KR102403717B1 - A method for detecting vital signs based on a radar senor and a system for monitoring and improving state of sleeping - Google Patents

Abstract

According to the present specification, disclosed are a method for detecting a biosignal based on a radar sensor, and a system for monitoring and improving a sleep using the same. According to an embodiment of the present invention, the system comprises: a first device (100) including a radar sensor (130); and a second device (200) wirelessly communicating with the first device (100). The radar sensor (130) performs radar transmission/reception with respect to a subject to obtain a heartbeat signal and a breathing signal separated from each other from a received radar, and the second device (200) receives data on the heartbeat signal and the breathing signal from the first device (100) to monitor a sleep. Therefore, the precision on bio-signal detection can be further improved.

Description

Radar sensor-based biosignal detection method and sleep monitoring and improvement system using same {A method for detecting vital signs based on a radar sensor and a system for monitoring and improving state of sleeping}

The present invention relates to a biosignal detection method and a sleep monitoring and improvement system using the same, and to a biosignal detection method based on a radar sensor so that it can be conveniently used in a daily sleeping space, and a sleep monitoring and improving system using the same.

Sleep is a very important factor for health, but it is known that about 20% of modern people suffer from sleep disorders.

Examples of sleep disorders include insomnia and sleep apnea.

Insomnia is a typical sleep disorder that results in fatigue, drowsiness, loss of motivation, etc.

Sleep apnea is a disease in which short-lived symptoms recur during sleep. If sleep apnea occurs more than 40 times a night, it is difficult to sleep deeply, and oxygen supply to the body becomes difficult. It causes moodiness, morning headache, lethargy, gravity and memory loss, and depression.

Polysomnography is commonly used to diagnose sleep disorders.

According to the polysomnography method, the entire process of sleep is investigated while sleeping in a hospital. It is performed in a way that comprehensively measures EEG, eye movement, muscle movement, respiration, and electrocardiogram during sleep and records the sleep state at the same time. By analyzing the records obtained through the examination, sleep-related diseases are diagnosed and treatment policies are established.

This polysomnography test requires patients to sleep with many biosignal sensors attached to their body, so it is inconvenient to get the same sleep as usual. only possible, so the accuracy of the diagnosis is reduced.

The present invention is an invention derived to solve the problems of the prior art. The inconvenience of the sleep diagnosis (monitoring) process is eliminated, the accuracy of diagnosis is improved, and it does not stop at just performing sleep diagnosis but also provides a means for improving sleep disorders. We would like to provide a way to provide them together.

Accordingly, the present invention provides a first device 100 including a radar sensor 130; and a second device 200 that wirelessly communicates with the first device 100, wherein the radar sensor 130 performs radar transmission/reception with respect to the subject, and a heartbeat signal and a respiration signal that are mutually separated from the reception radar , and the second device 200 receives data on the heartbeat signal and the respiration signal from the first device 100 to perform sleep monitoring and provides a radar sensor-based sleep monitoring and improvement system.

According to one embodiment, the system further includes a jetting device 140 that the first device 100 jets a liquid for improving sleep, and the jetting operation of the jetting device 140 is performed according to the heartbeat signal and the It may be controlled based on the breathing signal.

According to an embodiment, in the system, the radar sensor 130 has a short-channel receiving channel, and the radar sensor 130 applies a wavelet transform algorithm to receive a heartbeat signal and respiration from the receiving radar. It may be to acquire a signal.

According to an embodiment, in the system, the radar sensor 130 has a multi-channel reception channel, and the radar sensor 130 applies an Independent Component Analysis (ICA) algorithm to receive heart rate from the reception radar. It may be to acquire a signal and a breathing signal.

According to an embodiment, the system may be such that the radar sensor 130 detects the phase of the heartbeat signal and the phase of the respiration signal in order to increase the precision of detecting the biosignal.

The effects or advantages of the present invention are summarized as follows.

1. According to the present invention, bio-signals (heartbeat signal, respiration signal) for a subject (person) can be obtained by using a radar sensor. Because the normal polysomnography test requires patients to sleep with many biosignal sensors attached to their body, it is inconvenient to get the same sleep as usual. There is a problem in that the accuracy of diagnosis is lowered because only

2. According to the present invention, sleep improvement or sleep disorder healing effect can be obtained by providing a function of spraying a liquid suitable for sleep state or sleep disorder in the form of mist based on the detected biosignal (heartbeat signal, respiration signal) can

3. According to the present invention, when the radar reception channel is a single channel, a wavelet transform algorithm can be applied to obtain a heartbeat signal and a respiration signal from the received radar signal with high precision. In this case, it is possible to obtain a heartbeat signal and a respiration signal from the received radar signal with high precision by applying an Independent Component Analysis (ICA) algorithm.

4. According to the present invention, the phase of the heartbeat signal and the phase of the respiration signal can be detected by the radar sensor to be used in the signal separation process, and thereby, the precision of detecting the biosignal can be further improved.

5. According to the present invention, a second device (eg, a smartphone) that can check sleep monitoring data is provided, and through this, the user can conveniently check related information such as his or her sleep pattern and sleep disorder.

1 is a diagram showing an example of a Chirp signal (FMCW signal) transmitted by a radar sensor.
2 is a view for explaining the principle of detecting a biosignal using a Doppler radar according to the present invention.
3 is a view showing a biosignal detection method according to an embodiment of the present invention.
FIG. 4 is a diagram for conceptual explanation of separation of a heartbeat signal and a respiration signal according to the method of FIG. 3 .
5 is a diagram showing a wavelet transform algorithm usefully applicable when a radar reception channel is provided as a short channel.
6 is a conceptual diagram illustrating a case where a radar reception channel is applied to two channels.
7 and 8 are diagrams showing a sleep monitoring and improvement system according to an embodiment of the present invention.

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

1. Examples of sleep disorders to which the present invention is applied

The present invention can be used for diagnosing and improving various types of sleep disorders, representatively, it can be used for insomnia and sleep apnea. The following is a description of insomnia and sleep apnea.

1-1. insomnia

ㆍ Suspicion of abnormal heart function as the main cause of insomnia.

ㆍ In our body, there are sympathetic nerves that control emotions and parasympathetic nerves that promote physical activity, which are closely related to heartbeat. The sympathetic and parasympathetic nerves play opposite roles and either promote or inhibit the heartbeat.

ㆍLike a wave curve, non-REM (non-rapid eye movement) and REM (rapid eye movement) move for about 90 minutes in one cycle, and usually repeats 4 to 5 cycles overnight.

ㆍ Non-REM sleep, which accounts for 75-80% of total sleep, is again divided into stage 1, stage 2, and stage 3 sleep.

Stage 3 is slow wave sleep, the deepest sleep.

ㆍ During non-REM sleep, breathing slows down, heart rate and blood pressure drop, and mental activity decreases.

ㆍ REM sleep is a stage in which the brain takes a rest and organizes the information received during the day. During REM sleep, muscles relax, breathing and heartbeat change irregularly, and mental activity is active.

1-2. sleep apnea

ㆍSleep apnea is a condition in which breathing stops briefly during sleep.

ㆍAccurate diagnostic criteria for sleep apnea is when you breathe less for 10 seconds or more or stop breathing more than 5 times per hour during sleep.

ㆍ During apnea, the heart rate slows down, but the moment the apnea ends, the sympathetic nervous system is excited and the heart beats very fast .

ㆍ Obstructive sleep apnea can be diagnosed when uveal oscillation is accompanied by a decrease in heart rate, and central sleep apnea is diagnosed when there is only a decrease in heart rate without uveal oscillation.

2. Biosignal detection theory according to the present invention

The biosignal (heartbeat signal, respiration signal) detection method according to the present invention is based on the theory described below.

ㆍ According to the present invention, the displacement of the body due to respiration and heartbeat is measured and displayed using the mmWave sensor. The parameters of displacement due to respiration and heartbeat are generally shown in the table below.

Front of body (chest) back of body (back) Vital Signs Frequency Amplitude Amplitude Respiratory Rate (Adult) 0.1 - 0.5 Hz ~ 1 - 12mm ~ 0.1 - 0.5mm heart rate (adult) 0.8 - 2.0 Hz ~ 0.1 - 0.5mm ~ 0.01 - 0.2mm

ㆍ To measure these minute vibrations/displacements, the phase change of the FMCW signal with time is measured in the target range bin.

는 목표물이 거리

만큼 이동할 때의 위상 변화임. 더 작은 파장의 λ 가 더 좋은 변위 감도를 제공함)(

is the distance to the target

It is the phase change when moving by A smaller wavelength λ gives better displacement sensitivity)

- According to the present invention, a Chirp signal (FMCW signal) whose frequency is linearly-increasing periodically is transmitted toward the subject by the radar (refer to FIG. 1).

ㆍ The transmitted FMCW signal is obtained from the following equation.

ㆍ The signal of the receiver is a delayed version of the transmitted signal and is expressed by the following equation.

ㆍ After mixing and filtering, the signal received from the object in the range R is obtained through the following equation.

와

를 가지 있다.ㆍ For a single object, the bit signal b(t) is a sine wave,

Wow

have a

ㆍ Measure the phase displacement of the FMCW signal with time in the range bin of the object to measure the minute vibration.

만큼 이동하면 연속적인 측정에서의 위상 변화는 다음과 같이 나타난다. 예를 들어,

= 1mm 만큼의 작은 변위일 때, λ = 4mm에서 해당 위상 변화는

이다.・The distance to the object

Moving by , the phase change in successive measurements appears as follows. for example,

For a displacement as small as 1 mm, the corresponding phase change at λ = 4 mm is

to be.

ㆍ The phase can be measured by FFTing the bit signal b(t) and calculating the phase from the target range bin.

이라는 range bin에 있다고 가정하면, 시간 인덱스

에서

의 위상을 측정해 진동신호

를 추출할 수 있다(

은 처프 인덱스,

는연속 측정 사이의 시간). ㆍ FFT is performed and the object is

Assuming it is in a range bin called

at

Vibration signal by measuring the phase of

can be extracted (

is the chirp index,

is the time between successive measurements).

가 작아서 물체가 측정 시간 동안 동일한 range bin에서 벗어나지 않는다고 가정함)(vibration

is small so that the object does not deviate from the same range bin during the measurement time)

3. Biosignal detection method according to the present invention

3-1. Algorithm design of biosignal detection method

Bio-signal detection has been performed based on continuous waveform (CW) radar, but recently, there are many difficulties in detecting bio-signals due to interference of various clutter signals.

Accordingly, the present invention proposes a biosignal detection technique using a frequency modulation continuous waveform (FMCW) radar in order to solve this problem.

The proposed biosignal technique is as follows. First, the radar signal received from the receiving antenna is used to detect the biosignal through the de-chirping process.

A _h : amplitude of cardiac signal h(t) : change of heart with time

A _r : Respiratory signal amplitude r(t) : Lung displacement with time

h ₀ : initial position of the heart λ : wavelength

r ₀ : Lung initial position

Since respiration and heart rate are determined by the periodic movements of the lungs and heart over time, phase detection must be performed.

With respect to cardiac and respiratory signals having different repetition periods, two signals having different frequencies are separated from phase signals through wavelet transform (WT).

In addition, in order to accurately measure heart rate, which has a smaller signal strength than respiration, a multiple signal classification (MUSIC) algorithm that performs spectrum estimation through an eigenvector of noise is applied to measure respiration and heart rate relatively accurately.

3-2. Bio-signal detection principle using Doppler radar

2 is a diagram for explaining the principle of detecting a biosignal using a Doppler radar according to the present invention.

In FIG. 2, h(t) is a cardiac signal, r(t) is a respiratory signal, and v(t) is a human motion signal.

Equation T(t) described below is the transmitted signal by the radar sensor, R(t) is the received signal by the radar sensor, and B(t) is R(t) to the baseband ( It is a baseband signal obtained by lowering to the baseband. Through this process, a baseband signal for the subject (human) is obtained through the radar sensor.

3-3. Biosignal detection method

3 is a view showing a biosignal detection method according to an embodiment of the present invention. With reference to this, detailed steps of the biosignal detection method will be sequentially described.

In FIG. 3, B(t) is a baseband signal obtained by lowering a received signal by a radar sensor to a baseband.

According to the biosignal detection method of the present invention, first, the step (S11) of selecting a signal optimal point for the B(t) signal is performed. In general, for adults, the frequency range of the respiratory signal is 0.1 to 0.5 Hz, and the frequency range of the heartbeat signal is 0.8 to 2.0 Hz. As such, the frequency ranges of the respiration signal and the heartbeat signal are different, and an optimal point for each signal may be selected in each of the frequency ranges.

Next, a step S12 of performing noise component removal and signal separation is performed. Noise components removed in step S12 include DC-offset and clutter. Referring to FIG. 4 , the signal separation performed in step S12 means separating the B(t) signal into a heartbeat signal B _h (t) and a respiration signal B _r (t). Since the respiration signal is relatively large compared to the heart rate signal, the heart rate signal is embedded in the respiration signal in the case of the B(t) signal including the heart signal and respiration signal. Therefore, it is very important to separate the cardiac signal from the respiratory signal.

Separation of these two signals may be performed through a wavelet transform algorithm shown in FIG. 5, and through this, a mutually separated heartbeat signal B _h (t) and respiration signal B _r (t) may be obtained. .

According to the present invention, in order to increase the precision of signal detection, the radar reception channel can be applied to multiple channels. 6 is a conceptual diagram illustrating a case where a radar reception channel is applied to two channels. With reference to this, the signal separation algorithm in the case of two channels will be described as follows.

In the case of two channels, the signal B ₁ (t) obtained through the channel 1 and the signal B ₂ (t) obtained through the channel 2 may be expressed as follows.

And, the linear relational expression of the two-channel signals can be organized as follows.

는 심장에 대한 레이다 신호,

는 폐에 대한 레이더 신호를 나타낸 것이다. 독립성분분석(ICA: Independent Component Analysis) 원리에 따라 그 선형 관계식에서 분리된 신호가 non-Gaussian이 되도록 W 형렬을 추정함으로써 분리 신호

및

를 얻을 수 있다.In the following linear relation

is the radar signal to the heart,

shows the radar signal for the lungs. Separated signal by estimating W-form so that the separated signal from the linear relation becomes non-Gaussian according to the principle of Independent Component Analysis (ICA)

and

can get

Next, in order to increase the precision of signal detection, the phase detection step (S13), the MUSIC algorithm execution step (S14), and the body motion processing step (S15) are sequentially performed.

In the phase detection step S13, the phase θ _h (t) of the heartbeat signal and the phase θ _r (t) of the respiration signal, which are expressed by the following equations, are detected. Through this phase detection, the heartbeat signal B _h (t) and the respiration signal B _r (t) can be more precisely obtained.

The body motion processing step S15 is a step of removing noise components according to the movement of the subject (human). During the examination, a sleeping person shows movement, and therefore, the separated signal generally includes a noise component according to the movement. Therefore, by removing the noise component through step S15, it is possible to increase the precision of signal separation.

By performing the above-described steps, it is possible to finally obtain a heartbeat signal and a respiration signal separated from each other (S16). These bio-signals are transmitted to a separate computing device (eg, a smartphone) and can be used as basic data for monitoring and analyzing the sleep state of the subject, a screen display function thereof, and an alarm function ( S17).

4. Sleep improvement system according to the present invention

The present invention provides a sleep monitoring and improvement system using the above-described biosignal detection method based on a radar sensor.

7 and 8 are diagrams showing a sleep monitoring and improvement system according to an embodiment of the present invention.

Referring to this, the sleep monitoring and improvement system according to an embodiment of the present invention includes the first device 100 and the second device 200 .

The first device 100 is disposed around a subject (person) during sleep. As illustrated in FIG. 7 , the first device 100 may be used while being placed on a table around a bed, for example.

The first device 100 may be configured to include a Bluetooth module 110 , a controller 120 , a radar sensor 130 , and an injection device 140 .

The Bluetooth module 110 is configured for wireless communication with the second device 200 .

The control unit 120 is a configuration for controlling the operation of the first device 100 , and the biosignal detection operation by the radar sensor 130 , the injection operation of the injection device 140 , and the data transmission/reception operation of the Bluetooth module 110 are performed. It is performed under the control of the controller 120 .

The radar sensor 130 performs radar transmission/reception with respect to the subject and detects a biosignal based on the received radar. A mmWave sensor is used as the radar sensor 130, and a Chirp signal (FMCW signal) whose frequency is linearly increased periodically is transmitted toward the subject.

The radar sensor 130 detects two biosignals, that is, a heartbeat signal and a respiration signal, through the biosignal detection method described above. As described above, since the received radar signal is a state in which the heartbeat signal is buried in the respiration signal having a relatively high intensity, it is very important to separate the heart signal from the respiration signal in the present invention. The reception channel of the radar sensor 130 may be provided as a single channel or multiple channels. As described above, in the case of a short channel, a wavelet transform algorithm may be suitably applied, and in the case of a multi-channel, independent component analysis ( The W-type estimation algorithm according to the ICA: Independent Component Analysis) principle may be suitably applied.

Referring to FIG. 7 , the radar sensor 130 outputs a radar to the detection area (a dotted line display area), and the output range is selected within a range harmless to the human body. In the present invention, since a heartbeat signal and a respiration signal are detected as biosignals, it is preferable that the radar detection area be set to the chest area of the human body as a target.

The jetting device 140 is a device for jetting a liquid beneficial to sleep improvement in the form of a mist. Aroma perfume may be used as an example of the liquid sprayed by the spraying device 140 . The jetting device 140 may be configured to jet various types of liquid, and in this case, a liquid matching the type of sleep disorder analyzed based on the biosignal may be jetted.

Representative types of sleep disorders that can be diagnosed by the present invention include insomnia and sleep apnea. As described above, in the insomnia state and the sleep apnea state, the heartbeat signal and the respiration signal show specific characteristics to be distinguished from the normal state, so by analyzing the heartbeat signal and respiration signal detected through the radar sensor 130, user) can determine whether the patient is in a state of insomnia and whether he is in a state of sleep apnea. The determination is performed by the controller 120 , and for this purpose, the heartbeat signal and the respiration signal detected by the radar sensor 130 are provided to the controller 120 . The control unit 120 determines the type and duration of the sleep disorder based on the heartbeat signal and the respiration signal, and controls the injection device 140 according to a preset condition to spray the liquid for improving the sleep state.

The second device 200 is a mobile device for sleep monitoring and setting how to use the first device 100 . A smartphone may be suitably used as the second device 200 . In this case, a dedicated application (app) for using the service according to the present invention is installed and executed in the second device 200 .

The second device 200 transmits/receives data to and from the first device 100 through wireless communication. The bio-signals (eg, a heartbeat signal, a respiration signal) collected through the first device 100 are transmitted to the second device 200 to be stored and utilized. Based on the stored data, the second device 200 may monitor the sleep state of the user (subject) including the type and duration of the sleep disorder. The dedicated app of the first device 100 provides a monitoring result display screen, and the user can check his/her sleep information through the screen.

The user may set the usage of the first device 100 by using the second device 200 . For example, the user can set detailed usage conditions such as the type of sleep disorder to be monitored, whether and how liquid spray is applied and how, spray duration, and monitoring time period, as desired through the second device 200 .

The second device 200 may provide an alarm function. For example, as a result of monitoring the sleep state, when sleep apnea continues for a certain period of time or more, the alarm function may be performed by transmitting an alarm sound.

100: first device
110: bluetooth module
120: control unit
130: radar sensor
140: injection device
200: second device

Claims (5)

a first device 100 including a radar sensor 130 and a spraying device 140 for spraying a liquid for improving sleep in a mist form; and
Including; a second device 200 that wirelessly communicates with the first device 100;
The radar sensor 130 obtains a heartbeat signal and a respiration signal separated from each other by performing radar transmission/reception to the subject, and the injection operation of the injection device 140 is based on the heartbeat signal and the respiration signal to be controlled, and the second device 200 receives data about the heartbeat signal and the respiration signal from the first device 100 to perform sleep monitoring,
The biosignal detection method performed by the radar sensor 130 includes:
(S11) selecting a signal optimal point for the radar reception signal;
(S12) is a step of removing a noise component from the radar reception signal and then separating it into a heartbeat signal and a respiration signal. When the radar sensor 130 has a short-channel reception channel, a wavelet transform algorithm is applied and applying an Independent Component Analysis (ICA) algorithm when the radar sensor 130 has a multi-channel reception channel;
(S13) detecting the phase of the heartbeat signal and the phase of the respiration signal;
(S14) performing spectrum estimation by the MUSIC algorithm; and
(S15) removing a noise component according to the movement of the subject; including
A radar sensor based sleep monitoring and improvement system. delete delete delete delete

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