Wearable electromyographic device and system and methods for motion decoding of body parts

A computer-implemented method of training a neural network for generating upper or lower limb motion control signals to operate a virtual, robotic or prosthetic upper or lower limb, comprising providing or receiving, at a neural network, electromyographic data and associated kinematic upper or lower limb target data provided as a plurality of data chunks or blocks, and processing the plurality of data chunks or blocks to carrying out training of the neural network based on the plurality of data chunks or blocks; wherein each data chunk or block comprises a plurality of channel window data extracts and kinematic upper or lower limb target data associated with each channel window data extract; and optimizing the neural network architecture and hyperparameters using an optimization algorithm to provide a pretrained neural network for generating upper limb distal extremity motion control signals.