conclusions these open-label data show trends toward normalization of eeg and concomitant clinical improvement using magnetic stimulation for ptsd. results of the 21 patients who initiated therapy, 16 completed treatment. clinical improvements on the pcl-m were seen in these 16 patients, with an average pre-treatment score of 54.9 and post-treatment score of 31.8 (p < 0.001). in addition, relat...

OBJECTIVE Definition of appropriate frequency bands and choice of recording reference limit the interpretability of quantitative EEG, which may be further compromised by distorted topographies or inverted hemispheric asymmetries when employing conventional (non-linear) power spectra. In contrast, fPCA factors conform to the spectral structure of empirical data, and a surface Laplacian (2-dimens...

BACKGROUND Attention deficit disorder/hyperactivity disorder (ADHD) is a pathological condition that is not fully understood. In this study, we investigated electroencephalographic (EEG) power differences between children with ADHD and healthy control children. METHODS EEGs were recorded as part of routine medical care received by 80 children with ADHD aged 4-15 years at the Department of Ped...

Using a physiologically based model of brain activity, electroencephalogram (EEG) power spectra are calculated for signals derived from general linear combinations of voltages from multiple electrodes, with and without filtering by volume conduction. Two simple methods of combining scalp measurements to estimate unfiltered EEG power spectra are then proposed and their accuracy and robustness ar...

In this paper Empirical Mode Decomposition (EMD)-based features from single-channel electroencephalographic (EEG) data are proposed for rat’s sleep state classification. The classification performances of the EMD-based features and some classical power spectrum density (PSD)-based features are compared. Supported by experiments on real EEG data, we demonstrate that classification performances c...

The task oriented brain activity analysis and classification is a prime issue in EEG signal processing these days. The similar attempt has been done here to estimate the brain activity on the basis of power spectrum analysis. For this, the modified approach involving both Independent Component Analysis (ICA) and Principal Component Analysis (PCA) methodologies has been used in this paper to inv...

Juvenile Myoclonic Epilepsy recognition and its cognitive effect were investigated through Welch Periodogram analysis of EEG signals. The micro-volt brain delicate signals were measured by our laboratory KL-720 system with Kl-75004 Electroencephalogram module, after careful adjustments. The digital signal processing DSP proved itself through the MATLAB software as useful analyzing tool for the ...

Interictal electroencephalography (EEG) has clinically meaningful limitations in its sensitivity and specificity in the diagnosis of epilepsy because of its dependence on the occurrence of epileptiform discharges. We have developed a computer-aided diagnostic (CAD) tool that operates on the absolute spectral energy of the routine EEG and has both substantially higher sensitivity and negative pr...

In this paper, unique approach is presented for the electroencephalography (EEG) signals analysis. This is based on Eigen values distribution of a matrix which is called as scaled Hankel matrix. This gives us a way to find out the number of Eigen values essential for noise reduction and extraction of signal in singular spectrum analysis. This paper gives us an approach to classify the EEG signa...

OBJECTIVE To investigate whether sleep macrostructure and EEG power spectral density and coherence during NREM sleep are different in Asperger syndrome (AS) compared to typically developing children and adolescents. METHODS Standard all night EEG sleep parameters were obtained from 18 un-medicated subjects with AS and 14 controls (age range: 7.5-21.5years) after one adaptation night. Spectral...