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The Mobilize Center and Restore Center at Stanford University invite you to join our next webinar, featuring Ryan Roemmich and Jan Stenum from the Kennedy Krieger Institute and John Hopkins University
DETAILS
Title: Clinical Gait Analysis using Video-Based Pose Estimation: Multiple Perspectives, Clinical Populations, and Measuring Change
Speaker: Ryan Roemmich & Jan Stenum, Kennedy Krieger Institute and John Hopkins University
Time: Wednesday, March 8, 2023 at 9:00 AM Pacific Time
Registration: Click here to register
ABSTRACT
Identifying and understanding gait dysfunction is an important component of rehabilitation and the initiation of treatment. Current state-of-the-art approaches for gait analysis, such as marker-based motion capture systems and instrumented gait mats, are largely inaccessible due to prohibitive costs of time, money, and effort required to perform the assessments. Video based motion analysis provides an easy and accessible method for assessing clinically relevant gait measures in the clinic and at home.
In the first half of the webinar, Dr. Roemmich will demonstrate the ability to perform quantitative gait analyses in multiple clinical populations using videos that can be recorded simply using household devices. They will highlight and discuss the versatile workflow that leverages an open-source human pose estimation algorithm (OpenPose) and the comprehensive validation they conducted to support its use clinically. This includes 1) validation of the workflow in three different groups of participants (adults without gait impairment, persons post-stroke, and persons with Parkinson’s disease) via comparison to ground-truth three-dimensional motion capture, 2) demonstration of the ability to capture clinically relevant, condition-specific gait parameters, and 3) tracking of within-participant changes in gait, as is required to measure progress in rehabilitation and recovery.
In the tutorial during the second half of the webinar, Dr. Stenum will walk the audience through all the steps needed to execute this workflow for video-based clinical gait analysis (freely available on Github) and provide perspectives on best practices for getting optimal results in clinical and/or in-home settings.
DETAILS
Title: Clinical Gait Analysis using Video-Based Pose Estimation: Multiple Perspectives, Clinical Populations, and Measuring Change
Speaker: Ryan Roemmich & Jan Stenum, Kennedy Krieger Institute and John Hopkins University
Time: Wednesday, March 8, 2023 at 9:00 AM Pacific Time
Registration: Click here to register
ABSTRACT
Identifying and understanding gait dysfunction is an important component of rehabilitation and the initiation of treatment. Current state-of-the-art approaches for gait analysis, such as marker-based motion capture systems and instrumented gait mats, are largely inaccessible due to prohibitive costs of time, money, and effort required to perform the assessments. Video based motion analysis provides an easy and accessible method for assessing clinically relevant gait measures in the clinic and at home.
In the first half of the webinar, Dr. Roemmich will demonstrate the ability to perform quantitative gait analyses in multiple clinical populations using videos that can be recorded simply using household devices. They will highlight and discuss the versatile workflow that leverages an open-source human pose estimation algorithm (OpenPose) and the comprehensive validation they conducted to support its use clinically. This includes 1) validation of the workflow in three different groups of participants (adults without gait impairment, persons post-stroke, and persons with Parkinson’s disease) via comparison to ground-truth three-dimensional motion capture, 2) demonstration of the ability to capture clinically relevant, condition-specific gait parameters, and 3) tracking of within-participant changes in gait, as is required to measure progress in rehabilitation and recovery.
In the tutorial during the second half of the webinar, Dr. Stenum will walk the audience through all the steps needed to execute this workflow for video-based clinical gait analysis (freely available on Github) and provide perspectives on best practices for getting optimal results in clinical and/or in-home settings.