Noise detection in phonocardiograms by exploring similarities in spectral features

Publication date: July 2018 Source:Biomedical Signal Processing and Control, Volume 44 Author(s): Adriana Leal, Diogo Nunes, Ricardo Couceiro, Jorge Henriques, Paulo Carvalho, Isabel Quintal, César Teixeira Analysis and interpretation of heart sounds (HSs) can be seriously hindered by noise contamination when signals are acquired in noncontrolled environments. Signal processing methodologies are then required in order to robustly analyse HSs collected in different recording settings. Some works already address this problem using complex calculus that are usually dependent on the accurate segmentation of the signals. As such, the aim of the present study is the development of a low-complex automatic algorithm able to discriminate clean from contaminated HS signals (or phonocardiograms) recorded in real-life situations. Spectral features were used to characterize the different behaviours of clean and noisy HSs in phonocardiograms (PCGs) in noisy conditions. In particular, besides the normal interferences associated to the auscultation in a noncontrolled environment, other noisy sounds were purposely simulated and included vocalizations, ambient sounds and also other physiological interferences rather than HSs. The available signals were recorded in 24 healthy volunteers and in eight patients diagnosed with different cardiac disorders. The subjects included in the healthy dataset followed a pre-defined protocol, during which ambient, physiological and vocal interferenc...
Source: Biomedical Signal Processing and Control - Category: Biomedical Science Source Type: research