Abstract: Disclosed is an apparatus for memory enhancement based on electroencephalogram according to one embodiment of the present invention. According to the present invention, it is possible to identify forgotten items during retrieval in a re-learning process based on a user's brain signals measured in an initial learning process by means of a brain signal measurement unit capable of measuring brain signals, and provide the user with repetitive learning depending on the user's electrophysiological characteristics, resulting in a more effective enhancement of memory.

Abstract: An automatic sleep stage classification system for reducing the variation in performance between users using a contrastive learning method according to one embodiment of the present invention includes: a user terminal that measures a user's biosignal and preprocesses the user's measured biosignal; and a classification server that receives the user's preprocessed biosignal from the user terminal, extracts the user's unique biosignal feature, extracts a similar feature by comparing the user's extracted unique biosignal feature and the user's biosignal feature for contrastive learning, and classifies sleep stages based on the extracted similar feature, wherein the user's biosignal includes at least one of the user's electroencephalography (EEG), electrooculography (EOG), electrocardiogramalectromyography (EMG), respiratory effort signals, pulse, oxygen saturation (SpO2), and blood flow.

Abstract: A vehicle light includes: a light lens having a base panel made of a transparent plastic material, an outer paint layer disposed on an outer surface of the base panel, and an inner paint layer disposed on an inner surface of the base panel and including a light-transmitting hole formed therein; and a light source installed to be spaced apart from the light lens, in which light from the light source is transmitted out of the light lens through the light-transmitting hole and the base panel.