EEG signal classification for Epilepsy Seizure Detection using Improved Approximate Entropy. International Journal of Public Health Science (IJPHS), 2013; 2(1): 23-32.Sharanreddy, P.K.: EEG signal classification for epilepsy seizure detection using improved approximate entropy. International Journal of...
Bakker, A., Smith, B., Ainslie, P., & Smith, K. (2012). Near-infrared spectroscopy. Applied Aspects of Ultrasonography in Humans. Guerrero-Mosquera, C., Trigueros, A. M., & Navia-Vazquez, A. (2012). EEG signal processing for epilepsy. Epilepsy-histological, electroencephalographic and ...
EEG signalentropy based methodepileptic patientsfuzzy clusterOne of the major roles of Electrocephalography (EEG) is an aid to diagnose epilepsy. Abnormal patterns such as spikes, sharp wave complexes can be seen. Our main interest is to extract information about the dynamics from a few ...
Simultaneous HDEEG and MEG were acquired from surgical candidates in presurgical evaluation for epilepsy surgery36. Ictal MEG signals from 102-channel magnetometers and 204-channel gradiometers are epoched and pre-processed for source signal reconstruction. ViEEG locations fully contain MSL solutions (...
EEG signal classification play an important role in recognition of epilepsy. Recently, dictionary learning algorithms have shown the effectiveness in this field. When designing dictionaries, due to highly non-stationary of EEG signals, and collecting signals existing in different stimulus and drug modes...
The source of this disease is still not well understood. However, despite this, many patients can be medically treated if seizures are diagnosed on time. As a gold standard, the electroencephalogram (EEG) signal is very important in the diagnosis of epilepsy. The EEG recordings are collected by...
Review of Sparse Representation-Based Classification Methods on EEG Signal Processing for Epilepsy Detection, Brain-Computer Interface and Cognitive Impair... Review of Sparse Representation-Based Classification Methods on EEG Signal Processing for Epilepsy Detection, Brain-Computer Interface and Cognitive ...
signal classificationtime seriesabnormal brain activitybrain disorderselectroencephalogramepileptic brain activitiesneurological dysfunctionsEpilepsy is one of the most ... Chaovalitwongse, W.A.,YJ Fan,Sachdeo, R.C. - IEEE Transactions on Systems, Man, and Cybernetics - Part A: Systems and Humans 被...
Brain activity patterns have been widely analyzed using EEG signal processing. Hence, much research to date has investigated EEG signals of professionals such as artists and athletes. For instance, Hatfield et al. have found that left-hemisphere alpha wave activity significantly increases during the ...
This analogy to the interaction signal power between vertices inspired a computationally efficient network inference approach, and hence enables online seizure detection. In the simplified brain network inference approach, we employ the Fourier transform that is applied to the EEG data of each channel ...