Papers

16

Total Citations

840

H-Index

10

About

D.J. Reinkensmeyer is a pioneering figure in neurorehabilitation robotics, whose work fundamentally reshapes how we understand and treat motor recovery after neurological injury. His research centers on the intersection of human motor control, robotic assistance, and computational modeling, with a primary focus on developing intelligent rehabilitation technologies. Reinkensmeyer’s major contributions include the concept of “assist-as-needed” robotic therapy, which he formalized as an optimization problem in a highly influential 2005 paper (138 citations). He also uncovered a critical motor system property—the tendency to “slack” when movement error is small—providing a computational framework that now guides the design of robotic orthoses (119 citations). His early work on impedance control and internal model formation during reaching in random dynamical environments (212 citations) remains foundational in motor adaptation research. Beyond human studies, Reinkensmeyer has innovated robotic devices for rodent locomotion after spinal cord injury, bridging basic neuroscience and clinical application. His notable achievements include developing the SUE robot for forearm/wrist rehabilitation and designing exoskeleton mechanisms for finger therapy. With over 800 citations across his top ten papers, Reinkensmeyer’s work continues to inspire engineers and clinicians seeking to enhance neurorehabilitation through robotics.

Research Focus

Key Achievements

10
H-Index
16
Papers
840
Total Citations
53
Avg Citations/Paper
🏆 Most Cited Paper
Impedance Control and Internal Model Formation When Reaching in a Randomly Varying Dynamical Environment
212 citations · 2001
📈 Most Prolific Year: 2005 (4 Papers)
🤝 Key Collaborators: 48
🏛 Institutions: University of California, Irvine, California State University, San Marcos

Top Papers

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Key Collaborators

Contact & Links

Available for collaboration
Content generated · 13 days ago