@inproceedings{83e1026c7be34a5d96960cb386cadad1,
title = "Wearable Technology: Signal Recovery of Electrocardiogram from Short Spaced Leads in the Far-Field Using Discrete Wavelet Transform Based Techniques",
abstract = "Bipolar ECG leads recorded from closely spaced electrodes are challenging in any context. When they are positioned distally with respect to the source field (far-field), the recovery of clinically useful signal content represents an even greater challenge. Due to the increased interest in ambulatory wellness devices, particularly wrist-worn devices, there is a renewed interest in recovering ECG signals from distally located bipolar leads.In this study 10 bipolar leads were simultaneously recorded at various locations along the left arm. At the same time, a conventional proximal reading on the chest using Lead I was also recorded and stored. This process was repeated for 11 healthy subjects. ECGs were recorded for a period of approximately 6 minutes for each subject and sampled at a frequency of 2048 Hz. Wavelet-based filtering using Daubechies 4 wavelet decomposition and soft threshold was applied to each lead. QRS detection performance was assessed against Lead I for each subject. This investigation found that a lead positioned transversally (using BIS gelled electrodes) on the upper arm provided the best accuracy against the benchmark QRS detection (SEN = 0.998, PPV = 0.984). The most distally positioned bipolar lead using dry electrodes faired least favourable (SEN = 0.272, PPV = 0.202).",
author = "Niamh McCallan and Dewar Finlay and Pardis Biglarbeigi and Gilberto Perpi{\~n}an and Michael Jennings and Ng, {Kok Yew} and James McLaughlin and Omar Escalona",
year = "2019",
month = sep,
doi = "10.22489/CinC.2019.313",
language = "English",
series = "Computing in Cardiology",
publisher = "IEEE Computer Society",
booktitle = "2019 Computing in Cardiology, CinC 2019",
address = "United States",
note = "2019 Computing in Cardiology, CinC 2019 ; Conference date: 08-09-2019 Through 11-09-2019",
}