People

Professor Francisco Sepulveda

Professor
School of Computer Science and Electronic Engineering (CSEE)
Professor Francisco Sepulveda
  • Email

  • Telephone

    +44 (0) 1206 874151

  • Location

    1NW.3.20, Colchester Campus

  • Academic support hours

    Autumn 2018: Tuesdays 14:00-15:00 and Thursdays 11:00-12:00.

Profile

Biography

Member of the BCI-NE research group Member of the Artificial Intelligence Group Member of the Computational Intelligence Centre Member of the Centre for Assisted Living Technologies Previous positions: 1999 - 2002: Assistant Professor, Biomedical Engineering, Center for Sensorimotor Interaction, Aalborg University, Denmark 1996 - 1998: FAPESP Postdoctoral Fellow, Biomedical Engineering Dept., Unicamp, Brazil (See also:staff research interests by category)

Qualifications

  • PhD Summa Cum Laude in Biomedical/Electrical Engineering, UNICAMP (Brazil), with a Fellowship at the Bioengineering Unit, University of Strathclyde

  • MSc (Dist) in Bioengineering, Clemson University

  • BSc in Nuclear Engineering, University of California - Santa Barbara (receiving the 'Outstanding Student' award)

Research and professional activities

Research interests

Brain-computer interfaces

Open to supervise

Neural prostheses and neuromuscular electrical stimulation

Open to supervise

Bioelectronics

Open to supervise

Rehabilitation engineering

Open to supervise

Myoelectric operation of artificial limbs and robotic devices

Open to supervise

Biomedical signal analysis

Open to supervise

Computational neuroscience

Open to supervise

Sensori-motor neurophysiology

Open to supervise

Affective computing

Open to supervise

Intelligent systems, both artificial and natural

Open to supervise

Mathematical modelling of muscle and nerve

Open to supervise

Current research

Brain-computer interfaces

Neural prostheses and neuromuscular electrical stimulation

Bioelectronics

Rehabilitation engineering

Myoelectric operation of artificial limbs and robotic devices

Biomedical signal analysis

Computational neuroscience

Affective computing

Intelligent systems, both artificial and natural

Mathematical modelling of muscle and nerve

Teaching and supervision

Current teaching responsibilities

  • Fundamentals of Digital Systems (CE161)

  • Foundations of Electronics II (CE164)

  • Team Project Challenge (CE101)

Previous supervision

Youngjae Song
Youngjae Song
Thesis title: Sound-Production Related Cognitive Tasks for Onset Detection in Self-Paced Brain-Computer Interfaces
Degree subject: Computer Science
Degree type: Doctor of Philosophy
Awarded date: 8/12/2017
Luz Maria Alonso Valerdi
Luz Maria Alonso Valerdi
Thesis title: Human-Computer Interaction in Synchronous Motor Imagery Bcis: A Study Aided By a Simulated Living-Environment Platform
Degree subject: Computing and Electronic Systems
Degree type: Doctor of Philosophy
Awarded date: 20/2/2014
Youngjae Song
Youngjae Song
Degree subject: Advanced Computer Science
Degree type: Master of Science
Awarded date: 8/11/2013

Publications

Journal articles (56)

Jahangiri, A. and Sepulveda, F., (2019). The Relative Contribution of High-Gamma Linguistic Processing Stages of Word Production, and Motor Imagery of Articulation in Class Separability of Covert Speech Tasks in EEG Data. Journal of Medical Systems. 43 (2), 20-

Jahangiri, A. and Sepulveda, F., (2019). Correction to: The Relative Contribution of High-Gamma Linguistic Processing Stages of Word Production, and Motor Imagery of Articulation in Class Separability of Covert Speech Tasks in EEG Data. Journal of Medical Systems. 43 (8), 237-

Song, Y. and Sepulveda, F., (2018). A Novel Technique for Selecting EMG-Contaminated EEG Channels in Self-Paced Brain-Computer Interface Task Onset. IEEE Transactions on Neural Systems and Rehabilitation Engineering. 26 (7), 1353-1362

Al-Mulla, MR., Al-Bader, B., Ghaaedi, FK. and Sepulveda, F., (2017). Effects of Array Electrode Placement on Identifying Localised Muscle Fatigue. World Academy of Science, Engineering and Technology, International Journal of Biomedical and Biological Engineering. 4

Song, Y. and Sepulveda, F., (2017). A novel onset detection technique for brain?computer interfaces using sound-production related cognitive tasks in simulated-online system. Journal of Neural Engineering. 14 (1), 016019-016019

Damjanovic, L., Meyer, M. and Sepulveda, F., (2017). Raising the Alarm: Individual Differences in the Perceptual Awareness of Masked Facial Expressions. Brain and Cognition. 114, 1-10

Alonso-Valerdi, LM., Gutiérrez-Begovich, DA., Argüello-García, J., Sepulveda, F. and Ramírez-Mendoza, RA., (2016). User Experience May be Producing Greater Heart Rate Variability than Motor Imagery Related Control Tasks during the User-System Adaptation in Brain-Computer Interfaces. Frontiers in Physiology. 7 (JUL)

Alonso-Valerdi, LM., Sepulveda, F. and Ramírez-Mendoza, RA., (2015). Perception and cognition of cues Used in synchronous Brain–computer interfaces Modify electroencephalographic Patterns of control Tasks. Frontiers in human neuroscience. 9 (NOV), 636-636

Al-Mulla, MR. and Sepulveda, F., (2015). Super wavelet for sEMG signal extraction during dynamic fatiguing contractions. Journal of medical systems. 39 (1), 167-167

Al-Mulla, MR., Sepulveda, F. and Al-Bader, B., (2015). Optimal Elbow Angle for Extracting sEMG Signals During Fatiguing Dynamic Contraction. Computers. 4 (3), 251-264

Alonso-Valerdi, LM. and Sepulveda, F., (2014). Development of a simulated living-environment platform: design of BCI assistive software and modeling of a virtual dwelling place. Computer-Aided Design. 54, 39-50

Al-Mulla, MR. and Sepulveda, F., (2014). Novel Pseudo-Wavelet function for MMG signal extraction during dynamic fatiguing contractions. Sensors. 14 (6), 9489-9504

Vučković, A. and Sepulveda, F., (2012). A two-stage four-class BCI based on imaginary movements of the left and the right wrist. Medical Engineering and Physics. 34 (7), 964-971

Poli, R., Cinel, C., Matran-Fernandez, A., Sepulveda, F. and Stoica, A., (2012). Some steps towards realtime control of a space-craft simulator via a brain-computer interface. University of Essex, Tech. Rep. CES-525

Khan, YU. and Sepulveda, F., (2012). EEG single-trial classification of different motor imagery tasks using measures of dispersion and power in frequency bands. International Journal of Biomedical Engineering and Technology. 8 (4), 343-356

Wallace, D., Eltiti, S., Ridgewell, A., Garner, K., Russo, R., Sepulveda, F., Walker, S., Quinlan, T., Dudley, S., Maung, S. and others, (2011). Cognitive and physiological responses in humans exposed to a TETRA base station signal in relation to perceived electromagnetic hypersensitivity. Bioelectromagnetics. 33 (1), 23-39

Al-Mulla, MR., Sepulveda, F. and Colley, M., (2011). Evolved pseudo-wavelet function to optimally decompose sEMG for automated classification of localized muscle fatigue. Medical Engineering and Physics. 33 (4), 411-417

Al-Mulla, MR., Sepulveda, F. and Colley, M., (2011). An autonomous wearable system for predicting and detecting localised muscle fatigue. Sensors. 11 (2), 1542-1557

Khan, YU. and Sepulveda, F., (2011). Wrist movement discrimination in single-trial EEG for Brain–Computer Interface using band powers. International Journal of Biomedical Engineering and Technology. 6 (3), 272-285

Al-Mulla, MR., Sepulveda, F. and Colley, MJ., (2011). A Review of Non-Invasive Techniques to Detect and Predict Localised Muscle Fatigue. Sensors. 2011 (11), 3545-3594

Salvaris, M. and Sepulveda, F., (2010). Classification effects of real and imaginary movement selective attention tasks on a P300-based brain?computer interface. Journal of Neural Engineering. 7 (5), creators-Sepulveda=3AFrancisco=3A=3A

Wallace, D., Eltiti, S., Ridgewell, A., Garner, K., Russo, R., Sepulveda, F., Walker, S., Quinlan, T., Dudley, SEM., Maung, S. and others, (2010). Do TETRA (Airwave) base station signals have a short-term impact on health and well-being? A randomized double-blind provocation study. Environmental Health Perspectives. 118 (6), 735-735

Poli, R., Citi, L., Salvaris, M., Cinel, C. and Sepulveda, F., (2010). Eigenbrains: the free vibrational modes of the brain as a new representation for EEG. Engineering in Medicine and Biology Society (EMBC), 2010 Annual International Conference of the IEEE. 2010, 6011-6014

Salvaris, M., Cinel, C., Poli, R., Citi, L. and Sepulveda, F., (2010). Exploring multiple protocols for a brain-computer interface mouse. 2010 Annual International Conference of the IEEE Engineering in Medicine and Biology. 2010, 4189-4192

Dyson, M., Sepulveda, F. and Gan, JQ., (2010). Localisation of cognitive tasks used in EEG-based BCIs. Clinical Neurophysiology. 121 (9), 1481-1493

Poli, R., Cinel, C., Citi, L. and Sepulveda, F., (2010). Reaction-time binning: A simple method for increasing the resolving power of ERP averages. Psychophysiology. 47 (3), 467-485

Al-Mulla, MR. and Sepulveda, F., (2010). Novel Feature Modelling the Prediction and Detection of sEMG Muscle Fatigue towards an Automated Wearable System. Sensors. 10 (5), 4838-4854

Khan, YU. and Sepulveda, F., (2010). Brain–computer interface for single-trial EEG classification for wrist movement imagery using spatial filtering in the gamma band. IET Signal Processing. 4 (5), 510-510

Poli, R., Citi, L., Sepulveda, F. and Cinel, C., (2009). Analogue evolutionary brain computer interfaces. IEEE Computational Intelligence Magazine. 4 (4), 27-31

Menon, C., de Negueruela, C., Millán, JDR., Tonet, O., Carpi, F., Broschart, M., Ferrez, P., Buttfield, A., Tecchio, F., Sepulveda, F., Citi, L., Laschi, C., Tombini, M., Dario, P., Maria Rossini, P. and De Rossi, D., (2009). Prospects of brain–machine interfaces for space system control. Acta Astronautica. 64 (4), 448-456

Eltiti, S., Wallace, D., Ridgewell, A., Zougkou, K., Russo, R., Sepulveda, F. and Fox, E., (2009). Short-term exposure to mobile phone base station signals does not affect cognitive functioning or physiological measures in individuals who report sensitivity to electromagnetic fields and controls. Bioelectromagnetics. 30 (7), 556-563

Salvaris, M. and Sepulveda, F., (2009). Visual modifications on the P300 speller BCI paradigm. Journal of Neural Engineering. 6 (4), creators-Sepulveda=3AFrancisco=3A=3A

Gupta, CN., Khan, YU., Palaniappan, R. and Sepulveda, F., (2009). Wavelet framework for improved target detection in oddball paradigms using P300 and gamma band analysis. Biomedical Soft Computing and Human Sciences. 14, 61-67

Gupta, CN., Khan, YU., Palaniappan, R. and Sepulveda, F., (2009). Wavelet Framework for Improved Target Detection in Oddball Paradigms Using P300 and Gamma Band Analysis (< Special Issue> Biosensors: Data Acquisition, Processing and Control). International Journal of Biomedical Soft Computing and Human Sciences: the official journal of the Biomedical Fuzzy Systems Association. 14, 63-69

Zhou, S., Gan, JQ. and Sepulveda, F., (2008). Classifying mental tasks based on features of higher-order statistics from EEG signals in brain-computer interface. Information Sciences. 178 (6), 1639-1640

Vuckovic, A. and Sepulveda, F., (2008). Delta band contribution in cue based single trial classification of real and imaginary wrist movements. Medical & Biological Engineering & Computing. 46 (6), 529-539

Citi, L., Poli, R., Cinel, C. and Sepulveda, F., (2008). P300-Based BCI Mouse With Genetically-Optimized Analogue Control. IEEE Transactions on Neural Systems and Rehabilitation Engineering. 16 (1), 51-61

Vuckovic, A. and Sepulveda, F., (2008). Quantification and visualisation of differences between two motor tasks based on energy density maps for brain?computer interface applications. Clinical Neurophysiology. 119 (2), 446-458

Geng, T., Gan, JQ., Dyson, M., Tui, SSL. and Sepulveda, F., (2008). A novel design of 4-class BCI using two binary classifiers and parallel mental tasks. Computational Intelligence and Neuroscience. 2008, creators-Sepulveda=3AFrancisco=3A=3A

Zhou, S-M., Gan, JQ. and Sepulveda, F., (2008). Classifying mental tasks based on features of higher-order statistics from EEG signals in brain–computer interface. Information Sciences. 178 (6), 1629-1640

Geng, T., Gan, JQ., Dyson, M., Tsui, CSL. and Sepulveda, F., (2008). A Novel Design of 4-Class BCI Using Two Binary Classifiers and Parallel Mental Tasks. Computational Intelligence and Neuroscience. 2008, 1-5

Sepulveda, F., Dyson, M., Gan, JQ. and Tsui, CSL., (2007). A Comparison of Mental Task Combinations for Asynchronous EEG-Based BCIs. 2007 29th Annual International Conference of the IEEE Engineering in Medicine and Biology Society. 2007, 5055-5058

Eltiti, S., Wallace, D., Ridgewell, A., Zougkou, K., Russo, R., Sepulveda, F., Mirshekar-Syahkal, D., Rasor, P., Deeble, R. and Fox, E., (2007). Does Short-Term Exposure to Mobile Phone Base Station Signals Increase Symptoms in Individuals Who Report Sensitivity to Electromagnetic Fields? A Double-Blind Randomized Provocation Study. Environmental Health Perspectives. 115 (11), 1603-1608

Leon, E., Clarke, G., Callaghan, V. and Sepulveda, F., (2007). A user-independent real-time emotion recognition system for software agents in domestic environments. Engineering Applications of Artificial Intelligence. 20 (3), 337-345

Vučković, A. and Sepulveda, F., (2006). EEG single-trial classification of four classes of imaginary wrist movements based on Gabor coefficients

Vuckovic, A. and Sepulveda, F., (2006). EEG gamma band information in cue-based single trial classification of four movements about the right wrist

Leon, E., Clarke, G., Callaghan, V. and Sepulveda, F., (2004). Real-time detection of emotional changes for inhabited environments. Computers & Graphics. 28 (5), 635-642

Hansen, M., Haugland, MK. and Sepulveda, F., (2003). Feasibility of Using Peroneal Nerve Recordings for Deriving Stimulation Timing in a Foot Drop Correction System. Neuromodulation: Technology at the Neural Interface. 6 (1), 68-77

Jensen, W., Sinkjaer, T. and Sepulveda, F., (2002). Improving signal reliability for on-line joint angle estimation from nerve cuff recordings of muscle afferents. IEEE Transactions on Neural Systems and Rehabilitation Engineering. 10 (3), 133-139

Micera, S., Jensen, W., Sepulveda, F., Riso, RR. and Sinkjaer, T., (2001). Neuro-fuzzy extraction of angular information from muscle afferents for ankle control during standing in paraplegic subjects: an animal model. IEEE Transactions on Biomedical Engineering. 48 (7), 787-794

Santa-Cruz, MC., Riso, RR. and Sepulveda, F., (2000). Evaluation of neural network parameters towards enhanced recognition of naturally evoked EMG for prosthetic hand grasp control. Proc. Congr. Int. FES Soc, 436-439

Sepulveda, F., Granat, MH. and Cliquet, A., (1998). Gait restoration in a spinal cord injured subject via neuromuscular electrical stimulation controlled by an artificial neural network. International Journal of Artificial Organs. 21 (1), 49-62

Sepulveda, F., Granat, MH. and Cliquet, A., (1997). Two artificial neural systems for generation of gait swing by means of neuromuscular electrical stimulation. Medical Engineering & Physics. 19 (1), 21-28

Sepulveda, F. and Cliquet, A., (1995). An Artificial Neural System for Closed Loop Control of Locomotion Produced via Neuromuscular Electrical Stimulation. Artificial Organs. 19 (3), 231-237

Sepulveda, F. and Cliquet, A., (1994). Simple auto-adaptive neural circuit for control of human gait: a simulation based on back-propagation. Artificial Neural Networks in Engineering - Proceedings (ANNIE'94). 4, 585-590

Sepulveda, F., Wells, DM. and Vaughan, CL., (1993). A neural network representation of electromyography and joint dynamics in human gait. Journal of Biomechanics. 26 (2), 101-109

Book chapters (8)

Alonso-Valerdi, LM. and Sepulveda, FA., (2018). EEG pattern differences in motor imagery based control tasks used for brain-computer interfacing: From training sessions to online control. In: Brain-machine Interfaces Uses and Developments. Editors: Bryan, C. and Rios, I., . Nova Science Publishers. 43- 68. 1536133698. 9781536133691

Capllonch-Juan, M. and Sepulveda, F., (2017). Conduction velocity effects due to ephaptic interactions between myelinated axons. In: EMBEC & NBC 2017. Springer, Singapore. 659- 662. 9789811051210

Zhang, Q. and Sepulveda, F., (2017). Entropy-based Axon-to-Axon Mutual Interaction Characterization via Iterative Learning Identification. In: EMBEC & NBC 2017. Editors: Eskola, H., Väisänen, O., Viik, J. and Hyttinen, J., . Springer. 691- 694. 978-981-10-5121-0

Zhang, Q. and Sepulveda, F., (2017). Modelling and Control Design for Membrane Potential Conduction Along Nerve Fibre Using B-spline Neural Network. In: Advanced Computational Methods in Life System Modeling and Simulation. Editors: Fei, M., Ma, S., Li, X., Sun, X., Jia, L. and Su, Z., . Springer. 53- 62. 978-981-10-6369-5

Al-Mulla, MR., Sepulveda, F. and Suoud, M., (2015). Optimal Elbow Angle for MMG Signal Classification of Biceps Brachii during Dynamic Fatiguing Contraction. In: Bioinformatics and Biomedical Engineering. Springer International Publishing. 303- 314. 9783319164823

Al-Mulla, MR., Sepulveda, F. and Colley, MJ., (2011). sEMG based Techniques to Detect and Predict Localised Muscle Fatigue. InTech

Sepulveda, F., (2009). Chapter 7 An Overview of BMIs. In: International Review of Neurobiology. Elsevier. 93- 106. 9780123748218

Sepulveda, F., (2003). Artificial Neural Network Techniques in Human Mobility Rehabilitation. In: Computational Methods in Biophysics, Biomaterials, Biotechnology and Medical Systems. Springer US. 327- 362

Conferences (76)

Achanccaray, D., Chau, JM., Pirca, J., Sepulveda, F. and Hayashibe, M., (2019). Assistive Robot Arm Controlled by a P300-based Brain Machine Interface for Daily Activities

Jahangiri, A., Chau, JM., Achanccaray, DR. and Sepulveda, F., (2018). Covert Speech vs. Motor Imagery: a comparative study of class separability in identical environments

Iacob, A., Morosan, M., Sepulveda, F. and Poli, R., (2018). Genetic optimisation of BCI systems for identifying games related cognitive states

Al-Mulla, MR. and Sepulveda, F., (2018). Separation of Fatigue Content in sEMG Signals Using High Definition Electrodes

AlQattan, D. and Sepulveda, F., (2017). Towards Sign Language Recognitionusing EEG-Based Motor Imagery Brain Computer Interface

Song, YJ. and Sepulveda, F., (2017). An Online Self-Paced Brain-Computer Interface Onset Detection Based on Sound-Production Imagery Applied to Real-Life Scenarios

Zhang, Q. and Sepulveda, F., (2017). RBFNN-based Modelling and Analysis for the Signal Reconstruction of Peripheral Nerve Tissue

Sepulveda, FA. and Zhang, Q., (2017). A model study of the neural interaction via mutual coupling factor identification

Zhang, Q. and Sepulveda, F., (2017). A Statistical Description of Pairwise Interaction Between Nerve Fibres

Zhang, Q. and Sepulveda, F., (2017). On the Conduction of Nerve Signals along Coupled Axons Using a Pairwise Statistical Description

Jahangiri, A. and Sepulveda, FA., (2017). The contribution of different frequency bands in class separability of covert speech tasks for BCIs

Capllonch-Juan, M., Kolbl, F. and Sepulveda, FA., (2017). Unidirectional ephaptic stimulation between two myelinated axons

Iacob, A., Sepulveda, F. and Grierson, M., (2016). Identifying the State of Cognitive Flow Using EEG and Other Physiological Signals

Kolbl, F., Capllonch-Juan, M. and Sepulveda, F., (2016). Impact of the angle of implantation of Transverse Intrafascicular Multichannel Electrodes on axon activation

Kolbl, F., Capllonch-Juan, M. and Sepulveda, F., (2016). An Open Source Framework for Simulation of the Mechanisms of Neural Activation and Propagation

Juan, MC., Kölbl, F. and Sepulveda, F., (2016). Optimisation of the spatial discretisation of myelinated axon models

Alonso-Valerdi, LM., Gutierrez-Begovich, DA., Sepulveda, F. and Ramirez-Mendoza, RA., (2016). Exploratory Study of the Heart Rate Variability during the User-System Adaptation in a BCI

Song, Y. and Sepulveda, F., (2015). Classifying siren-sound mental rehearsal and covert production vs. idle state towards onset detection in brain-computer interfaces

Alonso-Valerdi, LM. and Sepulveda, F., (2015). Implementation of a Motor Imagery Based BCI System Using Python Programming Language

Al-mulla, M., Sepulveda, F. and Al-Bader, B., (2015). Optimal Elbow Angle for Extraction of sEMG and MMG Signals During Dynamic Fatiguing Contractions

Song, Y. and Sepulveda, F., (2014). Classifying speech related vs. idle state towards onset detection in brain-computer interfaces overt, inhibited overt, and covert speech sound production vs. idle state

Poli, R., Cinel, C., Sepulveda, F. and Stoica, A., (2013). Improving decision-making based on visual perception via a collaborative brain-computer interface

Poli, R., Cinel, C., Matran-Fernandez, A., Sepulveda, F. and Stoica, A., (2013). Towards cooperative brain-computer interfaces for space navigation

Eltiti, S., Wallace, D., Ridgewell, A., Zougkou, K., Russo, R., Sepulveda, F. and Fox, E., (2012). BEHAVIORAL AND PHYSIOLOGICAL RESPONSES DURING COGNITIVE TASKS NOT SUSCEPTIBLE TO THE NOCEBO EFFECT

Pavel, D., Callaghan, V., Sepulveda, F., Gardner, M. and Dey, AK., (2012). The story of our lives: From sensors to stories in self-monitoring systems

Alonso-Valerdi, LM. and Sepulveda, F., (2011). Python in brain-computer interfaces (BCI): development of a BCI based on motor imagery

Alonso-Valerdi, LM. and Sepulveda, F., (2011). Programming an offline-analyzer of motor imagery signals via python language

Al-Mulla, MR. and Sepulveda, F., (2010). A novel feature assisting in the prediction of sEMG muscle fatigue towards a wearable autonomous system

Al-Mulla, MR. and Sepulveda, F., (2010). Predicting the time to localized muscle fatigue using ANN and evolved sEMG feature

Al-Mulla, MR., Sepulveda, F., Colley, MJ. and Kattan, A., (2009). Classification of localized muscle fatigue with Genetic Programming on sEMG during isometric contraction

Dyson, M., Sepulveda, F., Gan, JQ. and Roberts, SJ., (2009). Sequential classification of mental tasks vs. idle state for EEG based BCIs

Al-Mulla, MR., Sepulveda, F., Colley, MJ. and Al-Mulla, F., (2009). Statistical Class Separation Using sEMG Features Towards Automated Muscle Fatigue Detection and Prediction

Kattan, A., Al-Mulla, MR., Sepulveda, F. and Poli, R., (2009). Detecting Localised Muscle Fatigue during Isometric Contraction using Genetic Programming.

Salvaris, M. and Sepulveda, F., (2009). Wavelets and ensemble of FLDs for P300 classification

Salvaris, M. and Sepulveda, F., (2009). Perceptual errors in the Farwell and Donchin matrix speller

Dyson, M., Balli, T., Gan, JQ., Sepulveda, F. and Palaniappan, R., (2008). Approximate entropy for EEG-based movement detection

Agapitos, A., Dyson, M., Lucas, SM. and Sepulveda, F., (2008). Learning to recognise mental activities

Dyson, M., Sepulveda, F. and Gan, JQ., (2008). Mental task classification against the idle state: A preliminary investigation

Salvaris, M. and Sepulveda, F., (2008). Classifying P300 paradigm data with Fisher linear discriminant and discrete wavelet transform

Agapitos, A., Dyson, M., Lucas, SM. and Sepulveda, F., (2008). Learning to recognise mental activities: genetic programming of stateful classifiers for brain-computer interfacing

Vuckovic, A. and Sepulveda, F., (2008). A four-class BCI based on motor imagination of the right and the left hand wrist

Poli, R., Cinel, C., Citi, L. and Sepulveda, F., (2007). Evolutionary brain computer interfaces

Salvaris, MS. and Sepulveda, F., (2007). Robustness of the Farwell & Donchin BCI protocol to visual stimulus parameter changes

Menon, C., De Negueruela, C., Millán, JDR., Tonet, O., Carpi, F., Broschart, M., Ferrez, P., Buttfield, A., Dario, P., Citi, L., Laschi, C., Tombini, M., Seplveda, F., Poli, R., Palaniappan, R., Tecchio, F., Rossini, PM. and De Rossi, D., (2006). Prospects of brain-machine interfaces for space system control

Tsui, CSL., Vučković, A., Palaniappan, R., Sepulveda, F. and Gan, JQ., (2006). Narrow band spectral analysis for movement onset detection in asynchronous BCI

Vuckovic, A. and Sepulveda, F., (2006). EEG-based eight class, single trial classification of imaginary wrist movements

Hubais, B., Sepulveda, F. and Navarro, I., (2006). Crossectional Investigation of Wrist Movement Intention Classification in EEG Signals

Tsui, CSL., Vuckovic, A., Palaniappan, R., Sepulveda, F. and Gan, JQ., (2006). Narrow band spectral analysis for onset detection in asynchronous BCI

Navarro, I., Hubais, B. and Sepulveda, F., (2005). A Comparison of Time, Frequency and ICA Based Features and Five Classifiers for Wrist Movement Classification in EEG Signals

Leon, E., Clarke, G., Sepulveda, F. and Callaghan, V., (2005). Real-time Physiological Emotion Detection Mechanisms: Effects of Exercise and Affect Intensity

Citi, L., Poli, R. and Sepulveda, F., (2004). An evolutionary approach to feature selection and classification in P300-based BCI

Leon, E., Clarke, G., Sepulveda, F. and Callaghan, V., (2004). Neural network-based improvement in class separation of physiological signals for emotion classification

Zhou, S-M., Gan, JQ. and Sepulveda, F., (2004). Using higher-order statistics from EEG signals for developing brain-computer interface (BCI) systems

Meckes, MP., Sepulveda, F. and Conway, BA., (2004). 1st order class separability using EEG-based features for classification of wrist movements with direction selectivity

Sepulveda, F. and Huber, JB., (2004). Descriptive vs. machine-learning models of vastus lateralis in FES-induced knee extension

Leon, E., Clarke, G., Sepulveda, F. and Callaghan, V., (2004). Optimised attribute selection for emotion classification using physiological signals

Sepulveda, F., Meckes, M., Conway, BA. and ieee, (2004). Cluster separation index suggests usefulness of non-motor EEG channels in detecting wrist movement direction intention

Leon, E., Clarke, G., Sepulveda, F. and Callaghan, V., (2004). Neural network-based improvement in class separation of physiological signals for emotion classification

Sepulveda, F. and Huber, JB., (2004). Descriptive vs. machine-learning models of vastus lateralis in FES-induced knee extension

Sepulveda, F., Meckes, M. and Conway, BA., (2004). Cluster separation index suggests usefulness of non-motor EEC channels in detecting wRist movement direction intention

Sepulveda, F., Buskgaard, A., Fjorback, MV., Huber, JB., Jensen, K. and Saigal, R., (2001). Wavelet packet analysis for angular data extraction from muscle afferent cuff electrode signals

Sepulveda, F., Jensen, W. and Sinkjær, T., (2001). Using nerve signals from muscle afferent electrodes to control FES-based ankle motion in a rabbit

Sepulveda, F., Jensen, W. and Sinkjær, T., (2001). First insights on muscle afferent nerve signals for closed-loop control of FES-generated rabbit ankle movements

Santa-Cruz, MC., Riso, R. and Sepulveda, F., (2001). Optimal selection of time series coefficients for wrist myoelectric control based on intramuscular recordings

Jensen, W., Riso, R. and Sepulveda, F., (2000). On-line joint angle estimation based on nerve cuff recordings from muscle afferents

Sepulveda, F., (2000). Nonparametric artificial neural network models for control of FES-based gait: a simulation approach

Sepulveda, F., (2000). Simulating FES gait: radial basis function networks vs. neuro-fuzzy inference and recurrent neural networks with plant wear factors

Patla, A., Sepulveda, F., Quevedo, A., Hollands, M. and Sorensen, K., (2000). Visual sampling characteristics during quiet standing and walking in an individual with peripheral neuropathy

Santa-Cruz, MC., Riso, RR., Sepulveda, F. and Lange, B., (1999). Natural control of wrist movements for myoelectric prostheses

Micera, S., Jensen, W., Sepulveda, F., Riso, RR. and Sinkjær, T., (1999). A fuzzy model for extraction of angular position information from whole nerve cuff muscle afferent recordings: Preliminary results

Santa-Cruz, MC., Riso, RR., Lange, B. and Sepulveda, F., (1999). Natural control of key grip and precision grip movements for a myoelectric prostheses

Sepulveda, F., (1999). SIMULATING FATIGUE AND HABITUATION IN FES-BASED GAIT RESTORATION: INCORPORATING PLANT WEAR FACTORS TO AN ARTIFICIAL NEURAL NETWORK CONTROLLER

Sepulveda, F., (1999). Current technology is the limiting factor in FES-based gait rehabilitation: the case for increased research on implanted electrodes

Sepulveda, F., (1999). The little neural network that could-or, could it?: a critical view of neural networks in human locomotion studies

Quevedo, AAF., Sepulveda, F., Castro, MCF., Sovi, FX., Nohama, P. and Cliquet, A., (1997). Development of control strategies for restoring function to paralyzed upper and lower limbs

Sepulveda, F. and Cliquet Jr, A., (1994). A neural algorithm for closed-loop control of NMES-generated gait

Reports and Papers (4)

Poli, R., Cinel, C., Sepulveda, F. and Stoica, A., (2012). A preliminary study of a collaborative brain-computer interface in a visual matching task

Fox, E., Eltiti, S., Russo, R., Mirshekar, D., Sepulveda, F., Wallace, D., Zougkou, K., Ridgewell, A., Deeble, R., Joseph, S. and others, (2007). Hypersensitivity Symptoms Associated with Electromagnetic Field Exposure

Citi, L., Poli, R., Cinel, C. and Sepulveda, F., (2006). P300-based brain computer interface mouse with genetically-optimised analogue control

Wolkotte, P., Sepulveda, F., Sinkjaer, T. and Grey, M., (2003). Modelling Human Locomotion

Thesis dissertation (1)

Sepulveda, FA., (1990). A neural network representation of human gait. PhD Thesis

Grants and funding

2016

Control of an assistant robot through a brain-computer interface for motor-disabled people

Pontificia Universidad Catolica Del Peru (PUCP)

2015

Enabling Technologies for Sensory Feedback in Next-Generation Assistive Devices

Engineering & Physical Sciences Res.Council

2008

Analogue Revolutionary Brain Computer In

Engineering & Physical Sciences Res.Council

Contact

f.sepulveda@essex.ac.uk
+44 (0) 1206 874151

Location:

1NW.3.20, Colchester Campus

Academic support hours:

Autumn 2018: Tuesdays 14:00-15:00 and Thursdays 11:00-12:00.