Control of an Electrical Prosthesis With an SSVEP-Based BCI
By Gernot R. Müller-Putz, Gert Pfurtscheller. IEEE Transactions on Biomedical Engineering, 2008
609 citations recorded by the source corpus.
Subfields: Cellular and Molecular Neuroscience, Cognitive Neuroscience, Electrical and Electronic Engineering
View Paper: https://www.semanticscholar.org/paper/b2451d7a84477eee22825c565ba42c0597828575
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
- Brendan Z. Allison
- Luis F. Nicolás-Alonso
- Jaime Gómez Gil
- Eric W. Sellers
- Bernhard Graimann
- Jinchang Ren
- Jaime Zabalza
- Huimin Zhao
In Cognitive Neuroscience
- Brendan Z. Allison
- Gert Pfurtscheller
- Luis F. Nicolás-Alonso
- Jaime Gómez Gil
- Bernhard Graimann
- Eric W. Sellers
- Yang Jiang
- Xiaopeng Zhao
In Electrical and Electronic Engineering
- Luis F. Nicolás-Alonso
- Jaime Gómez Gil
- Eric W. Sellers
- Brendan Z. Allison
- Bernhard Graimann
- Jinchang Ren
- Jaime Zabalza
- Huimin Zhao
Citations in the corpus
- Quo vadis artificial intelligence? (2022, background): “In the laboratory environment, researchers have managed to achieve non-invasive implementation for writing and spelling [91, 92], prosthetic/exoskeleton control [93], and for general-purpose communication [94].”
- EEG-Based Brain-Computer Interfaces Using Motor-Imagery: Techniques and Challenges (2019, methodology): “Müller-Putz and Pfurtschscheller [132] implemented an SSVEP-based robotic arms system with 4 flickering stimuli, each one representing a different function for the arm: later movement to the left or right and opening or closing of the hand.”
- A comprehensive review of EEG-based brain–computer interface paradigms (2019, positive): “Muller-Putz and Pfurtscheller [126] applied SSVEP in a hand prosthesis using four-class classification with LED flicker at 6, 7, 8 and 13 Hz.”
- Frequency Recognition in SSVEP-Based BCI using Multiset Canonical Correlation Analysis (2013, background): “[4], [5], [6], [7]. In recent years, SSVEP-based BCI has been increasingly studied since it requires less training to the user and provides relatively higher information transfer rate (ITR) [8], [9], [10], [11]. When subject focuses attention on the repetitive flicker of a visual stimulus, SSVEP is e”
- Brain-Computer Interfaces: A Gentle Introduction (2009, background): “In fact, several approaches have been investigated to control prostheses with invasive and non-invasive BCIs [39, 40, 44].”
- Brain Computer Interfaces, a Review (2012, background): “[13] presented a novel neuroprosthetic device for the restoration of the grasp function for people spinal cord injuries.”