Disease diagnostic device and method

Abstract

Disclosed is a methodology for diagnosing a brain-related disease of a user on the basis of brain impedance and brain cell response signals which can be acquired after injecting a current signal corresponding to one or more frequency bands into a pair of electrodes selected from among a plurality of electrodes attached to a subject to be diagnosed.

Description

Disease diagnosis device and method

[0001] The present invention relates to a disease diagnosis device and method for detecting the impedance of an electrode pair among a plurality of electrodes attached to a diagnosis subject based on one or more frequency bands, and determining whether a brain disease has developed in a diagnosis subject based on the reactive brain electrical signal and impedance of the electrode pair detected based on one or more frequency bands.

[0002] The proportion of the elderly population is increasing worldwide, and the incidence of dementia among the elderly is also rapidly increasing.

[0003] Given the current state of medical care, dementia is an incurable disease. Early diagnosis and early treatment are the only solutions to slow its progression. Therefore, a technology capable of accurately diagnosing dementia early and from an electrophysiological perspective is essential.

[0004] Meanwhile, existing X-ray-based CT scan technology is mostly used to determine whether there are structural abnormalities in the user's body, and when used on the user's brain, it is used to determine whether there are brain tumors or structural changes in the cerebral blood vessels.

[0005] Additionally, MRI technology measures the resonance of hydrogen nuclei in response to an external magnetic field, thereby determining blood oxygen content and blood flow. Functional magnetic resonance imaging (fMRI) is also known for analyzing brain function. While fMRI is excellent for analyzing brain function when the user's brain cells consume oxygen, it has limitations in that it is not suitable for measuring brain function when the user's brain cells do not consume oxygen and only experience ionic changes.

[0006] An embodiment of the present invention provides a disease diagnosis device and method capable of early and accurately diagnosing a brain disease from an electrophysiological perspective by detecting brain cell response signals of electrode pairs corresponding to one or more frequency bands among a plurality of electrodes attached to a subject of diagnosis, and determining whether a subject of diagnosis has a brain disease (e.g., Alzheimer's) based on an analysis result of a brain cell response signal corresponding to a single frequency band or a comparative analysis result between brain cell response signals corresponding to a plurality of frequency bands.

[0007] In addition, an embodiment of the present invention detects the impedance of the electrode pair corresponding to a plurality of frequency bands as a brain cell response signal of the electrode pair corresponding to a plurality of frequency bands among a plurality of electrode pairs attached to a diagnosis subject, and determines whether a brain disease has developed in the diagnosis subject based on a comparative analysis result between the impedances of the electrode pairs, thereby providing a disease diagnosis device and method capable of accurately diagnosing a specific brain disease that cannot be detected by existing diagnosis methods (for example, diagnosis based on the possibility of developing a brain disease as the impedance is higher) due to the detection of a relatively lower impedance than other brain diseases or the occurrence of a correlation between the measured electrode pairs.

[0008] The problems addressed by the present invention are not limited to those mentioned above. Other problems and advantages of the present invention not mentioned above can be understood through the following description and will be more clearly understood through embodiments of the present invention. Furthermore, it will be appreciated that the problems and advantages addressed by the present invention can be realized by the means and combinations thereof set forth in the claims.

[0009] A disease diagnosis device according to an embodiment of the present invention may include a signal generation unit that injects a current signal corresponding to one or more frequency bands into a selected electrode pair among a plurality of electrodes attached to a subject of diagnosis, a signal processing unit that detects a brain cell response signal of an electrode pair corresponding to one or more frequency bands based on a voltage signal measured at the electrode pair as the current signal is injected, and a processor that groups brain cell response signals corresponding to a first frequency band and a second frequency band among the one or more frequency bands into a first frequency group and a second frequency group, and determines whether a brain disease has developed in the subject of diagnosis based on an analysis result of a brain cell response signal in either the first frequency group or the second frequency group, or a comparative analysis result between a brain cell response signal in the first frequency group and a brain cell response signal in the second frequency group.

[0010] A disease diagnosis method according to an embodiment of the present invention is a disease diagnosis method performed by a disease diagnosis device, and may include a step of injecting a current signal corresponding to one or more frequency bands into a selected electrode pair among a plurality of electrodes attached to a subject of diagnosis, a step of detecting a brain cell response signal of an electrode pair corresponding to one or more frequency bands based on a voltage signal measured at the electrode pair as the current signal is injected, a step of grouping brain cell response signals corresponding to a first frequency band and a second frequency band among the one or more frequency bands into a first frequency group and a second frequency group, and a step of determining whether a brain disease has developed in the subject of diagnosis based on an analysis result of the brain cell response signal in the first frequency group or a comparative analysis result between the brain cell response signal in the first frequency group and the brain cell response signal in the second frequency group.

[0011] In addition, other methods for implementing the present invention, other systems, and computer-readable recording media storing a computer program for executing the method may be further provided.

[0012] According to the present invention, by injecting one or more currents into electrode pairs among a plurality of electrodes attached to a subject of diagnosis, detecting brain cell response signals of electrode pairs corresponding to one or more frequency bands, and determining whether a subject of diagnosis has a brain disease (e.g., Alzheimer's) based on the analysis result of the brain cell response signal corresponding to a single frequency band or the comparative analysis result between brain cell response signals corresponding to a plurality of frequency bands, it is possible to provide a disease diagnosis device and method capable of early and accurately diagnosing a brain disease from an electrophysiological perspective.

[0013] In addition, according to the present invention, among a plurality of electrodes attached to a subject for diagnosis, the impedance of the electrode pair corresponding to a plurality of frequency bands is detected as a brain cell response signal of the electrode pair corresponding to the applied current of a plurality of frequency bands for the electrode pairs, and based on the result of the comparative analysis between the impedances of the electrode pairs, whether or not the subject for diagnosis has developed a brain disease is determined, so that even in the case where a specific brain disease that cannot be detected by an existing diagnostic method (for example, a diagnosis based on the assumption that the higher the impedance, the more likely the subject for diagnosis has developed a brain disease) due to the detection of a relatively lower impedance than other brain diseases or the occurrence of a correlation between the measured electrode pairs, a disease diagnostic device and method can be provided that can accurately diagnose the same.

[0014] The effects of the present invention are not limited to those mentioned above, and other effects not mentioned will be clearly understood by those skilled in the art from the description below.

[0015] FIG. 1 is a drawing illustrating an example of a disease diagnosis system including a disease diagnosis device according to an embodiment of the present invention.

[0016] Figure 2 is a drawing illustrating an example of multiple electrodes of a disease diagnosis device.

[0017] FIG. 3 is a drawing illustrating an example of a configuration of a disease diagnosis device according to an embodiment of the present invention.

[0018] FIG. 4 is a drawing for explaining an example of selecting an electrode pair in a disease diagnosis device according to an embodiment of the present invention.

[0019] FIG. 5 is a diagram illustrating an example of grouping impedances of electrode pairs in a disease diagnosis device according to an embodiment of the present invention.

[0020] FIG. 6 is a diagram illustrating an example of determining whether a subject has a brain disease by using relatively low impedance in a disease diagnosis device according to an embodiment of the present invention.

[0021] FIG. 7 is a drawing for explaining that the method according to the present invention is applicable to a CT scanner.

[0022] Figure 8 is a flowchart for explaining a disease diagnosis method according to the present embodiment.

[0023] According to one embodiment of the present invention for solving the above technical problem, a device includes a signal generating unit that injects a current signal corresponding to one or more frequency bands into a selected electrode pair among a plurality of electrodes attached to a subject of diagnosis; a signal processing unit that detects a brain cell response signal of the electrode pair corresponding to the one or more frequency bands based on a voltage signal measured at the electrode pair as the current signal is injected; and a processor that groups the brain cell response signals corresponding to a first frequency band and a second frequency band among the one or more frequency bands into a first frequency group and a second frequency group, and determines whether the subject of diagnosis has developed a brain disease based on an analysis result of the brain cell response signal within either the first frequency group or the second frequency group, or a comparative analysis result between the brain cell response signal within the first frequency group and the brain cell response signal within the second frequency group.

[0024] In the above device, the brain cell response signal of the electrode pair corresponding to the first frequency band includes the impedance of the electrode pair corresponding to the first frequency band, and the processor can determine that the subject of the diagnosis has developed a brain disease when, as a result of analyzing the brain cell response signal within the first frequency group, the impedance of the electrode pair within the first frequency group is equal to or greater than a set ratio with respect to a preset maximum brain impedance.

[0025] In the above device, the brain cell response signals of the electrode pairs corresponding to the first frequency band and the second frequency band, respectively, include impedances of the electrode pairs corresponding to the first frequency band and the second frequency band, respectively, and the processor determines that the subject of the diagnosis has developed a brain disease when, as a result of comparative analysis between the brain cell response signals of each of the first frequency group and the second frequency group, a difference between the impedance of the electrode pair in the first frequency group and the impedance of the electrode pair in the second frequency group is equal to or greater than a preset brain impedance, or when the impedance of the electrode pair in the first frequency group and the impedance of the electrode pair in the second frequency group do not satisfy a preset relationship.

[0026] In the above device, the brain cell response signals of the electrode pairs corresponding to the first frequency band and the second frequency band, respectively, include the impedance of the electrode pairs corresponding to the first frequency band and the second frequency band, respectively, and the processor calculates statistical values ​​for the impedance of the electrode pairs in the first frequency group and the impedance of the electrode pairs in the second frequency group, and when the statistical values ​​are equal to or greater than a set value, it can be determined that the subject of the diagnosis has developed a brain disease.

[0027] In the above device, the processor can detect a frequency shift value for a current signal corresponding to the first frequency band and a voltage signal corresponding to the first frequency band, and determine whether a brain disease has developed in the subject of diagnosis based on the frequency shift value.

[0028] In the above device, the processor detects a first frequency shift value for a current signal corresponding to the first frequency band and a voltage signal corresponding to the first frequency band, and a second frequency shift value for a current signal corresponding to the second frequency band and a voltage signal corresponding to the second frequency band, and can determine whether a brain disease has developed in the subject of diagnosis based on a comparison result of the first frequency shift value and the second frequency shift value.

[0029] In the above device, the brain cell response signal corresponding to the first frequency band includes a plurality of brain cell response signals corresponding to each of a plurality of frequencies within the first frequency band, and the processor groups the plurality of brain cell response signals into the first frequency group, calculates statistical values ​​for the plurality of brain cell response signals within the first frequency group, and determines whether the subject of the diagnosis has developed a brain disease based on an analysis result of the statistical values.

[0030] In the above device, the signal generation unit can sequentially select an electrode pair among the plurality of electrodes and inject a current signal corresponding to one or more frequency bands.

[0031] The above device may be either a brain electrical signal CT scanner or a brain impedance CT scanner.

[0032] According to another embodiment of the present invention for solving the above technical problem, a method for diagnosing a disease is provided, which is performed by a disease diagnosis device, comprising: a step of injecting a current signal corresponding to one or more frequency bands into a selected electrode pair among a plurality of electrodes attached to a subject of diagnosis; a step of detecting a brain cell response signal of the electrode pair corresponding to the one or more frequency bands based on a voltage signal measured at the electrode pair as the current signal is injected; a step of grouping the brain cell response signals corresponding to a first frequency band and a second frequency band among the one or more frequency bands into a first frequency group and a second frequency group; and a step of determining whether the subject of diagnosis has developed a brain disease based on an analysis result of the brain cell response signal within the first frequency group or a comparative analysis result between the brain cell response signal within the first frequency group and the brain cell response signal within the second frequency group.

[0033] The present invention is capable of various modifications and embodiments. Specific embodiments are illustrated in the drawings and described in detail in the detailed description. The effects and features of the present invention, as well as the methods for achieving them, will become clearer with reference to the embodiments described in detail below, along with the drawings. However, the present invention is not limited to the embodiments disclosed below and can be implemented in various forms.

[0034] Hereinafter, embodiments of the present invention will be described in detail with reference to the attached drawings. When describing with reference to the drawings, identical or corresponding components are given the same drawing reference numerals, and redundant descriptions thereof will be omitted.

[0035] In the following examples, the terms first, second, etc. are not used in a limiting sense, but are used for the purpose of distinguishing one component from another.

[0036] In the examples below, singular expressions include plural expressions unless the context clearly indicates otherwise.

[0037] In the following examples, terms such as “include” or “have” mean that a feature or component described in the specification is present, and do not preclude the possibility that one or more other features or components may be added.

[0038] In some embodiments, where the implementation is otherwise feasible, a particular process sequence may be performed in a different order than described. For example, two processes described in succession may be performed substantially simultaneously, or in a reverse order from the described order.

[0039] FIG. 1 is a drawing illustrating an example of a disease diagnosis system including a disease diagnosis device according to an embodiment of the present invention, and FIG. 2 is a drawing illustrating an example of a plurality of electrodes of the disease diagnosis device.

[0040] Referring to FIG. 1, a disease diagnosis system (100) may include a disease diagnosis device (110) and a terminal (120).

[0041] The disease diagnosis device (110) may include a plurality of electrodes (111) and a disease diagnosis module (112).

[0042] The plurality of electrodes (111) may be composed of, for example, only ear electrodes (A1, A2) and prefrontal electrodes (FP1, FP2) according to the 10 / 20 electrode arrangement method as illustrated in FIG. 2, or may be 20 electrodes including the frontal lobe and the back, and in some cases, may be composed of only the frontal lobe or may be composed of more than 20 electrodes. The plurality of electrodes (111) may be attached to a subject of diagnosis (e.g., a person), and may be attached, for example, to points at 10% and 20% of a line connecting the nasion, which is a reference point in the front of the head, to the inion, which is a reference point in the back, and to points at 10% and 20% of a line connecting the left preauricular point, which is a reference point on the left, to the right preauricular point, which is a reference point on the right.

[0043] A plurality of electrodes (111) may be connected to the disease diagnosis module (112) via a connector, but are not limited thereto and may be connected wirelessly.

[0044] In an embodiment, a plurality of electrodes may be secured to a subject by, for example, passing through a plurality of holes included in a cover (113) made of a spandex material (e.g., an EEG cap) and attaching the covered subject to the diagnosis. In addition, a plurality of electrodes (111) may be attached to a structure in the form of a headband, headset, or helmet, for example.

[0045] The disease diagnosis module (112) can determine whether a brain disease has developed in a subject of diagnosis based on brain cell response signals from a plurality of electrodes (111) attached to the subject of diagnosis.

[0046] Specifically, the disease diagnosis module (112) can select an electrode pair (two electrodes) from among the plurality of electrodes (111) and inject a current signal corresponding to one or more frequency bands into the selected electrode pair. At this time, the disease diagnosis module (112) can sequentially select an electrode pair from among the plurality of electrodes (111) and inject a current signal corresponding to one or more frequency bands into the electrode pair of A1-FP1. For example, the disease diagnosis module (112) can select an electrode pair of A1-FP1 from among the plurality of electrodes (111) and inject a current signal corresponding to one or more frequency bands into the electrode pair of A1-FP1. In addition, the disease diagnosis module (112) can select an electrode pair of A1-FP2 from among the plurality of electrodes (111) and inject a current signal corresponding to one or more frequency bands into the electrode pair of A1-FP2.

[0047] The disease diagnosis module (112) can measure a voltage signal of an electrode pair into which a current signal corresponding to one or more frequency bands is injected, and detect a brain cell response signal of the electrode pair corresponding to one or more frequency bands based on the voltage signal of the electrode pair. At this time, the disease diagnosis module (112) can detect the brain cell response signal of the electrode pair by measuring the impedance of the electrode pair based on the current signal corresponding to one or more frequency bands injected into the electrode pair and the voltage signal measured at the electrode pair. The disease diagnosis module (112) can determine whether a brain disease has developed in a subject of diagnosis based on the analysis result of the brain cell response signal corresponding to a first frequency band among one or more frequency bands, or the comparative analysis result between the brain cell response signals corresponding to the first frequency band and the second frequency band among one or more frequency bands.

[0048] The disease diagnosis module (112) can transmit whether or not a brain disease has developed in a subject of diagnosis to a terminal (e.g., a doctor terminal) (120). At this time, the disease diagnosis module (112) transmits at least one signal among the current signal, the voltage signal, and the brain cell response signal of the electrode pair, together with the onset of the brain disease, to the terminal (120) through a network (or outputs the signal to the output unit of the disease diagnosis module (112), thereby providing a brain disease-related signal and a diagnosis result for the brain disease to a user of the terminal (120) (or a user of the disease diagnosis device (110)).

[0049] The terminal (120) can output at least one signal among the current signal, voltage signal, and brain cell response signal of the electrode pair, along with whether a brain disease has occurred.

[0050] The terminal (120) may include a communication terminal capable of performing the functions of a computing device, and may be, but is not limited to, a desktop computer, a smartphone, a laptop, a tablet PC, a smart TV, a mobile phone, a PDA (personal digital assistant), a media player, a micro server, a GPS (global positioning system) device, an e-book terminal, a digital broadcasting terminal, a navigation device, a kiosk, an MP3 player, a digital camera, home appliances, and other mobile or non-mobile computing devices operated by a user. Such user terminals are not limited to the above-described contents, and terminals capable of web browsing may be borrowed without limitation.

[0051] The network that plays a role of connecting the disease diagnosis device (110) and the terminal (120) may include wired networks such as a local area network (LAN), a wide area network (WAN), a metropolitan area network (MAN), and an integrated service digital network (ISDN), or wireless networks such as a wireless LAN (WLAN), code-division multiple access (CDMA), and satellite communication, but the scope of the present invention is not limited thereto. In addition, the network may transmit and receive information using short-range communication and / or long-range communication. Here, short-range communication may include Bluetooth, radio frequency identification (RFID), infrared data association (IrDA), ultra-wideband (UWB), ZigBee, and Wi-Fi technology, and long-range communication may include code-division multiple access (CDMA), frequency-division multiple access (FDMA), time-division multiple access (TDMA), orthogonal frequency-division multiple access (OFDMA), and single carrier frequency-division multiple access (SC-FDMA) technology.

[0052] A network may include interconnected network elements such as hubs, bridges, routers, and switches. The network may include one or more connected networks, such as a multi-network environment, including public networks such as the Internet and private networks such as secure corporate private networks. Access to the network may be provided via one or more wired or wireless access networks.

[0053] Furthermore, the network can support CAN (controller area network) communication, V2I (vehicle to infrastructure) communication, V2X (vehicle to everything) communication, WAVE (wireless access in vehicular environment) communication technology, and IoT (Internet of Things) network and / or 5G communication that exchange and process information between distributed components such as objects.

[0054] FIG. 3 is a drawing illustrating an example of a configuration of a disease diagnosis device according to an embodiment of the present invention.

[0055] Referring to FIG. 3, a disease diagnosis device (110) according to an embodiment of the present invention may include a plurality of electrodes (111) and a disease diagnosis module (112).

[0056] The plurality of electrodes (111) may include, for example, electrodes such as A1, A2, FP1, FP2, etc. In addition, the plurality of electrodes (111) may further include, for example, electrodes such as FPZ, F7, F3, FZ, F4, F8, T3, C3, CZ, C4, T4, T5, P3, PZ, P4, T6, O1, OZ, O2, etc.

[0057] The disease diagnosis module (112) may include a signal generation unit (310), a signal processing unit (320), a processor (330), and a memory (340).

[0058] The signal generation unit (310) can inject a current signal corresponding to one or more frequency bands into a pair of electrodes selected from among a plurality of electrodes attached to the subject of diagnosis. At this time, the signal generation unit (310) can sequentially select an electrode pair from among the plurality of electrodes and inject a current signal corresponding to one or more frequency bands.

[0059] Here, the one or more frequency bands may include, but are not limited to, a first frequency band, a second frequency band, and a third frequency band, for example. The first frequency band may be, for example, a low-frequency band in the range of 0 Hz to 100 Hz, which is a frequency band capable of interacting with the brain biosignal of the diagnosis subject. The second frequency band may be, for example, a high-frequency band in the range of 1 kHz to 20 kHz. In addition, the third frequency band may be a frequency band other than the first and second frequency bands, and may be, for example, a mid-frequency band in the range of 100 Hz to 1 kHz.

[0060] In addition, the current signal corresponding to the first frequency band may include a current signal corresponding to each of a plurality of first frequencies included in the first frequency band, and the current signal corresponding to the second frequency band may include a current signal corresponding to each of a plurality of second frequencies included in the second frequency band. When the first frequency band is a low-frequency band in the range of 0 Hz to 100 Hz, the current signal corresponding to the first frequency band may include, for example, a current signal corresponding to 10 Hz, a current signal corresponding to 20 Hz, a current signal corresponding to 100 Hz (e.g., a current signal at 10 Hz intervals, or a current signal at 1 Hz intervals), etc. In addition, when the second frequency band is a high-frequency band in the range of 1 kHz to 20 kHz, the current signal corresponding to the second frequency band may include, for example, a current signal corresponding to 1 kHz, a current signal corresponding to 2 kHz, a current signal corresponding to 20 kHz, etc.

[0061] The signal processing unit (320) can detect a brain cell response signal of an electrode pair corresponding to one or more frequency bands based on a voltage signal measured at the electrode pair as a current signal is injected into the electrode pair. At this time, the signal processing unit (320) measures a voltage signal corresponding to one or more frequency bands measured at the electrode pair, and measures an impedance of the electrode pair corresponding to one or more frequency bands based on the current signal corresponding to one or more frequency bands injected into the electrode pair and the voltage signal measured at the electrode pair, thereby detecting a brain cell response signal of the electrode pair corresponding to one or more frequency bands. At this time, the signal processing unit (320) can detect the impedance of the electrode pair based on the current signal and the voltage signal corresponding to the frequency band by [Mathematical Formula 1].

[0062]

[0063] Here, I is the current signal injected into the electrode pair, V is the voltage signal measured at the electrode pair, and Z is the impedance of the electrode pair. Impedance is an AC resistance and can vary with frequency. R is the resistance, L is the inductor, and C is the capacitor. f is the frequency.

[0064] Also, I0 represents the maximum current value, t represents time, and θ represents the phase.

[0065] That is, since the current signal (I) contains a frequency component, when the current signal (I) containing a frequency component is injected into the electrode pair, the measured voltage signal (V) also has a frequency component, just like the current signal. In other words, the impedance (Z) measured from the electrode pair also has a frequency component.

[0066] Unlike electroencephalography (EEG), which passively measures electrical signals generated from brain cells, the signal processing unit (320) can apply an electric field to the scalp of a subject of diagnosis and actively measure the response signals of brain cells accordingly. Since EEG measures signals from various brain cell regions mixed together on the scalp, the location (localization) of the source cannot be identified. However, the signal processing unit (320) measures the impedance of a specific electrode pair using the voltage signal measured at a specific electrode pair as a current signal is applied to a specific electrode pair, thereby detecting a response signal from a brain cell located between a specific electrode pair. In other words, the signal processing unit (320) can recognize the location of a brain cell generating a response signal more accurately than an EEG.

[0067] This signal processing unit (320) can measure the ion state of brain cells used for analysis of brain function through impedance measurement of electrode pairs using current signals and voltage signals of a set frequency band (e.g., frequency of 20 kHz or less), unlike conventional brain impedance measurement that measures brain moisture based on a frequency of 50 kHz or higher and uses this for body composition analysis, for example.

[0068] The processor (330) can control the signal generation unit (310) and the signal processing unit (320), and can control the entire process for determining whether a subject to be diagnosed has developed a brain disease.

[0069] The processor (330) may group brain cell response signals of electrode pairs corresponding to a first frequency band and a second frequency band among one or more frequency bands into a first frequency group and a second frequency group, respectively, but is not limited thereto and the grouping process may be omitted. Here, the brain cell response signal of the electrode pair may be the impedance of the electrode pair. In addition, the brain cell response signal corresponding to the first frequency band (or the second frequency band) may include one brain cell response signal corresponding to one frequency within the first frequency band (or the second frequency band) or a plurality of brain cell response signals respectively corresponding to a plurality of frequencies. Accordingly, the processor (330) may group the impedance of the electrode pair corresponding to one or more frequencies within the first frequency band or the second frequency band into the first frequency group or the second frequency group as the plurality of brain cell response signals corresponding to each of the plurality of frequencies within the first frequency band or the second frequency band. That is, the first frequency group may include a single impedance corresponding to a single frequency within the first frequency band, or may include a plurality of impedances each corresponding to a plurality of frequencies within the first frequency band. Furthermore, the second frequency group may include a single impedance corresponding to a single frequency within the second frequency band, or may include a plurality of impedances each corresponding to a plurality of frequencies within the second frequency band.

[0070] The processor (330) can determine whether a brain disease has developed in a subject based on the analysis result of a brain cell response signal within a first frequency group (i.e., impedance of an electrode pair corresponding to a first frequency band, i.e., impedance of one or more electrode pairs), or the comparative analysis result between a brain cell response signal within a first frequency group and a brain cell response signal within a second frequency group (i.e., impedance of an electrode pair corresponding to a second frequency band, i.e., impedance of one or more electrode pairs). Here, when a plurality of impedances are grouped into a first frequency group (or a second frequency group) as a plurality of brain cell response signals, the processor (330) can calculate statistical values ​​(e.g., mean, standard deviation, variance) for a plurality of impedances within the first frequency group (or the second frequency group), and determine whether a brain disease has developed in a subject based on the analysis result of the statistical values. At this time, the processor (330) can determine whether a brain disease has developed in a subject of diagnosis based on the analysis results of statistical values ​​for a plurality of impedances, but is not limited thereto, and can determine whether a brain disease has developed in a subject of diagnosis based on any one impedance selected according to a set standard (e.g., maximum, minimum, random) among a plurality of impedances.

[0071] At this time, the processor (330) can determine that the subject of diagnosis has developed a brain disease if, as a result of analyzing the brain cell response signal within the first frequency group (or the second frequency group), the impedance (a statistical value for one impedance or a plurality of impedances) of the electrode pair within the first frequency group (or the second frequency group) is greater than or equal to a set ratio for a preset maximum brain impedance (or the largest impedance among the impedances included in the first frequency group). Here, the maximum brain impedance may be, for example, an impedance measurable by a disease diagnosis device (specifically, an analog-to-digital converter), a maximum value that the brain impedance can have, or an arbitrarily set value. For example, if the average of the impedances included in the first frequency group is 150 kΩ, the set maximum impedance is 200 kΩ, and the set ratio is 60%, the processor (330) can determine that the subject of diagnosis has developed a brain disease because the average of the impedances, 150 kΩ, is greater than or equal to 120 kΩ, which is the set ratio of the maximum impedance.

[0072] In an embodiment, the signal processing unit (320) may include an analog-to-digital converter that converts a voltage signal measured at an electrode pair from an analog signal to a digital signal. The processor (330) may determine whether a brain disease has developed in a subject based on a preset maximum brain impedance (or the maximum impedance among the impedances included in the first frequency group), but is not limited thereto. The processor (330) may determine whether a brain disease has developed in a subject based on the maximum impedance that can be represented by the analog-to-digital converter included in the signal processing unit (320). For example, when the analog-to-digital converter is 12 bits, the range of values ​​that can be represented by the analog-to-digital converter is 0 to 4095, and therefore, the processor (330) may determine whether a brain disease has developed in a subject based on 4095, which is the maximum impedance that can be represented by the analog-to-digital converter. The processor (330) can determine that the subject of diagnosis has developed a brain disease if the impedance of the electrode pair within the first frequency group (or the second frequency group) is greater than or equal to 2457, which is a set ratio, for example, 60%, of the maximum brain impedance of 4095 that can be represented by the analog-to-digital converter.

[0073] The processor (330) determines whether a brain disease has developed in a subject of diagnosis based on the maximum impedance that can be represented by an analog-to-digital converter, thereby accurately determining whether a brain disease has developed in a subject of diagnosis regardless of the performance of the analog-to-digital converter in the disease diagnosis device, which may vary depending on the disease diagnosis device.

[0074] In addition, the processor (330) may determine that the subject of diagnosis has developed a brain disease when, as a result of comparative analysis between brain cell response signals of each of the first frequency group and the second frequency group, the difference (or ratio between the impedances) between the impedances (one or more impedances) of the electrode pairs in the first frequency group and the impedances (one or more impedances) of the electrode pairs in the second frequency group is greater than or equal to a preset brain impedance (or a preset ratio), or the impedances of the electrode pairs in the first frequency group and the impedances of the electrode pairs in the second frequency group do not satisfy a preset relationship (e.g., a linear or nonlinear relationship).

[0075] In an embodiment, the processor (330) may determine whether a subject has developed a brain disease based on statistics on the impedance of electrode pairs across multiple frequency groups. That is, the processor (330) may calculate statistical values ​​(e.g., mean, standard deviation, variance) for the impedance (one or more impedances) of electrode pairs within a first frequency group and the impedance (one or more impedances) of electrode pairs within a second frequency group, and if the statistical values ​​are greater than a set value, it may be determined that the subject has developed a brain disease.

[0076] In addition, the processor (330) can determine whether a brain disease has developed in a subject based on frequency shift values ​​for a current signal and a voltage signal in a single frequency band. That is, the processor (330) can detect frequency shift values ​​for a current signal corresponding to a first frequency band (or a second frequency band) and a voltage signal corresponding to the first frequency band (or a second frequency band), and determine whether a brain disease has developed in a subject based on the frequency shift values. Here, the frequency shift values ​​can include at least one of a change degree of a frequency shift, a change degree of a frequency phase, and a change degree of a frequency duty cycle.

[0077] In addition, the processor (330) can determine whether a brain disease has developed in a subject based on the comparison results of frequency shift values ​​for current signals and voltage signals in multiple frequency bands. That is, the processor (330) can detect a first frequency shift value for a current signal corresponding to a first frequency band and a voltage signal corresponding to the first frequency band, and a second frequency shift value for a current signal corresponding to a second frequency band and a voltage signal corresponding to the second frequency band, and can determine whether a brain disease has developed in a subject based on the comparison results of the first frequency shift value and the second frequency shift value.

[0078] The processor (330) may determine whether a brain disease has occurred by any one of various methods for determining whether a brain disease has occurred (for example, a method for determining whether a brain disease has occurred based on the analysis results of brain cell response signals within a frequency group, the comparative analysis results between brain cell response signals of each of a plurality of frequency groups, the statistical analysis results for brain cell response signals of each of a plurality of frequency groups, the frequency shift value analysis results for current signals and voltage signals corresponding to a single frequency band, and the comparative analysis results between frequency shift values ​​of each of a plurality of frequency bands), but is not limited thereto. For example, the processor (330) may finally determine whether a brain disease has occurred in a subject of diagnosis through a set number (for example, two) or more of various methods for determining whether a brain disease has occurred. At this time, the processor (330) may perform various methods for determining whether a brain disease has occurred in a preset order, but is not limited thereto, and may perform various methods for determining whether a brain disease has occurred in a preset order set (or changed) by a user. Here, the order or number of various methods for determining whether a brain disease has developed may be changed based on the personal information of the person being diagnosed (e.g., gender, age, diagnosis history, presence of other diseases, etc.).

[0079] In an embodiment, the processor (330) may refer to a data processing device built into hardware, for example, having a physically structured circuit to perform a function expressed by a code or instruction included in a program. Examples of such data processing devices built into hardware may include processing devices such as a microprocessor, a central processing unit (CPU), a processor core, a multiprocessor, an application-specific integrated circuit (ASIC), and a field programmable gate array (FPGA), but the scope of the present invention is not limited thereto.

[0080] The memory (340) can perform a function of temporarily or permanently storing information processed by the signal generator (310), the signal processor (320), and the processor (330). The memory (340) can store, for example, a preset maximum brain impedance, a reference for one or more frequency bands, a relationship set between frequency groups, etc.

[0081] The memory (340) may include a magnetic storage media or a flash storage media, but the scope of the present invention is not limited thereto. The memory (340) may include built-in memory and / or external memory, and may include a volatile memory such as DRAM, SRAM, or SDRAM, a non-volatile memory such as OTPROM (one time programmable ROM), PROM, EPROM, EEPROM, mask ROM, flash ROM, NAND flash memory, or NOR flash memory, a flash drive such as an SSD, a CF (compact flash) card, an SD card, a Micro-SD card, a Mini-SD card, an Xd card, or a memory stick, or a storage device such as an HDD.

[0082] FIG. 4 is a drawing for explaining an example of selecting an electrode pair in a disease diagnosis device according to an embodiment of the present invention.

[0083] Referring to FIG. 4, the disease diagnosis device (110) can select an electrode pair among a plurality of electrodes (111). At this time, the disease diagnosis device (110) can select a first electrode forming an electrode pair using a first switch (410), and can select a second electrode forming an electrode pair using a second switch (420). For example, the disease diagnosis device (110) can select an electrode pair of FP1-A1 among a plurality of electrodes (111) by switching the first switch (410) to be connected to FP1, and switching the second switch (420) to be connected to A1.

[0084] The disease diagnosis device (110) can sequentially select another electrode pair among the plurality of electrodes (111) by switching at least one of the first switch (410) and the second switch (420) to be connected to another electrode. For example, the disease diagnosis device (110) can select the electrode pair of F3-A1 among the plurality of electrodes (111) by switching the first switch (410) to be connected to F3 while the first switch (410) and the second switch (420) are connected to FP1 and A1, respectively, or can select the electrode pair of FP1-F7 among the plurality of electrodes (111) by switching the second switch (420) to be connected to F7. In addition, the disease diagnosis device (110) can select the electrode pair of F3-F7 among the plurality of electrodes (111) by switching the first switch (410) and the second switch (420) to be connected to F3 and F7, respectively.

[0085] The disease diagnosis device (110) can inject a current signal corresponding to one or more frequency bands into the selected electrode pair through the signal generation unit (310) using the first switch (410) and the second switch (420). The disease diagnosis device (110) can detect the impedance of the electrode pair as a brain cell response signal of the electrode pair corresponding to one or more frequency bands based on the voltage signal measured at the electrode pair as the current signal is injected through the signal processing unit (320). At this time, the disease diagnosis device (110) can detect the impedance of the electrode pair based on, for example, the four-terminal method or the two-terminal method. Here, the four-terminal method is a method of injecting a current signal into one electrode pair (two electrodes) while measuring a voltage signal at another electrode pair (two electrodes), and the two-terminal method is a method of providing a current signal to one electrode pair while simultaneously measuring a voltage signal at the electrode pair.

[0086] Here, the signal generation unit (310) may include a waveform generator (311) and a current generator (312).

[0087] The waveform generator (311) can generate a signal having at least one waveform. The waveform generator (311) can generate a signal having one waveform among, for example, a trigonometric function (sine, cosine), a biphasic wave, a square wave, a wave mixed with direct current and alternating current, a wave having pink noise, and a random wave.

[0088] The current generator (312) can generate a current signal corresponding to one or more frequency bands based on a signal output from the waveform generator (311). For example, the current generator (312) can generate a current signal corresponding to a low frequency band in the range of 0 Hz to 100 Hz and a current signal corresponding to a high frequency band in the range of 1 kHz to 20 kHz. At this time, the current generator (312) can generate the current signal corresponding to the low frequency band and the current signal corresponding to the high frequency band based on a set order, but is not limited thereto and can be generated in any order.

[0089] Additionally, the signal processing unit (320) may include a voltage meter (321) and a signal detection unit (322).

[0090] The voltage meter (321) can measure a voltage signal when a current signal corresponding to one or more frequency bands is injected into each electrode pair sequentially selected from among a plurality of electrodes, and transmit the voltage signal to the signal detection unit (322).

[0091] The voltage meter (321) can measure a voltage signal corresponding to one or more frequency bands by generating a current signal corresponding to one or more frequency bands from the current generator (312).

[0092] The signal detection unit (322) can detect the brain cell response signal of the electrode pair by measuring the impedance of the electrode pair based on the voltage signal measured by the voltage meter (321). At this time, the signal detection unit (322) can detect the brain cell response signal of the electrode pair corresponding to one or more frequency bands. For example, the signal detection unit (322) can detect the impedance of the electrode pair corresponding to a first frequency band (e.g., a low frequency band) and a second frequency band (e.g., a high frequency band) among one or more frequency bands, respectively.

[0093] FIG. 5 is a diagram illustrating an example of grouping impedances of electrode pairs in a disease diagnosis device according to an embodiment of the present invention.

[0094] Referring to FIG. 5, the disease diagnosis device can sequentially select, for example, electrode pairs of A1-FP1, A1-FP2, A2-FP1, and A2-FP2 among a plurality of electrodes attached to a diagnosis subject, and inject a current signal corresponding to a first frequency band (e.g., a low frequency band in the range of 0 Hz to 100 Hz) and a second frequency band (e.g., a high frequency band in the range of 1 kHz to 20 kHz) into the selected electrode pair. For example, the disease diagnosis device may inject, as current signals corresponding to the first frequency band to the electrode pair of A1-FP1, a current signal corresponding to a first frequency within the first frequency band (i.e., a current signal having a first frequency included in the first frequency band) and a current signal corresponding to a second frequency within the first frequency band (i.e., a current signal having a second frequency included in the first frequency band), and may inject, as current signals corresponding to the second frequency band to the electrode pair of A1-FP1, a current signal corresponding to a third frequency within the second frequency band and a current signal corresponding to a fourth frequency within the second frequency band.

[0095] The disease diagnosis device can detect a brain cell response signal of an electrode pair corresponding to a first frequency band and a brain cell response signal of an electrode pair corresponding to a second frequency band by measuring the impedance of each electrode pair based on a voltage signal measured at each electrode pair as a current signal is injected, based on the first and second frequency bands.

[0096] The disease diagnosis device can measure a first impedance of the electrode pair of A1-FP1 corresponding to the first frequency, for example, based on a voltage signal at a first frequency within a first frequency band measured at the electrode pair of A1-FP1 and a current signal corresponding to the first frequency within the first frequency band injected into the electrode pair of A1-FP1. The disease diagnosis device can measure a second impedance of the electrode pair of A1-FP1 corresponding to the second frequency, based on a voltage signal at a second frequency within the first frequency band measured at the electrode pair of A1-FP1 and a current signal corresponding to the second frequency within the first frequency band injected into the electrode pair of A1-FP1. The disease diagnosis device can measure a third impedance of the electrode pair of A1-FP1 corresponding to the third frequency, based on a voltage signal at a third frequency within the second frequency band measured at the electrode pair of A1-FP1 and a current signal corresponding to the third frequency within the second frequency band injected into the electrode pair of A1-FP1. Additionally, the disease diagnosis device can measure a fourth impedance of the electrode pair of A1-FP1 corresponding to the fourth frequency based on a voltage signal at a fourth frequency within the second frequency band measured from the electrode pair of A1-FP1 and a current signal corresponding to the fourth frequency within the second frequency band injected into the electrode pair of A1-FP1.

[0097] Likewise, the disease diagnosis device can measure the fifth to sixteenth impedances based on the current signals and voltage signals corresponding to the first and second frequencies within the first frequency band and the current signals and voltage signals corresponding to the third and fourth frequencies within the second frequency band for the electrode pairs A1-FP2, A2-FP1, and A2-FP2.

[0098] The disease diagnosis device can group the impedances of the electrode pairs A1-FP1, A1-FP2, A2-FP1, and A2-FP2, which correspond to the first frequency band and the second frequency band, respectively, that is, the first to sixteenth impedances. At this time, the disease diagnosis device can group the first, second, fifth, sixth, ninth, tenth, thirteenth, and fourteenth impedances measured in relation to the first frequency and the second frequency within the first frequency band into the first frequency group (510) corresponding to the first frequency band. In addition, the disease diagnosis device can group the third, fourth, seventh, eighth, eleventh, twelfth, fifteenth, and sixteenth impedances measured in relation to the third frequency and the fourth frequency within the second frequency band into the second frequency group (520) corresponding to the second frequency band.

[0099] In an embodiment, the disease diagnosis device may determine whether a subject has developed a brain disease based on, for example, impedances included in the second frequency group (520) (or the first frequency group (510)). At this time, the disease diagnosis device may determine that the subject has developed a brain disease if the average (or minimum impedance, maximum impedance, or any single impedance) of the impedances included in the second frequency group (520) is equal to or greater than a set ratio of the set maximum impedance, or if the average of the impedances included in the second frequency group (520) is equal to or greater than a set ratio of the maximum impedance among the impedances included in the second frequency group (520). For example, if the average of the impedances included in the second frequency group (520) is 150 kΩ, the set maximum impedance (or the maximum impedance among the impedances included in the second frequency group (520)) is 200 kΩ, and the set ratio is 60%, the disease diagnosis device can determine that the subject of diagnosis has developed a brain disease because the average of the impedances, 150 kΩ, is greater than or equal to 120 kΩ, which is the set ratio of the maximum impedance.

[0100] In addition, the disease diagnosis device can determine whether a subject has a brain disease based on the established relationship between the first frequency group (510) and the second frequency group (520). Here, the relationship between the first frequency group (510) and the second frequency group (520) may be a reference relationship determined by a statistical estimation method between the first frequency group and the second frequency group for other subjects. The reference relationship may be expressed, for example, as in [Mathematical Formula 2].

[0101]

[0102] Here, the reference relation may include not only a linear equation but also a polynomial equation or any other nonlinear equation that can describe the relationship between two groups, or an equation related to statistical distribution, an equation related to probability values, etc.

[0103] For example, when the reference relationship between the first frequency group (510) and the second frequency group (520) is a proportional relationship such as Y0=X0, if any one of the impedances included in the first frequency group (510) (or, minimum impedance, maximum impedance, first statistical value of the impedances (e.g., mean, standard deviation, variance, etc.)) is detected as 200 kΩ, and any one of the impedances included in the second frequency group (520) (or, minimum impedance, maximum impedance, second statistical value of the impedances) is detected as 200 kΩ, the disease diagnosis device can determine that the subject of diagnosis does not have a brain disease (e.g., determine that the subject is normal) by satisfying the reference relationship between the groups Y0=X0.

[0104] On the other hand, when the reference relationship between the first frequency group (510) and the second frequency group (520) is a proportional relationship such as Y0=X0, and when the impedance of any one of the impedances included in the first frequency group (510) is detected as 100kΩ and the impedance of any one of the impedances included in the second frequency group (520) is detected as 200kΩ, the disease diagnosis device can determine that the subject of diagnosis has developed a brain disease (e.g., abnormal judgment or dementia judgment) because the reference relationship between the groups Y0=X0 is not satisfied.

[0105] In addition, the disease diagnosis device can determine that the subject of diagnosis has developed a brain disease if, for example, the difference between the first impedance included in the first frequency group (510) and the second impedance included in the second frequency group (520) (i.e., the absolute value of the first impedance - the second impedance) is greater than a set impedance.

[0106] The disease diagnosis device is not limited to determining dementia as a brain disease using the relationship between frequency groups, but can also determine the type of dementia (e.g., vascular dementia, frontotemporal dementia, dementia with Lewy bodies, Parkinson's dementia, Alzheimer's dementia, etc.). In addition, the disease diagnosis device can determine all dementias classified by stage, such as cognitive decline, memory decline, mild cognitive impairment, early / middle stage, and dementia classified by the severity of symptoms, such as mild dementia / severe dementia. For example, the disease diagnosis device can determine mild cognitive impairment based on the relationship between the first frequency group and the second frequency group, and can determine the type of dementia based on the relationship between the second frequency group and the third group.

[0107] In the embodiment, the disease diagnosis device is not limited to determining whether a brain disease has developed in a subject based on a set relationship between the first and second frequency groups (510, 520), but may derive a relationship between one impedance (or an average of the impedances) among the impedances included in the first frequency group (510) and one impedance (or an average of the impedances) among the impedances included in the second frequency group (520), and determine whether a brain disease has developed in a subject based on a comparison result between a slope in the derived relationship and a slope in the set relationship between the first and second frequency groups (510, 520). At this time, the disease diagnosis device may determine that a brain disease has not developed in a subject if the difference between the slopes is within a set error range as a result of the comparison, and may determine that a brain disease has developed in a subject if the difference between the slopes is outside the error range.

[0108] In addition, the disease diagnosis device can compare the impedances included in the first frequency group (510) and the impedances included in the second frequency group (520), and determine whether a brain disease has developed in the subject of diagnosis based on the comparison result (e.g., the difference or ratio between the impedances within the frequency groups). For example, a disease diagnosis device may determine that a subject has developed a brain disease if the ratio (Z-HFB / Z-LFB) of impedances corresponding to a low frequency band (e.g., 0 Hz to 100 Hz) (impedances measured in the low frequency band) to impedances corresponding to a high frequency band (e.g., 1 kHz to 20 kHz) (Z-HFB: Impedance, High Frequency Band) (impedances measured in the high frequency band) is equal to or greater than a set value (e.g., '1'), or if the difference between the impedances corresponding to the high frequency band and the impedances corresponding to the low frequency band is equal to or greater than a set value (e.g., '1'). At this time, the disease diagnosis device may calculate a first statistical value (e.g., mean, standard deviation, variance, etc.) for impedances corresponding to the low-frequency band, calculate a second statistical value for impedances corresponding to the high-frequency band, and calculate a difference or ratio between impedances between the low-frequency band and the high-frequency band using the first statistical value and the second statistical value. In addition, the disease diagnosis device may determine that the subject of diagnosis has developed a brain disease, for example, if the difference between the first impedance among the impedances corresponding to the low-frequency band and the second impedance among the impedances corresponding to the high-frequency band (i.e., the absolute value of the first impedance - the second impedance) is greater than or equal to a set impedance.

[0109] In an embodiment, the disease diagnosis device may calculate statistical values ​​for impedances between a first frequency group (510) and a second frequency group (520), and if the statistical values ​​are greater than or equal to a set value, the diagnosis subject may be determined to have developed a brain disease. For example, the disease diagnosis device may calculate a first average of impedances included in the first frequency group (510) and a second average of impedances included in the second frequency group (520), respectively, and calculate standard deviations for the first average and the second average. If the standard deviations are greater than or equal to the set value, the diagnosis subject may be determined to have developed a brain disease.

[0110] In another embodiment, a disease diagnosis device may detect a frequency shift value for a current signal corresponding to a first frequency band (or a second frequency band) and a voltage signal corresponding to the first frequency band (or a second frequency band) that are injected into an electrode pair, and determine whether a brain disease has developed in a subject of diagnosis based on the frequency shift value. Here, the frequency shift value for the current signal and the voltage signal may include a change in at least one of a frequency shift change degree, a frequency phase change degree, and a frequency duty cycle change degree. In this case, the disease diagnosis device may determine that the greater the frequency shift value for the current signal and the voltage signal, the higher the possibility of developing a brain disease.

[0111] For example, if the frequency of the current signal corresponding to the first frequency band injected into the electrode pair of A1-FP1 is '10 Hz' and the frequency of the voltage signal corresponding to the first frequency band measured from the electrode pair of A1-FP1 is '11 Hz', the disease diagnosis device can detect the degree of frequency shift change as '1 Hz' as the frequency shift value for the current signal and the voltage signal, and if '1 Hz' is greater than or equal to a set shift value (for example, '0.5 Hz'), it can determine that the diagnosis subject has developed a brain disease. At this time, the disease diagnosis device can detect the degree of frequency shift change in the first frequency band for each of the other electrode pairs, that is, the electrode pairs of A1-FP2, A2-FP1, and A2-FP2, and if the average of the degrees of frequency shift change in the first frequency band for the electrode pairs of A1-FP1, A1-FP2, A2-FP1, and A2-FP2 is greater than or equal to the set shift value, it can determine that the diagnosis subject has developed a brain disease.

[0112] In addition, the disease diagnosis device detects the degree of phase change of the frequency as '90' as a variation value for the current signal and the voltage signal when the frequency of the current signal corresponding to the first frequency band injected into the electrode pair of A1-FP1 is '10 Hz' and the phase is '0', and the frequency of the voltage signal corresponding to the first frequency band measured from the electrode pair of A1-FP1 is '10 Hz' and the phase is '90', and when '90' is equal to or greater than the set variation value (e.g., '45'), it can determine that the subject of diagnosis has developed a brain disease. At this time, the disease diagnosis device detects the degree of phase change in frequency in the first frequency band for the electrode pairs of other electrode pairs, i.e., A1-FP2, A2-FP1, and A2-FP2, respectively, and if the average degree of phase change in frequency in the first frequency band for the electrode pairs of A1-FP1, A1-FP2, A2-FP1, and A2-FP2 is greater than a set variation value, it can be determined that the subject of diagnosis has developed a brain disease.

[0113] The disease diagnosis device detects a duty cycle change degree of the frequency as '20%' as a variation value for the frequency of the current signal corresponding to the first frequency band injected into the electrode pair of A1-FP1 when the frequency is '10 Hz' and the duty cycle is '50%', and a voltage signal corresponding to the first frequency band measured from the electrode pair of A1-FP1 when the duty cycle is '30%' (or '70%'), and if '20%' is equal to or greater than the set variation value (for example, '10%'), it can determine that the subject of diagnosis has developed a brain disease. At this time, the disease diagnosis device detects the duty cycle degree of the frequency in the first frequency band for the electrode pairs of other electrode pairs, i.e., A1-FP2, A2-FP1, and A2-FP2, similar to the process of determining whether a brain disease has developed based on the degree of frequency shift change and frequency phase change, and if the average of the duty cycle degree of the frequency in the first frequency band for the electrode pairs of A1-FP1, A1-FP2, A2-FP1, and A2-FP2 is greater than or equal to a set variation value, it can be determined that the subject of diagnosis has developed a brain disease.

[0114] In another embodiment, a disease diagnosis device may detect a first frequency shift value for a current signal and a voltage signal corresponding to a first frequency band and a second frequency shift value for a current signal and a voltage signal corresponding to a second frequency band, and determine whether a brain disease has developed in a subject of diagnosis based on a comparison result of the first frequency shift value and the second frequency shift value. That is, the disease diagnosis device may determine that a brain disease has developed in a subject of diagnosis if a difference or ratio between the first frequency shift value and the second frequency shift value satisfies a set condition.

[0115] For example, if a disease diagnosis device detects a phase shift degree of frequency as '30' as a first frequency shift value for a current signal and a voltage signal in a low-frequency band, and detects a phase shift degree of frequency as '90' as a second frequency shift value for a current signal and a voltage signal in a high-frequency band, it can determine that the subject of diagnosis has developed a brain disease because the difference between the first frequency shift value and the second frequency shift value, which is '60', is greater than or equal to the set shift value, which is '45'.

[0116] In addition, when the disease diagnosis device detects the duty cycle change degree of the frequency as '20%' as the first frequency shift value for the current signal and voltage signal in the low-frequency band, and the phase change degree of the frequency as the second frequency shift value for the current signal and voltage signal in the high-frequency band, it can be determined that the subject of diagnosis has developed a brain disease because the difference between the first frequency shift value and the second frequency shift value, which is '10%', is greater than or equal to the set shift value of '5'.

[0117] FIG. 6 is a diagram illustrating an example of determining whether a subject has a brain disease by using relatively low impedance in a disease diagnosis device according to an embodiment of the present invention.

[0118] Referring to FIG. 6, a disease diagnosis device injects a current signal corresponding to one or more frequency bands into an electrode pair sequentially selected from among a plurality of electrodes attached to a diagnosis subject, and based on a voltage signal measured at the electrode pair as the current signal is injected, the device can detect the impedance of the electrode pair as a brain cell response signal of the electrode pair corresponding to one or more frequency bands.

[0119] A disease diagnosis device can determine whether a subject has a brain disease based on the slopes of impedances corresponding to a low-frequency band and impedances corresponding to a high-frequency band among one or more frequency bands. At this time, the disease diagnosis device can determine whether a subject has a brain disease based on the impedances corresponding to the low-frequency band and the high-frequency band respectively measured in the subject, based on the fact that the first slope (610) of the trend line (or relationship) between the impedances corresponding to the low-frequency band (Z-LFB) and the impedances corresponding to the high-frequency band (Z-HFB) measured from a normal control (NC) is 1, and the second slope (620) of the trend line (or relationship) between the impedances corresponding to the low-frequency band and the impedances corresponding to the high-frequency band measured from an abnormal group (low-impedance dementia, LI-AD) is not 1 (e.g., the slope > 1). At this time, the impedances (Z-LFB) corresponding to the low-frequency band measured from the normal group and the abnormal group, respectively, may be, for example, an impedance (e.g., 100 KΩ or less) that is less than a set ratio of the maximum (or minimum) impedance among the total impedances (Z-LFB) corresponding to the low-frequency band measured from the normal group and the abnormal group, respectively, but is not limited thereto. In addition, the impedances (Z-HFB) corresponding to the high-frequency band measured from the normal group and the abnormal group, respectively, may be, for example, an impedance (e.g., 100 KΩ or less) that is less than a set ratio of the maximum (or minimum) impedance among the total impedances (Z-HFB) corresponding to the high-frequency band measured from the normal group and the abnormal group, respectively, but is not limited thereto.

[0120] The disease diagnosis device can diagnose the subject as normal if the slope of the trend line between the impedances corresponding to the low-frequency band measured in the subject and the impedances corresponding to the high-frequency band is 1, determining that the subject does not have dementia. In addition, the disease diagnosis device can diagnose the subject as abnormal if the slope of the trend line between the impedances corresponding to the low-frequency band measured in the subject and the impedances corresponding to the high-frequency band is not 1, determining that the subject has dementia.

[0121] Meanwhile, conventional disease diagnosis devices measure the impedance of the brain using a single frequency band under the premise that the higher the impedance measured from the electrode pair of the diagnosis subject, the higher the possibility of developing a brain disease. If the measured impedance is higher than a set value, the diagnosis subject can be determined to have developed a brain disease. At this time, conventional disease diagnosis devices can measure a relatively low impedance compared to other brain diseases when the diagnosis subject has developed a specific brain disease (e.g., brain disease accompanied by hyperactivity). Due to the low impedance, even though the diagnosis subject has developed a brain disease, the diagnosis subject may be determined to not have developed a brain disease, resulting in a misdiagnosis of the diagnosis subject as normal.

[0122] However, the disease diagnosis device according to an embodiment of the present invention determines whether a brain disease has developed in a subject of diagnosis based on the analysis results between impedances corresponding to different frequency bands (e.g., whether the slope between impedances corresponding to different frequency bands includes an error range), thereby accurately determining whether a brain disease has developed in a subject of diagnosis even if a relatively low impedance is measured for a specific brain disease.

[0123] FIG. 7 is a drawing for explaining that the method according to the present invention is applicable to a CT scanner.

[0124] In another embodiment of the present invention, the disease diagnosis method according to the present invention can be utilized to implement a CT scanner. Here, the CT scanner includes both a brain electrical signal CT scanner (computed tomography scanner) and a brain impedance CT scanner, which can analyze the function of a user's brain or determine the presence or absence of a disease occurring in the brain by measuring the brain's electrical signals and brain impedance in response to the current provided to the user's scalp.

[0125] Meanwhile, general bioimpedance measuring devices perform data processing for body composition analysis using frequencies in the range of several hundred KHz to several MHz, but the disease diagnosis method according to the present invention has a differentiated feature in that it uses a signal in a much lower frequency band than the frequency of the signal used by existing impedance measuring devices. In particular, FIG. 7 discloses an embodiment of calculating brain impedance using a frequency of several tens of KHz or less, which is the region where brain cells are active. As described above, the reason for using a frequency of several tens of KHz or less in the present invention is to interact with the activity frequency of brain cells. The present invention utilizes the characteristic that the reactivity of brain cells is measured differently when the brain cells are normal and when they are abnormal due to disease.

[0126] The operation of the disease diagnosis module (112) when the present invention is applied to a CT scanner is specifically described below with reference to FIG. 7.

[0127] First, the disease diagnosis module (112) can select two electrodes randomly from among the multiple electrodes placed on the user's head as shown in Fig. 7, configure an electrode pair, and then calculate impedance. Next, the disease diagnosis module (112) can randomly select an electrode pair different from the previously selected electrode pair, scan the selected electrodes by turning them on / off, and receive and analyze the resulting values.

[0128] As an example, the disease diagnosis module (112) can select an electrode pair that is opposite to each other in the (A)-(A') direction, such as an electrode pair composed of the F7 electrode and the T6 electrode of FIG. 7. As another example, the disease diagnosis module (112) can select any two electrodes as an electrode pair, such as an electrode pair composed of the Fp1 electrode and the Fp2 electrode of FIG. 7. That is, if the total number of electrodes is n, the number of types of electrode pairs that the disease diagnosis module (112) can select as electrode pairs can be nC2.

[0129] The disease diagnosis module (112) can reconstruct the impedance at a specific location within the brain in two or three dimensions using the brain impedance of each region collected in the aforementioned manner. Alternatively, the disease diagnosis module (112) can determine the size and distribution of ions near brain cells, or identify neurotransmitters and calculate the degree of secretion (activity) of the neurotransmitters from the brain impedance of each region collected in the aforementioned manner.

[0130] In particular, since the depth at which the signal penetrates into the user's brain varies depending on the magnitude and frequency of the current applied by the signal generator (310) included in the disease diagnosis module (112), when the disease diagnosis module (112) varies the current in the range of 2 mA or less and varies the frequencies of the selected electrode pairs corresponding to the first frequency band and the second frequency band, respectively, and measures and analyzes the brain cell response signal, the disease diagnosis module (112) according to the present invention can be utilized as a brain impedance CT scanner capable of diagnosing brain cells inside the brain as well as the scalp, as illustrated in FIG. 7. This utilizes the tendency for high-frequency signals to generally penetrate deeply and low-frequency signals to penetrate less deeply.

[0131] According to one embodiment of the present invention illustrated in FIG. 7, unlike the LORETA method that mathematically calculates the internal source using brain waves measured only from the scalp, the accuracy and consistency of the analysis can be guaranteed because the actual value is measured and utilized for analysis.

[0132] In addition, according to one embodiment of the present invention illustrated in FIG. 7, an electrical abnormality caused by an abnormality occurring in brain cells before a disease progresses in the brain and failure to maintain ion balance inside and outside the brain cells is estimated through impedance change, thereby enabling early diagnosis of brain-related diseases before structural changes such as brain tumors occur.

[0133] Figure 8 is a flowchart illustrating a disease diagnosis method according to the present embodiment. In the following description, any portions that overlap with the descriptions of Figures 1 through 7 will be omitted. The disease diagnosis method can be performed by a disease diagnosis device according to the present embodiment.

[0134] Referring to FIG. 8, in step S810, the disease diagnosis device may inject a current signal corresponding to one or more frequency bands into a selected electrode pair among a plurality of electrodes attached to the diagnosis subject. At this time, the disease diagnosis device may sequentially select an electrode pair among the plurality of electrodes and inject a current signal corresponding to one or more frequency bands. Here, the one or more frequency bands may include a first frequency band (e.g., a low frequency band in the range of 0 Hz to 100 Hz) and a second frequency band (e.g., a high frequency band in the range of 1 kHz to 20 kHz).

[0135] In step S820, the disease diagnosis device can detect brain cell response signals of the electrode pair corresponding to one or more frequency bands based on voltage signals measured at the electrode pairs as current signals are injected. The disease diagnosis device can detect brain cell response signals of the electrode pair corresponding to one or more frequency bands by measuring voltage signals corresponding to one or more frequency bands measured at the electrode pairs and measuring impedance of the electrode pair corresponding to one or more frequency bands based on the current signals corresponding to one or more frequency bands injected into the electrode pairs and the voltage signals measured at the electrode pairs. Here, the brain cell response signal corresponding to a first frequency band among the one or more frequency bands may include a plurality of brain cell response signals corresponding to each of a plurality of frequencies within the first frequency band. In addition, the brain cell response signal corresponding to a second frequency band among the one or more frequency bands may include a plurality of brain cell response signals corresponding to each of a plurality of frequencies within the second frequency band.

[0136] In step S830, the disease diagnosis device may group brain cell response signals corresponding to a first frequency band and a second frequency band among one or more frequency bands into a first frequency group and a second frequency group, respectively. Here, the brain cell response signals of the electrode pairs corresponding to the first frequency band and the second frequency band, respectively, may include the impedance of the electrode pairs corresponding to the first frequency band and the second frequency band, respectively.

[0137] In step S840, the disease diagnosis device can determine whether a brain disease has developed in the subject of diagnosis based on the analysis result of the brain cell response signal within the first frequency group or the comparative analysis result between the brain cell response signal within the first frequency group and the brain cell response signal within the second frequency group.

[0138] The disease diagnosis device can determine that a subject has developed a brain disease if, as a result of analyzing a brain cell response signal within the first frequency group (or the second frequency group), the impedance of an electrode pair within the first frequency group (or the second frequency group) is greater than a set ratio with respect to a preset maximum brain impedance.

[0139] In addition, the disease diagnosis device can determine that the subject of diagnosis has developed a brain disease when, as a result of comparative analysis between brain cell response signals of each of the first frequency group and the second frequency group, the difference (or ratio between the impedances) between the impedances (one or more impedances) of the electrode pairs in the first frequency group and the impedances (one or more impedances) of the electrode pairs in the second frequency group is greater than or equal to a preset brain impedance (or a preset ratio), or the impedances of the electrode pairs in the first frequency group and the impedances of the electrode pairs in the second frequency group do not satisfy a preset relationship.

[0140] In an embodiment, the disease diagnosis device may calculate statistical values ​​for the impedance (one impedance or multiple impedances) of an electrode pair within a first frequency group and the impedance (one impedance or multiple impedances) of an electrode pair within a second frequency group, and if the statistical values ​​are greater than a set value, it may be determined that the subject of diagnosis has developed a brain disease.

[0141] In addition, the disease diagnosis device can detect a frequency shift value for a current signal corresponding to the first frequency band (or the second frequency band) and a voltage signal corresponding to the first frequency band (or the second frequency band), and determine whether a brain disease has developed in the subject of diagnosis based on the frequency shift value. Here, the frequency shift value can include a change in at least one of a frequency shift change degree, a frequency phase change degree, and a frequency duty cycle change degree.

[0142] A disease diagnosis device detects a first frequency shift value for a current signal corresponding to a first frequency band and a voltage signal corresponding to the first frequency band, and a second frequency shift value for a current signal corresponding to a second frequency band and a voltage signal corresponding to the second frequency band, and can determine whether a subject of diagnosis has developed a brain disease based on a comparison result of the first frequency shift value and the second frequency shift value.

[0143] A disease diagnosis device according to an embodiment of the present invention detects brain cell response signals of electrode pairs corresponding to one or more frequency bands among a plurality of electrodes attached to a subject of diagnosis, and determines whether a brain disease (e.g., Alzheimer's) has developed in the subject of diagnosis based on the analysis result of the brain cell response signal corresponding to a single frequency band or the comparative analysis result between brain cell response signals corresponding to a plurality of frequency bands, thereby making it possible to diagnose brain diseases early and accurately while making the analysis process simple from an electrophysiological perspective.

[0144] By measuring the active responses of brain cells to external electrical stimulation, brain diseases can be diagnosed more accurately than conventional electroencephalography (EEG) analysis, which simply measures passive responses. Furthermore, by adopting a method that specifically measures the source of electrical signals, unlike EEG measurements where the source is unknown, the accuracy of analysis and diagnosis is enhanced. Furthermore, unlike EEG measurements, brain signals measured from a specific electrode are extremely unlikely to be mixed with signals from other electrodes, resulting in a very high accuracy of analysis and diagnosis.

[0145] In addition, the disease diagnosis device according to an embodiment of the present invention detects the impedance of the electrode pair corresponding to the plurality of frequency bands as a brain cell response signal of the electrode pair corresponding to the plurality of frequency bands among the plurality of electrode pairs attached to the diagnosis subject, and determines whether the diagnosis subject has developed a brain disease based on the result of comparative analysis between the impedances of the electrode pairs, so that even if a specific brain disease that cannot be detected by an existing diagnosis method (for example, a diagnosis based on the possibility of developing a brain disease as the impedance is higher) is developed in the diagnosis subject due to the detection of a relatively lower impedance than other brain diseases or the occurrence of a correlation between the measured electrode pairs, the disease can be accurately diagnosed.

[0146] The embodiments of the present invention described above may be implemented in the form of a computer program that can be executed through various components on a computer, and such a computer program may be recorded on a computer-readable medium. At this time, the medium may include a magnetic medium such as a hard disk, a floppy disk, and a magnetic tape, an optical recording medium such as a CD-ROM and a DVD, a magneto-optical medium such as a floptical disk, and a hardware device specifically configured to store and execute program instructions, such as a ROM, a RAM, a flash memory, etc.

[0147] Meanwhile, the computer program may be specifically designed and constructed for the present invention, or may be one known and available to those skilled in the computer software field. Examples of computer programs may include not only machine language code, such as that generated by a compiler, but also high-level language code that can be executed by a computer using an interpreter or the like.

[0148] The specific implementations described in the present invention are exemplary embodiments and do not limit the scope of the present invention in any way. For the sake of brevity, descriptions of conventional electronic components, control systems, software, and other functional aspects of the systems may be omitted. In addition, the lines connecting or connecting members between components illustrated in the drawings are merely representative of functional connections and / or physical or circuit connections, and may be replaced or represented as various additional functional connections, physical connections, or circuit connections in an actual device. In addition, unless specifically mentioned as “essential,” “important,” etc., a component may not be absolutely necessary for the application of the present invention.

[0149] The use of the term "above" and similar referential terms in the specification of the present invention (especially in the claims) may refer to both singular and plural. Furthermore, if a range is described in the present invention, it includes inventions that apply individual values ​​within the range (unless otherwise stated), and is equivalent to describing each individual value constituting the range in the detailed description of the invention. Finally, unless the order of the steps constituting the method according to the present invention is explicitly stated or otherwise stated to the contrary, the steps may be performed in any appropriate order. The present invention is not necessarily limited by the order in which the steps are described. The use of all examples or exemplary terms (e.g., "for example," etc.) in the present invention is merely intended to illustrate the present invention in detail, and the scope of the present invention is not limited by the examples or exemplary terms, unless otherwise defined by the claims. Furthermore, those skilled in the art will appreciate that various modifications, combinations, and variations can be made within the scope of the appended claims or their equivalents, depending on design conditions and factors.

[0150] One embodiment of the present invention can be utilized in manufacturing a medical device for treating cognitive dysfunction.

Claims

1. A signal generation unit that injects a current signal corresponding to one or more frequency bands into a pair of electrodes selected from among a plurality of electrodes attached to a subject of diagnosis; A signal processing unit that detects a brain cell response signal of the electrode pair corresponding to one or more frequency bands based on a voltage signal measured at the electrode pair as the current signal is injected; and A processor that groups the brain cell response signals corresponding to the first frequency band and the second frequency band among the one or more frequency bands into a first frequency group and a second frequency group, and determines whether the subject of the diagnosis has developed a brain disease based on the analysis result of the brain cell response signal in either the first frequency group or the second frequency group, or the comparative analysis result between the brain cell response signal in the first frequency group and the brain cell response signal in the second frequency group. Disease diagnostic device.

2. In paragraph 1, The brain cell response signal of the electrode pair corresponding to the first frequency band includes the impedance of the electrode pair corresponding to the first frequency band, The above processor, As a result of analyzing the brain cell response signal within the first frequency group, if the impedance of the electrode pair within the first frequency group is greater than or equal to a set ratio for a preset maximum brain impedance, it is determined that the subject of the diagnosis has developed a brain disease. Disease diagnostic device.

3. In paragraph 1, The brain cell response signal of the electrode pair corresponding to the first frequency band and the second frequency band, respectively, includes the impedance of the electrode pair corresponding to the first frequency band and the second frequency band, respectively, The above processor, As a result of the comparative analysis between the brain cell response signals of each of the first frequency group and the second frequency group, if the difference between the impedance of the electrode pair in the first frequency group and the impedance of the electrode pair in the second frequency group is greater than or equal to a preset brain impedance, or if the impedance of the electrode pair in the first frequency group and the impedance of the electrode pair in the second frequency group do not satisfy a preset relationship, it is determined that the subject of the diagnosis has developed a brain disease. Disease diagnostic device.

4. In paragraph 1, The brain cell response signal of the electrode pair corresponding to the first frequency band and the second frequency band, respectively, includes the impedance of the electrode pair corresponding to the first frequency band and the second frequency band, respectively, The above processor, Calculating statistical values ​​for the impedance of the electrode pair in the first frequency group and the impedance of the electrode pair in the second frequency group, and determining that the subject of the diagnosis has developed a brain disease when the statistical values ​​are greater than or equal to a set value. Disease diagnostic device.

5. In paragraph 1, The above processor, Detecting a frequency shift value for a current signal corresponding to the first frequency band and a voltage signal corresponding to the first frequency band, and determining whether a brain disease has developed in the subject of diagnosis based on the frequency shift value. Disease diagnostic device.

6. In paragraph 1, The above processor, Detecting a first frequency shift value for a current signal corresponding to the first frequency band and a voltage signal corresponding to the first frequency band, and a second frequency shift value for a current signal corresponding to the second frequency band and a voltage signal corresponding to the second frequency band, and determining whether a brain disease has developed in the subject of diagnosis based on a comparison result of the first frequency shift value and the second frequency shift value. Disease diagnostic device.

7. In paragraph 1, The brain cell response signal corresponding to the first frequency band includes a plurality of brain cell response signals corresponding to each of a plurality of frequencies within the first frequency band, The above processor, Grouping the plurality of brain cell response signals into the first frequency group, calculating statistical values ​​for the plurality of brain cell response signals within the first frequency group, and determining whether the subject of the diagnosis has a brain disease based on the analysis results of the statistical values. Disease diagnostic device.

8. In paragraph 1, The above signal generating unit, Sequentially selecting electrode pairs among the plurality of electrodes and injecting current signals corresponding to one or more frequency bands, Disease diagnostic device.

9. In paragraph 1, The above device, A disease diagnosis device, one of a brain electrical signal CT scanner and a brain impedance CT scanner.

10. A disease diagnosis method performed by a disease diagnosis device, A step of injecting a current signal corresponding to one or more frequency bands into a selected electrode pair among a plurality of electrodes attached to a subject of diagnosis; A step of detecting a brain cell response signal of the electrode pair corresponding to the one or more frequency bands based on a voltage signal measured at the electrode pair as the current signal is injected; A step of grouping the brain cell response signals corresponding to the first frequency band and the second frequency band among the one or more frequency bands into a first frequency group and a second frequency group, respectively; and A step of determining whether a brain disease has developed in the subject of diagnosis based on the analysis result of the brain cell response signal within the first frequency group or the comparative analysis result between the brain cell response signal within the first frequency group and the brain cell response signal within the second frequency group, How to diagnose disease.

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