On the Methodological Implications of Extracting Muscle Synergies from Human Locomotion

Abstract

We investigated the influence of three different high-pass (HP) and low-pass (LP) filtering conditions and a Gaussian (GNMF) and inverse-Gaussian (IGNMF) non-negative matrix factorization algorithm on the extraction of muscle synergies from myoelectric signals during human walking and running. To evaluate the effects of signal recording and processing on the outcomes, we analyzed the intraday and interday computation reliability. Results show that the IGNMF achieved a significantly higher reconstruction quality and on average needs one less synergy to sufficiently reconstruct the original signals compared to the GNMF. For both factorizations, the HP with a cut-off frequency of 250[Formula: see text]Hz significantly reduces the number of synergies. We identified the filter configuration of fourth order, HP 50[Formula: see text]Hz and LP 20[Formula: see text]Hz as the most suitable to minimize the combination of fundamental synergies, providing a higher reliability across all filtering conditions even if HP 250[Formula: see text]Hz is excluded. Defining a fundamental synergy as a single-peaked activation pattern, for walking and running we identified five and six fundamental synergies, respectively using both algorithms. The variability in combined synergies produced by different filtering conditions and factorization methods on the same data set suggests caution when attributing a neurophysiological nature to the combined synergies.

Modular organization of murine locomotor pattern in the presence and absence of sensory feedback from muscle spindles

“…using the classical Gaussian NMF algorithm (Lee & Seung, ; Santuz et al . , , b ). The code is available at Zenodo (https://doi.org/10.5281/zenodo.2588332), together with some example data.…”

“…; Santuz et al . ) matrix H contained the time‐dependent coefficients of the factorization with dimensions r × n , where the number of rows r represents the minimum number of synergies necessary to satisfactorily reconstruct the original set of signals V . The motor modules (Gizzi et al .…”

“…; Santuz et al . ). Motor modules and motor primitives are, together, a compact representation of the modular organization of the locomotor pattern.…”

“…; Santuz et al . ), and time‐dependent coefficients, also called motor primitives (Dominici et al . ; Santuz et al .…”

Modular control during incline and level walking in humans

“…stance and swing phase) were obtained from the pressure plate. The touchdown and toe-off were determined from the ground reaction forces using a validated custom post-processing algorithm (Santuz et al, 2017), where the touchdown was identified as the first non-zero pressure matrix after the last toe-off. In addition to the contact times, the pressure data were used to quantify step lengths, cadence, vertical ground reaction forces (VGRFs) and total impulse of the stance phase for the gait cycles.…”