David Amarantini

Accurate assessment of upper-limb movement alterations is a key component of post-stroke follow-up. Motion capture (MoCap) is the gold standard for assessment even in clinical conditions, but it requires a laboratory setting with a relatively complex implementation. Alternatively, inertial measurement units (IMUs) are the subject of growing interest, but their accuracy remains to be challenged. This study aims to assess the minimal detectable change (MDC) between spatiotemporal and quality variables obtained from these IMUs and MoCap, based on a specific protocol of IMU calibration and measurement and on data processing using the dead reckoning method. We also studied the influence of each data processing step on the level of between-system MDC. Fifteen post-stroke hemiparetic subjects performed reach or grasp tasks. The MDC for the movement time, index of curvature, smoothness (studied through the number of submovements), and trunk contribution was equal to 10.83%, 3.62%, 39.62%, and 25.11%, respectively. All calibration and data processing steps played a significant role in increasing the agreement. The between-system MDC values were found to be lower or comparable to the between-session MDC values obtained with MoCap, meaning that our results provide strong evidence that using IMUs with the proposed calibration and processing steps can successfully and accurately assess upper-limb movement alterations after stroke in clinical routine care conditions.

During movement, corticomuscular coherence is a measure of central-peripheral communication, while intermuscular coherence is a measure of the amount of common central drive to the muscles. Although these two measures are modified in stroke subjects, no author has explored a correlation between them, neither in stroke subjects nor in healthy subjects. Twenty-four chronic stroke subjects and 22 healthy control subjects were included in this cohort study, and they performed 20 active elbow extension movements. The electroencephalographic and electromyographic activity of the elbow flexors and extensors were recorded. Corticomuscular and intermuscular coherence were calculated in the time–frequency domain for each limb of stroke and control subjects. Partial rank correlations were performed to study the link between these two variables. Our results showed a positive correlation between corticomuscular and intermuscular coherence only for stroke subjects, for their paretic and non-paretic limbs (P < 0.022; Rho > 0.50). These results suggest, beyond the cortical and spinal hypotheses to explain them, that stroke subjects present a form of simplification of motor control. When central-peripheral communication increases, it is less modulated and more common to the muscles involved in the active movement. This motor control simplification suggests a new way of understanding the plasticity of the neuromuscular system after stroke.