Feedback of mechanical effectiveness induces adaptations in motor modules during cycling

Abstract

Recent studies have reported evidence that the motor system may rely on a modular organization, even if this behavior has yet to be confirmed during motor adaptation. The aim of the present study is to investigate the modular motor control mechanisms underlying the execution of pedaling by untrained subjects in different biomechanical conditions. We use the muscle synergies framework to characterize the muscle coordination of 11 subjects pedaling under two different conditions. The first one consists of a pedaling exercise with a strategy freely chosen by the subjects (Preferred Pedaling Technique, PPT), while the second condition constrains the gesture by means of a real time visual feedback of mechanical effectiveness (Effective Pedaling Technique, EPT). Pedal forces, recorded using a pair of instrumented pedals, were used to calculate the Index of Effectiveness (IE). EMG signals were recorded from eight muscles of the dominant leg and Non-negative Matrix Factorization (NMF) was applied for the extraction of muscle synergies. All the synergy vectors, extracted cycle by cycle for each subject, were pooled across subjects and conditions and underwent a 2-dimensional Sammon's non-linear mapping. Seven representative clusters were identified on the Sammon's projection, and the corresponding eight-dimensional synergy vectors were used to reconstruct the repertoire of muscle activation for all subjects and all pedaling conditions (VAF > 0.8 for each individual muscle pattern). Only 5 out of the 7 identified modules were used by the subjects during the PPT pedaling condition, while 2 additional modules were found specific for the pedaling condition EPT. The temporal recruitment of three identified modules was highly correlated with IE. The structure of the identified modules was found similar to that extracted in other studies of human walking, partly confirming the existence of shared and task specific muscle synergies, and providing further evidence on the modularity of the motor system.

The Application of Cycling and Cycling Combined with Feedback in the Rehabilitation of Stroke Patients: A Review

“…Figure 3. Visual biofeedback of the instantaneous mechanical effectiveness provided to the subjects in the study of De Marchis et al 80 The circle represents 1 revolution, whereas the red and blue colors represent the instantaneous mechanical effectiveness of the left and right limbs, respectively.…”

“…7,[15][16][17][18][19] Different sources of visual biofeedback were used, such as cycling speed, 15,16,19 EMG activity, 7,17 work, 18,19 mechanical effectiveness, 80 and weight shift. 81 The major characteristics of the biofeedback used in cycling of published studies are summarized in Table 3.…”

Intermuscular coherence contributions in synergistic muscles during pedaling

“…Synergy activation coefficients H were then extracted by using nonnegative reconstruction (Muceli et al 2010;De Marchis et al 2013b) by fixing the average muscle synergies and let only H update at every iteration of the NMF algorithm.…”

A Neural Network Embedded System for Real-time Estimation of Muscle Forces

“…This aspect can be studied evaluating the role of muscle activity [2,3,4] or the power exerted, using different techniques [5]. To this aim a biomechanical model based system, able to predict forces acting on each involved joint, can be adopted with the design of an optimization criterion suited to determine the contribution of each muscle to the overall force [6].…”