Papers

18

Total Citations

137

H-Index

7

About

Sami Bennour is a robotics researcher whose work sits at the intersection of cable-driven parallel robots (CDPRs) and rehabilitation engineering. Over the past decade, he has established himself as a specialist in the design, optimization, and simulation of cable-based robotic systems intended to assist patients in recovering motor function following injury or illness. Bennour's most cited contribution, "Design study of a cable-based gait training machine" (2017, 36 citations), laid important groundwork for applying CDPRs to lower-limb rehabilitation. He has since extended this vision to upper-limb recovery, developing task-based and sensitivity-driven design methodologies that incorporate real patient movement data — captured using Qualisys motion capture systems — and clinician input from occupational therapists to define clinically meaningful workspaces. This human-centered engineering approach distinguishes his work from purely theoretical robot design. A recurring challenge Bennour addresses is the limited rotational workspace of CDPRs. His proposals for hybrid configurations and reconfigurable 6-DoF platforms demonstrate creative engineering solutions to expand the practical applicability of these systems. Collectively, his publications have accumulated over 115 citations, reflecting a growing recognition within the rehabilitation robotics community of his methodical, application-driven contributions to improving quality of life for patients with mobility impairments.

Research Focus

Key Achievements

7
H-Index
18
Papers
137
Total Citations
8
Avg Citations/Paper
🏆 Most Cited Paper
Design study of a cable-based gait training machine
36 citations · 2017
📈 Most Prolific Year: 2022 (5 Papers)
🤝 Key Collaborators: 20
🏛 Institutions: University of Sousse, University of Monastir, Georgia Tech Lorraine

Top Papers

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Key Collaborators

Contact & Links

Available for collaboration
Content generated · 13 days ago