Myoelectric co-adaptation: stochastic and chaotic, yet describable
| dc.contributor.advisor | Scheme, Erik | |
| dc.contributor.advisor | Sensinger, Jon | |
| dc.contributor.author | Al-Tahir, Ishtar | |
| dc.date.accessioned | 2023-03-01T16:41:17Z | |
| dc.date.available | 2023-03-01T16:41:17Z | |
| dc.date.issued | 2021 | |
| dc.date.updated | 2023-03-01T15:03:04Z | |
| dc.description.abstract | Myoelectric control systems have advanced over decades, but their performance remains a challenge. Adaptive algorithms have emerged as a possible solution; however, the user is also always learning, causing the resulting system's performance to sometimes be subpar and even unstable. Most studies approximate these co-adaptive systems as combinations of deterministic and stochastic linear systems. Instead, we propose that chaos, a subtype of nonlinear dynamical systems, is required to explain the intermittent performance of myoelectric control systems. Slight, unknown, changes to a chaotic system can shift its dynamics between stable and unstable. In this work, a 10-day co-adaptive myoelectric control experiment was designed to explore this chaotic behaviour. Poincaré mapping, a technique used to visualize chaos, was used to observe how changes to experimental parameters influence the stability of co-adaptive systems and user learning. A better understanding of the dynamics of co-adaptive human-machine interfaces may enable the design and control of more robust systems in the future. | |
| dc.description.copyright | ©Ishtar Al-Tahir, 2021 | |
| dc.description.note | Electronic only. | |
| dc.format | text/xml | |
| dc.format.extent | xii, 95 pages | |
| dc.format.medium | electronic | |
| dc.identifier.uri | https://unbscholar.lib.unb.ca/handle/1882/14330 | |
| dc.language.iso | en_CA | |
| dc.publisher | University of New Brunswick | |
| dc.rights | http://purl.org/coar/access_right/c_abf2 | |
| dc.subject.discipline | Electrical and Computer Engineering | |
| dc.title | Myoelectric co-adaptation: stochastic and chaotic, yet describable | |
| dc.type | master thesis | |
| thesis.degree.discipline | Electrical and Computer Engineering | |
| thesis.degree.fullname | Master of Science in Engineering | |
| thesis.degree.grantor | University of New Brunswick | |
| thesis.degree.level | masters | |
| thesis.degree.name | M.Sc.E. |
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