Sparse models and recursive computations for determining arterial dynamics. (September 2017)

• Record Type: Journal Article
• Authors: Ganesh, Thendral; Joseph, Jayaraj; Bhikkaji, Bharath; Sivaprakasam, Mohanasankar
• Is Part Of: Biomedical signal processing and control. Volume 38(2017)
• Page Start: 9
• Page End: 21
• Publication Date: 2017-09
• Subjects: Carotid artery -- Ultrasound -- Arterial stiffness -- Vascular compliance -- LTI system -- Sparsity; Signal processing -- Periodicals; Biomedical engineering -- Periodicals; Signal Processing, Computer-Assisted -- Periodicals; Image Processing, Computer-Assisted -- Periodicals; Biomedical Engineering -- Periodicals; 610.28
• DOI: 10.1016/j.bspc.2017.02.010
• Languages: English
• ISSNs: 1746-8094

Abstract

Abstract : Highlights: Image free evaluation of the diameter and distension waveform of the Common Carotid Artery (CCA). Modelling the acquired RF signal as an output of an FIR filter, having sparse coefficients, leading to large data compression. Filter being data dependent (filter coefficients estimated from the data) as opposed to generic band-pass or low pass filters. Recursive methods with simple computations for real time filtering. Robust Distension waveform and Diameter estimation closely matching the ground truth (B-Mode Images). Abstract: Arteries expand and contract in every cardiac cycle. Arteries of a healthy individual are elastic. Increased arterial stiffness is an established marker of the vascular health. An estimate of this vascular stiffness may be obtained by measuring the diameter of the Common Carotid Artery (CCA) in each cardiac cycle. This is typically done using image based systems. ARTSENS 1 is a portable, image free, ultrasound device for evaluating the stiffness of the CCA. ARTSENS emits a sequence of ultrasound pulses and records the reflected echoes. These echoes are then used to identify the CCA and estimate its diameter, and thereby evaluate the arterial stiffness. This paper deals with development of algorithms for determining the echoes due to the CCA and the estimation of its diameter. Here, the propagation path of each ultrasound pulse is modeled as an FIR filter considering the Gaussian modulated sine (GMS) pulse as the input and its reflections from the walls of the artery and other anatomical structures as the output. The impulse response of the FIR filter is sparse as its output has only few significant echoes. The echoes are reconstructed using the estimated filter coefficients and observed that the reconstructed signal is noise free. This results in the reliable tracking of the artery walls and evaluating its lumen (inner) diameter. The filter coefficients (impulse response) are first determined using Matching Pursuit (MP) algorithms. Additionally, the MP algorithms are made recursive to enable online filtering of the data. The inner diameter of the CCA was calculated for twenty seven subjects using the reconstructed (filtered) data. The estimated diameters were compared with diameters obtained from a B-mode imaging system and was found to be in close match. Furthermore, it is found that for a subject, only the non-zero impulse responses and their sample numbers need to be stored to recover the filtered echoes. Leading to a significant data compression.