Comparison of envelope extraction algorithms for cardiac sound signal segmentation

Choi, Samjin; Jiang, Zhongwei

doi:10.1016/j.eswa.2006.12.015

Cited by 198 publications

(109 citation statements)

References 12 publications

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“…S3 and S4 are usually low amplitude and low frequency that make them difficult to be detected. These four heart sound components lie in the frequency range of 20-200 Hz [7].…”

Section: Heart Sound As Time Seriesmentioning

confidence: 99%

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Deterministic Approach to Detect Heart Sound Irregularities

Mengko¹,

Hamidah²,

Ricky³

2017

Adv. sci. technol. eng. syst. j.

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“…S3 and S4 are usually low amplitude and low frequency that make them difficult to be detected. These four heart sound components lie in the frequency range of 20-200 Hz [7].…”

Section: Heart Sound As Time Seriesmentioning

confidence: 99%

“…With sample rate at 44.1 kHz the amount of data generated is too large for our purpose, so this signal should be downsampled to 2000 Hz. The reason to choose this downsampling frequency is to make sure that all the heart sound which occurred in this frequency is properly represented [8]. …”

Section: Down Samplingmentioning

confidence: 99%

Deterministic Approach to Detect Heart Sound Irregularities

Mengko¹,

Hamidah²,

Ricky³

2017

Adv. sci. technol. eng. syst. j.

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“…The Shannon energy envelope is calculated as shown in Choi's paper [Choi & Jiang, 2008]. The square in the plot indicates the region where the [T1,T2] data points would be for a normal person.…”

Section: Diagnostic Parametersmentioning

confidence: 99%

Wireless PC-based phonocardiograph and diagnosis

Dao

2014

Preprint

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Auscultation is used to evaluate heart health and can indicate when it's needed to refer a patient to a cardiologist. Advanced PCG signal processing algorithms are developed to assist the physician in the initial diagnosis but they are primarily designed and demonstrated with research quality equipment. Therefore there is a need to demonstrate the applicability of those techniques with consumer grade instrument. Furthermore, routine monitoring would benefit from a wireless PCG sensor that allows continuous monitoring of cardiac signals of patients in physical activity, e.g., treadmill or weight exercise. In this work, a low-cost portable and wireless healthcare monitoring system based on phonocardiograph signal is implemented to validate and evaluate the most advanced algorithms. Off-the-shelf electronics and a notebook PC are used with MATLAB codes to record and analyze PCG signals which are collected with a notebook computer in tethered and wireless mode. High valued diagnostics based on the S1 and S2 signals and MATLAB codes are demonstrated. While the prototype is based on MATLAB, the later is not an absolute requirement.

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“…Many algorithms have been reported so far, and most of them are based on the energy or time-frequency characterization of the signal [1]- [3]. But they are mostly affected by amplitude and frequency variations of the heart sounds.…”

Section: Introductionmentioning

confidence: 99%

Detection of S1/S2 Components with Extraction of Murmurs from Phonocardiogram

Quan

Seok

Bae

2015

IEICE Trans. Inf. & Syst.

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SUMMARYThe simplicity is a type of measurement that represents visual simplicity of a signal, regardless of its amplitude and frequency variation. We propose an algorithm that can detect major components of heart sound using Gaussian regression to the smoothed simplicity profile of a heart sound signal. The weight and spread of the Gaussians are used as features to discriminate cardiac murmurs from major components of a heart sound signal. Experimental results show that the proposed method is very promising for robust and accurate detection of major heart sound components as well as cardiac murmurs.

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Comparison of envelope extraction algorithms for cardiac sound signal segmentation

Cited by 198 publications

References 12 publications

Deterministic Approach to Detect Heart Sound Irregularities

Deterministic Approach to Detect Heart Sound Irregularities

Wireless PC-based phonocardiograph and diagnosis

Detection of S1/S2 Components with Extraction of Murmurs from Phonocardiogram

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