IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
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IEEE Trans Neural Syst Rehabil Eng · Jun 2011
BCI demographics II: how many (and what kinds of) people can use a high-frequency SSVEP BCI?
Brain-computer interface (BCI) systems use brain activity as an input signal and enable communication without movement. This study is a successor of our previous study (BCI demographics I) and examines correlations among BCI performance, personal preferences, and different subject factors such as age or gender for two sets of steady-state visual evoked potential (SSVEP) stimuli: one in the medium frequency range (13, 14, 15 and 16 Hz) and another in the high-frequency range (34, 36, 38, 40 Hz). High-frequency SSVEPs (above 30 Hz) diminish user fatigue and risk of photosensitive epileptic seizures. ⋯ Results showed that demographic parameters as well as handedness, tiredness, alcohol and caffeine consumption, etc., have no significant effect on the performance of SSVEP-based BCI. Most subjects did not consider the flickering stimuli annoying, only five out of total 86 participants indicated change in fatigue during the experiment. 84 subjects performed with a mean information transfer rate of 17.24 ±6.99 bit/min and an accuracy of 92.26 ±7.82% with the medium frequency set, whereas only 56 subjects performed with a mean information transfer rate of 12.10 ±7.31 bit/min and accuracy of 89.16 ±9.29% with the high-frequency set. These and other demographic analyses may help identify the best BCI for each user.
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IEEE Trans Neural Syst Rehabil Eng · Apr 2011
Point-and-click cursor control with an intracortical neural interface system by humans with tetraplegia.
We present a point-and-click intracortical neural interface system (NIS) that enables humans with tetraplegia to volitionally move a 2-D computer cursor in any desired direction on a computer screen, hold it still, and click on the area of interest. This direct brain-computer interface extracts both discrete (click) and continuous (cursor velocity) signals from a single small population of neurons in human motor cortex. A key component of this system is a multi-state probabilistic decoding algorithm that simultaneously decodes neural spiking activity of a small population of neurons and outputs either a click signal or the velocity of the cursor. ⋯ We quantified point-and-click performance using various human-computer interaction measurements for pointing devices. We found that participants could control the cursor motion and click on specified targets with a small error rate (< 3% in one participant). This study suggests that signals from a small ensemble of motor cortical neurons (∼40) can be used for natural point-and-click 2-D cursor control of a personal computer.
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IEEE Trans Neural Syst Rehabil Eng · Apr 2011
Isomap approach to EEG-based assessment of neurophysiological changes during anesthesia.
Increasing concentrations of anesthetics in the blood induce a continuum of neurophysiological changes, which reflect on the electroencephalogram (EEG). EEG-based depth of anesthesia assessment requires that the signal samples are correctly associated with the neurophysiological changes occurring at different anesthetic levels. A novel method is presented to estimate the phase of the continuum using the feature data extracted from EEG. ⋯ Utilizing a recently proposed algorithm, Isomap, the dimensionality of the feature data is reduced to achieve a one-dimensional embedding representing this manifold and thereby the continuum of neurophysiological changes during induction of anesthesia. The Isomap-based estimation is validated with data recorded from nine patients during induction of propofol anesthesia. The proposed method provides a novel approach to assess neurophysiological changes during anesthesia and offers potential for the development of more advanced systems for the depth of anesthesia monitoring.
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IEEE Trans Neural Syst Rehabil Eng · Feb 2011
Closed-loop control of deep brain stimulation: a simulation study.
Deep brain stimulation (DBS) is an effective therapy to treat movement disorders including essential tremor, dystonia, and Parkinson's disease. Despite over a decade of clinical experience the mechanisms of DBS are still unclear, and this lack of understanding makes the selection of stimulation parameters quite challenging. The objective of this work was to develop a closed-loop control system that automatically adjusted the stimulation amplitude to reduce oscillatory neuronal activity, based on feedback of electrical signals recorded from the brain using the same electrode as implanted for stimulation. ⋯ Such changes reflected modifications in the firing patterns of the model neuronal population, and, differently from open-loop DBS, replaced the tremor-related pathological patterns with patterns similar to those simulated in tremor-free conditions. The closed-loop controller generated a LFP spectrum that approximated more closely the spectrum present in the tremor-free condition than did open loop fixed intensity stimulation and adapted to match the spectrum after a change in the neuronal oscillation frequency. This computational study suggests the feasibility of closed-loop control of DBS amplitude to regulate the spectrum of the local field potentials and thereby normalize the aberrant pattern of neuronal activity present in tremor.
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IEEE Trans Neural Syst Rehabil Eng · Feb 2011
An SSVEP BCI to control a hand orthosis for persons with tetraplegia.
Brain-computer interface (BCI) systems allow people to send messages or commands without moving, and hence can provide an alternative communication and control channel for people with limited motor function. In this study, we demonstrate a BCI system for orthosis control. Our BCI was asynchronous, meaning that subjects could move the orthosis whenever they wanted, instead of pacing themselves to external cues. ⋯ However, the false positive rate was high, and some subjects dislike the flickering lights required in SSVEP BCIs. In follow-up work, we hope to reduce both the false positive rate and the annoyance produced by flickering lights by hybridizing this BCI with a "brain switch," which could allow people to turn the SSVEP system on or off using a second type of brain activity when they do not wish to control the orthosis. We also hope to validate this approach with people with tetraplegia.