Marisol Rodriguez-Ugarte

Affiliations:
  • Miguel Hernández University of Elche, Spain
  • Imperial College London, UK (former)


According to our database1, Marisol Rodriguez-Ugarte authored at least 12 papers between 2014 and 2019.

Collaborative distances:
  • Dijkstra number2 of five.
  • Erdős number3 of five.

Timeline

Legend:

Book 
In proceedings 
Article 
PhD thesis 
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Other 

Links

Online presence:

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Bibliography

2019
The Effect of tDCS on EEG-Based Functional Connectivity in Gait Motor Imagery.
Proceedings of the Understanding the Brain Function and Emotions, 2019

2018
Effects of tDCS on Real-Time BCI Detection of Pedaling Motor Imagery.
Sensors, 2018

Novel tDCS montage favors lower limb motor imagery detection.
Proceedings of the 40th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, 2018

Comparison of different EEG signal analysis techniques for an offline lower limb motor imagery brain-computer interface.
Proceedings of the 40th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, 2018

2017
Personalized Offline and Pseudo-Online BCI Models to Detect Pedaling Intent.
Frontiers Neuroinformatics, 2017

Empirical mode decomposition use in electroencephalography signal analysis for detection of starting and stopping intentions during gait cycle.
Proceedings of the 26th IEEE International Symposium on Robot and Human Interactive Communication, 2017

Using EEG Signals to Detect Different Surfaces While Walking.
Proceedings of the Biomedical Applications Based on Natural and Artificial Computing, 2017

Classification of Gait Motor Imagery While Standing Based on Electroencephalographic Bandpower.
Proceedings of the Biomedical Applications Based on Natural and Artificial Computing, 2017

Effect on the classification of motor imagery in EEG after applying anodal tDCS with a 4×1 ring montage over the motor cortex.
Proceedings of the International Conference on Rehabilitation Robotics, 2017

2016
Analyzing electrode configurations to detect intention of pedaling initiation through EEG signals.
Proceedings of the 2016 IEEE International Conference on Systems, Man, and Cybernetics, 2016

Detection of intention of pedaling start cycle through EEG signals.
Proceedings of the 38th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, 2016

2014
Developing a Novel fMRI-Compatible Motion Tracking System for Haptic Motor Control Experiments.
Proceedings of the 2nd International Congress on Neurotechnology, 2014


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