TY - GEN
T1 - Meaningful assessment of surgical expertise
T2 - 1st International Workshop on Simulation and Synthesis in Medical Imaging, SASHIMI 2016 held in conjunction with 19th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2016
AU - Ershad, Marzieh
AU - Koesters, Zachary
AU - Rege, Robert V
AU - Majewicz, Ann
N1 - Funding Information:
This work was supported by the Intuitive Surgical Simulator loan program for the Southwestern Center for Minimally Invasive Surgery at UTSW (PI Rege). We thank Deborah Hogg and Lauren Scott for providing access to the simulator.
Publisher Copyright:
© Springer International Publishing AG 2016.
PY - 2016
Y1 - 2016
N2 - Many surgical assessment metrics have been developed to identify and rank surgical expertise; however,some of these metrics (e.g.,economy of motion) can be difficult to understand and do not coach the user on how to modify behavior. We aim to standardize assessment language by identifying key semantic labels for expertise. We chose six pairs of contrasting adjectives and associated a metric with each pair (e.g.,fluid/viscous correlated to variability in angular velocity). In a user study,we measured quantitative data (e.g.,limb accelerations,skin conductivity,and muscle activity),for subjects (n=3,novice to expert) performing tasks on a robotic surgical simulator. Task and posture videos were recorded for each repetition and crowd-workers labeled the videos by selecting one word from each pair. The expert was assigned more positive words and also had better quantitative metrics for the majority of the chosen word pairs,showing feasibility for automated coaching.
AB - Many surgical assessment metrics have been developed to identify and rank surgical expertise; however,some of these metrics (e.g.,economy of motion) can be difficult to understand and do not coach the user on how to modify behavior. We aim to standardize assessment language by identifying key semantic labels for expertise. We chose six pairs of contrasting adjectives and associated a metric with each pair (e.g.,fluid/viscous correlated to variability in angular velocity). In a user study,we measured quantitative data (e.g.,limb accelerations,skin conductivity,and muscle activity),for subjects (n=3,novice to expert) performing tasks on a robotic surgical simulator. Task and posture videos were recorded for each repetition and crowd-workers labeled the videos by selecting one word from each pair. The expert was assigned more positive words and also had better quantitative metrics for the majority of the chosen word pairs,showing feasibility for automated coaching.
KW - Crowdsourced assessment
KW - Semantic descriptors
KW - Surgical training and evaluation
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U2 - 10.1007/978-3-319-46720-7_59
DO - 10.1007/978-3-319-46720-7_59
M3 - Conference contribution
AN - SCOPUS:84996564762
SN - 9783319467191
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 508
EP - 515
BT - Medical Image Computing and Computer-Assisted Intervention - MICCAI 2016 - 19th International Conference, Proceedings
A2 - Ourselin, Sebastian
A2 - Joskowicz, Leo
A2 - Sabuncu, Mert R.
A2 - Wells, William
A2 - Unal, Gozde
PB - Springer Verlag
Y2 - 21 October 2016 through 21 October 2016
ER -