Non-linear Analysis of EMG Signals

Electromyography (EMG) is a common technique for the analysis of muscle contraction. Nonetheless, its interpretation is still far from being clear. Many musculoskeletal models try to implement information about muscle activation using EMG signals, but the results are not always reliable. The reason is that the relation between the muscle activation and the muscle contraction is not linear and typical EMG descriptors, like the root mean square, do not properly describe the activation of the muscle or its contraction.

The current project aims to apply non-linear analysis techniques to the interpretation of EMG. Surrogates and nonlinear prediction error for the study of non-linear signals will be implemented.

The study will use the data extracted during the BYMBOS project for the analysis of physical and mental stress in the students of UPF.

 

 

Mandatory courses: Advanced Biosignal Analysis (https://www.upf.edu/web/cbem/advanced-biosignal-analysis)

BYMBOS: https://www.upf.edu/web/bymbos

 [1] Tassani, S., Font-Llagunes, J. M., González Ballester, M. Á., & Noailly, J. (2019). Muscular tension significantly affects stability in standing posture. Gait and Posture, 68, 220–226. https://doi.org/10.1016/j.gaitpost.2018.11.034

 [2] Tassani, S., Chaves, P., Beardsley, M., Vujovic, M., Ramírez, J., Mendoza, J., Portero Tresserra, M., Gonzalez Ballester, M. A., & Hernandez-Leo, D. (2024). Breathing, Postural Stability, and Psychological Health: A Study to Explore Triangular Links. Frontiers in Bioengineering and Biotechnology.

 

Supervisor: Simone Tassani