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Eye Tracking in the Assessment of Electrocardiogram Interpretation Techniques

Bond, Raymond R., Finlay, Dewar D., Breen, Cathal, J, Boyd, Kyle, Nugent, Chris D, Black, Norman, Mcfarlane, Peter and Guldenring, Daniel (2012) Eye Tracking in the Assessment of Electrocardiogram Interpretation Techniques. In: International Conference of Computers in Cardiology, China. IEEE. 4 pp. [Conference contribution]

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URL: http://www.cinc.org/archives/2012/pdf/0581.pdf


Introduction: Human observers with varying degrees of expertise interpret the 12-lead Electrocardiogram (ECG) in different ways. Students adopt a strict protocol, whereas experts can identify abnormalities immediately. We investigate the use of eye tracking technology as a means of gaining insight into how a human observer interprets ECGs.Methods: A clinical scientist interpreted 29 ECGs (10 Acute Myocardial Infarction [AMI], 10 Ventricular Hypertrophy [VH] and 9 Left Bundle Branch Block [LBBB]), whilst an eye tracking device was used to record eye movement patterns. Results: The mean time for interpreting an ECG was 39.56 seconds (SD=11.56). No statistical significance was found between the duration of interpreting ECGs with different abnormalities - AMI ( =39.36, SD=13.49), VH ( =41.56, SD=9.67) and LBBB ( =37.56, SD=12.84). The time dedicated to looking at each lead across all 29 ECGs was determined. The subject fixated most on the rhythm strip (162 sec), followed by lead V1 (85 sec), V2 (71 sec), V6 (52 sec), V3 (50 sec), V5 (50 sec), II (37 sec), V4 (31 sec), I (26 sec), aVF (24 sec), aVL (21 sec), III (12 sec), and aVR (7 sec). Lead aVR was the least studied lead (t-test: p-value < 0.01). More time was given to studying the precordial leads compared to the limb leads (t-test: p-value=0.002). From visual analysis of the recorded data, it was possible to identify that the observer did use a systematic approach to interpretation. For e.g., in the majority of cases the rhythm strip was initially studied, even when prominent features such as ST segment elevation were present in a number of other leads.Conclusion: Eye tracking can be used to gain insight into how observers interpret the ECG. This could be used for training purposes to provide tailored and objective feedback on an individual’s ECG interpretation technique.

Item Type:Conference contribution (Paper)
Faculties and Schools:Faculty of Computing & Engineering
Faculty of Computing & Engineering > School of Computing and Mathematics
Faculty of Life and Health Sciences
Faculty of Life and Health Sciences > School of Health Sciences
Research Institutes and Groups:Computer Science Research Institute > Smart Environments
Computer Science Research Institute
ID Code:24561
Deposited By: Dr Raymond Bond
Deposited On:30 Jan 2013 11:35
Last Modified:23 Nov 2015 15:30

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