Year: 2022
Type: article
Abstract: Fetal heart rate (fHR) is an important indicator for monitoring of fetal cardiac health and development. The widely-used method based on ultrasound, however, is not continuous and often requires an expert to perform; thus, it is mostly used in clinics during checkups. The advances in wearable technology have paved the way for home assessment of fHR via the extraction of the mother's abdominal electrocardiogram (ECG) acquired by novel patches. Several methods have been developed for such; however, the computation is either too slow for real-time monitoring or too heavy to be performed in a wearable. In this work, we develop and validate the Lullaby algorithm - a novel method for fetal QRS extraction from aECG. The results showed that Lullaby is almost 7 times faster than existing methods with a better F1-score of 0.815, holding promise to transform perinatal monitoring.
Source: IEEE Sensors Letters
Authors: Daniel Jilani, Tai Le, Tim Etchells, Michael P. H. Lau, Hung Cao
Institution: University of California, Irvine
Language: English
Topic: ECG Monitoring and Analysis
Subfield: Cardiology and Cardiovascular Medicine
Field: Medicine
Domain: Health Sciences
Open Access status: green
OpenAlex ID: W4292387374