no code implementations • 20 Feb 2024 • Nikolaos Smyrnakis, Tasos Karakostas, R. James Cotton
Gait analysis from videos obtained from a smartphone would open up many clinical opportunities for detecting and quantifying gait impairments.
no code implementations • 30 Jul 2023 • R. James Cotton, J. D. Peiffer, Kunal Shah, Allison DeLillo, Anthony Cimorelli, Shawana Anarwala, Kayan Abdou, Tasos Karakostas
We find that contrastive learning on unannotated gait data learns a representation that captures clinically meaningful information.
no code implementations • 19 Mar 2023 • R. James Cotton, Allison DeLillo, Anthony Cimorelli, Kunal Shah, J. D. Peiffer, Shawana Anarwala, Kayan Abdou, Tasos Karakostas
Markerless motion capture using computer vision and human pose estimation (HPE) has the potential to expand access to precise movement analysis.
no code implementations • 4 Mar 2023 • R. James Cotton, Anthony Cimorelli, Kunal Shah, Shawana Anarwala, Scott Uhlrich, Tasos Karakostas
Markerless pose estimation allows reconstructing human movement from multiple synchronized and calibrated views, and has the potential to make movement analysis easy and quick, including gait analysis.
no code implementations • 17 Mar 2022 • R. James Cotton, Emoonah McClerklin, Anthony Cimorelli, Ankit Patel, Tasos Karakostas
Human pose estimation from monocular video is a rapidly advancing field that offers great promise to human movement science and rehabilitation.