Elena M. Gutierrez-Farewik
Papers
8
Total Citations
363
H-Index
6
About
Elena M. Gutierrez-Farewik is a leading researcher at the intersection of biomechanics, neuromusculoskeletal modeling, and wearable robotics, with a primary focus on developing intelligent control systems for powered exoskeletons. Her work centers on using machine learning and sensor fusion to decode human movement intentions and enable seamless human-robot interaction. She has made major contributions to estimating joint torques and predicting gait trajectories and phases using EMG-driven models, LSTM networks, and deep convolutional neural networks, with her most-cited papers accumulating over 100, 88, and 73 citations respectively. Gutierrez-Farewik has also advanced the understanding of shoulder kinematics through a comprehensive survey and pioneered muscle synergy-inspired methods for detecting movement intentions with minimal sensors, achieving accurate joint moment prediction using only a few EMG channels. Her recent work includes multi-objective human-in-the-loop optimization of exoskeleton assistance for pathological gait, such as dropfoot. With over 350 total citations and a portfolio spanning from fundamental biomechanics to applied rehabilitation robotics, her research is instrumental in making assistive devices more responsive, personalized, and effective for individuals with movement disorders.
Research Focus
Key Achievements
Top Papers
- 1
- 2Gait Trajectory and Gait Phase Prediction Based on an LSTM Network88 citations · 2020
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- 4A survey of human shoulder functional kinematic representations47 citations · 2018
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