Ranjan, Alok (2020) Do muscle synergies in the arm change when learning to use a multi-articulate pattern recognition controlled prosthetic hand? Master's Thesis / Essay, Biomedical Engineering.
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Abstract
Learning to use an advanced pattern recognition (PR) based myoelectric prosthesis implies learning to produce high-quality electromyogram (EMG) patterns with distinct, not too variable and highly reliable features. Significant improvements in feature space post-learning is reported in multiple studies, as a result, change in feature space is hypothesized to correlate with the improved performance. Moreover, to make motor learning a modular and efficient experience, it is important that we understand the underlying mechanisms of EMG pattern generation and provide a reasoning for the increase in performance. Muscle synergies that are defined as proportional activation of a group of muscles are proposed to be interneuronal networks involve in controlling the muscles and are organized at the level of spinal cord. As per, activation in one muscle in a synergy entails about the activations of other muscles in the group. Hence, muscle synergies can serve as primitives of motor control. Linear combination of muscle synergies and their activation coefficients are capable of describing complex forces and motion patterns in reduced dimensions. We used this information of muscle synergies and activation coefficients to look for the change in them with user learning.....
| Item Type: | Thesis (Master's Thesis / Essay) |
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| Supervisor name: | Verkerke, G.J. and Bongers, R.M. |
| Degree programme: | Biomedical Engineering |
| Thesis type: | Master's Thesis / Essay |
| Language: | English |
| Date Deposited: | 17 Aug 2020 20:48 |
| Last Modified: | 17 Aug 2020 20:48 |
| URI: | https://fse.studenttheses.ub.rug.nl/id/eprint/23124 |
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