A Hybrid Method for Ultrasound-Based Tracking of Skeletal Muscle Architecture

Objective: Tracking skeletal muscle architecture using B-mode ultrasound is a widely used method in the field of human movement science and biomechanics. Sequential methods based on optical flow algorithms allow for smooth and coherent muscle tracking but are known to drift over time. Non-sequential...

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Bibliographic Details
Published in:IEEE transactions on biomedical engineering 2023-04, Vol.70 (4), p.1114-1124
Main Authors: Verheul, Jasper, Yeo, Sang-Hoon
Format: Article
Language:English
Subjects:
Algorithms
Ankle
Ankle Joint
Automated muscle tracking
Automation
B-mode ultrasonography
Biomechanics
Drift
Feature extraction
Hough transform
Hough transformation
Human motion
Humans
Irregularities
Isometric Contraction
Jumping
Legged locomotion
Methods
Muscle contraction
Muscle Contraction - physiology
Muscle, Skeletal - diagnostic imaging
Muscle, Skeletal - physiology
Muscles
Musculoskeletal system
Noise sensitivity
Optical flow
Optical flow (image analysis)
Probes
Skeletal muscle
Tibialis anterior architecture
Tracking
Transforms
Ultrasonic imaging
Ultrasonic testing
Ultrasonography - methods
Ultrasound
Videos
Walking
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Description
Summary:Objective: Tracking skeletal muscle architecture using B-mode ultrasound is a widely used method in the field of human movement science and biomechanics. Sequential methods based on optical flow algorithms allow for smooth and coherent muscle tracking but are known to drift over time. Non-sequential feature detection methods on the other hand, do not suffer from drift, but are limited to tracking only lower-dimensional features. They are also known to be sensitive to image noise, and therefore often result in highly irregular tracking patterns. Building on the complimentary nature of both approaches, we present a novel automated hybrid muscle tracking approach that combines a sequential feature-point tracking method and a non-sequential method based on Hough transform. Methods: Tibialis anterior fascicle pennation angle and length, and central aponeurosis displacement, were measured in five healthy individuals during isometric contractions at five different ankle angles. Results: Our hybrid method was demonstrated to significantly (p < 0.001) reduce drift compared to two sequential methods, and curve irregularity was significantly (p < 0.001) decreased compared to a non-sequential method. Conclusion: These findings suggest that the proposed hybrid approach can uniquely mitigate drift and irregularity limitation of individual methods used for tracking skeletal muscle architecture. Significance: Automated muscle tracking allows for convenient analysis of large datasets, whereas automatic drift correction opens the door for tracking muscle architecture in long ultrasound recordings during common movements, such as walking, running, and jumping without the need for manual intervention.
ISSN:0018-9294
1558-2531
DOI:10.1109/TBME.2022.3210724