Ossel, Mike (2025) Design of an improved EMG measuring system. Master's Thesis / Essay, Biomedical Engineering.
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Abstract
Proper control is a key element in the use of myoelectric prosthetics. Factors such as weak muscles, noisy signals or muscle crosstalk can contribute to a reduction in signal detection, reducing the accuracy and quality of prosthetic control. This makes it more difficult to use a prosthesis, leading to users rejecting their usage and losing the benefit these tools provide. The main goal of this research was to create a new EMG signal processing algorithm for muscle onset detection, removing the influences of noise and muscle crosstalk, allowing for better prosthetic control. Two processing techniques were combined and used to process the EMG signals of both the biceps and triceps muscles of a prosthetic user, to attempt and improve the obtained activation sequence. The obtained signals were preprocessed using the highly modifiable Extended Generalized Teager-Kaiser Energy (EGTKE) operator. The EGTKE has previously been used in the detection of weaker signals and shows promise in the field of prosthetic control. The EGTKE response was processed using an morphological close operator (MCO), followed by a morphological open operator (MOO) to filter out any remaining onset artifacts. The implemented algorithm shows promise in regards to noise filtering, obtaining a clear activation response that remains largely unaffected by noise. Future research should focus on further improvements of the algorithm by performing a optimization study and comparison tests with different methods.
| Item Type: | Thesis (Master's Thesis / Essay) |
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| Supervisor name: | Roossien, C.C. and Kottapalli, A.G.P. |
| Degree programme: | Biomedical Engineering |
| Thesis type: | Master's Thesis / Essay |
| Language: | English |
| Date Deposited: | 20 Feb 2025 07:37 |
| Last Modified: | 20 Feb 2025 07:37 |
| URI: | https://fse.studenttheses.ub.rug.nl/id/eprint/34758 |
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