Alignment of magnetic sensing and clinical magnetomyography

Negin Ghahremani Arekhloo, Hossein Parvizi, Siming Zuo, Huxi Wang, Kianoush Nazarpour, Justus Marquetand, Hadi Heidari*

*Corresponding author for this work

Research output: Contribution to journalReview articlepeer-review

Abstract / Description of output

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.
Original languageEnglish
Pages (from-to)1-17
JournalFrontiers in Neuroscience
Publication statusPublished - 18 May 2023

Keywords / Materials (for Non-textual outputs)

  • electromyography
  • magnetomyography
  • motor unit decomposition
  • optically pumped magnetometer
  • tunnel magnetoresistance
  • spintronic sensors
  • superconducting quantum interference devices
  • wearable sensors


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