Sound Spectroanalytic Diagnosis of Malfunctioning Prosthetic Heart Valve

Kagawa, Y; Nitta, S.; Satoh, N.; K, Saji; Shibota, Y; Horiuchi, T; Tanaka, Motonao

doi:10.1620/tjem.123.77

Cited by 10 publications

(1 citation statement)

References 13 publications

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“…With the use of latest technology, mobile phones can also be used as an electronic stethoscope and the digital phonocardiogram signals can be easily acquired, saved and transmitted to a cardiologist for further analysis. Most of the research in the auscultation field is seen mainly till 1980s but due to other methods like Echocardiography, research trends in PCG decreased, but in past few years it has shown a boost due to improvements in personal computers and signal processing techniques [3][4]. The abrupt frequency changes, the complex and highly nonstationary nature of the heart sound signals make the heart sound signal analysis a tedious job.…”

Section: Previous Workmentioning

confidence: 99%

Heart Sounds Classification using Feature Extraction of Phonocardiography Signal

Singh¹,

Cheema²

2013

IJCA

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The Phonocardiogram (PCG) signals contain very useful information about the condition of the heart. By analyzing these signals, early detection and diagnosis of heart diseases can be done. It is also very useful in the case of infants, where ECG recording and other techniques are difficult to implement. In this paper, a classification method is proposed to classify normal and abnormal heart sound signals having murmurs without getting into the cumbersome process of segmenting fundamental heart sounds (FHS) using Electrocardiogram (ECG) gating. The proposed algorithm can be easily implemented on latest electronic stethoscopes, and therefore the unnecessary ECG can be avoided. General TermsClassification algorithm.

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Section: Previous Workmentioning

confidence: 99%

Heart Sounds Classification using Feature Extraction of Phonocardiography Signal

Singh¹,

Cheema²

2013

IJCA

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Frequency analysis of lonescu-Shiley prosthetic closing sounds in patients with normally functioning prostheses

Brais

Durand

Blanchard

et al. 1986

Med. Biol. Eng. Comput.

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Time-frequency analysis of the first heart sound: Part 3: Application to dogs with varying cardiac contractility and to patients with mitral mechanical prosthetic heart valves

Chen

Durand

Lee

et al. 1997

Med. Biol. Eng. Comput.

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The cone-kernel distribution (CKD) is first applied to the analysis of the intracardiac and the thoracic first heart sound (S1) of dogs in various cardiac contractile states, and secondly to the S1 of patients with mitral mechanical prosthetic heart valves. The CKD of native S1 in dogs shows that the dominant components of S1 are generally concentrated in a band at around 50 Hz with a horizontal flat or a semi-lunar shape, independently of the myocardial contractile state. There is no significant systematic rising frequency component. The instantaneous frequency of S1 shows a good cross-correlation with the time derivative of the left ventricular pressure (dP/dt), but the maximum frequency is not proportional to the maximum of dP/dt. The CKD of S1 in patients with mitral mechanical prosthetic heart valves showed a pulse-like component with a high-frequency bandwidth, which is distinct from the low constant-frequency components of S1 produced by native heart valves.

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Sound Spectroanalytic Diagnosis of Malfunctioning Prosthetic Heart Valve

Cited by 10 publications

References 13 publications

Heart Sounds Classification using Feature Extraction of Phonocardiography Signal

Heart Sounds Classification using Feature Extraction of Phonocardiography Signal

Frequency analysis of lonescu-Shiley prosthetic closing sounds in patients with normally functioning prostheses

Time-frequency analysis of the first heart sound: Part 3: Application to dogs with varying cardiac contractility and to patients with mitral mechanical prosthetic heart valves

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