Noninvasive viscoelasticity imaging, or “dynamic elastography”, methods have recently been developed to objectively quantify the local viscoelastic properties of soft tissues by measuring the local propagation velocity of mechanical shear vibrations (e.g. faster velocity indicates stiffer material). But, the existing elastography technologies require a potentially uncomfortable external mechanical stimulation (e.g. vibrations probe) to induce muscle vibrations; and sophisticated and expensive imaging equipments (such as MRI and ultrafast ultrasound elastography), involving complex signal processing, to record and analyze these muscle vibrations. The work in this dissertation lays the foundation for the development of a low cost, passive, non-invasive elastography by analyzing and processing Surface Mechanomyograms (S-MMGs) measured with one dimensional accelerometers from the biceps brachii muscle. Aim 1 of this dissertation focused on the 3-dimensional aspect of vibrations measured by accelerometers on the skin surface above the biceps brachii. While Aim 2 focused on using one-dimensional accelerometers to determine the propagation direction of the propagating S-MMG waves. Using this newly developed knowledge on S-MMG Aim 3 was accomplished, a method to analyze the propagating wave and develop a metric that can track the changes in the muscle was developed, namely, the coherence length. The coherence length was found to significantly increase with increased contraction levels for all seven of the subjects. Overall the results of this study show that the propagation features of S-MMG vibrations reflect the architecture and contraction level of the biceps brachii muscle. Hence S-MMG could potentially be used for monitoring physiological changes of skeletal muscles.
| Identifer | oai:union.ndltd.org:GATECH/oai:smartech.gatech.edu:1853/50139 |
| Date | 24 August 2012 |
| Creators | Archer, Akibi A. A. |
| Contributors | Sabra, Karim |
| Publisher | Georgia Institute of Technology |
| Source Sets | Georgia Tech Electronic Thesis and Dissertation Archive |
| Language | en_US |
| Detected Language | English |
| Type | Dissertation |
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