Article
A brain-computer interface (BCI) for the locked-in: comparison of different EEG classifications for the thought translation device.
Institute of Medical Psychology and Behavioral Neurobiology, Gartenstrasse 29, University of Tübingen, Tubingen, Germany.
Clinical Neurophysiology (impact factor:
3.41).
04/2003;
114(3):416-25.
pp.416-25
Source: PubMed
-
Citations (0)
- Cited In (14)
-
Article: Brain computer interfaces, a review.
[show abstract] [hide abstract]
ABSTRACT: A brain-computer interface (BCI) is a hardware and software communications system that permits cerebral activity alone to control computers or external devices. The immediate goal of BCI research is to provide communications capabilities to severely disabled people who are totally paralyzed or 'locked in' by neurological neuromuscular disorders, such as amyotrophic lateral sclerosis, brain stem stroke, or spinal cord injury. Here, we review the state-of-the-art of BCIs, looking at the different steps that form a standard BCI: signal acquisition, preprocessing or signal enhancement, feature extraction, classification and the control interface. We discuss their advantages, drawbacks, and latest advances, and we survey the numerous technologies reported in the scientific literature to design each step of a BCI. First, the review examines the neuroimaging modalities used in the signal acquisition step, each of which monitors a different functional brain activity such as electrical, magnetic or metabolic activity. Second, the review discusses different electrophysiological control signals that determine user intentions, which can be detected in brain activity. Third, the review includes some techniques used in the signal enhancement step to deal with the artifacts in the control signals and improve the performance. Fourth, the review studies some mathematic algorithms used in the feature extraction and classification steps which translate the information in the control signals into commands that operate a computer or other device. Finally, the review provides an overview of various BCI applications that control a range of devices.Sensors 01/2012; 12(2):1211-79. · 1.74 Impact Factor -
Article: The Sensorium: A Multimodal Neurofeedback Environment
Advances in Human-Computer Interaction. 01/2011; -
Conference Proceeding: Usability of Brain Computer Interfaces
[show abstract] [hide abstract]
ABSTRACT: Abstract. A Brain Computer Interface (BCI) is a control and/or communication system in which the user’s commands and messages do not depend on muscular control. If BCIs were to be considered and evaluated as assistive technology facilitating daily activities, they could avoid dissatisfaction and prevent abandonment. Approaches such as “User-centered design”, “User interfaces for all” and the most recent “Integrated model of usability” already highlight the importance of a complete and full evaluation of the interaction. The tradition of Human Computer Interaction (HCI) has already given us most of the tools we need to analyse and evaluate technology. In a series of studies, we assessed the usability of two BCI prototypes by measuring interaction with the systems in context, considering the performance, cognitive workload and satisfaction of non-disabled users in order to better understand how the interface affects these parameters. We tested two keyboard-controlled Java BCI prototypes based on the Thought Translation Device and the P300 Speller (P3S). In the first evaluation, we tested the learnability of BCIs on 6 healthy users through the Thinking Aloud technique, which showed that while all users easily learned how the system worked with Language Support Program (LSP), they failed with P3S. We then tested BCI efficiency on 30 participants (15 with LSP and 15 with P3S) through the Copy Spelling Task (CST) and administered the System Usability Scale (SUS) to measure usability and the Survey of Technology Use (SOTU) scale of the Matching Person and Technology (MPT) to measure predisposition to the use of technology. With the CST, we found that P3S users were more accurate in selecting and recognising letters on the screen. Both SUS and SOTU did not show any significant effects. After modifying our testing paradigm, we tested again using 61 participants with different computer skills, and administered usability and cognitive workload questionnaires. The results showed significant differences in the number of performed errors as well as in user satisfaction and the cognitive workload invested in the task. We found that the Thought Translation Device was more error-resistant, less stressful and more satisfactory for the users compared to the P3S.AAATE 2011 - Association for the Advancement of Assistive Technology in Europe, Maastricht, the Netherlands; 09/2011
Data provided are for informational purposes only. Although carefully collected, accuracy cannot be guaranteed.
The impact factor represents a rough estimation of the journal's impact factor and does not reflect the actual
current impact factor.
Publisher conditions are provided by RoMEO. Differing provisions from the publisher's actual policy or licence
agreement may be applicable.
Keywords
'mixed filter'
additional event-related cortical potential
brain-computer interface
certain SCP amplitude threshold
EEG data
event-related potentials
feedback training
immediate feedback
mixed filter condition
mixed filter feedback method
paralyzed patient
patient's control
Patients
patients' performance on-line
SCPs
selections
slow cortical potentials
Thought Translation Device
threshold-related decisions
time-series SCP data