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Jose L. Contreras Vidal, PhD

Full Affiliate Member, Research Institute
Houston Methodist


Contreras Vidal Lab - Brain-Machine Interface Lab


Biography

Dr. Contreras-Vidal earned his Ph.D. in cognitive and neural systems from Boston University. He held faculty appointments at the University of Maryland-College Park, MD  before joining the faculty of the University of Houston and becoming a full affiliate member of Houston Methodist Research Institute with appointments in the neurosciences research program and the department of neurosurgery. Dr. Contreras-Vidal is a professor of electrical and computer engineering at The University of Houston. He directs a neural and rehabilitation engineering research program focusing on non-invasive brain-machine interface systems and neuroprosthetics. 

Dr. Contreras-Vidal has also been a charter member of the NIH Motor Function, Speech and Rehabilitation study section, and has served on multiple NIH, NSF and international review panels. He is currently on the editorial boards of Neural Networks, Frontiers in Neuroprosthetics, the International Journal of Mobile Computer Interaction, and  Computers in Biology and Medicine. He is also  the president-elect of the International Graphonomics Society. Dr. Contreras-Vidal is the chairman of the NIH and NSF funded 2013 Clinical Brain-Neural Machine Interface Systems workshop at the Research Institute, and an IEEE Senior Member.

Description of Research

Neural interfaces, brain-machine interfaces, computational neuroscience, rehabilitation robotics

Description of Research
Dr. Contreras-Vidal’s research program was the first to demonstrate continuous decoding of human 3D hand kinematics from scalp electroencephalography (EEG). His research focuses on four areas:
-Reverse engineering the brain
-Innovating rehabilitation robotics
-Utilizing neural interfaces as tools for reverse-translational studies of brain plasticity
-Development of noninvasive neuroprosthetics and wearable exoskeletons for restoration and rehabilitation of motor function.

Education & Training

Fellow, Arizona State University
PhD, Boston University
BS, Monterrey Institute of Technology
MS, University of Colorado Boulder
Fellow, University of Fribourg
Publications

Sensory Integration in Human Movement: A New Brain-Machine Interface Based on Gamma Band and Attention Level for Controlling a Lower-Limb Exoskeleton
Ortiz, M, Ferrero, L, Iáñez, E, Azorín, JM & Contreras-Vidal, JL 2020, , Frontiers in Bioengineering and Biotechnology, vol. 8, 735. https://doi.org/10.3389/fbioe.2020.00735

Analysis of the EEG Rhythms Based on the Empirical Mode Decomposition During Motor Imagery When Using a Lower-Limb Exoskeleton. A Case Study
Ortiz, M, Iáñez, E, Contreras-Vidal, JL & Azorín, JM 2020, , Frontiers in Neurorobotics, vol. 14, 48. https://doi.org/10.3389/fnbot.2020.00048

Towards a Portable Magnetoencephalography Based Brain Computer Interface with Optically-Pumped Magnetometers
Paek, AY, Kilicarslan, A, Korenko, B, Gerginov, V, Knappe, S & Contreras-Vidal, JL 2020, . in 42nd Annual International Conferences of the IEEE Engineering in Medicine and Biology Society: Enabling Innovative Technologies for Global Healthcare, EMBC 2020., 9176159, Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS, vol. 2020-July, Institute of Electrical and Electronics Engineers Inc. pp. 3420-3423, 42nd Annual International Conferences of the IEEE Engineering in Medicine and Biology Society, EMBC 2020, Montreal, Canada, 7/20/20. https://doi.org/10.1109/EMBC44109.2020.9176159

An empirical comparison of neural networks and machine learning algorithms for EEG gait decoding
Nakagome, S, Luu, TP, He, Y, Ravindran, AS & Contreras-Vidal, JL 2020, , Scientific Reports, vol. 10, no. 1, 4372. https://doi.org/10.1038/s41598-020-60932-4

Regression-based reconstruction of human grip force trajectories with noninvasive scalp electroencephalography
Paek, AY, Gailey, A, Parikh, PJ, Santello, M & Contreras-Vidal, JL 2019, , Journal of neural engineering, vol. 16, no. 6, 066030. https://doi.org/10.1088/1741-2552/ab4063

Emotion Recognition by Point Process Characterization of Heartbeat Dynamics
Ravindran, AS, Nakagome, S, Wickramasuriya, DS, Contreras Vidal, JL & Faghih, RT 2019, . in 2019 IEEE Healthcare Innovations and Point of Care Technologies, HI-POCT 2019., 8962886, Institute of Electrical and Electronics Engineers Inc. pp. 13-16, 2019 IEEE Healthcare Innovations and Point of Care Technologies, HI-POCT 2019, Bethesda, United States, 11/20/19. https://doi.org/10.1109/HI-POCT45284.2019.8962886

Real-Time Seizure State Tracking Using Two Channels: A Mixed-Filter Approach
Ahmadi, MB, Craik, A, Azgomi, HF, Francis, JT, Contreras-Vidal, JL & Faghih, RT 2019, . in MB Matthews (ed.), Conference Record - 53rd Asilomar Conference on Circuits, Systems and Computers, ACSSC 2019., 9048990, Conference Record - Asilomar Conference on Signals, Systems and Computers, vol. 2019-November, Institute of Electrical and Electronics Engineers Inc. pp. 2033-2039, 53rd Asilomar Conference on Circuits, Systems and Computers, ACSSC 2019, Pacific Grove, United States, 11/3/19. https://doi.org/10.1109/IEEECONF44664.2019.9048990

Design of a customizable, modular pediatric exoskeleton for rehabilitation and mobility
Eguren, D, Cestari, M, Luu, TP, Kilicarslan, A, Steele, A & Contreras Vidal, JL 2019, . in 2019 IEEE International Conference on Systems, Man and Cybernetics, SMC 2019. vol. 2019-October, 8914629, Institute of Electrical and Electronics Engineers Inc. pp. 2411-2416, 2019 IEEE International Conference on Systems, Man and Cybernetics, SMC 2019, Bari, Italy, 10/6/19. https://doi.org/10.1109/SMC.2019.8914629

EEG-based neural decoding of gait in developing children
Luu, TP, Eguren, D, Cestari, M & Contreras Vidal, JL 2019, . in 2019 IEEE International Conference on Systems, Man and Cybernetics, SMC 2019. vol. 2019-October, 8914380, Institute of Electrical and Electronics Engineers Inc. pp. 3608-3612, 2019 IEEE International Conference on Systems, Man and Cybernetics, SMC 2019, Bari, Italy, 10/6/19. https://doi.org/10.1109/SMC.2019.8914380

Assessment of motor imagery in gamma band using a lower limb exoskeleton
Ortiz, M, Ianez, E, Gaxiola, J, Kilicarslan, A, Contreras-Vidal, JL & Azorin, JM 2019, . in 2019 IEEE International Conference on Systems, Man and Cybernetics, SMC 2019., 8914483, Conference Proceedings - IEEE International Conference on Systems, Man and Cybernetics, vol. 2019-October, Institute of Electrical and Electronics Engineers Inc. pp. 2773-2778, 2019 IEEE International Conference on Systems, Man and Cybernetics, SMC 2019, Bari, Italy, 10/6/19. https://doi.org/10.1109/SMC.2019.8914483

A translational roadmap for a brain-machine-interface (BMI) system for rehabilitation
Craik, A, Kilicarslan, A & Contreras-Vidal, JL 2019, . in 2019 IEEE International Conference on Systems, Man and Cybernetics, SMC 2019., 8914210, Conference Proceedings - IEEE International Conference on Systems, Man and Cybernetics, vol. 2019-October, Institute of Electrical and Electronics Engineers Inc. pp. 3613-3618, 2019 IEEE International Conference on Systems, Man and Cybernetics, SMC 2019, Bari, Italy, 10/6/19. https://doi.org/10.1109/SMC.2019.8914210

Characterization and real-time removal of motion artifacts from EEG signals
Kilicarslan, A & Contreras Vidal, JL 2019, , Journal of neural engineering, vol. 16, no. 5, 056027. https://doi.org/10.1088/1741-2552/ab2b61

Fronto-Parietal Brain Areas Contribute to the Online Control of Posture during a Continuous Balance Task
Goel, R, Nakagome, S, Rao, N, Paloski, WH, Contreras Vidal, JL & Parikh, PJ 2019, , Neuroscience, vol. 413, pp. 135-153. https://doi.org/10.1016/j.neuroscience.2019.05.063

Towards a Unified Framework for De-noising Neural Signals
Kilicarslan, A & Contreras-Vidal, JL 2019, . in 2019 41st Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2019., 8856876, Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS, Institute of Electrical and Electronics Engineers Inc. pp. 620-623, 41st Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2019, Berlin, Germany, 7/23/19. https://doi.org/10.1109/EMBC.2019.8856876

Classification and Transfer Learning of EEG during a Kinesthetic Motor Imagery Task using Deep Convolutional Neural Networks
Craik, A, Kilicarslan, A & Contreras Vidal, JL 2019, . in 2019 41st Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2019., 8857575, Institute of Electrical and Electronics Engineers Inc. pp. 3046-3049, 41st Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2019, Berlin, Germany, 7/23/19. https://doi.org/10.1109/EMBC.2019.8857575

At the crossroads of art and science: Neuroaesthetics begins to come into its own
Contreras Vidal, JL, Kever, J, Robleto, D & Rosengren, J 2019, Leonardo, vol. 52, no. 1, pp. 103-106. https://doi.org/10.1162/leon_a_01474

Assaying neural activity of children during video game play in public spaces: A deep learning approach
Ravindran, AS, Mobiny, A, Cruz-Garza, JG, Paek, A, Kopteva, A & Contreras Vidal, JL 2019, , Journal of neural engineering, vol. 16, no. 3, 036028. https://doi.org/10.1088/1741-2552/ab1876

Deep learning for electroencephalogram (EEG) classification tasks: A review
Craik, A, He, Y & Contreras-Vidal, JL 2019, , Journal of neural engineering, vol. 16, no. 3, 031001. https://doi.org/10.1088/1741-2552/ab0ab5

Neural Decoding of Robot-Assisted Gait during Rehabilitation after Stroke
Contreras-Vidal, JL, Bortole, M, Zhu, F, Nathan, K, Venkatakrishnan, A, Francisco, GE, Soto, R & Pons, JL 2018, , American Journal of Physical Medicine and Rehabilitation, vol. 97, no. 8, pp. 541-550. https://doi.org/10.1097/PHM.0000000000000914

Data Descriptor: Full body mobile brain-body imaging data during unconstrained locomotion on stairs, ramps, and level ground
Brantley, JA, Luu, TP, Nakagome, S, Zhu, F & Contreras-Vidal, JL 2018, , Scientific Data, vol. 5, 180133. https://doi.org/10.1038/sdata.2018.133