Alejandro Moya-Esteban
Papers
3
Total Citations
32
H-Index
3
About
Alejandro Moya-Esteban is a rising leader in biomechatronics and occupational ergonomics, whose work directly tackles the global burden of chronic low back pain. His research sits at the intersection of neuromechanics, musculoskeletal modeling, and soft robotics, with a central focus on developing intelligent, adaptive exosuits for industrial lifting. Moya-Esteban’s major contribution is pioneering real-time, model-based control systems that estimate internal lumbosacral joint loading—compression forces and moments—without relying on external load sensors. His most cited work (2023, 24 citations) introduced an electromyography-driven musculoskeletal model capable of estimating lumbosacral compression forces in real time during exoskeleton-assisted lifting. He further advanced the field by developing a soft back exosuit controlled by a neuromechanical model that adapts assistance to unknown loads, reducing harmful spinal compression forces (2025, 5 citations). His 2023 paper on adaptive assistance via model-based moment estimates (3 citations) demonstrates how continuous, internal-state-driven control outperforms traditional kinematic-based methods. By bridging computational biomechanics with wearable robotics, Moya-Esteban is laying the groundwork for next-generation occupational exoskeletons that are safer, smarter, and truly responsive to human physiology.
Research Focus
Key Achievements
Top Papers
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