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Assessing a non-invasive approach to detect myopathy in children

This 12-month grant by Dr Eduardo Martinez-Valdes focuses on testing the possibility of detecting and monitoring congenital myopathy without the use of needles.
Principal Investigator
Dr Eduardo Martinez-Valdes
University of Birmingham
Official title
Multi-electrode high-density surface electromyography for detection of myopathy in children
12 months
Total cost


Myopathies are conditions where changes in the muscle cells make them less able to contract. All these forms of congenital muscular dystrophy lead to muscle weakness and a decrease of muscle tone in early childhood. Later in life they are sometimes associated with delayed motor development and speech and learning difficulties. Myopathies in children are commonly diagnosed through a process called concentric needle electromyography (CNEMG). In this process, the electric potential generated by muscle cells when these cells are electrically or neurologically activated is analysed. However, despite being invasive and uncomfortable for the children, only a small area can be screened, which can affect the accuracy of the measurements. Dr Eduardo Martinez-Valdes and colleagues propose to utilise a new electromyography technique called high-density surface electromyography (HDEMG), which doesn’t use needles and should be able to screen larger areas and therefore be more accurate.

What are the aims of the project?

This project aims to compare the results obtained from CNEMG and HDEMG, to compare the levels of discomfort children experience during both recordings, as well as explore whether HDEMG is more affective at diagnosing children compared to CNEMG.

Why is this research important?

An accurate diagnosis of myopathies in children is essential for managing their symptoms early. However, the diagnosis involves an invasive method, which causes a lot of discomfort in children. Having an alternative, the non-invasive diagnostic approach will make the diagnosis of myopathy in children much more bearable and, importantly, more accurate.

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