Award Abstract # 2109635
CAREER: Human-Centric Control for Teleoperated Surgical Robots

NSF Org: CMMI
Division of Civil, Mechanical, and Manufacturing Innovation
Recipient: UNIVERSITY OF TEXAS AT AUSTIN
Initial Amendment Date: February 19, 2021
Latest Amendment Date: January 4, 2024
Award Number: 2109635
Award Instrument: Standard Grant
Program Manager: Alexandra Medina-Borja
amedinab@nsf.gov
 (703)292-7557
CMMI
 Division of Civil, Mechanical, and Manufacturing Innovation
ENG
 Directorate for Engineering
Start Date: October 1, 2020
End Date: March 31, 2026 (Estimated)
Total Intended Award Amount: $500,000.00
Total Awarded Amount to Date: $554,499.00
Funds Obligated to Date: FY 2019 = $449,238.00
FY 2020 = $22,950.00

FY 2021 = $7,988.00

FY 2022 = $16,000.00

FY 2023 = $16,000.00

FY 2024 = $42,323.00
History of Investigator:
  • Ann Majewicz Fey (Principal Investigator)
    Ann.MajewiczFey@utexas.edu
Recipient Sponsored Research Office: University of Texas at Austin
110 INNER CAMPUS DR
AUSTIN
TX  US  78712-1139
(512)471-6424
Sponsor Congressional District: 25
Primary Place of Performance: University of Texas at Austin
austin
TX  US  78759-5316
Primary Place of Performance
Congressional District:
37
Unique Entity Identifier (UEI): V6AFQPN18437
Parent UEI:
NSF Program(s): M3X - Mind, Machine, and Motor,
CAREER: FACULTY EARLY CAR DEV
Primary Program Source: 01002223DB NSF RESEARCH & RELATED ACTIVIT
01002324DB NSF RESEARCH & RELATED ACTIVIT

01002425DB NSF RESEARCH & RELATED ACTIVIT

01001920DB NSF RESEARCH & RELATED ACTIVIT

01002021DB NSF RESEARCH & RELATED ACTIVIT

01002122DB NSF RESEARCH & RELATED ACTIVIT
Program Reference Code(s): 060Z, 063Z, 1045, 116E, 7632, 9102, 9178, 9231, 9251, CL10
Program Element Code(s): 058Y00, 104500
Award Agency Code: 4900
Fund Agency Code: 4900
Assistance Listing Number(s): 47.041

ABSTRACT

Human-in-the-loop control strategies in which the user performs a task better, and feels more confident to do so, is an important area of research in teleoperated robotics. However, human behavior can often change as a result of environmental, physical, emotional, and social factors. The goal of this Faculty Early Career Development Program (CAREER) project is to design adaptive control systems that can interpret and react to the dynamic human user. This research will be impactful in the field of surgical robotics where interaction with the patient demands safety and effectiveness from both the human operator (surgeon) and the robotic system itself. Robotic systems that are aware and responsive to user skill and performance style could be more able to avoid user errors and respond to adverse events in unpredictable environments. By integrating real-time models of user intent, movement style, and expertise level with a surgical robotic platform, this project will advance the NSF mission to promote the progress of science and advance national health by exploring fundamental relationships human behavior, motor control, and machine manipulation within the context of surgical robotics. The project supports education and broadening participation in engineering by promoting innovation activities related to healthcare and technology development for medical simulation and training.

The goal of this CAREER project is to develop adaptive control algorithms for teleoperated robotic surgical systems that can respond to, ignore, and/or augment human motor control inputs depending on the output of user-centric models of behavior and task difficulty. Model output will be based in real-time, data-driven predictions and interpretations of human intent, surgical style, and level of expertise. Research objectives include: developing methods to model and control human behavior (e.g., user behavior and expertise) during unstructured teleoperation tasks; designing and analyzing adaptive control laws to enhance performance through visual and haptic guidance; and evaluating the effectiveness of these algorithms on clinically-relevant outcomes in training and intervention using a surgical robotic platform. A key innovation of this work is designing control methods to be agnostic of the specific task performed by the human operator: only user-centric metrics and movement data will serve as inputs to novel difficulty and stylistic prediction models that will then be used to create adaptive control algorithms. This work could lead to significant improvements in the adaptability, capability, and usability of teleoperated surgical systems when collaborating with a human user.

This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

PUBLICATIONS PRODUCED AS A RESULT OF THIS RESEARCH

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(Showing: 1 - 10 of 18)
Battaglia, Edoardo and Boehm, Jacob and Zheng, Yi and Jamieson, Andrew R. and Gahan, Jeffrey and Majewicz Fey, Ann "Rethinking Autonomous Surgery: Focusing on Enhancement over Autonomy" European Urology Focus , v.7 , 2021 https://doi.org/10.1016/j.euf.2021.06.009 Citation Details
Battaglia, Edoardo and Fey, Ann Majewicz "Cartesian Space Vibrotactile Cues Outperform Tool Space Cues when Moving from 2D to 3D Needle Insertion Task" BioRob , 2022 https://doi.org/10.1109/BioRob52689.2022.9925272 Citation Details
Battaglia, Edoardo and Mueller, Bradly and Hogg, Deborah and Rege, Robert and Scott, Daniel and Fey, Ann Majewicz "Evaluation of Pre-Training with the da Vinci Skills Simulator on Motor Skill Acquisition in a Surgical Robotics Curriculum" Journal of Medical Robotics Research , v.06 , 2021 https://doi.org/10.1142/S2424905X21500069 Citation Details
Boehm, Jacob R. and Fey, Nicholas P. and Fey, Ann Majewicz "Shaping Human Movement via Bimanually-Dependent Haptic Force Feedback" , 2023 https://doi.org/10.1109/WHC56415.2023.10224475 Citation Details
Boehm, J. and Fey, N. and Majewicz Fey, A. "Online Recognition of Bimanual Coordination Provides Important Context for Movement Data in Bimanual Teleoperated Robots" IEEE International Conference on Robotics and Automation , 2021 Citation Details
Ershad, Marzieh and Rege, Robert and Fey, Ann Majewicz "Adaptive Surgical Robotic Training Using Real-Time Stylistic Behavior Feedback Through Haptic Cues" IEEE Transactions on Medical Robotics and Bionics , v.3 , 2021 https://doi.org/10.1109/TMRB.2021.3124128 Citation Details
Hassun, Andres and Kho, Kimberly and Yvette_Williams-Brown, M and Fey, Ann Majewicz "Training with a Visual-Haptic Simulator for Trocar Insertion" Journal of Medical Robotics Research , 2024 https://doi.org/10.1142/S2424905X24400075 Citation Details
Leonard, Grey and Cao, Jing and Scielzo, Shannon and Zheng, Yi and Tellez, Juan and Zeh, Herbert J. and Fey, Ann Majewicz "The Effect of Stress and Conscientiousness on Simulated Surgical Performance in Unbalanced Groups: A Bayesian Hierarchical Model" Journal of the American College of Surgeons , v.231 , 2020 https://doi.org/10.1016/j.jamcollsurg.2020.07.397 Citation Details
Madera, Jonathan and Peters, Craig and Fey, Ann Majewicz "A Novel Pulley-Based Simulator for Ureteroscopy with Visuo-Haptic Feedback" Haptics Symposium , 2022 https://doi.org/10.1109/HAPTICS52432.2022.9765615 Citation Details
Rabe, Kaitlin "Ultrasound Sensing Can Improve Continuous Classification of Discrete Ambulation Modes Compared to Surface Electromyography" IEEE transactions on biomedical engineering , 2020 https://doi.org/0.1109/TBME.2020.3032077 Citation Details
Rowland, Drake and Davis, Benjamin and Higgins, Taylor and Fey, Ann Majewicz "Enhancing User Performance by Adaptively Changing Haptic Feedback Cues in a Fitts's Law Task" IEEE Transactions on Haptics , v.17 , 2024 https://doi.org/10.1109/TOH.2024.3358188 Citation Details
(Showing: 1 - 10 of 18)

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