TY - GEN
T1 - Motion analysis as an evaluation framework for eye-hand coordination
T2 - ASME 2014 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference, IDETC/CIE 2014
AU - Kim, Inki
AU - Miller, Scarlett R.
AU - Freivalds, Andris
N1 - Publisher Copyright:
Copyright © 2014 by ASME.
PY - 2014
Y1 - 2014
N2 - Helping resident surgeons quickly and accurately develop expertise in clinical skills is crucial for improving patient safety and care. Because most surgical skills require visually aided device manipulations, developing effective eye-hand coordination is a crucial component of most surgical training. While eye-hand coordination has typically been evaluated on the basis of time to complete a task and number of errors, growing evidence suggests that task performance can be distinguished by detecting eye gaze patterns and movement planning. However, few studies have explored methods for collecting and evaluating gaze patterns without significantly impeding the user (e.g. goggle eye trackers), reducing the utility of this approach. Therefore, the current study was developed to propose and test a framework for evaluating the quality of eye-hand coordination using a novel motion analysis technique. To validate the framework, three expert and three novice resident surgeons were video-taped during ultrasoundguided central-venous catheter insertion procedures and compared. Our method was able to show that experts demonstrate distinguished patterns in adjusted accuracy, movement trajectories and time allocation. The results also showed that expert performance in eye-hand coordination appears to be characterized by goal-oriented adjustment. This research framework can be used to characterize individual differences and improve surgical residence training and can also be applied in other domains where eye-hand coordination needs to be studied without impeding user performance.
AB - Helping resident surgeons quickly and accurately develop expertise in clinical skills is crucial for improving patient safety and care. Because most surgical skills require visually aided device manipulations, developing effective eye-hand coordination is a crucial component of most surgical training. While eye-hand coordination has typically been evaluated on the basis of time to complete a task and number of errors, growing evidence suggests that task performance can be distinguished by detecting eye gaze patterns and movement planning. However, few studies have explored methods for collecting and evaluating gaze patterns without significantly impeding the user (e.g. goggle eye trackers), reducing the utility of this approach. Therefore, the current study was developed to propose and test a framework for evaluating the quality of eye-hand coordination using a novel motion analysis technique. To validate the framework, three expert and three novice resident surgeons were video-taped during ultrasoundguided central-venous catheter insertion procedures and compared. Our method was able to show that experts demonstrate distinguished patterns in adjusted accuracy, movement trajectories and time allocation. The results also showed that expert performance in eye-hand coordination appears to be characterized by goal-oriented adjustment. This research framework can be used to characterize individual differences and improve surgical residence training and can also be applied in other domains where eye-hand coordination needs to be studied without impeding user performance.
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U2 - 10.1115/DETC201434575
DO - 10.1115/DETC201434575
M3 - Conference contribution
AN - SCOPUS:84926030697
T3 - Proceedings of the ASME Design Engineering Technical Conference
BT - 34th Computers and Information in Engineering Conference
PB - American Society of Mechanical Engineers (ASME)
Y2 - 17 August 2014 through 20 August 2014
ER -