Literature DB >> 10414903

Frequency filtering improves ultrasonic embolic signal detection.

H S Markus1, G Reid.   

Abstract

Problems in detection of Doppler cerebral embolic signals primarily occur for embolic signals of low relative intensity. A characteristic feature of embolic signals is that the intensity increase is maximal over a narrow frequency band. Therefore, frequency filtering of the data might improve embolic signal relative intensity and detectability. We implemented an off-line finite impulse response filter in software running on a commercially available transcranial Doppler system, using the time-domain audio data as input. The range of the filter was chosen by placing a box around the embolic signal on the spectral display. One hundred consecutive embolic signals from patients with carotid stenosis were analyzed; all had been recorded by a bigate system and the signal was analyzed in both proximal and distal channels. There was a highly significant increase in embolic signal relative intensity following frequency filtering; mean (SD) proximal channel prefiltering 12.75 (4.83) dB, postfiltering 16.36 (4.93) dB; distal channel prefiltering 13.42 (4.98) dB, postfiltering 16.60 (5.11) dB, for both p < 0.001. Despite all embolic signals being audible and visible in at least one channel on the frequency spectral display, in 17 cases, the amplitude increase associated with the embolic signal could not be clearly seen in time-domain data of one or both channels prior to filtering. Following frequency filtering, this was reduced to 5. Incorporation of such a frequency-filtering approach to an online system is likely to improve the sensitivity of online detection for embolic signals of low relative intensity.

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Year:  1999        PMID: 10414903     DOI: 10.1016/s0301-5629(99)00029-0

Source DB:  PubMed          Journal:  Ultrasound Med Biol        ISSN: 0301-5629            Impact factor:   2.998


  3 in total

1.  Denoising performance of modified dual-tree complex wavelet transform for processing quadrature embolic Doppler signals.

Authors:  Gorkem Serbes; Nizamettin Aydin
Journal:  Med Biol Eng Comput       Date:  2013-09-19       Impact factor: 2.602

2.  Detection of Doppler Microembolic Signals Using High Order Statistics.

Authors:  Maroun Geryes; Sebastien Ménigot; Walid Hassan; Ali Mcheick; Jamal Charara; Jean-Marc Girault
Journal:  Comput Math Methods Med       Date:  2016-12-14       Impact factor: 2.238

3.  A Software Tool for the Annotation of Embolic Events in Echo Doppler Audio Signals.

Authors:  Paola Pierleoni; Lorenzo Maurizi; Lorenzo Palma; Alberto Belli; Simone Valenti; Alessandro Marroni
Journal:  Biomed Inform Insights       Date:  2017-12-07
  3 in total

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