Kelly O. Thielbar
Papers
2
Total Citations
30
H-Index
2
About
Kelly O. Thielbar is a pioneering researcher in stroke rehabilitation, specializing in the intersection of robotics, motor learning, and personalized therapy for upper extremity impairments. Her work addresses the critical challenge of tailoring rehabilitation to the highly variable motor deficits of stroke survivors. Thielbar’s major contributions include developing intelligent robot training methods that use vector fields derived from an individual’s own movement statistics, enabling customized therapy that adapts to each patient’s unique impairment profile—a concept highlighted in her most-cited paper (25 citations). She has also explored innovative, robot-free approaches to augmenting error during reaching training, using distorted visual feedback to simulate forces and enhance motor recovery, as demonstrated in her 2019 study. By moving beyond traditional clinical assessments like the Fugl-Meyer scale, Thielbar’s research advances data-driven, personalized rehabilitation strategies. Her work is notable for bridging engineering and clinical neuroscience, offering scalable solutions that could transform post-stroke care. For students and researchers, Thielbar exemplifies how combining computational modeling with patient-specific data can lead to more effective, accessible therapies.
Research Focus
Key Achievements
Top Papers
- 1
- 2Stroke Rehabilitation with Distorted Vision Perceived as Forces5 citations · 2019