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This master's thesis investigates in what capacity a typical hand-prosthesis classification ANN (Artificial Neural Network) can be deployed on a microcontroller unit. A working, implemented interface is presented along with extra scripts, applications and functions for easy training and testing. Performance of different architectures as well as model-conversion tools are evaluated and compared
