Theses and Dissertations at Montana State University (MSU)
Permanent URI for this collectionhttps://scholarworks.montana.edu/handle/1/733
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Item Practicality and usability of high-density surface electromyography for lower limb prosthesis control(Montana State University - Bozeman, College of Engineering, 2022) Christensen, Fred Wallace; Chairperson, Graduate Committee: Corey PewSurface electromyography (sEMG) presents a pathway for prosthesis control but is prone to excess noise and signal corruption due to displacement. High Density Surface Electromyography (HDsEMG), which covers the same area as Traditional sEMG with multiple electrode channels as opposed to one channel, presents a way to overcome these challenges. Seven healthy participants were recruited and performed several activities of daily living with both Traditional sEMG and HDsEMG sensors on their Rectus Femoris, Biceps Femoris, Vastus Lateralis, and Semitendinosus muscles. These sensors were placed in both optimal locations over the muscle belly and in a location 1 cm distally from that optimal placement to simulate sensor displacement with use. From the data collected, four signals were created: a Traditional sEMG signal, the single HDsEMG signal with the highest signal-to-noise ratio (SNR) (Best Signal), a time mean of all HDsEMG signals (Composite Signal), and a time mean of all HDsEMG signals with SNR values greater than 2 dB (Threshold Signal). All signals' values for SNR, root-mean-squared means (RMS), DP ratio, and Omega ratio were compared in both optimal and displaced conditions. Phase lag and power domain similarity were used to assess response to displacement. Threshold mean and straight mean signals were identical in most values. The best signal displayed highest SNR, with the composite signal displaying second highest, and sEMG displaying lowest. These differences were more pronounced in extensor muscles in activities that involved large amounts of knee movements. sEMG signals displayed higher relative RMS values, as well as higher DP values. sEMG displayed statistically higher, but numerically similar Omega values. sEMG displayed a greater agreement between optimal and displaced signals in the frequency domain. Similarity was more dependent on activity type than signal type. Phase lag was determined to not be relevant. HDsEMG was proved to have potential for improved prosthesis control.