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Biomedical Engineering and Bioengineering Commons

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Humans

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Marquette University

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Full-Text Articles in Biomedical Engineering and Bioengineering

Visual Error Augmentation For Enhancing Motor Learning And Rehabilitative Relearning, Yejun Wei, Preeti Bajaj, Robert A. Scheidt, James L. Patton Jan 2005

Visual Error Augmentation For Enhancing Motor Learning And Rehabilitative Relearning, Yejun Wei, Preeti Bajaj, Robert A. Scheidt, James L. Patton

Biomedical Engineering Faculty Research and Publications

We developed a real-time controller for a 2 degree-of-freedom robotic system using xPC Target. This system was used to investigate how different methods of performance error feedback can lead to faster and more complete motor learning in individuals asked to compensate for a novel visuo-motor transformation (a 30 degree rotation). Four groups of normal human subjects were asked to reach with their unseen arm to visual targets surrounding a central starting location. A cursor tracking hand motion was provided during each reach. For one group of subjects, deviations from the "ideal" compensatory hand movement (i.e. trajectory errors) were amplified with …


A Pneumatically Actuated Manipulandum For Neuromotor Control Research, Aaron J Suminski, Kristina M. Ropella, Robert A. Scheidt Jan 2002

A Pneumatically Actuated Manipulandum For Neuromotor Control Research, Aaron J Suminski, Kristina M. Ropella, Robert A. Scheidt

Biomedical Engineering Faculty Research and Publications

Functional magnetic resonance imaging (fMRI) techniques have great potential for identifying which neural structures are involved in the control of goal-directed reaching movements. However, fMRI techniques alone are not capable of probing the neural mechanisms involved in acquisition of novel motor behaviors because such studies require that the moving limb be perturbed in a controlled fashion. We outline a plan to design and develop a non-metallic, pneumatically actuated tool that, along with systems identification techniques and functional magnetic resonance imaging (fMRI), will characterize and quantify how the human central nervous system uses sensory information during practice-based motor learning.