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Methods Inf Med 2016; 55(03): 258-265
DOI: 10.3414/ME15-01-0120
Original Articles
Schattauer GmbH

Data Driven Computer Simulation to Analyse an ECG Limb Lead System Used in Connected Health Environments[*]

Raymond Bond
1   University of Ulster, School of Computing and Mathematics, Newtownabbey, Antrim, UK
,
Dewar D. Finlay
2   University of Ulster, Engineering, Newtownabbey, Antrim, UK
,
Daniel Guldenring
2   University of Ulster, Engineering, Newtownabbey, Antrim, UK
,
Cathal Breen
3   University of Ulster, Health Science, Newtownabbey, Antrim, UK
› Author Affiliations
Further Information

Publication History

received: 09 September 2015

accepted in revised form 10 February 2016

Publication Date:
08 January 2018 (online)

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Summary

Background: Recently under the Connected Health initiative, researchers and small-medium engineering companies have developed Electrocardiogram (ECG) monitoring devices that incorporate non-standard limb electrode positions, which we have named the Central Einthoven (CE) configuration.

Objectives: The main objective of this study is to compare ECG signals recorded from the CE configuration with those recorded from the recommended Mason-Likar (ML) configuration.

Methods: This study involved extracting two different sets of ECG limb leads from each patient to compare the difference in the signals. This was done using computer simulation that is driven by body surface potential maps. This simulator was developed to facilitate this experiment but it can also be used to test similar hypotheses. This study included, (a) 176 ECGs derived using the ML electrode positions and (b) the 176 corresponding ECGs derived using the CE electrode positions. The signals from these ECGs were compared using root mean square error (RMSE), Pearson product-moment correlation coefficient (r) and similarity coefficient (SC). We also investigated whether the CE configuration influences the calculated mean cardiac axis. The top 10 cases where the ECGs were significantly different between the two configurations were visually compared by an ECG interpreter.

Results: We found that the leads aVL, III and aVF are most affected when using the CE configuration. The absolute mean difference between the QRS axes from both configurations was 28° (SD = 37°). In addition, we found that in 82% of the QRS axes calculated from the CE configuration was more rightward in comparison to the QRS axes derived from the ML configuration. Also, we found that there is an 18% chance that a misleading axis will be located in the inferior right quadrant when using the CE approach. Thus, the CE configuration can emulate right axis deviation. The clinician visually identified 6 out of 10 cases where the CE based ECG yielded clinical differences that could result in false positives.

Conclusions: The CE configuration will not yield the same diagnostic accuracy for diagnosing pathologies that rely on current amplitude criteria. Conversely, rhythm lead II was not significantly affected, which supports the use of the CE approach for assessing cardiac rhythm only. Any computerised analysis of the CE based ECG will need to take these findings into consideration.

Keywords

Electrocardiogram - computer simulation - limb lead systems - connected health - tele-health - electrode misplacement

* Supplementary material published on our web-site http://dx.doi.org/10.3414/ME15-01-0120


 

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