This is a continuation project of Modelling of upper limb muscular system using learning based system identification to finalise the last part of the project. The continuation project will focus on real-time testing of the model. NAISS resources are needed to train the model on data measured from participants. The model will then be run on a desktop pc where the participant will perform virtual assessments of prosthetic control. Original proposal text: This project aims to build a model of human’s upper limb muscular system using learning-based system identification. The research work will try to explain the dynamics behind multi-channels EMG signals and the control mechanism behind upper limb muscular system. The outcomes of this project could help us get a better understanding and improve the control of upper limb prosthesis. The used methods are neural state-space identification and graph neural network, etc.