Brain-Computer Interfaces: A Gentle Introduction
By Bernhard Graimann, Brendan Z. Allison, Gert Pfurtscheller. 2009
364 citations recorded by the source corpus.
Subfields: Cellular and Molecular Neuroscience, Cognitive Neuroscience, Electrical and Electronic Engineering
View Paper: https://www.semanticscholar.org/paper/43355cf5aed2dac7cd4b5ee023c086c44f5db5f6
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Cellular and Molecular Neuroscience
- Ayman Atia
- Jinchang Ren
- Lukas Cavigelli
- Luca Benini
- Jaime Zabalza
- Huimin Zhao
- Sarah N. Abdulkader
- Mostafa-Sami M. Mostafa
In Cognitive Neuroscience
- Ayman Atia
- Jinchang Ren
- Luca Benini
- Jaime Zabalza
- Huimin Zhao
- Sarah N. Abdulkader
- Mostafa-Sami M. Mostafa
- Natasha M. J. Padfield
In Electrical and Electronic Engineering
- Luca Benini
- Ayman Atia
- Jinchang Ren
- Lukas Cavigelli
- Jaime Zabalza
- Huimin Zhao
- Sarah N. Abdulkader
- Mostafa-Sami M. Mostafa
Citations in the corpus
- LSTM-Based EEG Classification in Motor Imagery Tasks (2018, background): “Other tunable parameters in LSTM cells are randomly initialized by random values of uniform distribution within [0, 1].”
- EEG-Based Brain-Computer Interfaces Using Motor-Imagery: Techniques and Challenges (2019, methodology): “The performance of SMR-BCIs is heavily dependent on the neurophysiological and psychological state of the user, with the control of SMR activity being found to be challenging for many users [9,23].”
- EEG-TCNet: An Accurate Temporal Convolutional Network for Embedded Motor-Imagery Brain–Machine Interfaces (2020, background): “cation between humans and external devices by analyzing neural activity of the human brain, typically recorded with noninvasive electroencephalography (EEG) [1].”
- Brain computer interfacing: Applications and challenges (2015, methodology): “Thus it has been used by epilepsy patients before surgery [103].”