Investigation of Perceptual-Motor Behavior Across the Expert Athlete to Disabled Patient Skill Continuum can Advance Theory and Practical Application

Unique behavioral strategies in visuomotor learning: Hope for the non-learner

The existence of individual differences in motor learning capability is well known but the behaviors or strategies that contribute to this variability have been vastly understudied. What performance characteristics distinguish an expert level performer from individuals who experience little to no success, those labeled non-learners? We designed a rule-based visuomotor task which requires identification (discovery) and then exploitation of specific explicit and implicit task components that requires a specific movement pattern, the task rule, for goal achievement. When participants first attempt the task, they are informed about the goal, but are naïve to the task rule. Therefore, the purpose of this experiment is to determine how acquisition of both implicit and explicit task components, the inherent elements of the task rule, reveals differing strategies associated with performance and task success. We test the hypothesis that an examination of performance will reveal sub-groups with varying levels of success. Further, for each subgroup, we expect to find a unique relationship between visual Time-in-Target feedback (a measure of success) and subsequent updating of each task component. Out of 32 non-disabled adults, we identified three distinct sub-groups: (Low Performer/Non-Learner (LP, N = 9), Moderate Performer (MP, N = 12) and High Performer (HP, N = 11)). A quantitative analysis of behavioral patterns reveals three findings: First, the LP sub-group demonstrated significantly lower task success which was associated with difficulty identifying the explicit component of the task. Second, the HP sub-group acquired the two task components in parallel over practice. Third, when both explicit and implicit component performance is plotted across sub-groups, a task component continuum emerges that seamlessly progresses from low to moderate to high performer groups. An exploratory analysis reveals that self-reported level of prior lifetime accumulation of video game and physical activity experience is a significant predictor of individual task performance (R² = 0.50). In summary, what appears to be a key distinction between varying levels of human rule-based motor learning is the process by which feedback is used to update performance of inherent elements of the task rule. Evidence of a performance continuum and limited prior experience suggests that Low Performer/Non-Learners are generally inexperienced with these kinds of tasks, although the role of genetics and other innate learning capabilities in visuomotor learning is still largely unknown. These findings provoke new research directions toward probing the differential performance strategies associated with expertise and the development of interventions aimed to convert non-learners into learners.

The Effect of Robotic Assisted Gait Training With Lokomat® on Balance Control After Stroke: Systematic Review and Meta-Analysis

Introduction: Disturbances of balance control are common after stroke, affecting the quality of gait and increasing the risk of falls. Because balance and gait disorders may persist also in the chronic stage, reducing individual independence and participation, they represent primary goals of neurorehabilitation programs. For this purpose, in recent years, numerous technological devices have been developed, among which one of the most widespread is the Lokomat®, an actuated exoskeleton that guide the patient's limbs, simulating a symmetrical bilateral gait. Preliminary evidence suggests that beyond gait parameters, robotic assisted gait training may also improve balance. Therefore, the aim of this systematic review was to summarize evidence about the effectiveness of Lokomat® in improving balance in stroke patients.

Methods: Randomized controlled trials published between January 1989 and August 2020, comparing Lokomat® training to conventional therapy for stroke patients, were retrieved from seven electronic databases. Balance, assessed by means of validated clinical scales, was considered as outcome measure. The Physiotherapy Evidence Database (PEDro) scale was used to evaluate the methodological quality of the studies. The study protocol was registered on PROSPERO (no. CRD42020197531).

Results: After the removal of the duplicates, according to the inclusion criteria, 13 studies were selected, involving 445 subacute or chronic stroke patients. Eleven papers contributed to three meta-analyses. Favorable results for recovery of balance in stroke survivors treated with Lokomat® were shown using Timed Up and Go (pooled mean difference = −3.40, 95% CI −4.35 to −2.44; p < 0.00001) and Rivermead Mobility Index as outcome measures (pooled mean difference = 0.40, 95% CI 0.26–0.55; p < 0.00001). Inconclusive results were found when balance was measured by means of the Berg Balance Scale (pooled mean difference = 0.17, 95% CI −0.26 to 0.60; p = 0.44).

Conclusions: Overall, most studies have shown beneficial effects of Lokomat® on balance recovery for stroke survivors, at least comparable to conventional physical therapy. However, due to the limited number of studies and their high heterogeneity, further research is needed to draw more solid and definitive conclusions.

Effects of mirror training on motor performance in healthy individuals: a systematic review and meta-analysis

Objective

Mirror training (MTr) is a rehabilitation technique for patients with neurological diseases. There is no consensus on its effects on motor function in healthy individuals. This systematic review and meta-analysis considers the effects of MTr on motor function in healthy individuals.

Design

This is a systematic review and meta-analysis.

Data sources

We searched six databases for studies assessing the effects of MTr on motor function in healthy individuals, published between January 1995 and December 2018. The Cochrane risk of bias was used to assess the quality of the studies. A meta-analysis was conducted with narrative synthesis.

Eligibility criteria for selecting studies

English-language randomised controlled trials reporting the behavioural results in healthy individuals were included.

Results

Fourteen randomised controlled trials involving 538 healthy individuals were eligible. Two short-term studies showed MTr was inferior to passive vision pattern (standardised mean difference 0.57 (95% CI 0.06 to 1.08), I²=0%, p=0.03). The methods varied and there is limited evidence supporting the effectiveness of MTr compared with three alternative training patterns, with insufficient evidence to support analyses of age, skill level or hand dominance.

Conclusion

The limited evidence that MTr affects motor performance in healthy individuals is weak and inconsistent among studies. It is unclear whether the effects of MTr on motor performance are more pronounced than the direct vision pattern, passive vision pattern or action observation. Further studies are needed to explore the short-term and long-term benefits of MTr and its effects on motor learning in healthy individuals.

PROSPERO registration number

CRD42019128881.

Exoskeleton and End-Effector Robots for Upper and Lower Limbs Rehabilitation: Narrative Review

Recovery of upper and lower limbs function is essential to reach independence in daily activities in patients with upper motor neuron syndrome (UMNS). Rehabilitation can provide a guide for motor recovery influencing the neurobiology of neuronal plasticity providing controlled, repetitive, and variable patterns. Increasing therapy dosage, intensity, number of repetition, execution of task-oriented exercises, and combining top-down and bottom-up approaches can promote plasticity and functional recovery. Robotic exoskeletons for upper and lower limbs, based on the principle of motor learning, have been introduced in neurorehabilitation. In this narrative review, we provide an overview of literature published on exoskeleton devices for upper and lower limb rehabilitation in patients with UMNS; we summarized the available current research evidence and outlined the new challenges that neurorehabilitation and bioengineering will have to face in the upcoming years. Robotic treatment should be considered a rehabilitation tool useful to generate a more complex, controlled multisensory stimulation of the patient and useful to modify the plasticity of neural connections through the experience of movement. Efficacy and efficiency of robotic treatment should be defined starting from intensity, complexity, and specificity of the robotic exercise, that are related to human-robot interaction in terms of motion, emotion, motivation, meaning of the task, feedback from the exoskeleton, and fine motion assistance. Duration of a single session, global period of the treatment, and the timing for beginning of robotic treatment are still open questions. There is the need to evaluate and individualize the treatment according to patient's characteristics. Robotic devices for upper and lower limbs open a window to define therapeutic modalities as possible beneficial drug, able to boost biological, neurobiological, and epigenetic changes in central nervous system. We need to implement large and innovative research programs to answer these issues in the near future.