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Individual Muscle Force Estimation in the Human Forearm Using Multi-Muscle MR Elastography (MM-MRE).
- Source :
-
IEEE transactions on bio-medical engineering [IEEE Trans Biomed Eng] 2023 Nov; Vol. 70 (11), pp. 3206-3215. Date of Electronic Publication: 2023 Oct 19. - Publication Year :
- 2023
-
Abstract
- Objective: To establish the sensitivity of magnetic resonance elastography (MRE) to active muscle contraction in multiple muscles of the forearm.<br />Methods: We combined MRE of forearm muscles with an MRI-compatible device, the MREbot, to simultaneously measure the mechanical properties of tissues in the forearm and the torque applied by the wrist joint during isometric tasks. We measured shear wave speed of thirteen forearm muscles via MRE in a series of contractile states and wrist postures and fit these outputs to a force estimation algorithm based on a musculoskeletal model.<br />Results: Shear wave speed changed significantly upon several factors, including whether the muscle was recruited as an agonist or antagonist (p = 0.0019), torque amplitude (p = <0.0001), and wrist posture (p = 0.0002). Shear wave speed increased significantly during both agonist (p = <0.0001) and antagonist (p = 0.0448) contraction. Additionally, there was a greater increase in shear wave speed at greater levels of loading. The variations due to these factors indicate the sensitivity to functional loading of muscle. Under the assumption of a quadratic relationship between shear wave speed and muscle force, MRE measurements accounted for an average of 70% of the variance in the measured joint torque.<br />Conclusion: This study shows the ability of MM-MRE to capture variations in individual muscle shear wave speed due to muscle activation and presents a method to estimate individual muscle force through MM-MRE derived measurements of shear wave speed.<br />Significance: MM-MRE could be used to establish normal and abnormal muscle co-contraction patterns in muscles of the forearm controlling hand and wrist function.
Details
- Language :
- English
- ISSN :
- 1558-2531
- Volume :
- 70
- Issue :
- 11
- Database :
- MEDLINE
- Journal :
- IEEE transactions on bio-medical engineering
- Publication Type :
- Academic Journal
- Accession number :
- 37279119
- Full Text :
- https://doi.org/10.1109/TBME.2023.3283185