Apparatus and method for providing electrical stimulation to the skin based on a wearable device to relieve symptoms of alcohol intoxication

Abstract

The present disclosure relates to a device and method for providing skin electrical stimulation based on a wearable device for alleviating symptoms of alcohol addiction, comprising: a communication module that communicates with an external device; a storage module that stores at least one process for providing skin electrical stimulation to alleviate symptoms of alcohol addiction; and a control module that performs an operation to provide skin electrical stimulation to alleviate symptoms of alcohol addiction based on the at least one process, wherein the control module acquires user state information to confirm an alcohol intake state, confirms an electrical stimulation intensity, an electrical stimulation speed, and an electrical stimulation time corresponding to the alcohol intake state based on previously stored electrical stimulation information, and can apply the electrical stimulation intensity to the user's wrist at the electrical stimulation speed during the electrical stimulation time.

Description

Technology Field

[0001] The present disclosure relates to a skin electrical stimulation device and method, and more specifically, to a wearable device-based skin electrical stimulation device and method for alleviating symptoms of alcohol addiction. Background Technology

[0002] Recently, in the fields of psychiatry and rehabilitation medicine, stimulation technology has been gaining attention as an emerging technology, and technologies such as ECT (Electroconvulsive Treatment), rTMS (Repetitive Transcranial Magnetic Stimulation), Tdcs (Transcranial Direct Current Stimulation), and NMS (Neuro Magnetic Stimulation) are being developed.

[0003] The most effective ECT is a decades-old treatment technique that is very safe and effective, but it has the disadvantage of being used restrictively in patients with severe schizophrenia or suicidal thoughts because it involves strong, invasive electrical brain stimulation in the operating room.

[0004] For this reason, brain stimulation technologies such as rTMS and tDCS, which are weaker forms of the technology, have been developed, but they have the disadvantage that they are not portable due to the bulk of the device, which limits their use by patients in their daily lives.

[0005] Thus, NMS that seeks brain stimulation through wearable technology is being developed, but most research is being conducted primarily for the purpose of controlling tic symptoms of tic disorders.

[0006] In Korea, alcoholism is a disease with a very high prevalence rate of 12.2%, making it one of the most socially burdensome conditions. Although treatments for alcoholism include inpatient care, cognitive behavioral therapy, and medication, none of these are sufficiently effective, causing severe suffering not only to the patients but also to their families.

[0007] Here, among the drugs used for drug treatment, a drug used for aversion therapy was effective but was withdrawn from the market due to fatal side effects.

[0008] Therefore, there is a need to develop a technology that is portable and can recognize when a patient (user) feels a craving for alcohol or consumes alcohol, and provide a negative perception of alcohol consumption by switching to other emotions that replace the craving through unpleasant electrical stimulation or by blocking the reward effects associated with alcohol consumption. Prior art literature

[0009] Korean Patent Publication No. 10-2333280 (Registration Date: November 26, 2021) The problem to be solved

[0010] The present disclosure provides a wearable device-based skin electrical stimulation device and method for alleviating symptoms of alcohol addiction, which detects an urge to consume alcohol or an action to consume alcohol, and applies electrical stimulation to the patient's skin to a degree that can cause unpleasant emotions based on an NMS method, thereby changing the emotion (mood) or blocking the reward effect through alcohol consumption, so as to stop alcohol consumption and gradually alleviate symptoms of alcohol addiction.

[0011] Meanwhile, the present disclosure provides a wearable device-based skin electrical stimulation device and method for alleviating symptoms of alcohol addiction, configured to be easily used anywhere whenever a patient consumes alcohol through a wearable device, thereby enabling the patient to stop the act of consuming alcohol regardless of time and place, and thus improving the patient's quality of life and restoring family functions.

[0012] The problems that this disclosure aims to solve are not limited to those mentioned above, and other unmentioned problems will be clearly understood by a person skilled in the art from the description below. means of solving the problem

[0013] A skin electrical stimulation device based on a wearable device for alleviating symptoms of alcohol addiction according to one aspect of the present disclosure for achieving the technical problem described above comprises: a communication module that communicates with an external device; a storage module that stores at least one process for providing skin electrical stimulation to alleviate symptoms of alcohol addiction; and a control module that performs an operation for providing skin electrical stimulation to alleviate symptoms of alcohol addiction based on the at least one process, wherein the control module acquires user state information to confirm an alcohol intake state, confirms an electrical stimulation intensity, an electrical stimulation speed, and an electrical stimulation time corresponding to the alcohol intake state based on previously stored electrical stimulation information, and can apply the electrical stimulation intensity to the user's wrist at the electrical stimulation speed during the electrical stimulation time.

[0014] Meanwhile, a method for providing skin electrical stimulation based on a wearable device for alleviating symptoms of alcohol addiction according to one aspect of the present disclosure may include: a step of acquiring user state information; a step of confirming an alcohol intake state based on the state information; a step of confirming an electrical stimulation intensity, an electrical stimulation speed, and an electrical stimulation time corresponding to the alcohol intake state based on previously stored electrical stimulation information; and a step of applying the electrical stimulation intensity at the electrical stimulation speed to the user's wrist during the electrical stimulation time.

[0015] In addition, a computer program stored on a computer-readable recording medium for executing a method for implementing the present disclosure may be further provided.

[0016] In addition, a computer-readable recording medium for recording a computer program for executing a method for implementing the present disclosure may be further provided. Effects of the invention

[0017] According to the aforementioned means for solving the problem of the present disclosure, the patient detects an urge to consume alcohol or the act of consuming alcohol, and applies electrical stimulation to the patient's skin based on an NMS method to a degree that causes unpleasant emotions, thereby changing the emotion (mood) or blocking the reward effect through alcohol consumption, so as to stop alcohol consumption, so as to gradually alleviate symptoms of alcohol addiction.

[0018] Meanwhile, according to the present disclosure, a wearable device is configured to be easily used anywhere whenever a patient consumes alcohol, thereby enabling the cessation of alcohol consumption regardless of time and place, which improves the patient's quality of life and restores family functions.

[0019] The effects of the present disclosure are not limited to those mentioned above, and other unmentioned effects will be clearly understood by a person skilled in the art from the description below. Brief explanation of the drawing

[0020] FIG. 1 is a diagram showing the network structure of a wearable device-based service provision system for alleviating symptoms of alcohol addiction according to one embodiment of the present disclosure. FIG. 2 is a flowchart illustrating the operation of a wearable device-based service provision system for alleviating symptoms of alcohol addiction according to one embodiment of the present disclosure. FIG. 3 is a drawing showing the configuration of a wearable device-based skin electrical stimulation providing device for alleviating symptoms of alcohol addiction according to one embodiment of the present disclosure. FIG. 4 is a drawing showing the configuration of a method for providing skin electrical stimulation based on a wearable device for alleviating symptoms of alcohol addiction according to one embodiment of the present disclosure. FIG. 5 is a drawing illustrating a specific operation for acquiring state information in a method for providing skin electrical stimulation based on a wearable device for alleviating symptoms of alcohol addiction according to one embodiment of the present disclosure. FIG. 6 is a drawing illustrating a specific operation for constructing an artificial intelligence-based pre-learning model capable of analyzing alcohol intake pattern information of a user to provide skin electrical stimulation for alleviating symptoms of alcohol addiction according to one embodiment of the present disclosure. FIGS. 7 and 8 are drawings illustrating an example of a user interface implemented on a display module of a skin electrical stimulation providing device for alleviating symptoms of alcohol addiction according to an embodiment of the present disclosure. Specific details for implementing the invention

[0021] The advantages and features of the present disclosure and the methods for achieving them will become clear by referring to the embodiments described below in detail together with the accompanying drawings. However, the present disclosure is not limited to the embodiments disclosed below but may be implemented in various different forms. These embodiments are provided merely to make the present disclosure complete and to fully inform those skilled in the art of the scope of the present disclosure, and the present disclosure is defined only by the scope of the claims.

[0022] The terms used in this specification are for describing embodiments and are not intended to limit the disclosure. In this specification, the singular form includes the plural form unless specifically stated otherwise in the text. The terms “comprises” and / or “comprising” as used in this specification do not exclude the presence or addition of one or more other components in addition to the components mentioned. Throughout the specification, the same reference numerals refer to the same components, and “and / or” includes each of the mentioned components and all combinations of one or more. Although terms such as “first,” “second,” etc., are used to describe various components, these components are not limited by these terms. These terms are used merely to distinguish one component from another. Accordingly, the first component mentioned below may be the second component within the technical scope of this disclosure.

[0023] Unless otherwise defined, all terms used herein (including technical and scientific terms) may be used in a meaning commonly understood by those skilled in the art to which this disclosure pertains. Additionally, terms defined in commonly used dictionaries are not to be interpreted ideally or excessively unless explicitly and specifically defined otherwise.

[0024] Throughout this disclosure, the same reference numerals denote the same components. This disclosure does not describe all elements of the embodiments, and general content in the art to which this disclosure pertains or content that overlaps between embodiments is omitted. As used in the specification, the term “part” or “module” refers to a hardware component such as software, FPGA, or ASIC, and the “part” or “module” performs certain roles. However, the term “part” or “module” is not limited to software or hardware. The “part” or “module” may be configured to reside in an addressable storage medium or may be configured to run one or more processors. Accordingly, by example, the “part” or “module” includes components such as software components, object-oriented software components, class components, and task components, as well as processes, functions, attributes, procedures, subroutines, segments of program code, drivers, firmware, microcode, circuits, data, databases, data structures, tables, arrays, and variables. The functions provided within the components and "parts" or "modules" may be combined into a smaller number of components and "parts" or "modules," or further separated into additional components and "parts" or "modules."

[0025] Throughout the specification, when a part is described as being "connected" to another part, this includes not only cases where they are directly connected but also cases where they are indirectly connected, and indirect connections include connections made via a wireless communication network.

[0026] Furthermore, when it is stated that a part "includes" a certain component, this means that, unless specifically stated otherwise, it does not exclude other components but may include additional components.

[0027] Throughout the specification, when it is stated that a component is located "on" another component, this includes not only cases where a component is in contact with another component, but also cases where another component exists between the two components.

[0028] Terms such as "first," "second," etc., are used to distinguish one component from another, and the components are not limited by the aforementioned terms.

[0029] Singular expressions include plural expressions unless there is an obvious exception in the context.

[0030] In each step, identification codes are used for convenience of explanation and do not describe the order of the steps; the steps may be performed differently from the specified order unless a specific order is clearly indicated in the context.

[0031] The terms used in the following description are defined as follows.

[0032] In this specification, an artificial intelligence-based pre-trained model may be used to recognize keywords or commands input by a user terminal. In this case, examples of artificial intelligence algorithms may include a Recurrent Neural Network (RNN) or a Transformer, but are not limited thereto, and other artificial intelligence algorithms may also be applied.

[0033] Although the present specification has been described as being limited to a 'providing device (100)', this may include all various devices capable of performing computational processing as a device for providing skin electrical stimulation based on a wearable device to alleviate symptoms of alcohol addiction. This providing device (100) corresponds to a 'user terminal' possessed by a user and may be configured to be worn on the user's wrist to apply electrical stimulation to the wrist.

[0034] Meanwhile, in this specification, the 'server (200)' is a device for storing stimulus information for a preset period through a providing device (100), that is, a user terminal, and providing this information as is to at least one preset related party terminal (300), or providing analysis information that analyzes whether there is improvement, whether there is a cure, etc., and may include a computer and / or portable terminal in addition to the server, or may take any one of these forms, and is not limited thereto.

[0035] Here, the server is a server that processes information by communicating with an external device, and may include an application server, a computing server, a database server, a file server, a game server, a mail server, a proxy server, and a web server.

[0036] The above computer may include, for example, a notebook, desktop, laptop, tablet PC, slate PC, etc. equipped with a web browser.

[0037] The above portable terminal may include, for example, all types of handheld-based wireless communication devices such as PCS (Personal Communication System), GSM (Global System for Mobile communications), PDC (Personal Digital Cellular), PHS (Personal Handyphone System), PDA (Personal Digital Assistant), IMT (International Mobile Telecommunication)-2000, CDMA (Code Division Multiple Access)-2000, W-CDMA (W-Code Division Multiple Access), WiBro (Wireless Broadband Internet) terminals, smartphones, etc., as well as wearable devices such as watches, rings, bracelets, anklets, necklaces, glasses, contact lenses, or head-mounted devices (HMDs).

[0038] The operating principles and embodiments of the present disclosure will be described below with reference to the attached drawings.

[0039] FIG. 1 is a diagram showing the network structure of a wearable device-based service provision system for alleviating symptoms of alcohol addiction according to one embodiment of the present disclosure.

[0040] Referring to FIG. 1, a wearable device-based service provision system (hereinafter referred to as the "service provision system") (10) for alleviating symptoms of alcohol addiction according to one embodiment of the present disclosure may be configured to include a skin electrical stimulation providing device (hereinafter referred to as the "providing device") (100), a server (200), and at least one related party terminal (300).

[0041] First, the providing device (100) is a wearable device configured to be worn on the wrist by a user and corresponds to a user terminal. This providing device (100) can use the services provided by the server (200) by downloading a separate platform (application) provided by the server (200) and running it.

[0042] Specifically, the providing device (100) can receive electrical stimulation according to the alcohol intake state after registering itself as a user when first using the service through the application.

[0043] At this time, according to one embodiment, the providing device (100) may generate an electric stimulus in response to an operation signal by a user to alleviate symptoms of alcohol addiction in which a person strongly craves alcohol, and according to another embodiment, the providing device (100) may automatically detect the user's alcohol intake state and generate an appropriate electric stimulus to alleviate symptoms of alcohol addiction.

[0044] First, in the case corresponding to one embodiment, when a user feels an urge to consume alcohol (craving for alcohol), if at least one condition for electrical stimulation is set through at least one button or input window provided on the providing device (100), the providing device (100) applies electrical stimulation to the user's wrist through the NMS method based on that at least one condition. In addition, even while electrical stimulation is being applied, if the providing device (100) inputs an operation regarding at least one of the electrical stimulation intensity, electrical stimulation speed, and electrical stimulation time from the user, it can change and reset the previously set at least one condition according to that operation.

[0045] In addition, in the case corresponding to another embodiment, the providing device (100) acquires state information to check the alcohol intake state and checks the electrical stimulation intensity, electrical stimulation speed, and electrical stimulation time corresponding to the alcohol intake state based on the previously stored electrical stimulation information. Accordingly, the providing device (100) applies an electrical stimulation intensity at an electrical stimulation speed to the user's wrist through the NMS method during the electrical stimulation time.

[0046] To this end, the providing device (100) can establish and provide an artificial intelligence-based pre-trained model by registering a user on the application, monitoring biometric information and motion information of the user in real time, and collecting alcohol consumption pattern information of the user for a preset period to train the original model.

[0047] For example, the providing device (100) detects whether the user has consumed alcohol based on the user's biometric information and motion information and previously stored alcohol consumption pattern information, and when alcohol consumption is detected, generates alcohol consumption pattern information for the user using the biometric information and motion information at that time. By accumulating and storing the generated alcohol consumption pattern information and using it to train the original model, an artificial intelligence-based pre-training model suitable for (customized for) the user can be constructed.

[0048] Here, the previously stored alcohol consumption pattern information is information generated by analyzing biometric information and motion information at the time when alcohol consumption is determined to have occurred, based on stimulus information for each of the multiple users registered in the server (200), and can serve as a criterion for detecting whether the user has consumed alcohol through a general alcohol consumption pattern based on the analysis results. In addition, the alcohol consumption state can be divided into multiple stages and stored based on the number of times alcohol is consumed, and biometric information and motion information for each stage can be stored.

[0049] Meanwhile, the providing device (100) generates stimulation information including at least one of the intensity and speed of the applied electrical stimulation during the time the electrical stimulation is executed, and transmits it to the server (200).

[0050] At this time, different intensities and speeds may be applied for each time interval during the time the electrical stimulation is executed, and the stimulation information may include information on at least one of the intensities and speeds of the electrical stimulation applied for the time interval. Here, the time during which the electrical stimulation is executed may be calculated by verifying the time from when the electrical stimulation started to when it was relieved, or it may be calculated from the time from when the electrical stimulation started to the time it ended under user control.

[0051] Additionally, the providing device (100) may transmit the stimulus information to the server (200) whenever the stimulus information is generated, or it may collect the stimulus information accumulated and stored during the corresponding period at preset intervals and transmit it to the server (200), and the transmission time and interval are not limited.

[0052] Meanwhile, the server (200) provides a service for alleviating symptoms of alcohol addiction to a user based on a separate platform (application) or web page through the providing device (100), and receives stimulus information as a result of the service provision from the providing device (100). Accordingly, the server (200) can transmit the stimulus information regarding the user as is to at least one related terminal (300) pre-configured for the providing device (100), or transmit analysis information based on the information regarding whether there has been improvement or recovery in symptoms of alcohol addiction and / or alcohol consumption behavior.

[0053] Meanwhile, at least one related party terminal (300-1, …, 300-n) may be a terminal carried by a related party (medical staff in charge, medical institution, guardian, etc.) that is set in correspondence with the providing device (100).

[0054] At this time, at least one related party terminal (300-1, …300-n) may be set by approval or registration of the corresponding providing device (100), or may be set directly by searching for the corresponding providing device (100). However, this is merely one embodiment and does not limit the method of setting at least one related party terminal corresponding to the corresponding providing device (100).

[0055] When at least one of these personnel terminals (300-1, …300-n) receives stimulus information and / or analysis information from the server (200), it can display this on its display module so that the relevant personnel can visually confirm it.

[0056] Here, at least one user terminal (200) and / or at least one related party terminal (300) may be a computer, UMPC (Ultra Mobile PC), workstation, netbook, PDA (Personal Digital Assistants), portable computer, web tablet, wireless phone, mobile phone, smartphone, pad, smart watch, wearable terminal, e-book, PMP (portable multimedia player), portable game console, navigation device, black box or digital camera, other mobile communication terminal, etc., capable of installing and running a number of applications (i.e., applications) desired by each user and / or related party. That is, each of the at least one user terminal (200) and / or at least one related party terminal (300) may be provided in various forms, and the number, type, and form thereof are not limited.

[0057] Here, at least one personnel terminal (300) may be a computer, UMPC (Ultra Mobile PC), workstation, netbook, PDA (Personal Digital Assistants), portable computer, web tablet, wireless phone, mobile phone, smartphone, pad, smart watch, wearable terminal, e-book, PMP (portable multimedia player), portable game console, navigation device, black box or digital camera, other mobile communication terminal, etc., capable of installing and running a number of applications (i.e., applications) desired by each personnel. That is, each of the at least one personnel terminal (300) may be provided in various forms and is not limited thereto.

[0058] In the following description of the present disclosure, for the sake of convenience and to prevent redundancy, the description will be limited to cases corresponding to other embodiments among the previously mentioned first embodiment and other embodiments.

[0059] FIG. 2 is a flowchart illustrating the operation of a wearable device-based service provision system for alleviating symptoms of alcohol addiction according to one embodiment of the present disclosure.

[0060] Referring to FIG. 2, the server (200) initiates a service for alleviating symptoms of alcohol addiction through a providing device (100) configured to be worn by a user (S101), and provides an application created to provide the service to be downloaded in response to a request from the providing device (100) (S103).

[0061] Next, the providing device (100) executes the application that was downloaded in step S103 (S105) and registers a user who wishes to receive the service on the application (S107).

[0062] Next, the providing device (100) monitors the biometric information and motion information of the user in real time, collects alcohol consumption pattern information of the user during a preset period, and builds and applies an artificial intelligence-based pre-trained model by training the original model (S109), and then determines whether the user has consumed alcohol using the pre-trained model (S111). That is, the providing device (100) inputs the biometric information and motion information of the user into the pre-trained model to determine (detect) whether the user feels an urge to consume alcohol or is consuming alcohol.

[0063] Next, when the providing device (100) determines, based on the judgment result of step 111, that the user is feeling an urge to consume alcohol or is consuming alcohol, it applies an electrical stimulus to the wrist of the user wearing the providing device (100) through the NMS method (S113), and when the application of the electrical stimulus ends, it generates stimulus application information (S115).

[0064] Next, the providing device (100) transmits the stimulus information generated by step S115 to the server (200) (S117), and the server (200) stores the received stimulus information (S119).

[0065] Next, the server (200) transmits the stimulus information stored in step S119 to at least one related terminal (300) that is pre-set for the corresponding providing device (100) (S121), and each of the at least one related terminal (300) can display the stimulus information on its display module so that each related person can visually confirm it.

[0066] Meanwhile, FIG. 2 illustrates a case where the server (200) transmits the stimulus information received by step S117 to at least one related terminal (300) as is. As previously explained, this is merely one embodiment, and the server may also analyze the received stimulus information to generate and transmit analysis information.

[0067] FIG. 3 is a diagram showing the configuration of a wearable device-based skin electrical stimulation providing device for alleviating symptoms of alcohol addiction according to one embodiment of the present disclosure.

[0068] Referring to FIG. 3, a skin electrical stimulation providing device (hereinafter referred to as the "providing device") (100) for alleviating symptoms of alcohol addiction according to one embodiment of the present disclosure may be configured to include a communication module (110), a storage module (120), an input module (130), a sensor module (140), and a control module (150).

[0069] The communication module (110) transmits and receives at least one piece of information or data to and from the server (200) and at least one other device / terminal. Here, the type and form of the at least one device / terminal are not limited.

[0070] This communication module (110) may perform communication to transmit and receive at least one piece of information or data, and transmits and receives wireless signals in a communication network according to wireless internet technologies.

[0071] Wireless internet technologies include, for example, WLAN (Wireless LAN), Wi-Fi (Wireless-Fidelity), Wi-Fi (Wireless Fidelity) Direct, DLNA (Digital Living Network Alliance), WiBro (Wireless Broadband), WiMAX (World Interoperability for Microwave Access), HSDPA (High Speed ​​Downlink Packet Access), HSUPA (High Speed ​​Uplink Packet Access), LTE (Long Term Evolution), LTE-A (Long Term Evolution-Advanced), etc., and the providing device (100) transmits and receives data according to at least one wireless internet technology within a range that includes internet technologies not listed above.

[0072] For short-range communication, short-range communication can be supported by utilizing at least one of the following technologies: Bluetooth™, RFID (Radio Frequency Identification), Infrared Data Association (IrDA), Ultra Wideband (UWB), ZigBee, Near Field Communication (NFC), Wireless-Fidelity (Wi-Fi), Wi-Fi Direct, and Wireless Universal Serial Bus (Wireless USB). Wireless communication between a device (100) and a server (200) can be supported using such wireless area networks. In this case, the wireless area network may be a wireless personal area network.

[0073] The storage module (120) can store data for at least one process (algorithm) or a program that reproduces the process for providing skin electrical stimulation to alleviate symptoms of alcohol addiction. In addition, the storage module (120) can store additional processes for performing other operations, and is not limited thereto.

[0074] The storage module (120) can store various information / data necessary to provide skin electrical stimulation for alleviating symptoms of alcohol addiction, as well as various other data that support various functions of the providing device (100). The storage module (120) can store a number of application programs (or applications) running on the providing device (100), data for the operation of the providing device (100), and commands. At least some of these application programs can be downloaded from an external server via wireless communication. Meanwhile, the application program can be stored in at least one memory provided in the storage module (120), installed on the providing device (100), and driven to perform an operation (or function) by at least one processor stored in the storage module (120) through the control module (150).

[0075] Meanwhile, at least one memory may include a storage medium of at least one type among flash memory type, hard disk type, multimedia card micro type, card type memory (e.g., SD or XD memory, etc.), RAM (Random Access Memory), SRAM (Static Random Access Memory), ROM (Read-Only Memory), EEPROM (Electrically Erasable Programmable Read-Only Memory), PROM (Programmable Read-Only Memory), magnetic memory, magnetic disk, and optical disk. In addition, the memory may store information temporarily, permanently, or semi-permanently, and may be provided as an embedded or removable type.

[0076] Additionally, the storage module (120) may build a database that stores various information necessary to provide skin electrical stimulation to alleviate symptoms of alcohol addiction, or may be linked with a separate external server (including a cloud server).

[0077] Meanwhile, the input module (130) is provided with at least one button or input window so that the user can input an operation signal to set (adjust) at least one condition (including at least one of the electric stimulation intensity, the electric stimulation speed, and the electric stimulation time) for the electric stimulation applied to the user or to control the application.

[0078] Thus, the user can set at least one condition for the electric stimulation through at least one button or input window before receiving the electric stimulation and receive the electric stimulation according to the set value, or adjust at least one condition for the electric stimulation while receiving the electric stimulation and adjust the electric stimulation according to the adjusted value.

[0079] Meanwhile, the sensor module (140) may be equipped with at least one sensor for acquiring the user's biometric information and motion information. Here, the biometric information may include at least one of brain waves, blood pressure, heart rate, electrocardiogram, skin temperature, and oxygen saturation, and the motion information may include at least one of hand movement, speed, and angle.

[0080] To this end, the sensor module (140) may be configured to include at least one of an accelerometer, an oxygen sensor, a bioimpedance sensor, a magnetometer, a heart rate sensor, a skin temperature sensor, a gesture sensor, and a UV sensor, and the types and number thereof are not limited.

[0081] Meanwhile, in addition to operations related to application programs, the control module (150) controls all components within the providing device (100) based on at least one processor to process input or output signals, data, information, etc., or executes instructions, algorithms, and application programs stored in at least one memory to perform various processes, and can provide or process appropriate information or functions to provide a service for alleviating symptoms of alcohol addiction.

[0082] Specifically, the control module (150) obtains the user's state information through a platform (application) to check the alcohol intake state, and based on the stored electrical stimulation information, checks the electrical stimulation intensity, electrical stimulation speed, and electrical stimulation time corresponding to the alcohol intake state, and then applies the electrical stimulation intensity at the electrical stimulation speed to the user's wrist during the electrical stimulation time. Here, the stored electrical stimulation information includes multiple alcohol intake states classified according to bio-information and motion information, and the electrical stimulation intensity, electrical stimulation speed, and electrical stimulation time can be set for each of the multiple alcohol intake states, and using this as an indicator, the electrical stimulation intensity, electrical stimulation speed, and electrical stimulation time appropriate (mapped) to the user's alcohol intake state can be checked and determined. That is, the electrical stimulation intensity, electrical stimulation speed, and electrical stimulation time are determined in response to the user's state that changes as alcohol is consumed, and electrical stimulation is provided. In other words, the stronger the state of alcohol intake, the stronger the electrical stimulation can be applied.

[0083] Meanwhile, the control module (150) establishes and provides an artificial intelligence-based pre-training model to perform the operations described above. Specifically, the control module (150) can establish an artificial intelligence-based pre-training model by initially registering the user and then collecting alcohol consumption pattern information for the user during a pre-set period to train the original model. At this time, the alcohol consumption pattern information can be generated by the control module (150) monitoring the user's biometric information and motion information in real time and detecting whether the user has consumed alcohol based on the previously stored alcohol consumption pattern information. That is, when the user's biometric information and motion information at a given time are viewed, if it is detected that the user is feeling an urge to consume alcohol or is consuming alcohol, alcohol consumption pattern information for the user can be generated using the biometric information and motion information at that time.

[0084] Thus, the control module (150) detects whether the user has consumed alcohol by using the user's biometric information and motion information obtained at pre-set intervals through the prior learning model. If the control module (150) detects that the user is feeling an urge to consume alcohol or is consuming alcohol, the acquired biometric information and motion information are obtained as the user's state information.

[0085] In addition, the specific operation of the control module (150) will be explained below based on the respective drawings.

[0086] FIG. 4 is a diagram showing the configuration of a method for providing skin electrical stimulation based on a wearable device for alleviating symptoms of alcohol addiction according to one embodiment of the present disclosure.

[0087] Referring to FIG. 4, the providing device (100) obtains the status information of the user through a platform (application) (S210), and checks the alcohol consumption status based on the obtained status information (S220).

[0088] Next, the providing device (100) checks the electrical stimulation intensity, electrical stimulation speed, and electrical stimulation time corresponding to the alcohol intake state confirmed by step S220 based on the previously stored electrical stimulation information (S230), and applies the electrical stimulation intensity at the electrical stimulation speed to the wrist of the user during the electrical stimulation time (S240).

[0089] FIG. 5 is a diagram showing a specific operation for acquiring state information in a method for providing skin electrical stimulation based on a wearable device for alleviating symptoms of alcohol addiction according to one embodiment of the present disclosure.

[0090] Referring to FIG. 5, the providing device (100) obtains the user’s biometric information and motion information in real time by monitoring them at preset intervals through a platform (application) (S211), and detects whether the user has consumed alcohol based on the previously stored alcohol consumption pattern information through an artificial intelligence-based pre-learning model (S212).

[0091] If an alcohol consumption impulse or alcohol consumption is detected by step S212, the providing device (100) obtains the biometric information and motion information at the corresponding time obtained by step S211 as state information (S213).

[0092] Meanwhile, if an urge to consume alcohol or alcohol consumption is detected or not detected by Step S212, the process returns to Step S211 and repeats the same action, regardless of the situation. This is to verify whether the symptoms of alcohol addiction are alleviated and at what point in time they are alleviated, even if an urge to consume alcohol or alcohol consumption is detected.

[0093] FIG. 6 is a diagram illustrating a specific operation of constructing an artificial intelligence-based pre-learning model capable of analyzing the alcohol intake pattern information of a user to provide skin electrical stimulation for alleviating symptoms of alcohol addiction according to one embodiment of the present disclosure.

[0094] Referring to FIG. 6, the providing device (100) initially registers itself as a user who wishes to receive services on a platform (application). Subsequently, the providing device (100) monitors the biometric information and motion information of the user in real time to collect alcohol consumption pattern information of the user for a preset period (S201), and performs learning on the original model using the collected alcohol consumption pattern information (S202).

[0095] Next, the providing device (100) can build a model that has been trained by step S202, that is, an artificial intelligence-based pre-trained model, and use it to detect whether the user has consumed alcohol (S203).

[0096] FIGS. 7 and 8 are drawings illustrating an example of a user interface implemented on a display module of a skin electrical stimulation providing device for alleviating symptoms of alcohol addiction according to one embodiment of the present disclosure.

[0097] First, referring to FIG. 7, biometric information and / or motion information regarding the user obtained through the sensor module (140) can be visually displayed on the display module (160) of the providing device (100). At this time, the number of times alcohol consumption has been detected (number of alcohol consumption detections) based on the biometric information and / or motion information may be displayed on the screen, and the time (interval) at which alcohol consumption was detected may also be displayed. However, this is only one embodiment, and situations where an urge to consume alcohol is felt may also be detected, in which case the number of alcohol consumption urge detections and the time (interval) at which they were detected may be displayed on the display module (160).

[0098] Meanwhile, referring to FIG. 8, at least one of the degree of electrical stimulation according to the alcohol intake state (alcohol intake stage) confirmed (determined) by the providing device (100), namely the electrical stimulation intensity, electrical stimulation speed, and electrical stimulation time, may be visually displayed on the display module (160) of the providing device (100). At this time, the degree of electrical stimulation may be provided in the form of a control bar, as an example, and through this, the user can adjust the degree of electrical stimulation by moving a control point on the control bar before or during the execution of electrical stimulation.

[0099] Meanwhile, the present disclosure performs inference for a specific purpose using a model implemented in an artificial neural network manner, and the artificial neural network will be examined below.

[0100] As used herein, a model may refer to any form of computer program that operates based on a network function, an artificial neural network, and / or a neural network. Throughout this specification, the terms model, neural network, network function, and neural network may be used interchangeably. A neural network is formed in which one or more nodes are interconnected through one or more links to form input and output node relationships within the neural network. The characteristics of a neural network may be determined by the number of nodes and links within the neural network, the relationships between the nodes and links, and the values ​​of the weights assigned to each link. A neural network may be composed of a set of one or more nodes. A subset of nodes constituting a neural network may form a layer.

[0101] A deep neural network (DNN) may refer to a neural network that includes multiple hidden layers in addition to an input layer and an output layer, and the intermediate hidden layer in a deep neural network consists of one or more, preferably two or more.

[0102] These deep neural networks may include convolutional neural networks (CNN), vision transformers, recurrent neural networks (RNN), Long Short Term Memory (LSTM) networks, Generative Pre-trained Transformer (GPT), auto encoders, Generative Adversarial Networks (GAN), restricted Boltzmann machines (RBM), deep belief networks (DBN), Q networks, U networks, Siamese networks, Generative Adversarial Networks (GAN), transformers, etc.

[0103] Alternatively, according to an embodiment, the deep neural network may be a model trained using a transfer learning method. Here, transfer learning refers to a learning method in which a pre-trained model (or base unit) having a first task is obtained by pre-training a large amount of unlabeled training data using a semi-supervised or self-learning method, and a target model is implemented by training labeled training data using a supervised learning method to fine-tune the pre-trained model to suit a second task. Examples of models trained using such a transfer learning method include BERT (Bidirectional Encoder Representations from Transformers), but are not limited thereto.

[0104] The description of the deep neural network described above is merely an example and the present disclosure is not limited thereto. In the case of the convolutional neural network described above, it consists of a feature learning unit that extracts features from an image and a classification unit that performs classification using the extracted features. The feature learning unit may include a convolutional layer in which features are extracted from an image using a kernel, a ReLU layer which is one of the activation functions, and a pooling layer to reduce the dimensionality of the data, but is not limited thereto. In addition, the classification unit may include a flatten layer that arranges the features extracted from the feature learning unit in a row, a fully connected layer where classification is actually performed, and a softmax function, but is not limited thereto.

[0105] Neural networks can be trained in at least one of supervised learning, unsupervised learning, semi-supervised learning, self-supervised learning, or reinforcement learning. The training of a neural network may be a process of applying knowledge to the neural network to perform a specific action.

[0106] Neural networks can be trained to minimize output errors. The training process involves repeatedly inputting training data into the network, calculating the error between the network's output and the target for the training data, and updating the weights of each node by backpropagating the error from the output layer to the input layer in a direction that reduces the error. In supervised learning, labeled data with correct answers is used for each training point, whereas in unsupervised learning, unlabeled data can be used. The amount of change in the connection weights of each updated node can be determined by the learning rate. The neural network's calculation of the input data and the backpropagation of the error can constitute a training cycle (epoch). The learning rate can be applied differently depending on the number of iterations of the neural network's training cycle. In addition, to prevent overfitting, methods such as increasing training data, regularization, dropout (which disables some nodes), and batch normalization layers can be applied.

[0107] Meanwhile, the model disclosed in one embodiment may borrow at least a part of a transformer. The transformer may be composed of an encoder that encodes embedded data and a decoder that decodes the encoded data. The transformer may have a structure that receives a series of data and outputs a series of data of different types after undergoing encoding and decoding steps. In one embodiment, the series of data may be processed into a form that the transformer can compute. The process of processing the series of data into a form that the transformer can compute may include an embedding process. Expressions such as data token, embedding vector, embedding token, etc., may refer to data embedded in a form that the transformer can process.

[0108] To encode and decode a series of data, the encoders and decoders within the transformer can be processed using an attention algorithm. An attention algorithm can refer to an algorithm that calculates the similarity between one or more keys for a given query, applies this similarity to the values ​​corresponding to each key, and then calculates an attention value by performing a weighted sum of the similarity-applied values.

[0109] Various types of attention algorithms can be classified depending on how the query, key, and value are configured. For example, if attention is calculated by setting the query, key, and value identically, this can be referred to as a self-attention algorithm. If attention is calculated by reducing the dimensionality of embedding vectors to process a series of input data in parallel and determining an individual attention head for each partitioned embedding vector, this can be referred to as a multi-head attention algorithm.

[0110] In one embodiment, the transformer may be composed of modules that perform a plurality of multi-head self-attention algorithms or multi-head encoder-decoder algorithms. In one embodiment, the transformer may also include additional components other than attention algorithms, such as embeddings, normalization, and softmax. A method for constructing the transformer using an attention algorithm may include the method disclosed in Vaswani et al., Attention Is All You Need, 2017 NIPS, which is incorporated herein by reference.

[0111] A transformer can be applied to various data domains, such as embedded natural language, segmented image data, and audio waveforms, to convert a series of input data into a series of output data. To convert data with various data domains into a series of data that can be input to the transformer, the transformer can embed the data. The transformer can process additional data that represents the relative positional or phase relationships between the series of input data. Alternatively, the series of input data may be embedded by additionally reflecting vectors that represent the relative positional or phase relationships between the input data. In one example, the relative positional relationships between the series of input data may include, but are not limited to, word order within a natural language sentence, the relative positional relationships of each segmented image, and the temporal order of segmented audio waveforms. The process of adding information that represents the relative positional or phase relationships between the series of input data may be referred to as positional encoding.

[0112] The aforementioned program may include code encoded in a computer language such as C, C++, JAVA, or machine language, which can be read by the computer's processor (CPU) through the computer's device interface, in order for the computer to read the program and execute the methods implemented in the program. Such code may include functional code related to functions that define the necessary functions for executing the methods, and may include control code related to execution procedures necessary for the computer's processor to execute the functions according to a predetermined procedure. Additionally, such code may further include memory reference code regarding where (address) additional information or media necessary for the computer's processor to execute the functions should be referenced in the computer's internal or external memory. In addition, if the processor of the computer needs to communicate with any other computer or server located remotely in order to execute the above functions, the code may further include communication-related code regarding how to communicate with any other computer or server located remotely using the communication module of the computer, and what information or media to transmit or receive during communication.

[0113] The above-mentioned storage medium refers to a medium that stores data semi-permanently and is readable by a device, rather than a medium that stores data for a short period of time, such as a register, cache, or memory. Specifically, examples of the above-mentioned storage medium include, but are not limited to, ROM, RAM, CD-ROM, magnetic tape, floppy disk, and optical data storage device. That is, the above-mentioned program may be stored on various recording media on various servers that the computer can access, or on various recording media on the user's computer. Additionally, the above-mentioned medium may be distributed across networked computer systems, and computer-readable code may be stored in a distributed manner.

[0114] The steps of the method or algorithm described in connection with the embodiments of the present disclosure may be implemented directly in hardware, implemented as a software module executed by hardware, or implemented by a combination thereof. The software module may reside in RAM (Random Access Memory), ROM (Read Only Memory), EPROM (Erasable Programmable ROM), EEPROM (Electrically Erasable Programmable ROM), Flash Memory, a hard disk, a removable disk, a CD-ROM, or any form of computer-readable recording medium well known in the art to which the present disclosure belongs.

[0115] Although embodiments of the present disclosure have been described above with reference to the attached drawings, those skilled in the art will understand that the present disclosure may be implemented in other specific forms without altering its technical concept or essential features. Therefore, the embodiments described above should be understood as illustrative in all respects and not restrictive. Explanation of the symbols

[0116] 10: Service provision system 100: Providing device 200: Server 300: At least one stakeholder terminal 110: Communication module 120: Storage module 130 : Input module 140 : Sensor module 150 : Control module 160 : Display module

Claims

Claim 1 A display module; a sensor module having at least one sensor for acquiring user's biometric information and motion information; a communication module for communicating with an external device; and a storage module for storing at least one process for providing skin electrical stimulation to alleviate symptoms of alcohol addiction. The system includes a control module that performs an operation to provide skin electrical stimulation for alleviating symptoms of alcohol addiction based on at least one process described above, wherein the control module acquires state information of the user to confirm the alcohol intake state, confirms the electrical stimulation intensity, electrical stimulation speed, and electrical stimulation time corresponding to the alcohol intake state based on previously stored electrical stimulation information, and applies the electrical stimulation intensity to the user's wrist at the electrical stimulation speed during the electrical stimulation time, wherein when the user is initially registered, an artificial intelligence-based pre-learning model is constructed by collecting alcohol intake pattern information for the user during a pre-set period and training an original model, and determines whether the user has consumed alcohol based on previously stored alcohol intake pattern information by monitoring the biometric information and the motion information, and if alcohol has been consumed, generates alcohol intake pattern information for the user using the biometric information and motion information at that time, acquires the biometric information and the motion information at pre-set intervals, inputs the acquired biometric information and motion information into the pre-learning model to determine whether the user has consumed alcohol, and if alcohol has been consumed, the Acquired biometric information and motion information are acquired as state information of the user, the electrical stimulation time is calculated as the period from the time the electrical stimulation starts until the time it is relieved or ends, and different electrical stimulation intensities and electrical stimulation speeds are controlled to be applied to multiple time intervals during the electrical stimulation time, and the number of alcohol intake detections and the time of alcohol intake detection based on the biometric information and motion information acquired through the sensor module are controlled to be displayed on the display module, and the electrical stimulation intensity corresponding to the alcohol intake pattern information,A skin electrical stimulation device based on a wearable device for alleviating symptoms of alcohol addiction, characterized by controlling at least one of an electrical stimulation speed and an electrical stimulation time to be displayed on the display module, controlling the degree of electrical stimulation to be displayed on the display module in the form of a control bar, receiving a movement of a control point on the control bar according to user input through the display module, and controlling the degree of electrical stimulation to be adjusted before or during the execution of the electrical stimulation based on the received input. Claim 2 A skin electrical stimulation device based on a wearable device for alleviating symptoms of alcohol addiction, characterized in that, in claim 1, it further comprises an input module having at least one button or input window so that the user can input an operation signal to adjust at least one of the electrical stimulation intensity, the electrical stimulation speed, and the electrical stimulation time, or to control an application. Claim 3 delete Claim 4 delete Claim 5 delete Claim 6 delete Claim 7 A skin electrical stimulation device based on a wearable device for alleviating symptoms of alcohol addiction, characterized in that, in claim 1, the electrical stimulation information stored above includes a plurality of alcohol intake states classified according to the bio-information and the operation information, and for each of the plurality of alcohol intake states, an electrical stimulation intensity, an electrical stimulation speed, and an electrical stimulation time are set. Claim 8 A method for providing skin electrical stimulation based on a wearable device for alleviating symptoms of alcohol addiction, performed by a skin electrical stimulation providing device, comprising: a step of acquiring user status information by a control module of the device; a step of confirming an alcohol intake state based on the status information by the control module; and a step of confirming an electrical stimulation intensity, electrical stimulation speed, and electrical stimulation time corresponding to the alcohol intake state based on previously stored electrical stimulation information by the control module. The method includes the step of applying the electrical stimulation intensity at the electrical stimulation speed to the user's wrist during the electrical stimulation time by the control module, wherein, when the user is initially registered by the control module, an artificial intelligence-based pre-learning model is constructed by collecting alcohol consumption pattern information for the user during a preset period and training an original model, and by the control module, the user's alcohol consumption status is determined based on previously stored alcohol consumption pattern information by monitoring biometric information and motion information, and by the control module, if alcohol consumption is present, alcohol consumption pattern information for the user is generated using the biometric information and motion information at the corresponding time point, and by the control module, the biometric information and motion information are acquired at preset intervals, and by the control module, the acquired biometric information and motion information are input into the pre-learning model to determine whether the user's alcohol consumption is present, and by the control module, if alcohol consumption is present, the acquired biometric information and motion information are acquired as the user's state information, and by the control module, from the time when the electrical stimulation begins The electrical stimulation time is calculated as the period until the point of alleviation or the point of termination, and the control module controls the application of different electrical stimulation intensities and electrical stimulation speeds to multiple time intervals during the electrical stimulation time, and the control module controls the display module to display the number of alcohol intake detections and the time of alcohol intake detection based on the bio-information and operation information obtained through the sensor module of the device.A method for providing skin electrical stimulation based on a wearable device for alleviating symptoms of alcohol addiction, performed by a skin electrical stimulation providing device, characterized by controlling, by the above control module, that at least one of the electrical stimulation intensity, electrical stimulation speed, and electrical stimulation time corresponding to the alcohol intake pattern information is displayed on the display module; by the above control module, that the degree of the electrical stimulation is displayed on the display module in the form of a control bar; by the above control module, that a movement of a control point on the control bar is received according to user input through the display module; and by the above control module, that the degree of the electrical stimulation is controlled to be adjusted before or during the execution of the electrical stimulation based on the received input. Claim 9 A method for providing skin electrical stimulation based on a wearable device for alleviating symptoms of alcohol addiction, performed by a skin electrical stimulation providing device, wherein, in claim 8, the step of confirming the electrical stimulation intensity, electrical stimulation speed, and electrical stimulation time is characterized by adjusting at least one of the electrical stimulation intensity, electrical stimulation speed, and electrical stimulation time based on the operation signal when an operation signal is input from the user by the control module to make a final determination. Claim 10 delete Claim 11 delete Claim 12 delete Claim 13 delete Claim 14 A method for providing skin electrical stimulation based on a wearable device for alleviating symptoms of alcohol addiction, performed by a skin electrical stimulation providing device, wherein, in claim 8, the electrical stimulation information stored above includes a plurality of alcohol intake states classified according to the bio-information and the operation information, and for each of the plurality of alcohol intake states, an electrical stimulation intensity, an electrical stimulation speed, and an electrical stimulation time are set. Claim 15 A computer program stored on a computer-readable recording medium to perform a wearable device-based skin electrical stimulation method for alleviating symptoms of alcohol addiction, which is combined with a computer that is hardware and performed by a skin electrical stimulation providing device according to any one of claims 8, 9 and 14.

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