Research and simulators development at ISIS is part of a collaborated effort between ISIS expert group, the Biorobotics Lab (BRL), and the Human Interface Technology lab (HIT Lab) at the University Of Washington

Research Projects:
Disclosure of Simulated Adverse Events in Obstetrics
PIs: Thomas Benedetti, Carolyn Prouty, Tom Gallagher, Leslie Carranza, Sara Kim, Karen Souter, Sarah Waller – STATUS: Pending
Face and Content Validity of a Mannequin Simulator for Suprapubic Catheter Placement
PI: Thomas Lendvay
Feasibility of Web-based Assessment of Physicians’ Communication Skills: A Pilot Study
PIs: Sara Kim, Tom Gallagher, Doug Brock, Carolyn Prouty, Odawni Palmer, Alan Gojdics, Eric Holmboe, Brian Hess, Kate Ross, Rebecca Lipner
High-Definition Video-endoscopy: An Assessment of Image Characteristics and Validated Laparoscopic Skills Curriculum Performance
PIs: Michael Wu, Paul Doetsch
ISIS Educational Database
PI: Brian Ross
Skills Acquisition in Single Incision Laparoscopic Surgery (SILS)
PIs: Andrew Wright, Carlos Pellegrini, Renato Soares, Saurabh Khandelwal, Brant Oelschlager, Roger Tatum
Survey for Medical Student Skills Curriculum
PIs: Brian Ross, Sara Kim, Julia Metzner
Survey for Resident interest in Global Health Rotations
PI: Ryan Jense
Transfer of Simulation Based Skills to Patients
PIs: Julia Metzner, Brian Ross, Stefan Lombaard, Todd Cannon, Karen Souter, Sally Barlow, Alec Rooke, Chris Kent, Krishna Natrajan
Validation Assessment metrics for Basic Surgical Skills
PIs: Andrew Wright, Sara Kim, Karen Horvath, Lisa McIntyre, Kristine Calhoun, Aaron Jensen, Samuel Park
Validation Study of Simpraxis Laparoscopic Cholecystectomy Surgical Trainer
PIs: Mika Sinanan, Brian Ross, Andrew Wright, Sara Kim
Virtual Reality Warm-Up for Robotic Surgery Skills Training
PIs: Thomas Lendvay, Rick Satava, Monika Kasina, Timothy Brand
Objective Assessment of Minimally Invasive Surgical Skill
Evaluation of the Raven Surgical Robotic System in Teleoperation
Objective Assessment of Pelvic Exam - E-Pelvis


See also
Research Simulators

Objective Assessment of Minimally Invasive Surgical Skill

Minimally invasive surgery (MIS) involves a multidimensional series of tasks requiring a synthesis between visual information and the kinematics and dynamics of the surgical tools. Analysis of these sources of information is a key step in defining objective criteria for characterizing surgical performance. The Blue and the Red DRAGONs are new systems for acquiring the kinematics and the dynamics of two endoscopic tools synchronized with the endoscopic view of the surgical scene. Modeling the process of MIS using a finite state model (Markov model - MM) reveals the internal structure of the surgical task and is utilized as one of the key steps in objectively assessing surgical performance. The experimental protocol includes 3 subtasks of the FLS. An objective learning curve was defined based on measuring quantitative statistical distance (similarity) between MM of experts and MM of residents at different levels of training. The objective learning curve was similar to that of the subjective performance analysis. The MM proved to be a powerful and compact mathematical model for decomposing a complex task such as laparoscopic suturing. Systems like surgical robots or virtual reality simulators in which the kinematics and the dynamics of the surgical tool are inherently measured may benefit from incorporation of the proposed methodology.

Additional Info - Red DRAGON
Developer - Biorobotics Lab (BRL)
Device: Red DRAGON (Two instrumented tools)
Methodology: Physical Model, FLS, Markov Model
Number of Subjects: 30 Human Subjects
Model: Markov model - 28 states
Status: Active Study
Publications:

Rosen J., J. D. Brown, L. Chang, M. Sinanan B. Hannaford, Generalized Approach for Modeling Minimally Invasive Surgery as a Stochastic Process Using a Discrete Markov Model, IEEE Transactions on Biomedical Engineering Vol. 53, No. 3, March 2006, pp. 399 - 413 PDF - ISIS_JP1

Evaluation of the Raven Surgical Robotic System in Teleoperation

Raven is Surgical Robot System for Open and Minimally Invasive Surgery - The surgical robotic system includes two portable surgical robotic arms (7 Degrees of Freedom each) and is capable of teleported from a distance via Internet (wired & wireless). The system can be deployed in a hospital operating room setup as well as an operating room in harsh environment (e.g. desert).The performance of the system is currently evaluated in a teleoperation mode.

Additional Info - Raven
Developer - Biorobotics Lab (BRL)
Device: Raven - Surgical Robot
Methodology: Physical Models & Animal Models (Pigs)
Number of Subjects: 5 Human Subjects
Model: Kinematics& Dynamics
Status: Active Study
Publications:

M.J.H. Lum, J. Rosen, M. N. Sinanan, B. Hannaford, Optimization of Spherical Mechanism for a Minimally Invasive Surgical Robot: Theoretical and Experimental Approaches, IEEE Transactions on Biomedical Engineering Vol. 53, No. 7, pp. 1440-1445, July 2006 PDF - ISIS_JP2

Rosen J., B. Hannaford, Doc at a Distance, IEEE Spectrum, pp. 34-38, October, 2006 PDF - ISIS_JP3

Lum M. J. H., D. Warden, J. Rosen, M. N. Sinanan, and B. Hannaford. Hybrid analysis of a spherical mechanism for a minimally invasive surgical (MIS) robot - design concepts for multiple optimizations. Proceedings of Medicine Meets Virtual Reality, Long Beach, CA, USA, January 2006. PDF - ISIS_CP1

Objective Assessment of Pelvic Exam - E-Pelvis

Inherent difficulties evaluating clinical competence of physicians has led to the widespread use of subjective skill assessment techniques. Inspired by an analogy between spoken language and surgical procedure, a generalized methodology using Markov Models (MMs), independent of the modality under study, was developed. The methodology that was applied to an endoscopic experiment is modified and applied to data collected with the E-Pelvis physical simulator. The simulator incorporates five contact pressure sensors located in key anatomical landmarks. Two 32-state fully connected MMs are used, one for each skill level. Each state corresponds to a unique five dimensional signature of contact pressures. Statistical distances measured between models representing subjects with different skill levels are sensitive enough to provide an objective measure of medical skill level. The method was tested with 41 expert subjects and 41 novice subjects in addition to the 30 subjects used for training the MM. Of the 82 subjects, 76 (92%) were classified correctly. Unique state transitions as well as pressure magnitudes for corresponding states were found to be skill dependent. The ‘white box’ nature of the model provides insight into the examination process performed.

Additional Info -
Developer - Biorobotics Lab (BRL)
Device: E-Pelvis Database
Methodology: Data Mining - Markov Model
Number of Subjects: 200 Human Subjects
Model: Markov Model
Status: Active Study
Publications:

Mackel T., J. Rosen, C. Pugh, Data Mining of the E-pelvis Simulator Database A Quest for a Generalized Algorithm for Objectively Assessing Medical Skill Proceedings of Medicine Meets Virtual Reality, Long Beach, CA, USA, January 2006. PDF - ISIS_CP6