Fri, Dec 19, 12-1pm THIS IS BEING RESCHEDULED TO DUE WEATHER
RIC, Room 1301 ()
The Neuro-Locomotion Lab
Speaker: T. George Hornby, PhD, PT
Assistant Professor, Department of Physical Therapy, University of Illinois at Chicago Research Scientist, SMPP, RIC
Title: Repeated, Volitional, Fatiguing Contractions in Human SCI:
General Findings, Potential Mechanisms, and Future Work or "I DON'T KNOW WHAT WE'RE YELLING ABOUT!!!!"
Abstract: In this talk, we will discuss some of the work performed on patients with motor incomplete SCI to assess patterns of neuromuscular fatigue during repeated, maximal effort, isometric contractions of the knee extensors. Preliminary studies demonstrated decreased volitional fatigue, but rather a "warm-up" of maximal torques similar to that shown with spastic motor behaviors. Further preliminary data provide some evidence that this behavior could be utilized in the clinical setting to minimize strength loss following SCI.
Director: George Hornby
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Thu, Dec 18, 2-3pm
RIC, Room 1301 ( )
Speaker: Francis Suh, PhD
Bionics Research Team, Future Fusion Technology Laboratory, Korea Institute of Science and Technology, Seoul, Korea & Department of Biomedical Engineering, Tulane University, New Orleans, LA
Title: Soft Tissue Biomechanics in Orthopaedics and Ophthalmology
Abstract: Dysfunction of human body organ can have debilitating consequences in the quality of person’s daily life. For example, arthritis, a disease of dysfunctional articular cartilage, is the leading cause of the musculoskeletal disabilities, in particular, for elderly population. Arthritis is a multi-factorial pathological condition of diarthrodial joint, which is generally manifested by the loss of structural integrity of articular cartilage as a mechanical bearing element in the joint. Unlike other vascular soft tissues, articular cartilage has little ability for spontaneous repair. Thus, once damaged, it usually embarks vicious catabolic chain reactions, which leads to a total loss of joint mobility. Another example is glaucoma, a disease of dysfunctional optic nerve head of eye, which is one of the three leading causes of blindness in the U.S. We hypothesize that the mechanical properties of peripapillary and posterior sclera are altered during the disease and play a significant role in the development and progression of glaucomatous damage to the neural and connective tissues within the optic nerve head.
I will present how a basic analytical model can be developed and applied to understand the normal and pathological behaviors of articular cartilage and posterior scleral tissues. A multi-fauceted approach, including analytical, computational, and experimental methods, will be presented as the validation process of the model. Also shown are the applications of such models to understand the core features of the pathological processes of the dysfunctional organs. After all, this approach will help us to develop a means to prevent or repair the damaged organs.
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Fri, Dec 5, 12-1pm
RIC, Room 1301 ( )
Speaker: Sangeetha Madhavan & Jon Shemmell
Title: Detecting ipsilateral connectivity from motor cortex to lower limb spinal motoneurons, and reorganizing cortical motor maps using paired electrical stimulation.
These two "impossible" tasks are currently being conducted in the Neuralplasticity Laboratory.
Sangeetha Madhavan and Jonathan Shemmell will describe the challenges and potential rewards of these two pioneering techniques.The Neuralplasticity Lab Presentation (Director: James Stinear)
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Mon, Dec 1, 2-3pm
RIC, Room 1301 ( )
SMPP Graduate Student Seminar: Zachary Danziger
Title: Developing Learning Algorithms for Human-Machine Interfaces
Abstract: Human-machine interfaces (HMI) must reconcile two concurrent learners in a high dimensional signal space: the person learning to use the interface, and the machine learning algorithm. The goal of these studies is to create and examine machine learning algorithms that adapt in a controlled and cadenced way to foster a harmonious learning environment between the user and the controlled device. To evaluate these algorithms we have developed a simple experimental framework.
Non-familiar finger motions, captured by a data glove, act as control signals to a virtual planar manipulator that is a stand-in for traditional HMIs. This research addresses 1) what sufficient action a machine learner must take to achieve a desired level of user proficiency with the HMI system, 2) what the structure of that algorithm should be, 3) what feedback the user requires to develop a representation of the system and 4) how we can investigate the optimal level of adaptation of the algorithm to the user.
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