
In multigate spectral Doppler (MSD) analysis, hundreds of small sample volumes (SVs) aligned along a pulse wave-line can be simultaneously investigated. The so-called spectral profile, reporting the scatterers' velocity distribution in a vessel, is obtained by estimating the frequency content of the echoes detected from each SV. The preferred frequency estimator is the Welch method, which is robust and fast, but requires an observation window (OW) of at least 64 to 128 samples to guarantee adequate spectral resolution. The blood amplitude and phase estimator (BAPES) and the blood iterative adaptive approach (BIAA) are alternative methods which were recently proven to be capable of producing good spectrograms from one SV using shorter OWs. This paper shows that BAPES and BIAA can be successfully applied to MSD estimations. The use of short OWs can be exploited to produce spectral profiles with high temporal resolution and/or to perform simultaneous investigations at multiple sites. Two in vivo examples of application are reported: in the first, the blood velocity distribution during the fast systolic acceleration in a carotid artery is detailed with high temporal resolution; in the second, four spectral profiles are simultaneously detected at different sites of the carotid bifurcation.
Blood Pressure, Signal Processing, Computer-Assisted, Ultrasonography, Doppler, Models, Theoretical, Pulse Wave Analysis, Signal-To-Noise Ratio, Carotid Arteries, Adaptive Spectral Estimation, Humans, Algorithms, Blood Flow Velocity
Blood Pressure, Signal Processing, Computer-Assisted, Ultrasonography, Doppler, Models, Theoretical, Pulse Wave Analysis, Signal-To-Noise Ratio, Carotid Arteries, Adaptive Spectral Estimation, Humans, Algorithms, Blood Flow Velocity
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 18 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Average | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Top 10% | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Top 10% |
