Extensors respond faster than flexors for the MCP joints even under the loss of the corticospinal system

Damage in the corticospinal system following stroke produces imbalance between flexors and extensors in the upper extremity including the fingers, eventually leading to flexion-favored postures. The substitution of the reticospinal tract for the damaged corticospinal tract is known to excessively activate flexors of the fingers while the fingers are voluntarily being extended. Here, we questioned whether the cortical source or/and neural pathways of the flexors and extensors of the fingers are coupled and what factor of impairment influences finger movement. In this study, a total of 7 male participants with hemiplegic stroke conducted isometric flexion and extension at the MCP joints in response to auditory tones. We measured activation and de-activation delays of the flexor and extensor of the MCP joints on the paretic side, as well as, force generation and co-contraction between the flexor and extensor. All participants generated greater torque in the direction of flexion (p=0.017). Regarding co-contraction, coupled activation of the extensor is also made during flexion in the similar way to coupled activation of the flexor made during extension. As opposite to our expectation, we observed that during extension, the extensor showed marginally significantly faster activation (p=0.66) while it showed faster de-activation (p=0.038), in comparison to activation and de-activation of the flexor during flexion. But movement smoothness was not affected by those factors. Our results imply that the cortical source and neural pathway for the extensors of the MCP joints are not coupled with those for the flexors of the MCP joints and extensor weakness mainly contributes to the asymmetry between flexors and extensors.

Extensors respond faster than flexors for the MCP joints even under the loss of the corticospinal system

Damage in the corticospinal system following stroke produces imbalance between flexors and extensors in the upper extremity including the fingers, eventually leading to flexion-favored postures. The substitution of the reticospinal tract for the damaged corticospinal tract is known to excessively activate flexors of the fingers while the fingers are voluntarily being extended. Here, we questioned whether the cortical source or/and neural pathways of the flexors and extensors of the fingers are coupled and what factor of impairment influences finger movement. In this study, a total of 7 male participants with hemiplegic stroke conducted isometric flexion and extension at the MCP joints in response to auditory tones. We measured activation and de-activation delays of the flexor and extensor of the MCP joints on the paretic side, as well as, force generation and co-contraction between the flexor and extensor. All participants generated greater torque in the direction of flexion (p=0.017). Regarding co-contraction, coupled activation of the extensor is also made during flexion in the similar way to coupled activation of the flexor made during extension. As opposite to our expectation, we observed that during extension, the extensor showed marginally significantly faster activation (p=0.66) while it showed faster de-activation (p=0.038), in comparison to activation and de-activation of the flexor during flexion. But movement smoothness was not affected by those factors. Our results imply that the cortical source and neural pathway for the extensors of the MCP joints are not coupled with those for the flexors of the MCP joints and extensor weakness mainly contributes to the asymmetry between flexors and extensors.

Kinematic Assessment to Measure Change in Impairment during Active and Active-Assisted Type of Robotic Rehabilitation for Patients with Stroke

Analysis of kinematic features related to clinical assessment scales may qualitatively improve the evaluation of upper extremity movements of stroke patients. We aimed to investigate kinematic features that could correlate the change in the Fugl-Meyer Assessment (FMA) score of stroke survivors through upper extremity robotic rehabilitation. We also analyzed whether changes in kinematic features by active and active-assisted robotic rehabilitation correlated differently with changes in FMA scores. Fifteen stroke patients participated in the upper extremity robotic rehabilitation program, and nine kinematic features were calculated from reach tasks for assessment. Simple and multiple linear regression analyses were used to characterize correlations. Features representing movement speed were associated with changes in FMA scores for the group that used an active rehabilitation robot. In contrast, in the group that used an active-assisted rehabilitation robot, features representing movement smoothness were associated with changes in the FMA score. These estimates can be an important basis for kinematic analysis to complement clinical scales.

Smoothness discriminates physical from motor imagery practice of arm-reaching movements.

Physical practice (PP) and motor imagery practice (MP) lead to the execution of fast and accurate arm movements. However, there is currently no information about the influence of MP on movement smoothness, nor about which performance parameters best discriminate these practices. In the current study, we assessed motor performances with an arm pointing task with constrained precision before and after PP (n= 15), MP (n= 15), or no practice (n= 15). We analyzed gains between Pre- and Post-Test for five performance parameters: movement duration, mean and maximal velocities, total displacements, and the number of velocity peaks characterizing movement smoothness. The results showed an improvement of performance after PP and MP for all parameters, except for total displacements. The gains for movement duration, and mean and maximal velocities were statistically higher after PP and MP than after no practice, and comparable between practices. However, motor gains for the number of velocity peaks were higher after PP than MP, suggesting that movements were smoother after PP than after MP. A discriminant analysis also identified the number of velocity peaks as the most relevant parameter that differentiated PP from MP. The current results provide evidence that PP and MP specifically modulate movement smoothness during arm reaching tasks. This difference may rely on online corrections through sensory feedback integration, available during PP but not during MP.

Quantification of early learning and movement sub-structure predictive of motor performance

Time-to-fall off an accelerating rotating rod (rotarod) is widely utilized to evaluate rodent motor performance. We reasoned that this simple outcome could be refined with additional measures explicit in the task (however inconspicuously) to examine what we call movement sub-structure. Our goal was to characterize normal variation or motor impairment more robustly than by using time-to-fall. We also hypothesized that measures (or features) early in the sub-structure could anticipate the learning expected of a mouse undergoing serial trials. Using normal untreated and baclofen-treated movement-impaired mice, we defined these features and automated their analysis using paw video-tracking in three consecutive trials, including paw location, speed, acceleration, variance and approximate entropy. Spectral arc length yielded speed and acceleration uniformity. We found that, in normal mice, paw movement smoothness inversely correlated with rotarod time-to-fall for the three trials. Greater approximate entropy in vertical movements, and opposite changes in horizontal movements, correlated with greater first-trial time-to-fall. First-trial horizontal approximate entropy in the first few seconds predicted subsequent time-to-fall. This allowed for the separation, after only one rotarod trial, of different-weight, untreated mouse groups, and for the detection of mice otherwise unimpaired after baclofen, which displayed a time-to-fall similar to control. A machine-learning support vector machine classifier corroborated these findings. In conclusion, time-to-fall off a rotarod correlated well with several measures, including some obtained during the first few seconds of a trial, and some responsive to learning over the first two trials, allowing for predictions or preemptive experimental manipulations before learning completion.

Speed but Not Smoothness of Gait Reacts to Rehabilitation in Multiple Sclerosis

Introduction. Improved gait is one of the leading therapy goals in multiple sclerosis. A plethora of clinical timed trials and state-of-the-art technology-based approaches are available to assess gait performance. Objectives. To examine what aspects of gait react to inpatient rehabilitation in MS and which parameters should be best assessed. Design. In this longitudinal study, we examined the performance of 76 patients with MS to shed further light on factors influencing gait, associations between tests, and the reaction to inpatient rehabilitation during an average time span of 16 d. Setting. Private specialist clinic for inpatient neurorehabilitation. Main Outcome Measures. Clinical walk tests (timed 25-foot walk test at normal pace, maximum pace over 10 m or 6 min) and IMU-based measures of movement smoothness. Results. All gait parameters were strongly intercorrelated (all p < 0.05 ), and a model multiple linear regression for the 6MWT revealed short distance velocity (10 m) and movement smoothness as predictors in a strong model ( R 2 adjusted 0.75, p < 0.01 ). A second model with natural pace on short distance and movement smoothness was almost equally strong ( R 2 adjusted 0.71, p < 0.01 ). Patients improved their walking speed ( p < 0.01 ), but not smoothness ( p = 0.08 – 0.12 ), over the course of rehabilitation. Conclusions. Since we were not able to observe improvements in smoothness of gait, we conclude that rehabilitation programs should be adapted to the patient’s physiological capacities in order to allow for such improvements in smoothness of gait. Externally valid gait capacity (6MWT) could be predicted by a single walk for 10 s at natural pace.

Dissociating Sensorimotor Recovery and Compensation During Exoskeleton Training Following Stroke

The quality of arm movements typically improves in the sub-acute phase of stroke affecting the upper extremity. Here, we used whole arm kinematic analysis during reaching movements to distinguish whether these improvements are due to true recovery or to compensation. Fifty-three participants with post-acute stroke performed ∼80 reaching movement tests during 4 weeks of training with the ArmeoSpring exoskeleton. All participants showed improvements in end-effector performance, as measured by movement smoothness. Four ArmeoSpring angles, shoulder horizontal (SH) rotation, shoulder elevation (SE), elbow rotation, and forearm rotation, were recorded and analyzed. We first characterized healthy joint coordination patterns by performing a sparse principal component analysis on these four joint velocities recorded during reaching tests performed by young control participants. We found that two dominant joint correlations [SH with elbow rotation and SE with forearm rotation] explained over 95% of variance of joint velocity data. We identified two clusters of stroke participants by comparing the evolution of these two correlations in all tests. In the “Recoverer” cluster (N = 19), both joint correlations converged toward the respective correlations for control participants. Thus, Recoverers relearned how to generate smooth end-effector movements while developing joint movement patterns similar to those of control participants. In the “Compensator” cluster (N = 34), at least one of the two joint correlations diverged from the corresponding correlation of control participants. Compensators relearned how to generate smooth end-effector movements by discovering various new compensatory movement patterns dissimilar to those of control participants. New compensatory patterns included atypical decoupling of the SE and forearm joints, and atypical coupling of the SH rotation and elbow joints. There was no difference in clinical impairment level between the two groups either at the onset or at the end of training as assessed with the Upper Extremity Fugl-Meyer scale. However, at the start of training, the Recoverers showed significantly faster improvements in end-effector movement smoothness than the Compensators. Our analysis can be used to inform neurorehabilitation clinicians on how to provide movement feedback during practice and suggest avenues for refining exoskeleton robot therapy to reduce compensatory patterns.