Abstract: A step of extracting components of one or more frequency bands from a first section of an EEG; a step of calculating a first index for each of the components of one or more frequency bands, wherein the first index is calculated based on a degree to which a magnitude of each of the components of one or more frequency bands with respect to a magnitude of a predetermined reference component in the first section exceeds a predetermined threshold value; a step of calculating a probability value for each of one or more patient statuses from the first index for each of the components of one or more frequency bands using a trained artificial neural network; and a step of determining the consciousness level of the patient based on the probability value for each of the one or more calculated patient statuses.

Abstract: The present disclosure relates to an acupoint stimulation device and an acupoint stimulation method using the same. The acupoint stimulation device includes: a power supply unit configured to supply power; a controller configured to generate an electrical stimulus signal applied to a skin of the subject; and an electrical stimulation unit including two or more electrodes configured to receive power from the power supply unit and to supply the stimulus signal to the acupoint area, wherein the electrodes are arranged in a state of being electrically insulated from each other and are in electrical contact with the skin of the subject. Thereby, it is possible to provide an appropriate amount of stimulation required for treatment and symptom relief by providing stimulation to an accurate acupoint position.

Abstract: A step of extracting components of one or more frequency bands from a first section of an EEG; a step of calculating a first index for each of the components of one or more frequency bands, wherein the first index is calculated based on a degree to which a magnitude of each of the components of one or more frequency bands with respect to a magnitude of a predetermined reference component in the first section exceeds a predetermined threshold value; a step of calculating a probability value for each of one or more patient statuses from the first index for each of the components of one or more frequency bands using a trained artificial neural network; and a step of determining the consciousness level of the patient based on the probability value for each of the one or more calculated patient statuses.