Georgetown University

Cornell Research Foundation Inc.

Jian-young Wu

Ophir Frieder

Cristopher Flagg

Hongtao Ma

Gholam Motamedi

Theodore H Schwartz

A gait analysis system, which includes a neural network with a recurrent neural network layer and a fully connected layer, that receives sensor data indicative of an individual's gait and outputs an assessment regarding the individual's health. The neural network is trained using training data indicative of abnormal gaits and normal gaits. To analyze the training data and the sensor data, the recurrent neural network layer parses each piece of data into a series of windows and analyzes each window in series to generate a context vector characterizing each window and the previously analyzed windows. The fully connected layer, having been trained to differentiate between normal gaits and abnormal gaits based on context vectors characterizing the training data, is used to generate a final assessment characterizing the user gate as normal or abnormal using one or more of the context vectors characterizing the sensor data.

Assessing diseases by analyzing gait measurements

A subdural electro-optical sensor system may include a substrate to which is attached an array of electrodes, light emitters, and light detectors. The sensor system may be sufficiently thin, flexible, sterile and biocompatible to be positioned subdurally.

Subdural electro-optical sensor

Growing community of inventors

Gaithersburg, MD, United States of America

Jian-young Wu