Ultrasound imaging and semi-automatic analysis of active muscle features in electrical stimulation by optical flow

Abstract

Ultrasound imaging is an effective way to measure the muscle activity in electrical stimulation studies. However, it is a time consuming task to manually measure pennation angle and muscle thickness, which are the benchmark features to analyze muscle activity from the ultrasound imaging. In previous studies, the muscle features were measured by calculating optical flow of the pennation angle by using only fibers of a muscle from the ultrasound, without carefully considering moving muscle edges during active and passive contraction. Therefore, this study aimed to measure the pennation angle and muscle thickness by using the edges and fibers of a muscle in a quantitative way in a semi-automatic optical flow based approach. The results of the semi-automatic analysis were compared to that of manual measurement. Through the comparison, it is clear that the proposed algorithm could achieve higher accuracy in tracking the thickness and pennation angle for a sequence of ultrasound images.

A clustering-based method for estimating pennation angle from B-mode ultrasound images

“…This toolbox has been updated from the first generation that can only track a single muscle fascicle to the recent fourth generation that enables the tracking of multiple fascicles. The toolbox can detect and track the orientations and lengths of fascicle and aponeurosis, thus, computing the PA sequence using the orientations (Darby et al, 2012 ; Kawamoto et al, 2014 ). The core technique of UltraTrack is to implement affine flow algorithms and pursue features from one frame to another using Lucas–Kanade or cross-correlation approaches (Cronin et al, 2011 ; Darby et al, 2012 ; Gillett et al, 2013 ; Farris and Lichtwark, 2016 ).…”

Optical Flow Analysis of Paralaryngeal Muscle Movement

“…These methods have previously been applied to robots to make their movement patterns more human-like and to monitor and optimize self-driving cars. 24,25 Optical flow methods have also been shown to be highly reliable and accurate for the study of muscle contraction biomechanics in leg muscles/tendons, [26][27][28][29] the heart, 30 and even humming bird wings. 31 Considering patients with pMTD are thought to have paralaryngeal muscle hyperfunction with phonation, it would be expected that patients with pMTD would have greater phonatory optical flow velocities in the paralaryngeal muscles compared with vocally healthy controls.…”

“…These methods have previously been applied to robots to make their movement patterns more human‐like and to monitor and optimize self‐driving cars 24,25 . Optical flow methods have also been shown to be highly reliable and accurate for the study of muscle contraction biomechanics in leg muscles/tendons, 26–29 the heart, 30 and even humming bird wings 31 …”