نتایج جستجو برای: eeg signal segmentation

تعداد نتایج: 509182  

Journal: :The Brain & Neural Networks 2004

Journal: :journal of medical signals and sensors 0
zahra vahabi rasool amirfattahi abdolreza mirzaee

abstract brian computer interface (bci) is a direct communication pathway between the brain and an external device. bcis are often aimed at assisting, augmenting or repairing human cognitive or sensory-motor functions. in this work a new algorithm is introduced to enhancing eeg signals that have been concerned the p300 problem. signal to noise ratio of eeg signals is very low and have  much art...

B Babadi B Bahrami M Noroozian R Seyedsadjadi

Fractal dimension of the electroencephalographic (EEG) signal has been argued to reflect the complexity of the underlying brain processes. To this date, conventional studies of EEG in mood disorders have not been able to distinguish between patients and normal individuals. Here we show that, compared to normal subjects, EEG fractal dimension is significantly augmented in the manic episode of bi...

B Babadi B Bahrami M Noroozian R Seyedsadjadi

Fractal dimension of the electroencephalographic (EEG) signal has been argued to reflect the complexity of the underlying brain processes. To this date, conventional studies of EEG in mood disorders have not been able to distinguish between patients and normal individuals. Here we show that, compared to normal subjects, EEG fractal dimension is significantly augmented in the manic episode of bi...

Journal: :Journal of neuroscience methods 2013
M Brandon Westover Mouhsin M Shafi Shinung Ching Jessica J Chemali Patrick L Purdon Sydney S Cash Emery N Brown

OBJECTIVE Develop a real-time algorithm to automatically discriminate suppressions from non-suppressions (bursts) in electroencephalograms of critically ill adult patients. METHODS A real-time method for segmenting adult ICU EEG data into bursts and suppressions is presented based on thresholding local voltage variance. Results are validated against manual segmentations by two experienced hum...

Introduction and Aims: Alzheimer’s disease is the most prevalent neurodegenerative disorder and a type of dementia. 80% of dementia in older adults is because of Alzheimer’s disease. According to multiple research articles, Alzheimer's has several changes in EEG signals such as slowing of rhythms, reduction in complexity and reduction in functional associations, and disordered functional commun...

Journal: :International Journal of Engineering Research and Advanced Technology 2018

Amin Noori, Mandana Sadat Ghafourian, Niloofar Zarif Sagheb Akbarpoor,

Epilepsy is the most common brain diseases that cause many problems in the daily life of the patient. In most attempts to automatic detection, the attack used an EEG. In this paper, The complete data set consists of five sets recorded from normal and epileptic patients. Each set containing 100 single-channel EEG segments. Here we used first and last sets (A and E). Set A consisted of segments r...

Journal: :international journal of advanced biological and biomedical research 0
nazlar ghassemzadeh ms student, department of biomedical engineering, tabriz branch , islamic azad university tabriz , iran siamak haghipour assistant professor, department of biomedical engineering, tabriz branch, islamic azad university tabriz, iran

the brain – computer interface (bci) provides a communicational channel between human and machine. most of these systems are based on brain activities. brain computer-interfacing is a methodology that provides a way for communication with the outside environment using the brain thoughts. the success of this methodology depends on the selection of methods to process the brain signals in each pha...

Journal: :journal of medical signals and sensors 0
sahar nesaei ahmad reza sharafat

we propose a novel approach for detecting precursors to epileptic seizures in intracranial electroencephalograms (ieeg), which is based on the analysis of system dynamics. in the proposed scheme, the largest lyapunov exponent of the discrete wavelet packet transform (dwpt) of the segmented eeg signals is considered as the discriminating features. such features are processed by a support vector ...

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