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Engineering and Technology

D-Index
77
Citations
20157
World Ranking
669
National Ranking
235

Research.com Recognitions

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

Overview

David J. Reinkensmeyer is affiliated with the University of California, Irvine in the United States. The primary focus of their research is within the field of medicine, specifically concentrated on rehabilitation and related interdisciplinary areas. Their work spans several subfields including rehabilitation, biomedical engineering, cognitive neuroscience, neurology, and psychiatry and mental health.

The main topics covered in their research include stroke rehabilitation and recovery, muscle activation and electromyography studies, cerebral palsy and movement disorders, EEG and brain-computer interfaces, telemedicine and telehealth implementation, assistive technology in communication and mobility, and botulinum toxin and related neurological disorders.

Recent papers authored by or involving David J. Reinkensmeyer include the following:

  • Big Data Analytics and Sensor-Enhanced Activity Management to Improve Effectiveness and Efficiency of Outpatient Medical Rehabilitation, 2020, International Journal of Environmental Research and Public Health
  • Feasibility of Wearable Sensing for In-Home Finger Rehabilitation Early After Stroke, 2020, IEEE Transactions on Neural Systems and Rehabilitation Engineering
  • Magnetically Counting Hand Movements: Validation of a Calibration-Free Algorithm and Application to Testing the Threshold Hypothesis of Real-World Hand Use after Stroke, 2021, Sensors
  • Rudimentary Dexterity Corresponds With Reduced Ability to Move in Synergy After Stroke: Evidence of Competition Between Corticoreticulospinal and Corticospinal Tracts?, 2020, Neurorehabilitation and neural repair
  • A day in the life: a qualitative study of clinical decision-making and uptake of neurorehabilitation technology, 2021, Journal of NeuroEngineering and Rehabilitation

Frequent coauthors who have collaborated with David J. Reinkensmeyer include:

  • Vicky Chan
  • Daniel K. Zondervan
  • Andria J. Farrens
  • Steven C. Cramer
  • Veronica A. Swanson

The scientist has published extensively in a number of recurring venues. The most frequent publication venues are Sensors, Journal of NeuroEngineering and Rehabilitation, Neurorehabilitation and neural repair, IEEE Transactions on Neural Systems and Rehabilitation Engineering, and International Journal of Environmental Research and Public Health.

David J. Reinkensmeyer has been recognized as a Fellow of the Indian National Academy of Engineering (INAE) in 2019.

Best Publications

  • Review of control strategies for robotic movement training after neurologic injury

    Laura Marchal-Crespo;David J Reinkensmeyer

  • Optimizing Compliant, Model-Based Robotic Assistance to Promote Neurorehabilitation

    E.T. Wolbrecht;V. Chan;D.J. Reinkensmeyer;J.E. Bobrow

  • Robotics, motor learning, and neurologic recovery.

    David J. Reinkensmeyer;Jeremy L. Emken;Steven C. Cramer

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

    Robert A. Scheidt;David J. Reinkensmeyer;Michael A. Conditt;W. Zev Rymer

  • Retraining the injured spinal cord

    V. Reggie Edgerton;Ray D. de Leon;Susan J. Harkema;John A. Hodgson

  • 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

  • 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

  • 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

  • Robot-enhanced motor learning: accelerating internal model formation during locomotion by transient dynamic amplification

    J.L. Emken;D.J. Reinkensmeyer

  • Robot-assisted movement training for the stroke-impaired arm: Does it matter what the robot does?

    Leonard E. Kahn;Peter S. Lum;Peter S. Lum;W. Zev Rymer;David J. Reinkensmeyer

  • Ocular biomechanics and biotransport.

    C. Ross Ethier;Mark Johnson;Jeff Ruberti

  • Web-based telerehabilitation for the upper extremity after stroke

    D.J. Reinkensmeyer;C.T. Pang;J.A. Nessler;C.C. Painter

  • Motor adaptation as a greedy optimization of error and effort.

    Jeremy L. Emken;Raul Benitez;Athanasios Sideris;James E. Bobrow

  • A Robot and Control Algorithm That Can Synchronously Assist in Naturalistic Motion During Body-Weight-Supported Gait Training Following Neurologic Injury

    D. Aoyagi;W.E. Ichinose;S.J. Harkema;D.J. Reinkensmeyer

  • Robotic Devices for Movement Therapy After Stroke: Current Status and Challenges to Clinical Acceptance

    Peter Lum;David Reinkensmeyer;Richard Mahoney;William Z. Rymer

  • A standardized approach to the Fugl-Meyer assessment and its implications for clinical trials.

    Jill See;Lucy Dodakian;Cathy Chou;Vicky Chan

  • Impedance control and internal model formation when reaching in a randomly varying dynamical environment.

    C. D. Takahashi;R. A. Scheidt;D. J. Reinkensmeyer

  • Human-robot cooperative movement training: Learning a novel sensory motor transformation during walking with robotic assistance-as-needed

    Jeremy L Emken;Raul Benitez;Raul Benitez;David J Reinkensmeyer

  • Recent trends in assistive technology for mobility.

    Rachel E Cowan;Benjamin J Fregly;Michael L Boninger;Leighton Chan

  • Retraining and assessing hand movement after stroke using the MusicGlove: comparison with conventional hand therapy and isometric grip training

    Nizan Friedman;Vicky Chan;Andrea N Reinkensmeyer;Ariel Beroukhim

  • Haptic Guidance Can Enhance Motor Learning of a Steering Task

    Laura Marchal Crespo;David J. Reinkensmeyer

Frequent Co-Authors

Steven C. Cramer
Steven C. Cramer University of California, Los Angeles
James E. Bobrow
James E. Bobrow University of California, Irvine
Roland R. Roy
Roland R. Roy University of California, Los Angeles
William Z. Rymer
William Z. Rymer Shirley Ryan AbilityLab
Christopher G. Atkeson
Christopher G. Atkeson Carnegie Mellon University
Derek G. Kamper
Derek G. Kamper University of North Carolina at Chapel Hill
Brian D. Schmit
Brian D. Schmit Marquette University
Benjamin J. Fregly
Benjamin J. Fregly Rice University
Nicolas Schweighofer
Nicolas Schweighofer University of Southern California
James W. Hicks
James W. Hicks University of Southern California

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