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Wrist and Arm Body Surface Bipolar ECG Leads Signal and Sensor Study for Long-term Rhythm Monitoring

Escalona, OJ, McFrederick, L, Borges, M, Linares, P, Villegas, R, Perpiñan, GI, McLaughlin, JAD and McEneaney, DJ (2017) Wrist and Arm Body Surface Bipolar ECG Leads Signal and Sensor Study for Long-term Rhythm Monitoring. In: 44th Computing in Cardiology Conference, 2017, Rennes, France, Rennes, France. Computing in Cardiology, 2017. Vol 44 4 pp. [Conference contribution]

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URL: http://www.cinc.org

DOI: 10.22489/CinC.2016.301-506

Abstract

With cardiovascular disease and heart arrhythmias continuing to have a high mortality rate, it is important to monitor the electrocardiogram (ECG) signal in a noninvasive, long-term wearable device. In this study we investigate sensors and the ECG signal-to-noise ratio map along the left arm, for wearable arm-ECG monitoring devices. In a pilot study, 11 subjects attending a cardiology outpatient clinic, far-field left-arm ECG recordings included signals from a combination of dry and special pre-gelled BIS-QuatroTM sensor system, axially and transversally oriented along the left arm: on the wrist, upper forearm and upper arm. A total of 10 bipolar leads were recorded simultaneously (using 18 acquisition channels). Each subject was recorded for 8 minutes at rest, using the bio-potential acquisition system; all data was imported and processed using Matlab and MS Excel. Analysis was completed to evaluate signal-to-noise ratio (SNR) distribution maps. An average ECG SNR figure of 42.63 was found in the dry-electrode positioned on the upper arm bipolar lead, whilst the SNR ratio positioned on the wrist was 13.14. Similar to this, in the BIS-electrodes (gelled), there was an average ECG SNR figure of 89.25 on the upper arm and of 5.18 positioned on the wrist. This study clinically evidenced the ECG S/N map on the left arm. It reveals that bipolar arm-ECG SNR are consistently stronger on the upper arm, when recorded with the gelled BIS sensors.

Item Type:Conference contribution (Paper)
Keywords:Bipolar ECG leads, long term monitoring, BIS sensors, AgCl dry electrodes, Signal-to-Noise ratio, SNR, far-field EGM, bi-polar leads, denoising, signal averaging, SFP alignment technique.
Faculties and Schools:Faculty of Computing & Engineering
Faculty of Computing & Engineering > School of Engineering
Research Institutes and Groups:Engineering Research Institute
Engineering Research Institute > Nanotechnology & Integrated BioEngineering Centre (NIBEC)
ID Code:39010
Deposited By: Professor Omar Escalona
Deposited On:24 Apr 2018 07:40
Last Modified:24 Apr 2018 07:40

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