Sergio Machaca

Johns Hopkins University

Papers

3

Total Citations

24

H-Index

3

About

Sergio Machaca is a researcher advancing the field of haptic feedback for robotic minimally invasive surgery (RMIS). His work addresses a critical gap in current surgical robots, which lack tactile feedback, forcing surgeons to rely solely on visual cues. Machaca’s research centers on developing and evaluating multi-modality haptic systems—including wrist-squeezing force feedback—to restore the sense of touch in teleoperated medical devices. His most-cited paper (2022, 9 citations) proposes a ROS-based modular haptic feedback system for RMIS training assessments, while a second highly cited study (2022, 8 citations) demonstrates that wrist-squeezing force feedback significantly improves both accuracy and speed in surgical training. A foundational 2020 paper (7 citations) explores the utility of dual-modality haptic feedback in teleoperated systems, bridging insights from human sensorimotor integration to robotic applications. Collectively, Machaca’s work has garnered over 24 citations, establishing him as a contributor to safer, more intuitive surgical robotics. His research holds promise for reducing training times and improving patient outcomes by giving surgeons a more natural, tactile connection to their instruments.

Research Focus

Key Achievements

3
H-Index
3
Papers
24
Total Citations
8
Avg Citations/Paper
🏆 Most Cited Paper
Towards a ROS-based Modular Multi-Modality Haptic Feedback System for Robotic Minimally Invasive Surgery Training Assessments
9 citations · 2022
📈 Most Prolific Year: 2022 (2 Papers)
🤝 Key Collaborators: 8
🏛 Institutions: Johns Hopkins University

Top Papers

  1. 1
  2. 2
  3. 3

Key Collaborators

Contact & Links

Available for collaboration
Content generated · 13 days ago