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
