Benjamin C. Conner
Papers
6
Total Citations
194
H-Index
5
About
Benjamin C. Conner is a pioneering researcher at the intersection of rehabilitation robotics, biomechanics, and pediatric neurology, with a focused expertise in improving motor function for individuals with cerebral palsy (CP). His work centers on developing and evaluating wearable robotic exoskeleton technologies—particularly ankle-based devices—to address the neuromuscular deficits that characterize CP and limit community mobility. Conner's most influential contribution, "Adaptive Ankle Resistance from a Wearable Robotic Device to Improve Muscle Recruitment in Cerebral Palsy" (2020, 72 citations), established a compelling framework for using resistance-based robotic training grounded in motor learning theory to enhance ankle muscle recruitment and walking efficiency. Complementary work on plantar pressure biofeedback during robot-resisted gait training further demonstrates his innovative integration of sensory feedback with robotic intervention. His 2022 systematic review and meta-analysis (35 citations) provided the field with critical evidence on the comparative effectiveness of robotic gait training against standard care. Notably, Conner has also embraced machine learning—specifically Bayesian Additive Regression Trees—to identify predictors of treatment response, reflecting a sophisticated, data-driven approach to personalized rehabilitation. With nearly 200 cumulative citations across six key publications, his research is meaningfully shaping the future of pediatric rehabilitation engineering.
Research Focus
Key Achievements
Top Papers
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