David Reinkensmeyer

Professor, Mechanical & Aerospace Engineering
The Henry Samueli School of Engineering

Professor, Anatomy & Neurobiology
School of Medicine

Professor, Biomedical Engineering


B.S., Massachusetts Institute of Technology, 1988, Electrical Engineering


M.S., University of California, Berkeley, 1991, Electrical Engineering


Ph.D., University of California, Berkeley, 1993, Electrical Engineering


Postdoctorate, Rehabilitation Institute of Chicago, 1998, Rehabilitation Robotics

Phone: (949) 824-5218
Fax: (949) 824-8585
Email:

University of California, Irvine
3225 Engineering Gateway
Mail Code: 3975
Irvine, CA 92697

picture of David  Reinkensmeyer

Research
Interests
Movement control, neurorehabilitation, and robotics
   
URLs Biorobotics - People
   
Biorobotics
   
iMove Collaboratory
   
Academic
Distinctions
Dr. Reinkensmeyer received the B.S. degree in electrical engineering from the Massachusetts Institute of Technology and the M.S. and Ph.D. degrees in electrical engineering from the University of California at Berkeley, studying robotics and the neuroscience of human movement. He carried out postdoctoral studies at the Rehabilitation Institute of Chicago and Northwestern University Medical School, building one of the first robotic devices for rehabilitation therapy after stroke. He became an assistant professor at U.C. Irvine in 1997, establishing a research program that develops robotic and sensor-based systems for movement training and assessment following neurologic injuries and disease. He is a co-inventor of the T-WREX arm training exoskeleton, commercialized by Hocoma A.G. as ArmeoSpring and now in use in over 700 rehabilitation units worldwide for people with stroke, spinal cord injury, multiple sclerosis, cerebral palsy and orthopedic injuries. He is also co-inventor of the MusicGlove hand training device, now being commercialized by Flint Rehabilitation Devices and in use by over 1000 clinical and individual users in the US. He is co-director of the NIDILRR MARS3 Robotic Rehabilitation Engineering Center, co-director of the NIH K12 Engineering Career Development Center in Movement and Rehabilitation Sciences, and Editor-in-Chief of the Journal of Neuroengineering and Rehabilitation.

Hobbies/Outside Interests
Hiking, mountain biking
   
Research
Abstract
Dr. Reinkensmeyer’s interests are in robotics and wearable sensors for neurorehabilitation, and computational neuroscience for movement control. His research group designs technologies for movement rehabilitation after neurologic injury based on an understanding of neuromuscular plasticity mechanisms. Developing improved technology for rehabilitation movement training after neurologic injury not only helps people improve their movement recovery, but also enhances scientific understanding of use-dependent plasticity. Such technology, along with computational models will play an essential role in assessing and enhancing forthcoming neuro-repair therapies.
   
Available Technologies
Publications Most recent 10 from 105
1. Computational neurorehabilitation: modeling plasticity and learning to predict recovery. Reinkensmeyer DJ, Burdet E, Casadio M, Krakauer JW, Kwakkel G, Lang CE, Swinnen SP, Ward NS, Schweighofer N.
J Neuroeng Rehabil. 2016 Apr 30;13(1):42. doi: 10.1186/s12984-016-0148-3. Review. PMID: 27130577

2. Movement Anticipation and EEG: Implications for BCI-Contingent Robot Therapy.
Norman S, Dennison M, Wolbrecht E, Cramer S, Srinivasan R, Reinkensmeyer D.
IEEE Trans Neural Syst Rehabil Eng. 2016 Feb 11. [Epub ahead of print]
PMID: 26891487 Similar articles

3. Design and Evaluation of the Kinect-Wheelchair Interface Controlled (KWIC) Smart Wheelchair for Pediatric Powered Mobility Training.
Zondervan DK, Secoli R, Darling AM, Farris J, Furumasu J, Reinkensmeyer DJ.
Assist Technol. 2015 Fall;27(3):183-92. doi: 10.1080/10400435.2015.1012607.
PMID: 26427746

4. Robotic Rehabilitator of the Rodent Upper Extremity: A System and Method for Assessing and Training Forelimb Force Production after Neurological Injury.
Sharp KG, Duarte JE, Gebrekristos B, Perez S, Steward O, Reinkensmeyer DJ.
J Neurotrauma. 2016 Mar 1;33(5):460-7. doi: 10.1089/neu.2015.3987. Epub 2016 Jan 18. PMID: 26414700

5. Use of a robotic device to measure age-related decline in finger proprioception.
Ingemanson ML, Rowe JB, Chan V, Wolbrecht ET, Cramer SC, Reinkensmeyer DJ.
Exp Brain Res. 2016 Jan;234(1):83-93. doi: 10.1007/s00221-015-4440-4. Epub 2015 Sep 16. PMID: 26378004

6. A novel device for studying weight supported, quadrupedal overground locomotion in spinal cord injured rats.
Hamlin M, Traughber T Jr, Reinkensmeyer DJ, de Leon RD.
J Neurosci Methods. 2015 May 15;246:134-41. doi: 10.1016/j.jneumeth.2015.03.015. Epub 2015 Mar 18.
PMID: 25794460

7. Effects of robotically modulating kinematic variability on motor skill learning and motivation. Duarte JE, Reinkensmeyer DJ.
J Neurophysiol. 2015 Apr 1;113(7):2682-91. doi: 10.1152/jn.00163.2014. Epub 2015 Feb 11. PMID: 25673732

8. Feasibility of a bimanual, lever-driven wheelchair for people with severe arm impairment after stroke. Smith BW, Zondervan DK, Lord TJ, Chan V, Reinkensmeyer DJ. Conf Proc IEEE Eng Med Biol Soc. 2014;2014:5292-5. doi: 10.1109/EMBC.2014.6944820. PMID: 25571188

9. The variable relationship between arm and hand use: a rationale for using finger magnetometry to complement wrist accelerometry when measuring daily use of the upper extremity. Rowe JB, Friedman N, Chan V, Cramer SC, Bachman M, Reinkensmeyer DJ. Conf Proc IEEE Eng Med Biol Soc. 2014;2014:4087-90. doi: 10.1109/EMBC.2014.6944522.
PMID: 25570890

10. Machine-Based, Self-guided Home Therapy for Individuals With Severe Arm Impairment After Stroke: A Randomized Controlled Trial.
Zondervan DK, Augsburger R, Bodenhoefer B, Friedman N, Reinkensmeyer DJ, Cramer SC. Neurorehabil Neural Repair. 2015 Jun;29(5):395-406. doi: 10.1177/1545968314550368
   
Research Center iMove Collaboratory http://imove.eng.uci.edu/
   
   
Link to this profile http://www.faculty.uci.edu/profile.cfm?faculty_id=4691
   
Last updated 09/02/2016