A Multidataset Characterization of Window-Based Hyperparameters for Deep CNN-Driven sEMG Pattern Recognition

The control performance of myoelectric prostheses would not only depend on the feature extraction and classification algorithms but also on interactions of dynamic window-based hyperparameters (WBHP) used to construct input signals. However, the relationship between these hyperparameters and how the...

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Veröffentlicht in:	IEEE transactions on human-machine systems 2024-02, Vol.54 (1), p.131-142
Hauptverfasser:	Kulwa, Frank, Zhang, Haoshi, Samuel, Oluwarotimi Williams, Asogbon, Mojisola Grace, Scheme, Erik, Khushaba, Rami, McEwan, Alistair A., Li, Guanglin
Format:	Artikel
Sprache:	eng
Schlagworte:	Algorithms Artificial neural networks Convolution neural network (CNN) Convolutional neural networks Decoding Electromyography Feature extraction Kernels Myoelectric control Myoelectricity Neural networks Pattern recognition Prostheses Prosthetics surface electromyogram (sEMG) signal upper limb window length window overlap Windows
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