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A Virtual Coach to Enhance Surgical Training using Human-Centric Modeling and Adaptive Haptic Guidance

Award Number: R01EB030125
ORGANIZATION: NATIONAL INSTITUTE Of BIOMEDICAL IMAGING & BIOENGINEERING
OPDIV: NIH
AWARD CLASS: DISCRETIONARY
AWARD ACTIVITY TYPE: SCIENTIFIC/HEALTH RESEARCH (INCLUDES SURVEYS)

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PROJECT SUMMARY We aim to reduce surgical robotic errors by developing novel technology to coach experienced practitioners by using real-time data-driven predictive models of operator behavior, task difﬁculty, and expertise levels during complex surgical training tasks. This technology could increase the effectiveness of simulation-based training, particularly for practicing clinicians, as the predictive models will inform the design of adaptive and personalized feedback for the surgeon. Surgical training typically involves didactic learning, skills labs, and practice on live patients. Safety concerns asso- ciated with training on patients has led to signiﬁcant developments in simulation-based technology; however, existing simulators may lack the ability promote mastery of skills for practicing providers. Improved training is important for both the provider and the patient. An estimated 100,000 death per year occur due to preventable medical errors. In robotic surgeries, the majority of patient injuries can be attributed to inexperience and lack of technical competence of the attending surgeon. These errors could potentially be avoided through personalized and adaptive coaching. In general, robotic systems can sense and adapt to their environment, even act autonomously to complete a task. However, the majority of surgical robots used today are “teleoperated systems". These systems only perform tasks directly commanded by the human operator, possibly with some scaling or tremor cancellation. There is a missed opportunity to leverage the intelligence of robotic systems to sense and interpret the movements of the surgeon and to enable some form of adaptive feedback for personalized coaching. Our prior work in human-centric modeling could hold the key to the technical challenge of integrating intelligent methods into existing surgical robotic training platforms by better understanding the technical strengths and weaknesses of the practicing surgeon in a data-driven manner. The long-term goal of this project is to improve surgical training outcomes by developing a personalized and adaptive surgical robotic coach capable of providing meaningful feedback to the practicing provider to optimize learning and skill transfer. The speciﬁc aims of the proposal include: (1) evaluate the ability of human- centric models to characterize surgeon performance using motion and video data, (2) design adaptive haptic or visual guidance cues to provide learners with real-time feedback and to optimize learning, and (3) evaluate the effectiveness of the adaptive technology coach through end-user validation using procedural-speciﬁc training models for general surgery, urology, and gynecologic oncology. This project could signiﬁcantly improve provider training in robotic surgery. The project could also improve provider training for laparoscopic and open surgery as the models used to develop the virtual coach are inherently human-centric and not tied to any speciﬁc surgical tasks or surgical platforms. Our team is uniquely positioned to achieve success in this project, bringing together experts in surgical robotics, human-centric modeling, machine learning, and advanced surgical training. We have conducted extensive preliminary studies in areas related to this proposal, supporting feasibility of this project. Our integration with the Simulation Center at UTSW will enable translation of successful outcomes of this project into the surgical training and retraining pipeline.


Issue Date FY	Funding FY	Legal Entity Name	Legal Entity Address	Legal Entity City	Legal Entity State	Legal Entity Zip Code	Legal Entity COUNTY	Legal Entity COUNTRY	Assistance Listing	Award Code	Budget Year	Action Date	Action Type	Action Amount

Issue Date FY: 2024 ( Subtotal = $0 )
2024	2023	UNIVERSITY OF TEXAS AT AUSTIN	110 INNER CAMPUS DR	AUSTIN	TX	78712	TRAVIS	USA	Discovery and Applied Research for Technological Innovations to Improve Human Health	000	4	12/5/2023	NON-COMPETING CONTINUATION	$0
														Subtotal = $0

Issue Date FY: 2023 ( Subtotal = $360,954 )
2023	2023	UNIVERSITY OF TEXAS AT AUSTIN	110 INNER CAMPUS DR	AUSTIN	TX	78712	TRAVIS	USA	Discovery and Applied Research for Technological Innovations to Improve Human Health	001	4	8/23/2023	NON-COMPETING CONTINUATION	$360,954
2023	2022	UNIVERSITY OF TEXAS AT AUSTIN	110 INNER CAMPUS DR	AUSTIN	TX	78712	TRAVIS	USA	Discovery and Applied Research for Technological Innovations to Improve Human Health	000	3	10/27/2022	NON-COMPETING CONTINUATION	$0
														Subtotal = $360,954

Issue Date FY: 2022 ( Subtotal = $360,869 )
2022	2022	UNIVERSITY OF TEXAS AT AUSTIN	110 INNER CAMPUS DR	AUSTIN	TX	78712	TRAVIS	USA	Discovery and Applied Research for Technological Innovations to Improve Human Health	001	3	9/20/2022	NON-COMPETING CONTINUATION	$360,869
2022	2021	UNIVERSITY OF TEXAS AT AUSTIN	110 INNER CAMPUS DR MN 13	AUSTIN	TX	78712	TRAVIS	USA	Discovery and Applied Research for Technological Innovations to Improve Human Health	000	2	11/3/2021	NON-COMPETING CONTINUATION	$0
														Subtotal = $360,869

Issue Date FY: 2021 ( Subtotal = $308,003 )
2021	2021	UNIVERSITY OF TEXAS AT AUSTIN	110 INNER CAMPUS DR MN 13	AUSTIN	TX	78712	TRAVIS	USA	Discovery and Applied Research for Technological Innovations to Improve Human Health	001	2	9/21/2021	NON-COMPETING CONTINUATION	$308,003
2021	2020	UNIVERSITY OF TEXAS AT AUSTIN	110 INNER CAMPUS DR MN 13	AUSTIN	TX	78712	TRAVIS	USA	Discovery and Applied Research for Technological Innovations to Improve Human Health	000	1	9/13/2021	NEW	$0
														Subtotal = $308,003

Issue Date FY: 2020 ( Subtotal = $327,275 )
2020	2020	UNIVERSITY OF TEXAS AT AUSTIN	110 INNER CAMPUS DR MN 13	AUSTIN	TX	78712	TRAVIS	USA	Discovery and Applied Research for Technological Innovations to Improve Human Health	000	1	9/17/2020	NEW	$327,275
														Subtotal = $327,275

Grand Total All Awards = $1,357,101

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A Virtual Coach to Enhance Surgical Training using Human-Centric Modeling and Adaptive Haptic Guidance

Award Number: R01EB030125

ORGANIZATION: NATIONAL INSTITUTE Of BIOMEDICAL IMAGING & BIOENGINEERING

OPDIV: NIH

AWARD CLASS: DISCRETIONARY

AWARD ACTIVITY TYPE: SCIENTIFIC/HEALTH RESEARCH (INCLUDES SURVEYS)

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