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Minimally Invasive Surgery (MIS) is a surgical technique involving small incisions performed by an endoscope and several long, thin instruments. MIS minimizes complications and speeds up recovery time compared to the traditional surgery. Unfortunately, from a surgeon s perspective, MIS is much more challenging than conventional open surgery because of the limited vision and sensing feedbacks. In the last decade, we have witnessed dramatic increases in performance of computerized assisted system, achieved through increasing computational capabilities and advances in sensor designs. The…mehr

Produktbeschreibung
Minimally Invasive Surgery (MIS) is a surgical
technique involving small incisions performed by an
endoscope and several long, thin instruments. MIS
minimizes complications and speeds up recovery time
compared to the traditional surgery. Unfortunately,
from a surgeon s perspective, MIS is much more
challenging than conventional open surgery because of
the limited vision and sensing feedbacks.
In the last decade, we have witnessed dramatic
increases in performance of computerized assisted
system, achieved through increasing computational
capabilities and advances in sensor designs. The
objective of this research is to design and realize a
novel prototype that advances the state of the art in
surgical training, assessment, and guidance for MIS.
The proposed Situational Awareness Enhancing System
(SAES) uses a unified framework incorporating
perception, comprehension, and projection software
modules that provide feedback during the exercises
and enable evaluation of the training procedure. The
low cost solution would permit our system to not only
measure a trainee s progress in acquiring psychomotor
skills, but also to evaluate instrument effectiveness
in reducing error.
Autorenporträt
Chuan Feng got his Ph.D. in Electrical and Computer Engineering
in 2007, from the University of Arizona. He also holds a MS
degree in Computer Science and a BS degree in Electrical
Engineering from Tsinghua University, China. His research
interests are in the area of biomedical engineering, human
computer interface, and model based systems design.