EEG-based tonic cold pain intensity assessment using CNN-LSTM

Pain has gradually become a problem that plagues human beings, to objectively identify different levels of pain in brain activity signals, this paper has designed a cold tenderness experiment to obtain acute pain signals, and the pre-treated signals have been analyzed by a deep learning network model to identify four levels of pain signals, and the classification accuracy reached 87.67%. It has been proven that deep learning models can effectively distinguish between different levels of pain signals.