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Open AccessArticle

Time-Frequency Distribution of Seismocardiographic Signals: A Comparative Study

1
Biomedical Acoustics Research Laboratory, University of Central Florida, 4000 Central Florida Blvd, Orlando, FL 32816, USA
2
Rush University Medical Center, 1653 W Congress Pky, Chicago, IL 60612, USA
*
Author to whom correspondence should be addressed.
Academic Editor: Gou-Jen Wang
Bioengineering 2017, 4(2), 32; https://doi.org/10.3390/bioengineering4020032
Received: 10 February 2017 / Revised: 1 April 2017 / Accepted: 5 April 2017 / Published: 7 April 2017
Accurate estimation of seismocardiographic (SCG) signal features can help successful signal characterization and classification in health and disease. This may lead to new methods for diagnosing and monitoring heart function. Time-frequency distributions (TFD) were often used to estimate the spectrotemporal signal features. In this study, the performance of different TFDs (e.g., short-time Fourier transform (STFT), polynomial chirplet transform (PCT), and continuous wavelet transform (CWT) with different mother functions) was assessed using simulated signals, and then utilized to analyze actual SCGs. The instantaneous frequency (IF) was determined from TFD and the error in estimating IF was calculated for simulated signals. Results suggested that the lowest IF error depended on the TFD and the test signal. STFT had lower error than CWT methods for most test signals. For a simulated SCG, Morlet CWT more accurately estimated IF than other CWTs, but Morlet did not provide noticeable advantages over STFT or PCT. PCT had the most consistently accurate IF estimations and appeared more suited for estimating IF of actual SCG signals. PCT analysis showed that actual SCGs from eight healthy subjects had multiple spectral peaks at 9.20 ± 0.48, 25.84 ± 0.77, 50.71 ± 1.83 Hz (mean ± SEM). These may prove useful features for SCG characterization and classification. View Full-Text
Keywords: seismocardiography; vibrocardiography; time-frequency analysis; short-time Fourier transform; continuous wavelet transform; chirplet transform; signal processing; signal characteristics seismocardiography; vibrocardiography; time-frequency analysis; short-time Fourier transform; continuous wavelet transform; chirplet transform; signal processing; signal characteristics
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Taebi, A.; Mansy, H.A. Time-Frequency Distribution of Seismocardiographic Signals: A Comparative Study. Bioengineering 2017, 4, 32.

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