Red blood cell blood glucose diagnosis system using high-frequency ultrasound and method thereof

Abstract

The present invention relates to a red blood cell blood glucose diagnosis system and method using high-frequency ultrasound, which enable efficient red blood cell blood glucose diagnosis using integrated backscatter (IB) analysis of cell membrane acoustic reflection signals of red blood cells collected using a high-frequency ultrasonic transducer. The red blood cell blood glucose diagnosis system comprises: an ultrasonic diagnosis signal processing unit for setting a diagnosis range and receiving red blood cell reflection signals reflected by applying ultrasonic signals to blood to be diagnosed; and a diagnostic signal analysis and determination unit for processing the reflected signal data received from the ultrasonic diagnostic signal processing unit and outputting glycated hemoglobin quantification and diabetes diagnosis results through integrated backscatter (IB) analysis.

Description

System and method for diagnosing red blood cell blood sugar using high-frequency ultrasound

[0001] The present invention relates to blood sugar diagnosis and management, and more particularly, to a red blood cell blood sugar diagnosis system and method using high-frequency ultrasound, which enables efficient red blood cell blood sugar diagnosis by using IB analysis (Integrated Backscatter analysis) of the cell membrane acoustic reflection signal of red blood cells collected using a high-frequency ultrasonic transducer.

[0002] In recent years, medical researchers have developed novel methods for monitoring blood sugar levels. These methods are particularly helpful for people with diabetes.

[0003] Diabetes is a serious disease that can cause problems in many body organs and systems, including the kidneys, heart, nerves, blood vessels, and eyes, for example.

[0004] People with diabetes must monitor their blood sugar levels frequently to maintain adequate levels of insulin in their blood.

[0005] By testing blood sugar levels frequently, people with diabetes can better manage their medications, diet, and exercise.

[0006] One invasive procedure for monitoring blood sugar levels involves pricking a patient's finger to obtain a blood sample. The blood sample is then analyzed and glucose concentrations are measured using an enzyme-based method.

[0007] On the other hand, noninvasive blood glucose monitoring does not involve pricking a finger or other invasive procedures on the body to collect a blood sample.

[0008] Rather, noninvasive techniques involve using optical techniques to monitor blood samples inside the body.

[0009] For example, fluorescence spectroscopy, Raman spectroscopy, surface plasmon resonance, optical interference imaging, optical polarimetry, and near-infrared spectroscopy can be used.

[0010] Most conventional non-invasive methods use incident light radiation to penetrate body tissues and monitor blood circulation within the tissues.

[0011] There is a correlation between light absorption and blood sugar concentration.

[0012] Non-invasive methods are divided into non-optical and optical methods. However, non-optical methods have the problem of large errors in measurement values ​​when body temperature and body movement change.

[0013] In the case of optical methods, there is a method of measuring blood sugar using the photoacoustic effect. Conventional blood sugar measurement methods using the photoacoustic effect used Nd:YAG lasers or variable wavelength OPO lasers, but these devices had the disadvantage of being very expensive and large in size.

[0014] Therefore, there is a need to develop new technologies that can diagnose diabetes using non-invasive characteristics, thereby reducing the pain and risk of infection in patients requiring continuous blood sugar management.

[0015] The present invention is intended to solve the problems of the blood sugar diagnosis and management technology of the prior art, and provides a red blood cell blood sugar diagnosis system and method using high frequency ultrasound, which enables efficient red blood cell blood sugar diagnosis by using IB analysis (Integrated Backscatter analysis) of the cell membrane acoustic reflection signal of red blood cells collected using a high frequency ultrasonic transducer.

[0016] The purpose of the present invention is to provide a red blood cell blood sugar diagnosis system and method using high-frequency ultrasound, which analyzes the cell membrane acoustic reflection signal of collected red blood cells using IB analysis (Integrated Backscatter analysis), thereby increasing the accuracy of diabetes diagnosis and enabling the quantification and provision of glycated hemoglobin according to blood sugar.

[0017] The purpose of the present invention is to provide a red blood cell blood sugar diagnosis system and method using high-frequency ultrasound, which enables non-invasive blood sugar diagnosis by irradiating red blood cells in blood with a signal through an ultrasound transducer, collecting the signal reflected from the red blood cells, and analyzing information on the membrane characteristics of the red blood cells using IB analysis (Integrated Backscatter analysis).

[0018] Other purposes of the present invention are not limited to the purposes mentioned above, and other purposes not mentioned will be clearly understood by those skilled in the art from the description below.

[0019] In order to achieve the above-described purpose, the present invention provides a red blood cell blood sugar diagnosis system using high-frequency ultrasound, which comprises: an ultrasound diagnosis signal processing unit that sets a diagnosis range, applies an ultrasound signal to blood to be diagnosed, and receives a reflected red blood cell signal; and a diagnostic signal analysis and judgment unit that processes the reflected signal data received from the ultrasound diagnosis signal processing unit and outputs a glycated hemoglobin quantification and diabetes diagnosis result through IB analysis (Integrated Backscatter analysis).

[0020] Here, the ultrasonic diagnostic signal processing unit is configured to include a high-frequency ultrasonic transducer and a pulse application / receiver, and the single-element high-frequency ultrasonic transducer having LiNbO3 as a piezoelectric material converts an electric signal applied through the pulse application / receiver into an acoustic signal, applies the signal to red blood cells in a prepared blood sample, and converts the ultrasonic signal reflected from the red blood cells into an electric signal and transmits the converted signal to the pulse application / receiver.

[0021] And, the ultrasound diagnostic signal processing unit is characterized in that it learns the diagnostic result data to set the diagnostic range and optimizes the diagnostic range by reflecting individual characteristics to set the diagnostic range.

[0022] And IB analysis (Integrated Backscatter analysis) is characterized by using high-frequency ultrasound to measure the intensity of the ultrasound reflection signal that reflects the changed characteristics of the red blood cell membrane, and classifies the signal according to the blood sugar level, by utilizing the fact that the glycated hemoglobin level of red blood cells increases as the blood sugar level increases and the characteristics of the red blood cell membrane change according to the glycated hemoglobin level.

[0023] And, the ultrasound diagnosis signal processing unit is characterized by including a diagnosis range setting unit that sets a range for diagnosing hypoglycemia, normal blood sugar, and hyperglycemia, an ultrasound signal applying unit that applies an ultrasound signal to blood to be diagnosed, and a red blood cell reflection signal receiving unit that collects ultrasound reflection signals of red blood cells in the blood.

[0024] And, the diagnostic range setting unit is characterized by including a diagnostic result data learning unit that learns diagnostic result data to set a diagnostic range that reflects individual characteristics, and a diagnostic range optimization unit that performs optimization to enable setting a diagnostic range that reflects individual characteristics using the diagnostic result data learning result.

[0025] And the diagnostic signal analysis and judgment unit is characterized by including a reflection signal data processing unit that converts the ultrasonic reflection signal of the red blood cells in the collected blood into data, an IB analysis unit that analyzes the intensity of the ultrasonic reflection signal reflecting the changed characteristics of the red blood cell membrane by using IB analysis (Integrated Backscatter analysis) to classify it according to the blood sugar level by using the characteristics of the red blood cell membrane that change according to the glycated hemoglobin level, a glycated hemoglobin quantification unit that performs glycated hemoglobin quantification using the analysis results of the IB analysis unit, and a diabetes diagnosis result output unit that outputs a diagnosis result based on the quantified glycated hemoglobin data.

[0026] According to the present invention, a method for diagnosing red blood cell blood sugar levels using high-frequency ultrasound to achieve another object is characterized by including a diagnostic range setting step for setting ranges for diagnosing hypoglycemia, normal blood sugar, and hyperglycemia; an ultrasonic signal applying step for applying an ultrasonic signal to blood to be diagnosed; a red blood cell reflection signal receiving step for collecting ultrasonic reflection signals of red blood cells in the blood; a reflection signal data processing step for converting the collected ultrasonic reflection signals of red blood cells in the blood into data; an IB analysis step for analyzing the intensity of the ultrasonic reflection signal reflecting the changed characteristics of the red blood cell membrane by using IB analysis (Integrated Backscatter analysis) to classify the result according to the blood sugar level by utilizing the fact that the characteristics of the red blood cell membrane change according to the glycated hemoglobin level; and a diabetes diagnosis result output step for performing glycated hemoglobin quantification using the IB analysis result and outputting the diagnosis result based on the quantified glycated hemoglobin data.

[0027] Here, the diagnostic range setting step is characterized by including a diagnostic result data learning step for learning diagnostic result data to set a diagnostic range reflecting individual characteristics, and a diagnostic range optimization step for performing optimization to enable setting a diagnostic range reflecting individual characteristics using the diagnostic result data learning result.

[0028] The red blood cell blood sugar diagnosis system and method using high-frequency ultrasound according to the present invention as described above has the following effects.

[0029] First, the cell membrane acoustic reflection signal of red blood cells collected using a high frequency ultrasonic transducer is used for IB analysis (Integrated Backscatter analysis) to enable efficient red blood cell blood sugar diagnosis.

[0030] Second, the cell membrane acoustic reflection signal of the collected red blood cells is analyzed using IB analysis (Integrated Backscatter analysis) to increase the accuracy of diabetes diagnosis and to provide quantified glycated hemoglobin according to blood sugar level.

[0031] Third, non-invasive blood sugar diagnosis is possible by examining signals from red blood cells in the blood using an ultrasound transducer, collecting the signals reflected from the red blood cells, and analyzing information on the membrane properties of the red blood cells using IB analysis (Integrated Backscatter analysis).

[0032] Figure 1 is a configuration diagram of a red blood cell blood sugar diagnosis system using high-frequency ultrasound according to the present invention.

[0033] Figure 2 is a detailed configuration diagram of the ultrasonic diagnostic signal processing unit.

[0034] Figure 3 is a detailed configuration diagram of the diagnostic range setting unit.

[0035] Figure 4 is a detailed configuration diagram of the diagnostic signal analysis and judgment unit.

[0036] Figure 5 is a flow chart showing a red blood cell blood sugar diagnosis method using high-frequency ultrasound according to the present invention.

[0037] Hereinafter, a preferred embodiment of a red blood cell blood sugar diagnosis system and method using high-frequency ultrasound according to the present invention will be described in detail.

[0038] The features and advantages of the red blood cell blood sugar diagnosis system and method using high-frequency ultrasound according to the present invention will become apparent through the detailed description of each embodiment below.

[0039] Figure 1 is a configuration diagram of a red blood cell blood sugar diagnosis system using high-frequency ultrasound according to the present invention.

[0040] The terms used in this disclosure have been selected from widely used, current terms, taking into account the functions of the disclosure. However, these terms may vary depending on the intentions of those skilled in the art, precedents, the emergence of new technologies, etc. Furthermore, in certain cases, terms may be arbitrarily selected by the applicant, and in such cases, their meanings will be described in detail in the relevant description of the invention. Therefore, the terms used in this disclosure should not be defined simply as names, but rather based on the meanings of the terms and the overall content of the disclosure.

[0041] When a part of the specification is said to "include" a component, this does not exclude other components, but rather implies the inclusion of other components, unless otherwise specifically stated. Furthermore, terms such as "part," "module," etc., used throughout the specification refer to a unit that processes at least one function or operation, which may be implemented in hardware, software, or a combination of hardware and software.

[0042] In particular, units that process at least one function or operation may be implemented as an electronic device including at least one processor, and at least one peripheral device may be connected to the electronic device depending on the method of processing the function or operation. The peripheral devices may include a data input device, a data output device, and a data storage device.

[0043] The red blood cell blood sugar diagnosis system and method using high frequency ultrasound according to the present invention enables efficient red blood cell blood sugar diagnosis by using IB analysis (Integrated Backscatter analysis) of the cell membrane acoustic reflection signal of red blood cells collected using a high frequency ultrasonic transducer.

[0044] To this end, the present invention may include a configuration that analyzes the cell membrane acoustic reflection signal of collected red blood cells using IB analysis (Integrated Backscatter analysis) to increase the accuracy of diabetes diagnosis and to quantify and provide glycated hemoglobin according to blood sugar level.

[0045] The present invention may include a configuration that enables non-invasive blood sugar diagnosis by irradiating red blood cells in blood with a signal through an ultrasound transducer, collecting a signal reflected from the red blood cells, and analyzing information on the membrane characteristics of the red blood cells using IB analysis (Integrated Backscatter analysis).

[0046] Blood sugar levels are the concentration of glucose in the blood, and glycated hemoglobin is formed when glucose binds to hemoglobin, a component of red blood cells. Higher blood sugar levels lead to higher glycated hemoglobin levels, and the properties of red blood cell membranes change depending on the glycated hemoglobin levels.

[0047] Ultrasound is a useful diagnostic tool because it safely penetrates human tissue with high-frequency sound waves and captures reflected signals from within. As the frequency increases, the resolution increases, allowing for the detection of changes down to the cellular level.

[0048] Integrated Backscatter analysis (IB analysis) measures the intensity of reflected signals and integrates their average power to analyze biological characteristics. IB analysis provides valuable information about biological composition and status, making it useful for disease diagnosis and monitoring.

[0049] Using this, the present invention collects ultrasonic reflection signals of red blood cells using a high-frequency ultrasonic transducer, analyzes the signals through IB analysis, and quantifies glycated hemoglobin according to blood sugar levels, thereby enabling diabetes diagnosis.

[0050] The red blood cell blood sugar diagnosis system using high-frequency ultrasound according to the present invention is largely composed of a high-frequency ultrasound transducer required for blood sugar analysis of red blood cells, a pulse application / receiver that applies a pulse to the ultrasound transducer and receives the returning ultrasonic reflection signal, and an oscilloscope that visualizes and digitizes the returned ultrasonic reflection signal.

[0051] Integrated Backscatter analysis (IB analysis) is used to classify and diagnose the ultrasonic reflection signal data of red blood cells collected through an oscilloscope according to blood sugar level.

[0052] Specifically, as shown in Fig. 1, it includes an ultrasound diagnosis signal processing unit (100) that sets a diagnosis range, applies an ultrasound signal to the blood to be diagnosed, and receives a reflected red blood cell signal, and a diagnostic signal analysis and judgment unit (200) that processes the reflected signal data received from the ultrasound diagnosis signal processing unit (100) and outputs a glycated hemoglobin quantification and diabetes diagnosis result through IB analysis (Integrated Backscatter analysis).

[0053] Here, the ultrasonic diagnostic signal processing unit (100) may be configured to include a high-frequency ultrasonic transducer and a pulse application / receiver, and the diagnostic signal analysis and judgment unit (200) may be configured to include an oscilloscope, but is not limited thereto.

[0054] And the ultrasound diagnostic signal processing unit (100) can learn the diagnostic result data to set the diagnostic range and optimize the diagnostic range reflecting individual characteristics to set the diagnostic range. This is to suppress the results from changing for each examination session due to the physical and lifestyle characteristics (fasting time, etc.) of each individual.

[0055] The single element high frequency ultrasonic transducer used in the present invention is specifically described as follows.

[0056] A single-element high-frequency ultrasonic transducer having LiNbO3 as a piezoelectric material converts an electrical signal applied through a pulse source / receiver into an acoustic signal, applies it to red blood cells in prepared blood, and converts the ultrasonic signal reflected from the red blood cells back into an electrical signal and transmits it to the pulse source / receiver.

[0057] LiNbO3 has low toxicity compared to other piezoelectric materials, making it useful for biological targets.

[0058] High-frequency ultrasound transducers have high resolution and are used to detect and provide information on changes at the cellular level.

[0059] And the specific explanation of IB analysis (Integrated Backscatter analysis) is as follows.

[0060] As blood sugar levels rise, glycated hemoglobin levels in red blood cells increase, and the characteristics of the red blood cell membrane change depending on the glycated hemoglobin level. Using high-frequency ultrasound, the intensity of the ultrasound reflection signal, which reflects the altered characteristics of the red blood cell membrane, is measured.

[0061] By classifying signals according to blood sugar levels, glycated hemoglobin is quantified according to blood sugar levels, and diabetes is diagnosed.

[0062] The detailed configuration of the ultrasonic diagnostic signal processing unit (100) is as follows.

[0063] Figure 2 is a detailed configuration diagram of an ultrasonic diagnostic signal processing unit.

[0064] The ultrasound diagnosis signal processing unit (100) includes, as shown in Fig. 2, a diagnosis range setting unit (21) that sets the range for diagnosing hypoglycemia, normal blood sugar, and hyperglycemia, an ultrasound signal applying unit (22) that applies an ultrasound signal to the blood to be diagnosed, and a red blood cell reflection signal receiving unit (23) that collects ultrasound reflection signals of red blood cells in the blood.

[0065] Here, the detailed configuration of the diagnostic range setting unit (21) is as follows.

[0066] Figure 3 is a detailed configuration diagram of the diagnostic range setting section.

[0067] The diagnostic range setting unit (21) includes a diagnostic result data learning unit (21a) that learns diagnostic result data to set a diagnostic range that reflects individual characteristics, as shown in Fig. 3, and a diagnostic range optimization unit (21b) that performs optimization to enable setting a diagnostic range that reflects individual characteristics using the diagnostic result data learning results.

[0068] And the detailed configuration of the diagnostic signal analysis and judgment unit (200) is as follows.

[0069] Figure 4 is a detailed configuration diagram of the diagnostic signal analysis and judgment unit.

[0070] The diagnostic signal analysis and judgment unit (200) includes, as shown in FIG. 4, a reflection signal data processing unit (41) that converts the ultrasonic reflection signal of the collected red blood cells into data, an IB analysis unit (42) that analyzes the intensity of the ultrasonic reflection signal reflecting the changed characteristics of the red blood cell membrane by using IB analysis (Integrated Backscatter analysis) to classify it according to the blood sugar level by utilizing the change in the characteristics of the red blood cell membrane according to the glycated hemoglobin level, a glycated hemoglobin quantification unit (43) that performs glycated hemoglobin quantification using the analysis results of the IB analysis unit (42), and a diabetes diagnosis result output unit (44) that outputs a diagnosis result based on the quantified glycated hemoglobin data.

[0071] The red blood cell blood sugar diagnosis method using high-frequency ultrasound according to the present invention is described in detail as follows.

[0072] Figure 5 is a flow chart showing a red blood cell blood sugar diagnosis method using high-frequency ultrasound according to the present invention.

[0073] The red blood cell blood sugar diagnosis method using high-frequency ultrasound according to the present invention largely includes a diagnosis range setting step (S501) for setting a range for diagnosing hypoglycemia, normal blood sugar, and hyperglycemia, an ultrasonic signal application step (S502) for applying an ultrasonic signal to blood to be diagnosed, a red blood cell reflection signal reception step (S503) for collecting ultrasonic reflection signals of red blood cells in the blood, a reflection signal data processing step (S504) for converting the collected ultrasonic reflection signals of red blood cells in the blood into data, an IB analysis step (S505) for analyzing the intensity of the ultrasonic reflection signal reflecting the changed characteristics of the red blood cell membrane by using the characteristics of the red blood cell membrane that change according to the glycated hemoglobin level, using IB analysis (Integrated Backscatter analysis), and classifying it according to the blood sugar level, and a diabetes diagnosis result output step (S506) for performing glycated hemoglobin quantification using the IB analysis results and outputting a diagnosis result based on the quantified glycated hemoglobin data.

[0074] Here, the diagnostic range setting step (S501) may include a diagnostic result data learning step for learning diagnostic result data to set a diagnostic range that reflects individual characteristics, and a diagnostic range optimization step for performing optimization to enable setting a diagnostic range that reflects individual characteristics using the diagnostic result data learning result.

[0075] And in the diagnostic range setting step (S501), the following procedure can be performed to extract a reference value for setting the range.

[0076] Blood samples are prepared at various blood glucose concentrations ranging from hypoglycemia to normal and hyperglycemia at regular intervals. Blood glucose concentrations are measured in the commonly used mg / dL unit. Blood samples prepared at different concentrations are diluted before data collection, as they are densely packed with cells, making it difficult to target single red blood cells.

[0077] An electrical signal is input to a high-frequency ultrasound transducer using a pulse source / receiver, and the high-frequency ultrasound transducer converts the input electrical signal into an ultrasound signal and applies the signal to red blood cells in the blood sample.

[0078] The ultrasonic signals reflected from red blood cells are converted back into electrical signals and transmitted to an oscilloscope. These signals are then digitized and collected. Because subtle differences in concentration within the collected signals are difficult to discern with the naked eye, Integrated Backscatter analysis (IB analysis) is used to classify the data based on blood sugar levels.

[0079] Using the IB analysis results, glycated hemoglobin is quantified according to blood sugar levels and a reference value is set for diagnosing diabetes.

[0080] The red blood cell blood sugar diagnosis system and method using high frequency ultrasound according to the present invention described above enables efficient red blood cell blood sugar diagnosis by using IB analysis (Integrated Backscatter analysis) of the cell membrane acoustic reflection signal of red blood cells collected using a high frequency ultrasonic transducer.

[0081] As described above, it will be understood that the present invention can be implemented in modified forms without departing from the essential characteristics of the present invention.

[0082] Therefore, the specified embodiments should be considered in an illustrative rather than a restrictive sense, and the scope of the present invention is indicated by the claims rather than the foregoing description, and all differences within the scope equivalent thereto should be construed as being included in the present invention.

[0083] The present invention relates to blood sugar diagnosis and management, and more particularly, to a red blood cell blood sugar diagnosis system and method using high-frequency ultrasound, which enables efficient red blood cell blood sugar diagnosis by using IB analysis (Integrated Backscatter analysis) of the cell membrane acoustic reflection signal of red blood cells collected using a high-frequency ultrasonic transducer.

Claims

1. An ultrasonic diagnostic signal processing unit that sets a diagnostic range, applies an ultrasonic signal to the blood to be diagnosed, and receives a reflected red blood cell signal; A red blood cell blood sugar diagnosis system using high-frequency ultrasound, characterized by including a diagnostic signal analysis and judgment unit that processes reflected signal data received from an ultrasound diagnostic signal processing unit and outputs a glycated hemoglobin quantification and diabetes diagnosis result through IB analysis (Integrated Backscatter analysis).

2. In paragraph 1, the ultrasonic diagnostic signal processing unit, Consisting of a high frequency ultrasonic transducer and a pulse injector / receiver, A red blood cell blood sugar diagnosis system using high-frequency ultrasound, characterized in that a single-element high-frequency ultrasound transducer having LiNbO3 as a piezoelectric material converts an electrical signal applied through a pulse source / receiver into an acoustic signal, applies the signal to red blood cells in a prepared blood sample, and converts the ultrasonic signal reflected from the red blood cells into an electrical signal and transmits the converted signal to the pulse source / receiver.

3. In paragraph 1, the ultrasonic diagnostic signal processing unit, A red blood cell blood sugar diagnosis system using high-frequency ultrasound characterized in that it sets the diagnostic range by learning diagnostic result data to optimize the diagnostic range reflecting individual characteristics in order to set the diagnostic range.

4. In paragraph 1, IB analysis (Integrated Backscatter analysis) By utilizing the fact that the higher the blood sugar level in red blood cells, the higher the glycated hemoglobin level, and the characteristics of the red blood cell membrane change according to the glycated hemoglobin level, A red blood cell blood sugar diagnosis system using high-frequency ultrasound, characterized in that the signal is classified according to blood sugar level by measuring the intensity of an ultrasonic reflection signal reflecting the characteristics of a changed red blood cell membrane using high-frequency ultrasound.

5. In paragraph 1, the ultrasonic diagnostic signal processing unit, A diagnostic range setting section that sets the range for diagnosing hypoglycemia, normal blood sugar, and hyperglycemia, An ultrasound signal application unit that applies an ultrasound signal to the blood to be diagnosed, A red blood cell blood sugar diagnosis system using high-frequency ultrasound, characterized by including a red blood cell reflection signal receiving unit that collects ultrasonic reflection signals of red blood cells in blood.

6. In paragraph 5, the diagnostic range setting unit, A diagnostic result data learning unit that learns diagnostic result data to set a diagnostic range that reflects individual characteristics, A red blood cell blood sugar diagnosis system using high-frequency ultrasound, characterized by including a diagnostic range optimization unit that performs optimization to enable setting a diagnostic range reflecting individual characteristics by using the results of learning diagnostic result data.

7. In paragraph 1, the diagnostic signal analysis and judgment unit, A reflection signal data processing unit that converts the ultrasonic reflection signals of red blood cells in the collected blood into data, An IB analysis unit that analyzes the intensity of the ultrasound reflection signal reflecting the changed characteristics of the red blood cell membrane by using IB analysis (Integrated Backscatter analysis) to classify the blood sugar level by utilizing the change in the characteristics of the red blood cell membrane according to the glycated hemoglobin level, and A glycated hemoglobin quantification unit that performs glycated hemoglobin quantification using the analysis results of the IB analysis unit, A red blood cell blood sugar diagnosis system using high-frequency ultrasound, characterized by including a diabetes diagnosis result output unit that outputs a diagnosis result based on quantified glycated hemoglobin data.

8. Diagnosis range setting step for setting the range for diagnosing hypoglycemia, normal blood sugar, and hyperglycemia; An ultrasound signal application step of applying an ultrasound signal to the blood to be diagnosed; A red blood cell reflection signal receiving step for collecting ultrasonic reflection signals of red blood cells in blood; A reflection signal data processing step for converting the ultrasonic reflection signal of red blood cells in the collected blood into data; An IB analysis step that classifies blood sugar levels by analyzing the intensity of the ultrasound reflection signal reflecting the changed characteristics of the red blood cell membrane using IB analysis (Integrated Backscatter analysis), which utilizes the fact that the characteristics of the red blood cell membrane change according to the glycated hemoglobin level; A method for diagnosing red blood cell blood sugar using high-frequency ultrasound, characterized by including a diabetes diagnosis result output step of performing glycated hemoglobin quantification using the IB analysis results and outputting a diagnosis result based on the quantified glycated hemoglobin data.

9. In paragraph 8, the diagnostic range setting step is: A diagnostic result data learning step that learns the diagnostic result data to set a diagnostic range that reflects individual characteristics, A red blood cell blood sugar diagnosis method using high-frequency ultrasound, characterized in that it includes a diagnostic range optimization step that performs optimization to enable setting a diagnostic range that reflects individual characteristics by using the diagnostic result data learning results.

Images