• DocumentCode
    1165777
  • Title

    Microembolic signal characterization using adaptive chirplet expansion

  • Author

    Zhang, Yu ; Zhang, Hong ; Zhang, Nanxiong

  • Author_Institution
    Digital Signal Process., Nat. Instruments, China
  • Volume
    52
  • Issue
    8
  • fYear
    2005
  • Firstpage
    1291
  • Lastpage
    1299
  • Abstract
    The adaptive chirplet expansion (ACE) is proposed to characterize high-intensity, transient signals from circulating microemboli. The nonnegative adaptive spectrogram based on the ACE gives a compact representation of the microembolic signal (MES) in joint-time, frequency domain. The mean instantaneous power (MIP) and mean instantaneous frequency (MIF) of MES are estimated from the adaptive spectrogram. Then, several important characteristics of MES, such as embolus-to-blood ratio (EBR), half width maximum (HWM), and embolic signal onset (ESO), are computed from the MIP, and the frequency modulation is examined in the MIF. To validate the new method, we improved the simulation model of the audio Doppler ultrasound signal. Some MESs together with a Doppler ultrasound signal from carotid blood flow are simulated in the simulation study. As a comparison, the adaptive Gabor expansion (AGE) also is implemented on these simulated signals. The experimental results of the simulation study show that the new method, based on the ACE, outperforms the AGE-based method in MES characterization. The consistent conclusion has been confirmed by the clinical study on some clinical MESs.
  • Keywords
    Doppler measurement; biomedical ultrasonics; blood; blood vessels; haemodynamics; medical signal processing; signal representation; time-frequency analysis; adaptive Gabor expansion; adaptive chirplet expansion; audio Doppler ultrasound signal; carotid blood flow; embolic signal onset; embolus-to-blood ratio; high-intensity transient signals; mean instantaneous frequency; mean instantaneous power; microembolic signal characterization; nonnegative adaptive spectrogram; signal representation; time-frequency domain; Chirp; Computational modeling; Digital signal processing; Energy states; Frequency domain analysis; Frequency estimation; Frequency modulation; Instruments; Spectrogram; Ultrasonic imaging; Algorithms; Computer Simulation; Echocardiography, Doppler; Feasibility Studies; Humans; Image Interpretation, Computer-Assisted; Infarction, Middle Cerebral Artery; Intracranial Embolism; Models, Biological; Signal Processing, Computer-Assisted;
  • fLanguage
    English
  • Journal_Title
    Ultrasonics, Ferroelectrics, and Frequency Control, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    0885-3010
  • Type

    jour

  • DOI
    10.1109/TUFFC.2005.1509787
  • Filename
    1509787