An Echo State Neural Network for Foetal ECG Extraction Optimised by Random Search
نویسندگان
چکیده
We present a novel application of an echo state neural network (ESN) to noninvasive foetal electrocardiogram (FECG) extraction. Extraction of the FECG is performed on abdominal recordings of pregnant women via maternal ECG cancellation. The FECG can then be used for foetal health monitoring by extracting clinically interpretable features. We show that optimising an ESN by random search gives almost equivalent performance to an exhaustive grid search with 85.6% vs. 87.9% accuracy on the test database. This is particularly useful as, while powerful, ESNs have many hyper-parameters which are not easily optimised using expert knowledge.
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