In this paper, a single-channel adaptive noise canceller (SCANC) is proposed to enhance heart sounds during auscultation. Heart sounds provide important information about the condition of the heart, but other sounds interfere with heart sounds during auscultation. The adaptive noise canceller (ANC) is widely used to reduce noises from biomedical signals, but it is not suitable for enhancing auscultatory sounds acquired by a stethoscope. While the ANC needs two inputs, a stethoscope provides only one input. Other approaches, such as ECG gating and wavelet de-noising, are rather complex and difficult to implement as real-time systems. The proposed SCANC uses a single-channel input based on Heart Sound Inherency Indicator and reference generator. The architecture is simple, so it can be easily implemented in real-time systems. It was experimentally confirmed that the proposed SCANC is efficient for heart sound enhancement and is robust against the heart rate variations.

This paper proposes a low-distortion noise canceller and its learning algorithm which is robust against crosstalk and is applicable for continuous sounds. The proposed canceller consists of two stages: cancellation of the crosstalk and cancellation of the noise. A recursive filter reduces the number of computations for noise cancellation stage. Separate filters for the adaptation and the filtering are introduced for crosstalk cancellation. Computer simulations show 10 dB improvement of the error power.