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[en] Similarly as in adults we can encounter various disorders of seizure character that more or less resemble epileptic attacks. An incorrect diagnosis of epilepsy places a child into an unnecessary stress and risks associated with antiepileptic treatment, regardless the negative consequences in psychological and social area. In addition. many clinical entities have a suitable treatment. Somatically dependant attacks prevail among non epileptic seizures. Many of them are related to a certain period of child development. Psychologically dependent attacks manifest rather in older school age or adolescence. A carefully taken history plays a decisive role in a differential diagnostic analysis. EEG is usually indicated and in some cases a monitored. (author)
[en] This paper presents the design of a 40 digital channels Holter for ambulatory studies of electroencephalography(EEG) and polisomnography (PSG), specially for epilepsy and sleep disorders. It includes a revision of the market and technologies used in such equipment. The requirements of design are established, and solutions are presented. It shows a functional diagram of the system including technologies like wireless communication, reading and writing in USB flash devices and a new amplifier design with dynamic compensation of direct current polarization
[en] This paper presents a third-order single-loop delta-sigma modulator of a biomedical micro-system for portable electroencephalogram (EEG) monitoring applications. To reduce the power consumption, the loop filter of the proposed modulator is implemented by applying a switched-capacitor structure. The modulator is designed in a 0.35-μm 2P4M standard CMOS process, with an active area of 365 x 290 μm2. Experimental results show that this modulator achieves a 68 dB dynamic range with an input sinusoidal signal of 100 Hz signal bandwidth under a 64 over-sampling ratio. The whole circuit consumes 515 μW under a 2.5 V power supply, which is suitable for portable EEG monitoring.
[en] In 31 patients with temporal lobe epilepsy, the precise site of epileptogenic focus was determined by means of a depth EEG recording as one of the presurgical evaluations. In 13 patients, a CT scan revealed focal lesions; 7 in the left temporal lobe and 6 in the right temporal lobe. In 5 of the 7 patients and in 5 of the 6 patients the epileptogenic foci were determined in the temporal lobe on the side of a CT lesion. However, in 2 of the patients with a CT lesion in the left temporal lobe, independent epileptogenic foci were found in both the temporal lobes, and in the other patient with a CT lesion in the right temporal lobe, they were found in the right frontal and left temporal lobes. Thus, the CT lesions agreed in lateralization and focality with the epileptogenic foci in 10 of the 13 patients (77%), but they disagreed in 3 (23%). A CT lesion disclosed in the temporal lobe does not necessarily indicate the side and/or site where the epileptogenic focus may be localized. Although exceptions may be made, spatial disagreement was exemplified between the CT lesion and epileptogenic focus. Therefore, extreme caution has to be taken on the side and/or site of the epileptogenic focus when functional surgical indication is to be made. (author)
[en] The univariate method of event-related desynchronization (ERD) analysis, which quantifies the temporal evolution of power within specific frequency bands from electroencephalographic (EEG) data recorded during a task or event, is extended to an event related multivariate spectral analysis method. With this method, time courses of cross-spectra, phase spectra, coherence spectra, band-averaged coherence values (event-related coherence, ERCoh), partial power spectra and partial coherence spectra are estimated from an ensemble of multivariate event-related EEG trials. This provides a means of investigating relationships between EEG signals recorded over different scalp areas during the performance of a task or the occurrence of an event. The multivariate spectral analysis method is applied to EEG data recorded during three different movement-related studies involving discrete right index finger movements. The first study investigates the impact of the EEG derivation type on the temporal evolution of interhemispheric coherence between activity recorded at electrodes overlying the left and right sensorimotor hand areas during cued finger movement. The question results whether changes in coherence necessarily reflect changes in functional coupling of the cortical structures underlying the recording electrodes. The method is applied to data recorded during voluntary finger movement and a hypothesis, based on an existing global/local model of neocortical dynamics, is formulated to explain the coherence results. The third study applies partial spectral analysis too, and investigates phase relationships of, movement-related data recorded from a full head montage, thereby providing further results strengthening the global/local hypothesis. (author)
[en] A 5-year-old girl presented with intractable seizures and nonfocal hemispheric slowing on EEG. Blood, urine, and CSF laboratory values were all normal. MR imaging of the brain demonstrated diffuse volume loss of the entire left hemisphere. Clinical and imaging findings were consistent with the diagnosis of Rasmussen encephalitis. Diffusion tensor imaging demonstrated increased ADC values and decreased fractional anisotropy (FA) of the affected (left) hemisphere. Tractography data showed decreased numbers of lines drawn in the affected hemisphere, with fewer lines drawn at higher FA thresholds, relative to the contralateral hemisphere, or to normal age-matched controls. Diffusion tensor imaging offers an adjunct MR imaging modality in diagnosis and monitoring of this rare condition. (orig.)
[en] Solution of the EEG source localization (inverse) problem utilizing model-based methods typically requires a significant number of forward model evaluations. For subspace based inverse methods like MUSIC (6), the total number of forward model evaluations can often approach an order of 103 or 104. Techniques based on least-squares minimization may require significantly more evaluations. The observed set of measurements over an M-sensor array is often expressed as a linear forward spatio-temporal model of the form: F = GQ + N (1) where the observed forward field F (M-sensors x N-time samples) can be expressed in terms of the forward model G, a set of dipole moment(s) Q (3xP-dipoles x N-time samples) and additive noise N. Because of their simplicity, ease of computation, and relatively good accuracy, multi-layer spherical models (7) (or fast approximations described in (1), (7)) have traditionally been the 'forward model of choice' for approximating the human head. However, approximation of the human head via a spherical model does have several key drawbacks. By its very shape, the use of a spherical model distorts the true distribution of passive currents in the skull cavity. Spherical models also require that the sensor positions be projected onto the fitted sphere (Fig. 1), resulting in a distortion of the true sensor-dipole spatial geometry (and ultimately the computed surface potential). The use of a single 'best-fitted' sphere has the added drawback of incomplete coverage of the inner skull region, often ignoring areas such as the frontal cortex. In practice, this problem is typically countered by fitting additional sphere(s) to those region(s) not covered by the primary sphere. The use of these additional spheres results in added complication to the forward model. Using high-resolution spatial information obtained via X-ray CT or MR imaging, a realistic head model can be formed by tessellating the head into a set of contiguous regions (typically the scalp, outer skull, and inner skull surfaces). Since accurate in vivo determination of internal conductivities is currently not currently possible, the head is typically assumed to consist of a set of contiguous isotropic regions, each with constant conductivity.
[en] Research has shown that biofeedback is a viable alternative treatment especially for disorders like headache and hypertension. The aim of this review paper is to illustrate ideas of a promising application of electroencephalograph (EEG) in biofeedback. This sort of biofeedback is called neurofeedback and its efficacy in treating epilepsy and Attention Deficit Hyperactivity Disorder (ADHD) is discussed. Lastly, a brief history of the study of neurofeedback is presented
[en] Focused ultrasound is now capable of noninvasively penetrating the intact human skull and delivering energy to specific areas of the brain with millimeter accuracy. The ultrasound energy is supplied in high-intensities to create brain lesions or at low-intensities to produce reversible physiological interventions. Conducting acoustic emission detection (AED) and electroencephalography (EEG) during transcranial focused ultrasound may lead to several new brain treatment and research applications. This study investigates the feasibility of using a novel scalp senor for acquiring concurrent AED and EEG during clinical transcranial ultrasound. A piezoelectric disk is embedded in a plastic cup EEG electrode to form the sensor. The sensor is coupled to the head via an adhesive/conductive gel-dot. Components of the sensor prototype are tested for AED and EEG signal quality in a bench top investigation with a functional ex vivo skull phantom. (paper)
[en] Cross Coherence time frequency transform and independent component analysis (ICA) method were used to analyse the electroencephalogram (EEG) signals in resting and action states during open and close eyes conditions. From the topographical scalp distributions of delta, theta, alpha, and beta power spectrum can clearly discriminate between the signal when the eyes were open or closed, but it was difficult to distinguish between resting and action states when the eyes were closed. In open eyes condition, the frontal area (Fp1, Fp2) was activated (higher power) in delta and theta bands whilst occipital (O1, O2) and partial (P3, P4, Pz) area of brain was activated alpha band in closed eyes condition. The cross coherence method of time frequency analysis is capable of discrimination between rest and action brain signals in closed eyes condition