Alignment of magnetic sensing and clinical magnetomyography

Ghahremani Arekhloo, N., Parvizi, H., Zuo, S., Wang, H., Nazarpour, K., Marquetand, J. and Heidari, H. (2023) Alignment of magnetic sensing and clinical magnetomyography. Frontiers in Neuroscience, 17, 1154572. (doi: 10.3389/fnins.2023.1154572)

[img] Text
296625.pdf - Published Version
Available under License Creative Commons Attribution.



Neuromuscular diseases are a prevalent cause of prolonged and severe suffering for patients, and with the global population aging, it is increasingly becoming a pressing concern. To assess muscle activity in NMDs, clinicians and researchers typically use electromyography (EMG), which can be either non-invasive using surface EMG, or invasive through needle EMG. Surface EMG signals have a low spatial resolution, and while the needle EMG provides a higher resolution, it can be painful for the patients, with an additional risk of infection. The pain associated with the needle EMG can pose a risk for certain patient groups, such as children. For example, children with spinal muscular atrophy (type of NMD) require regular monitoring of treatment efficacy through needle EMG; however, due to the pain caused by the procedure, clinicians often rely on a clinical assessment rather than needle EMG. Magnetomyography (MMG), the magnetic counterpart of the EMG, measures muscle activity non-invasively using magnetic signals. With super-resolution capabilities, MMG has the potential to improve spatial resolution and, in the meantime, address the limitations of EMG. This article discusses the challenges in developing magnetic sensors for MMG, including sensor design and technology advancements that allow for more specific recordings, targeting of individual motor units, and reduction of magnetic noise. In addition, we cover the motor unit behavior and activation pattern, an overview of magnetic sensing technologies, and evaluations of wearable, non-invasive magnetic sensors for MMG.

Item Type:Articles
Additional Information:This work was partially supported by EPSRC projects EP/X525716/1, EP/X034690/1, and EP/R004242/2. The works of NG were supported by the University of Glasgow Scholarship.
Glasgow Author(s) Enlighten ID:Zuo, Dr Siming and Parvizi, Mr Hossein and Ghahremani arekhloo, Negin and Heidari, Professor Hadi and Wang, Mr Huxi
Authors: Ghahremani Arekhloo, N., Parvizi, H., Zuo, S., Wang, H., Nazarpour, K., Marquetand, J., and Heidari, H.
College/School:College of Science and Engineering > School of Engineering > Electronics and Nanoscale Engineering
Journal Name:Frontiers in Neuroscience
Publisher:Frontiers Media
ISSN (Online):1662-4548
Copyright Holders:Copyright © 2023 Ghahremani Arekhloo, Parvizi, Zuo, Wang, Nazarpour, Marquetand and Heidari
First Published:First published in Frontiers in Neuroscience 17: 1154572
Publisher Policy:Reproduced under a Creative Commons License

University Staff: Request a correction | Enlighten Editors: Update this record

Project CodeAward NoProject NamePrincipal InvestigatorFunder's NameFunder RefLead Dept
317683UKRI EPSRC Impact Acceleration Accounts (IAA) 2022 - 2025Christopher PearceEngineering and Physical Sciences Research Council (EPSRC)EP/X525716/1ENG - Systems Power & Energy