Continuous Wavelet Transform for the Detection and Classification of Epileptiform Activity in the Eeg
نویسندگان
چکیده
This paper outlines a novel approach to wavelet based detection of epileptiform activity in the EEG. A special complex-valued wavelet filter is used in a continuous wavelet transform (CWT). The response of wavelet coefficients (WCs) to epileptiform discharges (EDs) is measured with respect to artifact-free background activity (BG). A detector based on the WCs of a single scale could operate at 45% sensitivity without false alarms or at 99% sensitivity with 19 false alarms per minute on an artifact-free recording.
منابع مشابه
Evaluation of the Hidden Markov Model for Detection of P300 in EEG Signals
Introduction: Evoked potentials arisen by stimulating the brain can be utilized as a communication tool between humans and machines. Most brain-computer interface (BCI) systems use the P300 component, which is an evoked potential. In this paper, we evaluate the use of the hidden Markov model (HMM) for detection of P300. Materials and Methods: The wavelet transforms, wavelet-enhanced indepen...
متن کاملFeature Extraction of Visual Evoked Potentials Using Wavelet Transform and Singular Value Decomposition
Introduction: Brain visual evoked potential (VEP) signals are commonly known to be accompanied by high levels of background noise typically from the spontaneous background brain activity of electroencephalography (EEG) signals. Material and Methods: A model based on dyadic filter bank, discrete wavelet transform (DWT), and singular value decomposition (SVD) was developed to analyze the raw data...
متن کاملP81: 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 کاملAutomatic Detection of Epileptiform Discharges in the EEG
The diagnosis of epilepsy generally includes a visual inspection of EEG recorded data by the Neurologist, with the purpose of checking the occurrence of transient waveforms called interictal epileptiform discharges. These waveforms have short duration (less than 100 ms), so the inspection process is usually time-consuming, particularly for ambulatory long-term EEG records. Therefore, an automat...
متن کاملA COMPARATIVE ANALYSIS OF WAVELET-BASED FEMG SIGNAL DENOISING WITH THRESHOLD FUNCTIONS AND FACIAL EXPRESSION CLASSIFICATION USING SVM AND LSSVM
This work presents a technique for the analysis of Facial Electromyogram signal activities to classify five different facial expressions for Computer-Muscle Interfacing applications. Facial Electromyogram (FEMG) is a technique for recording the asynchronous activation of neuronal inside the face muscles with non-invasive electrodes. FEMG pattern recognition is a difficult task for the researche...
متن کامل