Analysis of seismocardiographic signals using polynomial chirplet transform and smoothed pseudo Wigner-Ville distribution

@article{Taebi2017AnalysisOS,
  title={Analysis of seismocardiographic signals using polynomial chirplet transform and smoothed pseudo Wigner-Ville distribution},
  author={Amirtah{\`a} Taebi and Hansen A. Mansy},
  journal={2017 IEEE Signal Processing in Medicine and Biology Symposium (SPMB)},
  year={2017},
  pages={1-6}
}
  • A. Taebi, H. Mansy
  • Published 2017
  • Mathematics, Engineering, Computer Science
  • 2017 IEEE Signal Processing in Medicine and Biology Symposium (SPMB)
Seismocardiographic (SCG) signals are chest surface vibrations induced by cardiac activity. These signals may offer a method for diagnosing and monitoring heart function. Successful classification of SCG signals in health and disease depends on accurate signal characterization and feature extraction. One approach of determining signal features is to estimate its time-frequency characteristics. In this regard, four different time-frequency distribution (TFD) approaches were used including short… Expand
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Results showed that SCG events tended to have two slightly different morphologies, which suggests that variations in SCG morphology may be due, at least in part, to changes in the intrathoracic pressure or heart location since those parameters correlates more with lung volume than respiratory flow. Expand
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