4.6 Article

Arm-ECG Wireless Sensor System for Wearable Long-Term Surveillance of Heart Arrhythmias

Journal

ELECTRONICS
Volume 8, Issue 11, Pages -

Publisher

MDPI
DOI: 10.3390/electronics8111300

Keywords

bipolar cardiac electrograms; arm-ECG monitoring; wearable sensor systems; ECG dry electrodes; Wi-Fi connectivity; heart arrhythmic events detection

Funding

  1. European Union (EU): H2020-MSCA-RISE Programme (WASTCArD Project) [645759]
  2. Ulster Garden Villages Ltd.
  3. McGrath Trust (UK)
  4. Marie Curie Actions (MSCA) [645759] Funding Source: Marie Curie Actions (MSCA)

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This article presents the devising, development, prototyping and assessment of a wearable arm-ECG sensor system (WAMECG1) for long-term non-invasive heart rhythm monitoring, and functionalities for acquiring, storing, visualizing and transmitting high-quality far-field electrocardiographic signals. The system integrates the main building blocks present in a typical ECG monitoring device such as the skin surface electrodes, front-end amplifiers, analog and digital signal conditioning filters, flash memory and wireless communication capability. These are integrated into a comfortable, easy to wear, and ergonomically designed arm-band ECG sensor system which can acquire a bipolar ECG signal from the upper arm of the user over a period of 72 h. The small-amplitude bipolar arm-ECG signal is sensed by a reusable, long-lasting, Ag-AgCl based dry electrode pair, then digitized using a programmable sampling rate in the range of 125 to 500 Hz and transmitted via Wi-Fi. The prototype comparative performance assessment results showed a cross-correlation value of 99.7% and an error of less than 0.75% when compared to a reference high-resolution medical-grade ECG system. Also, the quality of the recorded far-field bipolar arm-ECG signal was validated in a pilot trial with volunteer subjects from within the research team, by wearing the prototype device while: (a) resting in a chair; and (b) doing minor physical activities. The R-peak detection average sensibilities were 99.66% and 94.64%, while the positive predictive values achieved 99.1% and 92.68%, respectively. Without using any additional algorithm for signal enhancement, the average signal-to-noise ratio (SNR) values were 21.71 and 18.25 for physical activity conditions (a) and (b) respectively. Therefore, the performance assessment results suggest that the wearable arm-band prototype device is a suitable, self-contained, unobtrusive platform for comfortable cardiac electrical activity and heart rhythm logging and monitoring.

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