Abstract

This paper presents a system simulation to compare between two adaptive filters based on  recursive least square (RLS) and normalized least mean square (NLMS), in their use for fetal heart rate (FHR) monitoring. The reference and primary signals are fed simultaneously to the inputs of the RLS and NLMS adaptive filters to extract the fetal signal. Each extracted signal is postprocessed using a newly developed enhancement technique. To evaluate the performance of the electrocardiogram (ECG) extraction, 20 abdominal ECG signals are acquired between the 36th and 38th gestation weeks. The detection sensitivities of 88.6 and 80.4% and positive prediction value of 82.8 and 72.1% were obtained for RLS and NLMS, respectively. The experimental results show that adaptive filtering using RLS algorithm performs better in extracting the fetal ECG signal.

Key words: Adaptive noise cancelation (ANC), recursive least square (RLS), normalized least mean square (NLMS), MQRS window, fetal electrocardiogram (FECG) extraction.