Nicola Lotti
Papers
17
Total Citations
450
H-Index
11
About
Nicola Lotti is a leading researcher in wearable robotics, specializing in soft exosuits and human-machine interfaces for rehabilitation and mobility assistance. His work centers on developing adaptive, intuitive control systems that bridge the gap between ergonomic design and precise intention detection. Lotti’s major contributions include pioneering model-based myoelectric control for soft arm exosuits (150 citations), which enables seamless human-robot interaction by interpreting muscle signals, and advancing EMG-driven machine learning for hand rehabilitation gloves (70 citations). He has also demonstrated real-world impact through a study showing that soft robotic shorts improve walking efficiency in older adults (38 citations), highlighting the potential of wearable tech for age-related mobility challenges. Lotti’s comparative analyses of myoelectric versus force control strategies (43 citations) and his exploration of immersive haptic feedback via neuromuscular electrical stimulation (25 citations) further underscore his innovative approach. His work on enhancing gait assistance with machine learning (22 citations) and addressing upper limb endurance in individuals with multiple sclerosis (12 citations) reflects a commitment to inclusive, clinically relevant solutions. With over 400 total citations, Lotti is shaping the next generation of wearable robots that are both comfortable and intelligent.
Research Focus
Key Achievements
Top Papers
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- 3Myoelectric or Force Control? A Comparative Study on a Soft Arm Exosuit43 citations · 2022
- 4Soft robotic shorts improve outdoor walking efficiency in older adults38 citations · 2024
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- 8Adaptive Hybrid FES-Force Controller for Arm Exosuit13 citations · 2022
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