Abstract
Auscultation of the heart sound is basically the process a physician understands the preliminary condition of a patient’s heart. A more efficient approach to understand the heart conditions can be achieved through modern digital signal processing techniques. Various authors have proposed different methods to predict the heart condition via the PCG signal. In this paper, a collaboration of hardware and software co-simulations using Xilinx system generator is implemented on pre-recorded PCG signals. The denoising is implemented with variational mode decomposition, while the peak detection and ANN are implemented through system generator for FPGA analysis. The initiation and end of each heart sound sample are detected from the retrospective normalized envelogram of the Shannon energy of each sound. This is followed by a dynamic thresholding to detect the peaks, whose data is fed into the ANN for abnormality detection.
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Acknowledgements
The authors would like to acknowledge project number BT/COE/34/SP28408/2018 of Department of Biotechnology (DBT), Government of India for the financial support via the NECBH Twinning grant with Dr. C. N. Gupta, of Department of BSBE, IIT Guwahati.
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Meitei, T.G., Singh, S.A., Majumder, S. (2021). Hardware-Based Analysis of PCG Signal for Heart Conditions. In: Singh, B., Coello Coello, C.A., Jindal, P., Verma, P. (eds) Intelligent Computing and Communication Systems. Algorithms for Intelligent Systems. Springer, Singapore. https://doi.org/10.1007/978-981-16-1295-4_14
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DOI: https://doi.org/10.1007/978-981-16-1295-4_14
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