Entropy Profiling for Detection of Fetal Arrhythmias in Short Length Fetal Heart Rate Recordings
Emerson Keenan, Radhagayrathi K Udhayakumar, Chandan K Karmakar, Fiona C Brownfoot, Marimuthu Palaniswami
42ND ANNUAL INTERNATIONAL CONFERENCES OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY: ENABLING INNOVATIVE TECHNOLOGIES FOR GLOBAL HEALTHCARE EMBC'20 | IEEE | Published : 2020
The use of fetal heart rate (FHR) recordings for assessing fetal wellbeing is an integral component of obstetric care. Recently, non-invasive fetal electrocardiography (NI-FECG) has demonstrated utility for accurately diagnosing fetal arrhythmias via clinician interpretation. In this work, we introduce the use of data-driven entropy profiling to automatically detect fetal arrhythmias in short length FHR recordings obtained via NI-FECG. Using an open access dataset of 11 normal and 11 arrhythmic fetuses, our method (TotalSampEn) achieves excellent classification performance (AUC = 0.98) for detecting fetal arrhythmias in a short time window (i.e. under 10 minutes). We demonstrate that our met..View full abstract
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Awarded by NHMRC
Awarded by Australian Research Council (ARC) Discovery Project
Emerson Keenan is supported by an Australian Government Research Training Program Scholarship at the University of Melbourne. Fiona Brownfoot is supported by a NHMRC Early Career Fellowship (NHMRC #1142636) and a Norman Beischer Clinical Research Fellowship. This work was supported by the Australian Research Council (ARC) Discovery Project under Grant DP190101248.