The limitations of conventional surface electromyography (sEMG) cause it to be unsuitable for use with the deep and compact muscles of the forearm. However, while source separation and localization techniques have been extensively explored to identify active sources in the brain using electroencephalography (EEG) signals, these techniques have not been adapted for identifying active sources in muscles using sEMG signals, despite being of a similar premise. Here, we perform an experiment to explore the capabilities of conventional EEG single-dipole localization techniques to localize the extensor digitorum and extensor indicis when selectively activated. The localization methodology consists of separating the raw sEMG signals using independent component analysis (ICA), estimating a physics-based forward model, and then correlating the obtained lead-field matrix with the ICA mixing matrix. The results show that single-dipole localization is not suitable for describing the active sources of muscles.
['Becky Su', 'Shouhei Shirafuji', 'Tomomichi Oya', 'Yousuke Ogata', 'Tetsuro Funato', 'Natsue Yoshimura', 'Luca Pion-Tonachini', 'Scott Makeig', 'Kazuhiko Seki', 'Jun Ota']
Source separation and localization of individual superficial forearm extensor muscles using high-density surface electromyography