Smart eye patch utilizing internet of things, and method and system for controlling operation thereof

Abstract

Disclosed are a smart eye patch utilizing the Internet of Things, and a method and a system for controlling the operation thereof. A terminal communicating with a smart eye patch including at least one light-emitting unit and sensor according to the present disclosure may comprise: a communication module; a display; a reception unit for receiving a signal from the smart eye patch; an analysis unit for processing and analyzing the received signal from the smart eye patch; and a control unit for controlling the operation of the smart eye patch according to the content analyzed by the analysis unit.

Description

Smart eye mask incorporating the Internet of Things, its operation control method and system

[0001] The present disclosure relates to a smart eye mask, and more specifically, to a smart eye mask incorporating the Internet of Things, and a method and system for controlling the operation thereof.

[0002] Traditionally, eye patches had only the function of protecting the eyes, or eyeballs.

[0003] Recently, the demand for vision correction surgeries such as LASIK and LASEK has been steadily increasing for cosmetic purposes or to relieve inconveniences in daily life.

[0004] In addition, as the aging population increases and the atmospheric environment changes, various eye diseases such as cataracts and glaucoma are increasing, and the demand for ophthalmic surgery is also increasing.

[0005] For this reason, the demand for wearing eye patches is increasing for postoperative care, including protection of the eyes after procedures or surgeries.

[0006] The present disclosure aims to provide information and guidance to the user regarding the timing of eye drop application by linking a smart eye patch and a terminal application, thereby improving the effectiveness of eye treatment.

[0007] The present disclosure provides a smart eye mask incorporating the Internet of Things, and a method and system for controlling its operation.

[0008] A smart eye mask incorporating the Internet of Things according to at least one of the various embodiments of the present disclosure comprises: a communication module; an eye protection part formed in a predetermined shape to cover at least one eye of a user; and a support part that supports the eye protection part so that it is fixed to the user's body, wherein the eye protection part may include at least one light-emitting part and at least one sensor.

[0009] According to at least one of the various embodiments of the present disclosure, the at least one light emitting element and the at least one sensor may be attached to one end of the eye protection element.

[0010] According to at least one of the various embodiments of the present disclosure, one end of the eye protection member may extend to a position corresponding to the user's temple area.

[0011] According to at least one of the various embodiments of the present disclosure, one end of the eye protection member may extend to a position corresponding to an area above the user's eyebrow.

[0012] According to at least one of the various embodiments of the present disclosure, the at least one light emitting unit may be formed as an LED element or an LED array.

[0013] According to at least one of the various embodiments of the present disclosure, the at least one sensor unit may include a touch sensor that senses a touch input of the user.

[0014] According to at least one of the various embodiments of the present disclosure, the eye protection member may be manufactured by scanning the user's facial shape and using a 3D printer based on the scanned facial shape data.

[0015] A terminal communicating with a smart eye mask including a light-emitting unit and a sensor according to at least one of various embodiments of the present disclosure may include a communication module; a receiving unit that receives a signal from the smart eye mask; an analyzing unit that processes and analyzes the received signal from the smart eye mask; and a controlling unit that controls the operation of the smart eye mask according to the content analyzed by the analyzing unit.

[0016] A method of operating a terminal that controls a smart eye mask by communicating with a smart eye mask including a light emitting unit and a sensor according to at least one of various embodiments of the present disclosure may include the steps of: obtaining user eye drop administration log information from the smart eye mask; analyzing the obtained user eye drop administration log information; determining whether the next eye drop administration time has elapsed based on the analysis result; and generating and transmitting a user eye drop administration guidance signal to the smart eye mask based on the determination result, thereby controlling the operation of the smart eye mask.

[0017] According to at least one of the various embodiments of the present disclosure,

[0018] First, it has the effect of increasing the therapeutic effect by encouraging users to use eye drops more accurately.

[0019] Second, a smart eye mask incorporating the Internet of Things and its operation control method and system can be provided.

[0020] FIG. 1 is a schematic diagram of a service system including a smart eye mask integrated with the Internet of Things according to one embodiment of the present disclosure.

[0021] Figure 2 is a block diagram of the terminal of Figure 1.

[0022] Fig. 3 is a block diagram of the smart blindfold of Fig. 1.

[0023] FIG. 4 is a diagram illustrating a smart sensor including at least one active area according to one embodiment of the present disclosure.

[0024] Figure 5 is a drawing illustrating the configuration of each active area of ​​Figure 4.

[0025] Figures 6 and 7 are flowcharts illustrating a method for optimizing drying of pathology slides according to the present disclosure.

[0026] Throughout this disclosure, the same reference numerals denote the same components. This disclosure does not describe all elements of the embodiments, and any content that is common in the technical field to which this disclosure pertains or that overlaps between embodiments is omitted. The terms "part, module, element, block" used in the specification may be implemented in software or hardware, and depending on the embodiments, multiple "parts, modules, elements, blocks" may be implemented as a single component, or a single "part, module, element, block" may include multiple components.

[0027] Throughout the specification, when a part is said to be "connected" to another part, this includes not only direct connection but also indirect connection, and indirect connection includes connection via a wireless communication network.

[0028] Additionally, when a part is said to "include" a component, this does not mean that it excludes other components, but rather that it may include other components, unless otherwise specifically stated.

[0029] Throughout the specification, when we say that an element is "on" another element, this includes not only cases where the element is in contact with the other element, but also cases where another element exists between the two elements.

[0030] The terms first, second, etc. are used to distinguish one component from another, and the components are not limited by the aforementioned terms.

[0031] Singular expressions include plural expressions unless the context clearly indicates otherwise.

[0032] The identification codes for each step are used for convenience of explanation and do not describe the order of each step. Each step may be performed in a different order than specified unless the context clearly indicates a specific order.

[0033] The operating principle and embodiments of the present disclosure are described below with reference to the attached drawings.

[0034] As used herein, the term "device according to the present disclosure" encompasses a variety of devices capable of performing computational processing and providing results to a user. For example, the device according to the present disclosure may include a computer, a server device, and a portable terminal, or may be any one of them.

[0035] Here, the computer may include, for example, a notebook, desktop, laptop, tablet PC, slate PC, etc. equipped with a web browser.

[0036] The above server device 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, a web server, etc.

[0037] The above portable terminal may include, for example, a wireless communication device that ensures portability and mobility, and may include all kinds of handheld-based wireless communication devices such as a 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) terminal, smart phone, etc., and wearable devices such as a watch, ring, bracelet, anklet, necklace, glasses, contact lens, or head-mounted device (HMD).

[0038] The artificial intelligence-related functions according to the present disclosure are operated via a processor and memory. The processor may be comprised of one or more processors. In this case, one or more processors may be a general-purpose processor such as a CPU, an AP, a Digital Signal Processor (DSP), a graphics-only processor such as a GPU or a Vision Processing Unit (VPU), or an artificial intelligence-only processor such as an NPU. One or more processors control the processing of input data according to predefined operating rules or artificial intelligence models stored in memory. Alternatively, if one or more processors are artificial intelligence-only processors, the artificial intelligence-only processor may be designed with a hardware structure specialized for processing a specific artificial intelligence model.

[0039] The predefined operation rules or artificial intelligence models are characterized by being created through learning. Here, being created through learning means that the basic artificial intelligence model is learned by a learning algorithm using a plurality of learning data, thereby creating a predefined operation rules or artificial intelligence model set to perform a desired characteristic (or purpose). This learning may be performed on the device itself on which the artificial intelligence according to the present disclosure is performed, or may be performed through a separate server and / or system. Examples of the learning algorithm include, but are not limited to, supervised learning, unsupervised learning, semi-supervised learning, or reinforcement learning.

[0040] An artificial intelligence model may be composed of multiple neural network layers. Each of the multiple neural network layers has multiple weight values, and performs neural network operations through operations between the operation results of the previous layer and the multiple weights. The multiple weights of the multiple neural network layers may be optimized based on the learning results of the artificial intelligence model. For example, the multiple weights may be updated so that the loss value or cost value obtained from the artificial intelligence model is reduced or minimized during the learning process. The artificial neural network may include a deep neural network (DNN), and examples thereof include, but are not limited to, a convolutional neural network (CNN), a deep neural network (DNN), a recurrent neural network (RNN), a restricted boltzmann machine (RBM), a deep belief network (DBN), a bidirectional recurrent deep neural network (BRDNN), or deep Q-networks.

[0041] According to an exemplary embodiment of the present disclosure, a processor can implement artificial intelligence. Artificial intelligence refers to a machine learning method based on an artificial neural network that imitates human neurons (biological neurons) to enable machines to learn. Artificial intelligence methodologies can be categorized into supervised learning, in which input data and output data are provided together as training data depending on the learning method, so that the solution (output data) to the problem (input data) is determined; unsupervised learning, in which only input data is provided without output data, so that the solution (output data) to the problem (input data) is not determined; and reinforcement learning, in which a reward (Reward) is provided from an external environment whenever an action (Action) is taken in the current state (State), and learning is performed in a direction to maximize this reward. In addition, artificial intelligence methodologies can be categorized according to the architecture of the learning model. The architectures of widely used deep learning technologies can be categorized into convolutional neural networks (CNNs), recurrent neural networks (RNNs), transformers, and generative adversarial networks (GANs).

[0042] The present device and system may include an artificial intelligence model. The artificial intelligence model may be a single artificial intelligence model or may be implemented as multiple artificial intelligence models. The artificial intelligence model may be composed of a neural network (or artificial neural network) and may include statistical learning algorithms that mimic biological neurons in machine learning and cognitive science. A neural network may refer to a model in general that has problem-solving capabilities by changing the binding strength of synapses through learning, formed by artificial neurons (nodes) that form a network by combining synapses. The neurons of the neural network may include a combination of weights or biases. The neural network may include one or more layers composed of one or more neurons or nodes. For example, the device may include an input layer, a hidden layer, and an output layer. The neural network constituting the device can infer a desired result (output) from an arbitrary input (input) by changing the weights of neurons through learning.

[0043] The processor can create a neural network, train (or learn) a neural network, perform a calculation based on received input data, generate an information signal based on the calculation result, or retrain the neural network. The models of the neural network can include various types of models such as CNN (Convolution Neural Network) such as GoogleNet, AlexNet, VGG Network, R-CNN (Region with Convolution Neural Network), RPN (Region Proposal Network), RNN (Recurrent Neural Network), S-DNN (Stacking-based deep Neural Network), S-SDNN (State-Space Dynamic Neural Network), Deconvolution Network, DBN (Deep Belief Network), RBM (Restrcted Boltzman Machine), Fully Convolutional Network, LSTM (Long Short-Term Memory) Network, Classification Network, etc., but are not limited thereto. The processor can include one or more processors for performing calculations according to the models of the neural network. For example, the neural network can be a deep neural network. It may include a deep neural network.

[0044] Neural networks include CNN (Convolutional Neural Network), RNN (Recurrent Neural Network), perceptron, multilayer perceptron, FF (Feed Forward), RBF (Radial Basis Network), DFF (Deep Feed Forward), LSTM (Long Short Term Memory), GRU (Gated Recurrent Unit), AE (Auto Encoder), VAE (Variational Auto) Encoder), DAE (Denoising Auto Encoder), SAE (Sparse Auto Encoder), MC (Markov Chain), HN (Hopfield Network), BM (Boltzmann Machine), RBM (Restricted Boltzmann Machine), DBN (Depp Belief Network), DCN (Deep Convolutional Network), DN (Deconvolutional Network), DCIGN (Deep Convolutional Inverse Graphics Network), Generative Adversarial Network (GAN), Liquid State Machine (LSM), Extreme Learning Machine (ELM), It will be understood by those skilled in the art that any neural network may be included, including but not limited to ESN (Echo State Network), DRN (Deep Residual Network), DNC (Differentiable Neural Computer), NTM (Neural Turning Machine), CN (Capsule Network), KN (Kohonen Network), and AN (Attention Network).

[0045] According to an exemplary embodiment of the present disclosure, the processor may be configured to perform a process for generating a CNN (Convolution Neural Network) such as GoogleNet, AlexNet, VGG Network, Region with Convolution Neural Network (R-CNN), Region Proposal Network (RPN), Recurrent Neural Network (RNN), Stacking-based deep Neural Network (S-DNN), State-Space Dynamic Neural Network (S-SDNN), Deconvolution Network, Deep Belief Network (DBN), Restrcted Boltzman Machine (RBM), Fully Convolutional Network, Long Short-Term Memory (LSTM) Network, Classification Network, Generative Modeling, eXplainable AI, Continual AI, Representation Learning, AI for Material Design, BERT, SP-BERT, MRC / QA for natural language processing, Text Analysis, Dialog System, GPT-3, GPT-4, Visual Analytics for vision processing, Visual Understanding, Video Synthesis, ResNet for data intelligence, Anomaly Detection, Prediction, Time-Series Forecasting, Various artificial intelligence structures and algorithms, including optimization, recommendation, and data creation, can be utilized, but are not limited thereto. Hereinafter, embodiments of the present disclosure will be described in detail with reference to the attached drawings.

[0046] In the present disclosure, a smart eye patch may refer to any form of electronic device that attaches or incorporates various electronic devices to provide a user (e.g., a patient) with information or guidance regarding eye medication application through digital technology, thereby enhancing the effectiveness of the treatment or processing signals to prevent problems. Meanwhile, the smart eye patch, excluding the attached or incorporated electronic devices, may be a traditional eye patch, or may be a device specifically designed for the smart eye patch according to the present disclosure, but is not limited thereto.

[0047] FIG. 1 is a schematic diagram of a service system (1) including a smart blindfold integrated with the Internet of Things according to one embodiment of the present disclosure.

[0048] Figure 2 is a block diagram of the configuration of the terminal (100) of Figure 1.

[0049] Figure 3 is a block diagram of the smart blindfold (200) of Figure 1.

[0050] A service system (1) according to at least one of the various embodiments of the present disclosure may include a smart eye mask that protects at least one eye of a user, including a communication module, a light-emitting unit, a sensor, and an output unit, and a terminal that communicates with the smart eye mask to obtain eye drop administration log information of the user sensed by the sensor, and controls the operation of the smart eye mask based on the obtained eye drop administration log information of the user.

[0051] Referring to FIG. 1, a service system (1) according to one embodiment of the present disclosure may be implemented by including a terminal (100) and a smart eye mask (200). In this case, the service system (1) may further be implemented by including a server (200) connected to at least one of the terminal (100) and the smart eye mask (200).

[0052] The terminal (100) can perform data communication with the smart eye mask (200) and control the operation of the smart eye mask (200). According to the present disclosure, the data communication can be performed through an application.

[0053] Referring to FIG. 2, the terminal (100) may include a memory (160) and a processor.

[0054] The processor may include a communication module (110), a data receiving unit (120), a data extraction unit (130), a data processing unit (140), and a control unit (150).

[0055] The communication module (110) provides a communication interface environment, so that the terminal (100) can exchange data with the smart eye mask (200).

[0056] The communication module (110) can provide a communication interface environment as needed to support the terminal (100) to exchange data with the server (300).

[0057] The data receiving unit (120) can receive data from the smart blindfold (200) through the communication module (110).

[0058] The data receiving unit (120) can receive data from the server (300) through the communication module (110).

[0059] The data extraction unit (130) can extract information from data of the smart blindfold (200) and / or server (300) received through the data reception unit (120).

[0060] The data processing unit (140) can process data from the smart eye mask (200) and / or server (300) received through the data receiving unit (120) or process data extracted through the data extraction unit (130).

[0061] The data processing unit (140) can generate necessary control signals based on the processed data.

[0062] The control unit (150) can control the overall operation of each component of the processor and further the terminal (100).

[0063] The memory (160) can pre-store various information or update the stored information. The memory (160) can temporarily store data or information processed by each component of the terminal (100).

[0064] The memory (160) may store software, such as programs, or related processing engines, as needed for processing and analyzing data received from the smart blindfold (200). The memory (160) may store information regarding an artificial intelligence learning engine. Such an engine may be implemented within the control unit (150).

[0065] The control unit (150) may include an analysis unit (not shown) that processes and analyzes the received signal of the smart blindfold (200).

[0066] The control unit (150) can control the operation of the smart blindfold (200) based on the content analyzed by the analysis unit.

[0067] The control unit (150) can extract the user's eye drop administration log data from the signal of the smart eye patch (200).

[0068] The control unit (150) can control the operation of a component attached to or built into the smart eye patch (200) based on the extracted user's eye drop administration log data.

[0069] The control unit (150) determines whether the next eye drop administration time has elapsed based on the extracted user eye drop administration log data, and accordingly provides information or guidance on the timing of eye drop administration through the smart eye patch (200). The specific algorithm for this is described in detail in FIGS. 6 and 7.

[0070] Next, the smart eye mask (200) protects at least one eye of the user, and by incorporating digital technology, it can perform not only eye protection but also management functions. Here, the management function may include, for example, various functions for protecting the user's eyes or vision. For convenience, the present disclosure assumes a situation in which the user needs to instill eye drops, and management related to eye drop instillation will be described as an example. However, the present disclosure is not limited thereto.

[0071] As mentioned above, examples of digital technologies incorporated into the smart blindfold (200) include Internet of Things technology and various wired / wireless communication technologies, but are not limited thereto.

[0072] A smart eye patch (200) according to one embodiment of the present disclosure can perform a user's eye drop instillation control operation by being equipped with, built-in to, or connected to at least one indicator, at least one sensor, or an output unit.

[0073] Referring to FIGS. 1 and 3, the smart blindfold (200) may be configured to include a memory (260) and a processor.

[0074] The processor may be configured to include a communication module (210), a sensor unit (220), a light emitting unit (230), an output unit (240), and a control unit (250).

[0075] The communication module (210) provides a communication interface environment, so that the smart eye mask (200) can exchange data with the terminal (100).

[0076] The communication module (210) can provide a communication interface environment as needed to support the smart eye mask (200) to exchange data with the server (300).

[0077] The sensor unit (220) may include at least one sensor to detect a user's input. If the user's input is a touch input, at least one sensor constituting the sensor unit (220) may be a touch sensor.

[0078] The sensor unit (220) can sense and acquire the user's body information. Here, the user's body information may include various information such as eye, blood pressure, or heart rate.

[0079] Depending on the body information, the sensor unit (220) may include an image sensor or various measurement sensors. For example, the image sensor may capture images of the user's eyeball or the area around the eyeball.

[0080] Images of the user's eyes or the area around the eyes captured in this way can be transmitted to a terminal (100) or server (300) and used for monitoring or analysis purposes.

[0081] In this regard, for example, if the terminal (100) is a terminal of a medical institution, the medical institution can analyze the image and control the operation of the smart eye patch (200) related to the timing of eye drop administration according to the user's eye condition. For example, the medical institution can adjust the preset timing of eye drop administration through the smart eye patch (200).

[0082] The light emitting unit (230) can operate according to an operation control signal of a terminal (100) or a server (300).

[0083] The light-emitting unit (230) is a component for performing the above-described indicator function, and can emit light to indicate a status related to the timing of eye drop administration by a user wearing a smart eye patch (200).

[0084] The light emitting unit (230) can be implemented in the form of a light emitting diode (LED) element of a specific color or an LED array.

[0085] The light-emitting portions (230) may be arranged at predetermined intervals and may be arranged in a predetermined shape so that the light-emitting content can be identified by a third party when viewed from the outside.

[0086] The light emitting unit (230) can emit light only in a specific color depending on the user's eye drop administration status according to a control signal from the terminal (100) or server (300).

[0087] The light emitting unit (230) can emit light in a specific pattern depending on the user's eye drop administration status according to a control signal from the terminal (100) or server (300).

[0088] The light-emitting unit (230) may emit light in a specific pattern with a specific color depending on the user's eye drop administration status according to a control signal from the terminal (100) or server (300).

[0089] The light emitting unit (230) may have elements of each color sequentially emit light in a specific pattern according to the user's eye drop administration status in accordance with a control signal from the terminal (100) or server (300).

[0090] The output unit (240) may include at least one of a display capable of outputting an image and a speaker capable of outputting a sound. For convenience, the output unit (240) is described in the present disclosure using a speaker as an example.

[0091] Meanwhile, the output unit (240) is not necessarily an essential component and may be replaced by or operated in conjunction with an external device capable of outputting sound. Such external devices may include an artificial intelligence speaker, an external speaker, or a terminal such as the user's smartphone.

[0092] The control unit (250) can control the operation of each component of the processor.

[0093] The control unit (250) may further include an artificial intelligence engine (not shown) required to sense the user's status.

[0094] In FIGS. 2 and 3, the memory (160, 260) may include at least one type of storage medium among a flash memory type, a hard disk type, an SSD (Solid State Disk type), an SDD (Silicon Disk Drive type), a multimedia card micro type, a card type memory (e.g., SD or XD memory, etc.), a random access memory (RAM), a static random access memory (SRAM), a read-only memory (ROM), an electrically erasable programmable read-only memory (EEPROM), a programmable read-only memory (PROM), a magnetic memory, a magnetic disk, and an optical disk.

[0095] In FIGS. 2 and 3, only one memory (160, 260) is illustrated for convenience, but it is not limited thereto and there may be multiple memories.

[0096] In FIGS. 2 and 3, the memory (160, 260) is illustrated and described as being built into the terminal (100) and smart eye mask (200) for convenience, but is not limited thereto. For example, in FIGS. 2 and 3, the memory (160, 260) may also be implemented in the form of a server located externally or remotely.

[0097] In FIGS. 2 and 3, the memory and processor may be implemented as separate chips. Alternatively, the memory and processor may be implemented as a single chip.

[0098] At least one component may be added or deleted to correspond to the performance of the components illustrated in FIGS. 2 and 3. Furthermore, it will be readily apparent to those skilled in the art that the relative positions of the components may be altered to correspond to the performance or structure of the system.

[0099] Meanwhile, each component illustrated in FIGS. 2 and 3 refers to software and / or hardware components such as Field Programmable Gate Array (FPGA) and Application Specific Integrated Circuit (ASIC).

[0100] FIG. 4 is a diagram illustrating a smart sensor including at least one active area according to one embodiment of the present disclosure.

[0101] Figure 5 is a drawing illustrating the configuration of each active area of ​​Figure 4.

[0102] Referring to FIG. 4, the smart eye mask (200) according to the present disclosure may be composed of an eye protection part and a support part.

[0103] The eye protection device may be formed into a predetermined shape to cover at least one eye of the user. Here, the predetermined shape may be, but is not limited to, a circular, oval, or polygonal shape, similar to a typical eyeglass shape.

[0104] The eye protection device may include a cover made of a material such as cotton over at least a portion of the inner surface located in front of the user's eye.

[0105] The support member may support the eye protection device so that it can perform its function. The support member may have a structure that supports the eye protection device so that it can be attached to the user's body or secured at a predetermined distance. For this purpose, the support member may take various forms, such as a strap or a band.

[0106] The support according to the present disclosure is like a traditional support, and is wrapped around a part of the user's body, i.e., the ear, so that the smart eye mask (200) is positioned in front of the eye to protect the eye.

[0107] For convenience, multiple active areas are indicated in Fig. 4.

[0108] The active area may refer to a physical area where at least one of the sensor unit, light emitting unit, and output unit of the smart eye mask (200) according to the present disclosure can be located.

[0109] Referring to FIG. 4, the first region (410, 420) may be located at the outermost end of the smart blindfold (200).

[0110] The first area (410, 420) can be an area extending from the outermost end of the smart blindfold (200).

[0111] The first area (410, 420) may correspond to the user's temple or upper eyebrow area when the user wears the smart eye mask (200).

[0112] The first region (410, 420) can be moved along the outermost line of the smart blindfold (200).

[0113] The second area (430) may be an area corresponding to a body part of the user, i.e., the upper part of the nose.

[0114] The third area (440, 450) may represent an area corresponding to the area where the user's eyes are located when viewed from the front.

[0115] Referring to Fig. 5, a configuration or combination of each activation area is disclosed.

[0116] For convenience of explanation, FIG. 5 illustrates an example in which a light-emitting unit (510), a sensor unit (520), and an output unit (530) are all provided in one active area. However, the present disclosure is not limited thereto.

[0117] Depending on the embodiment, the output section may be distributed and arranged in the first area (410, 420), the sensor section in the second area (430), and the light emitting section in the third area (440, 450).

[0118] The eye protection device can be manufactured by scanning the user's facial shape and using the eye patch manufacturing device (170) of FIG. 2 based on the scanned facial shape data. This eye patch manufacturing device (170) may be a 3D printer.

[0119] The shape, thickness, etc. of the eye protection device can be determined based on the scanned user's facial shape data.

[0120] The number, position, and combination of at least one of the sensor unit, light emitting unit, and output unit mounted on the eye protection device can be determined by the shape or thickness of the eye protection device or the scanned user's facial shape data.

[0121] Referring to FIGS. 4 and 5, the smart eye patch (200) can provide guidance to both the user (patient) and their guardian regarding the application of eye drops. In this case, the smart eye patch (200) can utilize both auditory and visual information for guidance.

[0122] For example, the smart eye mask (200) can output an eye drop notification as a sound through the output unit (530). Meanwhile, the smart eye mask (200) can provide an eye drop notification by outputting a predetermined light pattern through the light emitting unit (510).

[0123] Additionally, the sound and light pattern provided by the smart eye mask (200) are interrelated and may vary depending on the situation. For example, as the number of eye drop notifications increases or the time for eye drop application approaches, the sound intensity may increase or the light pattern may change.

[0124] Through this, users and guardians can immediately and intuitively recognize the situation of eye drop application, thereby minimizing cases of eye drop omission.

[0125] Meanwhile, an application running on a terminal (100) communicating with a smart eye patch (200) may provide eye drop notifications or information in the form of text, audio, images, or video, or may provide information or information through sound or vibration patterns. This allows both the user (patient) and their caregiver to be aware of the eye drop notification situation.

[0126] The specific operation control contents for the smart eye mask (200) of the terminal (100) of the aforementioned Fig. 2 are described in detail with reference to Figs. 6 and 7.

[0127] Figures 6 and 7 are flowcharts illustrating a method for controlling the operation of a smart blindfold (200) according to the present disclosure.

[0128] In operation S110, the terminal (100) can obtain the user's medication log information from the smart eye mask (200).

[0129] In operation S120, the terminal (100) can analyze the user medication log information of the acquired smart eye mask (200).

[0130] In operation S130, the terminal (100) can determine whether the next medication time has arrived based on the user's medication log information analyzed in operation S120.

[0131] In operation S140, if the user's next medication time has arrived based on the judgment result in operation S130, the terminal (100) can generate a medication guidance signal and transmit it to the smart eye mask (200).

[0132] On the other hand, if the user's next medication time has not arrived according to the judgment result in operation S130, the terminal (100) can operate as in FIG. 7 or obtain new medication log information.

[0133] Figure 7 may be a detailed process of Figure 6 or may be a separate process.

[0134] In Fig. 7, the operations of S110-S140 are the same as those in Fig. 6 described above, and the corresponding contents are cited and redundant descriptions are omitted here.

[0135] If the terminal (100) determines in operation S130 that the next medication time has arrived, it can generate a medication guidance signal as described above and transmit it to the smart eye mask (S140, FIG. 7).

[0136] On the other hand, if the terminal (100) determines in operation S130 that the next medication time has not arrived, it can perform the following process.

[0137] In operation S210, the terminal (100) can determine whether the time remaining until the next medication time has not yet arrived is within the first threshold time.

[0138] In operation S220, if the terminal (100) determines that the next medication time has not yet arrived but the remaining time until then is within the first threshold time, the terminal (100) can generate a first medication guidance signal and transmit it to the smart eye mask (200).

[0139] In operation S230, the terminal (100) can determine whether the next medication time has not yet arrived but the remaining time until then is not within the first threshold time as a result of the judgment in operation S210, and whether it is within the nth threshold time again.

[0140] In operation S240, if the terminal (100) determines that the next medication time has not yet arrived but the remaining time until then is within the nth threshold time based on the judgment result of operation S230, it can generate an nth medication guidance signal and transmit it to the smart eye mask (200).

[0141] If the terminal (100) determines that the next medication time has not yet arrived but the remaining time until then is not within the n threshold time, it can obtain new medication log information.

[0142] In order to distinguish the medication guidance signals, unlike as shown in FIG. 7, the medication guidance signal of operation S140 may be expressed as the first medication guidance signal, the medication guidance signal of operation S220 may be expressed as the second medication guidance signal, etc.

[0143] Below, the medication guidance signals or guides are described in more detail.

[0144] In the present disclosure, the step of controlling the operation of the smart eye patch (200) in the terminal (100) can be broadly divided depending on whether the user's eye drop administration time has elapsed as a result of the judgment.

[0145] The step of controlling the operation of the smart eye mask (200) in the terminal (100) can be such that, if it is determined that the user's eye drop administration time has elapsed, the light emitting part included in the smart eye mask (200) can be controlled to emit light in a first color.

[0146] The step of controlling the operation of the smart eye mask (200) in the terminal (100) can be such that, if it is determined that the user's eye drop administration time has elapsed, the smart eye mask (200) can be controlled to output a sound.

[0147] The step of controlling the operation of the smart eye patch (200) in the terminal (100) may further perform an operation of determining whether there is time less than the first threshold time remaining until the next eye drop administration time, if the judgment or analysis result shows that the user's eye drop administration time has passed and the next eye drop administration time has not passed.

[0148] As a result of the judgment, if the remaining time is less than the first threshold time until the next eye drop administration time, the light emitting part of the smart eye patch (200) can be controlled to light in a second color.

[0149] The analysis results may further determine whether the time for administering the next eye drop has not passed, but whether there is time remaining until the time for administering the next eye drop, which is greater than or equal to the first threshold time and less than or equal to the second threshold time.

[0150] If the analysis result shows that the next eye drop administration time has not passed but the remaining time is greater than or equal to the first threshold time and less than or equal to the second threshold time until the next eye drop administration time, the terminal (100) can control the light emitting part of the smart eye patch (200) to emit light in a third color.

[0151] In the above, the first color may be red (RG), the second color may be blue (B), and the third color may be green (G), but is not limited thereto.

[0152] In the present disclosure, the user's medication log information can basically be obtained by the user wearing the smart eye patch (200) and touching the touch sensor after instilling eye drops.

[0153] A user may forget to touch the touch sensor. Therefore, if the terminal (100) detects that the user is wearing the smart eye mask (200), it can provide information on whether medication has been administered, i.e., guidance or guide information on whether the touch sensor has been touched. This guidance or guide information can be output through the smart eye mask (200) in the form of color or sound.

[0154] Accordingly, when the smart eye mask (200) detects that the user is wearing it, it can provide information on whether medication has been administered, i.e., guidance or guide information on whether the touch sensor has been touched. This guidance or guide information can be provided in the form of color or sound.

[0155] The terminal (100) and / or smart eye patch (200) can determine the user's eye drop administration time based on the time the user touches the touch sensor. However, there may be a time difference between the time the user administers the eye drop and the time the user touches the touch sensor. Therefore, the interval or length of the aforementioned threshold time can be determined by taking this time difference into account.

[0156] If the touch sensor touch point is at a consistent interval for the user's eye drop administration, it can be accepted as the administration point. In this case, the consistent interval can also include a range within a predetermined time period.

[0157] However, if the touch sensor touch point for the user's eye drop administration is not at a constant interval, the terminal (100) and / or smart eye patch (200) may control the intensity of the information of the aforementioned medication guidance signal differently. For example, the sound may be made louder or the number of medication guidance or guides may be increased.

[0158] The terminal (100) and / or smart eye mask (200) may calculate the remaining time until the next medication time if it detects that the user touches an inactive area other than the active area equipped with a touch sensor. This may be to provide guidance on the next medication time, as touching the inactive area, for example, may indicate the removal of the smart eye mask (200).

[0159] The terminal (100) and / or smart eye mask (200) can provide an appropriate medication time guidance guide or control the contents of the scheduled medication guidance guide differently depending on the remaining time until the next medication time calculated.

[0160] If the user does not wear the eye mask even after the expected time for medication has elapsed, the terminal (100) and / or the smart eye mask (200) can provide a guide for wearing the smart eye mask (200) through the smart eye mask (200) and the user's registered terminal (not shown).

[0161] When an event occurrence signal is detected while the user is wearing the smart eye mask (200), the terminal (100) and / or the smart eye mask (200) can provide guidance on the next medication time based on the detected event. The event occurrence signal may include, for example, a foreign substance detected inside or outside the smart eye mask (200).

[0162] The terminal (100) and / or the smart eye mask (200) can control the medication guidance guide differently depending on the space in which the user wearing the smart eye mask (200) is located. For example, if the space in which the user wearing the smart eye mask (200) is located is a private space such as a home, the guidance guidance level can be set to the maximum. Otherwise, the level can be determined (medium or minimum) based on the type or type of the identified space, and the guidance guidance level can be controlled to be adjusted accordingly.

[0163] Meanwhile, the terminal (100) and / or the smart eye mask (200) can control the method of outputting the medication guidance guide differently depending on the space in which the user wearing the smart eye mask (200) is located. For example, as described above, if the user is located in a private space, the medication guidance guide can be provided not only through the smart eye mask (200) but also through or in conjunction with various external devices (e.g., TV, external speakers, etc.) that can be linked.

[0164] The terminal (100) and / or smart eye mask (200) can control the medication guidance differently based on current time information. For example, providing the medication guidance at the same level during daytime and late at night may cause discomfort to the user as well as third parties, so it may be desirable to provide the guidance at an adjusted level.

[0165] The present disclosure may also provide a medication guidance guide in a combined form of two or more of the embodiments described above.

[0166] Meanwhile, the disclosed embodiments may be implemented in the form of a recording medium storing computer-executable instructions. The instructions may be stored in the form of program code, and when executed by a processor, may generate program modules to perform the operations of the disclosed embodiments. The recording medium may be implemented as a computer-readable recording medium.

[0167] Computer-readable storage media include all types of storage media that store instructions that can be deciphered by a computer. Examples include read-only memory (ROM), random access memory (RAM), magnetic tape, magnetic disks, flash memory, and optical data storage devices.

[0168] The disclosed embodiments have been described with reference to the attached drawings as described above. Those skilled in the art will understand that the present disclosure can be implemented in forms other than the disclosed embodiments without altering the technical spirit or essential features of the present disclosure. The disclosed embodiments are illustrative and should not be construed as limiting.

Claims

1. In a smart blindfold with the Internet of Things, Communication module; An eye protection member formed into a predetermined shape to cover at least one eye of the user; and The above eye protection part includes a support member that supports the eye protection part to be fixed to the user's body, The above eye protection part, comprising at least one light emitting element and at least one sensor, Smart blindfold.

2. In claim 1, The at least one light emitting unit and the at least one sensor are attached to one end of the eye protection unit. Smart blindfold.

3. In claim 2, One end of the eye protection device extends to a position corresponding to the user's temple area or to a position corresponding to the upper part of the user's eyebrow. Smart blindfold.

4. In claim 1, At least one sensor above, including a touch sensor that senses the user's touch input, Smart blindfold.

5. In claim 1, The above eye protection part, Scan the user's facial shape and create a 3D printer based on the scanned facial shape data. Smart blindfold.

6. In a terminal communicating with a smart eye mask including a light emitting part and a sensor, Communication module; A receiving unit for receiving a signal from the smart blindfold; An analysis unit that processes and analyzes the received smart eye mask signal; and Including a control unit that controls the operation of the smart blindfold according to the contents analyzed in the above analysis unit. terminal.

7. In claim 5, The signal of the smart blindfold received above is, Containing information sensed through the above sensor, terminal.

8. In claim 7, The above control unit, Extracting the user's eye drop administration log data from the signal of the above smart eye patch, terminal.

9. In claim 8, The above control unit, Controlling the operation of the light-emitting unit based on the extracted user's eye drop administration log data, terminal.

10. In claim 9, The above control unit, If the next eye drop administration time has passed based on the user's eye drop administration log data extracted above, the light emitting part of the smart eye patch is controlled to emit light in the first color. terminal.

11. In claim 10, The above control unit, If the next eye drop administration time has passed based on the user's eye drop administration log data extracted above, the output unit of the smart eye patch is controlled to output a sound. terminal.

12. In claim 11, The above control unit, Based on the extracted user's eye drop administration log data, if the next eye drop administration time has passed, the smart eye patch's output unit is controlled to output a sound together with the first color light emission of the light emitting unit. terminal.

13. In claim 9, The above control unit, Based on the user's eye drop administration log data extracted above, if the next eye drop administration time has not passed but less than the first threshold time remains, the light emitting part of the smart eye patch is controlled to output a second color. terminal.

14. In claim 13, The above control unit, Based on the extracted user's eye drop administration log data, if there is a first threshold time or more and a second threshold time less than the next eye drop administration time, the light emitting part of the smart eye patch is controlled to output a third color. terminal.

15. A method for controlling the operation of a terminal that controls a smart eye mask by communicating with the smart eye mask including a light-emitting unit and a sensor, A step of obtaining the user's eye drop administration log information from the smart eye patch; A step of analyzing the user's eye drop administration log information obtained above; A step for determining whether the next eye drop administration time has passed as a result of the above analysis; and A step of generating a user's eye drop administration guidance signal based on the above judgment result and transmitting it to the smart eye patch to control the operation of the smart eye patch, How to control motion.

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