Processing signals from surface electrode arrays for noninvasive 3D mapping of muscle activity

Real time identification of active regions in muscles from high density surface electromyogram

“…The functions a n ðx; tÞ (referred to as basis waveforms in the following) could be simulated using a model replicating as far as possible the investigated physiological system: for example, the geometry of the tissues could be measured (by ultrasound scanning [22] or MRI [15,16,[18][19][20]23]), their conductivity could be taken from the literature [24,25] and the anatomy of the muscle fibres (positions of the IZ and tendons) could be investigated by preliminary surface EMG recordings [8][9][10][11]. Another possible choice is to measure the surface potential resulting from the activity of a specific region: needle EMG can be recorded from different locations and decomposed in order to identify the activity of single MUs [26]; then the surface response related to each identified MU can be estimated by spike triggered averaging [27], obtaining very selective information on the surface EMG response of the activity of specific muscle regions.…”

“…This method requires the (computationally intensive) decomposition of the surface EMG as a preliminary step, if interference EMG is considered. Sophisticated methods, based on advanced simulations by the finite elements method (FEM), were also proposed to investigate interference EMG [14][15][16][17][18]. More recently, FEM simulations combined with regularization techniques were applied [19][20].…”

“…The localization of sources within the brain was studied extensively from surface electroencephalogram (EEG) [13]. In the field of EMG, some studies have been proposed [14][15][16][17][18][19][20]. The identification of the source of a single MUAP was addressed by considering that the decay of the potential in the transverse direction with respect to the fibres is slower when the MU is deeper [17].…”

Three dimensional innervation zone imaging in spastic muscles of stroke survivors

“…Similar to employing EEG to reconstruct neural activities in the 3D brain space non-invasively in functional brain source imaging [14][15][16][17][18][19][20], high-density sEMG acquires the interference patterns of multiple motor unit action potentials (MUAPs) with a broad coverage, and therefore making possible the tracking of internal activities in deeper muscle regions; yet limited effort has been made to utilize high-density sEMG signals for functional muscle imaging [21][22][23]. It is only until recently that the technique has been employed to identify the 3D location of the IZs in vivo with decomposed MUAPs and electrically elicited M-wave recordings [24,25].…”

Three-Dimensional Innervation Zone Imaging from Multi-Channel Surface EMG Recordings

“…The bioelectrical activity imaging approach was first performed with an exhaustive search method based on a single sinusoidal current source model to localize internal muscle activities from surface EMG recordings. 24 Later, a distributed tripole model was employed to model muscle activities and a generalized Tikhonov regularization approach was utilized to solve the inverse problem to reconstruct internal muscle activities from multi-channel surface EMG signals. 25, 26 …”