University of Virginia Patent Foundation

Chad M Aldridge

Gustavo Kunde Rohde

Andrew M Southerland

Omar Uribe

Yan Zhuang

Mark McDonald

Mohamed Abul Hassan

An automated and quantitative facial weakness screening framework that utilizes a Bi-LSTM network to model the temporal dynamics among the shape and appearance features. The technique is beneficial to assist the paramedics or other users to identify the facial weakness in the field or, more importantly, whenever expertise in neurology is not available either for emergency patient triage (e.g., pre-hospital stroke care) or chronic disease management (e.g., Bell's palsy rehabilitation screen), leading to increased coverage and earlier treatment. The technique provides visualizable and interpretable results to increase its transparency and interpretability. The technique provides for inexpensive solutions that can be used in areas underserved by non-neurologists to more readily identify neurological deficits such as facial weakness in the field or other environment.

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Charlottesville, VA, United States of America

Chad M Aldridge