Papers

16

Total Citations

190

H-Index

7

About

Ali Nasr is a leading researcher in the field of wearable robotic exoskeletons, with a focus on human-robot interaction and assistive technologies. His work spans the design, control, and safety of active-passive exoskeletons for both rehabilitation and industrial applications. Nasr’s major contributions include developing computational models for optimal exoskeleton design, as evidenced by his most-cited paper (35 citations), and establishing comprehensive safety guidelines for wearable robots (33 citations). He has also advanced myoelectric control systems for prosthetic and exoskeleton devices, as highlighted in his influential review (27 citations) and work on machine-learning-driven control (20 citations). Notably, Nasr’s research on assist-as-needed hierarchical control (21 citations) and experimental evaluations of active-passive systems (20 citations) demonstrates his commitment to practical, human-centered robotics. With over 160 total citations across his publications, Nasr’s work is shaping the future of safe, efficient, and intelligent wearable robots, making significant strides in enhancing human strength and rehabilitation outcomes.

Research Focus

Key Achievements

7
H-Index
16
Papers
190
Total Citations
12
Avg Citations/Paper
🏆 Most Cited Paper
Optimal design of active-passive shoulder exoskeletons: a computational modeling of human-robot interaction
35 citations · 2022
📈 Most Prolific Year: 2023 (3 Papers)
🤝 Key Collaborators: 22
🏛 Institutions: University of Waterloo, K.N.Toosi University of Technology

Top Papers

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Key Collaborators

Contact & Links

Available for collaboration
Content generated · 13 days ago