Provided is a data processing apparatus including a signal data processor configured to collect signal data detected through polysomnography, to extract feature data by analyzing a feature of the collected signal data, and to transform the extracted feature data to time series data; and a sleep stage classification model processor configured to input the processed signal data to a pre-generated sleep stage classification model, and to classify a sleep stage corresponding to the signal data. The signal data processor is configured to extract feature data by analyzing a feature of each of an electroencephalographic (EEG) signal, an electro-oculographic (EOG) signal, and an electromyographic (EMG) signal with respect to the signal data, and to transform the extracted feature data to an epoch unit of time series data to input the extracted feature data to the pre-generated sleep stage classification model.
DATA PROCESSING APPARATUS FOR AUTOMATICALLY DETERMINING SLEEP DISORDER USING DEEP RUNNING AND OPERATION METHOD OF THE DATA PROCESSING APPARATUS