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

Min, Se Dong; Shin, Hyunki

doi:10.5370/jeet.2015.10.5.2126

Cited by 11 publications

(8 citation statements)

References 32 publications

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“…The detectors need to be tailor-made for the given purposesome authors [47], [55] deal only with the detection of the S1, while others deal with the detection of both S1 and S2, e.g. [17], [19], [69]- [71]. Both approaches are sufficient to determine fHR.…”

Section: Heart Sounds Detectionmentioning

confidence: 99%

A Review of Recent Advances and Future Developments in Fetal Phonocardiography

Kahánková

Mikolasova

Jaroš

et al. 2023

IEEE Rev. Biomed. Eng.

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Fetal phonocardiography (fPCG) is receiving attention as it is a promising method for continuous fetal monitoring due to its non-invasive and passive nature. However, it suffers from the interference from various sources, overlapping the desired signal in the time and frequency domains. This paper introduces the state-of-the-art methods used for fPCG signal extraction and processing, as well as means of detection and classification of various features defining fetal health state. It also provides an extensive summary of remaining challenges, along with the practical insights and suggestions for the future research directions.

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Section: Heart Sounds Detectionmentioning

confidence: 99%

A Review of Recent Advances and Future Developments in Fetal Phonocardiography

Kahánková

Mikolasova

Jaroš

et al. 2023

IEEE Rev. Biomed. Eng.

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“…The first heart sound, S1, which reproduces the closure of the mitral and the tricuspid valves, is generally distributed in the low-middle frequency range, between 10 Hz to 140 Hz [ 5 ]. In contrast, the S2 sound is related to the closure of the aortic and pulmonary valves [ 70 ] in a frequency range between 10 Hz and 400 Hz, with an upper bound higher than S1 but, in contrast, with a shorter duration [ 5 ]. Additional heart sounds are the third heart sound (S3) and the fourth heart sound (S4) [ 6 ] that can be present when patients show congestive heart failure or adventitious pulmonary sounds [ 71 , 72 ] associated with deteriorating cardiopulmonary conditions [ 72 , 73 , 74 ].…”

Section: Sensing Devices In Healthcarementioning

confidence: 99%

Sensing Devices for Detecting and Processing Acoustic Signals in Healthcare

et al. 2022

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Acoustic signals are important markers to monitor physiological and pathological conditions, e.g., heart and respiratory sounds. The employment of traditional devices, such as stethoscopes, has been progressively superseded by new miniaturized devices, usually identified as microelectromechanical systems (MEMS). These tools are able to better detect the vibrational content of acoustic signals in order to provide a more reliable description of their features (e.g., amplitude, frequency bandwidth). Starting from the description of the structure and working principles of MEMS, we provide a review of their emerging applications in the healthcare field, discussing the advantages and limitations of each framework. Finally, we deliver a discussion on the lessons learned from the literature, and the open questions and challenges in the field that the scientific community must address in the near future.

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“…The algorithm was able to detect HSs very effectively. • In study [56], the detection of S1 and S2 sounds using a combination of frequency filtering, energy detection, and interval regulation was presented. The proposed approach allowed for the localization of HSs with higher accuracy than using the Hilbert transform-based method.…”

Section: B Detection Of Heart Soundsmentioning

confidence: 99%

Passive Fetal Monitoring by Advanced Signal Processing Methods in Fetal Phonocardiography

et al. 2020

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Fetal phonocardiography (fPCG) is a non-invasive technique for detection of fetal heart sounds (fHSs), murmurs and vibrations. This acoustic recording is passive and provides an alternative lowcost method to ultrasonographic cardiotocography (CTG). Unfortunately, the fPCG signal is often disturbed by the wide range of artifacts that make it difficult to obtain significant diagnostic information from this signal. The study focuses on the filtering of an fPCG signal containing three types of noise (ambient noise, Gaussian noise, and movement artifacts of the mother and the fetus) having different amplitudes. Three advanced signal processing methods: empirical mode decomposition (EMD), ensemble empirical mode decomposition (EEMD), and adaptive wavelet transform (AWT) were tested and compared. The evaluation of the extraction was performed by determining the accuracy of S1 sounds detection and by determining the fetal heart rate (fHR). The evaluation of the effectiveness of the method was performed using signal-to-noise ratio (SNR), mean error of heart interval measurement (|∆T i |), and the statistical parameters of accuracy (ACC), sensitivity (SE), positive predictive value (PPV), and harmonic mean between SE and PPV (F1). Using the EMD method, ACC > 95% was achieved in 7 out of 12 types and levels of interference with average values of ACC = 88.73%, SE = 91.57%, PPV = 94.80% and F1 = 93.12%. Using the EEMD method, ACC > 95% was achieved in 9 out of 12 types and levels of interference with average values of ACC = 97.49%, SE = 97.89%, PPV = 99.53% and F1 = 98.69%. In this study, the best results were achieved using the AWT method, which provided ACC > 95% in all 12 types and levels of interference with average values of ACC = 99.34%, SE = 99.49%, PPV = 99.85% a F1 = 99.67%. INDEX TERMSFetal phonocardiography (fPCG), fetal heart rate (fHR), non-invasive fetal monitoring, empirical mode decomposition (EMD), ensemble empirical mode decomposition (EEMD), adaptive wavelet transform (AWT).

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

Cited by 11 publications

References 32 publications

A Review of Recent Advances and Future Developments in Fetal Phonocardiography

A Review of Recent Advances and Future Developments in Fetal Phonocardiography

Sensing Devices for Detecting and Processing Acoustic Signals in Healthcare

Passive Fetal Monitoring by Advanced Signal Processing Methods in Fetal Phonocardiography

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