KR102047476B1 - Neckband type healthcare wearable device, and method thereof - Google Patents

Abstract

The present invention can measure the user's own biological information, such as brain waves, pulse waves, respiratory rate while wearing the neck, such as a necklace worn around a person's neck, and can manage the user's own health based on the measured biometric information A neckband type healthcare wearable device and a method thereof are disclosed. The disclosed neckband type healthcare wearable device includes: a neckband body formed along an arc of an open circle and having one or more buttons on a surface thereof and electrically coupled with the one or more buttons; An EEG sensor for measuring an EEG of a user around the neckband body; A pulse wave sensor for measuring a pulse wave of a user around the neckband body; A first earphone part electrically connected to one end of the neckband body and having a first speaker for outputting sound; A second earphone unit electrically connected to the other end of the neckband body and having a second speaker for outputting sound; And an emotion and a physical state of the user, based on a correlation between the brain wave signal measured by the brain wave sensor and the pulse wave signal measured by the pulse wave sensor, provided inside the neckband body. And an analysis engine unit controlling to output a care signal to be improved.

Description

Neckband type healthcare wearable device and method thereof {Neckband type healthcare wearable device, and method}

The present invention relates to a neckband type healthcare wearable device and a method thereof, and more particularly, measures a user's own brain wave, pulse wave, respiratory rate, etc. while the user wears a neck, such as a necklace worn around a person's neck. The present invention relates to a neckband type healthcare wearable device and a method of managing a user's own health based on measured biometric information.

As medicine advances, devices are being developed to detect health by measuring electroencephalogram (EGE) or photo-plethysmography (PPG) signals.

The EEG tester detects and analyzes the EEG of the user in university hospitals and hospitals to objectively measure cognitive intensity, cognitive speed, concentration, and left / right brain activity detected from EEG to evaluate essential skills required for learning, and attention deficit excess Diagnose Behavioral Disorder (ADHD), Attention Deficit Disorder (ADD), Depression, Learning Disability, Anxiety Disorder, Insomnia, Autism, Dementia, etc. do.

By the way, the conventional EEG is composed of complex measurement equipment, do not provide a variety of application services using this, an application that can manage sleep by analyzing the characteristics of the EEG according to the sleep cycle (90 minutes 1 cycle) There is a problem that does not provide.

On the other hand, the pulse wave detector is a method of restoring the pulse wave of the blood passing through the skin tissue by measuring a light source reflected by the skin tissue or transmitted through the skin tissue by exciting the light source to the human skin (beneath skin). Therefore, it can be said that the light source / light receiving sensor is a necessary component for constructing the light volume pulse wave. In some cases, the implementation of the light source may be omitted and the ambient light may be utilized. In this case, however, since the signal is greatly affected as the ambient light changes, it is difficult to use in various environments.

Therefore, assuming a biosignal measurement environment that utilizes personalized electronic devices and wearable devices, the weight and volume of the system need to be minimized, and it is required to realize low power while saving power. do.

Korean Registered Patent Publication No. 0954817 (Registration Date: April 19, 2010)

An object of the present invention for solving the above problems is to measure the biometric information of the user's own brain waves, pulse waves, respiratory rate, etc. while wearing the user's neck, such as a necklace worn around a person's neck, The present invention provides a neckband type healthcare wearable device and a method for managing a user's own health.

Neckband type healthcare wearable device according to the present invention for achieving the above object is formed along an arc of an open circle, one or more buttons are provided on the surface, one or more components are provided inside the one A neckband body electrically coupled with the above buttons; An EEG sensor for measuring an EEG of a user around the neckband body; A pulse wave sensor for measuring a pulse wave of a user around the neckband body; A first earphone part electrically connected to one end of the neckband body and having a first speaker for outputting sound; A second earphone unit electrically connected to the other end of the neckband body and having a speaker for outputting sound; And an inside of the neckband body, converts and analyzes an EEG signal measured by the EEG sensor into data, converts and analyzes a pulse wave signal measured by the EEG sensor into data, and analyzes the EEG signal and the And an analysis engine unit configured to diagnose the emotion and the physical condition of the user according to the correlation between the pulse wave signals and output a care signal for improving the emotion and the physical condition.

Here, the EEG sensor is installed in any one of the neckband body, the first earphone unit, the second earphone unit, the pulse wave sensor is also of the neckband body, the first earphone unit, the second earphone unit It can be installed in either.

The apparatus may further include a storage unit provided inside the neckband body and storing a sound source signal corresponding to a care signal for improving the emotion and body state as data.

The apparatus may further include a respiratory rate measurement unit provided inside the neckband body to detect a respiratory signal for respiration of the user with a gyro sensor and measure respiratory rate from the detected respiratory signal.

The apparatus may further include a power generation unit provided in the neckband body to detect vibrations according to the movement of the user and generate power by using the sensed vibration signal.

The one or more buttons may include a play button for playing, stopping, or pausing a sound source; A call button for operating the neckband body in a call mode; A volume button for adjusting a volume of a sound output through the first earphone unit or the second earphone unit; A selection button for selecting a next song or a previous song for the sound source; And a power button for instructing power to be supplied for operation.

The apparatus may further include a power supply unit provided in the neckband body and supplying power required for the operation of the one or more buttons and components provided in the neckband body.

In addition, the inside of the neckband body, the analysis engine unit diagnoses the user's emotions and body conditions according to the correlation between the brain wave signal and the pulse wave signal to the outside of the care signal to improve the emotions and body conditions A communication unit for transmitting to the device in near field communication; And a connector for transmitting / receiving data to or from the external device with a USB type, or receiving power from an external device with a USB type.

In addition, the outer surface of the neckband body may be formed in the form of protrusions or irregularities to prevent the flow of the neckband body to move or move in accordance with the movement of the user.

On the other hand, the neckband type wearable healthcare method according to the present invention for achieving the above object is formed along an arc of an open circle, the outer surface is provided with one or more buttons and connectors, the storage unit and A neckband type wearable healthcare service method of a neckband body electrically coupled with one or more buttons including a breath rate measuring unit, a power generation unit, a power unit, and a communication unit, the method comprising: (a) the neckband body of the mode button Entering a healthcare mode according to a selection operation; (b) measuring, by the first earphone unit, an EEG of a user through an EEG sensor; (c) measuring, by the second earphone unit, a user's pulse wave through a pulse wave sensor; (d) the respiratory rate measuring unit detecting a respiratory signal for the user's breathing through a gyro sensor and measuring the respiratory rate from the detected respiratory signal; (e) analyzing and converting the measured brain wave signal and pulse wave signal into data by an analysis engine unit; (f) analyzing, by the analysis engine unit, the emotion and the physical condition of the user according to the correlation between the measured respiration rate and the brain wave signal and the pulse wave signal; And (g) controlling the analysis engine unit to output a care signal to improve the emotion and the physical condition.

Further, in the step (g), the analysis engine unit reads the sound source data corresponding to the care signal from the storage unit storing the sound source signal corresponding to the care signal for improving the emotion and the body state as data and the first signal. It may be controlled to be output to the earphone unit and the second earphone unit.

In addition, the step (a), after the power is supplied to the component provided in the inside of the neckband body from the power supply provided in the inside of the neckband body, the neckband body according to the selection operation of the mode button Enter healthcare mode.

In addition, in the step (a), the power generation unit provided in the neckband body detects a vibration according to the movement of the user through a vibration sensor, and generates power using the detected vibration signal to generate the power unit. It can be charged.

In addition, in the step (a), the neckband body may be configured to transmit and receive data to and from the external device via a connector provided in a USB type, or to receive power from a external USB type through the connector and charge the power supply unit. can do.

In addition, in the step (g), the analysis engine unit may transmit a care signal for improving the emotion and the physical state to the external device through short-range communication through a communication unit.

According to the present invention, the neckband device shakes and vibrates as the user moves, and the device can be operated without power supply from the outside by the power generated by the vibration.

In addition, by implementing a low-power saving power while minimizing weight and volume while the user walks around the neck, it is possible to manage the health by measuring the user's own biometric information.

1 is a view showing the appearance of the neckband type healthcare wearable device according to an embodiment of the present invention.
Figure 2 is a schematic diagram showing an internal configuration example of a neckband type healthcare wearable device according to an embodiment of the present invention.
3 is a flowchart illustrating an operation of a neckband type wearable healthcare method according to an exemplary embodiment of the present invention.
4 is a view showing a waveform of the EEG signal measured over time by the first earphone unit according to an embodiment of the present invention.
5 is a view showing the waveform of the pulse signal measured through the second earphone unit according to an embodiment of the present invention.
6 illustrates an example of cardiac-brain synchronization information according to an embodiment of the present invention.

Hereinafter, exemplary embodiments of the present invention will be described in detail with reference to the accompanying drawings so that those skilled in the art may easily implement the present invention. As those skilled in the art would realize, the described embodiments may be modified in various different ways, all without departing from the spirit or scope of the present invention.

In order to clearly describe the present invention, parts irrelevant to the description are omitted, and like reference numerals designate like elements throughout the specification.

Throughout the specification, when a part is "connected" to another part, this includes not only "directly connected" but also "electrically connected" with another element in between. . In addition, when a part is said to "include" a certain component, which means that it may further include other components, except to exclude other components unless otherwise stated.

When a portion is referred to as being "above" another portion, it may be just above the other portion or may be accompanied by another portion in between. In contrast, when a part is mentioned as "directly above" another part, no other part is involved between them.

Terms such as first, second, and third are used to describe various parts, components, regions, layers, and / or sections, but are not limited to these. These terms are only used to distinguish one part, component, region, layer or section from another part, component, region, layer or section. Accordingly, the first portion, component, region, layer or section described below may be referred to as the second portion, component, region, layer or section without departing from the scope of the invention.

The terminology used herein is for reference only to specific embodiments and is not intended to limit the invention. As used herein, the singular forms “a,” “an,” and “the” include plural forms as well, unless the phrases clearly indicate the opposite. As used herein, the meaning of "comprising" embodies a particular characteristic, region, integer, step, operation, element and / or component, and the presence of other characteristics, region, integer, step, operation, element and / or component It does not exclude the addition.

Terms indicating relative space such as "below" and "above" may be used to more easily explain the relationship of one part to another part shown in the drawings. These terms are intended to include other meanings or operations of the device in use with the meanings intended in the figures. For example, if the device in the figure is reversed, any parts described as being "below" of the other parts are described as being "above" the other parts. Thus, the exemplary term "below" encompasses both up and down directions. The device can be rotated 90 degrees or at other angles, the terms representing relative space being interpreted accordingly.

Unless defined otherwise, all terms including technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art. Commonly defined terms used are additionally interpreted to have a meaning consistent with the related technical literature and the presently disclosed contents, and are not interpreted in an ideal or very formal sense unless defined.

DETAILED DESCRIPTION Hereinafter, exemplary embodiments of the present invention will be described in detail with reference to the accompanying drawings so that those skilled in the art may easily implement the present invention. As those skilled in the art would realize, the described embodiments may be modified in various different ways, all without departing from the spirit or scope of the present invention.

1 is a view showing the appearance of the neckband type healthcare wearable device according to an embodiment of the present invention, Figure 2 is a schematic diagram showing an internal configuration example of the neckband type healthcare wearable device according to an embodiment of the present invention It is a block diagram.

1 and 2, the neckband type healthcare wearable device 100 according to the present invention includes a neckband body 110 and a first earphone unit 160 electrically connected to the neckband body 110. And a second earphone unit 170.

Here, the brain wave sensor for measuring the brain wave of the user around the neckband body 110, and the pulse wave sensor for measuring the pulse wave of the user around the neckband body 110 may be further included.

In the exemplary embodiment of the present invention, the brain wave sensor is mounted on the first earphone unit 160 and the pulse wave sensor is mounted on the second earphone unit 170 as an example. However, the present invention is not limited thereto, and the EEG sensor may be mounted in the neckband body 110, may be mounted in the second earphone unit 170, and the pulse wave sensor may be mounted in the neckband body 110 as well. Or may be mounted on the first earphone unit 160.

The neckband body 110 is formed along an arc of an open circle, the surface is provided with one or more buttons (112-120), one or more components are provided therein one or more buttons (112-120) Electrically coupled with

The first earphone unit 160 is electrically connected to one end of the neckband body 110 and includes an EEG sensor for measuring an EEG of a user, and a first speaker for outputting sound.

The second earphone unit 170 is electrically connected to the other end of the neckband body 110 and includes a pulse wave sensor for measuring a pulse wave of a user and a second speaker for outputting sound.

Here, the one or more buttons 112 to 120 provided on the outer surface of the neckband body 110 may include a play button 112 for playing, stopping, or pausing the sound source; A call button 114 for operating the neckband body in a call mode; A volume button 116 for adjusting a volume of sound output through the first earphone unit 160 or the second earphone unit 170; A selection button 118 for selecting a next song or a previous song for the sound source; And a power button 120 for instructing power to be supplied for operation.

On the other hand, the analysis engine 130 is not shown in Figure 1 is provided inside the neckband body 110, and converts the EEG signals measured through the first earphone unit 160 to the data, the second analysis The pulse signal measured by the earphone unit 170 is converted into data and analyzed, and a care signal for diagnosing the user's emotion and physical condition according to the correlation between the brain wave signal and the pulse wave signal and improving the emotional and physical condition. Control to output

The storage unit 210 is provided inside the neckband body 110 and stores a sound source signal corresponding to a care signal for improving emotion and body state as data.

The breathing rate measuring unit 220 is provided inside the neckband body 110 to detect a breathing signal for a user's breathing with a gyro sensor, and measure the breathing rate from the detected breathing signal.

The power generator 230 is provided inside the neckband body 110 to detect vibrations according to a user's movement, and generate and generate power using the sensed vibration signal.

The power supply unit 240 is provided inside the neckband body 110 and supplies power required for the operation of one or more buttons 112 to 120 and the components provided inside the neckband body 110.

The connector 250 transmits / receives data to or from an external device with a USB type, or receives power from an external device with a USB type.

The communication unit 260 is provided inside the neckband body 110 and analyzes the emotion and the physical state of the user based on the correlation between the EEG signal and the pulse wave signal. The improving care signal is transmitted to the external device through short range communication. In this case, as a short range communication technology, Bluetooth, Radio Frequency Identification (RFID), Infrared Data Association (IrDA), Ultra Wideband (UWB), ZigBee, and the like may be used.

And, although not shown in Figure 1 on the outer surface of the neckband body 110, the flow prevention portion for preventing the neckband body is moved or flow in accordance with the user's movement may be formed in the form of protrusions or irregularities.

3 is a flowchart illustrating an operation of a neckband type wearable healthcare method according to an exemplary embodiment of the present invention.

Referring to FIG. 3, in the neckband type wearable healthcare device 100 according to the present invention, the neckband body 110 first enters a healthcare mode according to a selection operation of a mode button according to a user's operation (S310). ).

In this case, after the power is supplied to each component from the power supply unit 240 provided inside the neckband body 110, the user may enter the healthcare mode according to the selection operation of the mode button.

In addition, the neckband body 110, the power generation unit 230 provided therein detects the vibration according to the user's movement through a vibration sensor, and generates a power using the detected vibration signal to the power supply 240 It can be charged.

In addition, the neckband body 110, the external device and the data via the connector 250 provided in the external or USB type, or the power supply 240 to receive power from the connector 250 to the USB type from the outside can do.

Subsequently, the first earphone unit 160 measures the EEG signal of the user as shown in FIG. 4 through the EEG sensor (S320).

An EEG is a waveform recorded by amplifying and amplifying the electric current generated by the activity of the brain. 4 is a view showing a waveform of the EEG signal measured over time by the first earphone unit according to an embodiment of the present invention. For example, the EEG information may include amplitude of an EEG waveform, frequency information of an EEG waveform, and the like.

Here, the first earphone unit 160 may obtain a plurality of brain wave information. The plurality of EEG information may mean a plurality of EEG information measured at different locations on the scalp in the same time zone. Alternatively, this may mean a plurality of EEG information measured at different time points at the same location on the scalp. Here, the same time zone means that the start time and the last time of the measurement are the same, and another time zone means that at least one of the start time and the last time of the measurement is different.

When the EEG information acquired at the first position in the same time zone is defined as the first EEG information, the EEG information acquired at the second position that is different from the first position may be defined as the second EEG information (see FIG. 4). ).

Alternatively, when the EEG information acquired in the first time zone at the same location is defined as the first EEG information, the EEG information acquired in the second time zone that is different from the first time zone may be defined as the second EEG information (FIG. 4).

Subsequently, the second earphone unit 170 measures the pulse wave signal of the user as shown in FIG. 5 through the pulse wave sensor (S330).

A pulse is a periodic pulsation caused by the heart's pulsation as blood from the heart touches the walls of the arteries. 5 is a view showing the waveform of the pulse signal measured through the second earphone unit according to an embodiment of the present invention. As shown in FIG. 5, pulse information may include waveform information regarding waves. For example, the pulse information may include information about the pulse rate, the amplitude of the pulse waveform, the period of the pulse waveform, the change of the pulse waveform period, the frequency of the pulse waveform, the speed at which the amplitude of the pulse changes, and the like.

Here, the pulse signal is included in the heart information about the heart activity, so the pulse signal may be expressed as the heart information.

Subsequently, the respiratory rate measuring unit 220 detects a respiratory signal for the user's breath through the gyro sensor and measures the respiratory rate from the detected respiratory signal (S340).

Subsequently, the analysis engine unit 130 converts the measured EEG signal and the pulse wave signal into data and analyzes the data (S350).

That is, the analysis engine unit 130 amplifies the acquired brain wave, removes the unwanted wave component from the amplified signal, and converts the signal from which the unwanted wave is removed into a digital signal. The analysis engine unit 130 analyzes the brain waves by performing Fourier transform on the amplified brain waves and calculates output values for each frequency of the brain waves.

The analysis engine unit 130 may acquire the EEG harmonic signal by processing the acquired EEG. Electroencephalogram is an index indicating the degree to which the frequency spectrum of a plurality of brain waves coincide. For example, the EEG harmonic may mean correlation of frequency information between a plurality of EEG waveforms. The phase relationship may represent a phase relationship between a plurality of EEG waveforms, and the degree of symmetry may mean a degree of symmetry between the plurality of EEG waveforms.

The types of brain waves generated in the human brain are divided into gamma waves, alpha waves, beta waves, theta waves, delta waves, infra low fluctuation (ILF), and DC according to frequency bands.

Gamma waves may have frequencies above 30 Hz. Alpha waves are brain waves that occur when humans close their eyes and relax their bodies and can have frequencies between 8 Hz and 12 Hz. Beta waves are most of the brain waves that occur when consciousness is awake and can have frequencies between 13 Hz and 32 Hz. Theta waves occur in shallow sleep and may have frequencies lower than alpha waves (4 Hz to 8 Hz) and are generated at the boundary between perception and dreams. A delta wave is a brain wave that can have a frequency below 4 Hz lower than theta wave and is most measured in sleep or unconsciousness. Slow cortical potential (SCP) can have frequencies below 1 Hz.

There may be a variety of ways to obtain the EEG harmonics.

For example, the analysis engine unit 130 may convert the first EEG information into the frequency domain and the second EEG information into the frequency domain.

At this time, the analysis engine 130 may determine that the more the frequency band in the same range between the first EEG information and the second EEG information, the higher the similarity, and the same range between the first EEG information and the second EEG information It may be determined that the lower the frequency band, the lower the similarity. In addition, EEG harmonics may be calculated using a maximum likelihood method or a cross-correlation method.

For example, EEG harmonics may be obtained by Equation 1 below.

Equation 1 is applied to the case where the EEG information acquired at the first position in the same time zone is defined as the first EEG information, and the EEG information acquired at the second position that is different from the first position is defined as the second EEG information. Can be.

In this case, it is assumed that EEG information is obtained from two channels (x, y).

Here, | CrossPowerSpectrum | is a mutual power spectrum density between channels x and y, and PowerSpectrum (X) and PowerSpectrum (Y) are magnetic power spectral densities of channels x and y.

Where | CrossPowerSpectrum | ² is C _n ² = (a _n u _n + b _n v _n ) ² + (a _n v _n -b _n u _n ) ² = | cospectrum | ² + | quadspectrum | ² a _n and b _n are Fourier cosine coefficients and sine coefficients of the EEG signal x (t) obtained in the channel (x), respectively. U _n and v _n are Fourier cosine coefficients and sine coefficients of the EEG signal y (t) obtained in the channel y different from the channel x, respectively. PowerSpectrum (X) = a _n ² + b _n ² , and PowerSpectrum (Y) = u _n ² + v _n ² .

By the equation 1, the analysis engine 130 may obtain the EEG harmonics based on the EEG information. EEG harmonics may have a value between 0 and 1.

The closer the EEG harmonic value is to 1, the more similar or coincident the frequency spectrum of the two EEGs is. The EEG coherence is an average of values calculated by Equation 1 for a predetermined measurement time in all channel combinations that can be derived from a plurality of channels. EEG harmonics may be measured for each frequency band. Here, the EEG harmonics are obtained by averaging the value calculated by Equation 1 for a predetermined measurement time in, for example, a 171 channel combination derived from two channels.

On the other hand, the phase relationship (phase) can be obtained by the following equation (2).

The phase relationship is the average of values calculated by Equation 2 for a predetermined measurement time in all channel combinations that can be derived from a plurality of channels. The phase diagram may be measured for each frequency band. For example, the phase diagram is an average of values calculated by Equation 2 for a predetermined measurement time in a channel combination derived from two channels.

In addition, an amplitude asymmetry may be obtained by Equation 3 below.

The symmetry is an average of the values calculated by Equation 3 for a predetermined measurement time in all channel combinations that can be derived from a plurality of channels. Symmetry can be measured for each frequency band. For example, Amplitude asymmetry is an average of the values calculated by Equation 3 for a predetermined measurement time in a channel combination derived from two channels.

In addition, power is calculated through FFT (4 seconds Epoch, Hanning Window, Overlapping 50%) after removing noise from the measured EEG, and means a value averaged for a predetermined measurement time. Power may be calculated for each of a plurality of channels. Power can be measured for each frequency band (DC, ILF, delta, theta, alpha, beta, gamma, etc.).

Meanwhile, the analysis engine unit 130 may remove the noise signal from the pulse signal as shown in FIG. 5, convert the noise signal into a digital signal, and analyze the result.

Cardiac harmony is an indicator of pulse rate change rate. A method of acquiring cardiac harmonics based on pulse information may include, for example, referring to FIG. 5, for example, a first waveform in a predetermined section (eg, a first section) and a predetermined section (eg, not completely coincident with the first section). The similarity of the second waveform in the second section) can be measured.

There are many ways to obtain cardiac harmony.

For example, the analysis engine unit 130 may convert the first waveform into the frequency domain (first pulse information) and convert the second waveform into the frequency domain (second pulse information).

In this case, the analysis engine unit 130 may determine that the more the frequency band in the same range between the first pulse information and the second pulse information, the higher the similarity, and the same range between the first pulse information and the second pulse information It may be determined that the lower the frequency band, the lower the similarity. In addition, cardiac harmony may be calculated using a maximum likelihood method or a cross-correlation method.

Cardiac harmony can be obtained by Equation 4 below.

Here, the power at the center of the peak means power in a predetermined band (for example, 0.03 Hz) centered on the frequency with the largest power in the power spectrum (for example, 0.04 to 0.4 Hz) of the pulse information.

The predetermined band centered on the frequency with the highest power in the power spectrum can be appropriately set as needed. For example, the frequency of the peak center power may be used at 0.08 to 0.15 Hz, and 0.04 to 0.26 Hz may be used.

In addition, the power of the entire band means the total power of the power spectrum of the pulse information.

By such an equation (4), the analysis engine unit 130 may obtain the heart harmony degree based on the pulse information. Cardiac harmonics may have a value between 0 and 1. The closer the cardiacity is to a value of 1, the more regular the change in heart rate over time.

Subsequently, the analysis engine unit 130 diagnoses the user's emotion and physical condition according to the measured respiratory rate and the correlation between the brain wave signal and the pulse wave signal (S360).

That is, as shown in FIG. 6, the analysis engine unit 130 uses the heart-brain synchronization information based on the heart harmony and the brain wave harmony, and according to the correlation between the heart harmony and the brain wave harmony, the user's body (health) state. To diagnose. 6 illustrates an example of cardiac-brain synchronization information according to an embodiment of the present invention. In FIG. 6, (a) shows the cardiac harmonics in a predetermined time interval, (b) shows the EEG harmonics in the predetermined time interval, (c) shows the cardiac harmonics in (a), Cardiac-brain synchronization information based on the EEG coordination in (b) is shown. As shown in (c), the x-axis of the graph may mean cardiac harmonics, and the y-axis of the graph may mean electroencephalogram.

That is, through the heart-brain synchronization information, the correlation between heart harmony and brain wave harmony may be grasped. For example, it may be possible to express a linear function model by regression analysis between cardiac harmonics and brain wave harmonics. That is, the heart and brain wave harmonization may be expressed by Equation 5 below.

Here, y means EEG harmonics, and x means heart harmony. a and b can be any rational number to satisfy the relation.

As the convergence is possible with a regression equation as shown in Equation 5, the cardiac-brain synchronism may be greater, and it may be judged as a healthy state. Here, a state that can be fully converged by a regression equation such as Equation 5 may be defined as the highest proximity state, and a state that cannot be converged by a regression equation such as Equation 5 may be defined as the lowest proximity state. have. That is, the degree of convergence to the regression equation as in Equation 5 will be defined as proximity.

According to an embodiment of the present invention, the analysis engine unit 130 may determine the proximity to the first function model on the basis of the heart harmony and the EEG harmonics, through which can determine the heart-brain synchronization.

The same method can be applied to the cardiac and phase relationship, cardiac and symmetry, or cardiac and power to determine the correlation between the cardiac and the brain.

Cardiac-brain synchronization information may be an indicator of the state of health considering both autonomic and central nerves. Because cardiac harmonization can be a health indicator for the autonomic nervous system, and EEG harmonics can be a health indicator for the central nervous system, since cardiac and brain harmonization information is considered at the same time. to be. For example, the analysis engine 130 may determine cardiac-brain synchronization information and determine a health state based on the proximity.

On the other hand, the higher the cardiac harmony may be determined to be a healthy state. In addition, even if the cardiac harmonization is increased, it may be determined that the state in which the EEG harmonization is not increased is unhealthy. In other words, it is possible to determine the state of health by grasping the correlation between heart harmony and brain wave harmony and displaying the heart-brain synchronization information in the form of a graph.

Subsequently, the analysis engine unit 130 controls to output a care signal for improving emotion and physical state (S370).

That is, the analysis engine unit 130 reads the sound source data corresponding to the care signal from the storage unit 140 storing the sound source signal corresponding to the care signal for improving the emotion and the body state as data, and the first earphone unit. The controller 160 may control the output to the 160 and the second earphone unit 170.

For example, the analysis engine unit 130 outputs the sound source signal for enhancing the alpha wave or the sound source signal for improving the sad or depressed state to the first earphone unit 160 and the second earphone unit 170. To control.

In addition, the analysis engine unit 130 may transmit the care signal for improving the emotion and the physical state to the external device through short-range communication through the communication unit.

Therefore, the user hears the sound source signal suitable for his or her physical state or the sound source signal for improving the sad or depressed state through the first earphone unit 160 and the second earphone unit 170, thereby improving the emotion and the physical state. It will be able to improve.

Meanwhile, although not shown in the drawings, the present invention may be modeled by learning the relationship between the cardiac harmonics and the EEG harmonics analyzed by the analysis engine unit 130, and predicting other data by inputting only one data through the modeled model. It can be provided with a learning device or a learning server.

That is, the learning device (server) accumulates and stores the measured heart harmony and the brain wave harmonics daily, and then aggregates the data in weekly, monthly, and yearly units. Can be stored in the database.

Next, the learning apparatus (server) may be classified into a modeling data group for generating a model by modeling the training data and a verification data group for verifying the generated model.

In addition, the learning apparatus (server) learns the cardiac harmonics and the brain wave harmonics on a weekly or monthly basis with respect to the modeling data group, and calculates an estimation function equation (H (x)) indicating the relationship between the heart harmonics and the brain wave harmonics. Can be.

Next, the learning apparatus (server) calculates distance values ([H (x) -y (x)] 2) between the EEG harmonics for each user and the estimated data corresponding to the graph of the estimation function H (x). Calculate each of the calculated distance values and divide them by the number of data (m) according to the number of users. The value of the slope (a) and the intercept (b) of can be calculated.

Subsequently, the learning apparatus (server) substitutes the calculated slope (a) and intercept (b) values into the estimation function to determine the selection function (y = ax + b), and calculates the EEG harmonics according to the heart harmony. A selection model can be generated to calculate.

The learning apparatus (server) substitutes each cardiac harmonic degree x calculated for each user r into a selected model, calculates an EEG harmonic degree y for each user, and an EEG harmonic degree y for each user. ) Is compared and listed, and according to the result of the listing, it is possible to select a week or month in which the EEG is the highest.

In addition, the learning apparatus (server) calculates the cardiac harmonics (x) for each user for the verification data group, and substitutes the calculated cardiac harmonics (x) into the selected model, respectively, and the EEG harmonics (y). ) Are calculated, and for each cardiac harmonic (x) and brain wave harmonic (y) calculated for each user, distance values with a graph of the estimated function are calculated, and the distance average values for the calculated distance values are calculated. Calculate and compare the calculated distance average value with the minimum distance value, and verify the selected model according to whether or not the difference between the calculated distance average value and the minimum distance value is within the error range. have.

In addition, the learning apparatus (server) reclassifies the classified modeling data group into three fields of weekly, monthly, and year according to the date classification, and for each of the reclassified modeling data groups, the cardiac harmonics (x) for each user (x). ), And EEG harmonics (y) can be learned, and an estimation function (H (x)) representing the relationship between heart harmony (x) and EEG harmonics (y) can be calculated for each of the three fields.

Next, the learning apparatus (server) has a distance value (H (x) −) between the EEG harmonics data (y) for each user in each of three fields and the estimated data corresponding to the graph of the estimation function (H (x)). y (x)] 2) are calculated, and the calculated distance values are summed and divided by the number of data (m) according to the number of users (r). The slope (a) and intercept (b) values of the functional equations having the adjacent cardiac harmonics (x) and the EEG harmonics (y) can be calculated according to three fields, respectively.

In addition, the learning apparatus (server) substitutes the slope (a) and the intercept (b) values calculated according to the three fields into the estimation functions for each of the three fields, respectively, to determine the selected function equation (y = ax + b). In addition, a selection model that calculates EEG harmonics according to heart harmony can be generated for each of three fields according to week, month and year.

As described above, according to the present invention, a user wears a neck, such as a necklace worn on a person's neck, and measures biometric information such as brain waves, pulse waves, respiratory rate of the user, and the user based on the measured biometric information. A neckband type healthcare wearable device and a method thereof for managing health of a person can be realized.

Those skilled in the art to which the present invention pertains may understand that the present invention may be embodied in other specific forms without changing the technical spirit or essential features thereof, so that the embodiments described above are exemplary in all respects and are not intended to be limiting. Should be. The scope of the present invention is shown by the following claims rather than the detailed description, and all changes or modifications derived from the meaning and scope of the claims and their equivalents should be construed as being included in the scope of the present invention. .

100: neckband type healthcare wearable device 110: neckband body
112: play button 114: call button
116: volume button 118: selection button
120: power button 160: first earphone unit
170: second earphone unit 210: storage unit
220: respiratory rate measuring unit 230: power generation unit
240: power supply 250: connector
260: communication unit

Claims (15)

A neckband body formed along an arc of an open circle, having one or more buttons on a surface thereof, and having one or more components therein electrically coupled to the one or more buttons;
An EEG sensor for measuring an EEG of a user around the neckband body;
A pulse wave sensor for measuring a pulse wave of a user around the neckband body;
A first earphone part electrically connected to one end of the neckband body and having a first speaker for outputting sound;
A second earphone unit electrically connected to the other end of the neckband body and having a second speaker for outputting sound; And
It is provided inside the neckband body, the brain wave signal measured by the brain wave sensor is converted into data and analyzed, the pulse wave signal measured by the pulse wave sensor is converted into data and analyzed, the brain wave signal and pulse wave signal An analysis engine unit configured to diagnose the emotion and the physical state of the user based on the heart-brain synchronization information based on the control unit, and output a care signal for improving the emotion and the physical state;
Including,
The cardiac-brain synchronization information is an index indicating a health state in consideration of autonomic and central nerves at the same time,
Neckband type healthcare wearable device.
The method of claim 1,
The EEG sensor is installed on any one of the neckband body, the first earphone unit, and the second earphone unit, and the pulse wave sensor is also any one of the neckband body, the first earphone unit, and the second earphone unit. Neckband type healthcare wearable device installed in the
The method of claim 1,
A storage unit provided inside the neckband body and storing a sound source signal corresponding to a care signal for improving the emotion and the body state as data;
Further comprising, a neckband type healthcare wearable device.
The method of claim 1,
A respiratory rate measurement unit provided inside the neckband body to detect a respiratory signal for respiration of the user with a gyro sensor, and measure respiratory rate from the detected respiratory signal;
Further comprising, a neckband type healthcare wearable device.
The method of claim 1,
A power generation unit provided inside the neckband body and configured to generate vibration by detecting a vibration according to the movement of the user and generating power using the detected vibration signal;
Further comprising, a neckband type healthcare wearable device.
The method of claim 1,
The one or more buttons may include a play button for playing, stopping or pausing a sound source; A call button for operating the neckband body in a call mode; A volume button for adjusting a volume of a sound output through the first earphone unit or the second earphone unit; A selection button for selecting a next song or a previous song for the sound source; A power button for instructing power to be supplied; And a mode button for selecting a health care mode or a normal mode.
The method of claim 1,
A power supply unit provided inside the neckband body and supplying power to the one or more buttons and components provided inside the neckband body;
Further comprising, a neckband type healthcare wearable device.
The method of claim 1,
A care signal provided inside the neckband body, the analysis engine unit diagnosing the user's emotion and body condition according to the correlation between the brain wave signal and the pulse wave signal to improve the emotion and body state to an external device Communication unit for transmitting in the near field communication; And
A connector for transmitting and receiving data to or from the external device with a USB type;
Further comprising, a neckband type healthcare wearable device.
The method of claim 1,
The neckband type healthcare wearable device having an outer surface of the neckband body in the form of a protrusion or an uneven shape to prevent the neckband body from being moved or moved according to the movement of the user.
It is formed along an arc of an open circle, and has at least one button and a connector on an outer surface thereof, and has a storage unit, a respiration rate measuring unit, a power generation unit, a power unit, and a communication unit therein. Neckband type wearable healthcare service method of neckband body combined with
(a) entering the healthcare mode according to a selection operation of a mode button by the neckband body;
(b) measuring, by the first earphone unit, an EEG signal of a user through an EEG sensor;
(c) measuring, by the second earphone unit, a pulse wave signal of the user through a pulse wave sensor;
(d) the respiratory rate measuring unit detecting a respiratory signal for the user's breathing through a gyro sensor and measuring the respiratory rate from the detected respiratory signal;
(e) analyzing and converting the measured brain wave signal and pulse wave signal into data by an analysis engine unit;
(f) analyzing, by the analysis engine unit, the emotion and the physical condition of the user based on the measured respiratory rate and heart-brain synchronization information based on the brain wave signal and the pulse wave signal; And
(g) controlling the analysis engine unit to output a care signal to improve the emotion and the physical condition;
Including,
The cardiac-brain synchronization information is an index indicating a health state in consideration of autonomic and central nerves at the same time,
Neckband type wearable healthcare method.
The method of claim 10,
In the step (g), the analysis engine unit reads the sound source data corresponding to the care signal from the storage unit storing the sound source signal corresponding to the care signal for improving the emotion and body state as data, and the first earphone unit. And controlling the output to the second earphone unit.
The method of claim 10,
In the step (a), after the power is supplied from the power supply unit provided inside the neckband body to the component provided inside the neckband body, the neckband body is subjected to the healthcare according to the selection operation of the mode button. Neckband type wearable healthcare method to enter mode.
The method of claim 10,
In the step (a), the power generation unit provided in the neckband body detects the vibration according to the movement of the user through a vibration sensor, and generates power using the detected vibration signal to charge the power supply unit. , Neckband type wearable healthcare method.
The method of claim 13,
In the (a) step, the neckband body, the USB to transmit and receive data with an external device through a connector provided in the external type, or to receive power from the external USB type through the connector to charge the power supply unit, Band type wearable healthcare method.
The method of claim 10,
In the step (g), the analysis engine unit, the neckband type wearable healthcare method for transmitting a care signal for improving the emotional and physical state to the external device via a communication unit in the short-range communication.

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