of the ROI to the frequency component intensity of the non-ROI in the frequency-converted respiration rate signal. 14. The method of claim 13,
The respiratory rate characteristic reference value is a respiratory rate characteristic average value,
Wherein the respiratory rate characteristic average value is set to an arithmetic average or moving average value of a respiratory rate characteristic value calculated a plurality of times in a predetermined time interval for normal breathing. 14. The method of claim 13,
Wherein the step of sensing abnormal breathing comprises:
Further comprising the step of determining the type of ideal respiration based on the current respiration rate feature value if the current user's respiration is determined to be abnormal breathing. 14. The method of claim 13,
And outputting an abnormal breath detection result. 14. The method of claim 13,
Wherein said abnormal breathing comprises at least one of obstructive apnea, mixed apnea, and central apnea. 16. The method of claim 15,
Wherein the region of interest is in the 0.2 Hz to 0.3 Hz band and the non-interest region is in the 0 Hz to 0.19 Hz band.

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