Mostrando 10 resultados de: 35
Publisher
2022 IEEE ANDESCON: Technology and Innovation for Andean Industry, ANDESCON 2022(5)
IFAC-PapersOnLine(5)
2018 IEEE 3rd Ecuador Technical Chapters Meeting, ETCM 2018(3)
NeuroImage(3)
2017 IEEE 2nd Ecuador Technical Chapters Meeting, ETCM 2017(2)
Área temáticas
Fisiología humana(16)
Enfermedades(15)
Física aplicada(8)
Ciencias de la computación(7)
Métodos informáticos especiales(6)
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:scopusClustering of EEG occipital signals using k-means
Conference ObjectAbstract: Recent studies show that it is feasible to use electrical signals from Electro-encephalography (EEG)Palabras claves:Butterworth Filter, Clusterization, Direct Current Artifacts, Electro-encephalography, Fast fourier transform, Occipital Lobe, Signal PreprocessingAutores:Carlos A. Salazar, Carmen Vaca-Ruiz, Christian Sacarelo, Enrique Pelaez, Francis R. Loayza, Kerly Ochoa, Victor Asanza ArmijosFuentes:googlescopusAuthor Correction: Federated learning enables big data for rare cancer boundary detection (Nature Communications, (2022), 13, 1, (7346), 10.1038/s41467-022-33407-5)
OtherAbstract: In this article the author name Carmen Balaña was incorrectly written as Carmen Balaña Quintero. ThePalabras claves:Autores:Agzarian M., Alexander G.S., Baid U., Balaña C., Bendszus M., Bhardwaj S., Bilello M., Brugnara G., Calabrese E., Capellades J., Cha S., Chang K., Chen C., Chong C., Cloughesy T.F., Currie S., Davatzikos C., Dicker A.P., Dostál M., Dou Q., Edwards B., Ellingson B.M., Ezhov I., Falcão A.X., Farinhas J., Fatania K., Flanders A.E., Foley P., Francis R. Loayza, Frood R., Garrett J., Ghodasara S., Gruzdev A., Hagiwara A., Haunschmidt A., Heng P.A., Holcomb J., Huang R.Y., Ingalhalikar M., Jadhav M., Jeraj R., Jiang M., Jones C.K., Karkada D., Keřkovský M., Kofler F., Kopřivová T., Kozubek M., LaMontagne P., Larson M., Liem S., Lombardo J., Lucio D.R., Lux F., Maier-Hein K., Maldjian J.A., Marcus D., Martins S.B., Matula P., Meckel S., Menotti D., Metz M., Michálek J., Mitchell J.R., Mohan S., Necker G., Oughourlian T., Palmer J.D., Pandey U., Pati S., Pichler J., Pinho M.C., Preetha C.J., Puig J., Raymond C., Reddy D., Reina G.A., Rudie J., Sahm F., Saini J., Sair H.I., Sako C., Sebastian Quevedo, Sheller M., Shukla G., So T.Y., Sprenger F., Teixeira B.C.A., To M.S., Trenkler J., Venkataraman A., Villanueva-Meyer J., Vogelbaum M.A., Vollmuth P., Vybíhal V., Wagner B.C., Wang C., Wang S.H., Wick W., Wiestler B., Yogananda C.G.B., Zenk M.Fuentes:scopusAutomatic Brain White Matter Hyperintensities Segmentation with Swin U-Net
Conference ObjectAbstract: This work proposes an automatic segmentation approach to detect White Matter Hyperintensities (WMH)Palabras claves:deep learning, segmentation, Swin-Transformer, WMHAutores:Bryan V. Piguave, Enrique Pelaez, Francis R. Loayza, José ViteriFuentes:googlescopusAutomatic brain white matter hypertinsities segmentation using deep learning techniques
Conference ObjectAbstract: White Matter Hyperintensities (WMH) are lesions observed in the brain as bright regions in Fluid AttPalabras claves:Convolutional neural network, U-net, WMH SegmentationAutores:Enrique Pelaez, Fabricio Layedra, Francis R. Loayza, José ViteriFuentes:googlescopusBCI 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:scopusBrain Activity and Functional Connectivity Patterns Associated With Fast and Slow Motor Sequence Learning in Late Middle Adulthood
ArticleAbstract: The human brain undergoes structural and functional changes across the lifespan. The study of motorPalabras claves:aging, Connectivity, fast learning, FMRI, motor sequence learning, slow learningAutores:Aznárez-Sanado M., Eudave L., Fernández-Seara M.A., Francis R. Loayza, Luis E.O., Martínez M., Pastor M.A., Villagra F.Fuentes:scopusAnatomical Patterns Recognition of Impulse Control Disorders of Parkinsonian Patients Using Deep Learning of MRI structural images
Conference ObjectAbstract: In Parkinson's disease (PD) several neuropsychiatric conditions are highly frequent including impulsPalabras claves:deep learning, Impulsive Compulsive Disorders, MRI, PÁRKINSONAutores:Alexander Saravia, Enrique Pelaez, Francis R. Loayza, Jocellyn Luna, Obeso I., Victor Asanza ArmijosFuentes:googlescopusA 3D-Printed EEG based prosthetic arm
Conference ObjectAbstract: Nowadays, with the use of 3D printers, the upper limb prosthesis is more available, mainly the myoelPalabras claves:3D-printed, Brain-Computer Interface, Electroencephalographic, Neurosky, Prosthetic ArmAutores:Francis R. Loayza, Fuentes-Gonzalez J., Infante-Alarcon A., Victor Asanza ArmijosFuentes:googlescopusA Pipeline for Segmenting and Classifying Brain Lesions Caused by Stroke: A Machine Learning Approach
Conference ObjectAbstract: Brain injuries caused by strokes are one of the leading causes of disability in the world. Current pPalabras claves:Artificial Intelligence, Brain injuries, Machine learning, strokeAutores:Alex Macas, Enrique Pelaez, Francis R. Loayza, Franco-Maldonado H., Roberto MenaFuentes:scopus