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Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)(6)
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scopus(11)
Comparison among physiological signals for biometric identification
Conference ObjectAbstract: The biometric is an open research field that requires analysis of new techniques to increase its accPalabras claves:biometric, Classifiers mixture, Multimodal system, physiological signals, Signal processingAutores:Alvarez-Uribe K.C., Diego Hernán Peluffo-Ordóñez, Miguel A. Becerra, Moreno-Revelo M.Y., Ortega-Adarme M.Fuentes:scopusAnalysis of motor imaginary BCI within multi-environment scenarios using a mixture of classifiers
Conference ObjectAbstract: Brain-computer interface (BCI) is a system that provides communication between human beings and machPalabras claves:Brain-Computer Interface, ENVIRONMENTS, Mixture of classifiers, Signal processingAutores:A. E. Castro-Ospina, Diego Hernán Peluffo-Ordóñez, Marín-Castrillón D.M., Miguel A. Becerra, Moreno-Revelo M.Y., Ortega-Adarme M.Fuentes:scopusData fusion and information quality for biometric identification from multimodal signals
ArticleAbstract: Biometric identification is carried out by processing physiological traits and signals. Biometrics sPalabras claves:Biometry, data fusion, information quality, Signal processingAutores:Andrés Viveros, Diego Hernán Peluffo-Ordóñez, Laura Daniela Lasso-Arciniegas, Miguel A. Becerra, Serna-Guarin L., Tobon C.Fuentes:scopusExploratory Study of the Effects of Cardiac Murmurs on Electrocardiographic-Signal-Based Biometric Systems
Conference ObjectAbstract: The process of distinguishing among human beings through the inspection of acquired data from physicPalabras claves:Biometric identification, Cardiac murmur, Electrocardiographic signal, Signal processingAutores:Camilo Zapata-Hernandez, Carolina M. Duque-Mejía, Delgadotrejos E., Diego Hernán Peluffo-Ordóñez, Javier E. Revelo-Fuelagán, Miguel A. Becerra, Serna-Guarin L., Xiomara P. Blanco-ValenciaFuentes:scopusFeature Extraction Analysis for Emotion Recognition from ICEEMD of Multimodal Physiological Signals
Conference ObjectAbstract: The emotions identification is a very complex task due to depending on multiple variables individualPalabras claves:Emotion recognition, Improved complementary ensemble empirical mode decomposition, Multimodal, physiological signals, Signal processingAutores:A. E. Castro-Ospina, Carolina M. Duque-Mejía, Cristian Mejía-Arboleda, Diego Hernán Peluffo-Ordóñez, Gomez-Lara J.F., Javier E. Revelo-Fuelagán, Miguel A. Becerra, Ordóñez-Bolaños O.A., Rodríguez J.L.Fuentes:scopusElectroencephalographic signals and emotional states for tactile pleasantness classification
Conference ObjectAbstract: Haptic textures are alterations of any surface that are perceived and identified using the sense ofPalabras claves:Electroencephalographic signal, Sensorial stimulus, Signal processing, Tactile pleasantnessAutores:A. E. Castro-Ospina, Cristian Mejía-Arboleda, Diego Hernán Peluffo-Ordóñez, Durango J., Londoño-Delgado E., Miguel A. Becerra, Pelaez-Becerra S.M.Fuentes:scopusNon-generalized Analysis of the Multimodal Signals for Emotion Recognition: Preliminary Results
Conference ObjectAbstract: Emotions are mental states associated with some stimuli, and they have a relevant impact on the peopPalabras claves:Emotion recognition, physiological signals, Signal processingAutores:A. E. Castro-Ospina, Camilo Zapata-Hernandez, Carolina M. Duque-Mejía, Cristian Mejía-Arboleda, Diego Hernán Peluffo-Ordóñez, Londoño-Delgado E., Miguel A. BecerraFuentes:scopusOdor pleasantness classification from electroencephalographic signals and emotional states
Conference ObjectAbstract: Odor identification refers to the capability of the olfactory sense for discerning odors. The interePalabras claves:Electroencephalographic signal, Emotion, Odor pleasantness, Sensorial stimuli, Signal processingAutores:A. E. Castro-Ospina, Diego Hernán Peluffo-Ordóñez, Londoño-Delgado E., Marín-Castrillón D.M., Miguel A. Becerra, Pelaez-Becerra S.M., Serna-Guarin L.Fuentes:scopusParkinson’s Disease Diagnosis Through Electroencephalographic Signal Processing and Sub-optimal Feature Extraction
Conference ObjectAbstract: Parkinson’s disease is the second most common neurological disorder after Alzheimer. Several limitatPalabras claves:EEG, Machine learning, Medical informatics, Parkinson’s Disease, Signal processing, Waveform shapeAutores:Diego Hernán Peluffo-Ordóñez, Manuel Eugenio Morocho-Cayamcela, Pozo-Ruiz S., Torres D.M.Fuentes:scopusLow Resolution Electroencephalographic-Signals-Driven Semantic Retrieval: Preliminary Results
Conference ObjectAbstract: Nowadays, there exist high interest in the brain-computer interface (BCI) systems, and there are mulPalabras claves:Electroencephalographic signal, Machine learning, Semantic category, Semantic retrieval, Signal processingAutores:Botero-Henao O.I., Cristian Mejía-Arboleda, Diego Hernán Peluffo-Ordóñez, Londoño-Delgado E., Marín-Castrillón D.M., Miguel A. BecerraFuentes:scopus