The role of muscle synergies and task constraints on upper limb motor impairment after stroke

Abstract

This study explores the role of task constraints over muscle synergies expression in the context of upper limb motor impairment after stroke. We recruited nine chronic stroke survivors with upper limb impairments and fifteen healthy controls, who performed a series of tasks designed to evoke muscle synergies through various spatial explorations. These tasks included an isometric force task, a dynamic reaching task, the clinical Fugl-Meyer (FM) assessment, and a pinch task. Electromyographic data from 16 upper limb muscles were collected during each task, alongside intermuscular coherence (IMC) measurements during the pinch task to assess neuromuscular connectivity. The findings confirm that motor impairment is inversely related to the diversity of muscle synergies, with fewer synergies and more stereotypical synergy structures observed post-stroke. The study further reveals that the nature of motor tasks significantly affects the number of identifiable muscle synergies, with less constrained tasks revealing a broader array of synergies. These findings highlight the importance of carefully selecting motor tasks in the context of clinical research and assessments to understand a patient's motor impairment, thus aiding in developing tailored rehabilitation strategies.

Keywords: FuglmMaeyer; Impairment; Motor control; Muscle synergies; Stroke; Upper limb.

Fig. 1

Experimental setup. (A) Illustration of the participant position and EMG sensor placement (black dots, grey dots are located ventrally), VRF view, and instrumented handle for the static task. A button replaced the handle for the dynamic task (not shown). (B) Screenshot of the VR feedback displayed on the screen, showing the target (light blue) and movable (red) spheres. Each VRF wall was located 100 N away from the centre. (C) Representation of target directions (arrows) for the static and dynamic task from a starting position (dark grey sphere). (D) Pinch task schematic, the participants exerted a concentric force onto a force transducer (centre cuboid) over a ball mount. The participant rested their forearms over the table; the height and pitch of the transducer were adjusted individually

Fig. 2

Average group force traces from the (A) static task and (B) pinch task, and comparison of force coefficient of variation (CV) between the stroke and non-stroke groups. Time is normalised (Norm) across the duration of the task

Fig. 3

Frequency of occurrence of the number of extracted synergies for the stroke (white bottom bars) and non-stroke (top black bars) groups per task

Fig. 4

Scatter plot and linear regression fit of the FM score and the number of synergies for the stroke group in each task. Dashed lines show 95% CI for the regression fit

Fig. 5

Individual (white overlaid bars) and clusters mean of normalised synergies (greyscale bars) for the non-stroke (top) and stroke groups (bottom). Eight synergy clusters (S1–S8) were grouped according to the maximum number of identified synergies across participants for each task and group. Three consecutive cluster analyses allowed the grouping of synergies across tasks and study groups. Letters above the white overlaid bars correspond to each participant ID, as in Table 1. Muscles are labelled in an abbreviated form: superior (ST), middle (MT) and inferior trapezius (IT), supraspinatus (Sup), infraspinatus (Inf), teres minor (TM), serratus anterior (SA), anterior (AD), middle (MD), and posterior deltoid (PD), pectoralis major (PM), long head of biceps brachii (Bic), long head of triceps brachii (Tr), brachioradialis (Brac), extensor carpi radialis (ECR), and flexor carpi radialis (FCR)

Fig. 6

Histograms of cluster similarities (dot product), median value (vertical red line) and average (blue vertical line). Columns from left to right display the non-stroke, stroke and both groups combined similarities for each synergy (S1–S8). The Y-axes of each subplot represent the frequency of occurrence of a bin of the dot product (20 bins). The dot products for each group were calculated from every possible pairing between cluster members (S1– S8). Similarly, the combined dot products were calculated across all tasks and groups (S1– S8)

Fig. 7

Analysis of Inter-Muscular Coherence (IMC). Left panel: IMC results for pinch tasks between the First Dorsal Interosseous (FDI) and Abductor Pollicis Brevis (APB) muscles, comparing non-stroke (solid line) and stroke groups (dashed line). Centre panel: Above-threshold (AT) area under the curve (AUC) for IMC, displaying data points and fitted model (solid red line) along with 95% confidence intervals (dotted lines). Right panel: Mean IMC of stroke participants plotted against Fugl-Meyer (FM) score, with the fitted model and 95% confidence intervals shown

Fig. 8

Relationship between muscle synergies and inter-muscular coherence. Left panel: Area under the curve (AUC) for Inter-Muscular Coherence (IMC) plotted against the number of muscle synergies (MSs) extracted from the Fugl-Meyer (FM) assessment task. Data points are shown alongside the fitted model (solid red line) and 95% confidence intervals (dotted lines). Right panel: Mean above-threshold z-coherence values plotted against the number of muscle synergies, with each data point representing an average from the FM task, accompanied by the fitted trend line and confidence intervals