Abstract: A system for and a method of analyzing a corneal lesion using an anterior segment image according to the present invention. The system includes: an image acquisition unit configured to acquire an anterior segment image from the eyeball of a subject, a feature extractor configured to extract feature information on a position and a cause of a lesion in the cornea from the anterior segment image by applying a convolution layer to the anterior segment image through machine learning on the basis of a database in which clinical information pre-acquired by analyzing positions and causes of lesions in the corneas of subjects is stored; and a result determination unit configured to identify a position of the cornea from anterior segment image using the feature information and to analyze and determine the position and the cause of the lesion in the cornea from the position of the cornea.

Abstract: A system for and a method of analyzing a corneal lesion using an anterior segment image according to the present invention. The system includes: an image acquisition unit configured to acquire an anterior segment image from the eyeball of a subject, a feature extractor configured to extract feature information on a position and a cause of a lesion in the cornea from the anterior segment image by applying a convolution layer to the anterior segment image through machine learning on the basis of a database in which clinical information pre-acquired by analyzing positions and causes of lesions in the corneas of subjects is stored; and a result determination unit configured to identify a position of the cornea from the anterior segment image using the feature information and to analyze and determine the position and the cause of the lesion in the cornea from the position of the cornea.

Abstract: A method and system for diagnosis of a cataract, using deep learning, wherein deep learning predicts the degree of progression of a cataract from slit lamp examination result images and retroillumination examination result images and the severity is assessed on the basis of the prediction, whereby a therapeutic plan is established. A method for diagnosis of a cataract, using deep learning may include: receiving slit lamp examination result images and health diagnosis results of a subject; inputting the examination result images into a deep learning prediction model to predict a degree of progression of a cataract in the lens nucleus and determining whether the subject is affected by a cataract; assessing the severity of the cataract on the basis of the degree of progression of the cataract in the lens nucleus; and using the severity of the cataract or the health examination result to determine a cataract treatment.

Abstract: The present invention relates to a device for regenerating nerve cells and suppressing immune diseases, and more particularly, to a device for regenerating nerve cells and suppressing immune diseases, which uses a contact lens containing a conductive material to increase the effect of microcurrent on nerve cell regeneration and immune response suppression. The device for regenerating nerve cells and suppressing immune diseases comprises: a contact lens comprising a body configured to be worn on a cornea, and a conductive material inserted into the body and serving to induce a microcurrent generated outside the body; a plurality of channels configured to come into close contact with skins around eyes and to generate a flow of microcurrent on upper part of the contact lens; and a signal supply unit configured to supply electrical signals to the plurality of channels.

Abstract: An apparatus for controlling a bidirectional resonant DC-DC converter includes a bidirectional resonant DC-DC converter that includes a primary-side full-bridge circuit that is coupled to the input side, a secondary-side full-bridge circuit that is coupled to the output side, and a resonant tank that is coupled between the primary-side full-bridge circuit and the secondary-side full-bridge circuit, and a PWM control unit that performs PWM control on the primary-side full-bridge circuit and the secondary-side full-bridge circuit and performs phase shift PWM control and dead-time PWM control.

Abstract: Provided is a diagnosis system for anterior eye diseases. An image obtainer obtains an anterior eye image of an image obtainer configured to obtain an anterior eye image of a subject. A characteristic extractor extracts characteristic information of the obtained anterior eye image on the basis of a machine-learning model. A disease analyzer determines whether or not an anterior eye of the subject has a disease and classifying a disease class according to the extracted characteristic information.

Abstract: The present invention relates to a device for regenerating nerve cells and suppressing immune diseases, and more particularly, to a device for regenerating nerve cells and suppressing immune diseases, which uses a contact lens containing a conductive material to increase the effect of microcurrent on nerve cell regeneration and immune response suppression. The device for regenerating nerve cells and suppressing immune diseases comprises: a contact lens comprising a body configured to be worn on a cornea, and a conductive material inserted into the body and serving to induce a microcurrent generated outside the body; a plurality of channels configured to come into close contact with skins around eyes and to generate a flow of microcurrent on upper part of the contact lens; and a signal supply unit configured to supply electrical signals to the plurality of channels.

Abstract: Disclosed is a method of measuring a refractive error using a reflection image of a pupil for a visible ray, the method capable of diagnosing and self-examining a refractive error using only an image captured by a smartphone camera. The method may include obtaining an image by projecting a visible ray, using a flash, onto the retina of a subject and capturing, using a smartphone camera, a shape and location of the image reflected in the pupil of the subject, applying the image to a residual neural network (ResNet) model trained using data of an ImageNet based on clinical information into which result values of a refractive error of the subjects have been incorporated, and outputting the refractive error of the image and a measurement factor measured to determine the refractive error based on the shape and the location reflected in the pupil in a process of deriving the refractive error of the image.

Abstract: A system for and a method of analyzing a corneal lesion using an anterior segment image according to the present invention. The system includes: an image acquisition unit configured to acquire an anterior segment image from the eyeball of a subject, a feature extractor configured to extract feature information on a position and a cause of a lesion in the cornea from the anterior segment image by applying a convolution layer to the anterior segment image through machine learning on the basis of a database in which clinical information pre-acquired by analyzing positions and causes of lesions in the corneas of subjects is stored; and a result determination unit configured to identify a position of the cornea from the anterior segment image using the feature information and to analyze and determine the position and the cause of the lesion in the cornea from the position of the cornea.

Abstract: A vision assistance apparatus may include an image acquisition unit configured to acquire an image by capturing the scene of the front which a user watches, a sensor unit configured to acquire sensing information on objects located in front of the user, a control unit configured to analyze the image acquired by the image acquisition unit and generate a notification signal for the front scene through an analysis result of the image and the sensing information acquired by the sensor unit, and an output unit configured to provide the user with the notification signal generated by the control unit in the form of sound.

Abstract: A battery charging method for an on-board charger (OBC) includes: applying, by a controller, an output voltage of a first converter to a second converter by controlling the output voltage based on a result of a comparison between a battery load voltage and a battery rated voltage; controlling, by the controller, the second converter to perform a frequency modulation on the output voltage using a low-speed frequency modulation method or a high-speed frequency modulation method based on a result of the control of the output voltage; and generating, by the controller, a frequency harmonic of a system frequency in a battery current based on a modulation method used to perform the frequency modulation. An output voltage of the first converter is controlled based on a load voltage state of a battery and applied to the second converter.

Abstract: Disclosed is a method of measuring a refractive error using a reflection image of a pupil for a visible ray, the method capable of diagnosing and self-examining a refractive error using only an image captured by a smartphone camera. The method may include obtaining an image by projecting a visible ray, using a flash, onto the retina of a subject and capturing, using a smartphone camera, a shape and location of the image reflected in the pupil of the subject, applying the image to a residual neural network (ResNet) model trained using data of an ImageNet based on clinical information into which result values of a refractive error of the subjects have been incorporated, and outputting the refractive error of the image and a measurement factor measured to determine the refractive error based on the shape and the location reflected in the pupil in a process of deriving the refractive error of the image.

Abstract: Provided is a diagnosis system for anterior eye diseases. An image obtainer obtains an anterior eye image of an image obtainer configured to obtain an anterior eye image of a subject. A characteristic extractor extracts characteristic information of the obtained anterior eye image on the basis of a machine-learning model. A disease analyzer determines whether or not an anterior eye of the subject has a disease and classifying a disease class according to the extracted characteristic information.

Abstract: A vision assistance apparatus may include an image acquisition unit configured to acquire an image by capturing the scene of the front which a user watches, a sensor unit configured to acquire sensing information on objects located in front of the user, a control unit configured to analyze the image acquired by the image acquisition unit and generate a notification signal for the front scene through an analysis result of the image and the sensing information acquired by the sensor unit, and an output unit configured to provide the user with the notification signal generated by the control unit in the form of sound.

Abstract: The present disclosure relates to a method for preparing a Graves' ophthalmopathy phenotype animal model, the method including a step of administering zymosan A to a subject other than humans, a Graves' ophthalmopathy phenotype animal model prepared thereby, and a method for screening a therapeutic material for alleviation or treatment of Graves' ophthalmopathy. By using the method for preparing a Graves' ophthalmopathy phenotype animal model, which includes a step of administering zymosan A to a subject other than humans according to the present disclosure, an experimental animal model for Graves' ophthalmopathy, which simultaneously exhibits blepharitis, orbital tissue inflammation, and exophthalmos, may be obtained. In addition, the animal model prepared by the preparation method of the present disclosure may be advantageously used for researching the development of a therapeutic agent for Graves' ophthalmopathy the etiology of which has not been yet accurately revealed.

Abstract: A battery charging method for an on-board charger (OBC) includes: applying, by a controller, an output voltage of a first converter to a second converter by controlling the output voltage based on a result of a comparison between a battery load voltage and a battery rated voltage; controlling, by the controller, the second converter to perform a frequency modulation on the output voltage using a low-speed frequency modulation method or a high-speed frequency modulation method based on a result of the control of the output voltage; and generating, by the controller, a frequency harmonic of a system frequency in a battery current based on a modulation method used to perform the frequency modulation. An output voltage of the first converter is controlled based on a load voltage state of a battery and applied to the second converter.