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      Unobtrusive ambulatory EEG using a smartphone and flexible printed electrodes around the ear

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          Abstract

          This study presents first evidence that reliable EEG data can be recorded with a new cEEGrid electrode array, which consists of ten electrodes printed on flexible sheet and arranged in a c-shape to fit around the ear. Ten participants wore two cEEGrid systems for at least seven hours. Using a smartphone for stimulus delivery and signal acquisition, resting EEG and auditory oddball data were collected in the morning and in the afternoon six to seven hours apart. Analysis of resting EEG data confirmed well-known spectral differences between eyes open and eyes closed conditions. The ERP results confirmed the predicted condition effects with significantly larger P300 amplitudes for target compared to standard tones, and a high test-retest reliability of the P300 amplitude (r > = .74). Moreover, a linear classifier trained on data from the morning session revealed similar performance in classification accuracy for the morning and the afternoon sessions (both > 70%). These findings demonstrate the feasibility of concealed and comfortable brain activity acquisition over many hours.

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          Most cited references31

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          Control of a two-dimensional movement signal by a noninvasive brain-computer interface in humans.

          Brain-computer interfaces (BCIs) can provide communication and control to people who are totally paralyzed. BCIs can use noninvasive or invasive methods for recording the brain signals that convey the user's commands. Whereas noninvasive BCIs are already in use for simple applications, it has been widely assumed that only invasive BCIs, which use electrodes implanted in the brain, can provide multidimensional movement control of a robotic arm or a neuroprosthesis. We now show that a noninvasive BCI that uses scalp-recorded electroencephalographic activity and an adaptive algorithm can provide humans, including people with spinal cord injuries, with multidimensional point-to-point movement control that falls within the range of that reported with invasive methods in monkeys. In movement time, precision, and accuracy, the results are comparable to those with invasive BCIs. The adaptive algorithm used in this noninvasive BCI identifies and focuses on the electroencephalographic features that the person is best able to control and encourages further improvement in that control. The results suggest that people with severe motor disabilities could use brain signals to operate a robotic arm or a neuroprosthesis without needing to have electrodes implanted in their brains.
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            Dynamics of Active Sensing and perceptual selection.

            Sensory processing is often regarded as a passive process in which biological receptors like photoreceptors and mechanoreceptors transduce physical energy into a neural code. Recent findings, however, suggest that: first, most sensory processing is active, and largely determined by motor/attentional sampling routines; second, owing to rhythmicity in the motor routine, as well as to its entrainment of ambient rhythms in sensory regions, sensory inflow tends to be rhythmic; third, attentional manipulation of rhythms in sensory pathways is instrumental to perceptual selection. These observations outline the essentials of an Active Sensing paradigm, and argue for increased emphasis on the study of sensory processes as specific to the dynamic motor/attentional context in which inputs are acquired. (c) 2010 Elsevier Ltd. All rights reserved.
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              How about taking a low-cost, small, and wireless EEG for a walk?

              To build a low-cost, small, and wireless electroencephalogram (EEG) system suitable for field recordings, we merged consumer EEG hardware with an EEG electrode cap. Auditory oddball data were obtained while participants walked outdoors on university campus. Single-trial P300 classification with linear discriminant analysis revealed high classification accuracies for both indoor (77%) and outdoor (69%) recording conditions. We conclude that good quality, single-trial EEG data suitable for mobile brain-computer interfaces can be obtained with affordable hardware. Copyright © 2012 Society for Psychophysiological Research.
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                Author and article information

                Journal
                Sci Rep
                Sci Rep
                Scientific Reports
                Nature Publishing Group
                2045-2322
                17 November 2015
                2015
                : 5
                : 16743
                Affiliations
                [1 ]Neuropsychology Lab, Department of Psychology, European Medical School, University of Oldenburg , Oldenburg, Germany
                [2 ]Cluster of Excellence Hearing4all, University of Oldenburg , Oldenburg, Germany
                [3 ]Neurosensory Science, University of Oldenburg , Germany
                [4 ]Institute of Biomedical Engineering, University of Oxford , Oxford, UK
                Author notes
                Article
                srep16743
                10.1038/srep16743
                4648079
                26572314
                a95e1fb1-c264-4b12-ab3a-07f979485300
                Copyright © 2015, Macmillan Publishers Limited

                This work is licensed under a Creative Commons Attribution 4.0 International License. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in the credit line; if the material is not included under the Creative Commons license, users will need to obtain permission from the license holder to reproduce the material. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/

                History
                : 22 April 2015
                : 19 October 2015
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