Literature DB >> 22350712

Eye-tracking analysis of skilled performance in clinical extracorporeal circulation.

Yasuko Tomizawa1, Hirotaka Aoki, Satoshi Suzuki, Toru Matayoshi, Ryohei Yozu.   

Abstract

The manipulation of extracorporeal circulation (ECC), which is performed by perfusionists during cardiovascular surgery, is a highly sophisticated cognitive process based on visual information obtained from information sources such as ECC indicators, surgeons, an operating field, a scrub nurse, surgical instruments, displays, patients, among others. An eye-tracking approach is expected to be a powerful means of automatic and rapid analysis. This paper presents the results of a pilot study in which an eye-tracking approach was applied to the analysis of ECC operation tasks conducted during real clinical cardiovascular surgery in the operating room. Eye-tracking data on four perfusionists were recorded while they were manipulating the ECC during a series of cardiovascular surgeries. The experience of the perfusionists ranged from 2 to 26+ years. Based on the data obtained, fixation-by-fixation cataloging of eye-tracking data in which each fixation was transcribed in timeline style was performed for each perfusionist. Gaze allocation tendencies during the surgeries for all four perfusionists were determined through a comparative analysis. It was noted that an expert engineer dispersed his attention more widely than did intermediate and novice perfusionists. Taking the results of the data analysis into consideration, we discuss the implications of well-skilled perfusionists' performance during the manipulation of ECC, as well as the principles that guide how eye-tracking data obtained in real surgery should be processed. This is the first study on the application of an eye-tracking approach to the analysis of ECC operation tasks to be reported in the Japanese literature.

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Year:  2012        PMID: 22350712     DOI: 10.1007/s10047-012-0630-z

Source DB:  PubMed          Journal:  J Artif Organs        ISSN: 1434-7229            Impact factor:   1.731


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