Daniel P. Ferris

Daniel P. Ferris received the B.S. degree from the University of Central Florida, the M.S. degree from the University of Miami, Miami, FL, USA, and the Ph.D. degree from University of California, Berkeley, CA, USA. He worked as a Postdoctoral Researcher in the UCLA Department of Neurology and the University of Washington Department of Electrical Engineering. He is currently the Robert W. Adenbaum Professor of Engineering Innovation and Senior Associate Chair, J. Crayton Pruitt Family Department of Biomedical Engineering at the Herbert Wertheim College of Engineering at the University of Florida. He studies the neuromechanical control of human locomotion in health and disability. Specifically, he focuses on robotic lower limb exoskeletons, bionic lower limb prostheses, and mobile brain imaging.

Associated articles

TNSRE, Featured Articles
State-of-the-Art and Future Directions for Robotic Lower Limb Exoskeletons
Research on robotic exoskeletons has rapidly expanded over the previous decade. Advances in robotic hardware and energy supplies have enabled viable prototypes for human testing. This review paper describes current lower limb robotic exoskeletons, with specific regard to common trends... Read more
TNSRE, Featured Articles
Locomotor Adaptation by Transtibial Amputees Walking With an Experimental Powered Prosthesis Under Continuous Myoelectric Control
Lower limb amputees can use electrical activity from their residual muscles for myoelectric control of a powered prosthesis. The most common approach for myoelectric control is a finite state controller that identifies behavioral states and discrete changes in motor tasks.... Read more
OJEMB, Featured Articles
Comparison of Signal Processing Methods for Reducing Motion Artifacts in High-Density Electromyography During Human Locomotion
Objective: High-density electromyography (EMG) is useful for studying changes in myoelectric activity within a muscle during human movement, but it is prone to motion artifacts during locomotion. We compared canonical correlation analysis and principal component analysis methods for signal decomposition... Read more