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Zakeri, Z. 
ORCID: 0000-0003-2588-8360, Mansfield, N. ORCID: 0000-0001-6769-1721, Sunderland, C. ORCID: 0000-0001-7484-1345 and Omurtag, A. ORCID: 0000-0002-3773-8506,
2020.
Physiological correlates of cognitive load in laparoscopic surgery.
Scientific Reports, 10: 12927.
ISSN 2045-2322
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1345080_a826_Zakeri.pdf - Published version Download (1MB) | Preview |
Abstract
Laparoscopic surgery can be exhausting and frustrating, and the cognitive load experienced by surgeons may have a major impact on patient safety as well as healthcare economics. As cognitive load decreases with increasing proficiency, its robust assessment through physiological data can help to develop more effective training and certification procedures in this area. We measured data from 31 novices during laparoscopic exercises to extract features based on cardiac and ocular variables. These were compared with traditional behavioural and subjective measures in a dual-task setting. We found significant correlations between the features and the traditional measures. The subjective task difficulty, reaction time, and completion time were well predicted by the physiology features. Reaction times to randomly timed auditory stimuli were correlated with the mean of the heart rate (0.29 r =−) and heart rate variability (0.4 r =). Completion times were correlated with the physiologically predicted values with a correlation coefficient of 0.84. We found that the multi-modal set of physiology features was a better predictor than any individual feature and artificial neural networks performed better than linear regression. The physiological correlates studied in this paper, translated into technological products, could help develop standardised and more easily regulated frameworks for training and certification.
| Item Type: | Journal article | ||||
|---|---|---|---|---|---|
| Publication Title: | Scientific Reports | ||||
| Creators: | Zakeri, Z., Mansfield, N., Sunderland, C. and Omurtag, A. | ||||
| Publisher: | Springer Nature | ||||
| Date: | 2020 | ||||
| Volume: | 10 | ||||
| ISSN: | 2045-2322 | ||||
| Identifiers: |
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| Rights: | © The Author(s) 2020. Open Access. This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/. | ||||
| Divisions: | Schools > School of Science and Technology | ||||
| Record created by: | Linda Sullivan | ||||
| Date Added: | 17 Jul 2020 15:56 | ||||
| Last Modified: | 31 May 2021 15:17 | ||||
| URI: | https://irep.ntu.ac.uk/id/eprint/40249 |
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