<?xml version="1.0" encoding="UTF-8" standalone="yes"?><oembed><version><![CDATA[1.0]]></version><provider_name><![CDATA[TBI Rehabilitation]]></provider_name><provider_url><![CDATA[https://tbirehabilitation.wordpress.com]]></provider_url><author_name><![CDATA[Kostas Pantremenos]]></author_name><author_url><![CDATA[https://tbirehabilitation.wordpress.com/author/onganalop/]]></author_url><title><![CDATA[[Abstract + References] Movement Quality: A Novel Biomarker Based on Principles of&nbsp;Neuroscience]]></title><type><![CDATA[link]]></type><html><![CDATA[
<h2>Abstract</h2>



<p>A major problem in neurorehabilitation is the lack of objective outcomes to measure movement quality. Movement quality features, such as coordination and stability, are essential for everyday motor actions. These features allow reacting to continuously changing environment or to resist external perturbations. Neurological disorders affect movement quality, leading to functionally impaired movements. Recent findings suggest that the central nervous system organizes motor elements (eg, muscles, joints, fingers) into task-specific ensembles to stabilize motor tasks performance. A method to quantify this feature has been previously developed based on the uncontrolled manifold (UCM) hypothesis. UCM quantifies movement quality in a spatial-temporal domain using intertrial analysis of covariation between motor elements. In this point-of-view article, we first describe major obstacles (eg, the need for group analysis) that interfere with UCM application in clinical settings. Then, we propose a process of quantifying movement quality for a single individual with a novel use of bootstrapping simulations and UCM analysis. Finally, we reanalyze previously published data from individuals with neurological disorders performing a wide range of motor tasks, that is, multi-digit pressing and postural balance tasks. Our method allows one to assess motor quality impairments in a single individual and to detect clinically important motor behavior changes. Our solution may be incorporated into a clinical setting to assess sensorimotor impairments, evaluate the effects of specific neurological treatments, or track movement quality recovery over time. We also recommended the proposed solution to be used jointly with a typical statistical analysis of UCM parameters in cohort studies.</p>



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