Publication Type : Conference Paper
Thematic Areas : Learning-Technologies, Medical Sciences, Biotech
Publisher : Third International Conference on Computing and Network Communications (CoCoNet’19) (accepted).
Source : Third International Conference on Computing and Network Communications (CoCoNet’19) (accepted), Trivandrum, Kerala, India, 2019.
Url : https://scholar.google.com/scholar?oi=bibs&cluster=12226035599432383457&btnI=1&hl=en
Campus : Amritapuri
School : School of Biotechnology
Center : Amrita Mind Brain Center, Biotechnology, Computational Neuroscience and Neurophysiology
Department : Computational Neuroscience Laboratory, biotechnology
Year : 2020
Abstract : A majority of the analysis platforms for electroencephalography (EEG) data are implemented on platforms that not easily available for learners or for resource-limited environments. In this paper, we implemented an online laboratory for EEG analysis using JavaScript, while making the user interface easy and viable for non-programmers and experimentalists and as a learning platform. This virtual laboratory platform implements common EEG analysis techniques like power spectral density extraction, channel extraction, filtering and learning primitives allowing users to upload and analyse EEG data.
Cite this Research Publication : J. Alphonse and Dr. Shyam Diwakar, “Deploying a Web-based Electroencephalography Data Analysis Virtual Laboratory”, in Proceedings of the Third International Conference on Computing and Network Communications (CoCoNet’19) (accepted), Trivandrum, Kerala, India, 2019.