Apparatus and method for estimating biometric information

An apparatus configured to estimate biometric information includes a sensor configured to measure a light signal reflected from a subject and a temperature of the subject, and a processor configured to perform temperature correction on the light signal reflected from the subject based on the temperature of the subject using a light signal-temperature relationship between the light signal reflected from the subject and the temperature of the subject to thereby obtain a temperature-corrected light signal, and estimate the biometric information of the subject based on the temperature-corrected light signal.

CROSS-REFERENCE TO RELATED APPLICATION(S)

This application claims priority under 35 USC § 119(a) of Korean Patent Application No. 10-2016-0153165, filed on Nov. 17, 2016, in the Korean Intellectual Property Office, the entire disclosure of which is incorporated herein by reference in its entirety for all purposes.

BACKGROUND

Apparatuses and methods consistent with exemplary embodiments relate to the estimation of biometric information of a subject.

2. Description of Related Art

In the past, healthcare services were centered on the treatment of illnesses preliminarily in hospitals and medical institutions. However, with a the growing interest in quality of life and well-being as well as an improvement in living standards, there has been an increasing interest in proactive health management services of diseases by the measurement of the health status of healthy people.

In a traditional method of non-invasively measuring a substance in the blood, the concentration of a substance in the blood is measured by a scattered light signal transmitted through the blood being tested. A change in the concentration of a substance in the blood may be represented by a change in a scattering coefficient of the blood. The change in the scattering coefficient may be obtained from a change in the scattered light signal, and thus, the concentration of the substance in the blood may be estimated on the basis of the change in the scattered light signal. In order to accurately estimate the concentration of the substance in the blood from the change in the scattered light signal, the measured change of the scattered light signal should be caused by nothing other than the change in the scattering coefficient of the blood. However, in reality, a change in the temperature of the skin or tissue that is in contact with the sensor also affects the scattered light signal, and thus, it is desirable to correct for this influence, in order to obtain more accurate results.

To this end, a method of correcting a scattered light signal affected by the change of a temperature of skin or tissue is being studied.

SUMMARY

According to an aspect of an exemplary embodiment, there is provided an apparatus configured to estimate biometric information, the apparatus including: a sensor configured to measure a light signal reflected from a subject and a temperature of the subject; and a processor configured to perform temperature correction on the light signal reflected from the subject based on the temperature of the subject using a light signal-temperature relationship between the light signal reflected from the subject and the temperature of the subject to thereby obtain a temperature-corrected light signal, and estimate the biometric information of the subject based on the temperature-corrected light signal.

The processor may be configured to generate the light signal-temperature relationship in advance in a reference state.

The reference state may include a fasting state of the subject.

The sensor may include a light source configured to emit the light signal to the subject, a light sensor configured to measure the light signal by detecting the light signal reflected from the subject, and a temperature sensor configured to measure the temperature of the subject.

The sensor may include a plurality of light sensors and a plurality of temperature sensors, each of the temperature sensors being provided in proximity to a corresponding light sensor of the plurality of light sensors.

The processor may be configured to generate the light signal-temperature relationship based on light signals measured by each of the plurality of light sensors and temperatures measured by each of the plurality of temperature sensors corresponding to the respective light sensors.

The processor may be configured to select a light sensor to be used for estimating the biometric information from among the plurality of light sensors based on intensities of the light signals measured by each of the plurality of light sensors.

The processor may be configured to perform temperature corrections on the light signals measured by each of the plurality of light sensors using the temperatures measured by each of the temperature sensors corresponding to the respective light sensors, generate temperature-corrected light signals based on the temperature corrections, and select the light sensor to be used for estimating the biometric information from among the plurality of light sensors based on intensities of the temperature-corrected light signals.

The biometric information may include at least one of triglyceride, blood sugar, moisture, hemoglobin, cholesterol, alcohol, and fat.

The apparatus may further include a display configured to display the measured light signal, the measured temperature, or the estimated biometric information.

The apparatus may further include a communicator configured to transmit the measured light signal, the measured temperature, or the estimated biometric information to an external electronic device.

The processor may be configured to make a determination as to whether the measured temperature is abnormal, and according to the determination, request the sensor to re-measure the light signal or the temperature, or correct the light signal-temperature relationship.

According to an aspect of another exemplary embodiment, there is provided a method of estimating biometric information, the method including: measuring a light signal reflected from a subject and a temperature of the subject; performing temperature correction on the light signal reflected from the subject based on the temperature of the subject using a light signal-temperature relationship between the light signal reflected from the subject and the temperature of the subject to thereby obtain a temperature-corrected light signal; and estimating the biometric information of the subject based on the temperature-corrected light signal.

The method may further include generating the light signal-temperature relationship in advance in a reference state.

The reference state may include a fasting state of the subject.

The biometric information may include at least one of triglyceride, blood sugar, moisture, hemoglobin, cholesterol, alcohol, and fat.

The method may further include displaying the measured light signal, the measured temperature, or the estimated biometric information.

According to an aspect of another exemplary embodiment, there is provided an apparatus configured to estimate biometric information, the apparatus including: a sensor configured to measure, at predetermined time intervals, a light signal reflected from a subject and a temperature of the subject in a reference state; and a processor configured to generate a light signal-temperature relationship between the light signal reflected from the subject and the temperature of the subject, by using the light signal reflected from the subject and the temperature of the subject as learning data to generate the light-signal temperature relationship.

The reference state may include a fasting state of the subject.

The sensor may be configured to measure the light signal reflected from the subject and the temperature of the subject during a predetermined time period and the processor may be configured to generate the light signal-temperature relationship based on the light signal reflected from the subject and the temperature of the subject measured during the predetermined time period.

Other exemplary features and aspects will be apparent from the following detailed description, the drawings, and the claims.

DETAILED DESCRIPTION

Exemplary, non-limiting advantages and features may be understood more readily by reference to the following detailed description of exemplary embodiments and the accompanying drawings. Apparatuses and methods may, however, be embodied in many different forms and should not be construed as being limited to the exemplary embodiments set forth herein. Rather, these exemplary embodiments are provided so that this disclosure will be thorough and complete and will fully convey the concept of the exemplary embodiments to those skilled in the art, and the exemplary embodiments will only be defined by the appended claims. Like reference numerals refer to like elements throughout the specification.

It will be understood that, although the terms first, second, etc., may be used herein to describe various elements, these elements should not be limited by these terms. These terms are only used to distinguish one element from another. Also, the singular forms are intended to include the plural forms as well, unless the context clearly indicates otherwise. In the specification, unless explicitly described to the contrary, the word “comprise” and variations such as “comprises” or “comprising”, will be understood to imply the inclusion of stated elements but not the exclusion of any other elements. The term ‘unit’, as used herein, may refer to, but is not limited to referring to, a software or hardware component, such as a Field Programmable Gate Array (FPGA) or Application Specific Integrated Circuit (ASIC), which performs certain tasks. A unit may advantageously be configured to reside on the addressable storage medium and configured to execute on one or more processors.

Thus, a unit may include, by way of example, components, such as software components, object-oriented software components, class components and task components, processes, functions, attributes, procedures, subroutines, segments of program code, drivers, firmware, microcode, circuitry, data, databases, data structures, tables, arrays, and variables. The functionality provided for in the components and units may be combined into fewer components and units or further separated into additional components and units.

FIG. 1is a block diagram illustrating an apparatus for estimating biometric information according to an exemplary embodiment.

Referring toFIG. 1, the apparatus100for estimating biometric information includes a sensing unit110(e.g., sensor) and a processor120.

The sensing unit110may measure a light signal reflected from a subject and measure a temperature of the subject in order to generate a light signal-temperature relationship. In this case, the light signal reflected from the subject may include a scattered light signal that is specularly reflected from the surface of the subject and a scattered light signal that is diffuse and is reflected from an inside of the irradiated subject. When a user's command is input to the apparatus100or when the apparatus100is in a reference state, the sensing unit110may measure the light signal and/or temperature from the subject. For example, the user's command may be input to the apparatus100through a standard input device, such as a keyboard, a mouse, or a voice processor, which is mounted in or connected to the apparatus100. In this case, the reference state may include a fasting state of the subject and may be set differently according to an age, sex and/or skin condition of the user and/or according to the biometric information to be measured.

Data about the light signal and/or temperature measured by the sensing unit110may be stored in a database disposed inside and/or outside of the apparatus100. The database may store the data about the light signal and/or temperature by matching it with the user, measurement time, and the like. For example, the database may include a solid state drive and a hard disk drive, and the hard disk drive may include a buffer1, a hard disk drive (HDD) controller, a driver, a read/write (R/W) channel circuit, and a head disk assembly (HAD).

The processor120may perform temperature correction by applying the temperature measured from the subject to the light signal measured from the subject using the light signal-temperature relationship. More specifically, the processor120may perform temperature correction on the basis of the light signal-temperature relationship by subtracting or excluding a signal or a portion of a signal associated with the temperature from the light signal measured the subject.

In the reference state, the processor120may generate the light signal-temperature relationship in advance. In addition, in order to generate in advance the light signal-temperature relationship in the reference state, the sensing unit110may measure the light signal and/or temperature from the subject in the reference state.

Referring to Equation 1 below, it is seen that a scattered light signal Xscattered light(a scattered light signal reflected from the subject) is the same as or proportional to a value obtained by adding a signal Xbiologicalgenerated by the biometric information of the subject, a signal Xtemperaturegenerated by temperature, and an error value Xerror. However, for convenience of description, it will be assumed that ΔXerroris zero.
ΔXscattered light≅ΔXbiological+ΔXtemperature+ΔXerrorEquation (1)

If ΔXbiologicalis zero or is small enough to be assumed zero, as shown in Equation 2 below, Equation 1 may be expressed as Equation 2. For example, in the case where there is no change of substance in the blood of the subject, the following Equation 2 may be applied when the light signal and temperature are measured from the subject.
ΔXscattered light≅ΔXtemperature(if,ΔXbiological≅0)  Equation (2)

That is, the processor120assumes that the light signal Xscattered lightthat is measured when ΔXbiologicalis zero or small enough to be assumed zero is a signal Xtemperaturewhich is generated by temperature, and may generate the light signal-temperature relation on the basis of the relationship between the temperature at the time of light signal measurement and the light signal Xscattered light.

Meanwhile, when triglyceride or blood sugar of the subject is considered as biometric information, the above Equation 1 may be expressed as Equation 3 below. (In Equation 3, ΔXtriglyceride(triglyceride) is stated, but it may be replaced by ΔXblood sugar(blood sugar)).
ΔXscattered light≅ΔXtriglyceride+ΔXtemperature+ΔXerrorEquation (3)

Meanwhile, when the subject is in a fasting state, ΔXtriglycerideOr ΔXblood sugar) is zero or small enough to be assumed zero, and thus the above Equation 3 for the subject in a fasting state may be expressed as the following Equation 4.
ΔXscattered light≅ΔXtemperature(subject is in a fasting state)  Equation (4)

Therefore, the processor120may generate the light signal-temperature relation on the basis of the relationship between the scattered light signal measured in a fasting state of the subject and the temperature at the time of measuring the scattered light signal.

Meanwhile, the processor120may generate the light signal-temperature relationship in advance before extracting the biometric information. In addition, the light signal-temperature relation generated in advance by the processor120may be stored in the database, wherein the light signal-temperature relation may be matched with the measurement time, the measured light signal and/or temperature.

Additionally, the processor120may determine whether the measured temperature is abnormal, and may request the sensing unit110to re-measure a light signal and/or temperature or correct the light signal-temperature relationship in consideration of the measured temperature according to the determination. For example, when the temperature measured at the time of measuring the light signal from the subject for generating the light signal-temperature relation deviates from a predetermined temperature range (e.g., a room temperature, 15° C. to 20° C.), the processor120may determine that the measured temperature is abnormal. In addition, the processor120may repeatedly request the sensing unit110to re-measure the light signal and/or temperature until the temperature measured from the subject is within the predetermined temperature range. Meanwhile, the processor120may correct the light signal-temperature relationship by taking into consideration a degree of deviation (difference) of the measured temperature from the predetermined temperature range.

In one example, when the user of the apparatus100measures a light signal and/or temperature from the subject in order to generate a light signal-temperature relationship for ultra-low temperature environments, such as a refrigerated cold storage warehouse, an ultra-high altitude region, the Antarctic area, and the like, the generated light signal-temperature relation is difficult to be applied to a general environment. Therefore, the processor120may request the sensing unit110to measure the light signal and/or temperature when the apparatus100is in a general environment or may correct the light signal-temperature relationship in consideration of the fact that the light signal-temperature relationship has been generated for the ultra-low temperature environments.

The processor120may estimate the biometric information of the subject on the basis of a temperature-corrected light signal. In this case, the biometric information may include a substance contained in the body of the subject, including triglyceride, blood sugar, moisture, hemoglobin, cholesterol, alcohol, fat, and the like. The processor120may calculate a scattering coefficient from the temperature-corrected light signal, and estimate the biometric information of the subject on the basis of the calculated scattering coefficient. For example, the processor120may estimate triglyceride content or blood sugar level of the subject on the basis of the temperature-corrected light signal. In another example, the processor120may estimate triglyceride content or blood sugar level of the subject on the basis of a light signal which is not temperature-corrected.

In addition, the processor120may determine the health status of the subject on the basis of the estimated biometric information. For example, the processor120may compare the estimated triglyceride content and/or blood sugar level of the subject with a predetermined reference value and determine whether the subject's health status is abnormal. In addition, the processor120may compare the estimated triglyceride content and/or blood sugar level with a predetermined reference value and determine a degree of risk of a disease associated with the triglyceride content and/or blood sugar level of the subject according to a degree to which a difference between the compared values deviates from a predetermined tolerance range. For example, the processor120may determine that the greater the difference between the triglyceride content and/or blood sugar level and the reference value is, the higher the risk of a disease associated with the triglyceride content and/or blood sugar level of the subject is.

The processor120may include a bus and a predetermined electronic circuit (or an integrated circuit). The processor120may realize various functions to be implemented in the apparatus100for estimating biometric information and control and manage the overall operation of the apparatus100in order to realize the functions described below.

FIG. 2is a block diagram illustrating a sensing unit according to an exemplary embodiment.

Referring toFIG. 2, the sensing unit200includes a light source210, a light sensor220, and a temperature sensor230.

The light source210may emit light to a subject. For example, the light source210may include a light emitting diode. Here, the light emitting diode may be a light emitting device which emits light, such as RGB light, RGBW light, infrared light, near-infrared light, mid-infrared light, and the like. In addition, the light source210may include a fixing device to fix the light emitting diode so as to emit light to the subject at a predetermined angle or an angle adjusting device to adjust the angle at which the light emitting diode emits light to the subject in response to a control signal of the processor120. In addition, the light source210may include one or more light source modules configured as independent modules, and each light source module may be set to emit light of a different wavelength band or set to sequentially and repeatedly emit light of multiple wavelength bands.

When the emitted light is reflected from the subject, the light sensor220may measure a light signal by detecting the reflected light. For example, the light sensor220may include a photodiode, a photo transistor (PTr), or a charge-coupled device (CCD), but is not limited thereto. The light sensor220may detect a light signal from at least one of light reflected from the skin of the subject which is transmitted by the light source, absorption light, and light scattered by a biological component. In addition, one or more light sensors220may be provided and be implemented as an array of a predetermined structure spaced apart from the light source210at a specific distance.

The temperature sensor230may measure a temperature of the subject. For example, the temperature sensor230may include an infrared temperature sensor which measures the temperature of the subject by detecting infrared rays (e.g., thermal infrared rays, mid-infrared rays, near infrared rays) radiated from the subject.

In addition, the light source210may include one or more light source modules, and the processor120may determine an optimal light source module for estimating biometric information on the basis of the light signal detected by the light sensor220. For example, the optimal light source module for estimating biometric information may vary depending on the positions of the light source210and the light sensor220, wherein the optimal light source may refer to a light source module disposed at a specific position among one or more light source modules included in the light source210. However, aspects of the exemplary embodiments are not limited to those described above, and in the case where the light source210includes one or more modules each of which is set to emit light of a specific wavelength band, the optimal light source may refer to a light source module which emits light of a particular wavelength band.

FIG. 3is a diagram illustrating a sensing unit according to an exemplary embodiment.

Referring toFIG. 3, the sensing unit300includes a light source310, a plurality of light sensors321,322, and323, and a plurality of temperature sensors331,332, and333, and each of the temperature sensors331to333may be disposed in proximity to one of the plurality of light sensors321to323. That is, as shown inFIG. 3, the first temperature sensor331is disposed close to the first light sensor321, the second temperature sensor332is disposed close to the second light sensor322, and the third temperature sensor333is disposed close to the third light sensor323. AlthoughFIG. 3shows only three light sensors321to323and three temperature sensors331to333, these sensors are only illustrated to represent all of the plurality of light sensors321to323and the plurality of temperature sensors331to333in one drawing, and the number of light sensors321to323and the number of temperature sensors331to333are each not limited to three as shown inFIG. 3. In addition, althoughFIG. 3illustrates an example in which the number of light sensors321to323is the same as the number of temperature sensors331to333, the number of light sensors321to323and the number of temperature sensors331to333may be different from each other.

The processor120may generate a light signal-temperature relationship which corresponds to each of the light sensors321to323. Referring toFIG. 3, the sensing unit300includes three light sensors321to323and three temperature sensors321to323, and thus the processor120may generate the first light signal-temperature relationship (Equation 5, below) on the basis of a relationship between a temperature and a light signal measured by the first temperature sensor331and the first light sensor321, the second light signal-temperature relationship (Equation 6, below) on the basis of a relationship between a temperature and a light signal measured by the second temperature sensor332and the second light sensor322, and the third light signal-temperature relationship (Equation 7, below) on the basis of a relationship between a temperature and a light signal measured by the third temperature sensor333and the third light sensor323.
Yfirst light sensor=a1*Xfirst temperature sensor+b1Equation (5)
Ysecond light sensor=a2*Xsecond temperature sensor+b2Equation (6)
Ythird light sensor=a3*Xthird temperature sensor+b3Equation (7)

However, Equations 5 to 7 are only examples to show the light signal-temperature relationships as linear relationships. In addition, the light signal-temperature relations may not be linear relationships, unlike Equations 5 to 7.

The processor120may generate or correct the light signal-temperature relationship on the basis of the light signals and/or temperatures which are measured a number of times by the plurality of light sensors321to323and the plurality of temperature sensors331to333, respectively, in order to increase the accuracy of the light signal-temperature relationship.

In another example, the processor120may request the plurality of light sensors321to323and temperature sensors331to333to measure the light signal and/or temperature several times, and may generate the light signal-temperature relationship on the basis of maximum values of a plurality of light signals and/or temperatures measured, an average of the maximum values, minimum values, an average of the minimum values, and an intermediate value between the maximum value and the minimum value.

In another example, the processor120may request the plurality of light sensors321to323and temperature sensors331to333to measure the light signal and/or temperature several times, and may correct a light signal-temperature relationship previously generated by learning a plurality of light signals and/or temperatures measured by the plurality of light sensors321to323and temperature sensors331to333. For example, the processor120may use a deep-learning algorithm, such as long short-term memory (LSTM), deep neural network (DNN), recurrent neural network (RNN), bidirectional recurrent deep neural network (BRDNN), convolutional neural network (CNN), restricted Boltzmann machine (RBM), deep belief network (DBN), and the like, when learning the plurality of light signals and/or temperatures measured by the plurality of light sensors321to323and temperature sensors331to333.

The processor120may select a light sensor to be used for estimating biometric information from among the plurality of light sensors321to323.

For example, the processor120may use all of the plurality of light sensors321to323when measuring a light signal from the subject in order to generate the light signal-temperature relationship. Also, in the case where the processor120measures the light signal from the subject in order to estimate biometric information, the processor120may select some light sensors from among the plurality of light sensors321to323according to a predetermined criterion.

For example, the processor120may select a light sensor to be used for estimating biometric information by taking into consideration the signal intensity of the measured light signal, wherein the processor120may select the light signal from among the light signals measured by the plurality of light sensors321to323according to the order of intensities of the light signals and select the light sensor that corresponds to the selected light signal as the light sensor to be used for estimating biometric information.

In another example, the processor120may calculate a signal-to-noise (SNR) of a light signal detected by each of the light sensors321to323and select the light sensor that detects a light signal having the highest SNR among the calculated light signals as the light sensor used for estimating biometric information.

The processor120may correct temperatures of the light signals measured by the plurality of light sensors321to323and select a light sensor to be used for estimating biometric information from among the temperature-corrected light sensors321to323.

For example, the processor120may select the light sensor to be used for estimating biometric information by taking into consideration signal intensities of the temperature-corrected light signals, wherein the processor120may select the light sensor to be used for estimating biometric information in the order of highest intensity to weakest intensity of the temperature-corrected light signal.

In another example, the processor120may select a light sensor to be used for estimating biometric information on the basis of a light signal which is not temperature corrected.

The processor120may extract biometric information of the subject, as described above.

More specifically, the processor120may calculate a triglyceride content using the following Equation 8 on the basis of an intensity of a scattered light detected by the sensing unit110. Hereinafter, in the description related to Equation 8, it is assumed that two light sensors are selected from the plurality of light sensors according to various criteria described above.

Here, μs′ may denote a reduced scattering coefficient, μamay denote an absorption coefficient, ρ1may denote a distance from the light source310to the first light sensor331, ρ2may denote a distance from the light source310to the second light sensor322, R1may denote the intensity of a scattered light at the first light sensor331, and R2may denote the intensity of a scattered light at the second light sensor332. The processor120may calculate an amount of change in the reduced scattering coefficient, which may be defined as a ratio R1/R2of intensities of two detected scattered light signals, and may measure the triglyceride content of the subject. For example, the processor120may calculate the reduced scattering coefficient in a reference state (e.g., a fasting state of the subject), in which the triglyceride content of the subject does not change, calculate the reduced scattering coefficient after a predetermined amount of time has elapsed since consumption of food containing fat, and compute an amount of change in the reduced scattering coefficient, thereby calculating the triglyceride content of the subject.

According to another exemplary embodiment, the sensing unit300may include a plurality of light sensors220and one temperature sensor230. For example, the temperature sensor230may be disposed in proximity to one of light sensors220, or may be disposed at a position which is equally spaced apart from each of the light sensors220.

In addition, in the sensing unit300, each of the light sensors220may measure a light signal and the single temperature sensor230may measure a temperature of the subject. Meanwhile, the processor120may generate as many light signal-temperature relationships as the number of light sensors220on the basis of relationships between each of the light signals measured by the respective light sensors220and the temperature measured by the temperature sensor230.

More specifically, in a case where the sensing unit300includes three light sensors220and one temperature sensor230, the processor120may generate the first light signal-temperature relationship (Equation 9, below) on the basis of a relationship between a light signal measured by the first light sensor and a temperature measured by the temperature sensor, the second light signal-temperature relationship (Equation 10, below) on the basis of a relationship between a light signal measured by the second light sensor and the temperature measured by the temperature sensor, and the third light signal-temperature relationship (Equation 11, below) on the basis of a relationship between a light signal measured by the third light sensor and the temperature measured by the temperature sensor.
Yfirst light sensor=c1*Xtemperature sensor+d1Equation (9)
Ysecond light sensor=c2*Xtemperature sensor+d2Equation (10)
Ythird light sensor=c3*Xtemperature sensor+d3Equation (11)

However, Equations 9 to 11 are merely examples which illustrate the light signal-temperature relationships as linear relationships. In addition, the light signal-temperature relationships may not be linear relationships, unlike Equations 8 to 10.

FIG. 4show graphs for describing a result of performing temperature correction on a scattered light signal.

FIG. 4illustrates light signals measured by each of three light sensors331to333of the sensing unit300and temperature-corrected light signals.

Referring toFIG. 4, it is shown that a value of the scattered light signal increases as the number of times of measurement increases. This results from the fact that the signal generated by the temperature increases as the number of times of measurement increases. As the number of times of measurement increases or as the elapsed time of operation of the apparatus100for estimating biometric information increases, the heat generated by the apparatus100increases, and accordingly the magnitude of the signal generated by the temperature may gradually increase.

Referring to the light signals after temperature correction, it is shown that the signals generated by the temperature are excluded.

FIG. 5is a block diagram illustrating an apparatus for estimating biometric information according to another exemplary embodiment.

Referring toFIG. 5, the apparatus500for estimating biometric information includes a sensing unit510(e.g., sensor), a processor520, a display530, and a communicator540. The sensing unit510and the processor520have been described above in detail with reference toFIG. 1, and hence a redundant or unnecessary description will be omitted herein.

The display530may display a light signal or temperature measured at the sensing unit510or biometric information estimated by the processor520. For example, the display530may display a triglyceride content or blood sugar level estimated by the processor520on the basis of the light signal and temperature measured at the sensing unit510. In addition, the display530may display a graph to show changes in triglyceride content or blood sugar level over time, and the apparatus500may be utilized as a monitoring device to monitor the health status of the subject.

The processor520may monitor the trend of changes in biometric information of the subject during a predetermined period of time. For example, the processor520may obtain a maximum value or minimum value of each of the graphs generated at predetermined intervals and may detect a trend of changes in maximum value or minimum value on the basis of a rise or fall of the obtained value. However, since the rise or fall of the maximum value or minimum value of the biometric information may temporarily appear, the processor520may determine that the biometric information of the subject is rising or falling when the rise or fall of the maximum value or minimum value continues beyond a predetermined reference period.

In addition, the display530may generate a user interface screen for displaying at least one piece of specific information arranged in chronological order along one axis. More specifically, the display530may generate the user interface screen for arranging pieces of information contained in health-related information in chronological order and displaying the arranged information in a horizontal direction or a vertical direction.

The communicator540may transmit the light signal or temperature measured by the sensing unit510or the estimated biometric information to an external electronic device. For example, the communicator540may communicate with the external electronic device through a wireless or wired communication. Here, the wireless communication may include Bluetooth communication, Bluetooth low energy (BLE) communication, near field communication (NFC), wireless local area network (WLAN) communication, ZigBee communication, infrared data association (IrDA) communication, Wi-Fi direct (WFD) communication, ultra-wideband (UWB) communication, Ant+ communication, Wi-Fi communication, radio frequency identification (RFID) communication, 3G communication, 4G communication, 5G communication, or the like. Also, the wired communication may include a universal serial bus (USB), high definition multimedia interface (HDMI), recommended standard 232 (RS-232), a plain old telephone service (POTS), or the like.

Additionally, the apparatus500for estimating biometric information may further include an application to provide an application related to biometric information estimation.

For example, the application may include a short message service (SMS) application or a multimedia messaging service (MMS) application, an email application, a calendar application, an alarm application, a healthcare application (e.g., an application for measuring an amount of exercise, a blood sugar level, or the like), an environment information application (e.g., an application for providing atmospheric pressure information, humidity information, or temperature information), or the like.

In addition, the application may be an application related to information exchange between the apparatus500and the external electronic device. In this case, the application related to information exchange may include a notification relay application for transmitting specific information to the external electronic device or a device management application for managing the external electronic device.

Also, the application may include a function for transmitting notification information generated in the application (e.g., SMS or MMS application, email application, healthcare application, environment information application or the like.) of the apparatus500to the external electronic device. In another example, the application may receive notification information from the external electronic device and provide it to the user. In still another example, the application may manage (e.g., install, delete, or update) at least some functions (e.g., turning on or off of the external electronic device itself or some components thereof or control of brightness or resolution) of the external electronic device, applications running on the external electronic device, or services (e.g., call services or message services) provided by the external electronic device.

FIG. 6is a flowchart illustrating a method of estimating biometric information according to an exemplary embodiment.

Referring toFIG. 6, the apparatus500for estimating biometric information measures a light signal reflected from a subject and measures a temperature of the subject in order to generate a light signal-temperature relationship, in operation610. In this case, the light signal reflected from the subject may include a scattered light signal that is specularly reflected from the surface of the subject and a scattered light signal that is diffuse reflected from the inside of the irradiated subject. For example, the apparatus500may measure the light signal and/or temperature of the subject when a user's command is input to the apparatus500or the apparatus500is in a reference state.

The apparatus500performs temperature correction on the light signal measured from the subject with reference to the measured temperature on the basis of the light signal-temperature relationship, in operation620. More specifically, the apparatus500may perform the temperature correction on the basis on the light signal-temperature relationship by subtracting or excluding a signal associated with the temperature from the measured light signal reflected by the subject.

In a reference state, the apparatus500may generate the light signal-temperature relationship in advance. In this case, the reference state may include a fasting state of the subject and may be set differently according to the age, sex and skin condition of the user and the biometric information to be measured. In addition, the light signal-temperature relationship generated in advance by the apparatus500may be stored in a database, wherein the light signal-temperature relationship may be matched with the measurement time, the measured light signal and/or temperature.

The apparatus500estimates biometric information of the subject on the basis of the temperature-corrected light signal, in operation630. In this case, the biometric information may include at least one of triglyceride, blood sugar, moisture, hemoglobin, cholesterol, alcohol, and fat. Also, the apparatus500may calculate a scattering coefficient from the temperature-corrected light signal and estimate the biometric information of the subject on the basis of the extracted scattering coefficient. For example, the apparatus500may estimate a triglyceride content or blood sugar level of the subject on the basis of the temperature-corrected light signal. In another example, the apparatus100may estimate the triglyceride content or blood sugar level of the subject on the basis of the light signal which is not temperature-corrected.

Additionally, the apparatus500for estimating biometric information may display the measured light signal and/or temperature or the estimated biometric information on a display. For example, the apparatus500may display the triglyceride content or blood sugar level estimated on the basis of the measured light signal and temperature on the display. In addition, the apparatus500may display a graph to show changes in triglyceride content or blood sugar level over time.

The apparatus500may monitor the trend of changes in biometric information of the subject during a predetermined period of time. For example, the apparatus500may obtain a maximum value or minimum value of each of the graphs generated at predetermined intervals and may detect a trend of changes in maximum value or minimum value on the basis of a rise or fall of the obtained value. However, since the rise or fall of the maximum value or minimum value of the biometric information may temporarily appear, the apparatus500may determine that the biometric information of the subject is rising or falling when the rise or fall of the maximum value or minimum value continues beyond a predetermined reference period.

In addition, the apparatus500may generate a user interface screen for displaying at least one piece of specific information arranged in chronological order along one axis. More specifically, the apparatus500may generate the user interface screen for arranging pieces of information contained in health-related information in chronological order and displaying the arranged information in a horizontal direction or a vertical direction.

FIG. 7is a block diagram illustrating an apparatus for estimating biometric information according to another exemplary embodiment.

Referring toFIG. 7, the apparatus700includes a sensing unit710(e.g, sensor) and a processor720.

In a reference state, the sensing unit710may measure a light signal and/or temperature from a subject at predetermined time intervals. Here, the predetermined time interval may be set to days, weeks, months, years, etc., but is not limited thereto, and may vary according to the health status of the user or the purpose of biometric information estimation. For example, the light signal and/or temperature may be set to be measured at shorter intervals in the case where the user's health status is poor, and the time interval may be set to a relatively long period in the case where data is to be collected over a long period of time. In addition, the reference state may include a fasting state of the subject and may be set differently according to the age, sex, and skin condition of the user and the type of biometric information to be measured.

The sensing unit710may include a light source, a light sensor, and a temperature sensor to measure a light signal and a temperature.

In this case, the light source of the sensing unit710may emit light to the subject. For example, the light source may include a light emitting diode to emit light to the subject. Here, the light emitting diode may be a light emitting device which emits light, such as RGB light, RGBW light, infrared light, near-infrared light, mid-infrared light, and the like. The sensing unit710may include one or more light source modules configured as independent modules, and each light source module may be set to emit light of a different wavelength band or set to sequentially and repeatedly emit light of multiple wavelength bands.

When the emitted light is reflected from the subject, the light sensor of the sensing unit710may measure a light signal by detecting the reflected light. For example, the light sensor of the sensing unit710may include a photodiode, a PTr, or a CCD, but is not limited thereto. The light sensor of the sensing unit710may detect a light signal from at least one of light reflected from the skin of the subject which is irradiated by the light source, absorption light, and light scattered by a biological component.

The temperature sensor of the sensing unit710may measure a temperature of the subject. For example, the temperature sensor of the sensing unit710may include an infrared temperature sensor which measures the temperature of the subject by detecting infrared rays (e.g., thermal infrared rays, mid-infrared rays, near infrared rays) radiated from the subject.

The processor720may generate a light signal-temperature relationship using the measured light signal and/or temperature as learning data. For example, the apparatus700for estimating biometric information may include a database inside or outside thereof to store data on the light signal and/or temperature measured by the sensing unit710. In addition, the processor720may generate a linear equation or a predetermined expression of a relationship which represents a relationship between a light signal and a temperature, on the basis of the light signal and the temperature measured using the sensing unit710in the reference state.

The sensing unit710may measure a light signal and a temperature at a predetermined time period, and the processor720may generate the light signal-temperature relationship on the basis of the light signal and temperature measured at the predetermined time period.

For example, the user of the apparatus700may set a time period during which it is determined that a fasting state is periodically maintained. If the predetermined time period is from 6 a.m. to 7 a.m., the sensing unit710may measure a light signal or a temperature from the subject at predetermined time intervals (e.g., 10 minutes, 15 minutes, etc.). The processor720may generate the light signal-temperature relationship on the basis of the light signal and/or temperature measured at the predetermined time period, and the light signal-temperature relationship may be assumed as a light signal-temperature relatiionship generated on the basis of the light signal and/or temperature measured in the reference state.

FIG. 8is a flowchart illustrating a method of estimating biometric information according to another exemplary embodiment.

Referring toFIG. 8, the apparatus700for estimating biometric information may measure a light signal and/or temperature from a subject in a fasting state at a predetermined time interval, in operation810. Here, the predetermined time interval may be set to days, weeks, months, years, etc., but is not limited thereto, and may vary according to the health status of the user or the purpose of biometric information estimation. In addition, the reference state may include a fasting state of the subject and may be set differently according to the age, sex, and skin condition of the user and the type of biometric information to be measured. The apparatus700may store the measured light signal and/or temperature as learning data.

The apparatus700generates a light signal-temperature relationship using the measured light signal and/or temperature as learning data, in operation820. The apparatus700may generate a linear equation or a predetermined expression of a relationship which represents a relationship between a light signal and a temperature, on the basis of the light signal and the temperature measured in the reference state.

The exemplary embodiments can be implemented as computer readable codes in a computer readable record medium. Codes and code segments constituting the computer program can be easily inferred by a skilled computer programmer in the art. The computer readable record medium includes all types of recording media in which computer readable data are stored. Examples of the computer readable recording medium include a ROM, a RAM, a CD-ROM, a magnetic tape, a floppy disk, and an optical data storage. Further, the recording medium may be implemented in the form of a carrier wave such as Internet transmission. In addition, the computer readable recording medium may be distributed to computer systems over a network, in which computer readable codes may be stored and executed in a distributed manner.