Muscle synergies and spinal maps are sensitive to the asymmetry induced by a unilateral stroke

Abstract

BackgroundPrevious studies have shown that a cerebrovascular accident disrupts the coordinated control of leg muscles during locomotion inducing asymmetric gait patterns. However, the ability of muscle synergies and spinal maps to reflect the redistribution of the workload between legs after the trauma has not been investigated so far.MethodsTo investigate this issue, twelve post-stroke and ten healthy participants were asked to walk on a treadmill at controlled speeds (0.5, 0.7, 0.9, 1.1 km/h), while the EMG activity of twelve leg muscles was recorded on both legs. The synergies underlying muscle activation and the estimated motoneuronal activity in the lumbosacral enlargement (L2-S2) were computed and compared between groups.ResultsResults showed that muscle synergies in the unaffected limb were significantly more comparable to those of the healthy control group than the ones in the affected side. Spinal maps were dissimilar between the affected and unaffected sides highlighting a significant shift of the foci of the activity toward the upper levels of the spinal cord in the unaffected leg.ConclusionsMuscle synergies and spinal maps reflect the asymmetry as a motor deficit after stroke. However, further investigations are required to support or reject the hypothesis that the altered muscular organization highlighted by muscle synergies and spinal maps may be due to the concomitant contribution of the altered information coming from the upper part of the CNS, as resulting from the stroke, and to the abnormal sensory feedback due to the neuromuscular adaptation of the patients.

Coordination of muscles to control the footpath during over-ground walking in neurologically intact individuals and stroke survivors

“…For comparisons of mode structure and activation timing between the stroke survivors and healthy controls, NMF was performed using four modes for all the stroke survivors. Pearson’s correlation was used to quantify the similarity of the mode structure (Clark et al 2010) and activation timing (Tropea et al 2013; Coscia et al 2015) between stroke survivors and matched controls. We performed one-sample t test to determine whether stroke survivors’ correlation coefficients are significantly different from the healthy controls.…”

How are Muscle Synergies Affected by Electromyography Pre-Processing?

“…Muscle synergies were extracted here using Factor Analysis (FA) with "varimax" rotation. This algorithm has been shown to be very reliable for muscle synergies extraction [32] and to provide results equivalent to the commonly used NMF algorithm [23,32,59]. The number of extracted factors (muscles synergies i.e., the dimensionality of the muscle activity subspace identified by the algorithm) was chosen based on two alternative criteria:…”

“…In order to compare the synergy weights across preprocessing conditions, for each number of retained synergies (4 or 5 -see results), we calculated the median and absolute median deviation (MAD) of the weights over all the subjects. The number of synergies was kept constant across subjects and conditions to simplify the analyses and allow for direct statistical comparison of weight coefficients as already proposed in other works [21,23,38,52].…”

“…This should be taken into careful consideration when using muscle synergies dimensionality (i.e., number of extracted synergies according to a criterion) e.g. in rehabilitation, to determine the severity of movement impairment and/or to monitor the effect of a rehabilitative treatment [23].…”

“…The muscle synergies concept has been widely used both to explain a variety of motor behaviors (e.g., reaching [5][6][7][8], posture [9], locomotion [10][11][12][13]) and animals (e.g., primate grasping [14] frog jumping [15,16], cats' locomotion [17]), to study pathologies (e.g., to determine age-related [18,19] or pathology-related modifications in muscles co-activations [20] and to predict the degree of impairment of stroke patients [21][22][23][24][25]). Muscle synergies (and factorization methods in general) can also be viewed as a useful tool to reveal underlying patterns in muscle activity that may reflect different levels of neural functions [26,27], to compare performance across subjects [28] and to reduce the input features for a classifier [29,30].…”