Event-Related Potentials (ERPs) are modifications of the brain activity in response to external sensory stimulation. P300 is a positive ERP component that occurs 300 ms after the presentation of a rare stimulus and in...
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Event-Related Potentials (ERPs) are modifications of the brain activity in response to external sensory stimulation. P300 is a positive ERP component that occurs 300 ms after the presentation of a rare stimulus and in...
详细信息
ISBN:
(数字)9798350371499
ISBN:
(纸本)9798350371505
Event-Related Potentials (ERPs) are modifications of the brain activity in response to external sensory stimulation. P300 is a positive ERP component that occurs 300 ms after the presentation of a rare stimulus and indicates conscious perception of an unexpected change in sensory stimulation. Since the amplitude of ERPs is comparable to that of background electroencephalography, the most widespread approach to render ERPs correctly detectable is time-domain averaging. ERPs are physiologically affected by variations in latency, referred to as latency jitter. The most promising techniques to address latency jitter are cross-correlation template matching algorithms, which estimate single-trial latencies and resynchronize them according to a template that best describes the ERP component. Adaptive Wavelet Filtering (AWF) is an algorithm applied in the wavelet domain to provide the optimal compromise of time-frequency resolution in detecting ERPs. The choice of an appropriate decomposition frequency is crucial in the application of AWF, as it is essential for identifying the correct template and estimating single-trial latencies. In this study, we investigated the influence of frequency on the performance of AWF to optimize it. The algorithm was tested on simulated data with varying latency shifts and signal-to-noise ratios as well as for data recorded from 11 healthy subjects during an auditory oddball paradigm. Results on both simulated and real EEG data showed how frequency decomposition of 3 Hz is the most appropriate for P300 waveform detection.
Episodes of complete failure to respond during attentive tasks - lapses of responsiveness ('lapses') - accompanied by behavioral signs of sleep such as slow-eyeclosure are known as behavioral microsleeps (BMs)...
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ISBN:
(纸本)9781457717871
Episodes of complete failure to respond during attentive tasks - lapses of responsiveness ('lapses') - accompanied by behavioral signs of sleep such as slow-eyeclosure are known as behavioral microsleeps (BMs). The occurrence of BMs can have serious/fatal consequences, particularly in the transport sectors, and therefore further investigations on neurophysiological correlates of BMs are highly desirable. In this paper we propose a combination of High Resolution EEG techniques and an advanced method for time-varying functional connectivity estimation for reconstructing the temporal evolution of causal relations between cortical regions of BMs occurring during a visuomotor tracking task. The preliminary results highlight connectivity patterns involving parietal and fronto-parietal areas both preceding and following the onset of a BM.
Lack of a clear analytical metric for identifying artifact free, clean electroencephalographic (EEG) signals inhibits robust comparison of different artifact removal methods and lowers confidence in the results of EEG...
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ISBN:
(纸本)9781424441198
Lack of a clear analytical metric for identifying artifact free, clean electroencephalographic (EEG) signals inhibits robust comparison of different artifact removal methods and lowers confidence in the results of EEG analysis. An algorithm is presented for identifying clean EEG epochs by thresholding statistical properties of the EEG. Thresholds are trained on EEG datasets from both healthy subjects and stroke / spinal cord injury patient populations via differential evolution (DE).
To be correctly mastered, brain-computerinterfaces (BCIs) need an uninterrupted flow of feedback to the user. This feedback is usually delivered through the visual channel. Our aim was to explore the benefits of vibr...
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To be correctly mastered, brain-computerinterfaces (BCIs) need an uninterrupted flow of feedback to the user. This feedback is usually delivered through the visual channel. Our aim was to explore the benefits of vibrotactile feedback during users' training and control of EEG-based BCI applications. A protocol for delivering vibrotactile feedback, including specific hardware and software arrangements, was specified. In three studies with 33 subjects (including 3 with spinal cord injury), we compared vibrotactile and visual feedback, addressing: (I) the feasibility of subjects' training to master their EEG rhythms using tactile feedback;(II) the compatibility of this form of feedback in presence of a visual distracter;(III) the performance in presence of a complex visual task on the same (visual) or different (tactile) sensory channel. The stimulation protocol we developed supports a general usage of the tactors;preliminary experimentations. All studies indicated that the vibrotactile channel can function as a valuable feedback modality with reliability comparable to the classical visual feedback. Advantages of using a vibrotactile feedback emerged when the visual channel was highly loaded by a complex task. In all experiments, vibrotactile feedback felt, after some training, more natural for both controls and SCI users.
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