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Found 5 papers, 1 papers with code
PerSival: Neural-network-based visualisation for pervasive continuum-mechanical simulations in musculoskeletal biomechanics
Within this work we use a sparse grid surrogate to capture the surface deformation of the m.~biceps brachii in order to train a deep learning model, used for real-time visualisation of the same muscle.
Low-dimensional Data-based Surrogate Model of a Continuum-mechanical Musculoskeletal System Based on Non-intrusive Model Order Reduction
In recent decades, the main focus of computer modeling has been on supporting the design and development of engineering prototyes, but it is now ubiquitous in non-traditional areas such as medical rehabilitation.
High-density magnetomyography is superior to high-density surface electromyography for motor unit decomposition: a simulation study
Individual motor unit firings are currently identified in vivo by decomposing electromyographic (EMG) signals.
Investigating the spatial resolution of EMG and MMG based on a systemic multi-scale model
The spatial selectivity of the MMG components aligned with the muscle fibres and normal to the body surface outperforms the spatial selectivity of surface EMG.
Decoding the Rejuvenating Effects of Mechanical Loading on Skeletal Maturation using in Vivo Imaging and Deep Learning
Here, we present an image-based deep learning approach to quantitatively describe the dynamic effects of short-term aging and adaptive response to treatment in proximal mouse tibia and fibula.
