Detecting human emotions using electroencephalography (EEG) using dynamic programming approach

The relation between human emotions and EEG signals have been actively studied during the last few decades. In this paper, we study a novel attempt to measure the human brain activity and analyze its signals using electroencephalography (EEG) in order to classify the human emotions indicated by the brain wavelets. The study will measure the brain wavelets of female students in order to detect the emotions of happiness, sadness, and fear. This study will use specially designed sensors placed around the scalp. The measured signals transfer to a computing device. The data collected analyze by a software system, which developed by our team. We use dynamic programming to extract the maximum number of quality service that provides to the user when the device captures specific signals for each emotion.