Armband sensors location assessment for left Arm-ECG bipolar leads waveform components discovery tendencies around the MUAC line

OJ Escalona, Sephorah Mukhtar, David McEneaney, Dewar Finlay

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Abstract

Sudden cardiac death (SCD) risk can be reduced by early detection of short-lived and transient cardiac arrhythmias using long-term electrocardiographic (ECG) monitoring. Early detection of ventricular arrhythmias can reduce the risk of SCD by allowing appropriate interventions. Long-term continuous ECG monitoring, using a non-invasive armband-based wearable device is an appealing solution for detecting early heart rhythm abnormalities. However, there is a paucity of understanding on the number and best bipolar ECG electrode pairs axial orientation around the left mid-upper arm circumference (MUAC) for such devices. This study addresses the question on the best axial orientation of ECG bipolar electrode pairs around the left MUAC in non-invasive armband-based wearable devices, for the early detection of heart rhythm abnormalities. A total of 18 subjects with almost same BMI values in the WASTCArD arm-ECG database were selected to assess arm-ECG bipolar leads quality using proposed metrics of relative (normalized) signal strength measurement, arm-ECG detection performance of the main ECG waveform event component (QRS) and heart-rate variability (HRV) in six derived bipolar arm ECG-lead sensor pairs around the armband circumference, having regularly spaced axis angles (at 30° steps) orientation. The analysis revealed that the angular range from −30° to +30°of arm-lead sensors pair axis orientation around the arm, including the 0° axis (which is co-planar to chest plane), provided the best orientation on the arm for reasonably good QRS detection; presenting the highest sensitivity (Se) median value of 93.3%, precision PPV median value at 99.6%; HRV RMS correlation (p) of 0.97 and coefficient of determination (R2) of 0.95 with HRV gold standard values measured in the standard Lead-I ECG.
Original languageEnglish
Article number7240
Number of pages22
JournalSensors (Switzerland)
Volume22
Issue number19
Early online date24 Sep 2022
DOIs
Publication statusPublished online - 24 Sep 2022

Bibliographical note

Funding Information:
This research was supported by funding from the European Union (EU): H2020-MSCA-RISE Programme (WASTCArD Project, Grant #645759). Professor Omar Escalona’s dedication to WASTCArD database building was supported by philanthropic funds: the Ulster Garden Villages Ltd. and the McGrath Trust.

Publisher Copyright:
© 2022 by the authors.

Keywords

  • bipolar cardiac electrograms
  • arm-ECG monitoring
  • wearable sensor systems
  • signal averaged ECG
  • QRS detection performance
  • bipolar arm-ECG P-wave vectors
  • MUAC
  • BMI

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