OpenCap: Human movement dynamics from smartphone videos

• DOI: 10.1371/journal.pcbi.1011462
• Publication Date: 2023-10-19T17:22:56Z
• Authors: Scott D. Uhlrich; Antoine Falisse; Łukasz Kidziński; Julie Muccini; Michael Ko; Akshay S. Chaudhari; Jennifer L. Hicks; Scott L. Delp
• Keywords: Motion Capture; Dynamics; Motion analysis; Functional movement

Measures of human movement dynamics can predict outcomes like injury risk or musculoskeletal disease progression. However, these measures are rarely quantified in large-scale research studies clinical practice due to the prohibitive cost, time, and expertise required. Here we present validate OpenCap, an open-source platform for computing both kinematics (i.e., motion) forces) using videos captured from two more smartphones. OpenCap leverages pose estimation algorithms identify body landmarks videos; deep learning biomechanical models estimate three-dimensional kinematics; physics-based simulations muscle activations dynamics. OpenCap’s web application enables users collect synchronous visualize data that is automatically processed cloud, thereby eliminating need specialized hardware, software, expertise. We show accurately predicts dynamic measures, activations, joint loads, moments, which be used screen risk, evaluate intervention efficacy, assess between-group differences, inform rehabilitation decisions. Additionally, demonstrate practical utility through a 100-subject field study, where clinician estimated 25 times faster than laboratory-based approach at less 1% cost. By democratizing access analysis, accelerate incorporation metrics into studies, trials, practice.