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Fulltext Fetal heart sound analysis: a preliminary evaluation

Baskaran A, Sivalingam N

Med J Malaysia, 1996 Mar;51(1):64-7.
PMID: 10967981

The aim of this study, is to determine whether the fine characteristics of the fetal heart sounds could be used to identify intrauterine growth retarded fetuses. A preliminary evaluation, was conducted to compare these characteristics between intrauterine growth retarded fetuses and normal fetuses in the antenatal period after 36 weeks of gestation. Altogether, 7 IUGR fetuses were compared with 12 normal fetuses. An instrument named the Fetal Frequency Phonocardiogram was designed for this purpose. When connected to a personal computer and with a software programme specially written, the fetal heart sound characteristics were analysed. After detailed analysis, there were 3 significant differences between IUGR and normal fetuses, all of which gave a p-value of < 0.01. The frequency of the first heart sound was significantly higher in the IUGR fetuses compared to normal fetuses. The ratio of the amplitude of the first heart sound over the second heart sound was higher in the IUGR group. Finally, the ratio of the time between the first and second heart sound over the cardiac cycle was shorter in the IUGR fetuses. Fetal heart sound analysis, may provide a simple non-invasive method of detecting and monitoring fetuses at risk in the antenatal period.

Matched MeSH terms: Heart Sounds*
Fulltext Real-Time Smart-Digital Stethoscope System for Heart Diseases Monitoring

Chowdhury MEH, Khandakar A, Alzoubi K, Mansoor S, M Tahir A, Reaz MBI, et al.

Sensors (Basel), 2019 Jun 20;19(12).
PMID: 31226869 DOI: 10.3390/s19122781

One of the major causes of death all over the world is heart disease or cardiac dysfunction. These diseases could be identified easily with the variations in the sound produced due to the heart activity. These sophisticated auscultations need important clinical experience and concentrated listening skills. Therefore, there is an unmet need for a portable system for the early detection of cardiac illnesses. This paper proposes a prototype model of a smart digital-stethoscope system to monitor patient's heart sounds and diagnose any abnormality in a real-time manner. This system consists of two subsystems that communicate wirelessly using Bluetooth low energy technology: A portable digital stethoscope subsystem, and a computer-based decision-making subsystem. The portable subsystem captures the heart sounds of the patient, filters and digitizes, and sends the captured heart sounds to a personal computer wirelessly to visualize the heart sounds and for further processing to make a decision if the heart sounds are normal or abnormal. Twenty-seven t-domain, f-domain, and Mel frequency cepstral coefficients (MFCC) features were used to train a public database to identify the best-performing algorithm for classifying abnormal and normal heart sound (HS). The hyper parameter optimization, along with and without a feature reduction method, was tested to improve accuracy. The cost-adjusted optimized ensemble algorithm can produce 97% and 88% accuracy of classifying abnormal and normal HS, respectively.

Matched MeSH terms: Heart Sounds/physiology
Fulltext Multi-level basis selection of wavelet packet decomposition tree for heart sound classification

Safara F, Doraisamy S, Azman A, Jantan A, Abdullah Ramaiah AR

Comput Biol Med, 2013 Oct;43(10):1407-14.
PMID: 24034732 DOI: 10.1016/j.compbiomed.2013.06.016

Wavelet packet transform decomposes a signal into a set of orthonormal bases (nodes) and provides opportunities to select an appropriate set of these bases for feature extraction. In this paper, multi-level basis selection (MLBS) is proposed to preserve the most informative bases of a wavelet packet decomposition tree through removing less informative bases by applying three exclusion criteria: frequency range, noise frequency, and energy threshold. MLBS achieved an accuracy of 97.56% for classifying normal heart sound, aortic stenosis, mitral regurgitation, and aortic regurgitation. MLBS is a promising basis selection to be suggested for signals with a small range of frequencies.

Matched MeSH terms: Heart Sounds/physiology*
Fulltext Acoustic cardiac signals analysis: a Kalman filter-based approach

Salleh SH, Hussain HS, Swee TT, Ting CM, Noor AM, Pipatsart S, et al.

Int J Nanomedicine, 2012;7:2873-81.
PMID: 22745550 DOI: 10.2147/IJN.S32315

Auscultation of the heart is accompanied by both electrical activity and sound. Heart auscultation provides clues to diagnose many cardiac abnormalities. Unfortunately, detection of relevant symptoms and diagnosis based on heart sound through a stethoscope is difficult. The reason GPs find this difficult is that the heart sounds are of short duration and separated from one another by less than 30 ms. In addition, the cost of false positives constitutes wasted time and emotional anxiety for both patient and GP. Many heart diseases cause changes in heart sound, waveform, and additional murmurs before other signs and symptoms appear. Heart-sound auscultation is the primary test conducted by GPs. These sounds are generated primarily by turbulent flow of blood in the heart. Analysis of heart sounds requires a quiet environment with minimum ambient noise. In order to address such issues, the technique of denoising and estimating the biomedical heart signal is proposed in this investigation. Normally, the performance of the filter naturally depends on prior information related to the statistical properties of the signal and the background noise. This paper proposes Kalman filtering for denoising statistical heart sound. The cycles of heart sounds are certain to follow first-order Gauss-Markov process. These cycles are observed with additional noise for the given measurement. The model is formulated into state-space form to enable use of a Kalman filter to estimate the clean cycles of heart sounds. The estimates obtained by Kalman filtering are optimal in mean squared sense.

Matched MeSH terms: Heart Sounds/physiology
Occurrences of heart disease in apparently healthy cats in Klang Valley, Malaysia

Khor KH, Chin MX

J Adv Vet Anim Res, 2020 Sep;7(3):501-508.
PMID: 33005676 DOI: 10.5455/javar.2020.g446

Objective: Annual health screening inclusive of heart workup is recommended for the detection of heart diseases, especially in asymptomatic patients (no clinical signs). This study determined the occurrences of the common heart disease and the risk factors in apparently healthy cats.
Materials and methods: This prospective study that screened 59 healthy cats and the status of the heart were evaluated based on a combination of findings from physical examination, electrocardiography, blood pressure measurement, routine blood test, urinalysis, and total thyroid level.
Results: Approximately 40.7% (n = 24/59) of the apparently healthy cats were diagnosed with heart disease hypertrophic cardiomyopathy (62.5%) remains to be the most commonly diagnosed. The mean age was 4.9-year old (age range, 7-month-old to 19-year-old). The prevalence was higher in males (45.0%; n = 17/38) cats, especially the domestic shorthairs (46.0%; n = 11/24). Among the healthy cats with vertebral heart scale (VHS) > 8.0, only 52% (n = 12/23) of them were diagnosed with cardiomyopathy. However, 33% (n = 12/36) of the cats with normal VHS ≤ 7.9 were diagnosed with heart disease. Consistently, all healthy cats with abnormal heart sounds were diagnosed with heart disease. About 31.4% (n = 16/51) of these cats with typical heart sound had cardiomyopathy too.
Conclusion: The occurrence of cardiomyopathy in apparently healthy cats has no association with the patient's age, sex, and VHS, except for the heart sound. Echocardiography remains the best diagnostic tool, as normal heart size and normal heart sound do not exclude cardiomyopathy in this group of apparently healthy cats.

Matched MeSH terms: Heart Sounds
Fulltext The rare congenital anomaly of scimitar syndrome: an unusual presentation in symptomatic adult

Siti Zulaiha Binti Che Hat

Malaysian Journal of Medicine and Health Sciences, 2020;16(3):334-336.
MyJurnal

Scimitar syndrome is a rare congenital heart defect occurring in 1 to 3 per 100,000 live births. This is a case of a 26 years old lady presenting with episodic fainting spells since the age of 18 years old. She was initially diagnosed with epilepsy until a referral to our centre found a soft splitting of the second heart sound and multiple premature ventricular complexes on ECG. The computed tomography of the pulmonary artery confirmed the diagnosis if Scim- itar syndrome in the presence of anomalous single right pulmonary vein draining into infra-diaphragmatic systemic venous circulation. A corrective open-heart surgery to re-implant the pulmonary vein was performed with excellent clinical outcomes. Therefore, it is crucial for clinicians to embody high index of suspicion of congenital anomaly even in adults presenting with indefinite clinical symptoms. This report also represents the first published case of adult Scimitar syndrome from Malaysia.

Matched MeSH terms: Heart Sounds