Fetal heart rate estimation via adaptive least mean square linear prediction methods

Adaptive signal processing methods are presented in support of a noninvasive ambulatory fetal heart rate monitor. Adaptive least mean square (LMS) linear prediction methods are used for fetal heart tone signature analysis and detection in the presence of background acoustic noise. The signal processing techniques designed to identify, analyze, and detect the fetal phonocardiographic signature are discussed. Subsequent evaluation of the detected fetal heart tone events are used to determine the instantaneous heart rate. Preliminary investigation has indicated that linear prediction is feasible for detecting the fetal heart tones in an advanced acoustic fetal heart rate monitor. A prediction length of eight was found to be suboptimal in minimizing the total mean square error over the training event.<
>