@inproceedings{8b9fae285079401c8472eeab2c8ab4ad,
title = "Wrist and Arm Body Surface Bipolar ECG Leads Signal and Sensor Study for Long-term Rhythm Monitoring",
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.",
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.",
author = "OJ Escalona and L McFrederick and M Borges and P Linares and R Villegas and GI Perpi{\~n}an and JAD McLaughlin and DJ McEneaney",
year = "2017",
month = oct,
day = "9",
language = "English",
volume = "44",
editor = "Alan Murray",
booktitle = "Unknown Host Publication",
publisher = "Computing in Cardiology",
note = "44th Computing in Cardiology Conference, 2017, Rennes, France ; Conference date: 09-10-2017",
}