Andrea Sarasola-Sanz
Bernstein Center for Computational Neuroscience Tübingen, University of Tübingen, Tecnalia
Papers
11
Total Citations
300
H-Index
8
About
Andrea Sarasola-Sanz is a pioneering researcher at the intersection of neural engineering, rehabilitation robotics, and brain-machine interfaces, with a particular focus on restoring motor function in stroke patients. Her work has made substantial contributions to the development of hybrid brain-machine interfaces (hBMIs) that integrate EEG and EMG signals, demonstrating that combining neural and muscular activity yields more robust and accurate control systems than traditional single-signal approaches — a finding that has garnered over 80 citations and influenced the field's direction significantly. A hallmark of Sarasola-Sanz's research is her pursuit of multi-dimensional motor decoding: her classification of distinct reaching movements from EEG signals (65 citations) and multi-joint kinematics decoding from EMG challenged prevailing limitations in signal resolution and control complexity. Her innovative mirror myoelectric interface addressed pathological muscle synergies directly, offering a more physiologically informed rehabilitation strategy. Notably, her 2021 work introduced the functional synergy recruitment index as a reliable biomarker for tracking motor recovery in chronic stroke, bridging neuroscience and clinical assessment. Across her career, spanning from foundational exoskeleton control studies to advanced neural interface design, Sarasola-Sanz has consistently worked to translate cutting-edge neurotechnology into meaningful clinical rehabilitation tools.
Research Focus
Key Achievements
Top Papers
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- 2Classification of different reaching movements from the same limb using EEG65 citations · 2017
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- 8Towards decoding of functional movements from the same limb using EEG12 citations · 2015
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