Invention Grant
- Patent Title: Assessing diseases by analyzing gait measurements
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Application No.: US16889642Application Date: 2020-06-01
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Publication No.: US11589781B2Publication Date: 2023-02-28
- Inventor: Gholam Motamedi , Ophir Frieder , Cristopher Flagg , Jian-Young Wu
- Applicant: GEORGETOWN UNIVERSITY
- Applicant Address: US DC Washington
- Assignee: GEORGETOWN UNIVERSITY
- Current Assignee: GEORGETOWN UNIVERSITY
- Current Assignee Address: US DC Washington
- Agency: Blank Rome LLP
- Main IPC: A61B5/11
- IPC: A61B5/11 ; A61B5/00 ; G06F40/205

Abstract:
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.
Public/Granted literature
- US20200375501A1 ASSESSING DISEASES BY ANALYZING GAIT MEASUREMENTS Public/Granted day:2020-12-03
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