TY - JOUR
T1 - Rate of Orientation Change as a New Metric for Robot-Assisted and Open Surgical Skill Evaluation
AU - Sharon, Yarden
AU - Jarc, Anthony M.
AU - Lendvay, Thomas S.
AU - Nisky, Ilana
N1 - Funding Information: This work was supported in part by the Helmsley Charitable Trust through the ABC Robotics Initiative and by the Marcus Endowment Fund both at Ben-Gurion University of the Negev, the ISF under Grant 327/20; in part by the Israeli Ministry of Science and Technology under Grant 15627-3; and in part by a Grant for the Israel Italy Virtual Lab on Artificial Somatosensation for Humans and Humanoids. The work of Yarden Sharon was supported in part by the Besor Scholarship and in part by the Israeli Planning and Budgeting Committee Scholarship. Publisher Copyright: © 2018 IEEE.
PY - 2021/5/1
Y1 - 2021/5/1
N2 - Surgeons' technical skill directly impacts patient outcomes. To date, the angular motion of the instruments has been largely overlooked in objective skill evaluation. To fill this gap, we have developed metrics for surgical skill evaluation that are based on the orientation of surgical instruments. We tested our new metrics on two datasets with different conditions: (1) a dataset of experienced robotic surgeons and nonmedical users performing needle-driving on a dry lab model, and (2) a small dataset of suturing movements performed by surgeons training on a porcine model. We evaluated the performance of our new metrics (angular displacement and the rate of orientation change) alongside the performances of classical metrics (task time and path length). We calculated each metric on different segments of the movement. Our results highlighted the importance of segmentation rather than calculating the metrics on the entire movement. Our new metric, the rate of orientation change, showed statistically significant differences between experienced surgeons and nonmedical users / novice surgeons, which were consistent with the classical task time metric. The rate of orientation change captures technical aspects that are taught during surgeons' training, and together with classical metrics can lead to a more comprehensive discrimination of skills.
AB - Surgeons' technical skill directly impacts patient outcomes. To date, the angular motion of the instruments has been largely overlooked in objective skill evaluation. To fill this gap, we have developed metrics for surgical skill evaluation that are based on the orientation of surgical instruments. We tested our new metrics on two datasets with different conditions: (1) a dataset of experienced robotic surgeons and nonmedical users performing needle-driving on a dry lab model, and (2) a small dataset of suturing movements performed by surgeons training on a porcine model. We evaluated the performance of our new metrics (angular displacement and the rate of orientation change) alongside the performances of classical metrics (task time and path length). We calculated each metric on different segments of the movement. Our results highlighted the importance of segmentation rather than calculating the metrics on the entire movement. Our new metric, the rate of orientation change, showed statistically significant differences between experienced surgeons and nonmedical users / novice surgeons, which were consistent with the classical task time metric. The rate of orientation change captures technical aspects that are taught during surgeons' training, and together with classical metrics can lead to a more comprehensive discrimination of skills.
KW - Medical robotics
KW - human motion analysis
KW - physical human-robot interaction
KW - surgical robotics
KW - surgical skill evaluation
UR - http://www.scopus.com/inward/record.url?scp=85108792430&partnerID=8YFLogxK
U2 - https://doi.org/10.1109/TMRB.2021.3073209
DO - https://doi.org/10.1109/TMRB.2021.3073209
M3 - Article
SN - 2576-3202
VL - 3
SP - 414
EP - 425
JO - IEEE Transactions on Medical Robotics and Bionics
JF - IEEE Transactions on Medical Robotics and Bionics
IS - 2
M1 - 9404322
ER -