Congratulations to Daniela S. Oliveira for publishing her first paper!
Congratulations to our Ph.D. student Daniela Souza de Oliveira on the publication of her first paper with the topic of “Neuronal decoding of high-density surface EMG signals: influence of anatomy and synchronization on the number of identified motor units” in the Journal of Neural Engineering.
The methods for decomposing high-density surface electromyography (HD-sEMG) signals in humans show large variability in the number of motor units identified, but the underlying physiology is largely unknown. By extracting volume conductor properties from muscle biopsies, MRI, and ultrasound images, Daniela found out that she could predict the number of identified motor units based on the thickness of the subcutaneous fat layer, the spatial distribution of motor unit locations, and muscle volume. The predictive power decreased with increasing muscle force, so at higher force levels other factors may influence the variability in the number of motor units identified.
Great work by Daniela, and we look forward to her next publication!