Apparatus for sleep quality analysis using a wearable device with flexible electrodes, method for sleep quality analysis, and system for sleep quality analysis

Abstract

The present invention relates to an apparatus for sleep quality analysis using a wearable device with flexible electrodes, to a method for sleep quality analysis, and to a system for sleep quality analysis. The present invention may: transmit, to a wearable device worn by a user, a measurement control signal for controlling measurement and transmission of biometric data for sleep state analysis; collect, from the wearable device, the biometric data measured by the wearable device, via flexible electrodes attached to the user; and analyze the collected biometric data using artificial intelligence to determine a sleep stage indicative of the user's sleep quality.

Description

Sleep quality analysis device, sleep quality analysis method, and sleep quality analysis system using a wearable device utilizing flexible electrodes

[0001] The present invention relates to a sleep quality analysis device, a sleep quality analysis method, and a sleep quality analysis system using a wearable device utilizing a flexible electrode, and more specifically, to a technology for improving user convenience through a wearable device without wires using a flexible electrode that is well attached to the skin and yet elastic, thereby minimizing foreign body sensation, and for precisely analyzing and determining sleep stages without disturbing the user's sleep.

[0002] With the rapid growth of IoT (Internet of Things) technology, various wearable devices that utilize it are being developed.

[0003] Healthcare wearable devices are being developed to monitor health status and activity information by measuring users' biometric and movement signals.

[0004] They are divided into wellness wearable devices for healthcare services and medical wearable devices for medical purposes.

[0005] A representative wellness wearable device is a fitness device that monitors various biosignal data and provides it to users.

[0006] Wearable biosignal sensors that can track multimodal biosignals in real time, such as electroencephalogram (EEG) data, electrooculography (EOG) data, electromyogram (EMG) data, photoplethysmography (PPG) data, and electrocardiogram (ECG) data, are attracting attention for health monitoring in daily life.

[0007] To ensure stable collection of these biosignals, the electrodes must be highly conductive, flexible, and biocompatible with human skin.

[0008] Additionally, these properties must be met in a thin film form to make the electrodes highly transparent, which is useful for real-time, daily monitoring of biosignals from exposed skin such as the face, such as for drowsy driver detection or voice recognition.

[0009] Additionally, high optical transparency enables light-based biological activity monitoring techniques such as laser speckle imaging for diagnosing facial nerve disorders.

[0010] There is also growing interest in research into flexible / stretchable electrodes for use in various wearable devices.

[0011] Flexible and stretchable electrode materials are being increasingly actively researched as multifunctional materials that can be used not only as electrodes but also as strain sensors themselves.

[0012] Meanwhile, unlike elements formed on rigid substrates, flexible electronic elements maintain their properties even when repeated stress is applied, and have the characteristic of being easily bent, and can be used in flexible electronic components such as flexible displays and touch screens, or sensors that can be attached to free-form surfaces.

[0013] Although composite materials have been mainly used up to now, since all composite materials fall into the solid electrode category, it is difficult to secure a long lifespan by applying them to the ultimate elastic element.

[0014] The present invention aims to provide a sleep quality analysis device, a sleep quality analysis method, and a sleep quality analysis system that improve user convenience through a wearable device without wires using a flexible electrode that is well attached to the skin and is thin and elastic, minimizing foreign body sensation, and precisely analyzes and determines sleep stages without disturbing the user's sleep.

[0015] The present invention aims to provide a sleep quality analysis device, a sleep quality analysis method, and a sleep quality analysis system that precisely analyze and determine sleep stages by analyzing electroencephalogram (EEG) data, electrooculography (EOG) data, electromyogram (EMG) data, photoplethysmography (PPG) data, and electrocardiogram (ECG) data collected from a wearable device using an artificial intelligence algorithm.

[0016] The present invention aims to implement long-term and stable sleep and health monitoring in daily life by analyzing a user's sleep stage by tracking multi-mode biosignals in real time using a flexible electrode that is thin and elastic while being well attached to the skin to minimize foreign body sensation.

[0017] A sleep quality analysis device according to one embodiment of the present invention includes a measurement processing unit that transmits a measurement control signal for controlling measurement and transmission of biometric data for sleep state analysis to a wearable device worn by a user, a data collection unit that collects biometric data measured by the wearable device through a flexible electrode attached to the user from the wearable device, and a data analysis unit that determines a sleep stage indicating the sleep quality of the user by analyzing the collected biometric data using artificial intelligence, wherein the flexible electrode includes an elastic thin film based on a conductive polymer thin film modified with an adhesive and an ionic liquid in which tannic acid and sorbitol are mixed based on a preset mass ratio, and can be attached to a face area and the head area of ​​the user to measure the biometric data.

[0018] The flexible electrode is positioned at a first attachment location of the mask pack structure corresponding to the tip of the eyebrows above the two eyes for measuring the biometric data on the user's face, at a second attachment location of the mask pack structure corresponding to two parts around the eyes for measuring the biometric data on the user's face, at a third attachment location of the mask pack structure corresponding to two parts around the cheek and chin for measuring the biometric data on the user's face, and at a fourth attachment location of the mask pack structure corresponding to the space between the eyebrows, and when the mask pack structure is aligned and worn on the user's face based on the positions punched on the mask pack structure, it is attached to the first attachment location, the second attachment location, the third attachment location, and the fourth attachment location, and is attached to the user's face corresponding to the first attachment location, the second attachment location, the third attachment location, and the fourth attachment location, and is connected to the wearable device after the mask pack structure is removed, and transmits biometric data measured according to movement of the attached face part to the wearable device, and is attached to the mastoid process of the user. It can be additionally attached to the corresponding fifth attachment location to transmit biometric data to the wearable device.

[0019] The above data collection unit can collect the biometric data including at least one of electroencephalogram (EEG) data, electrooculography (EOG) data, electromyogram (EMG) data, photoplethysmography (PPG) data, and electrocardiogram (ECG) data.

[0020] The data analysis unit generates a first detection signal based on the brainwave data, generates a second detection signal synchronized with the first detection signal among the safety latitude data, the electromyography data, and the electrocardiogram data, extracts a first feature from the first detection signal, extracts a second feature from the second detection signal, and learns a determination criterion for determining the sleep stage using the first feature and the second feature using artificial intelligence, and determines the sleep stage based on the learned determination criterion.

[0021] The above data analysis unit can verify the determination criteria by artificial intelligence learning the electroencephalogram (EEG) and the determination criteria that divide the sleep stages into REM (rapid eye movement) sleep stages and first to third sleep stages for the biometric data.

[0022] The flexible electrode may include an insulating tape layer, a conductive tape layer, an electric wire connected to the wearable device, a stretchable thin film layer including the adhesive and the polymer thin film, and a SEBS (styrene ethylene butylene styrene) substrate.

[0023] The adhesive has a mass ratio of the tannic acid and the sorbitol of 1:0.1 to 1:9, and the conductive polymer thin film can be any one of PEDOT:PSS / p-MIM:TFSI, PEDOT:PSS / EMIM:TFSI, and PEDOT:PSS / Li:TFSI.

[0024] According to one embodiment of the present invention, a sleep quality analysis method includes a step of transmitting, by a measurement processing unit, a measurement control signal for controlling measurement and transmission of biometric data for sleep state analysis to a wearable device worn by a user, a step of collecting, by a data collection unit, biometric data measured by the wearable device through a flexible electrode attached to the user from the wearable device, and a step of determining, by a data analysis unit, a sleep stage indicating the sleep quality of the user by performing an artificial intelligence analysis on the collected biometric data, wherein the flexible electrode includes a stretchable thin film based on a conductive polymer thin film modified with an adhesive and an ionic liquid in which tannic acid and sorbitol are mixed based on a preset mass ratio, and can be attached to a face area and the head area of ​​the user to measure the biometric data.

[0025] According to one embodiment of the present invention, a sleep stage and sleep quality analysis system comprises: a wearable device worn by a user and using flexible electrodes attached to the user to measure biometric data for analyzing the sleep state of the user; a user terminal device that transmits a measurement control signal for controlling measurement and transmission of the biometric data to the wearable device and collects the biometric data from the wearable device; and an artificial intelligence server that determines a sleep stage representing the sleep quality of the user by performing an artificial intelligence analysis on the collected biometric data and transmits the determined sleep stage to the user terminal device and an administrator terminal device; wherein the flexible electrode comprises a stretchable thin film based on a conductive polymer thin film modified with an adhesive and an ionic liquid in which tannic acid and sorbitol are mixed based on a preset mass ratio, and can be attached to a face area and the head area of ​​the user to measure the biometric data.

[0026] According to one embodiment of the present invention, a flexible electrode is included in a sleep quality analysis device, and includes an adhesive in which tannic acid and sorbitol are mixed based on a preset mass ratio, and an elastic film based on a conductive polymer thin film in which the tannic acid and the sorbitol are mixed based on a preset mass ratio and modified with an ionic liquid, wherein the adhesive and the elastic film may have a mass ratio of the tannic acid and the sorbitol of 1:0.1 to 1:9.

[0027] The thickness of the adhesive may be 1 nm to 10,000 nm, and the thickness of the elastic thin film may be 1 nm to 10,000 nm.

[0028] The above conductive polymer thin film may be any one of PEDOT:PSS / p-MIM:TFSI, PEDOT:PSS / EMIM:TFSI, and PEDOT:PSS / Li:TFSI.

[0029] The present invention can provide a sleep quality analysis device, a sleep quality analysis method, and a sleep quality analysis system that improve user convenience through a wearable device without wires using a flexible electrode that is well attached to the skin and has elasticity to minimize foreign body sensation, and precisely analyzes and determines sleep stages without disturbing the user's sleep.

[0030] The present invention can provide a sleep quality analysis device, a sleep quality analysis method, and a sleep quality analysis system that precisely analyze and determine sleep stages by analyzing electroencephalogram (EEG) data, electrooculography (EOG) data, electromyogram (EMG) data, electrocardiogram (ECG) data, and photoplethysmography (PPG) data collected from a wearable device using an artificial intelligence algorithm.

[0031] The present invention utilizes a flexible electrode that adheres well to the skin while being elastic and thus minimizing foreign body sensation, thereby tracking multi-mode biosignals in real time and analyzing the user's sleep stage, thereby enabling long-term and stable sleep and health monitoring in daily life.

[0032] FIG. 1 is a drawing illustrating a sleep quality analysis device using a wearable device utilizing a flexible electrode according to one embodiment of the present invention.

[0033] FIG. 2a and FIG. 2b are drawings illustrating a sleep quality analysis system using a wearable device utilizing a flexible electrode according to one embodiment of the present invention.

[0034] FIGS. 3 to 5 are drawings explaining a method for attaching a flexible electrode to a measurement target according to one embodiment of the present invention.

[0035] Figure 6 is a drawing explaining the structure of a flexible electrode according to one embodiment of the present invention.

[0036] FIG. 7 is a drawing illustrating an optical microscope image of an adhesive constituting a stretchable thin film of a flexible electrode according to one embodiment of the present invention.

[0037] FIG. 8 is a drawing explaining the crack initiation strain of a thin film related to an adhesive constituting a flexible thin film of a flexible electrode according to one embodiment of the present invention.

[0038] FIG. 9 and FIG. 10 are drawings explaining the adhesive strength of an adhesive constituting a stretchable thin film of a flexible electrode according to one embodiment of the present invention.

[0039] FIGS. 11A to 11D are drawings explaining the strain and elasticity of a flexible thin film of a flexible electrode according to one embodiment of the present invention.

[0040] FIG. 12 is a drawing explaining the improvement in elasticity of the elastic film of a flexible electrode according to one embodiment of the present invention.

[0041] FIG. 13 is a drawing illustrating a cytotoxicity analysis of a flexible thin film of a flexible electrode according to an embodiment of the present invention.

[0042] FIGS. 14a to 15b are drawings explaining the results of biometric data measurement of a flexible electrode according to one embodiment of the present invention.

[0043] FIG. 16 is a diagram explaining a sleep stage determined by a data analysis unit according to one embodiment of the present invention.

[0044] FIG. 17 is a diagram illustrating a method for increasing the quality of analysis data based on artificial intelligence learning in a data analysis unit according to one embodiment of the present invention.

[0045] FIG. 18 is a drawing illustrating a procedure for performing a sleep stage determination algorithm in a data analysis unit according to one embodiment of the present invention.

[0046] FIG. 19 is a drawing explaining a method for analyzing sleep quality using a wearable device utilizing a flexible electrode according to one embodiment of the present invention.

[0047] Below, various embodiments of this document are described with reference to the attached drawings.

[0048] The examples and terms used herein are not intended to limit the technology described in this document to a particular embodiment, but should be understood to encompass various modifications, equivalents, and / or alternatives of the embodiments.

[0049] In the following description of various embodiments, if it is determined that a detailed description of a related known function or configuration may unnecessarily obscure the gist of the invention, the detailed description will be omitted.

[0050] The terms described below are defined based on their functions in various embodiments, and may vary depending on the intent or custom of the user or operator. Therefore, their definitions should be based on the contents of this specification.

[0051] In connection with the description of the drawings, similar reference numerals may be used for similar components.

[0052] A singular expression may include a plural expression unless the context clearly indicates otherwise.

[0053] In this document, expressions such as "A or B" or "at least one of A and / or B" may include all possible combinations of the items listed together.

[0054] Expressions such as "first," "second," "first," or "second," may modify the components without regard to order or importance, and are used only to distinguish one component from another, but do not limit the components.

[0055] When it is said that a component (e.g., a first component) is “(functionally or communicatively) connected” or “connected” to another component (e.g., a second component), the component may be directly connected to the other component, or may be connected via another component (e.g., a third component).

[0056] In this specification, “configured to” may be used interchangeably with “suitable for,” “capable of,” “modified to,” “made to,” “capable of,” or “designed to,” depending on the context, for example, in terms of hardware or software.

[0057] In some contexts, the expression "a device configured to" may mean that the device is "capable of" doing something in conjunction with other devices or components.

[0058] For example, the phrase "a processor configured (or set) to perform A, B, and C" may mean a dedicated processor (e.g., an embedded processor) for performing those operations, or a general-purpose processor (e.g., a CPU or application processor) that can perform those operations by executing one or more software programs stored in a memory device.

[0059] Also, the term 'or' means 'inclusive or' rather than 'exclusive or'.

[0060] That is, unless otherwise stated or clear from context, the expression 'x utilizes a or b' means any one of the natural inclusive permutations.

[0061] The terms '..bu', '..gi', etc. used below mean a unit that processes at least one function or operation, and this can be implemented by hardware, software, or a combination of hardware and software.

[0062]

[0063] FIG. 1 is a drawing illustrating a sleep quality analysis device using a wearable device utilizing a flexible electrode according to one embodiment of the present invention.

[0064] FIG. 1 illustrates components of a sleep quality analysis device using a wearable device utilizing a flexible electrode according to one embodiment of the present invention.

[0065] Referring to FIG. 1, a sleep quality analysis device (100) according to one embodiment of the present invention includes a measurement processing unit (101), a data collection unit (102), and a data analysis unit (103), and can collect a user's biometric data through a wearable device (110) utilizing a flexible electrode.

[0066] For example, the measurement processing unit (101) can transmit a measurement control signal to a wearable device worn by a user to control measurement and transmission of biometric data for measurement sleep state analysis.

[0067] That is, the measurement processing unit (101) can transmit a biometric data measurement control signal to the wearable device (110) to collect biometric data for analyzing the user's sleep state through a flexible electrode connected to the wearable device (110).

[0068] The data collection unit (102) can collect biometric data measured by the wearable device (110) through a flexible electrode attached to the user from the wearable device (110).

[0069] The data analysis unit (103) can determine the sleep stage indicating the user's sleep quality by analyzing the collected biometric data using artificial intelligence.

[0070] For example, the flexible electrode utilized by the wearable device (110) includes a stretchable thin film based on a conductive polymer thin film modified with an adhesive and an ionic liquid in which tannic acid and sorbitol are mixed based on a preset mass ratio, and can be attached to the user's face and around the head to measure biometric data.

[0071] The wearable device (110) is capable of Bluetooth communication, two brain wave channels, one safety channel, one electromyography channel, and PPG-based heart rate measurement, and is also equipped with an accelerometer sensor to measure various bio-signals for sleep stage analysis, thereby constructing, generating, and transmitting bio-data.

[0072] For example, the two brainwave channels may correspond to the F7-A2 channel and the F8-A1 channel based on the image provided in FIG. 3, and may correspond to a combination of the first flexible electrode and the fifth flexible electrode.

[0073] The first flexible electrode is attached to F7 and F8, and the fifth flexible electrode is attached to A1 and A2.

[0074] For example, an EEG channel may be a channel through which EEG data is collected.

[0075] In addition, the flexible electrode is positioned at a first attachment location of the mask pack structure corresponding to the tip of the eyebrows above the two eyes for measuring biometric data on the user's face, at a second attachment location of the mask pack structure corresponding to two parts around the eyes for measuring biometric data on the user's face, at a third attachment location of the mask pack structure corresponding to two parts around the cheek and chin for measuring biometric data on the user's face, and at a fourth attachment location of the mask pack structure corresponding to the space between the eyebrows.

[0076] Additionally, the flexible electrodes can be attached to the first attachment location, the second attachment location, the third attachment location, and the fourth attachment location when the mask pack structure is aligned and worn on the user's face based on the positions punched on the mask pack structure.

[0077] In addition, the flexible electrodes are attached to the user's face corresponding to the first attachment location, the second attachment location, the third attachment location, and the fourth attachment location, and are connected to the wearable device (110) after the mask pack structure is removed so that biometric data measured according to movement of the attached face location can be transmitted to the wearable device (110). The electrode attached to the fourth attachment location can be used as a reference electrode.

[0078] In addition, a flexible electrode can be additionally attached to the fifth attachment location corresponding to the user's pubic bone to transmit biometric data measured from that location to the wearable device.

[0079] The data collection unit (102) can collect biometric data including at least one of electroencephalogram (EEG) data, electrooculography (EOG) data, electromyogram (EMG) data, photoplethysmography (PPG) and electrocardiogram (ECG) data.

[0080] The data analysis unit (103) can generate a first detection signal based on brain wave data and generate a second detection signal synchronized with the first detection signal among safety latitude data, electromyography data, photoplethysmography, and electrocardiogram data.

[0081] The data analysis unit (103) extracts a first feature from a first detection signal, extracts a second feature from a second detection signal, learns a determination criterion for determining a sleep stage using the first feature and the second feature, and determines a sleep stage based on the learned determination criterion.

[0082] The data analysis unit (103) can verify the determination criteria by learning the brain wave and determination criteria that classify the sleep stage into REM (rapid eye movement) sleep stage and 1st to 3rd sleep stage according to the sleep depth for the biometric data using artificial intelligence.

[0083] The adhesive constituting the flexible electrode may have a mass ratio of tannic acid and sorbitol of 1:0.1 to 1:9, and the conductive polymer thin film may be any one of PEDOT:PSS / p-MIM:TFSI, PEDOT:PSS / EMIM:TFSI, and PEDOT:PSS / Li:TFSI.

[0084] For example, when the mass ratio of tannic acid and sorbitol is about 1:0.6 to about 1:9, or about 1:0.67 to about 1:9, the crack onset strain may be about 30% or more, resulting in high elasticity.

[0085] The thickness of the stretchable film can be from about 1 nm to about 10,000 nm, the thickness of the stretchable film can be from about 1 nm to about 10,000 nm, from about 1 nm to about 5,000 nm, from about 1 nm to about 1,000 nm, from about 100 nm to about 10,000 nm, from about 100 nm to about 5,000 nm, or from about 100 nm to about 1,000 nm.

[0086] The crack onset strain of the flexible film can be about 1% or more, about 10% or more, about 20% or more, about 30% or more, about 40% or more, about 50% or more, about 60% or more, about 70% or more, about 80% or more, about 90% or more, about 100% or more, about 110% or more, or about 120% or more.

[0087] When the crack initiation strain of the flexible film is about 10% or more, it can have an appropriate function when used as a medical device electrode.

[0088] The crack initiation strain of the flexible film can be appropriately adjusted and used depending on the application.

[0089] Accordingly, the present invention utilizes a flexible electrode that adheres well to the skin while being thin and elastic, minimizing foreign body sensation, to track multi-mode biosignals in real time and analyze the user's sleep stage, thereby enabling long-term and stable sleep and health monitoring in daily life.

[0090] FIG. 2a and FIG. 2b are drawings illustrating a sleep quality analysis system using a wearable device utilizing a flexible electrode according to one embodiment of the present invention.

[0091] FIG. 2a illustrates a case where a sleep stage and sleep quality analysis system using a wearable device utilizing a flexible electrode according to one embodiment of the present invention is configured with a wearable device and a user terminal device, and the user terminal device performs the role of the sleep quality analysis device described in FIG. 1.

[0092] Referring to FIG. 2a, a sleep quality analysis system (200) using a wearable device utilizing a flexible electrode according to one embodiment of the present invention is composed of a user terminal device (201) and a wearable device (202).

[0093] The wearable device (202) can collect biometric data including at least one of EEG, EOG, PPG, and EMG based on the measurement control processing of the user terminal device (201) and transmit the collected data to the user terminal device (201).

[0094] A separate device equipped with an LED and a photodiode to measure the PPG signal can be attached to the auricle or earlobe and can communicate with the user terminal device (201) as an independent wearable device.

[0095] The sleep quality analysis system (200) is manufactured in a wearable device (202) in a manner that electrodes can be attached to exposed skin to ensure convenience of wearing, and a signal measured by the wearable device (202) can be transmitted to a user terminal device (201) via wireless communication.

[0096] FIG. 2b illustrates an embodiment of a sleep quality analysis system using a wearable device utilizing a flexible electrode according to an embodiment of the present invention, which is composed of a wearable device, a user terminal device, an artificial intelligence server, and an administrator terminal device, and in which the artificial intelligence server performs the role of analyzing sleep stages among the roles of the sleep quality analysis device described in FIG. 1.

[0097] Referring to FIG. 2b, a sleep quality analysis system (210) using a wearable device utilizing a flexible electrode according to one embodiment of the present invention is composed of a wearable device (212), a user terminal device (211), an artificial intelligence server (213), and an administrator terminal device (214).

[0098] For example, a wearable device (212) can be worn by a user and measure biometric data for analyzing the user's sleep state by utilizing flexible electrodes attached to the user.

[0099] The wearable device (212) can collect biometric data including at least one of EEG, EOG, PPG, and EMG based on measurement control processing of the user terminal device (211) and transmit the collected data to the user terminal device (211).

[0100] According to one embodiment of the present invention, a user terminal device (211) can transmit a measurement control signal for controlling measurement and transmission of biometric data to a wearable device and collect biometric data from the wearable device.

[0101] For example, the artificial intelligence server (213) may use artificial intelligence to analyze biometric data collected from a wearable device (212) to determine a sleep stage indicating the user's sleep quality, and transmit the determined sleep stage to the user terminal device (211) and the administrator terminal device (214).

[0102] For example, the flexible electrode comprises a stretchable film based on a conductive polymer film modified with an adhesive and an ionic liquid in which tannic acid and sorbitol are mixed based on a predetermined mass ratio.

[0103] Additionally, flexible electrodes can be attached to the user's face and around the head to measure biometric data.

[0104] For example, the administrator terminal device (214) may include a medical terminal device that makes judgments regarding the user's sleep state or a terminal device located in a management facility such as a hospital.

[0105] The sleep quality analysis system (200) or sleep quality analysis system (210) allows general users who are interested in sleep to evaluate their own sleep quality and monitor whether the quality of sleep is improving through exercise or hobbies.

[0106] In addition, if the sleep quality analysis system (200) or the sleep quality analysis system (210) secures sufficient accuracy in determining sleep stages, it can replace polysomnography and support sleep stage analysis in a comfortable environment at home.

[0107] Sleep stages are broadly divided into wakefulness, REM sleep, and non-REM sleep.

[0108] Non-REM sleep is divided into stages N1, N2, and N3. Each stage of sleep, including REM sleep, performs unique functions such as memory storage, cognitive consolidation, and emotional processing.

[0109] When you sleep, the cycle of each stage repeats, and you may wake up in between. The quality of your sleep can be determined by how much of each stage of sleep is distributed throughout the entire sleep.

[0110] Accordingly, the present invention can provide a sleep quality analysis device, a sleep quality analysis method, and a sleep quality analysis system that precisely analyze and determine sleep stages by analyzing electroencephalogram (EEG) data, electrooculography (EOG) data, electromyogram (EMG) data, photoplethysmography (PPG), and electrocardiogram (ECG) data collected from a wearable device using an artificial intelligence algorithm.

[0111] FIGS. 3 to 5 are drawings explaining a method for attaching a flexible electrode to a measurement target according to one embodiment of the present invention.

[0112] FIG. 3 illustrates a location where a flexible electrode according to one embodiment of the present invention should be attached to a subject to measure brain wave data related to brain waves.

[0113] Referring to Fig. 3, the side portion (300) and the upper portion (310) of the head of the subject of measurement are shown.

[0114] In the case of polysomnography equipment, electrodes must be attached using adhesive (paste) to areas with hair, such as F3, F4, C3, C4, O1, and O2, so it can be very difficult to attach the electrodes to the same locations at home by yourself.

[0115] The flexible electrode used according to one embodiment of the present invention can be attached to a location where it can be easily attached without removing hair, such as F7 and F8.

[0116] Since F7 and F8 are located relative to the forehead, it is believed that even inexperienced users will be able to easily attach the electrodes to the correct locations by using a structure such as a mask.

[0117] For example, the first attachment location may correspond to F7 and F8, and the fifth attachment location may correspond to A1 and A2 identified in the upper surface portion (310).

[0118] Figure 4 illustrates a method for attaching a flexible electrode to a measurement subject according to one embodiment of the present invention.

[0119] Referring to FIG. 4, in step (S401), a mask pack structure (410) to which a flexible electrode (411) is attached and a user (400) as a measurement subject are prepared.

[0120] In step (S402), the mask pack structure (410) is attached to the face of the user (400), and the mask pack structure (410) is worn by the user by aligning major areas such as the eyes, nose, and mouth through the perforated locations of the mask pack structure (410).

[0121] When the flexible electrode (411) with adhesiveness is attached to the skin in step (S403), the mask pack structure (410) is removed, and the wearable measuring device (420) is connected to the flexible electrode (411).

[0122] FIG. 5 more specifically illustrates and explains a configuration in which a flexible electrode according to one embodiment of the present invention is positioned on a mask pack structure to be attached to the face of a subject of measurement.

[0123] Referring to FIG. 5, a mask pack structure (500) for attaching a flexible electrode according to one embodiment of the present invention is illustrated.

[0124] A plurality of flexible electrodes are positioned in the mask pack structure (500), and the plurality of flexible electrodes include a first flexible electrode (510), a second flexible electrode (511), a third flexible electrode (512), and a fourth flexible electrode (513).

[0125] The first flexible electrode (510) collects electroencephalogram (EEG) data among biometric data.

[0126] The second flexible electrode (511) collects electrooculography (EOG) data among the biometric data.

[0127] The third flexible electrode (512) collects electromyogram (EMG) data among biometric data.

[0128] The fourth flexible active (513) is used to collect reference potential data of biometric data and eliminate the common mode of each biometric data.

[0129] The first flexible electrode (510) is attached to a first attachment location corresponding to the tip of the two eyebrows on the upper part of the user's face.

[0130] The second flexible electrode (511) is attached to the second attachment location corresponding to two parts of the user's face around the eyes.

[0131] The third flexible electrode (512) is attached to the third attachment location corresponding to two parts of the user's face, namely, the cheek and chin area.

[0132] The fourth flexible electrode (513) is attached to the fourth attachment location corresponding to the area between the eyebrows on the user's face.

[0133] The first flexible electrode (510), the second flexible electrode (511), the third flexible electrode (512), and the fourth flexible electrode (513) are connected to a wearable device after the mask pack structure is removed, and measure biometric data according to movement of the attached facial area or brain movement, and transmit the measured biometric data to the connected wearable device.

[0134] For example, a fifth flexible electrode (not shown) can be directly attached by the user to the mastoid position behind the user's ear without using a mask pack structure.

[0135] Here, the positions of the top projections correspond to A1 and A2 based on the upper surface (310) of Fig. 3, and the fifth flexible electrode can be attached to the corresponding positions and then connected to the wearable device.

[0136] Figure 6 is a drawing explaining the structure of a flexible electrode according to one embodiment of the present invention.

[0137] Figure 6 illustrates components constituting a flexible electrode according to one embodiment of the present invention.

[0138] Referring to FIG. 6, a flexible electrode (600) according to one embodiment of the present invention may include an insulating tape layer (601), a conductive tape layer (602), a wire (603) connected to a wearable device, a flexible thin film layer (604) including an adhesive and a polymer thin film, a SEBS (styrene ethylene butylene styrene) substrate (605), and an adhesive layer (606) for attaching the SEBS substrate.

[0139] The flexible electrode (600) is a flexible electrode that can be attached to the skin, and can be an electrode that not only has excellent conductivity but is also transparent and aesthetically pleasing.

[0140] The flexible electrode (600) can implement signal characteristics superior to those of a dry electrode and exhibit performance equivalent to that of a wet electrode.

[0141] According to one embodiment of the present invention, the mass ratio of tannic acid and sorbitol of the stretchable thin film constituting the flexible electrode (600) is about 1:0.1 to about 1:3, about 1:0.1 to about 1:2, about 1:0.1 to about 1:1.5, about 1:0.1 to about 1:1, about 1:0.1 to less than 1:1, about 1:0.1 to about 1:0.9, about 1:0.1 to about 1:0.8, about 1:0.1 to about 1:0.7, about 1:0.1 to about 1:0.67, about 1:0.11 to about 1:3, about 1:0.11 to about 1:2, about 1:0.11 to about 1:1.5, about 1:0.11 to about 1:1, about 1:0.11 to Less than 1:1, about 1:0.11 to about 1:0.9, about 1:0.11 to about 1:0.8, about 1:0.11 to about 1:0.7, about 1:0.11 to about 1:0.67, about 1:0.2 to about 1:3, about 1:0.2 to about 1:2, about 1:0.2 to about 1:1.5, about 1:0.2 to about 1:1, about 1:0.2 to less than 1:1, about 1:0.2 to about 1:0.9, about 1:0.2 to about 1:0.8, about 1:0.2 to about 1:0.7, about 1:0.2 to about 1:0.67, about 1:0.25 to about 1:3, about 1:0.25 to about 1:2, about 1:0.25 to about 1:1.5, about 1:0.25 to about 1:1, about 1:0.25 to less than 1:1, about 1:0.25 to about 1:0.9, about 1:0.25 to about 1:0.8, about 1:0.25 to about 1:0.7, about 1:0.25 to about 1:0.67, about 1:0.3 to about 1:3, about 1:0.3 to about 1:2, about 1:0.3 to about 1:1.5, about 1:0.3 to about 1:1, about 1:0.3 to less than 1:1, about 1:0.3 to about 1:0.9, about 1:0.3 to about 1:0.8, about 1:0.3 to about 1:0.7, about 1:0.3 to about 1:0.67, about 1:0.35 to about 1:3, about 1:0.35 to about 1:2, about 1:0.35 to about 1:1.5, about 1:0.35 to about 1:1, about 1:0.35 to less than 1:1, about 1:0.35 to about 1:0.9, about 1:0.35 to about 1:0.8, about 1:0.35 to about 1:0.7, about 1:0.35 to about 1:0.67, about 1:0.4 to about 1:3, about 1:0.4 to about 1:2, about 1:0.4 to about 1:1.5, about 1:0.4 to about 1:1, about 1:0.4 to less than 1:1, about 1:0.4 to about 1:0.9, about 1:0.4 to about 1:0.8, about 1:0.4 to about 1:0.7, about 1:0.4 to about 1:0.67, about 1:0.43 to about 1:3, about 1:0.43 to about 1:2, about 1:0.43 to about 1:1.5, about 1:0.43 to about 1:1, about 1:0.43 to less than 1:1, about 1:0.43 to about 1:0.9, about 1:0.43 to about 1:0.8, about 1:0.43 to about 1:0.7, about 1:0.43 to about 1:0.67, about 1:0.45 to about 1:3, about 1:0.45 to about 1:2, about 1:0.45 to about 1:1.5, about 1:0.45 to about 1:1, about 1:0.45 to less than 1:1, about 1:0.45 to about 1:0.9, about It may be, but is not limited to, 1:0.45 to about 1:0.8, about 1:0.45 to about 1:0.7, or about 1:0.45 to about 1:0.67.

[0142] In one embodiment of the present invention, the electrode thin film contains tannic acid and sorbitol in an appropriate ratio, thereby simultaneously resolving the disadvantage of low elasticity of tannic acid and the disadvantage of low adhesiveness due to hygroscopicity of sorbitol, and can have high mechanical elasticity, high adhesiveness, and stability in air.

[0143] The conductive polymer thin film is PEDOT:PSS, and the ionic liquid may contain a methylimidazolium cation and an anion of TFSI (trifluoromethanesulfonimide) or TCB (tetracyanoborate).

[0144] Tannic acid (TA) and d-sorbitol were mixed according to mass fraction so that the total mass of TA and d-sorbitol was 0.4 g. The mass fraction of each component increased by 10% from 0 to 100%.

[0145] Afterwards, 1 mL of deionized water was added to the mixture and stirred using a vortex until completely dissolved to prepare a tannic acid:d-sorbitol solution.

[0146] The mass fractions of tannic acid and d-sorbitol in each solution; and the mass ratio of d-sorbitol to tannic acid (mass of sorbitol / mass of tannic acid) calculated under each condition can be summarized in Table 1 below.

[0147] Mass fraction of sample tannic acid Mass fraction of sorbitol Mass of sorbitol / Mass of tannic acid 1100 20.9 0.10.11 30.8 0.20.25 40.7 0.30.43 50.60.40.67 60.50.5 170.40.6 1.5 80.30.72 33 90.20.84 100.10.99 110 1-

[0148] In the production of SEBS (styrene-ethylene-butylene-styrene) substrates, SEBS was dissolved in toluene at a concentration of 300 mg ml-1 to prepare an SEBS solution.

[0149] A flexible SEBS substrate is manufactured by spin-coating and heat-treating (70°C, 30 minutes) a SEBS solution on glass treated with a perfluorodecyltrichlorosilane (FDTS) self-assembled monolayer.

[0150] Tannic acid: d-sorbitol thin film was fabricated by spin-coating a tannic acid: d-sorbitol solution on a SEBS substrate pretreated with UV-ozone for 1 hour. In one embodiment, the thin film was formed using a spin-coating method, but any general solution process can be used without limitation.

[0151] For example, spray coating, which is a continuous process during the solution process, can be used.

[0152] A tannic acid:d-sorbitol adhesive film is formed on a PEDOT:PSS / zonyl / ethylene glycol (EG) electrode.

[0153] In the preparation of PEDOT:PSS:Zonyl FS-300:ethylene glycol solution, 10 wt% of Zonyl FS-300 and 5 wt% of ethylene glycol were mixed with the PEDOT:PSS solution (CLEVIOSTM PH 1000 grade, Heraeus Inc.) and stirred for 1 hour using a vortexer.

[0154] A stretchable SEBS substrate was fabricated and pretreated with UV-ozone for 1 hour. A PEDOT:PSS:Zonyl FS-300:ethylene glycol solution was spin-coated onto the substrate and heat-treated (70°C, 15 minutes) to fabricate a PEDOT:PSS:Zonyl FS-300:ethylene glycol transparent electrode thin film. Subsequently, a tannic acid:d-sorbitol solution was spin-coated onto the thin film, thereby fabricating a PEDOT:PSS-based dry transparent electrode thin film with adhesiveness and stretchability in a double-layer structure.

[0155] p-MIM:TFSI was added to deionized water at a concentration of 33.8 mg mL-1 and stirred for 10 minutes to prepare a p-MIM:TFSI solution. Thereafter, a PEDOT:PSS (CLEVIOSTM PH 1000grade, Heraeus Inc.) solution and the above solution were mixed at a mass ratio of PEDOT:PSS / p-MIM:TFSI of 1:1.3 and stirred with a vortex for 4 hours to prepare a PEDOT:PSS / p-MIM:TFSI solution.

[0156] Tannic acid: d-sorbitol can be mixed so that the mass ratio is 1:1.695, and 2.5 mL of deionized water is added to prepare a tannic acid: d-sorbitol solution.

[0157] A PEDOT:PSS:p-MIM:TFSI transparent electrode thin film was fabricated by spin-coating and heat-treating (70°C, 15 min) a PEDOT:PSS / p-MIM:TFSI solution on a substrate.

[0158] p-MIM:TFSI can be removed by washing the thin film by placing acetonitrile on it for 10 seconds and then rotating the substrate to remove the solvent.

[0159] Afterwards, a tannic acid:d-sorbitol solution is placed on the thin film for 60 seconds and then spin-coated to produce a tannic acid:d-sorbitol adhesive thin film on the PEDOT:PSS / p-MIM:TFSI thin film.

[0160] The fabricated thin film can be stored in a vacuum desiccator for at least 1 hour to completely remove any remaining solvent.

[0161] A flexible electrode (600) is configured and a flexible thin film layer (604) for measuring biosignals is described in more detail using FIGS. 7 to 12.

[0162] FIG. 7 is a drawing illustrating an optical microscope image of an adhesive constituting a stretchable thin film of a flexible electrode according to one embodiment of the present invention.

[0163] Referring to FIG. 7, an optical microscope image (700) shows the frequency of occurrence of cracks according to the surface morphology and the mass ratio of tannic acid:d-sorbitol after taking an optical microscope image of a tannic acid:d-sorbitol thin film manufactured on a SEBS substrate.

[0164] When the mass ratio of tannic acid:d-sorbitol is 0.9:0.1 to 0.7:0.3, cracks exist, but the frequency of crack occurrence per unit area is significantly reduced compared to a film that does not contain sorbitol, confirming that the elasticity of the film increases as the mass ratio of d-sorbitol increases.

[0165] FIG. 8 is a drawing explaining the crack initiation strain of a thin film related to an adhesive constituting a flexible thin film of a flexible electrode according to one embodiment of the present invention.

[0166] Referring to FIG. 8, the graph (800) shows that when the mass ratio of tannic acid and d-sorbitol is 0.6:0.4, 0.5:0.5, 0.4:0.6, 0.3:0.7, 0.2:0.8, and 0.1:0.9, respectively, the crack initiation strain of the thin film is approximately 50% or more, confirming that the elasticity is very excellent.

[0167] In particular, when the mass ratio of tannic acid and d-sorbitol is 0.4:0.6 and 0.3:0.7, the crack initiation strain of the thin film is approximately 120% or more, confirming that it has very high elasticity.

[0168] Graph (810) shows that when the mass ratio of tannic acid:d-sorbitol is 0.6:0.4, the crack initiation strain of the thin film is about 50% or more at spin coating speeds of 1000 rpm, 2000 rpm, 3000 rpm, 4000 rpm, and 5000 rpm, respectively, confirming that the thin film has elasticity regardless of the spin coating speed and thickness, and at this time, the thickness of the tannic acid:d-sorbitol thin film is about 300 nm to 1,000 nm.

[0169] FIG. 9 and FIG. 10 are drawings explaining the adhesive strength of an adhesive constituting a stretchable thin film of a flexible electrode according to one embodiment of the present invention.

[0170] Figure 9 illustrates the results of measuring the adhesive strength of an adhesive constituting a flexible thin film of a flexible electrode according to one embodiment of the present invention.

[0171] Referring to FIG. 9, image (900) illustrates a 90° peel test according to ASTM D3330 standard using a universal material testing machine (AGX-500N, Shimadzu Ltd.) to measure the adhesive strength of a tannic acid:d-sorbitol thin film manufactured on a SEBS substrate.

[0172] Image (901) illustrates a 180° peel test according to ASTM D3330 standard using a universal material testing machine (AGX-500N, Shimadzu Ltd.) to measure the adhesive strength of a tannic acid:d-sorbitol thin film manufactured on a SEBS substrate.

[0173] Graph (910) shows the adhesion force [N / cm] according to the mass ratio of tannic acid:d-sorbitol (tannic acid:d-sorbitol).

[0174] When the mass ratio of tannic acid:d-sorbitol is 0.9:0.1, 0.8:0.2, 0.7:0.3, and 0.6:0.4, it is confirmed that the adhesive strength is 0.4 N / cm or more.

[0175] In addition, considering that the decrease in adhesive strength of tannic acid is generally due to cracking, it can be confirmed that the elasticity is improved at the mass ratio of tannic acid:d-sorbitol of 0.9:0.1, from the improved adhesive strength.

[0176] When the mass ratio of d-sorbitol is 0.5 or higher, it was confirmed that hygroscopicity increases and adhesive strength decreases. However, the adhesive strength may vary depending on the environment (relative humidity) in which the experiment is conducted, and as the relative humidity decreases, the proportion of d-sorbitol in the thin film that can have adhesive strength may increase.

[0177] FIG. 10 illustrates additional experimental results related to measuring the adhesive strength of an adhesive constituting a stretchable thin film of a flexible electrode according to one embodiment of the present invention.

[0178] Referring to FIG. 10, the image (1000) confirms that when a tannic acid:d-sorbitol thin film having a mass ratio of 0.6:0.4 is attached to the body skin, a weight having a mass of 100 g can be lifted using only the adhesive force of the thin film.

[0179] Graph (1010) confirmed that when the mass ratio of tannic acid:d-sorbitol was 0.6:0.4, the adhesive strength was 0.4 N / cm or more at spin coating speeds of 1000 rpm, 2000 rpm, 3000 rpm, 4000 rpm, and 5000 rpm, respectively. In particular, it was confirmed that as the spin coating speed of the thin film decreased, the thickness of the thin film increased, thereby increasing the adhesive strength.

[0180] FIGS. 11A to 11D are drawings explaining the strain and elasticity of a flexible thin film of a flexible electrode according to one embodiment of the present invention.

[0181] Figure 11a shows the strain of the elastic thin film of the flexible electrode according to one embodiment of the present invention.

[0182] Referring to FIG. 11a, the optical image (1100) may be an OM image of a PEDOT:PSS / ionic additive / SEBS thin film obtained at various strains.

[0183] Optical images (1100) then show the results of investigations into the elasticity of these films under increasing tensile strain using an optical microscope.

[0184] In this experiment, PEDOT:PSS thin films with or without ionic additives were spin-cast onto styrene-ethylene-butylene-styrene (SEBS) thermoplastic elastomer substrates and then stretched to various strains (ε = 10%, 20%, 30%, 40%, 50%) to show the change in strain, as shown in the optical images (1100).

[0185] Figure 11b shows the average strain of the elastic thin film of the flexible electrode according to one embodiment of the present invention.

[0186] Referring to FIG. 11b, the graph (1110) confirms that the PEDOT:PSS / p-MIM:TFSI thin film has a much higher average strain (εc) of more than 50%.

[0187] This confirms that it is superior to the PEDOT:PSS / EMIM:TFSI (εc = 13%) and PEDOT:PSS / Li:TFSI (εc = 27%) thin films.

[0188] Figure 11c illustrates simulation results for the mechanical properties of a stretchable thin film of a flexible electrode according to one embodiment of the present invention.

[0189] Referring to FIG. 11c, graph (1120) shows that the PEDOT:PSS / p-MIM:TFSI thin film is relatively robust to strain related to mechanical properties.

[0190] FIG. 11d shows the elastic modulus (E) and tensile strength (S) along with the strain (εf) through simulation of the elastic thin film of the flexible electrode according to one embodiment of the present invention.

[0191] Referring to FIG. 11d, graph (1130) represents the elastic modulus, graph (1131) represents the tensile strength, and graph (1132) represents the strain.

[0192] PEDOT:PSS standalone films prepared with ionic additives exhibit reduced elastic modulus (E) and tensile strength (S) and improved strain at break (εf ).

[0193] In particular, the PEDOT:PSS / p-MIM:TFSI standalone film showed the lowest E (= 10 MPa) and S (= 5 MPa), which are 39 times and 8 times lower, respectively, than the bare PEDOT:PSS standalone film (E = 388 MPa, S = 38 MPa).

[0194] FIG. 12 is a drawing explaining the improvement in elasticity of the elastic film of a flexible electrode according to one embodiment of the present invention.

[0195] Figure 12 illustrates a process for improving the elasticity of a flexible thin film of a flexible electrode according to one embodiment of the present invention.

[0196] Referring to FIG. 12, ion exchange between PEDOT:PSS and p-MIM:TFSI occurs in step (1200), PEDOT:PSS nanofibrils are formed in step (1201), and hydrogen bonding occurs in step (1202), thereby improving elasticity.

[0197] That is, the enhanced elasticity of the PEDOT:PSS / p-MIM:TFSI film can be achieved through the strong hydrogen bonding of the PEODT+-TFSI--p-MIM+-PSS- network formed by the favorable ion exchange between PEDOT:PSS and p-MIM:TFSI.

[0198] FIG. 13 is a drawing illustrating a cytotoxicity analysis of a flexible thin film of a flexible electrode according to an embodiment of the present invention.

[0199] Figure 13 illustrates simulation results for cytotoxicity analysis of a flexible thin film of a flexible electrode according to one embodiment of the present invention.

[0200] Referring to FIG. 13, the graph (1300) shows that the stretchable thin film of the flexible electrode according to one embodiment of the present invention is a material suitable for attachment to a living body.

[0201] The cytotoxicity of PEDOT:PSS / p-MIM:TFSI thin films was measured and compared by testing the viability of fibroblast cells, which play an important role in the body and perform various functions.

[0202] For comparison, polyethyleneimine (PEI) and d-sorbitol were used as positive and negative controls, respectively.

[0203] Additionally, dimethylsulfoxide (DMSO), which is known to improve the electrical conductivity of PEDOT:PSS but is toxic, was selected as an additional positive control for the PEDOT:PSS / DMSO thin films.

[0204] Additionally, the cytotoxicity of bare PEDOT:PSS and SEBS substrates is investigated to confirm the safety of PEDOT:PSS / p-MIM:TFSI / SEBS electrodes for biosignal sensors.

[0205] In graph (1300), cell viability of 15% and 99% for PEI and d-sorbitol, respectively, demonstrates the accuracy of the cytotoxicity test.

[0206] It was confirmed that the bare PEDOT:PSS thin film and SEBS substrate did not exhibit cytotoxicity, with cell viability exceeding 90%.

[0207] Considering that the toxicity threshold is ~80%, PEDOT:PSS / DMSO films were toxic based on a G3% decrease in cell viability.

[0208] In particular, the fact that the cell viability was less than 80% even after 8 dilutions indicates the high toxicity of DMSO extracted from the PEDOT:PSS / DMSO thin film.

[0209] In contrast, the PEDOT:PSS / p-MIM:TFSI thin film showed a high cell viability of over 95%.

[0210] These results demonstrate the usefulness of PEDOT:PSS / p-MIM:TFSI thin films fabricated on SEBS substrates as stretchable transparent electrodes applicable to human epidermis for biosignal monitoring.

[0211] FIGS. 14a to 15b are drawings explaining the results of biometric data measurement of a flexible electrode according to one embodiment of the present invention.

[0212] Figure 14a illustrates voltage changes in bio-data measurement results of a flexible electrode according to one embodiment of the present invention.

[0213] Referring to FIG. 14a, the graph (1400) shows that the PQRST wave is well confirmed in the PEDOT:PSS / p-MIM:TFSI thin film for measuring signals related to bio-data such as ECG signals among the materials constituting the elastic thin film.

[0214] In particular, graph (1400) shows that the noise is lower than that obtained using PEDOT:PSS / EMIM:TFSI and PEDOT:PSS / Li:TFSI electrodes.

[0215] PEDOT:PSS / EMIM:TFSI electrodes generate signals with unclear PQRST waveforms due to high background noise.

[0216] The signals measured using the PEDOT:PSS / Li:TFSI electrode showed less noise than those obtained with the PEDOT:PSS / EMIM:TFSI electrode, but the P wave was less frequently detected.

[0217] Figure 14b illustrates an impedance change in a bio-data measurement result of a flexible electrode according to one embodiment of the present invention.

[0218] Referring to FIG. 14b, graph (1410) shows that the improved electrode / skin interface and resulting reduced contact resistance were confirmed through impedance measurements, with the lowest impedance occurring with the PEDOT:PSS / p-MIM:TFSI electrode using a thin film of indium tin oxide (instead of human skin).

[0219] Figure 14c illustrates simulation results for the mechanical reliability of a flexible electrode according to one embodiment of the present invention.

[0220] Referring to FIG. 14c, the graph (1420) shows the results of an investigation into the mechanical reliability of the PEDOT:PSS / p-MIM:TFSI electrode by comparing ECG signals obtained under various bending conditions (angle = 0°, G0°, 120°) of the index finger to which the PEDOT:PSS / p-MIM:TFSI electrode was attached.

[0221] The ECG signal shows a clear PQRST wave regardless of the bending angle due to the high elasticity of the PEDOT:PSS / p-MIM:TFSI electrode.

[0222] Additionally, according to graph (1421), it can be confirmed that the PEDOT:PSS / p-MIM:TFSI electrode can collect ECG signals stably, outperforming other electrodes, even after repeatedly bending the index finger 3000 times.

[0223] FIG. 15a illustrates a measurement result of data based on an EOG signal in relation to a biometric data measurement result of a flexible electrode according to one embodiment of the present invention.

[0224] Referring to FIG. 15a, the graph (1500) shows the measurement results of data based on the EOG signal.

[0225] FIG. 15b illustrates a measurement result of data based on an EMG signal in relation to a biometric data measurement result of a flexible electrode according to one embodiment of the present invention.

[0226] Referring to FIG. 15b, the graph (1510) shows the measurement results of data based on EMG signals.

[0227] The circuitry used to measure EOG and EMG signals is similar to the circuitry used for the ECG measurement above, but the amplification factor and cutoff frequency of the active filter optimized for EOG and EMG measurements are different.

[0228] EOG measures the difference in electrical potential induced by the eye's polarity. To obtain an EOG signal, two electrodes are placed near the eye, diagonally across the eye, detecting both vertical and horizontal movements.

[0229] As can be seen in the graph (1500), the flexible electrodes are shown to acquire EOG signals according to various eye movements up, down, left and right.

[0230] As shown in the graph (1510), the flexible electrode detects the difference in potential generated in the muscle fibers and shows the change in the electromyography signal according to the movement of the muscle.

[0231] Assuming that a person experiences rapid eye movement sleep, these EMG signals can be used together with EOG signals to map real-time sleep stages.

[0232] FIG. 16 is a diagram explaining a sleep stage determined by a data analysis unit according to one embodiment of the present invention.

[0233] Referring to FIG. 16, a conceptual diagram (1600) is provided to explain the sleep structure in relation to the sleep stage determined by the data analysis unit according to one embodiment of the present invention.

[0234] Human sleep can basically be divided into two types: non-rapid eye movement (NREM) sleep and rapid eye movement (REM) sleep.

[0235] Non-REM sleep can be divided into N1 sleep (stage 1), N2 sleep (stage 2), and N3 sleep (stage 3) depending on the depth of sleep.

[0236] In relation to the present invention, the data analysis unit can use sleep spindles and slow wave sleep as measured brain wave indicators to determine sleep stages.

[0237] Here, sleep spindles are bursts of neural oscillatory activity with a frequency of 10 to 16 Hz that last at least 0.5 seconds and are generated by the interaction between the thalamic reticular nucleus (TRN) and other thalamic nuclei during stage 2 of non-REM sleep. Sleep spindles are observed in mammalian non-REM sleep, and their functions are known to control both sensory processing and long-term memory consolidation. The formation of sleep spindles is known to be a waveform generated when signals are transmitted from one part of the cerebral cortex to another.

[0238] Slow wave sleep is the deepest stage of non-REM sleep and is characterized by large delta waves in the brain waves. It is an important stage for memory consolidation into long-term memory.

[0239] In other words, the concept diagram (1600) indicates that the sleep stage determined by the data analysis unit is composed of multiple cycles and changes over time, and that the change in the sleep stage can be analyzed and determined based on biological data.

[0240] FIG. 17 is a diagram illustrating a method for increasing the quality of analysis data based on artificial intelligence learning in a data analysis unit according to one embodiment of the present invention.

[0241] Referring to FIG. 17, in a data analysis unit according to one embodiment of the present invention, an artificial intelligence algorithm (1700) implements sleep signal noise removal and signal quality amplification using a convolutional neural network (CNN).

[0242] In the first layer, such as the artificial intelligence algorithm (1700), a filter of size 3*3*1 may be used to create 64 feature maps and an activation function may be included.

[0243] Activation functions can be applied to each layer of the network to perform the function of making each input have a complex non-linear relationship.

[0244] Activation functions that can be used include the sigmoid function, tanh function, rectified linear unit (ReLU), and leaky ReLU, which can transform inputs into normalized outputs.

[0245] In this invention, the explanation focuses on the case where ReLU is used.

[0246] As an example, the learning unit (131) may perform learning by using 64 filters of size 3*3*64 for the 2nd to 17th layers, adding a batch normalization layer between the convolution layer and ReLU, and using one filter of size 3*3*64 for the last layer to create an output signal with noise removed.

[0247] Meanwhile, the noise removal and signal quality amplifier (1311) can use an algorithm that increases the sampling rate as an example of preprocessing for signal quality amplification. That is, a sleep signal acquired at 100 Hz can be upsampled and amplified to 200 Hz and used. In this case, the control unit learns the network parameters by modifying the learning data (y) as follows.

[0248] y =U(D(x))

[0249] At this time, function D(x) may be a down-sampling function, and U(x) may be an up-sampling function.

[0250] The data analysis unit uses learned noise removal and signal quality amplification to generate a sleep signal by removing noise from the actually detected brain wave signal and amplifying the signal quality.

[0251] It can be applied not only to brainwave signals but also to other biosignals other than brainwave signals.

[0252] FIG. 18 is a drawing illustrating a procedure for performing a sleep stage determination algorithm in a data analysis unit according to one embodiment of the present invention.

[0253] Figure 18 illustrates a procedure for performing a sleep stage determination algorithm in a data analysis unit according to one embodiment of the present invention.

[0254] Referring to Fig. 18, according to the sleep stage determination algorithm (1800), the data analysis unit can learn the determination criteria using not only the first detection signal (S1) generated by detecting brain wave signals, but also the second detection signal (S2) generated by detecting other biosignals.

[0255] At this time, the first detection signal (S1) and the second detection signal (S2) can each undergo an indirect learning process to extract features.

[0256] The first process (A1) can learn a filter to extract features from brainwave signals, and the second process (A2) can learn a filter to extract features from other biosignals.

[0257] The first process (A1) and the second process (A2) may be composed of a convolutional neural network (CNN) and may be formed with a multi-channel neural network structure.

[0258] For example, when using two convolutional neural network (CNN) channels, brainwave signals and electrocardiogram signals can be input respectively.

[0259] The data analysis unit can learn to encode temporal information, such as transition rules of sleep stages, from the first feature or the first feature and the second feature extracted from the previous stage through the third process (A3).

[0260] The data analysis unit consists of two BLSTM (Bidirectional Long Short Term Memory) layers, and can add temporal information to the first and second features learned from the first process (A1) and the second process (A2) through short connections.

[0261] The sleep stage determination algorithm generated by the data analysis department, the determination criteria, can be stored in advance.

[0262] The data analysis unit can determine the user's current sleep stage based on the first detection signal and the second detection signal based on the biometric data provided from the wearable device using the above-mentioned determination criteria.

[0263] FIG. 19 is a drawing explaining a method for analyzing sleep quality using a wearable device utilizing a flexible electrode according to one embodiment of the present invention.

[0264] FIG. 19 illustrates a procedure for performing a sleep quality analysis method using a wearable device utilizing a flexible electrode according to an embodiment of the present invention, and the sleep quality analysis method according to an embodiment of the present invention may be a sleep quality analysis method using a wearable device utilizing a flexible electrode.

[0265] Referring to FIG. 19, in step (S1901), a sleep quality analysis method according to an embodiment of the present invention transmits a measurement control signal to a wearable device.

[0266] That is, a sleep quality analysis method according to one embodiment of the present invention can transmit a measurement control signal for controlling measurement and transmission of biometric data for sleep state analysis to a wearable device worn by a user.

[0267] In step (S1902), a sleep quality analysis method according to an embodiment of the present invention collects biometric data based on a measurement control signal from a wearable device.

[0268] That is, the sleep quality analysis method according to one embodiment of the present invention can collect biometric data measured by the wearable device through flexible electrodes attached to the user from the wearable device.

[0269] For example, the flexible electrode includes a stretchable film based on a conductive polymer film modified with an adhesive and an ionic liquid in which tannic acid and sorbitol are mixed based on a preset mass ratio, and can be attached to the user's face and around the head to measure biometric data.

[0270] For example, electroencephalogram (EEG) data, electrooculography (EOG) data, and electromyogram (EMG) data can be collected from the face, and photoplethysmography (PPG) data can be collected from around the head.

[0271] In step (S1903), a sleep quality analysis method according to an embodiment of the present invention analyzes biometric data to determine a sleep stage indicating sleep quality.

[0272] That is, a sleep quality analysis method according to one embodiment of the present invention can determine a sleep stage indicating the user's sleep quality by analyzing the collected biometric data using artificial intelligence.

[0273] Accordingly, the present invention can provide a sleep quality analysis device, a sleep quality analysis method, and a sleep quality analysis system that improve user convenience through a wearable device without wires using a flexible electrode that is well attached to the skin and has elasticity to minimize foreign body sensation, and precisely analyzes and determines sleep stages without disturbing the user's sleep.

[0274] The devices described above may be implemented as hardware components, software components, and / or a combination of hardware components and software components. For example, the devices and components described in the embodiments may be implemented using one or more general-purpose computers or special-purpose computers, such as, for example, a processor, a controller, an arithmetic logic unit (ALU), a digital signal processor, a microcomputer, a field programmable array (FPA), a programmable logic unit (PLU), a microprocessor, or any other device capable of executing instructions and responding to them. The processing device may execute an operating system (OS) and one or more software applications running on the operating system. The processing device may also access, store, manipulate, process, and generate data in response to the execution of the software. For ease of understanding, the processing device is sometimes described as being used alone; however, one of ordinary skill in the art will recognize that the processing device may include multiple processing elements and / or multiple types of processing elements. For example, a processing unit may include multiple processors, or a processor and a controller. Other processing configurations, such as parallel processors, are also possible.

[0275] Software may include a computer program, code, instructions, or a combination of one or more of these, and may configure a processing device to perform a desired operation or, independently or collectively, command the processing device. The software and / or data may be permanently or temporarily embodied in any type of machine, component, physical device, virtual equipment, computer storage medium or device, or transmitted signal wave, for interpretation by the processing device or for providing instructions or data to the processing device. The software may be distributed on network-connected computer systems and stored or executed in a distributed manner. The software and data may be stored on one or more computer-readable recording media.

[0276] Although the embodiments described above have been described with limited drawings, those skilled in the art will recognize that various modifications and variations can be made based on the above description. For example, appropriate results can still be achieved even if the described techniques are performed in a different order than described, and / or components of the described systems, structures, devices, circuits, etc. are combined or combined in a different manner than described, or are replaced or substituted with other components or equivalents.

[0277] Therefore, other implementations, other embodiments, and equivalents to the claims also fall within the scope of the claims described below.

Claims

1. A measurement processing unit that transmits a measurement control signal to a wearable device worn by a user to control measurement and transmission of biometric data for sleep state analysis; A data collection unit that collects biometric data measured by the wearable device through a flexible electrode attached to the user from the wearable device; and It includes a data analysis unit that determines a sleep stage indicating the user's sleep quality by analyzing the collected biometric data with artificial intelligence, The above flexible electrode comprises a stretchable thin film based on a conductive polymer thin film modified with an adhesive and an ionic liquid in which tannic acid and sorbitol are mixed based on a preset mass ratio, and is characterized in that it is attached to the user's face and around the head to measure the biometric data. Sleep quality analysis device.

2. In paragraph 1, The flexible electrode is positioned at a first attachment location of the mask pack structure corresponding to the tip of the eyebrows above the two eyes for measuring the biometric data on the user's face, at a second attachment location of the mask pack structure corresponding to two parts around the eyes for measuring the biometric data on the user's face, at a third attachment location of the mask pack structure corresponding to two parts around the cheek and chin for measuring the biometric data on the user's face, and at a fourth attachment location of the mask pack structure corresponding to the space between the eyebrows, and when the mask pack structure is aligned and worn on the user's face based on the positions punched on the mask pack structure, it is attached to the first attachment location, the second attachment location, the third attachment location, and the fourth attachment location, and is attached to the user's face corresponding to the first attachment location, the second attachment location, the third attachment location, and the fourth attachment location, and is connected to the wearable device after the mask pack structure is removed, and transmits biometric data measured according to movement of the attached face part to the wearable device, and is attached to the mastoid of the user. It is characterized by being additionally attached to the corresponding fifth attachment location and transmitting biometric data to the wearable device. Sleep quality analysis device.

3. In paragraph 1, The above data collection unit is characterized in that it collects the bio-data including at least one of electroencephalogram (EEG) data, electrooculography (EOG) data, electromyogram (EMG) data, and photoplethysmography (PPG) data. Sleep quality analysis device.

4. In paragraph 3, The data analysis unit generates a first detection signal based on the electroencephalogram data, generates a second detection signal synchronized with the first detection signal among the safety latitude data, the electromyography data and the electrocardiogram data, extracts a first feature from the first detection signal, extracts a second feature from the second detection signal, and learns a determination criterion for determining the sleep stage using the first feature and the second feature using artificial intelligence, and determines the sleep stage based on the learned determination criterion. Sleep quality analysis device.

5. In paragraph 4, The data analysis unit is characterized in that it verifies the determination criteria by learning the brain wave and the determination criteria that classify the sleep stage into the REM (rapid eye movement) sleep stage and the first to third sleep stages for the biometric data using artificial intelligence. Sleep quality analysis device.

6. In paragraph 1, The flexible electrode is characterized by including an insulating tape layer, a conductive tape layer, an electric wire connected to the wearable device, an elastic thin film layer including the adhesive and the polymer thin film, and a SEBS (styrene ethylene butylene styrene) substrate. Sleep quality analysis device.

7. In paragraph 1, The adhesive has a mass ratio of the tannic acid and the sorbitol of 1:0.1 to 1:9, The conductive polymer thin film is characterized by being any one of PEDOT:PSS / p-MIM:TFSI, PEDOT:PSS / EMIM:TFSI, and PEDOT:PSS / Li:TFSI. Sleep quality analysis device.

8. A step of transmitting, in a measurement processing unit, a measurement control signal for controlling measurement and transmission of biometric data for sleep state analysis to a wearable device worn by a user; In the data collection unit, a step of collecting biometric data measured by the wearable device through a flexible electrode attached to the user from the wearable device; and In the data analysis unit, a step is included to determine a sleep stage indicating the user's sleep quality by performing an artificial intelligence analysis on the collected biometric data. The above flexible electrode comprises a stretchable thin film based on a conductive polymer thin film modified with an adhesive and an ionic liquid in which tannic acid and sorbitol are mixed based on a preset mass ratio, and is characterized in that it is attached to the user's face and around the head to measure the biometric data. How to analyze sleep quality.

9. A wearable device that is worn by a user and measures biometric data for analyzing the user's sleep state by utilizing flexible electrodes attached to the user; A user terminal device that transmits a measurement control signal for controlling measurement and transmission of the biometric data to the wearable device and collects the biometric data from the wearable device; and An artificial intelligence server is included that analyzes the collected biometric data using artificial intelligence to determine a sleep stage representing the user's sleep quality, and transmits the determined sleep stage to the user terminal device and the administrator terminal device. The above flexible electrode comprises a stretchable thin film based on a conductive polymer thin film modified with an adhesive and an ionic liquid in which tannic acid and sorbitol are mixed based on a preset mass ratio, and is characterized in that it is attached to the user's face and around the head to measure the biometric data. Sleep quality analysis system.

10. In paragraph 9, The flexible electrode is positioned at a first attachment location of the mask pack structure corresponding to the tip of the eyebrows above the two eyes for measuring the biometric data on the user's face, at a second attachment location of the mask pack structure corresponding to two parts around the eyes for measuring the biometric data on the user's face, at a third attachment location of the mask pack structure corresponding to two parts around the cheek and chin for measuring the biometric data on the user's face, and at a fourth attachment location of the mask pack structure corresponding to the space between the eyebrows, and when the mask pack structure is aligned and worn on the user's face based on the positions punched on the mask pack structure, it is attached to the first attachment location, the second attachment location, the third attachment location, and the fourth attachment location, and is attached to the user's face corresponding to the first attachment location, the second attachment location, the third attachment location, and the fourth attachment location, and is connected to the wearable device after the mask pack structure is removed, and transmits biometric data measured according to movement on the attached face to the wearable device, and corresponds to the mastoid of the user. It is characterized by being additionally attached to the fifth attachment location and transmitting biometric data to the wearable device. Sleep quality analysis system.

11. In the flexible electrode included in the sleep quality analysis device, An adhesive in which tannic acid and sorbitol are mixed based on a preset mass ratio; and The above tannic acid and the above sorbitol are mixed based on a preset mass ratio, and include a stretchable thin film based on a conductive polymer thin film modified with an ionic liquid, The adhesive and the elastic film are characterized in that the mass ratio of the tannic acid and the solitol is 1:0.1 to 1:

9. Flexible electrode.

12. In paragraph 11, The thickness of the adhesive is 1 nm to 10,000 nm, The thickness of the above elastic film is characterized by being 1 nm to 10,000 nm. Flexible electrode.

13. In paragraph 11, The conductive polymer thin film is characterized by being any one of PEDOT:PSS / p-MIM:TFSI, PEDOT:PSS / EMIM:TFSI, and PEDOT:PSS / Li:TFSI. Flexible electrode.

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