University of Washington

Anthony Law

Randall Bly

Shwetak N Patel

Lynn B McGrath

Alex T Mariakakis

Jacob Baudin

Angelique Berens

Muneaki Miyasaka

In some embodiments, techniques for using machine learning to enable visible light pupilometry are provided. In some embodiments, a smartphone may be used to create a visible light video recording of a pupillary light reflex (PLR). A machine learning model may be used to detect a size of a pupil in the video recording over time, and the size over time may be presented to a clinician. In some embodiments, a system that includes a smartphone and a box that holds the smartphone in a predetermined relationship to a subject's face is provided. In some embodiments, a sequential convolutional neural network architecture is used. In some embodiments, a fully convolutional neural network architecture is used.

Smartphone-based digital pupillometer

An adapter for endoscopy can operably connect camera features and light source features of a portable electronic device with a respective viewfinder and illumination element of a medical endoscope. Systems including an endoscope, adapter, and handheld electronic device with a microphone, light source, and camera can, when connected, be used to perform stroboscopic endoscopic examinations.

Phone adapter for flexible laryngoscope and rigid endoscopes

Growing community of inventors

Seattle, WA, United States of America

Anthony Law