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Optimization of surface multi-channel electrode arrays and motor unit extraction in underrepresented populations

Project description

Identifying motor unit behaviour in underrepresented populations

The motor unit (MU) consists of the motor neuron and the muscle fibres it controls. High-density surface electrodes (HDsEMG) and decomposition algorithms (DA) are recent non-invasive methods used to identify MUs. However, current DAs can only analyse MU behaviour in healthy young males, resulting in a knowledge gap in underrepresented populations (URP) such as clinical, female, and obese individuals. Supported by the Marie Skłodowska-Curie Actions programme, the MUDecomp project aims to enhance the current technology of HDsEMG and DA for a more diverse population by identifying limitations in HDsEMG and DA for URPs, adjusting electrode configurations for URPs, and improving DA for individuals across URPs. Adapting this non-invasive technology is a crucial innovation for diagnostic models in clinical populations.

Objective

The motor unit (MU) represents the final common pathway consisting of the motor neuron and all the muscle fibres it innervates. Force is controlled by recruiting MUs or modulating their discharge rate. Traditional MU behaviour investigations use intramuscular electrodes and signal processing which identifies only a few MUs close to the electrode. Recently, High-Density surface electrodes(HDsEMG) allowed for MU identification non-invasively, but it has limitations. Decomposition algorithms (DA) can with validity and reliability identify MUs, but this is primarily in healthy young males. Greater adipose tissue thickness increases signal filtering, leading to a lower amplitude MU action potential which is more difficult to detect with the current DAs. This challenge has left a 'knowledge gap' in the study of MU behaviour in underrepresented populations (URP) (clinical, female, obese). This fellowship aims to optimize the state-of-the-art technology of HDsEMG and DA for a more diverse population. I aim to (1) identify limitations of HD-sEMG and DA in URPs; (2) adapt electrode configurations for URPs, and (3) optimize DA for individuals across URPs. This project is pertinent, as a large sector of the population is not studied, hindering MU behaviour research progression. I will focus on URPs where MU identification is challenging. I will fill this knowledge gap to allow the study of MU behaviour and assessment of all populations. Adapting this non-invasive technology is an important innovation which may be used as a model for diagnosis in clinical populations.
The quality and success of this project are ensured by collaborations between myself and experts in signal processing (my supervisor Dr. Negro) and a company leading in multichannel electrode design. Their knowledge and expertise along with the facilities will guarantee the success of this project. The training will provide me with substantial hard and soft skills to become an independent translational scientist.

Coordinator

UNIVERSITA DEGLI STUDI DI BRESCIA
Net EU contribution
€ 188 590,08
Address
PIAZZA MERCATO 15
25121 Brescia
Italy

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Region
Nord-Ovest Lombardia Brescia
Activity type
Higher or Secondary Education Establishments
Links
Total cost
No data

Partners (1)