Mostrando 5 resultados de: 5
Filtros aplicados
Subtipo de publicación
Conference Object(5)
Área temáticas
Enfermedades(3)
Fisiología humana(2)
Física aplicada(2)
Ciencias de la computación(1)
Funcionamiento de bibliotecas y archivos(1)
Año de Publicación
2021(5)
Origen
scopus(5)
Classification of subjects with parkinson's disease using finger tapping dataset
Conference ObjectAbstract: Parkinson's disease is the second most common neurodegenerative disorder and affects more than 7 milPalabras claves:classification, Finger Tapping, Machine learning, Parkinson's DiseaseAutores:Diego Hernán Peluffo-Ordóñez, Enrique Pelaez, Francis R. Loayza, Leandro L. Lorente-Leyva, Sanchez-Pozo N.N., Victor Asanza ArmijosFuentes:scopusBCI system using a novel processing technique based on electrodes selection for hand prosthesis control
Conference ObjectAbstract: This work proposes an end-to-end model architecture, from feature extraction to classification usingPalabras claves:Bio-signals analysis, Brain computer interface, Embedded Systems, Fpga, Neural networksAutores:Alisson Constantine, Diego Hernán Peluffo-Ordóñez, Enrique Pelaez, Francis R. Loayza, Victor Asanza ArmijosFuentes:scopusA voice analysis approach for recognizing Parkinson's disease patterns
Conference ObjectAbstract: Many of the patients diagnosed with Parkinson's disease (PD) do not know they have it until the mostPalabras claves:Machine learning, PÁRKINSON, Voice AnalysisAutores:Enrique Pelaez, Francis R. Loayza, Paucar G. Bryan, Yu Chen TaiFuentes:scopusPattern recognition of white matter lesions associated with diabetes mellitus type 2
Conference ObjectAbstract: The White Matter Hyperintensities (WMHs) are usually associated with diabetes which is relevant in mPalabras claves:classification, DIABÉTES, Machine learning, segmentation, WMH brain lesionsAutores:Alvarado R., Enrique Pelaez, Francis R. Loayza, Jocellyn Luna, Pastor M.A.Fuentes:scopusSSVEP-EEG signal classification based on emotiv EPOC BCI and raspberry pi
Conference ObjectAbstract: This work presents the experimental design for recording Electroencephalography (EEG) signals in 20Palabras claves:Brain computer interface, classification, Data acquisition, Machine learning, SSVEP-EEG, XGBoostAutores:Enrique Pelaez, Félix Rosales-Uribe, Francis R. Loayza, Hector Trivino-Gonzalez, Jamil Torres-Brunes, Karla Avilés-Mendoza, Raquel Tinoco-Egas, Ricardo Cajo, Victor Asanza ArmijosFuentes:scopus