Detection of the third heart sound using a tailored wavelet approach: Method verification

Abstract

Heart sounds can be considered as mechanical fingerprints of myocardial function. The third heart sound normally occurs in children but disappears with maturation. The sound can also appear in patients with heart failure. The sound is characterised by its low-amplitude and low-frequency content, which makes it difficult to identify by the traditional use of the stethoscope. A wavelet-based method has recently been developed for detection of the third heart sound. This study investigated if the third heart sound could be identified in patients with heart failure using this detection method. The method was also compared with auscultation using conventional phonocardiography and with characterisation of the patients with echocardiography. In the first study, 87% of the third heart sounds were detected using the wavelet method, 12% were missed, and 6% were false positive. In study 2, the wavelet-detection method identified 87% of the patients using the third heart sound, and regular phonocardiography identified two (25%) of the subjects.

A Localization Method for First and Second Heart Sounds Based on Energy Detection and Interval Regulation

“…FPP correction modifies PTI values using (8); a redundant peak time interval at the nth PTI, PTIn, is removed by comparison between the former and the latter PTI value. In the FNP correction, in contrast, a new PTI is added using (9). The estimated S 1 and S 2 intervals are decided by average values of 50% higher or lower.…”

“…9(a) and (b) show the initially detected S 1 and its PTI. RAD correction was carried out using (8), (9), and (10). Figs.…”

“…Although heart sounds are a useful tool clinically, they are hard to analyze from the non-stationary characteristic. That is, making a cardiac disorder diagnosis based on heart sounds is still a considerable challenge [5][6][7][8][9][10][11][12]. Thus, the accurate localization of S 1 and S 2 is an important issue for heart sound analysis and clinical applications.…”

Detection of the third and fourth heart sounds using Hilbert-Huang transform

“…In 2005, Hult et al . have developed a wavelet-based method for recognition of S3 [17]. However, the wavelet transform is not an adaptive method.…”

Accessing heart dynamics to estimate durations of heart sounds

“…They model the occurrence of S1 and S2 by a pair of impulses, respectively, that are convolved with the thoracic transfer function to yield S1 and S2 on the chest. Hult et al (2005) proposed a tailored wavelet-based approach to detect the presence of the low amplitude and low frequency S3 sound. Gamero and Watrous (2003) proposed a hidden Markov model (HMM) based probabilistic approach to model the systolic and diastolic interval durations, which are subsequently used to detect the presence of S1 and S2.…”