Results 11 to 20 of about 1,664,025 (288)

Deep and Wide Transfer Learning with Kernel Matching for Pooling Data from Electroencephalography and Psychological Questionnaires

Sensors, 2021
Motor imagery (MI) promotes motor learning and encourages brain–computer interface systems that entail electroencephalogram (EEG) decoding. However, a long period of training is required to master brain rhythms’ self-regulation, resulting in users with ...
Diego Fabian Collazos-Huertas, Luisa Fernanda Velasquez-Martinez, Hernan Dario Perez-Nastar, Andres Marino Alvarez-Meza, German Castellanos-Dominguez   +4 more
doaj   +1 more source

Kernel-Based Regularized EEGNet Using Centered Alignment and Gaussian Connectivity for Motor Imagery Discrimination

Computers, 2023
Brain–computer interfaces (BCIs) from electroencephalography (EEG) provide a practical approach to support human–technology interaction. In particular, motor imagery (MI) is a widely used BCI paradigm that guides the mental trial of motor tasks without ...
Mateo Tobón-Henao, Andrés Marino Álvarez-Meza, Cesar German Castellanos-Dominguez   +2 more
doaj   +1 more source

KCS-FCnet: Kernel Cross-Spectral Functional Connectivity Network for EEG-Based Motor Imagery Classification

Diagnostics, 2023
This paper uses EEG data to introduce an approach for classifying right and left-hand classes in Motor Imagery (MI) tasks. The Kernel Cross-Spectral Functional Connectivity Network (KCS-FCnet) method addresses these limitations by providing richer ...
Daniel Guillermo García-Murillo, Andrés Marino Álvarez-Meza, Cesar German Castellanos-Dominguez   +2 more
doaj   +1 more source

Recognition of a signal peptide by the signal recognition particle [PDF]

Nature, 2010
Targeting of proteins to appropriate subcellular compartments is a crucial process in all living cells. Secretory and membrane proteins usually contain an amino-terminal signal peptide, which is recognized by the signal recognition particle (SRP) when nascent polypeptide chains emerge from the ribosome.
Janda, C, Li, J, Oubridge, C, Hernández, H, Robinson, C, Nagai, K   +5 more
openaire   +2 more sources

Feet Segmentation for Regional Analgesia Monitoring Using Convolutional RFF and Layer-Wise Weighted CAM Interpretability

Computation, 2023
Regional neuraxial analgesia for pain relief during labor is a universally accepted, safe, and effective procedure involving administering medication into the epidural.
Juan Carlos Aguirre-Arango, Andrés Marino Álvarez-Meza, German Castellanos-Dominguez   +2 more
doaj   +1 more source

Regression Networks for Neurophysiological Indicator Evaluation in Practicing Motor Imagery Tasks

Brain Sciences, 2020
Motor Imagery (MI) promotes motor learning in activities, like developing professional motor skills, sports gestures, and patient rehabilitation. However, up to 30% of users may not develop enough coordination skills after training sessions because of ...
Luisa Velasquez-Martinez, Julian Caicedo-Acosta, Carlos Acosta-Medina, Andres Alvarez-Meza, German Castellanos-Dominguez   +4 more
doaj   +1 more source

Affective Neural Responses Sonified through Labeled Correlation Alignment

Sensors, 2023
Sound synthesis refers to the creation of original acoustic signals with broad applications in artistic innovation, such as music creation for games and videos.
Andrés Marino Álvarez-Meza, Héctor Fabio Torres-Cardona, Mauricio Orozco-Alzate, Hernán Darío Pérez-Nastar, German Castellanos-Dominguez   +4 more
doaj   +1 more source

CNN-based framework using spatial dropping for enhanced interpretation of neural activity in motor imagery classification

Brain Informatics, 2020
Interpretation of brain activity responses using motor imagery (MI) paradigms is vital for medical diagnosis and monitoring. Assessed by machine learning techniques, identification of imagined actions is hindered by substantial intra- and inter-subject ...
D. F. Collazos-Huertas, A. M. Álvarez-Meza, C. D. Acosta-Medina, G. A. Castaño-Duque, G. Castellanos-Dominguez   +4 more
doaj   +1 more source

Image-Based Learning Using Gradient Class Activation Maps for Enhanced Physiological Interpretability of Motor Imagery Skills

Applied Sciences, 2022
Brain activity stimulated by the motor imagery paradigm (MI) is measured by Electroencephalography (EEG), which has several advantages to be implemented with the widely used Brain–Computer Interfaces (BCIs) technology.
Diego F. Collazos-Huertas, Andrés M. Álvarez-Meza, German Castellanos-Dominguez   +2 more
doaj   +1 more source

Subject-Dependent Artifact Removal for Enhancing Motor Imagery Classifier Performance under Poor Skills

Sensors, 2022
The Electroencephalography (EEG)-based motor imagery (MI) paradigm is one of the most studied technologies for Brain-Computer Interface (BCI) development.
Mateo Tobón-Henao, Andrés Álvarez-Meza, Germán Castellanos-Domínguez   +2 more
doaj   +1 more source