Patent Description:
Generally, blood triglyceride levels rise for <NUM> to <NUM> hours after intake of fat, and begin to fall thereafter. Accordingly, by measuring a variation in triglyceride levels after fat intake, an amount of fat intake, lipolysis ability, and the like may be obtained as important health indicators to be used for healthcare management.

There is a method of invasively measuring triglyceride levels by taking blood samples at intervals of <NUM> to <NUM> minutes and analyzing the blood samples. However, while the invasive method of measuring the blood triglyceride levels may provide high reliability in measurement, it may cause pain and inconvenience as well as an increased risk of disease infections due to the use of injection. Recently, research has been conducted on methods of non-invasively estimating a variation in triglyceride levels by measuring optical characteristics without blood sampling. Document <CIT> is directed to an apparatus and a method for estimating a substance in blood. When scattered light signals are detected by detectors, a similarity calculator calculates a similarity between the detected scattered light signals, such as a Pearson correlation coefficient or a Spearman correlation coefficient. A similarity determiner compares the calculated similarity to a reference similarity, which may be preset as a data reliability threshold. When the calculated similarity is the preset threshold or greater, the similarity determiner determines that the detected scattered light signals are reliable for estimating the level of the substance in blood. On the contrary, when the calculated similarity is less than the preset threshold, it is determined that redetection of the scattered light signals is necessary.

The invention is described in the claims. The invention provides an optical sensor according to claim <NUM>. The invention provides further a method of measuring an optical signal according to claim <NUM>. The invention provides further an apparatus for estimating a blood concentration according to claim <NUM>. Preferred embodiments are described in the dependent claims.

The above and/or other aspects of the disclosure will become apparent and more readily appreciated from the following description of the example embodiments, taken in conjunction with the accompanying drawings, in which:.

Hereinafter, example embodiments of the disclosure will be described in detail with reference to the accompanying drawings. It should be noted that wherever possible, the same reference symbols refer to same parts even in different drawings. In the following description, a detailed description of known functions and configurations incorporated herein will be omitted when it may obscure the subject matter of the disclosure.

Process steps described herein may be performed differently from a specified order, unless the specified order is clearly stated as being necessary in the context of the disclosure. For example, each step may be performed in a specified order, at substantially the same time, or in a reverse order.

Further, the terms used throughout in this specification are defined in consideration of the functions according to example embodiments, and can be varied according to a purpose of a user or manager, or precedent and so on. Therefore, definitions of the terms should be made on the basis of the overall context.

Any references to singular may include plural unless expressly stated otherwise. In the specification, it should be understood that the terms, such as 'including' or 'having,' etc., are intended to indicate the existence of the features, numbers, steps, actions, components, parts, or combinations thereof disclosed in the specification, and are not intended to preclude the possibility that one or more other features, numbers, steps, actions, components, parts, or combinations thereof may exist or may be added.

Further, components that will be described in the specification are discriminated merely according to functions mainly performed by the components. That is, two or more components which will be described later can be integrated into a single component. Furthermore, a single component which will be explained later can be separated into two or more components. Moreover, each component which will be described can additionally perform some or all of a function executed by another component in addition to the main function thereof. Some or all of the main function of each component which will be explained can be carried out by another component. Each component may be implemented in hardware or software, or a combination thereof.

In the disclosure, the term "at least one of" includes any and all combinations of one or more of the associated listed items. For example, the term "at least one of A and B" or "at least one of A or B" is only used to describe that three cases may exist: only A exists, both A and B exist, and only B exists. Similarly, "at least one of A, B, and C" or "at least one of A, B, or C" indicates that there may exist seven cases: only A exists, only B exists, only C exists, both A and B exist, both A and C exist, both C and B exist, and all A, B, and C exist.

In the following description, a term 'module,' 'unit,' or 'part' refers to an element that performs at least one function or operation. The 'module' or 'unit' may be realized as hardware, software, or combinations thereof. A plurality of 'modules,' 'units,' or 'parts' may be integrated into at least one module or chip and realized as at least one processor, except for a case where respective 'modules' or 'units' need to be realized as discrete specific hardware.

<FIG> is a block diagram illustrating an example of an optical sensor <NUM> according to an example embodiment.

The optical sensor <NUM> of <FIG> is a device for measuring an optical signal with respect to an object, and evaluating quality of the measured optical signal. The optical signal is a signal generated based on the light emitted by the light source and returning from the object. The optical signal measured by the optical sensor <NUM> is used to determine optical characteristics of the object. The optical sensor <NUM> may be embedded in an electronic device, or may be enclosed in a housing to be provided as a separate device. Examples of the electronic device may include a cellular phone, a smartphone, a tablet PC, a laptop computer, a personal digital assistant (PDA), a portable multimedia player (PMP), a navigation, an MP3 player, a digital camera, a wearable device, and the like; and examples of the wearable device may include a wristwatch-type wearable device, a wristband-type wearable device, a ring-type wearable device, a waist belt-type wearable device, a necklace-type wearable device, an ankle band-type wearable device, a thigh band-type wearable device, a forearm band-type wearable device, and the like. However, the electronic device is not limited to the above examples, and the wearable device is neither limited thereto.

Referring to <FIG>, the optical sensor <NUM> includes a light source <NUM>, a photodetector array <NUM>, and a processor <NUM>. Here, the processor <NUM> may include one or more processors, a memory, or a combination thereof.

The light source <NUM> emits light onto an object. For example, the light source <NUM> may emit light of a specific wavelength, e.g., near infrared (NIR) light, onto an object. However, wavelengths of light to be emitted by the light source <NUM> may vary depending on a purpose of measurement and/or the types of analytes. Further, the light source <NUM> is not necessarily a single light-emitting body, and may be formed as an array of a plurality of light-emitting bodies. In the case where the light source <NUM> is formed as an array of a plurality of light-emitting bodies, the plurality of light-emitting bodies may emit light of different wavelengths, or may emit light of the same wavelength. Further, some of the plurality of light-emitting bodies may emit light of the same wavelength, and others may emit light of different wavelengths. In an example embodiment, the light source <NUM> may include a light-emitting diode (LED), a laser diode, a fluorescent body, and the like, but these are merely examples, and the disclosure is not limited thereto.

The photodetector array <NUM> detects an optical signal at each distance from the light source <NUM>, and measures a light intensity of the detected optical signal. To this end, the photodetector array <NUM> includes a plurality of photodetectors positioned at different distances from the light source <NUM>. Each photodetector detects an optical signal reflected or scattered from an object, and measures a light intensity of the detected optical signal. In an example embodiment, each photodetector may include a photo diode, a photo transistor (PTr), a charge-coupled device (CCD), and the like, but is not limited thereto.

The processor <NUM> may control the overall operation of the optical sensor <NUM>.

The processor <NUM> determines a correlation coefficient between predetermined variables based on the light intensity measured by the photodetector array <NUM>. The variables for determining the correlation coefficient are obtained using an equation for calculating an effective attenuation coefficient of the object irradiated by the light source. The effective attenuation coefficient calculating equation is expressed by the following Equation <NUM> or Equation <NUM>. <MAT><MAT>.

In Equations <NUM> and <NUM>, ρ denotes a distance between the light source and the photodetector, R(ρ) denotes a light intensity measured by the photodetector at a position which is away from the light source by the distance ρ, S<NUM> denotes a light intensity emitted by the light source to the object, µeff denotes an effective attenuation coefficient, and µa denotes an absorption coefficient. Here, S<NUM> may be a value determined experimentally.

In an example embodiment, the processor <NUM> may determine a correlation coefficient (hereinafter referred to as a first correlation coefficient) between <MAT> and ρ by using <MAT> and ρ of Equation <NUM> as variables.

In another embodiment, the processor <NUM> may determine a correlation (hereinafter referred to as a second correlation coefficient) coefficient between R(ρ) and ρ-<NUM> by using R(ρ) and ρ-<NUM> of Equation <NUM> as variables.

The processor <NUM> determines the quality of the optical signal detected by the photodetector array <NUM> based on the determined correlation coefficient (the first correlation coefficient and/or the second correlation coefficient). The processor <NUM> compares the correlation coefficient (the first correlation coefficient and/or the second correlation coefficient) with a predetermined threshold; and in response to the correlation coefficient exceeding the predetermined threshold, the processor <NUM> determines that the quality of the optical signal is an acceptable level or higher (or good quality), and in response to the correlation coefficient being less than or equal to the predetermined threshold, the processor <NUM> determines that the quality of the optical signal is less than the acceptable level (or poor quality).

Upon determining that the quality of the optical signal detected by the photodetector array <NUM> is an acceptable level or higher, the processor <NUM> terminates measurement, and provides the measured light intensity to an apparatus for measuring optical characteristics of an object.

On the other hand, upon determining that the quality of the optical signal detected by the photodetector array <NUM> is less than the acceptable level, the processor <NUM> discards measured values and controls the light source <NUM> and the photodetector array <NUM> to re-emit light and re-measure a light intensity.

<FIG> is a graph illustrating an example of an effective attenuation coefficient calculating equation. <FIG> may be a graph showing Equation <NUM>.

Referring to <FIG>, Equation <NUM> may be shown in a linear graph with a y-axis representing <MAT> and an x-axis representing ρ.

Accordingly, upon plotting <MAT>, which is calculated based on the measured light intensity, with respect to ρ, in the case where a result of plotting deviates from linearity, the processor <NUM> may determine that the quality of the detected optical signal is less than the acceptable level. On the other hand, in the case where a result of the plotting maintains linearity, the processor <NUM> may determine that the quality of the detected optical signal is an acceptable level or higher. That is, a correlation coefficient between <MAT> and ρ may be used to determine the quality of the detected optical signal.

<FIG> is a graph illustrating another example of an effective attenuation coefficient calculation equation. <FIG> may be a graph showing Equation <NUM>.

Referring to <FIG>, Equation <NUM> may be shown in a power function graph with a y-axis representing R(ρ) and an x-axis representing ρ, as shown in the left graph; and Equation <NUM> may be shown in a linear graph with a y-axis representing R(ρ) and an x-axis representing ρ-<NUM>, as shown in the right graph.

Accordingly, upon plotting R(ρ), which is the measured light intensity, with respect to ρ-<NUM>, in the case where a result of plotting deviates from linearity, the processor <NUM> may determine that the quality of the detected optical signal is less than the acceptable level. On the other hand, in the case where a result of plotting maintains linearity, the processor <NUM> may determine that the quality of the detected optical signal is an acceptable level or higher. That is, a correlation coefficient between R(ρ) and ρ-<NUM> may be used to determine the quality of the detected optical signal.

<FIG> is a block diagram illustrating another example of an optical sensor. The optical sensor <NUM> of <FIG> is a device for measuring an optical signal upon which optical characteristics of an object is determined, and evaluating quality of the measured optical signal. The optical sensor <NUM> may be embedded in an electronic device, or may be enclosed in a housing to be provided as a separate device. Examples of the electronic device may include a cellular phone, a smartphone, a tablet PC, a laptop computer, a personal digital assistant (PDA), a portable multimedia player (PMP), a navigation, an MP3 player, a digital camera, a wearable device, and the like; and examples of the wearable device may include a wristwatch-type wearable device, a wristband-type wearable device, a ring-type wearable device, a waist belt-type wearable device, a necklace-type wearable device, an ankle band-type wearable device, a thigh band-type wearable device, a forearm band-type wearable device, and the like. However, the electronic device is not limited to the above examples, and the wearable device is neither limited thereto.

Referring to <FIG>, the optical sensor <NUM> includes a light source <NUM>, a photodetector array <NUM>, a processor <NUM>, an input interface <NUM>, a memory <NUM>, a communication interface <NUM>, and an output interface <NUM>. Here, the light source <NUM>, the photodetector array <NUM>, and the processor <NUM> are the same as the light source <NUM>, the photodetector array <NUM>, and the processor <NUM> respectively, such that detailed description thereof will be omitted.

The input interface <NUM> may receive input of various operation signals from a user. In an example embodiment, the input interface <NUM> may include a keypad, a dome switch, a touch pad (static pressure/capacitance type), a jog wheel, a jog switch, a hardware (H/W) button, and the like. Particularly, the touch pad, which forms a layer structure with a display, may be called a touch screen.

The memory <NUM> may store programs or commands for operation of the optical sensor <NUM>, and may store data input to and output from the optical sensor <NUM>. Further, the memory <NUM> may store the detected optical signal, the measured light intensity, the determined correlation coefficient, a quality determination result, and the like.

The memory <NUM> may include at least one storage medium of a flash memory type memory, a hard disk type memory, a multimedia card micro type memory, a card type memory (e.g., an SD memory, an XD memory, etc.), a Random Access Memory (RAM), a Static Random Access Memory (SRAM), a Read Only Memory (ROM), an Electrically Erasable Programmable Read Only Memory (EEPROM), a Programmable Read Only Memory (PROM), a magnetic memory, a magnetic disk, and an optical disk, and the like. Further, the optical sensor <NUM> may operate an external storage medium, such as web storage and the like, which performs a storage function of the memory <NUM> on the Internet.

The communication interface <NUM> may perform communication with an external device. For example, the communication interface <NUM> may transmit, to the external device, the data input to the optical sensor <NUM>, data stored in and processed by the optical sensor <NUM>, and the like, or may receive, from the external device, various data useful for detecting an optical signal, measuring a light intensity, and determining quality of an optical signal.

In an example embodiment, the external device may be medical equipment using the data input to the optical sensor <NUM>, the data stored in and processed by the optical sensor <NUM>, and the like, and/or the external device may be a printer to print out results, and/or a display to display the results. In addition, the external device may be a digital TV, a desktop computer, a cellular phone, a smartphone, a tablet PC, a laptop computer, a personal digital assistant (PDA), a portable multimedia player (PMP), a navigation, an MP3 player, a digital camera, a wearable device, and the like, but is not limited thereto.

The communication interface <NUM> may communicate with an external device by using Bluetooth communication, Bluetooth Low Energy (BLE) communication, Near Field Communication (NFC), WLAN communication, Zigbee communication, Infrared Data Association (IrDA) communication, Wi-Fi Direct (WFD) communication, Ultra-Wideband (UWB) communication, Ant+ communication, WIFI communication, Radio Frequency Identification (RFID) communication, <NUM> communication, <NUM> communication, <NUM> communication, and the like. However, this is merely an example and is not intended to be limiting.

The output interface <NUM> may output the data input to the optical sensor <NUM>, the data stored in and processed by the optical sensor <NUM>, and the like. In an example embodiment, the output interface <NUM> may output the data input to the optical sensor <NUM>, the data stored in and processed by the optical sensor <NUM>, and the like, by using at least one of an acoustic method, a visual method, and a tactile method. To this end, the output interface <NUM> may include a display, a speaker, a vibrator, and the like.

<FIG> is a block diagram illustrating an example of an apparatus <NUM> for estimating a blood concentration. The blood concentration estimating apparatus <NUM> of <FIG> is an apparatus for non-invasively estimating a blood concentration of an analyte or a change in blood concentration of an analyte by using an optical signal, and may be embedded in the aforementioned electronic device or may be enclosed in a housing to be provided as a separate device. Examples of the analyte may include glucose, triglyceride, cholesterol, protein, lactate, ethanol, uric acid, ascorbic acid, and the like.

Referring to <FIG>, the blood concentration estimating apparatus <NUM> includes an optical sensor <NUM> and a processor <NUM>. Here, the optical sensor <NUM> is the same as the optical sensors <NUM> and <NUM> of <FIG> and <FIG>, such that detailed description thereof will be omitted. The processor <NUM> may be implemented as a separate component from an internal processor of the optical sensor <NUM>, or may be integrally formed with the internal processor of the optical sensor <NUM>.

The processor <NUM> may control the overall operation of the blood concentration estimating apparatus <NUM>.

The processor <NUM> may determine a change in optical characteristics based on a light intensity measured by the optical sensor <NUM>. The optical characteristics may include at least one of a scattering coefficient and an effective attenuation coefficient.

In an example embodiment, the processor <NUM> may determine a scattering coefficient using the following Equation <NUM>, and may determine a change in the scattering coefficient based on the determined scattering coefficient and an initial value of the scattering coefficient.

Herein, µs' denotes the scattering coefficient, µa denotes the absorption coefficient, ρ<NUM> denotes a distance between a light source and a first photodetector, ρ<NUM> denotes a distance between a light source and a second photodetector, R(ρ<NUM>) denotes a light intensity measured for each distance by the first photodetector, and R(ρ<NUM>) denotes a light intensity measured for each distance by the second photodetector.

In another embodiment, the processor <NUM> may determine an effective attenuation coefficient using the aforementioned Equation <NUM> or Equation <NUM>, and may determine a change in the effective attenuation coefficient based on the determined effective attenuation coefficient and an initial value of the effective attenuation coefficient.

Upon determining a change in optical characteristics, the processor <NUM> may estimate a change in blood concentration of an analyte by using the determined change in optical characteristics and a blood concentration estimation model. The blood concentration estimation model defines a correlation between the change in optical characteristics and the change in blood concentration of the analyte, and may be generated by regression analysis or machine learning. Examples of the regression analysis algorithm may include simple linear regression, multi linear regression, logistic regression, proportional Cox regression, and the like, and examples of the machine learning may include Artificial Neural Network, Decision Tree, Genetic Algorithm, Genetic Programming, K-Nearest Neighbor, Radial Basis Function Network, Random Forest, Support Vector Machine, deep-learning, and the like.

In addition, the processor <NUM> may estimate a blood concentration based on the estimated change in blood concentration and an initial value of the blood concentration.

<FIG> is a block diagram illustrating another example of an apparatus <NUM> for estimating a blood concentration. The blood concentration estimating apparatus <NUM> is an apparatus for non-invasively estimating blood concentration of an analyte or a change in blood concentration of an analyte by using an optical signal, and may be embedded in the aforementioned electronic device or may be enclosed in a housing to be provided as a separate device.

Referring to <FIG>, the blood concentration estimating apparatus <NUM> includes an optical sensor <NUM>, a processor <NUM>, an input interface <NUM>, a memory <NUM>, a communication interface <NUM>, and an output interface <NUM>. Here, the optical sensor <NUM> and the processor <NUM> are the same as the optical sensor <NUM> and the processor <NUM> of <FIG> respectively, such that detailed description thereof will be omitted. Further, the input interface <NUM>, the memory <NUM>, the communication interface <NUM>, and the output interface <NUM> of <FIG> are the same as or substantially similar to the input interface <NUM>, the memory <NUM>, the communication interface <NUM>, and the output interface <NUM> of <FIG> respectively, such that description thereof will be briefly made.

The input interface <NUM> may receive input of various operation signals from a user.

The memory <NUM> may store programs or commands for operation of the blood concentration estimating apparatus <NUM>, and may store data input to and output from the blood concentration estimating apparatus <NUM>. Further, the memory <NUM> may store the detected optical signal, the measured light intensity, the determined correlation coefficient, a quality determination result, a change in blood concentration of an analyte, a blood concentration of an analyte, and the like.

The communication interface <NUM> may perform communication with an external device. For example, the communication interface <NUM> may transmit, to the external device, the data input to the blood concentration estimating apparatus <NUM>, the data stored in and processed by the blood concentration estimating apparatus <NUM>, and the like, or may receive, from the external device, various data useful for detecting an optical signal, measuring a light intensity, determining the quality of an optical signal, determining optical characteristics, estimating a blood concentration of an analyte, and the like.

The output interface <NUM> may output the data input to the blood concentration estimating apparatus <NUM>, data stored in and processed by the blood concentration estimating apparatus <NUM>, and the like.

<FIG> is a block diagram illustrating an example of a system <NUM> for estimating a blood concentration. The blood concentration estimating system of <FIG> may be an example where an optical sensor and a blood concentration estimating apparatus are provided as separate components.

Referring to <FIG>, the blood concentration estimating system <NUM> includes an optical sensor <NUM> and a blood concentration estimating apparatus <NUM>.

The optical sensor <NUM> includes a light source <NUM>, a photodetector array <NUM>, a processor <NUM>, and a communication interface <NUM>. The light source <NUM>, the photodetector array <NUM>, and the processor <NUM> may be the same as the light source <NUM>, the photodetector array <NUM>, and the processor <NUM> of <FIG> respectively.

That is, the light source <NUM> emits light onto an object, and the photodetector array <NUM> measures a light intensity by detecting an optical signal returning from the object. The processor <NUM> determines the quality of the optical signal based on the measured light intensity; and upon determining that the quality of the optical signal is less than the acceptable level, the processor <NUM> discards the measured value and controls the light source <NUM> and the photodetector array <NUM> to re-emit light and to re-measure a light intensity.

The processor <NUM> may transmit an optical signal of an acceptable level or higher quality and a light intensity to the blood concentration estimating apparatus <NUM> through the communication interface <NUM> by using various communication techniques. For example, the communication techniques may include Bluetooth communication, Bluetooth Low Energy (BLE) communication, Near Field Communication (NFC), WLAN communication, Zigbee communication, Infrared Data Association (IrDA) communication, Wi-Fi Direct (WFD) communication, Ultra-Wideband (UWB) communication, Ant+ communication, WIFI communication, Radio Frequency Identification (RFID) communication, <NUM> communication, <NUM> communication, <NUM> communication, and the like.

The blood concentration estimating apparatus <NUM> may perform the function of the processor <NUM> of <FIG>. That is, the blood concentration estimating apparatus <NUM> may determine optical characteristics of an object by receiving the optical signal and the light intensity from the optical sensor <NUM>, and may estimate a change in blood concentration of an analyte and/or a blood concentration of the analyte based on the determined optical characteristics.

<FIG> is a flowchart illustrating an example of a method of measuring an optical signal. The optical signal measuring method of <FIG> may be performed by the optical sensors <NUM> and <NUM> of <FIG> and <FIG>.

Referring to <FIG>, the optical sensor emits light onto an object in <NUM>. For example, the optical sensor emits light of a predetermined wavelength, e.g., near infrared (NIR) light, onto an object. However, wavelengths of light to be emitted by a light source may vary depending on a purpose of measurement and/or the types of analytes.

The optical sensor detects an optical signal reflected or scattered from the object, and measures a light intensity of the detected optical signal in <NUM>.

The optical sensor determines a correlation coefficient between predetermined variables based on the measured light intensity in <NUM>. The variables for determining the correlation coefficient are obtained from an effective attenuation coefficient calculating equation. The effective attenuation coefficient calculating equation is expressed by Equation <NUM> or Equation <NUM>.

In an example embodiment, the optical sensor may determine a correlation coefficient between <MAT> and ρ by using <MAT> and ρ of Equation <NUM> as variables.

In another embodiment, the optical sensor may determine a correlation coefficient between R(ρ) and ρ-<NUM> by using R(ρ) and ρ-<NUM> of Equation <NUM> as variables.

The optical sensor determines the quality of an optical signal based on the determined correlation coefficient in <NUM>. For example, the optical sensor compares the correlation coefficient with a predetermined threshold Th; and in response to the correlation coefficient exceeding the predetermined threshold Th, the optical sensor determines that the quality of an optical signal is an acceptable level or higher, and in response to the correlation coefficient being less than or equal to the predetermined threshold Th, the optical sensor determines that the quality of an optical signal is less than the acceptable level.

Upon determining that the quality of the optical signal is less than the acceptable level, the optical sensor discards the measured value in <NUM>, and returns to the operation <NUM> to re-emit light onto an object, re-detect an optical signal, and re-measure a light intensity.

Further, upon determining that the quality of the optical signal is an acceptable level or higher, the optical sensor terminates measurement.

<FIG> is a flowchart illustrating an example of a method of estimating a blood concentration of an analyte. The blood concentration estimating method of <FIG> may be performed by the blood concentration estimating apparatuses <NUM> and <NUM> of <FIG> and <FIG>.

Referring to <FIG>, the blood concentration estimating apparatus emits light onto an object in <NUM>. For example, the blood concentration estimating apparatus may emit light of a predetermined wavelength (e.g., near infrared (NIR) light) onto an object.

The blood concentration estimating apparatus detects an optical signal reflected or scattered from the object, and measures a light intensity of the detected optical signal in <NUM>.

The blood concentration estimating apparatus determines a correlation coefficient between predetermined variables based on the measured light intensity in <NUM>. The variables for determining the correlation coefficient areobtained from an equation for calculating an effective attenuation coefficient of the object irradiated by the light source. The effective attenuation coefficient calculating equation is expressed by Equation <NUM> or Equation <NUM>.

For example, the blood concentration estimating apparatus may determine a correlation coefficient between <MAT> and ρ by using <MAT> and ρ of Equation <NUM> as variables; or may determine a correlation coefficient between R(ρ) and ρ-<NUM> by using R(ρ) and ρ-<NUM> of Equation <NUM> as variables.

The blood concentration estimating apparatus determines the quality of an optical signal based on the determined correlation coefficient in <NUM>. For example, the blood concentration estimating apparatus compares the correlation coefficient with a predetermined threshold Th; and in response to the correlation coefficient exceeding the predetermined threshold Th, the blood concentration estimating apparatus determines that the quality of an optical signal is an acceptable level or higher, and in response to the correlation coefficient being less than or equal to the predetermined threshold Th, the blood concentration estimating apparatus determines that the quality of an optical signal is less than the acceptable level.

Upon determining that the quality of the optical signal is an acceptable level or higher, the blood concentration estimating apparatus determines a change in optical characteristics based on the measured light intensity in <NUM>. The optical characteristics may include at least one of a scattering coefficient and an effective attenuation coefficient.

In an example embodiment, the blood concentration estimating apparatus may determine an effective attenuation coefficient by using the aforementioned Equation <NUM> or Equation <NUM>, and may determine a change in the effective attenuation coefficient based on the determined effective attenuation coefficient and an initial value of the effective attenuation coefficient.

In another embodiment, the blood concentration estimating apparatus may determine a scattering coefficient by using the aforementioned Equation <NUM>, and may determine a change in the scattering coefficient based on the determined scattering coefficient and an initial value of the scattering coefficient.

Upon determining the change in optical characteristics, the blood concentration estimating apparatus may estimate a change in blood concentration of an analyte by using the determined change in optical characteristics and a blood concentration estimation model, and may estimate a blood concentration of the analyte based on the estimated change in blood concentration and an initial value of the blood concentration in <NUM>. The blood concentration estimation model defines a correlation between the change in optical characteristics and the change in blood concentration of the analyte, and may be generated by regression analysis or machine learning. Examples of the regression analysis algorithm may include, but not limited to, simple linear regression, multi linear regression, logistic regression, proportional Cox regression, and the like, and examples of the machine learning may include, but not limited to, Artificial Neural Network, Decision Tree, Genetic Algorithm, Genetic Programming, K-Nearest Neighbor, Radial Basis Function Network, Random Forest, Support Vector Machine, deep-learning, and the like.

Upon determining that the quality of the optical signal is less than the acceptable level, the blood concentration estimating apparatus discards the measured value in <NUM>, and returns to the operation <NUM> to re-emit light onto an object, re-detect an optical signal returning from the object, and re-measure a light intensity.

The disclosure can be realized as a computer-readable code written on a computer-readable recording medium. The computer-readable recording medium may be any type of recording device in which data is stored in a computer-readable manner. Examples of the computer-readable recording medium include a ROM, a RAM, a CD-ROM, a magnetic tape, a floppy disc, an optical data storage, and a carrier wave (e.g., data transmission through the Internet). The computer-readable recording medium can be distributed over a plurality of computer systems connected to a network so that a computer-readable code is written thereto and executed therefrom in a decentralized manner. Functional programs, codes, and code segments needed for realizing the disclosure can be easily deduced by one of ordinary skill in the art.

Claim 1:
An optical sensor (<NUM>, <NUM>, <NUM>, <NUM>, <NUM>) comprising:
a light source (<NUM>, <NUM>, <NUM>) configured to emit light;
a photodetector array (<NUM>, <NUM>, <NUM>) comprising a plurality of photodetectors positioned at different distances from the light source, each photodetector being configured to detect an optical signal returning from an object irradiated by the light emitted by the light source, and to measure a light intensity of the detected optical signal; and
a processor (<NUM>, <NUM>, <NUM>, <NUM>, <NUM>) configured to determine a correlation coefficient between
(i) <MAT> and ρ,
or
(ii) R(p) and ρ-<NUM>,
based on the measured light intensity,
wherein ρ denotes a distance between the light source and a photodetector of the plurality of photodetectors, R(ρ) denotes a light intensity measured by the photodetector positioned away from the light source by the distance ρ, and S<NUM> denotes a light intensity emitted by the light source,
and wherein the processor is further configured to compare the determined correlation coefficient with a predetermined threshold, wherein,
based on the determined correlation coefficient exceeding a threshold, the processor is further configured to determine that a quality of the optical signal is the acceptable level or higher, and, based on the determination that the quality of the optical signal is the acceptable level or higher, the processor is further configured to provide the measured light intensity to an apparatus for measuring optical characteristics of the object; and based on the determined correlation coefficient being less than or equal to the threshold, the processor is further configured to determine that the quality of the optical signal is less than the acceptable level, and based on the determination that the quality of the optical signal is less than the acceptable level, the processor is further configured to discard the measured light intensity, and to control the light source and the photodetector array to repeatedly perform the emitting of the light and to measure the light intensity.