Mood Detector - On Using Machine Learning to Identify Moods and Emotions

This paper presents the design and implementation of the Mood Detector application, which is designed to detect the mood and emotional state of the user by analyzing 3 physical parameters (pulse, skin electro conductivity and temperature) by using a machine learning algorithm which is trained with data from the users. The application has been tested repetitively until the results generated by the learning algorithm have been validated 100%, thus confirming that the machine learning algorithms provides the correct output. The application also integrates a music recommender system, which suggests the user to listen to specific playlists, designed according to his currently detected mood.