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The goal of this study is to compare clinical performance measures in an immersive virtual reality (VR) environment to performance with a physical upper limb prosthesis.

The goal of this proposal, developed by an interdisciplinary team led by Shu Cole, PhD, professor of health and wellness design at Indiana University, is to conduct research to generate new knowledge that can be used to improve the airline travel experiences of people with disabilities, including those with the greatest support needs.

This study utilizes a wearable data glove system that translates hand movements into signals that control a cursor on a screen. We examined how participants learn a redundant novel task, which can be completed through various solutions.

Stroke survivors vary greatly in their motor deficits and rehabilitative needs. Here, we gather unstructured upper limb movement data and seek to understand if there are patterns in their kinetics that reflect the underlying neuromuscular alterations. In doing so, we can improve our abilities to evaluate patients and design personalized rehab therapy.

True behavioral restitution, a return to normal motor patterns with the affected limb post-stroke, requires the recruitment and restoration of the residual ipsilesional hemisphere/corticospinal tract (CST). Following stroke, the spontaneous recovery mechanism selectively and continuously uses a more optimized neural network for motor execution, depending on the degree of CST damage.

Sensory inputs such as vision, proprioception, and touch play a crucial role in post-stroke recovery. Our research delves into how these sensory contributions can be assessed to develop effective, personalized therapy strategies. Enhancing and tailoring sensory inputs to an individual¡¯s needs allows us to explore how learning outcomes can be improved and errors reduced. Through synthetic simulations that combine muscular, visual, and proprioceptive inputs, we aim to understand better the complex processes involved in motor learning.

Body Computer Interface (BCI) is the idea that one can control a robot simply by thinking about it. In this study, we are laying the groundwork for further BCI and robotic development for individuals to control a hand opening device called the Electro encephalographic mediated glove (or Eglove) using an EEG cap connected to a motorized glove.

Can you build a soft, exo-robot as a wearable orthosis to provide assistance during both rehabilitation and activities of daily living? Can this same device also be used as a therapeutic device by tuning to anti-assistance mode, providing more meaningful therapy to the user?