D-Index & Metrics Best Publications

D-Index & Metrics D-index (Discipline H-index) only includes papers and citation values for an examined discipline in contrast to General H-index which accounts for publications across all disciplines.

Discipline name D-index D-index (Discipline H-index) only includes papers and citation values for an examined discipline in contrast to General H-index which accounts for publications across all disciplines. Citations Publications World Ranking National Ranking
Neuroscience D-index 49 Citations 8,165 206 World Ranking 3479 National Ranking 1600

Overview

What is he best known for?

The fields of study he is best known for:

  • Artificial intelligence
  • Neuroscience
  • Cognition

Jose L. Contreras-Vidal focuses on Physical medicine and rehabilitation, Electroencephalography, Neuroscience, Brain–computer interface and Developmental psychology. In general Physical medicine and rehabilitation, his work in Exoskeleton is often linked to Jerk and Injury prevention linking many areas of study. His Electroencephalography research incorporates themes from Gait, Cursor, Artificial intelligence, Simulation and Scalp.

His Neuroscience study combines topics from a wide range of disciplines, such as Central pattern generator and Subthalamic nucleus. His Brain–computer interface research includes elements of Electromyography, Signal integrity and Computer vision. His work carried out in the field of Developmental psychology brings together such families of science as Analysis of variance, Audiology, Working memory, Adaptation and Neurocognitive.

His most cited work include:

  • Parkinsonism reduces coordination of fingers, wrist, and arm in fine motor control (323 citations)
  • Reconstructing Three-Dimensional Hand Movements from Noninvasive Electroencephalographic Signals (285 citations)
  • Adaptation to gradual as compared with sudden visuo-motor distortions. (259 citations)

What are the main themes of his work throughout his whole career to date?

Electroencephalography, Artificial intelligence, Physical medicine and rehabilitation, Brain–computer interface and Neuroscience are his primary areas of study. His work deals with themes such as Gait, Neural decoding, Speech recognition and Scalp, which intersect with Electroencephalography. In the field of Artificial intelligence, his study on Artificial neural network overlaps with subjects such as Context.

His Physical medicine and rehabilitation study combines topics in areas such as Rehabilitation and Clinical trial. The concepts of his Brain–computer interface study are interwoven with issues in Human–computer interaction and Biomechanics. His research investigates the connection with Human–computer interaction and areas like Task which intersect with concerns in Developmental psychology.

He most often published in these fields:

  • Electroencephalography (42.11%)
  • Artificial intelligence (29.67%)
  • Physical medicine and rehabilitation (25.36%)

What were the highlights of his more recent work (between 2018-2021)?

  • Electroencephalography (42.11%)
  • Physical medicine and rehabilitation (25.36%)
  • Rehabilitation (12.92%)

In recent papers he was focusing on the following fields of study:

His primary areas of study are Electroencephalography, Physical medicine and rehabilitation, Rehabilitation, Artificial intelligence and Brain–computer interface. His Electroencephalography research is multidisciplinary, relying on both Modality, Neuroimaging, Motion artifacts and Scalp. His research related to Powered exoskeleton, Gait and Exoskeleton might be considered part of Physical medicine and rehabilitation.

His Rehabilitation research is multidisciplinary, incorporating perspectives in Classifier, Neuroplasticity and Speech recognition. His biological study spans a wide range of topics, including Signal-to-noise ratio, Motor imagery, Computer vision and Pattern recognition. His research in Brain–computer interface intersects with topics in Architecture and Human–computer interaction.

Between 2018 and 2021, his most popular works were:

  • Deep learning for electroencephalogram (EEG) classification tasks: a review. (181 citations)
  • Fronto-Parietal Brain Areas Contribute to the Online Control of Posture during a Continuous Balance Task. (13 citations)
  • An empirical comparison of neural networks and machine learning algorithms for EEG gait decoding. (11 citations)

In his most recent research, the most cited papers focused on:

  • Artificial intelligence
  • Neuroscience
  • Cognition

Jose L. Contreras-Vidal mainly investigates Electroencephalography, Brain–computer interface, Artificial intelligence, Physical medicine and rehabilitation and Exoskeleton. His Electroencephalography study introduces a deeper knowledge of Neuroscience. His research integrates issues of Modality, Magnetoencephalography, Computer vision and Scalp in his study of Brain–computer interface.

His Artificial intelligence study incorporates themes from Volume conduction and Photoplethysmogram. In the subject of general Physical medicine and rehabilitation, his work in Powered exoskeleton is often linked to Minimal clinically important difference, thereby combining diverse domains of study. His Exoskeleton research includes themes of Gait, Motor imagery, Task and Human–computer interaction.

This overview was generated by a machine learning system which analysed the scientist’s body of work. If you have any feedback, you can contact us here.

Best Publications

Deep learning for electroencephalogram (EEG) classification tasks: a review.

Alexander Craik;Yongtian He;Jose L Contreras-Vidal.
Journal of Neural Engineering (2019)

525 Citations

Parkinsonism reduces coordination of fingers, wrist, and arm in fine motor control

Hans Leo Teulings;José L. Contreras-Vidal;George E. Stelmach;Charles H. Adler.
Experimental Neurology (1997)

433 Citations

Reconstructing Three-Dimensional Hand Movements from Noninvasive Electroencephalographic Signals

Trent J. Bradberry;Rodolphe J. Gentili;Rodolphe J. Gentili;José L. Contreras-Vidal.
The Journal of Neuroscience (2010)

402 Citations

Adaptation to gradual as compared with sudden visuo-motor distortions.

Florian A. Kagerer;José L. Contreras-Vidal;George E. Stelmach.
Experimental Brain Research (1997)

340 Citations

The H2 robotic exoskeleton for gait rehabilitation after stroke: early findings from a clinical study

Magdo Bortole;Magdo Bortole;Anusha Venkatakrishnan;Anusha Venkatakrishnan;Fangshi Zhu;Juan C Moreno.
Journal of Neuroengineering and Rehabilitation (2015)

284 Citations

Visuomotor adaptation in normal aging.

Ethan R. Buch;Sereniti Young;José L. Contreras-Vidal.
Learning & Memory (2003)

222 Citations

Neural decoding of treadmill walking from noninvasive electroencephalographic signals.

Alessandro Presacco;Ronald Goodman;Larry Forrester;Larry Forrester;Jose Luis Contreras-Vidal.
Journal of Neurophysiology (2011)

222 Citations

High accuracy decoding of user intentions using EEG to control a lower-body exoskeleton

Atilla Kilicarslan;Saurabh Prasad;Robert G. Grossman;Jose L. Contreras-Vidal.
international conference of the ieee engineering in medicine and biology society (2013)

207 Citations

Elderly subjects are impaired in spatial coordination in fine motor control

José L. Contreras-Vidal;Hans L. Teulings;George E. Stelmach.
Acta Psychologica (1998)

175 Citations

A neural model of cerebellar learning for arm movement control: cortico-spino-cerebellar dynamics.

Jose L. Contreras-Vidal;Stephen Grossberg;Daniel Bullock.
Learning & Memory (1997)

150 Citations

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