RODOLFO V.
GARCIA BERMUDEZ
Universidad Técnica de Manabí
Portoviejo, EcuadorPublications en collaboration avec des chercheurs de Universidad Técnica de Manabí (11)
2024
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Cross-dataset evaluation of wearable fall detection systems using data from real falls and long-term monitoring of daily life
Measurement: Journal of the International Measurement Confederation, Vol. 235
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UMATUG: A dataset of inertial signals of older and young adults using a gerontologic simulator collected during instrumented Timed Up and Go (iTUG) tests
Data in Brief
2021
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Differentiation of saccadic eye movement signals
Sensors, Vol. 21, Núm. 15
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Features Selection for Fall Detection Systems Based on Machine Learning and Accelerometer Signals
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
2020
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A hybrid unsupervised-Deep learning tandem for electrooculography time series analysis
PLoS ONE, Vol. 15, Núm. 7 July
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Evaluating Mutual Information and Chi-Square Metrics in Text Features Selection Process: A Study Case Applied to the Text Classification in PubMed
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
2019
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Unsupervised Learning as a Complement to Convolutional Neural Network Classification in the Analysis of Saccadic Eye Movement in Spino-Cerebellar Ataxia Type 2
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
2017
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Architecture for neurological coordination tests implementation
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
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Automatic glissade determination through a mathematical model in electrooculographic records
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
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Data mining process for identification of non-spontaneous saccadic movements in clinical electrooculography
Neurocomputing, Vol. 250, pp. 28-36
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Evaluation of algorithms for automatic classification of heart sound signals
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)