Webinar #4: “Characterization of the neuromuscular system by the analysis of HD EMG signals” by Prof. Boudaoud (UTC)

The fourth webinar in the Expert Talks series will be a talk from Professor Sofiane Boudaoud from the University of Technology of Compiègne.  The Webinar is free to attend for anyone. Register now!

About the talk

The neuromuscular system is a complex multiscale and multiphysic System of Systems (SoS) that is responsible in conveying the neural information into a generated force that will initiate motion of the musculoskeletal system. Classically, electromyography technique is related to the use of few electrodes with no standardized position in clinical applications. Usually, in clinical routine, the surface EMG (sEMG) amplitude is assessed using classical descriptors like ARV and RMS, but with possible meaningless interpretation due to electrode position variability.

A recent technique, High Density surface electromyography (HD-sEMG), overcomes this limitation by providing spatial activation maps or images of the muscle contraction using a surface electrode grid. It opens the door to more sophisticated signal analysis that takes into account this spatial representation and increases to robustness of the obtained results. Through the webinar, recent works will be presented to illustrate the powerness of this technique, using TMSi devices (REFA System), for deeper investigation of the neuromuscular system.

About the speaker

Since 2007, Sofiane Boudaoud is at the Biomechanics and Biomedical Engineering laboratory (BMBI lab, Link) at the University of Technology of Compiègne (UTC), France as assistant then associate professor in biomedical signal processing in 2014. He received the Ph.D. degree from the University of Nice-Sophia Antipolis, France, in signal processing in 2006 after master degrees in electrical engineering and in signal processing for telecommunication in 1998 and 2002 respectively.

More recently, in 2019, he reached the grade of full professor in signal processing related to biomedical applications and leads a team in this field. His main research interests are centered on electrophysiological signal analysis and modeling linked to the neuromuscular system using HD-sEMG technology for clinical applications.

References

1. M Al Harrach, S Boudaoud, V Carriou and F Marin. Multi-muscle Force Estimation using Data Fusion and HD-sEMG: an Experimental Study. 4th IEEE ICABME beirut, Lebanon, October 2017.
2. M Al Harrach, S. Boudaoud, V. Carriou, J Laforet, AJ Letocart, JF Grosset, F Marin. Investigation of the HD-sEMG probability density function shapes with varying muscle force using data fusion and shape descriptors. Comp. Biol Med. 2017 Oct 1; 89:44-58.
3. Al Harrach, S. Boudaoud, M. Hassan, F. Ayachi, D. Gamet, J.F. Grosset, and F. Marin. Denoising of HD-sEMG signals using Canonical Correlation Analysis. Medical & Biological Engineering & Computing 2017;55 (3):375-388.
4. Al Harrach, S. Boudaoud, D. Gamet, J.F. Grosset, and F. Marin. “Evaluation of High Order Statistic Trends from HD-sEMG recordings during Ramp Exercise”. 36th IEEE EMBS Conf., Chicago, U.S.A, 2014. September.

About the TMSi Webinar series Expert Talks

TMSi organizes several webinars in the coming period on various applications. The webinars are free of charge and cover a variety of applications you can research using TMSi systems. You may expect talks on a variety of topics, such as clinical applications for high density EMG and EEG. We will announce the talks via our LinkedIn page and website. Registration is free and each session will consist of approximately 30 minutes presentation and 15 minutes discussion, for a total of 45 minutes.