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A hidden markov model-based analysis framework using eye-tracking data to characterise re-orientation strategies in minimally invasive surgery

Content Provider	Springer Nature Link
Author	Sodergren, Mikael Hans Orihuela Espina, Felipe Clark, James Darzi, Ara Yang, Guang Zhong
Copyright Year	2009
Abstract	Natural Orifice Translumenal Endoscopic Surgery (NOTES) represents a new paradigm in minimally invasive surgery whereby an operator uses a flexible instrument to navigate within an anatomical space. The flexible instrument is introduced via a natural body orifice such as the mouth to perform an operative intervention controlled by the surgeon without making incisions in the anterior abdominal wall. It differs from laparoscopic (traditional keyhole) surgery in two main ways: (1) the instruments used in NOTES are not rigid as in laparoscopic surgery and not specifically designed for this application; and (2) there are no incisions in the anterior abdominal wall. Disorientation during NOTES is a significant problem because as in laparoscopic surgery the operator typically uses a 2D camera-monitor interface for visualisation by the camera at the site of the operation. Furthermore, the positional cue offered by the external component (outside the body) of the camera is absent, and camera navigation is more cumbersome. When the operator is disorientated, it is important to be able to re-orientate quickly to minimise potential surgical errors. It is hypothesised that when surgeons become disorientated, there exist discrete patterns in psychophysical behaviour which are associated with effective re-orientation, and that these patterns are recognisable. In this study, we examine visual re-orientation behaviour in 18 subjects using eye-tracker data in a model comprised of selective image manipulation of everyday objects in a box trainer. We characterise effective behaviour using a fixation sequence similarity-based hidden Markov model. We show that the output of this algorithm is reliable in differentiating visual behavioural sequences, and that there are specific behavioural patterns and strategies associated with successful re-orientation in this model. Good re-orientation strategy appears to rely on identification and focus on a central object within the scene and judging position of its surrounding peripheral objects, suggesting integration of both geometric and feature information in a systematic way. Using selective, inconsistent feature cues for re-orientation were associated with less effective performance.
Starting Page	275
Ending Page	283
Page Count	9
File Format	PDF
ISSN	16124782
Journal	Cognitive Processing
Volume Number	11
Issue Number	3
e-ISSN	16124790
Language	English
Publisher	Springer-Verlag
Publisher Date	2009-11-24
Publisher Place	Berlin, Heidelberg
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	Re-orientation Strategy Surgery Artificial Intelligence (incl. Robotics) Behavioural Sciences Neurosciences
Content Type	Text
Resource Type	Article
Subject	Experimental and Cognitive Psychology Artificial Intelligence Cognitive Neuroscience Medicine

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