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This paper reports an experience in the setting-up and evaluation of a telemedicine solution to provide an electroencephalography service between a secondary hospital placed in Calahorra (Calahorra Hospital Foundation, FHC) and a tertiary hospital placed in Logrontildeo (San Pedro Hospital, HSP) both in La Rioja, Spain. We have evaluated technical and clinical aspects of the tele-EEG (electroencephalography)...
To realize brain computer interface, a recording electroencephalogram (EEG) and determining whether or not P300 is evoked by the presented stimulus have become increasingly important. Using the machine learning method for this classification is effective, but constructing feature vectors with all data points might result in very high-dimensional data. Because such redundant features are undesirable...
The correlation dimension was used in this paper as a quantifier to describe the chaotic behavior of sleep EEG recorded from the hippocampus of adult rats during vigilance states of quiet-waking, slow-wave sleep, and REM sleep. A modified Grassberger-Procaccia method was implemented to compute the correlation integral using a Euclidean distance normalized by the embedding dimension. The performance...
This paper assesses the use of independent component analysis (ICA) as applied to epileptic scalp electroencephalographic (EEG) recordings. In particular we address the newly introduced spatio-temporal ICA algorithm (ST-ICA), which uses both spatial and temporal information derived from multi-channel biomedical signal recordings to inform (or update) the standard ICA algorithm. ICA is a technique...
Nonlinear electroencephalographic entropy parameters have been proposed for the assessment of depth of anesthesia. The influence of remifentanil, a commonly used intraoperative opioid, on these parameters, namely approximate entropy (ApEn), sample entropy (SampEn), and permutation entropy (PeEn), during induction of propofol anesthesia was studied. Remifentanil was shown to reduce the propofol-induced...
Stroke has remained as a leading cause of death and neurological disability worldwide in the past decades. Previous structural and functional studies reported little information regarding cortical neural network after stroke. Using the causality measure based on multi-channel electroencephalograph (EEG), i.e. partial directed coherence (PDC) in this paper, we investigated the different network patterns...
In this paper we illustrate the capability of tracking brain activity during the observation of commercial TV spots by using advanced high resolution EEG statistical techniques in time and frequency domains. In particular, we analyzed the statistically significant cortical spectral power activity in different frequency bands during the observation of a commercial videoclip related to the use of a...
This study investigates the relationship between the sources of MEG interictal spikes and the distribution of spikes in invasive ECoG in a group of 38 epilepsy patients. An amplitude/surface area measure is defined to quantify ECoG spikes. It is found that all MEG spikes are associated with an ECoG spike that is, according to this measure, among the largest in each patient. For different brain regions...
A non-contact EEG electrode with input capacitance neutralization and common-mode noise suppression circuits is presented. The coin sized sensor capacitively couples to the scalp without direct contact to the skin. To minimize the effect of signal attenuation and channel gain mismatch, the input capacitance of each sensor is actively neutralized using positive feedback and bootstrapping. Common-mode...
This study explores the electroencephalographic (EEG) correlates of emotions during music listening. Principal component analysis (PCA) is used to correlate EEG features with complex music appreciation. This study also applies machine-learning algorithms to demonstrate the feasibility of classifying EEG dynamics in four subjectively-reported emotional states. The high classification accuracy (81.58plusmn3...
Brain-computer interfaces (BCI) based on event related potentials (ERP) have been successfully developed for applications like virtual spellers and navigation systems. This study tests the use of visual stimuli unbalanced in the subject's field of view to simultaneously cue mental imagery tasks (left vs. right hand movement) and detect subject attention. The responses to unbalanced cues were compared...
The C major scale was used either as frequent or as infrequent stimulus in the oddball auditory evoked field measurement where the other stimulus was constructed by removing one the tones in the scale. Multivariate statistical analysis was employed to judge whether there was a significant difference between the responses to complete and incomplete scales in each subject for each `target' tone which...
Spinal cord injury (SCI) results in deficits of sensory, motor and autonomous functions, with tremendous consequences for the patients. The loss of motor functions, especially grasping, leads to a dramatic decrease in quality of life. With the help of neuroprostheses, the grasp function can be substantially improved in cervical SCI patients. Nowadays, systems for grasp restoration can only be used...
With the recent concern on patient's outcome following general anesthesia, automatic control of drugs has been a field of interest. The Bispectral Index (BIS) is an EEG based hypnosis monitor, in current use at the operating theatre as a guiding tool for the anesthesiologist to titrate drugs, and prevent awareness. When trying to model a certain process, it's very important to obtain information of...
Detecting artifacts produced in electroencephalographic (EEG) data by muscle activity, eye blinks and electrical noise, etc., is an important problem in EEG signal processing research. These artifacts must be corrected before further analysis because it renders subsequent analysis very error-prone. One solution is to reject the data segment if artifact is present during the observation interval, however,...
In the mean square error sense, principal component analysis (PCA) or Karhunen-Loeve transform (KLT) can optimally summarize the high dimensional data into only a few meaningful ones. However, for the biomedical signal analysis, e.g. electroencephalogram (EEG), the data need to be updated or downdated very often. This fact makes the PCA impractical to be employed, especially in real-time signal analysis...
In this study, we developed numerical methods for investigating the sources of epileptic activity from intracranial EEG recordings acquired from intracranial subdural electrodes (iEEG) in patients undergoing pre-surgical evaluation at the epilepsy center of the Mayo Clinic (Rochester, MN). The data were analyzed using independent component analysis (ICA), which identifies and isolates maximally independent...
Approximately 300,000 Americans suffer from epilepsy but no treatment currently exists. A device that could predict a seizure and notify the patient of the impending event or trigger an antiepileptic device would dramatically increase the quality of life for those patients. A patient-specific classification algorithm is proposed to distinguish between preictal and interictal features extracted from...
A brain-computer interface (BCI) to detect motor imagery from cerebrum hemodynamic data measured by NIRS (near-infrared spectroscopy) was constructed and the effect of the online feedback training for subjects was evaluated. Concentrations of Oxy- and deOxy-hemoglobin in the motor cortex during motor imagery of subject's right hand was measured by 52-channel NIRS system, and the mean magnitude of...
Chronic sleepiness is a common symptom in the sleep disorders, such as, Obstructive Sleep Apnea, Periodic leg movement syndrome, narcolepsy etc. It affects 5% of the adult population and is associated with significant morbidity and increased risk to individual and society. MSLT and MWT are the existing tests for measuring sleepiness. Sleep Latency (SL) is the main measures of sleepiness computed in...
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