Internet-of-Things-Enabled Markerless Running Gait Assessment from a Single Smartphone Camera.

ABSTRACT: Running gait assessment is essential for the development of technical optimization strategies as well as to inform injury prevention and rehabilitation. Currently, running gait assessment relies on (i) visual assessment, exhibiting subjectivity and limited reliability, or (ii) use of instrumented approaches, which often carry high costs and can be intrusive due to the attachment of equipment to the body. Here, the use of an IoT-enabled markerless computer vision smartphone application based upon Google's pose estimation model BlazePose was evaluated for running gait assessment for use in low-resource settings. That human pose estimation architecture was used to extract contact time, swing time, step time, knee flexion angle, and foot strike location from a large cohort of runners. The gold

SUBMITTER: Young F 

PROVIDER: S-EPMC9866353 | biostudies-literature | 2023 Jan

REPOSITORIES: biostudies-literature