1 citations · 3 across the 5 of their papers we have counts for
5 papers
Unlocking the Full Potential of High-Density Surface EMG: Novel Non-Invasive High-Yield Motor Unit Decomposition
Agnese Grison, Irene Mendez Guerra, Alexander Kenneth Clarke +3
The decomposition of high-density surface electromyography (HD-sEMG) signals into motor unit discharge patterns has become a powerful tool for investigating the neural control of m…
Learning Cortico-Muscular Dependence through Orthonormal Decomposition of Density Ratios
Shihan Ma, Bo Hu, Tianyu Jia +5
The cortico-spinal neural pathway is fundamental for motor control and movement execution, and in humans it is typically studied using concurrent electroencephalography (EEG) and e…
Quasi-Linear ICA for Motor Unit Decomposition during Dynamic Contractions
Alexander Kenneth Clarke, Dimitrios Halatsis, Agnese Grison +6
Decomposing surface electromyography (EMG) into the spike trains of individual motor neurons is a long-standing inverse problem and a key step toward motor-neuron-driven neural int…
Conditional Generative Models for Simulation of EMG During Naturalistic Movements
Shihan Ma, Alexander Kenneth Clarke, Kostiantyn Maksymenko +4
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…
Deep Metric Learning with Locality Sensitive Angular Loss for Self-Correcting Source Separation of Neural Spiking Signals
Alexander Kenneth Clarke, Dario Farina
Neurophysiological time series, such as electromyographic signal and intracortical recordings, are typically composed of many individual spiking sources, the recovery of which can…