Conditional Generative Models for Simulation of EMG During Naturalistic Movements

The manuscript has been accepted in IEEE Transactions on Neural Networks and Learning Systems! https://ieeexplore.ieee.org/document/10636282 Numerical models of electromyography (EMG) signals have provided a huge contribution to our fundamental understanding of human neurophysiology and remain a central pillar of motor neuroscience and the development of human–machine interfaces. However, while modern…

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NeuroMotion: Open-source Simulator with Neuromechanical and Deep Network Models to Generate Surface EMG signals during Voluntary Movement

The manuscript has been accepted in PLOS Computational Biology! https://journals.plos.org/ploscompbiol/article?id=10.1371/journal.pcbi.1012257 Neuromechanical studies investigate how the nervous system interacts with the musculoskeletal (MSK) system to generate volitional movements. Such studies have been supported by simulation models that provide insights into variables that cannot be measured experimentally and allow a large number…

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NeuroMotion: Open-source Simulator with Neuromechanical and Deep Network Models to Generate Surface EMG signals during Voluntary Movement

Our new preprint is available online: https://www.biorxiv.org/content/10.1101/2023.10.05.560588 Neuromechanical studies investigate how the nervous system interacts with the musculoskeletal (MSK) system to generate volitional movements. Such studies have been supported by simulation models that provide insights into variables that cannot be measured experimentally and allow a large number of conditions to…

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Conditional Generative Models for Simulation of EMG During Naturalistic Movements

Our new preprint is available online: https://arxiv.org/abs/2211.01856 Numerical models of electromyographic (EMG) signals have provided a huge contribution to our fundamental understanding of human neurophysiology and remain a central pillar of motor neuroscience and the development of human-machine interfaces. However, whilst modern biophysical simulations based on finite element methods are…

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A myoelectric digital twin for fast and realistic modelling in deep learning

Our new article has been published in Nature Communications: https://www.nature.com/articles/s41467-023-37238-w Muscle electrophysiology has emerged as a powerful tool to drive human machine interfaces, with many new recent applications outside the traditional clinical domains, such as robotics and virtual reality. However, more sophisticated, functional, and robust decoding algorithms are required to…

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