Research Article
Wrist EMG Monitoring Using Neural Networks Techniques
Table 1
Features of the BP-ANN model.
| Feature | Description | References |
| Topology | MLP | [23] | Inputs | Vinp | — | Outputs | Vout | — | Hidden layer and neuron | one layer with 25 neurons | [24] | Activation function (input-hidden-output) | Fiden–Ftanh–Ftanh | [25] | Training algorithm | Extended back-propagation | — | Learning parameters | MSE simple | [21] | Cost function | MSE simple | — | Weight update | Batch | [22] | Weight initialization | Haykin heuristic | [26] | Convergence criteria | Epochs (1,000–200,000) | — |
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