Papers

8

Total Citations

353

H-Index

7

About

Dean D. Molinaro is a pioneering researcher in wearable robotics and human-machine interfaces, with a focus on developing intelligent control systems for robotic lower-limb exoskeletons. His work sits at the intersection of biomechanics, machine learning, and rehabilitation engineering, addressing one of the central challenges in the field: creating exoskeleton controllers that work seamlessly across diverse real-world environments and user populations. Molinaro's most impactful contributions include a real-time gait phase estimator for multimodal locomotion control (153 citations) and a unified exoskeleton control framework that estimates human joint moments to autonomously adapt assistance without context-specific tuning (104 citations). These advances represent a significant step toward clinically viable, generalizable exoskeleton systems. His deep learning approaches to slope prediction, locomotion mode classification, and biological hip torque estimation further demonstrate his commitment to data-driven, user-adaptive solutions. More recently, his work has extended to stroke rehabilitation, proposing online adaptation frameworks that personalize assistance for individuals with varying gait impairments. With over 350 total citations and a body of work spanning sensing, estimation, and control, Molinaro is establishing himself as a leading voice in next-generation assistive robotics research.

Research Focus

Key Achievements

7
H-Index
8
Papers
353
Total Citations
44
Avg Citations/Paper
🏆 Most Cited Paper
Real-Time Gait Phase Estimation for Robotic Hip Exoskeleton Control During Multimodal Locomotion
153 citations · 2021
📈 Most Prolific Year: 2021 (2 Papers)
🤝 Key Collaborators: 15
🏛 Institutions: Georgia Institute of Technology, Robotics Research (United States)

Top Papers

  1. 1
  2. 2
  3. 3
  4. 4
  5. 5
  6. 6
  7. 7
  8. 8

Key Collaborators

Contact & Links

Available for collaboration
Content generated · 14 days ago