Results 221 to 230 of about 68,383 (283)
Cognitive Constraint Rules In Design Of Multi-mode Computer Interfaces For Disabled Users
Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society Volume 13: 1991, 2005 The authors present a scheme for custom design of computer interfaces for users with disabilities. Optimization is based on calculation of a benchmark score which estimates the rate at which the individual will be able to use particular application software.
Michael Rosen +1 more
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Idle Mode Detection for Somatosensory-Based Brain-Computer Interface
, 2015 Objective. Idle mode detection is a vital problem to be solved in self-paced asynchronized BCI, because patients need to control the BCI system whenever he or she wants, rather than output commands according to the system cues which is essentially different between self-paced and synchronized BCIs.
Xiaokang Shu +4 more
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Medical & Biological Engineering & Computing, 2019 Improper selection of the number and the amplitude of noise channels in noise-assisted multivariate empirical mode decomposition (NA-MEMD) would induce mode mixing and leakage in the obtained intrinsic mode functions (IMF), which would degrade the performance in applications like brain-computer interface (BCI) systems based on motor imagery.
Yang Zheng, Guanghua Xu
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Study on the Interactive Mode of Eye Control Mode in Human–Computer Interface
, 2019 The ergonomic experiment of human-computer interaction mode of eye movement control is carried out for efficient and precise interaction requirements of the human-machine interface. Based on eye movement behavior, operational performance and subjective feeling data, the advantages and disadvantages of eye movement control behaviors such as eye gaze and
Yingwei Zhou +5 more
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Empirical mode decomposition of EEG signals for brain computer interface
SoutheastCon 2017, 2017 Motor imagery (MI) based brain-computer interface (BCI) systems show potential applications in neural rehabilitation. In MI-BCI systems, the brain signals from movement imagination, without actual movement of limbs, can be acquired, processed and characterized to translate into actionable signals that can be used to activate external devices.
MD Erfanul Alam, Biswanath Samanta
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Journal of Neuroscience Methods, 2010 This paper presents an empirical mode decomposition (EMD) and refined generalized zero crossing (rGZC) approach to achieve frequency recognition in steady-stated visual evoked potential (SSVEP)-based brain computer interfaces (BCIs). Six light emitting diode (LED) flickers with high flickering rates (30, 31, 32, 33, 34, and 35 Hz) functioned as visual ...
Chi-Hsun Wu +9 more
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, 2009 This paper presents an Empirical mode decomposition (EMD) approach for achieving high-speed frequency-tagged steady state visual evoked potential (SSVEP) brain computer interface (BCI) system. Empirical mode decomposition (EMD) has been demonstrated as a local and fully data-driven technique for the data processing of nonlinear and non-stationary time ...
Chi-Hsun Wu +2 more
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Investigation of voice and text output modes with abstraction in a computer interface
Interacting with Computers, 1996 A human-computer interface is described, which was designed to study user preferences and the effectiveness of output modes and levels of information abstraction in a decision making environment. The interface was tested in an exploratory study of an apartment selection problem.
Norm Archer +3 more
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Comparison of Three Computer Scanning Modes as an Interface Method for Persons With Cerebral Palsy
The American Journal of Occupational Therapy, 1992 Abstract Occupational therapists are becoming increasingly involved with interface assessments. This involvement is improving the ability of persons with physical disabilities to interact with computers, augmentative communication aids, and other devices. The ability to use these devices facilitates participation in activities that would
Jennifer Angelo
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Batch Mode Active Learning Algorithm Combining with Self-training for Multiclass Brain-computer Interfaces [PDF]
Journal of Information and Computational Science, 2015 In this paper, an batch mode active learning algorithm combining with the beneflts of self-training for solving the multiclass Brain-computer Interface (BCI) problem, which initially only needs a small set of labeled samples to train classiflers. The algorithm applied active learning to select the most informative samples and self-training to select ...
Minyou Chen
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