Francisco Sepulveda
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Cited by
A review of non-invasive techniques to detect and predict localised muscle fatigue
MR Al-Mulla, F Sepulveda, M Colley
Sensors 11 (4), 3545-3594, 2011
Classifying mental tasks based on features of higher-order statistics from EEG signals in brain–computer interface
SM Zhou, JQ Gan, F Sepulveda
Information Sciences 178 (6), 1629-1640, 2008
Visual modifications on the P300 speller BCI paradigm
M Salvaris, F Sepulveda
Journal of neural engineering 6 (4), 046011, 2009
P300-based BCI mouse with genetically-optimized analogue control
L Citi, R Poli, C Cinel, F Sepulveda
IEEE transactions on neural systems and rehabilitation engineering 16 (1), 51-61, 2008
A neural network representation of electromyography and joint dynamics in human gait
F Sepulveda, DM Wells, CL Vaughan
Journal of biomechanics 26 (2), 101-109, 1993
Does short-term exposure to mobile phone base station signals increase symptoms in individuals who report sensitivity to electromagnetic fields? A double-blind randomized†…
S Eltiti, D Wallace, A Ridgewell, K Zougkou, R Russo, F Sepulveda, ...
Environmental health perspectives 115 (11), 1603-1608, 2007
A user-independent real-time emotion recognition system for software agents in domestic environments
E Leon, G Clarke, V Callaghan, F Sepulveda
Engineering applications of artificial intelligence 20 (3), 337-345, 2007
Delta band contribution in cue based single trial classification of real and imaginary wrist movements
A Vuckovic, F Sepulveda
Medical & biological engineering & computing 46 (6), 529-539, 2008
Towards cooperative brain-computer interfaces for space navigation
R Poli, C Cinel, A Matran-Fernandez, F Sepulveda, A Stoica
Proceedings of the 2013 international conference on Intelligent user†…, 2013
Neuro-fuzzy extraction of angular information from muscle afferents for ankle control during standing in paraplegic subjects: an animal model
S Micera, W Jensen, F Sepulveda, RR Riso, T Sinkjśr
IEEE Transactions on Biomedical Engineering 48 (7), 787-794, 2001
An autonomous wearable system for predicting and detecting localised muscle fatigue
MR Al-Mulla, F Sepulveda, M Colley
Sensors 11 (2), 1542-1557, 2011
Short‐term exposure to mobile phone base station signals does not affect cognitive functioning or physiological measures in individuals who report sensitivity to†…
S Eltiti, D Wallace, A Ridgewell, K Zougkou, R Russo, F Sepulveda, E Fox
Bioelectromagnetics: Journal of the Bioelectromagnetics Society, The Society†…, 2009
Wavelets and ensemble of FLDs for P300 classification
M Salvaris, F Sepulveda
2009 4th International IEEE/EMBS Conference on Neural Engineering, 339-342, 2009
A two-stage four-class BCI based on imaginary movements of the left and the right wrist
A Vučković, F Sepulveda
Medical engineering & physics 34 (7), 964-971, 2012
Brain–computer interface for single-trial EEG classification for wrist movement imagery using spatial filtering in the gamma band
YU Khan, F Sepulveda
IET signal processing 4 (5), 510-517, 2010
Do TETRA (Airwave) base station signals have a short-term impact on health and well-being? A randomized double-blind provocation study
D Wallace, S Eltiti, A Ridgewell, K Garner, R Russo, F Sepulveda, ...
Environmental Health Perspectives 118 (6), 735, 2010
A novel design of 4-class BCI using two binary classifiers and parallel mental tasks
T Geng, JQ Gan, M Dyson, CSL Tsui, F Sepulveda
computational Intelligence and Neuroscience 2008, 2008
sEMG techniques to detect and predict localised muscle fatigue
MR Al-Mulla, F Sepulveda, M Colley
EMG methods for evaluating muscle and nerve function, 157-186, 2012
Two artificial neural systems for generation of gait swing by means of neuromuscular electrical stimulation
F Sepulveda, MH Granat, A Cliquet Jr
Medical engineering & physics 19 (1), 21-28, 1997
A comparison of time, frequency and ICA based features and five classifiers for wrist movement classification in EEG signals
I Navarro, B Hubais, F Sepulveda
2005 IEEE Engineering in Medicine and Biology 27th Annual Conference, 2118-2121, 2006
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