A Machine Learning Pipeline for Measurement of Arterial Stiffness in A-Mode Ultrasound

• Published in: IEEE transactions on ultrasonics, ferroelectrics, and frequency control Vol. 69; no. 1; pp. 106 - 113
• Main Authors: Sahani, Ashish Kumar, Srivastava, Divyansh, Sivaprakasam, Mohanasankar, Joseph, Jayaraj
• Format: Journal Article
• Language: English
• Published: United States IEEE 01.01.2022; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Arterial stiffness (AS); Artificial neural networks; Biomedical measurement; Blood pressure; Carotid Arteries - diagnostic imaging; Correlation coefficients; Current measurement; Data acquisition; Diameters; Graphical user interfaces; Health care facilities; Humans; Machine Learning; machine learning (ML); Measuring instruments; Modulus of elasticity; neural network; Pulse measurements; Signal processing; Signal processing algorithms; Signal Processing, Computer-Assisted; Stiffness; Tracking systems; Ultrasonic imaging; Ultrasonic variables measurement; Ultrasonography; ultrasound; Vascular Stiffness
• ISSN: 0885-3010; 1525-8955; 1525-8955
• DOI: 10.1109/TUFFC.2021.3109117

Arterial stiffness (AS) of the carotid artery is an early marker of stratifying cardiovascular disease risk. This article aims to improve the performance of ARTSENS, a noninvasive A-mode ultrasound-based device for measuring AS. The primary objective of ARTSENS is to enable the measurement of elasti...