Objective: Time frequency-based methods have been employed for event detection in audio signals.
Methods: The spectrogram can be used to extract loudness and
energy functions by taking the row sum. The loudness function has been
differentiated to obtain the on-set events of the audio. This concept could be
replicated in the case of bio-signals such as phonocardiograms to extract
on-set and off-set boundaries. A continuous Wavelet Transform-based
Time-Frequency algorithm for on-set and off-set event detection has been
developed for Phonocardiograms and this method has been tested on the
Phonocardiogram (PCG) dataset hosted in the Physionet repository. To validate
the simulation, real implementation has also been carried out with real heart
sound recordings obtained from a Bluetooth-based stethoscope.
Results: The simulation carried out using PCG sounds from the
Physionet database gave an F1-score of 99.11%. Similar results were found using
the real heart sound recordings from stemoscope with an F1- score of 99.30%.
Conclusion: Experimental evaluation and Simulations both indicate
that a Continuous Wavelet Transform-based time-frequency algorithm can be used
to derive on-set and off-set events of the sounds in the PCG signal.
Author
(s) Details
Vishwanath Madhava
Shervegar
Department of Electronics & Communication Engineering, Moodlakatte
Institute of Technology, Kundapura, India.
Please see the book here:- https://doi.org/10.9734/bpi/erpra/v2/3276
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