On Using Python to Run, Analyze, and Decode EEG Experiments

Colin Conrad (), Om Agarwal, Carlos Calix Woc, Tazmin Chiles, Daniel Godfrey, Kavita Krueger, Valentina Marini, Alexander Sproul and Aaron Newman
Additional contact information
Colin Conrad: Dalhousie University
Om Agarwal: Dalhousie University
Carlos Calix Woc: Dalhousie University
Tazmin Chiles: Dalhousie University
Daniel Godfrey: Dalhousie University
Kavita Krueger: Dalhousie University
Valentina Marini: Dalhousie University
Alexander Sproul: Dalhousie University
Aaron Newman: Dalhousie University

A chapter in Information Systems and Neuroscience, 2020, pp 287-293 from Springer

Abstract: Abstract As the NeuroIS field expands its scope to address more complex research questions with electroencephalography (EEG), there is greater need for EEG analysis capabilities that are relatively easy to implement and adapt to different protocols, while at the same time providing an open and standardized approach. We present a series of open source tools, based on the Python programming language, which are designed to facilitate the development of open and collaborative EEG research. As supplementary material, we demonstrate the implementation of these tools in a NeuroIS case study and provide files that can be adapted by others for NeuroIS EEG research.

Keywords: Research methods; Python; Machine learning; Open science; Brain-computer interface (search for similar items in EconPapers)
Date: 2020
References: Add references at CitEc
Citations:

There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:lnichp:978-3-030-28144-1_32

Ordering information: This item can be ordered from
http://www.springer.com/9783030281441

DOI: 10.1007/978-3-030-28144-1_32

Access Statistics for this chapter

More chapters in Lecture Notes in Information Systems and Organization from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().