KR20240085329A - Dual Wearable Bands Supporting Bio-Signal Correction Function - Google Patents

Abstract

A first wearable band and a second wearable band, each equipped with a sensor unit for sensing biological signals and wirelessly connected to a terminal supporting multi-pairing, wherein the first and second wearable bands are detected by the first wearable band. a control unit that analyzes the accuracy of the first bio-signal and the second bio-signal detected by the second wearable band, selects a bio-signal with high accuracy as a reference signal, and corrects the remaining bio-signals with the reference signal; and a communication unit that transmits the reference signal and the bio-signal corrected by the error correction unit to the terminal. A dual wearable band including a is disclosed.

Description

Dual Wearable Bands Supporting Bio-Signal Correction Function}

The present invention relates to a dual wearable band that is worn on both wrists and measures biological signals. In particular, it relates to a dual wearable band that measures biological signals from both wrists and supports error correction based on biological signals measured with high accuracy. will be.

Sleep plays an important role in maintaining physical and emotional health and immunity. It recovers fatigue from the brain and body tissues that occur during wakefulness and conserves energy, enabling normal daily life. It is also central to the development and maintenance of learning and memory abilities. Responsible for the function.

Insufficient sleep or poor sleep quality can cause physical problems such as headaches, fatigue, difficulty acquiring new knowledge or learning, decreased activity level, and daytime sleepiness, or emotional difficulties such as anxiety, depression, and helplessness. Patients with insomnia are known to have a 9.82 times higher risk of developing clinically serious depression than the general population, which is known to cause a decline in quality of life. When depression occurs, sleep quality further deteriorates, falling into a vicious cycle.

Accordingly, in the treatment of sleep disorders, it may be an important factor to accurately analyze each individual's sleep state and identify factors that affect sleep.

Because sleep disorders occur while you are sleeping, it is difficult for even you to identify the symptoms, so for an accurate diagnosis, polysomnography, which comprehensively tests brain waves, muscle movements, breathing, electrocardiogram, and oxygen saturation during sleep, can be used. there is. However, polysomnography is not easy to test and treat due to the high cost of analysis.

Accordingly, there is a demand for the development of a system that can overcome the above limitations and effectively analyze sleep quality. In particular, the development of sleep analysis methods and devices to analyze the quality of sleep of users with sleep disorders, analyze the causes thereof, and provide them to users can be very important in the prevention, diagnosis, and treatment of sleep disorders. .

Registered Patent Publication No. 10-1771835 (Biological signal-based sleep interaction impact analysis method, hereinafter referred to as Prior Art 1) is based on analysis based on the combined characteristics of various biological signals measured from two people sleeping in one space, In order to provide various indicators to judge the interaction of human sleep, it is a computer-based biosignal-based sleep interaction analysis method. The method uses a computer input/output device to collect biometric data from two people sleeping in the same space. Respiration, electrocardiogram, and electroencephalogram signals are measured, and the signals are processed to extract biometric information such as breathing interval, heartbeat position, heartbeat interval, band EEG, and sleep stage, and phase information and moment of biometric information from the extracted information. A biometric information acquisition step of acquiring phase information; Using a computer processing device, synchronization analysis technology is applied to the phases of the same biometric information measured from the two people to calculate a synchronization index, and when the synchronization index value is greater than a predetermined value, it is determined that synchronization has occurred, and the synchronization section is determined. A synchronization characteristic analysis step between biological systems that is detected and quantified by calculating the ratio divided by the total sleep section; Using a computer processing device, the cross-correlation of the sleep stages, heart rate intervals, breathing intervals, and band brain waves of the two people is analyzed, the sleep stages of the two people are smoothed, the cross-correlation is analyzed, and the cross-correlation of the two people is analyzed. The heart rate interval is extracted from the heart rate position, the average heart rate is calculated in 30-second increments, the average heart rate is smoothed to calculate the average heart rate trend, and the average heart rate trend is cross-correlated to analyze the correlation, and the two The cross-correlation is analyzed by calculating and smoothing the 30-second power of the human's band brain waves, and calculating and smoothing the average breathing rate in the breathing interval of the two people in 30-second units and analyzing the cross-correlation to determine the delay time of the cross-correlation A correlation analysis step between biological systems calculated using correlation coefficient values; Using a computer processing device, the degree to which the other person's biometric information contributes to changes in the biometric information phase of one of the two people is evaluated using the EMA (Evolution Map Approach) method, and directional calculations are made every 30 seconds. Among the biometric information, the heart rate variability index is calculated from the heart rate interval to analyze the influence of the autonomic nervous system, the central nervous system influence is analyzed by calculating the coherence index from the band EEG, and the strength of the influence, which is the direction of the directional calculation, is determined. In the analysis of the influence of the autonomic nervous system and the influence of the central nervous system, the positive or negative influence is calculated through the ratio of the difference between the heart rate variability index and the coherence index for each sleep stage according to the difference in the directional calculation, between biological systems. Impact characteristics analysis stage; And using a computer processing device, calculate the number and duration of changes in the sleep stage of the other person to the same stage while the sleep stage of one of the two people changes, and calculate the number and duration into the total sleep. It includes a sleep interaction analysis step that converts the information into a ratio, and when measuring the signal in the biometric information acquisition step, the awakening section of one of the two people is excluded as a distortion section, and the synchronization section is measured during sleep. A biosignal-based sleep interaction analysis method is disclosed, which is established between one biosignal.

Prior art 1 is a method of investigating the influence of one party's sleep disorder or deep sleep on the other person, that is, mutual influence during sleep, in family members such as couples, brothers, and sisters who sleep in the same bed or in adjacent beds. It is far from a technology that can infer a diagnosis of depression by checking a person's sleep status.

Registered Patent Publication No. 10-1771835 (announcement date: August 25, 2017)

Jeong Soo-hyun, Park Jeong-hyun, Yoon Hyeong-jun, Kim Jeong-ho, Kim Nam-cheol, and Kim Sang-hoon. ‘The relationship between sleep quality and depressive symptoms in college students: The moderating effect of positive psychology’, Biological Therapeutic Psychiatry Vol. 24, No. 3, 2018.

The representative problem that the present invention aims to solve is to monitor health status and infer depression and obsessive-compulsive disorder by measuring the user's biosignals. In order to increase the accuracy of the measured biosignals, the biosignals of both wrists are measured with high accuracy. The goal is to provide a dual wearable band that supports error correction based on biometric signals.

As a means of solving the above problem, the dual wearable band proposed by the present invention includes a first wearable band and a second wearable band, each equipped with a sensor unit for sensing biological signals, and wirelessly connected to a terminal that supports multi-pairing.

In particular, the first and second wearable bands analyze the accuracy of the first bio-signal detected in the first wearable band and the second bio-signal detected in the second wearable band, select the bio-signal with high accuracy as the reference signal, and It includes a control unit that corrects the remaining bio-signals with a signal, and a communication unit that transmits the reference signal and the bio-signal corrected by the control unit to the terminal.

In the dual wearable band as described above, the control unit can accurately determine that the intensity of light reflected by the PPG operation of the sensor unit is greater than the set intensity.

In addition, if the intensity of light reflected by the PPG operation of the sensor unit is less than the set intensity, the control unit may transmit a message recommending that the wearable band be worn closely with the wrist to the terminal through the communication unit.

In addition, the sensor unit may include one or more of an acoustic vibration sensor, an optical sensor, a pressure sensor, a Hall sensor, and an acceleration sensor that detects the state of blood vessels or muscles in the wrist, and the biosignals sensed by the sensor unit include heart rate, It may include at least one of electrocardiogram, electromyogram, respiration, and oxygen saturation.

Meanwhile, while the sensor unit is operating, the control unit may unpair from the terminal a wearable band that has stopped detecting biometric signals for a set time among the first wearable band or the second wearable band.

Alternatively, if either the first bio-signal or the second bio-signal exceeds an error range compared to the reference signal, the wearable band transmitting the signal may be unpaired from the terminal.

At this time, the wearable band that has been unpaired from the terminal can be automatically paired with another preset terminal.

A representative effect of the present invention is that error correction is supported in measuring the user's biosignals, thereby improving accuracy.

Additionally, since depression is inferred based on biosignals with improved accuracy, diagnostic accuracy is improved and can be used for early response to depression.

In addition, since you normally wear a dual wearable band with someone close to you and use it in dual mode when you need to accurately measure biosignals, it is suitable for family members and can be used in dual mode and then worn separately to measure the biosignals of two wearable bands. If they are different, they are automatically paired to the original user's smartphone, making it convenient to use.

1 is a schematic configuration diagram of a dual wearable band according to the present invention;
Figure 2 is a diagram showing an example of operation of a dual wearable band according to the present invention;
Figures 3 to 6 are diagrams showing further examples of various operations of the dual wearable band according to the present invention.

The present invention relates to a dual wearable band that supports a bio-signal correction function. In particular, in the case of the existing single band, it improves the problems such as the high bio-signal error and the need for grounding for electrocardiogram measurement, as well as heart rate and respiration during sleep. It measures sleep and sleep time and provides related data for users to monitor.

Hereinafter, preferred embodiments of the present invention (hereinafter referred to as dual wearable band) will be described in detail with reference to the attached drawings.

Referring to FIG. 1, the dual wearable band includes a first wearable band 10 and a second wearable band each equipped with sensor units 11 and 12 for sensing biological signals and wirelessly connected to a terminal 200 that supports multi-pairing. Includes a wearable band (20). The terminal 200 may be any one of a smartphone, tablet PC, desktop PC, and laptop.

The first and second wearable bands (10, 20) analyze the accuracy of the first bio-signal detected by the first wearable band (10) and the second bio-signal detected by the second wearable band (20) and A control unit (12, 22) that selects a bio signal as a reference signal and corrects the remaining bio signals with the reference signal, and sends the reference signal and the bio signal corrected by the control unit (12, 22) to the terminal (200). It includes communication units 13 and 23 that transmit. Here, accuracy may mean, for example, that the intensity of light reflected by the operation of PPG (Photoplethysmogram) is above the set intensity or is received consistently. Therefore, high accuracy means that the intensity of reflected light is at the set intensity. Above, it may mean a state in which the intensity of light is greater when compared.

The first biosignal of the first wearable band 10 may be provided to the second wearable band 20 through the terminal 200, and the second biosignal of the second wearable band 20 may also be provided to the terminal 200. It can be provided to the first wearable band 10 through. Therefore, the control units 12 and 22 analyze the accuracy of the first bio-signal detected by the first wearable band 10 and the second bio-signal detected by the second wearable band 20, and select the bio-signal with high accuracy as the reference signal. , and the remaining biosignals can be corrected using the above reference signal. This process can also be performed in the terminal 200. That is, the first and second bio-signals of the first and second wearable bands 10 and 20 are transmitted to the terminal 200, and the terminal 200 analyzes the accuracy of the first and second bio-signals and selects bio-signals with high accuracy. is selected as the reference signal and the remaining biosignals are corrected with the reference signal.

The first and second wearable bands 10 and 20 are provided in a form that can be placed on the wrist and can collect the wearer's biological signals. The collected biological signals can be processed in the first and second wearable bands 10 and 20 to support specific functions. Additionally, the collected bio-signals may be transmitted to the terminal 200 and processed to perform specific functions on the first and second wearable bands 10 and 20. For example, the reflected light due to the PPG operation of the sensor units 11 and 21 may be reflected by the processing of the terminal 200 or the self-judgment of the control units 12 and 22 of the first and second wearable bands 10 and 20. If the intensity is less than the set intensity, a message recommending that the first and second wearable bands 10 and 20 be worn closely to the wrist may be output as shown in FIG. 2 . Alternatively, the recommendation message may be output from the terminal 200.

The sensor units 11 and 21 may include one or more of an acoustic vibration sensor, an optical sensor, an electromyography sensor, a pressure sensor, a Hall sensor, and an acceleration sensor that detects the state of blood vessels or muscles in the wrist. Additionally, the biosignals sensed by the sensor units 11 and 21 may include at least one of heart rate, electrocardiogram, electromyogram, respiration, and oxygen saturation.

The first and second wearable bands 10 and 20 can more accurately detect biosignals detected at the wrist due to the sensor units 11 and 21 and the message recommendation.

In addition, by using an electromyography sensor and an optical sensor, an electromyography sensor and an acoustic vibration sensor, or an electromyography sensor and an acceleration sensor, it is possible to more accurately detect biosignals corresponding to movement information of the extensor digitorum or extensor digitorum small, which are difficult to detect with only an electromyography sensor.

An acoustic vibration sensor is a sensor for measuring vibration on the skin surface and may include a piezo sensor or microphone, a laser distance sensor, an accelerometer, or a muscle vibration sensor (mechano-myography, MMG). Muscle vibration sensors can measure non-invasively by measuring micro-vibrations caused by changes in the volume of muscle fibers that appear when muscles are activated. Muscle vibration sensors can support signal collection for measuring muscle fatigue and identifying movement intentions. Muscle vibration sensors can measure even minute muscles in a small size. Due to differences in bone density and muscle thickness, different parts of the body may produce unique sounds. Muscle vibration sensors can recognize differences between sounds to detect, for example, the position of a finger. These muscle vibration sensors can determine response by analyzing mechanical vibration according to location. When a finger, etc., touches a specific object, a subtle acoustic signal is generated within the human body. This signal spreads through the skin surface and arm muscles and bones, and then changes in wavelength as it passes through soft muscle tissue and hard joints. The muscle vibration sensor can calculate the difference in bone density and muscle mass and trace back to detect the point where the sound first occurred.

Along with muscle contraction, subtle vibrations occur on the body surface of active muscles. Vibration can be caused by pressure waves that occur as the muscle fibers of the contracting muscle expand and deform laterally. Muscle vibration sensors can evaluate muscle activity by recording and analyzing vibrations in the subtle low-frequency band (less than 100 Hz). Electromyogram (EMG) sensors reflect the electrical state of active muscles, but muscle vibration sensors can reflect the mechanical state of active muscles. Because muscle vibration sensors detect biosignals related to the mechanical contraction of muscle fibers, they can support the determination of mechanical aspects of muscle activity strategies, such as motor unit recruitment and firing rate.

Acoustic vibration sensors may include sensors that detect tremor as vibrations recorded on the body surface of the human body. Tremor can be classified into rest tremor and action tremor depending on the presence or absence of significant muscle activity. Similar to muscle vibration, there is forcetremor (FT), which is a tremor that occurs during muscle contraction, and has a frequency range of 3~6Hz related to body inertia, stretch reflex, etc., and 8~12Hz related to rhythmic input from the center to motor neurons. can appear at the same time. Therefore, the signal sensed by the acoustic vibration sensor may include the FT waveform mixed with the MMG waveform, which measures low-frequency vibration due to lateral changes in muscle fibers. The isometric tremor waveform is a type of physiological artifact that supports the detection of sensing signals related to the movement of the antagonist muscle rather than the agonist muscle in muscle antagonism. Regarding the vibration characteristics of muscle tissue, as muscle activity increases, the damping coefficient of soft tissue increases and attenuates resonance.

Therefore, the effect of isometric tremor may be greater on antagonist muscles with less activity than on agonist muscles with greater activity. The acoustic vibration sensor may further include a condenser microphone (MIC), an acceleration sensor (ACC), etc. A condenser microphone attaches an air chamber to a sensor and measures changes in air pressure in the chamber due to body surface vibration. Acceleration sensors may be more affected by isometric tremors than condenser microphones. By comparing antagonist and agonist muscles during fatigued muscle contraction, the acoustic vibration sensor compares the effect of isometric tremor on MMG (MMG MIC and MMG ACC, respectively) measured with a condenser microphone (MIC) and an acceleration sensor (ACC) to determine fatigue, etc. Supports finding the value of .

The electromyography sensor can perform electromyography measurements around the radial and ulnar arteries. The electromyogram sensor can acquire electromyograms from the forearm extensors. For electromyography sensing of the forearm extensor muscle, the attachment location of the electromyogram sensor can be attached between the digital extensor muscle and the small extensor muscle of the forearm extensor muscle involved in finger movement, and signals involved in finger movement can be measured. The electromyography sensor can measure electromyography of the wrist's thumb-direction deflection or thumb-direction deflection.

Optical sensors measure muscle activation optically. When light is emitted from the skin non-invasively, some of it is transmitted through skin tissues such as skin, subcutaneous fat, and muscles, and some of it is reflected. The optical properties of skin tissues other than muscles do not change according to the movement of the human body, but the optical properties of muscles change according to the principle shown above, so the degree of muscle activation can be measured using the amount of reflected light. To explain this in more detail, looking at the muscle activation process, nerve signals containing movement-related information are transmitted from the brain through the central nervous system to movement-related muscles extending to each region and stimulated. In a muscle activated by stimulation, the actin that makes up the I-band inside the muscle fiber and the myosin that makes up the A-band pull on each other, causing the muscle to contract, causing the entire muscle fiber bundle to become shorter and thicker. Accordingly, the muscles become denser and stronger due to the concentration of muscle fibers. This shape simultaneously results in a change in optical properties, and the reflection and transmittance of light changes due to differences in muscle density. In addition, some of the light emitted from the skin surface is transmitted and absorbed depending on the optical characteristics of each epidermis, muscle, blood vessel, and bone, and some is reflected by each medium. Among these, the light reflected from each medium is acquired through a light receiving unit attached right next to the light emitting unit. At this time, in tissues such as epidermis or bone, the optical properties do not change even when the human body moves, and in the case of vascular tissue, a small alternating current signal is generated according to the heartbeat. However, as mentioned above, in muscle tissue, the reflectance, an optical characteristic, changes due to density changes due to movement and muscle thickness changes, which changes the amount of light obtained from the light receiver. Due to this change, the magnitude value of the signal that the optical sensor senses increases when the muscle contracts, and conversely, the magnitude value of the signal it senses decreases when the muscle relaxes.

Optical sensors detect sensing values using characteristics such as muscle movement, bone movement, and hemoglobin light transmission or reflection. Optical sensors can support recognition of finger motion using finger tendon changes (finger flexor tendons).

The optical sensor may include a pulse sensor. The pulse sensor may be comprised of a high-brightness LED. The pulse sensor supports pulse measurement and oxygen saturation measurement. Pulse sensors include pulse oximeter sensors. The pulse oximeter sensor supports pulse and oxygen saturation measurement using peripheral blood flow (Photoelectric lethysmography: PPG).

The pulse sensor supports non-vascular measurement of blood oxygen saturation by applying light of two different wavelengths from a semiconductor device to the fingertip. Oxidized haemoglobin (HbO2) and reduced hemoglobin (Hb) in the blood have different spectral characteristics when irradiated with light with a wavelength between 500 nm and 1000 nm.

-HbO2 and Hb show different patterns in light absorption rate, and the amount of blood flowing into the finger through the artery changes with the heartbeat. The photodiode placed in the light receiving part of the pulse sensor supports the estimation of pulse by measuring the output voltage changed in proportion to the amount of light that changes during the incident process depending on the amount of Hbo2 and Hb in the blood in proportion to the blood volume.

Additionally, the pulse sensor supports calculating oxygen saturation in response to changes in the amount of light.

Hall sensors can support blood pressure and pulse measurement. The Hall sensor can be placed on the radial protrusion or ulnar protrusion of the wrist (the bone that protrudes from the bottom of the wrist) to measure the pulse wave of the radial artery. The Hall sensor 114 may include a semiconductor made of indium antimonide (InSb), indium arsenide (InAs), germanium (Ge), silicon (Si), etc. Since the Hall sensor can measure the strength of a magnetic field using the Hall electromotive force caused by a magnetic field, it can measure the magnetic field or the magnetic field of a small part, and when a change in the magnetic field is due to location, etc., it is possible to measure these positions. The Hall sensor uses a magnetic Hall element to obtain electrical signals from changes in voltage due to changes in the position of a permanent magnet placed on the radial artery. The electrical signal refers to the waveform signal of the pulse, and this signal can be differentiated through the hardware of the circuit to obtain only signals based on changes in the magnetic field.

Meanwhile, the chemical receptor located in the aortic body, one of the sensory nervous systems that regulate blood pressure, detects an increase in CO2 and a decrease in O2, and blood volume increases for smooth oxygen supply, causing blood pressure to rise. To increase blood supply, the heart rate increases, which also increases the pulse rate and increases blood pressure. The Hall sensor distinguishes pulse waves according to their shape by using the characteristic of the separation time difference between the main pulse wave of the radial artery leaving the heart and the reflected wave reflected from the abdominal artery to the radial artery (in the case of high blood pressure, they appear to merge together). Supports you to perform. In addition, through the above-mentioned characteristics, it is possible to know the blood vessel characteristics of an individual and helps to know the general characteristics of blood pressure.

The acceleration sensor may include a 3-axis linear acceleration sensor (elimination of gravity). The acceleration sensor supports motion measurement for wrist twists, hand movements, etc. An accelerometer is a sensor that measures acceleration in a given direction, and can obtain acceleration information according to the user's motion of moving the device.

Figures 3 to 6 are diagrams showing other various examples of operation of the dual wearable band according to the present invention. Figure 3 shows that bio-signals are detected in either the first wearable band 10 or the second wearable band 20. It indicates an operational relationship in which pairing is canceled after a certain period of time in a state where pairing is not performed.

This operational relationship assumes that the sensor units 11 and 21 are in operation. That is, among the first wearable band 10 or the second wearable band 20, the wearable band in which bio-signal detection has stopped for a set time is unpaired with the terminal 200. For example, it is checked whether a signal is detected by the sensor unit 11 of the first wearable band 10 (S11), and if no signal is detected, it is checked whether a certain amount of time has elapsed since no signal was detected (S12). At this time, if a certain amount of time has not elapsed, it is checked whether a signal is detected, and if a certain amount of time has elapsed from the point in time when the signal has not been detected, the first wearable band 10 releases the pairing with the terminal 200.

This situation may mean that the user has worn the first wearable band 10 so loosely that a signal is not detected, or has taken off the first wearable band 10. Therefore, when worn loosely, there is no signal detection despite the tight wearing message, so pairing is canceled to block unnecessary calculation processes performed for error correction, thereby preventing overload or power loss of the first wearable band 10. Alternatively, when the device is not worn, pairing is canceled, so the process of unpairing with the previous terminal is omitted when pairing with another terminal, thereby reducing the convenience and time of pairing with another terminal.

Figure 4 shows the process of unpairing when the biological signals are detected and the signals are normal, but the biological signals collected from the first and second wearable bands 10 and 20 are clearly different. In the case of FIG. 4, this is a process in a state in which multi-pairing is performed on one terminal 200. Taking the first wearable band 10 as an example, it is checked whether a biological signal is detected (S11) and whether the signal is normal. (S14), it is checked whether the error range exceeds the set error range when compared with the biological signal of the second wearable band 20 (S15), and if it does not exceed the error range, a signal is transmitted to the terminal 200 ( S16), otherwise pairing is canceled (S17). Pairing is canceled when the biosignal of the first wearable band 10 exceeds the error range when compared with the reference signal of the second wearable band 20, and the first wearable band 10 is worn by another person. Therefore, canceling pairing is also desirable for other people to quickly pair.

In the case of Figures 5 and 6, it is confirmed whether pairing has been released (S18), and if pairing is confirmed, pairing with another terminal is automatically performed (S19). At this time, it is assumed that the other terminal must be registered in advance, and for this purpose, the first and second wearable bands 10 and 20 may be equipped with an auto-switching unit for automatic pairing. The control units 12 and 22 maintain multi-pairing during sleeping time, and when waking up in the morning, the first and second wearable bands 10 and 20 are connected to the terminal 200 through the auto switching unit when the first and second wearable bands 10 and 20 are in the same situation as Figures 3 and 4. As soon as you cancel pairing, it immediately pairs with another pre-registered terminal.

As described above, although the embodiments have been described with limited examples and drawings, various modifications and variations can be made by those skilled in the art from the above description. For example, the described techniques are performed in a different order than the described method, and/or components of the described system, structure, device, circuit, etc. are combined or combined in a different form than the described method, or other components are used. Alternatively, appropriate results may be achieved even if substituted or substituted by an equivalent.

Therefore, other implementations, other embodiments, and equivalents of the claims also fall within the scope of the claims described below.

10: First wearable band
20: Second wearable band
11,21: Sensor unit
12,22: Control unit
13,23: Department of Communications
200: terminal

Claims (8)

It includes a first wearable band and a second wearable band, each equipped with a sensor unit for sensing biological signals and wirelessly connected to a terminal that supports multi-pairing,
The first and second wearable bands are,
Analyze the accuracy of the first bio-signal detected by the first wearable band and the second bio-signal detected by the second wearable band, select the bio-signal with high accuracy as the reference signal, and correct the remaining bio-signals with the reference signal. a control unit that does;
a communication unit transmitting the reference signal and the bio-signal corrected by the control unit to the terminal;
Dual wearable band including. According to paragraph 1,
A dual wearable band in which the control unit determines with accuracy that the intensity of light reflected by the PPG operation of the sensor unit is greater than the set intensity. According to paragraph 2,
If the intensity of light reflected by the PPG operation of the sensor unit is less than the set intensity, the control unit transmits a message recommending that the wearable band be worn closely with the wrist to the wearable band or to the terminal through the communication unit. Dual wearable band. According to paragraph 1,
The sensor unit is a dual wearable band including one or more of an acoustic vibration sensor, an optical sensor, a pressure sensor, a Hall sensor, and an acceleration sensor that detects the state of blood vessels or muscles of the wrist. According to paragraph 1,
The biological signals sensed by the sensor unit are:
A dual wearable band that includes at least one of heart rate, electrocardiogram, electromyogram, respiration, and oxygen saturation. According to paragraph 1,
With the sensor unit in operation,
A dual wearable band, wherein among the first wearable band or the second wearable band, the wearable band that has stopped detecting biological signals for a set time is released from pairing with the terminal. According to paragraph 1,
A dual wearable band in which, when either the first bio-signal or the second bio-signal exceeds an error range compared to the reference signal, the wearable band transmitting the corresponding signal is unpaired from the terminal. According to clause 6 or 7,
A dual wearable band, wherein the wearable band that has been unpaired from the terminal includes an auto-switching unit that automatically pairs with another preset terminal.