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Roy, J. K. , Roy, T. S. , Mandal, N. & Postolache, O. A. (2018). A simple technique for heart sound detection and identification using kalman filter in real time analysis. In 2018 International Symposium in Sensing and Instrumentation in IoT Era, ISSI 2018. Shanghai: IEEE.

J. K. Roy et al.,  "A simple technique for heart sound detection and identification using kalman filter in real time analysis", in 2018 Int. Symp. in Sensing and Instrumentation in IoT Era, ISSI 2018, Shanghai, IEEE, 2018

@inproceedings{roy2018_1775918169559,
	author = "Roy, J. K.  and Roy, T. S.  and Mandal, N. and Postolache, O. A.",
	title = "A simple technique for heart sound detection and identification using kalman filter in real time analysis",
	booktitle = "2018 International Symposium in Sensing and Instrumentation in IoT Era, ISSI 2018",
	year = "2018",
	editor = "",
	volume = "",
	number = "",
	series = "",
	doi = "10.1109/ISSI.2018.8538255",
	publisher = "IEEE",
	address = "Shanghai",
	organization = "",
	url = "http://issi2018.csp.escience.cn"
}

TY  - CPAPER
TI  - A simple technique for heart sound detection and identification using kalman filter in real time analysis
T2  - 2018 International Symposium in Sensing and Instrumentation in IoT Era, ISSI 2018
AU  - Roy, J. K. 
AU  - Roy, T. S. 
AU  - Mandal, N.
AU  - Postolache, O. A.
PY  - 2018
DO  - 10.1109/ISSI.2018.8538255
CY  - Shanghai
UR  - http://issi2018.csp.escience.cn
AB  - During Clinical assessment of a patient, the doctor uses an acoustic stethoscope to detect abnormalities in the heart sound and predict abnormal conditions of the human heart. The heart sound is a complex signal. To analysis this complex signal for determination of the intensity of diseases, the distribution pattern through signal analysis, such as the determination of harmonic, Amplitude, phase, entropy, power and all other necessary statistical value estimation is essential. The Kalman filter [9] is a statistical filter tool, which is very popular to suppress background noise and to capture the original pattern from the noisy signal. The Kalman Filter actually compares the measured value with the estimated value. In this way it can predict and correct the measured value. This feature will easily identify and distinguish between Normal heart sound, abnormal heart sound and cardiac murmurs. This paper discusses a simple technique to estimate the very low amplitude S3, S4 and cardiac murmur sound of the heart using a prototype developed electronic stethoscope. The Kalman filter approach and Matlab simulation are used to analyze the sound. The research also investigated the pattern of amplitude, phase and Kalman gain distribution of normal and abnormal heart sound.

ER  -