14 research outputs found

    Elbow Extension Predicts Motor Impairment and Performance after Stroke

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    Background and Purpose. Kinematic motion analysis has helped to characterize poststroke reaching strategies with the hemiparetic arm. However, the relationships between reaching strategy and performance on common functional outcome measures remain unclear. Methods. Thirty-five participants were tested for motor performance and motor impairment using the Wolf Motor Function Test (time and functional ability measure) and Fugl-Meyer assessment, respectively. Kinematic motion analysis of a forward reaching paradigm provided potential predictors of reaching strategy including shoulder flexion, elbow extension, and trunk displacement. A stepwise linear regression model with three potential predictors was used in addition to Pearson-product moment correlations. Results. Kinematic analysis of elbow extension predicted performance on both the Wolf Motor Function Test and Fugl-Meyer assessment. Shoulder flexion and trunk displacement did not significantly predict functional or reaching time outcomes. The Wolf Motor Function Test and the Fugl-Meyer assessment were highly correlated. Conclusions. The ability to incorporate elbow extension during reach is a significant predictor of motor performance and hemiparetic arm motor capacity after stroke

    A Clinically Relevant Method of Analyzing Continuous Change in Robotic Upper Extremity Chronic Stroke Rehabilitation

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    Background. Robots designed for rehabilitation of the upper extremity after stroke facilitate high rates of repetition during practice of movements and record precise kinematic data, providing a method to investigate motor recovery profiles over time. Objective. To determine how motor recovery profiles during robotic interventions provide insight into improving clinical gains. Methods. A convenience sample (n = 22), from a larger randomized control trial, was taken of chronic stroke participants completing 12 sessions of arm therapy. One group received 60 minutes of robotic therapy (Robot only) and the other group received 45 minutes on the robot plus 15 minutes of translation-to-task practice (Robot + TTT). Movement time was assessed using the robot without powered assistance. Analyses (ANOVA, random coefficient modeling [RCM] with 2-term exponential function) were completed to investigate changes across the intervention, between sessions, and within a session. Results. Significant improvement (P < .05) in movement time across the intervention (pre vs post) was similar between the groups but there were group differences for changes between and within sessions (P < .05). The 2-term exponential function revealed a fast and slow component of learning that described performance across consecutive blocks. The RCM identified individuals who were above or below the marginal model. Conclusions. The expanded analyses indicated that changes across time can occur in different ways but achieve similar goals and may be influenced by individual factors such as initial movement time. These findings will guide decisions regarding treatment planning based on rates of motor relearning during upper extremity stroke robotic interventions

    A Tablet-Based Tool for Accurate Measurement of Hand Proprioception After Stroke

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    Background and Purpose: Proprioceptive deficits in the hand are common following stroke, but current clinical measurement techniques are too imprecise to detect subtle impairments or small changes. We developed a tablet-based tool to measure static hand proprioception using an adaptive staircase procedure. Methods: In 16 individuals with chronic stroke and age-matched controls, we quantified proprioception at the metacarpophalangeal joint of the index finger using 3 methods: the tablet task, a custom passive movement direction discrimination test (PMDD), and a manual assessment similar to the Fugl-Meyer (F-M) proprioception subsection. Results: The tablet-based measure and the PMDD both identified impaired proprioception in the affected hand relative to the unaffected hand (P = 0.024 and 0.028), and relative to the control group (P = 0.040 and 0.032), while manual assessment did not. The PMDD had a ceiling effect as movement excursions greater than 15^ were not biomechanically feasible. The tablet-based measure and the PMDD detected impaired proprioception in 56% to 75%, and the F-M in only 29%, of patients. PMDD and tablet-based measures were both correlated with primary tactile sensation, but not manual dexterity. Discussion and Conclusions: Both the tablet-based tool and the custom PMDD performed better than manual assessment. The PMDD may be useful when the deficit is mild or assessment of dynamic proprioception is desired. As the tablet-based measure does not have the ceiling effect that is associated with the PMDD, it may be useful with any level of proprioceptive impairment, and may be preferable if testing or clinician training time needs to be minimized, or pain or spasticity is present

    Effects of Motor Cortical Stimulation during Planar Reaching Movement

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    Background: The purpose was to examine the effects of single pulse transcranial magnetic stimulation (TMS) over primary motor cortex delivered at different times during a center-out reaching task in a robot reaching environment. Methods: Eleven right-handed subjects participated. Movement hotspots and thresholds were determined for each subject, and the stimulation intensity was set at 120% of the movement threshold. TMS was delivered at rest and when subjects performed a series of reaching tasks. The 5 different conditions were: no stimulation, sham stimulation, and stimulation at 150, 500, or 1000 ms post go cue. Outcome measures included TMS-evoked movement during rest and in the 150ms condition, trajectory deviations (no stimulation, sham, and 150ms conditions), and peak velocity (PV), path length, reaction time, acceleration time, and deceleration time for all conditions. Results: When TMS was applied at 150 ms, the evoked path lengths were significantly shorter than at rest and had less deviation than the no-stimulation condition (p &lt; 0.05). Peak velocities were lowest during the no-stimulation condition and highest during the 500ms condition (p &lt; 0.05). Path lengths were significantly shorter during the no-stimulation, sham, and 150ms condition compared to the 500ms and 1000ms conditions. Conclusions: TMS applied during the reaction time phase suppressed movements evoked by TMS, decreased trajectory deviations, and shortened path length, while TMS delivered after movement onset increased PV and path length. TMS stimulation may be delivered to enhance movement parameters and potentially facilitate reach training in the robotic rehabilitation environment
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