Ao, DiFregly, Benjamin J.2025-01-092025-01-092024Ao, D., & Fregly, B. J. (2024). Comparison of synergy extrapolation and static optimization for estimating multiple unmeasured muscle activations during walking. Journal of NeuroEngineering and Rehabilitation, 21(1), 194. https://doi.org/10.1186/s12984-024-01490-yhttps://hdl.handle.net/1911/118138Calibrated electromyography (EMG)-driven musculoskeletal models can provide insight into internal quantities (e.g., muscle forces) that are difficult or impossible to measure experimentally. However, the need for EMG data from all involved muscles presents a significant barrier to the widespread application of EMG-driven modeling methods. Synergy extrapolation (SynX) is a computational method that can estimate a single missing EMG signal with reasonable accuracy during the EMG-driven model calibration process, yet its performance in estimating a larger number of missing EMG signals remains unknown.engExcept where otherwise noted, this work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives (CC BY-NC-ND) license. Permission to reuse, publish, or reproduce the work beyond the terms of the license or beyond the bounds of fair use or other exemptions to copyright law must be obtained from the copyright holder.Journal articleEMG-driven modelSynergy extrapolationStatic optimizationModel personalizationMuscle forceMuscle activationStrokes12984-024-01490-yhttps://doi.org/10.1186/s12984-024-01490-y