Deep learning algorithm for neurological disorder classification.

neurlal-network

Link – A natural evolution optimization based deep learning algorithm for neurological disorder classification. Abstract Neurological disorders are one of the significant problems of the nervous system that affect essential functions of the human brain and spinal cord. Monitoring brain activity through electroencephalography (EEG) has become an important tool in the diagnosis of brain disorders. […]

Machine Learning Techniques for Divergent Thinking EEG Data.

creativity

Link – Classifying Creativity: Applying Machine Learning Techniques to Divergent Thinking EEG Data. Abstract Prior research has shown that greater EEG alpha power (8-13 Hz) is characteristic of more creative individuals, and more creative task conditions. The present study investigated the potential for machine learning to classify more and less creative brain states. Participants completed […]

EEG classification across sessions and subjects through transfer learning

Link – EEG classification across sessions and across subjects through transfer learning in motor imagery-based brain-machine interface system. Abstract Transfer learning enables the adaption of models to handle mismatches of distributions across sessions or across subjects. In this paper, we proposed a new transfer learning algorithm to classify motor imagery EEG data. By analyzing the […]