AUTHOR=Abdou Abdelrahman , Krishnan Sridhar TITLE=Enhancement of single-lead dry-electrode ECG through wavelet denoising JOURNAL=Frontiers in Signal Processing VOLUME=Volume 4 - 2024 YEAR=2024 URL=https://www.frontiersin.org/journals/signal-processing/articles/10.3389/frsip.2024.1396077 DOI=10.3389/frsip.2024.1396077 ISSN=2673-8198 ABSTRACT=Neonatal electrocardiogram (ECG) monitoring is an important diagnostic tool for physicians in identifying cardiac issues for infants at birth. Long-term remote neonatal dry electrode ECG monitoring solutions can be an additional step for preventative healthcare measures. In these solutions, power and computationally efficient embedded signal processing techniques for denoising newborn ECG can assist in increasing neonatal medical wearable time. Wavelet denoising is an appropriate denoising mechanism with its low computational complexity that can be implemented on embedded microcontrollers for long-term remote ECG monitoring. Discrete wavelet transform (DWT) denoising for dry electrode neonatal ECG using different wavelet families is investigated. The wavelet families and mother wavelets used include Daubechies; db1, db2, db3, db4, db6, symlets; sym5 and coiflets; coif5. 19 newborn ECG signals undergo added white Gaussian noise (AWGN) of different levels and denoising is performed to select the appropriate wavelets for neonatal dry electrode ECG. The selected wavelets then undergo real noise additions of baseline wander and electrode motion to determine their robustness and accuracy. Signal to noise ratio (SNR), mean squared error (MSE) and power spectral density (PSD) are used to examine denoising performance. db1, db2, db3 wavelets are eliminated from analysis where 30 dB AWGN led to negative SNR improvement for at least one newborn ECG, removing important ECG information. Whereas db4, and sym5 are eliminated from selection due to their different waveform morphology compared to dry electrode newborn ECG's QRS complex. db6 and coif5 are selected due to their highest SNR improvement and lowest MSE of; 6.26x10 -6 , 1.65x10 -7 compared to other wavelets, respectively. Their wavelet shapes are more like newborn ECG's QRS morphology validating its selection. db6 and coif5 showed similar denoising performance decreasing electrode motion and baseline wander noisy ECG signals by 10 dB and 14 dB, respectively. Further denoising of inherent dry electrode noise is observed. DWT with coif5 or db6 wavelets are appropriate for denoising dry electrode newborn ECG for long-term neonatal dry electrode ECG monitoring solutions under different noise types. Their similarity to newborn dry electrode newborn ECG yielding accurate and robust reconstructed denoised newborn dry electrode ECG signals.