Work focusing on the combination of EMG and fMRI in skeletal muscle. / Two commonly used diagnostic techniques for examining muscle function in vivo are functional magnetic resonance imaging (fMRI) and electromyography (EMG). EMG allows for examination of the functional, electrical activity of muscle during force production. Comparatively, fMRI or more specifically blood oxygen level dependant imaging can be applied to visualize muscle activation and recovery post-exercise. It is a combination of oxygenation, metabolism, blood flow and blood volume. The proposed method combines both techniques in simultaneous data acquisition to provide greater muscle physiological information during exercise. Additionally, both techniques are non-invasive making repeated measurements feasible.
EMG hardware filtering was designed and constructed to facilitate EMG measurements alongside MRI scans during simultaneous acquisition. Next, a complex artifact subtraction method called fMRI artifact slice template removal (FASTR) was implemented. With custom scripts and small adaptations to FASTR, it was modified for use with EMG/fMRI, specifically, with a echo planar imaging (EPI) BOLD sequence. Several experiments were then performed to test it's capabilities improving the signal-to-noise ratio (SNR) of the EMG data from 2.8 to 46 in one case.
After EMG hardware and software were developed and implemented, a simple exercise protocol was developed to investigate changes in concurrent BOLD/EMG, recording before, during and following exercise. A linear correlation analyses was performed to compare EMG and BOLD results. A strong correlation between the EMG root-mean-square (RMS) peak amplitude and the length of time to recover back to baseline was noted (r=0.681, n=3).
For future studies, multiple EMG measurements should be applied to improve the amount of information collected during voluntary exercise. Lastly, this technique may have usage with not just BOLD MRI scans, but with various other techniques such as near infrared spectroscopy (NIRS), and diffusion tensor imaging (DTI) in order to further probe muscle physiology. / Thesis / Master of Applied Science (MASc) / Two commonly used methods for detecting disease and injury in muscle are magnetic resonance imaging (MRI), and electromyography (EMG). EMG provides information about the electrical activity of muscle during exercise, while MRI scans give two or three dimensional images of the body. Using these two techniques at the same time, provides the opportunity to obtain greater physiological information of muscle during and after exercise. The goal of this work was to design and create an EMG system that functioned alongside MRI scans. However, combining these two techniques presented several challenges that needed to be solved before this was possible. These issues were resolved and diminished by utilizing specific hardware and software solutions alongside rigorous testing. Additionally, results from the combination of these two techniques have demonstrated there is great potential for future studies. In conclusion, using EMG and MRI together is feasible, and allows for further investigation into muscle physiology.
| Identifer | oai:union.ndltd.org:mcmaster.ca/oai:macsphere.mcmaster.ca:11375/20948 |
| Date | 16 June 2017 |
| Creators | Behr, Michael |
| Contributors | Noseworthy, Michael, Biomedical Engineering |
| Source Sets | McMaster University |
| Language | English |
| Detected Language | English |
| Type | Thesis |
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