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» Nonlinear classification of EEG data for seizure detection
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ICASSP
2011
IEEE
12 years 9 months ago
Improving kernel-energy trade-offs for machine learning in implantable and wearable biomedical applications
Emerging biomedical sensors and stimulators offer unprecedented modalities for delivering therapy and acquiring physiological signals (e.g., deep brain stimulators). Exploiting th...
Kyong-Ho Lee, Sun-Yuan Kung, Naveen Verma
KES
2006
Springer
13 years 5 months ago
Spiking Neural Network Based Classification of Task-Evoked EEG Signals
This paper presents an improved technique to detect evoked potentials in continuous EEG recordings using a spiking neural network. Human EEG signals recorded during spell checking,...
Piyush Goel, Honghai Liu, David J. Brown, Avijit D...
EUSFLAT
2007
176views Fuzzy Logic» more  EUSFLAT 2007»
13 years 7 months ago
Modifying the Classic Peak Picking Technique Using a Fuzzy Multi Agent to Have an Accurate P300-based BCI
EEG-based brain computer interface (BCI) provides a new communication channel between the human brain and a computer. The classification of EEG data is an important task in EEG-ba...
Gholamreza Salimi Khorshidi, Ayyoub Jaafari, Ali M...
ICONIP
2007
13 years 7 months ago
A Comparative Study of Synchrony Measures for the Early Detection of Alzheimer's Disease Based on EEG
It has repeatedly been reported in the medical literature that the EEG signals of Alzheimer’s disease (AD) patients are less synchronous than in age-matched control patients. Thi...
Justin Dauwels, François B. Vialatte, Andrz...
BMCBI
2008
142views more  BMCBI 2008»
13 years 5 months ago
Identification of biomarkers for genotyping Aspergilli using non-linear methods for clustering and classification
Background: In the present investigation, we have used an exhaustive metabolite profiling approach to search for biomarkers in recombinant Aspergillus nidulans (mutants that produ...
Irene Kouskoumvekaki, Zhiyong Yang, Svava Ó...