This study introduces an advanced computational model for simulating surface electromyography (sEMG) signals during muscle contractions. The model integrates five elements that simulate the chain of processes from motor intention to voltage variation...
IEEE transactions on neural networks and learning systems
May 2, 2025
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,...
Amyotrophic lateral sclerosis (ALS) is a progressive neurodegenerative disorder that leads to motor neuron degeneration, muscle weakness, and respiratory failure. Despite ongoing research, effective treatments for ALS are limited. This study aimed to...
IEEE journal of biomedical and health informatics
Mar 6, 2025
Accurate control over individual fingers of robotic hands is essential for the progression of human-robot interactions. Accurate prediction of finger forces becomes imperative in this context. The state-of-the-art neural decoders can extract neural s...
Despite the advances in bionic reconstruction of missing limbs, the control of robotic limbs is still limited and, in most cases, not felt to be as natural by users. In this study, we introduce a control approach that combines robotic design based on...
Amyotrophic lateral sclerosis (ALS) is a fatal neurodegenerative disease affecting motor neurons. Although genes causing familial cases have been identified, those of sporadic ALS, which occupies the majority of patients, are still elusive. In this s...
Journal of electromyography and kinesiology : official journal of the International Society of Electrophysiological Kinesiology
Dec 19, 2024
This study proposed a U-Net based partial convolutional time-domain model for a real-time high-density surface electromyography (HD-sEMG) decomposition. The model combines U-Net and a separation block containing partial convolution, aiming to efficie...
IEEE transactions on neural networks and learning systems
Sep 3, 2024
To overcome the energy efficiency bottleneck of the von Neumann architecture and scaling limit of silicon transistors, an emerging but promising solution is neuromorphic computing, a new computing paradigm inspired by how biological neural networks h...
IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
Aug 26, 2024
Sarcopenia is a comprehensive degenerative disease with the progressive loss of skeletal muscle mass with age, accompanied by the loss of muscle strength and muscle dysfunction. Individuals with unmanaged sarcopenia may experience adverse outcomes. P...
Join thousands of healthcare professionals staying informed about the latest AI breakthroughs in medicine. Get curated insights delivered to your inbox.