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Table 2 Best performing LSTM network configurations for FOG detection

From: Prediction and detection of freezing of gait in Parkinson’s disease from plantar pressure data using long short-term memory neural-networks

Network or training parameter

Values / Options

LSTM layers (units in each LSTM layer)

2 layers (16 units) and 3 layers (32 units)

Initial learning rate 

0.01

Learning rate decay

Decreases to half, every 5 epochs

Optimizer

Adam optimizer

Loss function

Cross entropy loss function

Batch size

1

Training epochs

30