Detection of seizure rhythmicity by recurrences
نویسندگان
چکیده
منابع مشابه
extremal region detection guided by maxima of gradient magnitude
a problem of computer vision applications is to detect regions of interest under dif- ferent imaging conditions. the state-of-the-art maximally stable extremal regions (mser) detects affine covariant regions by applying all possible thresholds on the input image, and through three main steps including: 1) making a component tree of extremal regions’ evolution (enumeration), 2) obtaining region ...
Risk of seizure recurrences after first unprovoked seizure during childhood.
OBJECTIVE To find out incidence of seizure recurrence and its risk factor after the first unprovoked attack in children below 12 years of age. METHODS A prospective study was carried out between 30th April 1996 - 1st May 1997 with the aim to find out the incidence of seizure recurrence and its risk factor after the first unprovoked attack in children below 12 years of age. All patients aged b...
متن کاملCircadian Rhythmicity by Autocatalysis
The temperature compensated in vitro oscillation of cyanobacterial KaiC phosphorylation, the first example of a thermodynamically closed system showing circadian rhythmicity, only involves the three Kai proteins (KaiA, KaiB, and KaiC) and ATP. In this paper, we describe a model in which the KaiA- and KaiB-assisted autocatalytic phosphorylation and dephosphorylation of KaiC are the source for ci...
متن کاملEarly seizure detection.
For patients with medically intractable epilepsy, there have been few effective alternatives to resective surgery, a destructive, irreversible treatment. A strategy receiving increased attention is using interictal spike patterns and continuous EEG measurements from epileptic patients to predict and ultimately control seizure activity via chemical or electrical control systems. This work compar...
متن کاملEpileptic Seizure Detection by Exploiting Temporal Correlation of EEG Signals
Electroencephalogram (EEG), a record of electrical signal to represent the human brain activity, has great potential for the diagnosis to treatment of mental disorder and brain diseases such as epileptic seizure. Features extraction and classification of EEG signals is the crucial task to detect the stage of ictal (i.e., seizure period) and interictal (i.e., period between seizures) signals for...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Chaos: An Interdisciplinary Journal of Nonlinear Science
سال: 2008
ISSN: 1054-1500,1089-7682
DOI: 10.1063/1.2973817