Rolling ball sifting algorithm for the augmented visual inspection of carotid bruit auscultation

Adam Huang, Chung Wei Lee, Hon Man Liu

Research output: Contribution to journalArticlepeer-review

4 Scopus citations


Carotid bruits are systolic sounds associated with turbulent blood flow through atherosclerotic stenosis in the neck. They are audible intermittent high-frequency (above 200 Hz) sounds mixed with background noise and transmitted low-frequency (below 100 Hz) heart sounds that wax and wane periodically. It is a nontrivial task to extract both bruits and heart sounds with high fidelity for further computer-aided auscultation and diagnosis. In this paper we propose a rolling ball sifting algorithm that is capable to filter signals with a sharper frequency selectivity mechanism in the time domain. By rolling two balls (one above and one below the signal) of a suitable radius, the balls are large enough to roll over bruits and yet small enough to ride on heart sound waveforms. The high-frequency bruits can then be extracted according to a tangibility criterion by using the local extrema touched by the balls. Similarly, the low-frequency heart sounds can be acquired by a larger radius. By visualizing the periodicity information of both the extracted heart sounds and bruits, the proposed visual inspection method can potentially improve carotid bruit diagnosis accuracy.

Original languageEnglish
Article number30179
JournalScientific Reports
StatePublished - 25 Jul 2016


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