Papers
6
Total Citations
82
H-Index
5
About
Gabriel Delgado is a leading researcher at the intersection of wearable robotics, human motion analysis, and rehabilitation technology. His work centers on developing intelligent, bioinspired systems to restore mobility and suppress pathological tremors, addressing some of the most prevalent movement disorders. Delgado’s major contributions include a comprehensive review on wearable technologies for tremor suppression (52 citations), which has become a foundational reference in the field. He also pioneered a bioinspired hierarchical electronic architecture for robotic locomotion assistance, drawing directly from the human motor system to control exoskeletons. To address the critical challenge of balance in overground exoskeletons, he developed BenchBalance, a benchmarking system that quantifies stability for both robots and their users. His recent work pushes the boundaries of personalization, introducing novel methods for three-dimensional gait trajectory prediction using regression and LSTM models, enabling individualized rehabilitation. Delgado’s research is distinguished by its translational focus—moving from fundamental biomechanics to deployable, user-specific assistive devices. With a growing citation impact and a portfolio of highly cited papers, he is shaping the next generation of adaptive, human-centered robotic systems for clinical and daily-life applications.
Research Focus
Key Achievements
Top Papers
- 1A Review on Wearable Technologies for Tremor Suppression52 citations · 2021
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