A brain–computer interface (BCI) for the locked-in: comparison of different EEG classifications for the thought translation device

  title={A brain–computer interface (BCI) for the locked-in: comparison of different EEG classifications for the thought translation device},
  author={Thilo Hinterberger and Andrea K{\"u}bler and Jochen Kaiser and Nicola Neumann and Niels Birbaumer},
  journal={Clinical Neurophysiology},
The Thought Translation Device: structure of a multimodal brain-computer communication system
The Thought Translation Device (TTD) is a brain-computer-interface (BCI) which successfully enabled totally paralyzed patients to communicate by using their brain potentials only. An extended version
EEG-Based Brain-Computer Interface System
The current approaches and methods used in BCI research are outlined, with emphasis on the signal processing part of the system, consisting of preprocessing, feature extraction, and classification.
A self-paced brain-computer interface system with a low false positive rate.
An improved SBCI that uses features extracted from three neurological phenomena to detect an intentional control command in noisy EEG signals is proposed, achieving a high true positive (TP) to false positive (FP) ratio.
EEG Based Brain Computer Interface for Speech Communication: Principles and Applications
There is enough evidence that the direct speech prediction from the neurological signals is a promising technology with fruitful results and challenging issues.
Brain-Computer Interface with cortical electrical activity recording
The main goal of the study was to discriminate the specific neuronal pattern related to the animal's control action against background brain activity of freely-moving animal against one of the generic NPLS algorithm.
Toward functioning and usable brain–computer interfaces (BCIs): A literature review
An exhaustive review of the literature about brain–computer interfaces (BCIs) that could be used with paralysed patients and the electroencephalography (EEG) is the best candidate for the continuous use in the environment of patients’ houses, due to its portability and ease of use.
Quantitative EEG-Based Brain-Computer Interface
In this chapter, BCIs based on two types of oscillatory EEG, the steady-state visual evoked potential from the visual cortex and the sensorimotor rhythm from the sensorsimotor cortex, are introduced and their physiological bases, principles of operation, and implementation approaches are provided.
ECoG-Based BCI for BCI-MEG Research
This experiment showed that ECoG-based motor imagery performed well despite a short training period, providing future possibility for MEG-based BCI with higher sensitivity than present MEG sensors.
Brain Computer Interfaces, a Review
The state-of-the-art of BCIs are reviewed, looking at the different steps that form a standard BCI: signal acquisition, preprocessing or signal enhancement, feature extraction, classification and the control interface.


Brain-computer interface: a new communication device for handicapped persons
First results on a BCI developed in Graz are reported: 85% correct movements can be obtained after only a few days training.
The thought translation device: a neurophysiological approach to communication in total motor paralysis
The results demonstrate that the fast and stable SCP self-control can be achieved with operant training and without mediation of any muscle activity, and allows communication even in total locked-in states.
Brain-computer communication: self-regulation of slow cortical potentials for verbal communication.
This training schedule is the first to enable severely paralyzed patients to communicate without any voluntary muscle control by using self-regulation of an electroencephalogram potential only and could be a model for training patients in other brain-computer interface techniques.
Brain-computer interface research at the Wadsworth Center.
  • J. Wolpaw, D. McFarland, T. Vaughan
  • Computer Science
    IEEE transactions on rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
  • 2000
This EEG-based brain-computer interface (BCI) could provide a new augmentative communication technology for those who are totally paralyzed or have other severe motor impairments.
Abstract A biofeedback paradigm was developed for self-regulation of cortical DC-shifts. Subjects received continuous visual feedback of their actual DC-shift during six sec. intervals. Feedback
Self-Regulation of The Brain and Behavior
This work focuses on the application of Operant Conditioning of the EEG for the Management of Epileptic Seizures and on the relationships between Subjective Experience, Behavior, and Physiological Activity in Biofeedback Learning.
A spelling device for the paralysed
A new means of communication for the completely paralysed that uses slow cortical potentials of the electro-encephalogram to drive an electronic spelling device is developed.