Correlation Analysis and Modeling of EEG – EMG Signal for Startle-Induced Seizures
نویسندگان
چکیده
منابع مشابه
P81: Detection of Epileptic Seizures Using EEG Signal Processing
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...
متن کاملLamotrigine for startle-induced seizures
Startle-induced seizures are reflex seizures precipitated by a sudden, surprising stimulus, usually auditory. Aetiologies, electroencephalographic correlates, and brain structural abnormalities are variable. Because of the frequent tonic component at onset, falling is a major clinical problem. There is no established drug of choice, and therapy is often unsatisfactory. Adjunctive lamotrigine th...
متن کاملEMG-EEG correlation
The study of relationship between EMG and EEG provides us with physiological information about how activities of the cerebral cortex, mainly those of the sensori-motor cortex, are related to the movement of interest, whether it is voluntary or involuntary. In case of voluntary movement, we study the EMG-EEG correlation mainly to investigate cortical mechanisms underlying the central motor contr...
متن کاملComparative Analysis of Wavelet-based Feature Extraction for Intramuscular EMG Signal Decomposition
Background: Electromyographic (EMG) signal decomposition is the process by which an EMG signal is decomposed into its constituent motor unit potential trains (MUPTs). A major step in EMG decomposition is feature extraction in which each detected motor unit potential (MUP) is represented by a feature vector. As with any other pattern recognition system, feature extraction has a significant impac...
متن کاملUsing EMG Signal Analysis
A signal analysis technique is developed for discriminating a set of lower arm and wrist functions using surface EMG signals. Data wete obtained from four electrodes placed around the proximal forearm. The functions analyzed included wrist flexion/extension, wrist abduction/adduction, and forearm pronation/supination. Multivariate autoregression models were derived for each function; discrimina...
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: OnLine Journal of Biological Sciences
سال: 2018
ISSN: 1608-4217
DOI: 10.3844/ojbsci.2018.17.23