KR20240065523A - Apparatus and method for estimating analyte concentration - Google Patents

Abstract

The present invention relates to a sample concentration estimation device, which includes an electrode unit that contacts or is inserted into the analysis target and detects a sample signal corresponding to the sample included in the analysis target, and is formed on the upper part of the electrode unit to determine biocompatibility, sample selectivity, and limitation. It is characterized by including a membrane that uses at least one characteristic, and a processor that generates a signal to be applied to the electrode unit and estimates the concentration of the sample based on the sample signal detected through the electrode unit.

Description

Sample concentration estimation device and method {APPARATUS AND METHOD FOR ESTIMATING ANALYTE CONCENTRATION}

The present invention relates to a sample concentration estimation device and method, and more specifically, to a sample concentration estimation device and method that can estimate the concentration of a sample existing in a living body.

Various medical devices are being developed to diagnose a patient's health condition. These medical devices measure the concentration of samples such as blood sugar in the process of diagnosing a patient's health condition. Generally, an invasive method is used to measure the concentration of a sample such as blood sugar. Although devices using the invasive method have high accuracy, they may cause risks such as pain and infection to the patient during the process of measuring the concentration of the sample. Not only does the possibility exist, but there is also the problem of poor usability.

The background technology of the present invention is disclosed in 'Portable Blood Sugar Meter' in Republic of Korea Patent Publication No. 10-1605110 (March 15, 2016).

An object of one aspect of the present invention is to provide a sample concentration estimation device and method that can accurately estimate the concentration of a sample present in a living body based on information collected through a multimodal sensor.

An apparatus for estimating sample concentration according to one aspect of the present invention includes an electrode unit that is in contact with or inserted into an analysis target and detects a sample signal corresponding to a sample included in the analysis target; A membrane formed on top of the electrode unit to utilize at least one of the following characteristics: biocompatibility, sample selectivity, and restriction; and a processor that generates a signal to be applied to the electrode unit and estimates the concentration of the sample based on the sample signal detected through the electrode unit.

In the present invention, the sample signal is characterized in that it includes information about at least one of current, voltage, impedance, frequency, and resonance frequency.

The present invention further includes a memory storing a first concentration estimation model in which relationship information regarding the concentration of the specimen according to the specimen signal is learned, wherein the processor connects the electrode to the first concentration estimation model stored in the memory. It is characterized by estimating the concentration of the sample by applying the sample signal detected through the method.

In the present invention, the processor collects the sample signal from the analysis object through the electrode unit and corrects the first concentration estimation model based on the collected sample signal.

In the present invention, the electrode unit includes at least one electrode, and the electrode is an invasive electrode or a non-invasive electrode.

In the present invention, the invasive electrode is characterized as a needle electrode or microneedle electrode.

In the present invention, an enzyme layer is formed on the entire or end portion of the electrode, and the enzyme layer is formed on part or all of the plurality of electrodes.

In the present invention, the electrode unit is characterized in that it includes a thermal electrode.

In the present invention, the processor detects a biological signal related to the analysis target through the electrode unit, and the biological signal includes information about at least one of an electrocardiogram and a pulse wave.

The present invention further includes a sensor unit that detects at least one of an optical signal and a photoacoustic signal for the analysis target, wherein the processor detects at least one of the optical signal and the photoacoustic signal detected through the sensor unit. It is characterized by estimating the concentration of the sample.

In the present invention, the sensor unit detects the optical signal by irradiating light to the analysis target and receiving light reflected from the analysis target.

In the present invention, the sensor unit detects the photoacoustic signal by irradiating light to the analysis target and receiving sound emitted from the analysis target.

The present invention is characterized in that it further includes an auxiliary electrode unit that detects the sample signal by contacting or inserted into an area of the analysis target that is different from the area in contact with the electrode unit.

In the present invention, the auxiliary electrode unit is characterized in that it is formed in the shape of an ear clip.

According to one aspect of the present invention, the present invention can accurately estimate the concentration of a sample existing in a living body and provide information about the estimated concentration of the sample to the user.

Additionally, according to one aspect of the present invention, the present invention can reduce the risk of pain, discomfort, infection, etc. that occurs in the process of estimating the concentration of a sample existing in a living body.

Meanwhile, the effects of the present invention are not limited to the effects mentioned above, and other effects not mentioned can be clearly understood by those skilled in the art from the description below.

Figure 1 is a block diagram showing a sample concentration estimation device according to a first embodiment of the present invention.
Figure 2 is a perspective view showing a sample concentration estimation device according to the first embodiment of the present invention.
Figure 3 is an exemplary diagram showing the sample concentration estimation device attached according to the first embodiment of the present invention.
Figure 4 is an exemplary diagram showing various embodiments of the electrode unit.
Figure 5 is a cross-sectional view showing a sample concentration estimation device according to the first embodiment of the present invention.
Figure 6 is an exemplary diagram showing various embodiments of combinations of electrodes included in the electrode unit.
Figure 7 is a perspective view showing a sample concentration estimation device according to another embodiment of the present invention.
Figure 8 is a cross-sectional view showing a sample concentration estimation device according to another embodiment of the present invention.
Figure 9 is an example diagram showing relationship information about the concentration of a sample according to impedance.
Figure 10 is a block diagram showing a sample concentration estimation device according to a second embodiment of the present invention.
Figure 11 is a perspective view showing a sample concentration estimation device according to a second embodiment of the present invention.
Figure 12 is a block diagram showing a sample concentration estimation device according to a third embodiment of the present invention.
Figure 13 is a perspective view showing a sample concentration estimation device according to a third embodiment of the present invention.
Figure 14 is a flowchart showing a method for estimating sample concentration according to an embodiment of the present invention.
Figure 15 is an exemplary diagram showing the effect of the sample concentration estimation device according to an embodiment of the present invention.

Hereinafter, a sample concentration estimation device and method according to an embodiment of the present invention will be described in detail with reference to the attached drawings. In this process, the thickness of lines or sizes of components shown in the drawings may be exaggerated for clarity and convenience of explanation. In addition, the terms described below are terms defined in consideration of functions in the present invention, and may vary depending on the intention or custom of the user or operator. Therefore, definitions of these terms should be made based on the content throughout this specification.

Figure 1 is a block diagram showing a sample concentration estimating device according to a first embodiment of the present invention, Figure 2 is a perspective view showing a sample concentration estimating device according to a first embodiment of the present invention, and Figure 3 is a block diagram showing a sample concentration estimating device according to a first embodiment of the present invention. It is an exemplary diagram showing the sample concentration estimation device attached according to the first embodiment, Figure 4 is an exemplary diagram showing various embodiments of the electrode unit, and Figure 5 is a diagram showing the sample concentration according to the first embodiment of the present invention. It is a cross-sectional view showing the estimation device, Figure 6 is an exemplary diagram showing various embodiments of the combination of electrodes included in the electrode unit, Figure 7 is a perspective view showing a sample concentration estimation device according to another embodiment of the present invention, Figure 8 is a cross-sectional view showing a sample concentration estimation device according to another embodiment of the present invention, and Figure 9 is an exemplary diagram showing relationship information about sample concentration according to impedance.

Referring to Figures 1 and 2, the sample concentration estimation device 10 according to the first embodiment of the present invention includes a substrate 110, an electrode unit 120, a communication unit 130, a battery 140, and a memory 150. ) and a processor 160. The sample concentration estimation device 10 according to the first embodiment of the present invention may further include various components in addition to those shown in FIG. 1, or some of the above components may be omitted. The sample concentration estimation device 10 according to an embodiment of the present invention may be implemented in a wearable form such as a band, patch, or ear clip, or may be implemented in a form that can be implanted into the body. The sample concentration estimation device 10 may be attached to the user's body, as shown in FIG. 3 .

The electrode unit 120 may be formed on the lower part of the substrate 110 . The electrode unit 120 may be in contact with or inserted into an analysis target (i.e., a subject), detect a sample signal corresponding to a sample included in the analysis target, and output the detected sample signal to the processor 160. Here, the analysis target may refer to the user's body to which the sample concentration estimation device 10 is attached. The electrode unit 120 may apply various signals to the analysis target under the control of the processor 160 to detect the sample signal. The sample concentration estimation device 10 according to an embodiment of the present invention may include at least one electrode unit 120.

The electrode unit 120 may include at least one electrode 121 provided to contact or be inserted into an analysis object. Electrodes 121 may be invasive or non-invasive. The invasive electrode may be formed to be insertable into an analysis target. Invasive electrodes may be implemented in the form of needles or microneedles. Non-invasive electrodes can be implemented in the form of dry electrodes or wet electrodes. Non-invasive electrodes can be formed to be able to contact the analysis target. For example, non-invasive electrodes can contact the user's skin. The cross-section of the non-invasive electrode may be triangular, square, circular, or a combination of square and circular. However, the shape of the electrode 121 is not limited to the above-described embodiment, and the electrode 121 may be implemented in various shapes. The electrode unit 120 may be implemented as including a plurality of electrodes, as shown in FIGS. 4A and 4B. Additionally, the electrode unit 120 may be implemented in a form including microneedles, as shown in FIG. 4C. Additionally, the electrode unit 120 may be implemented in a form including a flat electrode (eg, a dry electrode), as shown in FIG. 4D.

The electrode 121 may be made of carbon nanotubes (CNTs) or graphene. Carbon nanotubes or graphene have excellent conductivity, so sample signals can be detected from the analysis target more accurately.

An enzyme layer 122 may be formed on the entire or end portion of the electrode 121. The enzyme layer 122 may include an enzyme, and the enzyme may induce an electrochemical action by reacting the sample included in the analysis object. According to one embodiment, the enzyme may consist of GOx, GDH, etc. The enzyme layer 122 can be formed only when the electrode 121 is implemented in an invasive manner. A membrane 123 may be formed on the entire electrode 121 or at an end. The membrane 123 may be formed on top of the enzyme layer 122 and may selectively transmit and restrict substances so that the sample included in the analysis object can react with the enzyme. In other words, the membrane 123 can exclude or block substances or cells other than the sample so that they do not react with the enzyme. In order to implement the above-described function, the membrane 123 may utilize at least one of the characteristics of biocompatibility, sample selectivity, and restriction. More specifically, the membrane 123 has characteristics that adjust the degree of biocompatibility to correspond to the sample whose concentration is to be estimated, sample selectivity that allows only the sample whose concentration is to be estimated while adjusting the concentration of the transmitted sample, At least one or more of the following characteristics can be used: a limitation that limits the penetration of specific specimens other than the specimen whose concentration is to be estimated while adjusting the degree of limitation. This membrane 123 may include a hydrophilic polymer material and a hydrophobic polymer material. An insulating layer 124 may be formed in the area of the electrode 121 excluding the area in contact with the analysis target.

On the other hand, when the electrodes 121 are comprised of a plurality of electrodes and the membrane 123 is formed on the plurality of electrodes 121, the shape and size of the membrane 123 formed on each electrode 121 may be different from each other. . In this way, the present invention can distinguish interfering species by adjusting the shape and size of the membrane 123, for example, when measuring changes in the elasticity and density of red blood cells using impedance.

Figure 5a is an exemplary diagram showing a case where an enzyme layer and a membrane are formed on an electrode. Referring to Figure 5a, the enzyme layer 122 is laminated on the top (outside) of the electrode 121 in a form surrounding the electrode 121, and the membrane 123 is laminated in a form surrounding the enzyme layer 122, forming an enzyme layer ( 122) can be laminated on the top (outside). Figure 5b is an example diagram showing a case where an enzyme layer 122, a membrane 123, and an insulating layer 124 are formed on the electrode 121. Referring to FIG. 5B, the insulating layer 124 may be laminated on a portion of the upper portion of the membrane 123 (excluding the peak portion). Meanwhile, in the above-described embodiment, the insulating layer 124 was described as being formed on the top of the membrane 123, but when the membrane 123 is formed only at the tip of the electrode, the insulating layer 124 is formed on the enzyme layer 122. Alternatively, it may be formed on the top of the electrode 121.

When the electrode unit 120 includes a plurality of electrodes 121, some of the plurality of electrodes 121 may be invasive electrodes and others may be non-invasive electrodes. That is, the electrode unit 120 may include both invasive electrodes and non-invasive electrodes. The shape of the electrode unit 120 is not limited to the above-described embodiment, and all of the plurality of electrodes 121 included in the electrode unit 120 may be invasive electrodes or non-invasive electrodes. Non-invasive electrodes have the advantage of being able to be used semi-permanently compared to invasive electrodes formed with enzymes. In addition, non-invasive electrodes have the advantage of not requiring calibration, unlike invasive electrodes that require individual calibration of the electrode as enzymes are formed. On the other hand, invasive electrodes have the advantage of higher accuracy compared to non-invasive electrodes when used to detect the concentration of a sample. The present invention can use invasive electrodes and non-invasive electrodes in combination when measuring the concentration of a sample, and thus can have both the advantages of non-invasive electrodes and the advantages of invasive electrodes.

When the electrode unit 120 includes a plurality of electrodes 121, the enzyme layer 122 may be formed on some or all of the plurality of electrodes 121. The enzyme layer 122 may be formed only on some of the plurality of electrodes 121. In this case, the electrode portion 120 includes the electrode 121 on which the enzyme layer 122 is formed and the electrode on which the enzyme layer 122 is not formed. It can include all (121). The enzyme layer 122 may be formed on an invasive electrode.

When the electrode unit 120 includes a plurality of electrodes 121, the membrane 123 may be formed on some or all of the plurality of electrodes 121. The membrane 123 may be formed on only some of the plurality of electrodes 121. In this case, the electrode portion 120 includes an electrode 121 on which the membrane 123 is formed and an electrode 121 on which the membrane 123 is not formed. It can include everyone. The membrane 123 may be formed together with the enzyme layer 122, or may be formed independently of the enzyme layer 122. Figure 6a is an example diagram showing a case where the enzyme layer 122 and the membrane 123 are formed on some of the plurality of electrodes 121, and the enzyme layer 122 and the membrane 123 are not formed on some of the plurality of electrodes 121. 6b is an exemplary diagram showing a case where the enzyme layer 122 and the membrane 123 are formed on some of the plurality of electrodes 121, and only the enzyme layer 122 is formed on some of the plurality of electrodes 121, and Figure 6c shows the plurality of electrodes 121. This is an example showing a case where the enzyme layer 122 and the membrane 123 are formed in some of them, and only the membrane 123 is formed in some of them.

For example, when the electrode unit 120 includes four electrodes 121, three of the four electrodes 121 may be invasive electrodes and the remaining one may be a non-invasive electrode. At this time, one of the three invasive electrodes includes the enzyme layer 122 and the membrane 123, the other includes only the enzyme layer 122, and the remaining one includes the enzyme layer 122 and the membrane 123. It may not include everything. As such, in the present invention, the electrode unit 120 can be configured to include electrodes 121 of different shapes, and thus various signals can be received from the analysis target. Information detected through different types of electrodes 121 included in the electrode unit 120 can be compared by the processor 160, and information on the result of the comparison is stored in the sample detected through the electrode unit 120. It can be used to correct the concentration of a sample calculated from a signal or sample signals. As such, the present invention can not only estimate the concentration of a sample more accurately by using electrodes 121 with a plurality of different shapes, but also calculate the amount of change in sample concentration, and estimate the concentration corresponding to the sample to be measured. errors can be corrected.

Referring to FIG. 7 , the electrode unit 120 may include a first electrode unit 120-1 and a second electrode unit 120-2. The first electrode unit 120-1 and the second electrode unit 120-2 may each include at least one electrode 121. The first electrode unit 120-1 and the second electrode unit 120-2 may be implemented in different shapes. For example, when the first electrode unit 120-1 includes an invasive electrode, the second electrode unit 120-2 may include a non-invasive electrode, and the first electrode unit 120-1 When it includes the electrode 121 on which the enzyme layer 122 is formed, the second electrode portion 120-2 may include the electrode 121 on which the enzyme layer 122 is not formed, and the first electrode portion ( When 120-1 includes the electrode 121 on which the membrane 123 is formed, the second electrode portion 120-2 may include the electrode 121 on which the membrane 123 is not formed. That is, the second electrode unit 120-2 is configured according to the type of electrode 121 (invasive type, non-invasive type), whether the enzyme layer 122 is formed, whether the membrane 123 is formed, and whether the insulating layer 124 is formed. At least one part may be formed differently from the first electrode part 120-1. Referring to FIG. 8A, the enzyme layer 122 and the membrane 123 may be formed on the electrodes 121 included in the first electrode unit 120-1, but the enzyme layer 122 and the membrane 123 may be formed on the electrodes 121 included in the first electrode unit 120-1. The enzyme layer 122 and the membrane 123 may not be formed on the included electrodes 121. Referring to Figure 8b, the enzyme layer 122 and the membrane 123 may be formed on some of the electrodes included in the first electrode unit 120-1, but the enzyme layer 122 may not be formed on the rest. You can. Meanwhile, when the membrane 123 is formed on the plurality of electrodes 121, the membrane 123 may be formed on each of the plurality of electrodes 121, as shown in FIG. 8B, or may be formed on the plurality of electrodes, as shown in FIG. 8C. It may also be formed in a form that covers (121) at the same time. In this way, the present invention can estimate the concentration of the sample more accurately by estimating the concentration of the sample by using a combination of an electrode group with a membrane and an electrode group without a membrane, and by comparing the signals measured through each group. You can obtain information about nuisance species. The present invention can improve the accuracy of sample concentration estimation results by performing correction for interfering species through information on interfering species when estimating sample concentration.

The communication unit 130 can communicate with various types of external devices according to various types of communication methods. According to one embodiment, the communication unit 130 may transmit information (e.g., concentration of the sample) calculated by the processor 160 to an outside (e.g., user terminal). For example, the communication unit 130 may be a communication circuit and may be provided inside the substrate 110. According to one embodiment, the communication unit can communicate with an external device using various wired and wireless communication technologies including NFC, RFID, Bluetooth, Long Range, etc. However, it is not limited to this.

The battery 140 can supply power required for operation to the electrode unit 120, the communication unit 130, and the processor 160. The battery 140 may be charged through a wireless charging method and/or a wired charging method. The battery 140 may be provided inside the substrate 110.

The memory 150 may store various information required during the operation of the processor 160. Additionally, the memory 150 may store various information calculated during the operation of the processor 160. Memory 150 may be provided inside the substrate 110.

The processor 160 may be operatively connected to the electrode unit 120, the communication unit 130, the battery 140, and the memory 150. The processor 160 may be implemented as a central processing unit (CPU), digital signal processor (DSP), micro controller unit (MCU), or system on chip (SoC), and runs an operating system or application to run the processor. A plurality of hardware or software components connected to 160 can be controlled, various data processing and calculations can be performed, at least one command stored in the memory 150 is executed, and the execution result data is stored in the memory ( 150). A processor may be provided inside the substrate 110.

The processor 160 may detect a sample signal corresponding to a sample included in the analysis object through the electrode unit 120 and estimate the concentration of the sample based on the detected sample signal. According to one embodiment, the sample signal may include information about at least one of current, voltage, impedance, frequency, and resonance frequency. According to one embodiment, the information about impedance may include information about at least one of resistance, impedance, impedance spectrum, magnitude, phase, capacitance, inductance, electromagnetic wave impedance, and dielectric constant. According to one embodiment, the sample may include at least one of blood sugar, cholesterol, triglycerides, protein, minerals, ketones, and lactate. That is, the processor 160 detects information about at least one of current, voltage, impedance, frequency, and resonance frequency for the analysis target through the electrode unit 120, and based on the detected information, blood sugar, cholesterol, and neutral Concentrations for at least one of fat, protein, minerals, ketones, and lactate can be estimated.

The processor 160 may generate a signal and apply it to the electrode unit 120. According to one embodiment, the processor 160 can detect a sample signal by applying power to the analysis object while changing the voltage, current, or frequency, and receiving a response signal according to the application of power through the electrode unit 120. there is. For example, the processor 160 can detect a sample signal by applying AC power to the analysis target while changing the frequency in a preset band and receiving a response signal according to the application of AC power through the electrode unit 120. there is. According to one embodiment, the sample signal detected through the electrode unit 120 may be spectrum data. For example, the processor 160 may detect an impedance spectrum for an analysis target using electrochemical impedance spectroscopy (EIS) and use the detected impedance spectrum as a sample signal for estimating the concentration of the sample. In this way, the present invention can quickly identify abnormalities in the user's condition (e.g., hypoglycemia, etc.) by estimating the concentration of the sample through impedance measurement, and solve problems that occur due to inaccurately estimating the concentration of the sample (e.g., error alarm, etc.). can be solved. According to another embodiment, the processor 160 may detect a sample signal by applying a preset signal to the analysis target and receiving a response signal according to the application of the signal through the electrode unit 120.

According to one embodiment, the processor 160 may use electromagnetic waves as a signal to estimate the concentration of the sample. That is, the processor 160 uses the electrode 121 like an antenna to radiate electromagnetic waves to the analysis target through the electrode 121, receives the electromagnetic waves reflected from the analysis target through the electrode 121, and You can also use this to estimate the concentration of the sample. At this time, the processor 160 may use electromagnetic waves having a frequency between 100Hz and 60GHz. The processor 160 may apply a frequency to the analysis target while changing the frequency, receive electromagnetic waves reflected from the analysis target accordingly, and use information about the received electromagnetic waves as a sample signal. When using electromagnetic waves as a sample signal, the present invention can estimate the concentration of the sample from only one electrode 121. However, even when electromagnetic waves are used, a plurality of electrodes 121 can be used to estimate the concentration of the sample. For example, some of the plurality of electrodes 121 may be used to emit electromagnetic waves, and other parts may be used to receive electromagnetic waves. For another example, all of the plurality of electrodes 121 may be used to emit and receive electromagnetic waves.

According to one embodiment, a first concentration estimation model in which relationship information about the concentration of the sample according to the sample signal is learned may be stored in the memory 150, and the processor 160 may store the first concentration estimation model stored in the memory 150. The concentration of the sample can be estimated by applying the sample signal detected through the electrode unit 120 to the concentration estimation model. The correlation between at least one of current, voltage, impedance, frequency, and resonance frequency and the concentration of the sample may be learned in advance through deep learning or machine learning to generate a first concentration estimation model, and the processor 160 may generate the first concentration estimation model. The concentration of the sample corresponding to the sample signal detected through the electrode unit 120 can be calculated using the concentration estimation model. According to one embodiment, the first concentration estimation model may be stored in the memory 150 for each sample, and the processor 160 uses the first concentration estimation model corresponding to the sample when estimating the concentration of the sample. Concentration can be estimated. As shown in Figure 9, the impedance and the concentration of the sample have a correlation, and the processor 160 can estimate the concentration of the sample using this correlation.

According to one embodiment, the processor 160 may collect a sample signal from the analysis object through the electrode unit 120 and correct the first concentration estimation model stored in the memory 150 based on the collected sample signal. . The correlation between the sample signal and the concentration of the sample may be different for each individual. Therefore, the present invention optimizes the first concentration estimation model to suit the user by additionally learning the first concentration estimation model using personal data (i.e., sample signal collected through the electrode unit 120) to more accurately concentrate the sample. can be estimated.

According to one embodiment, when the electrode 121 is formed as shown in FIG. 7, the first electrode portion 120-1 consists of the electrode 121 on which the membrane 123 is formed, and the second electrode portion For example, in the case where (120-2) consists of the electrode 121 without the membrane 123 formed, the processor 160 is based on the first sample signal detected through the first electrode unit 120-1. to estimate the concentration of the sample, estimate the concentration of the sample based on the second sample signal detected through the second electrode unit 120-2, and estimate the concentration of the sample based on the first sample signal and the second sample signal. The concentration of the sample estimated based on the sample signal can be compared, and correction for the concentration of the sample can be performed based on the comparison result. That is, the processor 160 estimates the concentration of a specific sample through the first electrode unit 120-1 consisting of the enzyme layer 122 and the electrode 121 on which the membrane 123 is formed, and the enzyme layer 122 And the concentration of all samples, including interfering species, is estimated through the second electrode unit 120-2, which consists of the electrode 121 without the membrane 123, and the concentration of all samples, including interfering species, is estimated through the second electrode unit 120-2. The concentration of the sample can be estimated more accurately by correcting the concentration of the sample compared to the interfering species based on the estimated concentration, or by correcting the error range so that only the concentration of the sample to be estimated can be estimated.

According to one embodiment, the processor 160 may detect a biological signal for an analysis target through the electrode unit 120. According to one embodiment, the biosignal may include information about at least one of an electrocardiogram and a pulse wave. That is, the processor 160 can detect at least one of the user's electrocardiogram and pulse wave through the electrode unit 120.

According to one embodiment, the processor 160 determines the state of the analysis target based on the biological signal detected through the electrode unit 120 and generates an event to estimate the concentration of the sample based on the state of the analysis target. You can. That is, the processor 160 can determine whether an abnormality (e.g., headache, hunger, convulsions, fainting, etc.) has occurred in the user using at least one of the electrocardiogram and pulse wave, and if it is determined that an abnormality has occurred in the user, A sample signal can be detected through the electrode unit 120, and the concentration of the sample can be estimated based on the detected sample signal. According to one embodiment, the memory 150 may store a state estimation model in which relationship information regarding the state of the analysis object according to the biological signals of the analysis object is learned, and the processor 160 may store the state estimation model stored in the memory 150. The state of the analysis target can be determined by applying the biological signal detected through the electrode unit 120 to the state estimation model. For example, the processor 160 calculates at least one of heart rate variability (HRV) and/or pulse rate variability (PRV) based on the electrocardiogram and/or pulse wave, and the calculated heart rate variability and /Or, the state of the analysis target can be determined by applying the pulse wave variability to the state estimation model. That is, a state estimation model can be generated by learning the correlation between the electrocardiogram and/or pulse wave and the state of the analysis target in advance through deep learning or machine learning, and the processor 160 uses this state estimation model to generate the first The state of the analysis object corresponding to the biometric data generated through the measurement model can be estimated. In this way, the present invention can reduce power consumption by generating an event that estimates the concentration of the sample only when a specific situation occurs.

According to one embodiment, the temperature of the analysis target can be detected through the electrode unit 120. That is, the electrode unit 120 may include a thermal electrode, and temperature measurement of the analysis target may be performed through the thermal electrode.

According to one embodiment, the processor 160 may transmit information about the concentration of the sample to a preset user terminal through the communication unit 130. That is, the processor 160 can transmit information about the concentration of the sample to the user terminal of the user or guardian so that information can be confirmed. Additionally, the processor 160 may transmit information about the biosignal of the analysis target to a preset user terminal through the communication unit 130. That is, the processor 160 can transmit information about biometric signals to the user terminal so that the user can check them. Additionally, the processor 160 may transmit information about the temperature of the analysis target to a preset user terminal through the communication unit 130.

According to one embodiment, the processor 160 determines whether the concentration of the sample is within a preset setting range, and if it is determined that the concentration of the sample is not within the setting range, the user preset through the communication unit 130 A warning signal can be transmitted to the terminal. That is, when the concentration of the sample is lower than the predetermined concentration, the processor 160 can notify the user or guardian through the user terminal that the concentration of the sample has decreased below the predetermined concentration. In addition, when the concentration of the sample is higher than a predetermined concentration, the user or guardian can be notified through the user terminal that the concentration of the sample has increased above the predetermined concentration.

According to one embodiment, the processor 160 may calculate the amount of change in concentration of the sample over time based on the estimated concentration of the sample. Each time the concentration of the sample is estimated, the processor 160 can store the estimated value of the concentration of the sample and the time at which the estimate was made in the memory 150, and can store the estimated value and the estimated time stored in the memory 150 in time. The change in concentration of the sample can be calculated. The processor 160 may transmit information about the change in concentration of the sample over time to a preset user terminal through the communication unit 130. According to one embodiment, the processor 160 may predict the concentration of the sample at a future point in time based on the change in concentration of the sample over time. For example, the processor 160 may predict the concentration of the sample after a preset time and provide the predicted concentration to the user. The setting time may vary depending on the user's intention. According to one embodiment, the processor 160 may calculate the concentration change amount of the sample for a preset unit time (hereinafter referred to as sample concentration change rate) based on the sample concentration change amount over time, and the calculated concentration change rate and the preset concentration change rate may be calculated. The set standard concentration change rate can be compared, and a warning signal can be generated according to the comparison result and transmitted to the outside through the communication unit 130. That is, the processor 160 can notify the user of this fact when the concentration of the sample suddenly increases or decreases. The processor 160 can calculate the time required for the concentration of the sample to reach a preset value based on the change in concentration of the sample over time. If the calculated time is less than or equal to the preset standard time, the processor 160 can calculate the time required for the concentration of the sample to reach a preset value. A warning signal can also be transmitted to a preset user terminal.

According to one embodiment, the processor 160 may determine whether an abnormality has occurred in the electrode unit 120. According to one embodiment, the processor 160 determines whether the value of the sample signal detected through the electrode unit 120 exceeds a preset upper limit, is less than a preset lower limit, or if the sample signal is not detected through the electrode unit 120. If not, it can be determined that an abnormality has occurred in the electrode unit 120. If it is determined that an abnormality has occurred, the processor 160 may transmit information about whether an abnormality has occurred to a preset user terminal through the communication unit 130.

Meanwhile, in the above-described embodiment, the process of estimating the concentration of the sample and the process of determining the state of the analysis target are described as being performed independently by the sample concentration estimating device 10, but the above-described process is performed using a concentration estimation model or state. It may also be performed by a user terminal or an external server where the estimated model is stored. When this process is performed by an external device, the sample concentration estimation device 10 can transmit the information necessary to perform the process to the external device and receive information about the results of performing the process from the external device. .

Figure 10 is a block diagram showing a sample concentration estimation device according to a second embodiment of the present invention, and Figure 11 is a perspective view showing a sample concentration estimation device according to a second embodiment of the present invention.

Referring to Figures 10 and 11, the sample concentration estimation device 20 according to the second embodiment of the present invention includes a substrate 210, an electrode unit 220, a sensor unit 230, a communication unit 240, and a battery ( 250), memory 260, and processor 270. The sample concentration estimating device 20 according to the second embodiment may be a type in which a sensor unit 230 is added to the sample concentration estimating device 10 according to the first embodiment. Meanwhile, hereinafter, descriptions of components that overlap with those of FIG. 1 will be omitted.

The sensor unit 230 may detect at least one of an optical signal and a photoacoustic signal (optoultrasonic signal) for an analysis target under the control of the processor 270 and output the detected signal to the processor 270 . According to one embodiment, the sensor unit 230 may irradiate light to an analysis target, receive light reflected from the analysis target, and detect an optical signal for the analysis target from the received light. According to one embodiment, the sensor unit 230 may detect the photoacoustic signal by irradiating light to the analysis target and receiving sound emitted from the analysis target. According to one embodiment, the sensor unit 230 may split light received from an analysis target and detect a Raman spectrum from the split light. For example, the sensor unit 230 may detect a Raman spectrum for an analysis target using Raman spectroscopy (RS), and use the detected Raman spectrum as an optical signal for the analysis target. The sensor unit 230 may be provided at the bottom of the substrate to face the analysis target.

The processor 270 may estimate the concentration of the sample based on at least one of an optical signal and a photoacoustic signal detected through the sensor unit 230. That is, the processor 160 may estimate the concentration of the sample based on information (optical signals and photoacoustic signals) about the optical characteristics of the sample detected through the sensor unit 230.

According to one embodiment, a second concentration estimation model in which relationship information about the concentration of the sample according to the optical signal and/or photoacoustic signal is learned may be stored in the memory 260, and the processor 270 may be stored in the memory ( The concentration of the sample can be estimated by applying the optical signal and/or photoacoustic signal detected through the sensor unit 230 to the second concentration estimation model stored in 260). A second concentration estimation model can be generated by learning the correlation between the optical signal and/or photoacoustic signal and the concentration of the sample in advance through deep learning or machine learning, and the processor 270 uses the second concentration estimation model. Thus, the concentration of the sample corresponding to the optical signal and/or photoacoustic signal detected through the sensor unit 230 can be calculated. According to one embodiment, the second concentration estimation model may be stored in the memory 260 for each sample, and the processor 270 uses the second concentration estimation model corresponding to the sample when estimating the concentration of the sample. Concentration can be estimated.

According to one embodiment, the processor 270 collects optical signals and/or photoacoustic signals from the analysis object through the sensor unit 230, and stores the memory 260 based on the collected optical signals and/or photoacoustic signals. The second concentration estimation model stored in can be corrected. The correlation between the optical signal and/or photoacoustic signal and the concentration of the sample may be slightly different for each individual. Therefore, the present invention optimizes the second concentration estimation model for the user by additionally learning the second concentration estimation model using personal data (i.e., optical signals and/or photoacoustic signals collected through the sensor unit 230). This allows the concentration of the sample to be estimated more accurately.

According to one embodiment, the processor 270 estimates the concentration of the sample by using at least one of the optical signal and the photoacoustic signal detected through the sensor unit 230 and the sample signal detected through the electrode unit 220. You may. For example, the correlation between optical signals, photoacoustic signals, sample signals, and sample concentration is learned through deep learning or machine learning to create a concentration estimation model, and the concentration of the sample is determined using the generated concentration estimation model. It can also be estimated.

According to one embodiment, the processor 270 uses at least one of an optical signal and a photoacoustic signal detected through the sensor unit 230 to generate a sample signal or electrode unit 220 detected through the electrode unit 220. Correction for the concentration of the sample estimated based on the sample signal detected through can also be performed. That is, the optical signal and/or photoacoustic signal detected through the sensor unit 230 may be used as a signal for correcting the sample signal detected through the electrode unit 220 or an estimated value of the concentration of the sample. In this way, the present invention can improve the accuracy of estimating the concentration of a sample by using the information detected through the sensor unit 230 and the information detected through the electrode unit 220 in a complex manner.

Figure 12 is a block diagram showing a sample concentration estimation device according to a third embodiment of the present invention, and Figure 13 is a perspective view showing a sample concentration estimation device according to a third embodiment of the present invention.

Referring to FIGS. 12 and 13, the sample concentration estimation device 30 according to an embodiment of the present invention includes a substrate 310, an electrode unit 320, an auxiliary electrode unit 330, a communication unit 340, and a battery ( 350), memory 360, and processor 370. The sample concentration estimating device 30 according to the third embodiment may be a type in which an auxiliary electrode unit 330 is added to the sample concentration estimating device 30 according to the first or second embodiment. Meanwhile, hereinafter, descriptions of components that overlap with those of FIG. 1 will be omitted.

The auxiliary electrode unit 330 contacts an area of the analysis target that is different from the area in contact with the electrode unit 320, detects a sample signal from the analysis target under the control of the processor 370, and sends the detected sample signal to the target area. It can be output to the processor 370. That is, the auxiliary electrode unit 330 may be used to detect a sample signal for an area different from the area where the electrode unit 320 is in contact. According to one embodiment, the auxiliary electrode unit 330 may include tongs that are pressed and bound to one side of the analysis object, and an electrode (e.g., a flat electrode) may be provided on the inner cross section of the tongs that contacts the analysis object. there is. For example, the auxiliary electrode unit 330 may be implemented in the form of an ear clip that can be attached to a person's ear. A terminal to which a cable is connected may be provided on one side of the substrate 310, and the auxiliary electrode unit 330 may be connected to the substrate through a cable.

The processor 370 may estimate the concentration of the sample by complexly using the sample signal detected through the auxiliary electrode unit 330 and the sample signal detected through the electrode unit 320. For example, the correlation between the sample signal at the first and second positions and the concentration of the sample is learned through deep learning or machine learning to create a concentration estimation model, and the concentration of the sample is used using the generated concentration estimation model. can be estimated. In this way, the present invention can improve the accuracy of estimating the concentration of a sample by using the information detected through the auxiliary electrode unit 330 and the information detected through the electrode unit 320 in a complex manner.

According to one embodiment, the processor 370 may perform correction for the sample signal detected through the electrode unit 320 based on the sample signal detected through the auxiliary electrode unit 330. That is, the sample signal detected through the auxiliary electrode unit 330 can be used as a signal to correct the sample signal detected through the electrode unit 320. According to one embodiment, the processor 370 may use the sample signal detected through the auxiliary electrode unit 330 as an indicator for determining whether there is an abnormality in the sample signal detected through the electrode unit 320. That is, the processor 370 determines whether an error has occurred in the sample signal detected through the electrode unit 320 by comparing the sample signal detected through the auxiliary electrode unit 330 with the sample signal detected through the electrode unit 320. You can judge whether or not.

Figure 14 is a flowchart showing a method for estimating sample concentration according to an embodiment of the present invention. Hereinafter, with reference to FIG. 14, the operating method of the sample concentration estimation device according to the first embodiment of the present invention will be described. Meanwhile, hereinafter, detailed description of the configuration that overlaps with the above-described content will be omitted and the description will focus on the time-series configuration. Some of the processes described later may be performed in an order different from the order described later or may be omitted.

First, the processor 160 can detect a sample signal corresponding to the sample from the analysis target through the electrode unit 120 (S100). Here, the sample signal may include information on at least one of current, voltage, impedance, frequency, and resonance frequency.

Next, the processor 160 may estimate the concentration of the sample based on the sample signal (S200). The processor 160 may estimate the concentration of the sample by applying the sample signal detected through the electrode unit 120 to the first concentration estimation model stored in the memory 150.

Subsequently, the processor 160 may transmit information about the estimated concentration of the sample to a preset user terminal through the communication unit 130 (S300). That is, the processor 160 can transmit information about the concentration of the sample to the user terminal so that the user can check it.

Figure 15 is an exemplary diagram showing the effect of the sample concentration estimation device according to an embodiment of the present invention. Referring to Figure 15, it can be seen that in the case of a conventional CGM (Continuous Glucose Monitor, red), there is a delay time (about 15 minutes) in checking changes in blood sugar. On the other hand, it can be seen that the present invention (MGM, purple) can confirm changes in blood sugar more quickly than the conventional CGM. In the case of hypoglycemia, it can have a significant impact on the human body in about 15 minutes. However, in the case of the present invention, changes in the concentration of the sample can be quickly confirmed, so it can effectively support the user even in situations that require a rapid response, such as hypoglycemia.

As described above, the sample concentration estimation device and method according to an embodiment of the present invention can accurately estimate the concentration of a sample existing in a living body and provide information about the estimated concentration of the sample to the user. Additionally, the sample concentration estimation device and method according to an embodiment of the present invention can reduce the risk of pain, discomfort, infection, etc. that occurs in the process of estimating the concentration of a sample existing in a living body. In addition, the sample concentration estimation device and method according to an embodiment of the present invention corrects the result of estimating the concentration of the sample through signals collected through various sensors in the process of estimating the concentration of the sample, thereby making it more accurate in vivo. The concentration of the sample present can be estimated.

Implementations described herein may be implemented, for example, as a method or process, device, software program, data stream, or signal. Although discussed only in the context of a single form of implementation (eg, only as a method), implementations of the features discussed may also be implemented in other forms (eg, devices or programs). The device may be implemented with appropriate hardware, software, firmware, etc. The method may be implemented in a device such as a processor, which generally refers to a processing device that includes a computer, microprocessor, integrated circuit, or programmable logic device. Processors also include communication devices such as computers, cell phones, portable/personal digital assistants (“PDAs”) and other devices that facilitate communication of information between end-users.

The present invention has been described with reference to the embodiments shown in the drawings, but these are merely illustrative, and those skilled in the art will recognize that various modifications and equivalent embodiments can be made therefrom. You will understand. Therefore, the true technical protection scope of the present invention should be determined by the scope of the patent claims below.

10: Sample concentration estimation device 110: Substrate
120: electrode unit 130: communication unit
140: Battery 150: Memory
160: Processor 20: Sample concentration estimation device
210: substrate 220: electrode portion
230: sensor unit 240: communication unit
250: Battery 260: Memory
270: Processor 30: Sample concentration estimation device
310: substrate 320: electrode portion
330: Auxiliary electrode unit 340: Communication unit
350: Battery 360: Memory
370: processor

Claims (14)

An electrode unit that is in contact with or inserted into the analysis target and detects a sample signal corresponding to the sample included in the analysis target;
A membrane formed on top of the electrode unit to utilize at least one of the following characteristics: biocompatibility, sample selectivity, and restriction; and
a processor that generates a signal to be applied to the electrode unit and estimates the concentration of the sample based on the sample signal detected through the electrode unit;
A sample concentration estimation device comprising:
According to clause 1,
The sample signal includes information on at least one of current, voltage, impedance, frequency, and resonance frequency.
According to clause 1,
a memory storing a first concentration estimation model in which relationship information regarding the concentration of the sample according to the sample signal is learned;
It further includes,
The sample concentration estimation device characterized in that the processor estimates the concentration of the sample by applying the sample signal detected through the electrode unit to the first concentration estimation model stored in the memory.
According to clause 3,
The processor collects the sample signal from the analysis object through the electrode unit, and corrects the first concentration estimation model based on the collected sample signal.
According to clause 1,
The electrode unit includes at least one electrode,
A sample concentration estimation device, characterized in that the electrode is an invasive electrode or a non-invasive electrode.
According to clause 5,
A sample concentration estimation device, wherein the invasive electrode is a needle electrode or microneedle electrode.
According to clause 5,
An enzyme layer is formed on the entire or end portion of the electrode,
When the electrode unit includes a plurality of electrodes, the enzyme layer is formed on some or all of the plurality of electrodes.
According to clause 1,
The sample concentration estimation device characterized in that the electrode unit includes a thermal electrode.
According to clause 1,
The processor detects a biological signal related to the analysis target through the electrode unit,
A sample concentration estimation device, wherein the biosignal includes information about at least one of an electrocardiogram and a pulse wave.
According to clause 1,
A sensor unit that detects at least one of an optical signal and a photoacoustic signal for the analysis target;
It further includes,
The sample concentration estimation device is characterized in that the processor estimates the concentration of the sample based on at least one of an optical signal and a photoacoustic signal detected through the sensor unit.
According to clause 10,
The sensor unit detects the optical signal by irradiating light to the analysis object and receiving light reflected from the analysis object.
According to clause 10,
The sensor unit detects the photoacoustic signal by irradiating light to the analysis target and receiving sound emitted from the analysis target.
According to clause 1,
An auxiliary electrode part that detects the sample signal by contacting or inserting into an area of the analysis target that is different from the area in contact with the electrode part;
A sample concentration estimation device further comprising:
According to clause 13,
A sample concentration estimation device, wherein the auxiliary electrode unit is formed in the shape of an ear clip.

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