Evaluating Sparse Inertial Measurement Unit Configurations for Inferring Treadmill Running Motion.

ABSTRACT: Inertial measurement units (IMUs) are used to analyze running performance. While leveraging one sensor to estimate kinematic and kinetic variables is common, sparsity limits the number of digital biomarkers that can be evaluated. Shallow recurrent decoder networks (SHRED) can reconstruct a dense set of time-series signals from a single input sensor and have been successful in human mobility applications, highlighting the potential for this algorithm to monitor running. We trained and tested subject-specific SHRED models of nine subjects running on a treadmill to map from one input sensor to the remaining three IMUs. We varied the type of input to reflect experimental parameters that are important in running studies-sensor location, sensor type, sampling rate, and running speed-and compared

SUBMITTER: Pitts MN 

PROVIDER: S-EPMC11991315 | biostudies-literature | 2025 Mar

REPOSITORIES: biostudies-literature