Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Embedded Force Sensor with Deep Transformation Calibration for Interventional Soft Robots.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference·2025
Same author

Design Optimization of a Hybrid-Driven Soft Surgical Robot with Biomimetic Constraints.

Biomimetics (Basel, Switzerland)·2024
Same author

Hyperelastic Modeling and Validation of Hybrid-Actuated Soft Robot with Pressure-Stiffening.

Micromachines·2023
Same author

Stiffness Adaptation of a Hybrid Soft Surgical Robot for Improved Safety in Interventional Surgery.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference·2022
Same author

Comparison of Mechanistic and Learning-based Tip Force Estimation on Tendon-driven Soft Robotic Catheters.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference·2022
Same author

Design of a Linear Wavenumber Spectrometer for Line Scanning Optical Coherence Tomography with 50 mm Focal Length Cylindrical Optics.

Sensors (Basel, Switzerland)·2022

Related Experiment Video

Updated: Nov 18, 2025

Using Virtual Reality to Transfer Motor Skill Knowledge from One Hand to Another
05:12

Using Virtual Reality to Transfer Motor Skill Knowledge from One Hand to Another

Published on: September 18, 2017

547.8K

Deep Learning-Based Haptic Guidance for Surgical Skills Transfer.

Pedram Fekri1, Javad Dargahi1, Mehrdad Zadeh2

  • 1Mehchanical, Industrial, and Aerospace Engineering Department, Concordia University, Montreal, QC, Canada.

Frontiers in Robotics and AI
|February 8, 2021
PubMed
Summary

This study introduces a deep learning skill transfer system to reduce surgical errors and improve medical education. The AI model provides real-time haptic guidance, enhancing surgeon training and supervision.

Keywords:
COVID-19LSTMbone drillingdeep learningforce feedbackhapticrecurrent neural networksurgical skill transfer

More Related Videos

Author Spotlight: Revolutionizing Remote Surgery with Augmented Reality and Robotics for Enhanced Precision and Accessibility
07:46

Author Spotlight: Revolutionizing Remote Surgery with Augmented Reality and Robotics for Enhanced Precision and Accessibility

Published on: August 9, 2024

1.0K
Technical Approach for Infrared Tracking for Soft Tissue Navigation with a Holographic Head-Mounted Display and Preclinical Validation
10:25

Technical Approach for Infrared Tracking for Soft Tissue Navigation with a Holographic Head-Mounted Display and Preclinical Validation

Published on: September 2, 2025

288

Related Experiment Videos

Last Updated: Nov 18, 2025

Using Virtual Reality to Transfer Motor Skill Knowledge from One Hand to Another
05:12

Using Virtual Reality to Transfer Motor Skill Knowledge from One Hand to Another

Published on: September 18, 2017

547.8K
Author Spotlight: Revolutionizing Remote Surgery with Augmented Reality and Robotics for Enhanced Precision and Accessibility
07:46

Author Spotlight: Revolutionizing Remote Surgery with Augmented Reality and Robotics for Enhanced Precision and Accessibility

Published on: August 9, 2024

1.0K
Technical Approach for Infrared Tracking for Soft Tissue Navigation with a Holographic Head-Mounted Display and Preclinical Validation
10:25

Technical Approach for Infrared Tracking for Soft Tissue Navigation with a Holographic Head-Mounted Display and Preclinical Validation

Published on: September 2, 2025

288

Area of Science:

  • Medical Education Technology
  • Surgical Training Systems
  • Artificial Intelligence in Healthcare

Background:

  • Medical errors and adverse events remain a significant concern in surgery.
  • Traditional surgical training is costly, has limited trial-and-error opportunities, and faces challenges exacerbated by the COVID-19 pandemic.
  • Existing patient safety initiatives have not fully eradicated surgical errors.

Purpose of the Study:

  • To develop an AI-driven skill transfer system for surgical training.
  • To model expert surgeon behavior for effective skill transmission.
  • To provide real-time haptic guidance for novice and expert surgeons.

Main Methods:

  • Utilized deep learning algorithms to model expert surgeon actions.
  • Developed a skill transfer method learning from expert demonstrations.
  • Employed a simulated operating room environment for femur drilling surgery.
  • Collected data and assessed model performance in the simulation.

Main Results:

  • The proposed deep learning model successfully learned expert surgical behaviors.
  • The system generated real-time haptic guidance signals.
  • Experimental results demonstrated an acceptable error rate in haptic signal emission.
  • The simulation validated the system's effectiveness in a realistic surgical scenario.

Conclusions:

  • AI-powered skill transfer systems offer a viable solution to enhance surgical education and reduce errors.
  • Real-time haptic feedback can effectively guide and supervise surgeons during procedures.
  • The developed method shows promise for improving surgical proficiency and patient safety.