H-Index & Metrics Best Publications

H-Index & Metrics

Discipline name H-index Citations Publications World Ranking National Ranking
Engineering and Technology D-index 66 Citations 14,061 167 World Ranking 392 National Ranking 175

Research.com Recognitions

Awards & Achievements

2019 - Fellow of the Indian National Academy of Engineering (INAE)

Overview

What is he best known for?

The fields of study he is best known for:

  • Artificial intelligence
  • Physical therapy
  • Neuroscience

David J. Reinkensmeyer mainly investigates Physical medicine and rehabilitation, Robot, Rehabilitation, Physical therapy and Artificial intelligence. His studies in Physical medicine and rehabilitation integrate themes in fields like Treadmill, Treadmill training, Biomechanics, Spinal cord injury and Motor control. His Robot research integrates issues from Work, Feedback control, Gait training and Simulation.

His Rehabilitation research is multidisciplinary, incorporating elements of Stroke and Robotic paradigms. His research investigates the connection with Physical therapy and areas like Hemiparesis which intersect with concerns in Arm exercise. The Artificial intelligence study combines topics in areas such as Neurologic injury, Communication and Motor learning.

His most cited work include:

  • Review of control strategies for robotic movement training after neurologic injury (746 citations)
  • Understanding and treating arm movement impairment after chronic brain injury: progress with the ARM guide. (398 citations)
  • Persistence of motor adaptation during constrained, multi-joint, arm movements. (344 citations)

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

David J. Reinkensmeyer mostly deals with Physical medicine and rehabilitation, Rehabilitation, Robot, Artificial intelligence and Simulation. His research integrates issues of Treadmill, Physical therapy, Spinal cord injury, Motor control and Stroke in his study of Physical medicine and rehabilitation. The concepts of his Rehabilitation study are interwoven with issues in Computer game, Activities of daily living, Hemiparesis, Work and Functional movement.

David J. Reinkensmeyer has included themes like Gait, Pneumatic actuator, Orthotics and Trajectory in his Robot study. David J. Reinkensmeyer studies Robotics, a branch of Artificial intelligence. His Simulation research is multidisciplinary, relying on both Motion, Mechanism, Rehabilitation robotics and Control engineering, Control theory.

He most often published in these fields:

  • Physical medicine and rehabilitation (53.44%)
  • Rehabilitation (31.98%)
  • Robot (27.13%)

What were the highlights of his more recent work (between 2014-2021)?

  • Physical medicine and rehabilitation (53.44%)
  • Rehabilitation (31.98%)
  • Stroke (20.65%)

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

His primary areas of investigation include Physical medicine and rehabilitation, Rehabilitation, Stroke, Motor learning and Simulation. His studies deal with areas such as Neurorehabilitation, Motor control and Finger movement as well as Physical medicine and rehabilitation. David J. Reinkensmeyer combines subjects such as Robotics, Randomized controlled trial, Artificial intelligence and Medical education with his study of Rehabilitation.

His Stroke research includes elements of Motor system, Powered exoskeleton, Wrist and Neurological injury. His Motor learning research includes themes of Human–computer interaction, Functional ability, Haptic technology and Fugl meyer. His Simulation study integrates concerns from other disciplines, such as Robot, Control theory, Robot kinematics and Lever.

Between 2014 and 2021, his most popular works were:

  • Computational neurorehabilitation: modeling plasticity and learning to predict recovery (82 citations)
  • Rehabilitation and Health Care Robotics (53 citations)
  • A Home-Based Telerehabilitation Program for Patients With Stroke. (39 citations)

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

  • Artificial intelligence
  • Physical therapy
  • Neuroscience

His primary areas of study are Physical medicine and rehabilitation, Rehabilitation, Stroke, Robotics and Artificial intelligence. His biological study spans a wide range of topics, including Principal component analysis and Simulation. His study in Rehabilitation is interdisciplinary in nature, drawing from both Wrist, Activities of daily living and Motor control.

His study explores the link between Stroke and topics such as Physical therapy that cross with problems in Randomized controlled trial. His Robotics study is concerned with the field of Robot as a whole. The various areas that David J. Reinkensmeyer examines in his Robot study include Nursing and Communication.

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

Review of control strategies for robotic movement training after neurologic injury

Laura Marchal-Crespo;David J Reinkensmeyer.
Journal of Neuroengineering and Rehabilitation (2009)

1066 Citations

Understanding and treating arm movement impairment after chronic brain injury: progress with the ARM guide.

D J Reinkensmeyer;L E Kahn;L E Kahn;M Averbuch;M Averbuch;A McKenna-Cole;A McKenna-Cole.
Journal of Rehabilitation Research and Development (2014)

602 Citations

Optimizing Compliant, Model-Based Robotic Assistance to Promote Neurorehabilitation

E.T. Wolbrecht;V. Chan;D.J. Reinkensmeyer;J.E. Bobrow.
international conference of the ieee engineering in medicine and biology society (2008)

451 Citations

Robotics, motor learning, and neurologic recovery.

David J. Reinkensmeyer;Jeremy L. Emken;Steven C. Cramer.
Annual Review of Biomedical Engineering (2004)

449 Citations

Retraining the injured spinal cord

V. Reggie Edgerton;Ray D. de Leon;Susan J. Harkema;John A. Hodgson.
The Journal of Physiology (2001)

420 Citations

Robot-assisted reaching exercise promotes arm movement recovery in chronic hemiparetic stroke: a randomized controlled pilot study.

Leonard E Kahn;Leonard E Kahn;Michele L Zygman;W Zev Rymer;W Zev Rymer;David J Reinkensmeyer;David J Reinkensmeyer.
Journal of Neuroengineering and Rehabilitation (2006)

418 Citations

Persistence of motor adaptation during constrained, multi-joint, arm movements.

Robert A. Scheidt;David J. Reinkensmeyer;Michael A. Conditt;W. Zev Rymer.
Journal of Neurophysiology (2000)

412 Citations

Automating Arm Movement Training Following Severe Stroke: Functional Exercises With Quantitative Feedback in a Gravity-Reduced Environment

R.J. Sanchez;Jiayin Liu;S. Rao;P. Shah.
international conference of the ieee engineering in medicine and biology society (2006)

403 Citations

A randomized controlled trial of gravity-supported, computer-enhanced arm exercise for individuals with severe hemiparesis.

Sarah J. Housman;Kelly M. Scott;David J. Reinkensmeyer;David J. Reinkensmeyer.
Neurorehabilitation and Neural Repair (2009)

396 Citations

Web-based telerehabilitation for the upper extremity after stroke

D.J. Reinkensmeyer;C.T. Pang;J.A. Nessler;C.C. Painter.
international conference of the ieee engineering in medicine and biology society (2002)

346 Citations

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