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Hand Gesture Recognition Using EMG-IMU Signals and Deep Q-Networks
ArticleAbstract: Hand gesture recognition systems (HGR) based on electromyography signals (EMGs) and inertial measurePalabras claves:deep Q-network, Electromyography, Hand gesture recognition, inertial measurement unit, reinforcement learningAutores:Ángel Leonardo Valdivieso Caraguay, Juan Pablo Vasconez, Lorena Isabel Barona López, Marco E. BenalcázarFuentes:googlescopusHand Gesture Recognition and Tracking Control for a Virtual UR5 Robot Manipulator
Conference ObjectAbstract: Human-machine interfaces (HMIs) have received an increased attention during the past decades, speciaPalabras claves:Hand gesture recognition, Human Robot Interface, Movement Tracking, Virtual Robotic ManipulatorAutores:Alex Chico, Ángel Leonardo Valdivieso Caraguay, Juan Pablo Vasconez, Lorena Isabel Barona López, Marco E. Benalcázar, Patricio J. Cruz, Patricio Javier Cruz Davalos, Robin AlvarezFuentes:googlescopusHand Gesture and Arm Movement Recognition for Multimodal Control of a 3-DOF Helicopter
Conference ObjectAbstract: This paper presents the application of hand gestures and arm movements to control a dual rotor testbPalabras claves:3-DOF helicopter, Arm movement recognition, Hand gesture recognition, Multimodal controlAutores:Ángel Leonardo Valdivieso Caraguay, Juan Pablo Vasconez, Lorena Isabel Barona López, Marco E. Benalcázar, Patricio J. Cruz, Patricio Javier Cruz Davalos, Ricardo Romero, Robin AlvarezFuentes:googlescopusHand gesture recognition using machine learning and infrared information: a systematic literature review
ArticleAbstract: Currently, gesture recognition is like a problem of feature extraction and pattern recognition, in wPalabras claves:Gesture recognition, Infrared information, Machine learning, Systematic literature reviewAutores:Marco E. Benalcázar, Rubén NogalesFuentes:googlescopusHand gesture recognition using machine learning and the myo armband
Conference ObjectAbstract: Gesture recognition has multiple applications in medical and engineering fields. The problem of handPalabras claves:Autores:Andrés G. Jaramillo, Andrés Jaramillo-Yánez, Jonathan A. Zea, Marco E. Benalcázar, Víctor Hugo AndaluzFuentes:scopusFeature Evaluation of EMG Signals for Hand Gesture Recognition Based on Mutual Information, Fuzzy Entropy and RES Index
Conference ObjectAbstract: In the field of hand gesture recognition based on electromyography, the selection of features is stiPalabras claves:Electromyography, Feature evaluation, Fuzzy entropy, Hand gesture recognition, mutual information, Myo armband sensorAutores:Ángel Leonardo Valdivieso Caraguay, Jonathan A. Zea, Lorena Isabel Barona López, Marco E. Benalcázar, Xavier AguasFuentes:googlescopusEducational Impact on Ecuadorian University Students Due to the COVID-19 Context
ArticleAbstract: The mobility restrictions imposed in different countries due to the pandemic of Sars-CoV2 has hugelyPalabras claves:covid-19, ECUADOR, Educational impact, PLS-SEM, SARS-COV2, University StudentsAutores:Ángel Leonardo Valdivieso Caraguay, Cesar J. Santacruz, Daniel Velastegui, Lorena Isabel Barona López, Marco E. Benalcázar, Victor Hugo VimosFuentes:scopusConstruction of a Dataset for Static and Dynamic Hand Tracking Using a Non-invasive Environment
Conference ObjectAbstract: The research consists of hand gesture recognition using a commercial sensor called Leap Motion ContrPalabras claves:Acquisition system, Hand gesture recognition, Non-invasive monitoringAutores:Alexis Palate, Bryan Toalumbo, Javier Vargas, Marco E. Benalcázar, Ronnie Martinez, Rubén NogalesFuentes:googlescopus2D semantic segmentation of the prostate gland in magnetic resonance images using convolutional neural networks
Conference ObjectAbstract: Convolutional Neural Networks is one of the most commonly used methods for automatic prostate segmenPalabras claves:Central Gland, convolutional neural networks, Encoder-Classifier, Encoder-Decoder, MRIs, NCI-ISBI 2013, Peripheral Zone, Prostate Segmentation, U-net, VGG16Autores:Marco E. Benalcázar, Silvia P. VacacelaFuentes:googlescopusA Brain-Computer Interface for Controlling IoT Devices using EEG Signals
Conference ObjectAbstract: Motor disability is the loss of the ability to move a limb of the body. Motor disabilities make diffPalabras claves:Bci, EEG, IOT, k-NNAutores:Kelvin Ortíz Chicaiza, Marco E. BenalcázarFuentes:scopus