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Deploying a Web-based Electroencephalography Data Analysis Virtual Laboratory

Publication Type : Conference Paper

Thematic Areas : Biotech, Learning-Technologies, Medical Sciences

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 : biotechnology, Computational Neuroscience Laboratory

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.

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