Non-linear Analysis of EMG Signals 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 describe properly the activation of the muscle, nor its contraction.

 

The aim of the current project is to apply non-linear analysis techniques to the interpretation of EMG.

The study is developed in the framework of 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

 

Supervisor: Simone Tassani

Co-Supervisor: Ralph G. Andrzejak