Robotic Assistance for Upper Limbs May Induce Slight Changes in Motor Modules Compared With Free Movements in Stroke Survivors: A Cluster-Based Muscle Synergy Analysis

Abstract

Background: The efficacy of robot-assisted rehabilitation as a technique for achieving motor recovery is still being debated. The effects of robotic assistance are generally measured using standard clinical assessments. Few studies have investigated the value of human-centered instrumental analysis, taking the modular organization of the human neuromotor system into account in assessing how stroke survivors interact with robotic set-ups. In this paper, muscle synergy analysis was coupled with clustering procedures to elucidate the effect of human-robot interaction on the spatial and temporal features, and directional tuning of motor modules during robot-assisted movements. Methods: Twenty-two stroke survivors completed a session comprising a series of hand-to-mouth movements with and without robotic assistance. Patients were assessed instrumentally, recording kinematic, and electromyographic data to extract spatial muscle synergies and their temporal components. Patients' spatial synergies were grouped by means of a cluster analysis, matched pairwise across conditions (free and robot-assisted movement), and compared in terms of their spatial and temporal features, and directional tuning, to examine how robotic assistance altered their motor modules. Results: Motor synergies were successfully extracted for all 22 patients in both conditions. Seven clusters (spatial synergies) could describe the original datasets, in both free and robot-assisted movements. Interacting with the robot slightly altered the spatial synergies' features (to a variable extent), as well as their temporal components and directional tuning. Conclusions: Slight differences were identified in the characteristics of spatial synergies, temporal components and directional tuning of the motor modules of stroke survivors engaging in free and robot-assisted movements. Such effects are worth investigating in the framework of a modular description of the neuromusculoskeletal system to shed more light on human-robot interaction, and the effects of robotic assistance and rehabilitation.

Keywords: centroids; directional tuning; muscle synergies; robotic assistance; spatial synergies; stroke; synergy clustering; temporal components.

Figures

Figure 1

Study workflow. Twenty-two stroke survivors were recruited. They were administered the Fugl–Meyer Assessment, then they performed free and robot-assisted repetitions of the HTMM. For each of the two experimental conditions, muscle synergies were extracted using NMF. Each dataset was analyzed with the k-means clustering algorithm, and mean spatial synergies (centroids) were extracted. The two centroid datasets were matched and compared in terms of spatial composition, temporal components, and directional tuning.

Figure 2

The robotic set-up, comprising a Mitsubishi Pa10 robot and a handle with a revolute joint is shown during the execution of the hand-to-mouth movement (split in four frames representing progressive phases of the movement).

Figure 3

Panel (A) shows the nomenclature for kinematic computations. Panel (B) shows the conventions adopted in this study. The shoulder flexion angle is projected in the sagittal plane; 0° indicate no flexion (arm leaning along the body), while 90° indicate the shoulder flexed so that the arm is elevated frontally. The elbow angle is 0° if the arm and forearm are aligned. Positive angles indicate when the forearm is flexed. In panel (C), the conventions for visualization of the results are reported. In respect to panel (B), shoulder flexion angles are ofsetted (+270°). This convention was chosen to facilitate visualization of the movement when considering synergy directional tuning.

Figure 4

Patients' muscle synergies and their temporal components in free HTMM. Rows 1–3 show the composition of the synergies; rows 4–6 show the corresponding temporal components.

Figure 5

Patients' muscle synergies and temporal components in robot-assisted HTMM. Rows 1–3 show the composition of the synergies; rows 4–6 show the corresponding temporal components.

Figure 6

Mean spatial synergies (MSS), matched pairwise by similarity, assessed with the dot product on muscle coefficients, for both free and robot-assisted conditions, with the associated temporal components (TC).

Figure 7

Temporal Components (TC) of muscle synergies, matched pairwise by similarity, for both free and robot-assisted conditions. The mean temporal component is highlighted (light gray plot). Bar graphs show the magnitude (integral) of the mean temporal components, comparing free and robot-assisted conditions. The black histogram highlights the difference between the magnitude of the temporal components in free and robot-assisted conditions.

Figure 8

Mean directional tuning of muscle synergies for each pair of centroids. Each radar plot shows a scatter plot of the activations of each synergy centroid within the workspace, plotted versus shoulder elevation and elbow flexion, respectively, according to the convention illustrated in Figure 2C. When shoulder flexion is indicated, the radar plot should be interpreted as the projection on the sagittal plane, with movements executed by pointing rightwards. When elbow flexion is indicated, its full extension is at 0°. Blue plots indicate shoulder flexion in free movement trials; cyan plots indicate elbow flexion in free movements; red plots indicate shoulder flexion in robot-assisted trials; magenta plots indicate elbow flexion in robot-assisted tracks; squares are plotted to indicate the barycenter of the distribution. The final bar plot summarizes the mean spatial tuning for each of the intrinsic body coordinates considered (shoulder flexion and elbow flexion) and each experimental condition.