US 12,295,727 B2
Gait-based assessment of neurodegeneration
Richard Morris, San Antonio, TX (US); and Barbara Schnan Mastronardi, San Antonio, TX (US)
Assigned to GaitIQ, Inc., San Antonio, TX (US)
Filed by GaitIQ, Inc., San Antonio, TX (US)
Filed on Mar. 28, 2024, as Appl. No. 18/620,011.
Application 18/620,011 is a continuation of application No. 16/948,166, filed on Sep. 4, 2020, granted, now 11,986,286.
Claims priority of provisional application 62/895,973, filed on Sep. 4, 2019.
Prior Publication US 2024/0382108 A1, Nov. 21, 2024
This patent is subject to a terminal disclaimer.
Int. Cl. A61B 5/11 (2006.01); A61B 5/00 (2006.01); G06N 20/00 (2019.01); G06T 7/73 (2017.01); G06V 20/40 (2022.01); G06V 40/20 (2022.01)
CPC A61B 5/112 (2013.01) [A61B 5/1127 (2013.01); A61B 5/4082 (2013.01); A61B 5/4088 (2013.01); G06N 20/00 (2019.01); G06T 7/74 (2017.01); G06V 20/46 (2022.01); G06V 40/25 (2022.01); G06T 2207/10016 (2013.01); G06T 2207/20081 (2013.01); G06T 2207/30196 (2013.01); G06T 2207/30204 (2013.01); G06T 2210/22 (2013.01)] 20 Claims
OG exemplary drawing
 
1. A method for gait-based testing for a neurodegenerative condition in a patient, the method comprising:
acquiring gait kinematic data for the patient, the gait kinematic data comprising one or more time-dependent signals each representing a kinematic parameter of a joint or body segment;
processing the gait kinematic data with one or more computer processors to derive, from the one or more time-dependents signals, one or more respective gait metrics each indicative of a degree of variability, between curve segments for multiple strides within the respective time-dependent signal, in characteristic shapes of the curve segments; and
operating a machine-learning model on input comprising the one or more gait metrics, using the one or more computer processors, to determine at least one predictive score associated with the neurodegenerative condition and the patient, the machine-learning model trained on a training dataset comprising gait metrics derived from gait kinematic data for a plurality of patients along with evaluation scores quantifying the neurodegenerative condition in the respective one of the plurality of patients.