[Purpose] In earlier studies of driver distraction, researchers classified distraction into two levels (not distracted, and distracted). This study classified four levels of distraction (neutral, low, medium, high). [Subjects and Methods] Fifty Asian subjects (n=50, 43 males, 7 females), age range 20-35 years, who were free from any disease, participated in this study. Wireless EEG signals were...

Might EEG measured while one imagines words or sentences provide enough information for one to identify what is being thought? Analysis of EEG data from an experiment in which two syllables are spoken in imagination in one of three rhythms shows that information is present in EEG alpha, beta and theta bands. Envelopes are used to compute filters matched to a particular experimental condition; t...

We present a hybrid system for automatic analysis of clinical routine EEG, comprising a spectral analysis and an expert system. EEG raw data are transformed into the time-frequency domain by the so-called adaptive frequency decomposition. The resulting frequency components are converted into pseudo-linguistic facts via fuzzification. Finally, an expert system applies symbolic rules formulated b...

Sleep stages are mainly classified via electroencephalogram (EEG) which involves some prominent characters not only in amplitude but also in frequency. What is more, researchers are using computer assisted analysis to acquire the panoramic view of long duration sleep EEG. However, unlike the empirical judgment, it is fairly difficult to decide the specific values of sleep rules for computer bas...

The data presented here had been originally collected for a research project entitled 'Sleep EEG spectral analysis in psychophysiological insomnia and normal sleep subjects'. This article describes the data of 11 subjects, referred to Sleep Disorders Research Center (SDRC) in Kermanshah, Iran. The data includes 14 EEG, 6 EOG, and 3 EMG channels, with a sampling ratio of 256 Hz. It includes powe...

A new approach to recognize and predict succedent epileptic seizure by using single channel electroencephalogram (EEG) analysis is proposed. Spectral analysis of a brain time series of the left frontal FP1-F7 (LF) scalp location signal is devoted for seizure prediction and analysis. Important findings showing the presence of preictal spectral changes in studied brain signal are described. Spect...

This paper presents power spectral density (PSD) characteristics extracted from three-dimensional (3D) electroencephalogram (EEG) models in brain balancing application. There were 50 healthy subjects contributed the EEG dataset. Development of 3D models involves pre-processing of raw EEG signals and construction of spectrogram images. The resultant images which are two-dimensional (2D) were con...

Spectral decomposition, to this day, still remains the main analytical paradigm for the analysis of EEG oscillations. However, conventional spectral analysis assesses the mean characteristics of the EEG power spectra averaged out over extended periods of time and/or broad frequency bands, thus resulting in a "static" picture which cannot reflect adequately the underlying neurodynamic. A relativ...

Introduction: Quantitative assessments of the effects induced by repetitive transcranial magnetic stimulation (rTMS) are crucial to develop more efficient and personalized treatments. Objectives: To determine the spectral powers of different subbands of EEG correlated with treatment response to rTMS.   Materials and Methods: the spectral powers of different...

We investigated the effect of incision and sternotomy on the auditory evoked potential (AEP) and EEG, to try to predict a haemodynamic response to incision or sternotomy using the AEP and EEG in 41 patients undergoing cardiac surgery during propofol and alfentanil anaesthesia. The AEP and EEG were recorded before incision, between incision and sternotomy, and after sternotomy. Peak latencies an...