Purpose: To examine whether performance improvements in the virtual environment generalize to the natural environment. Study design: we had 64 individuals, 32 of which were individuals with DMD and 32 were typically developing individuals. Methods: The groups practiced two coincidence timing tasks. In the more tangible button-press task, the individuals were required to ‘intercept’ a falling virtual object at the moment it reached the interception point by pressing a key on the computer. In the more abstract task, they were instructed to ‘intercept’ the virtual object by making a hand movement in a virtual environment using a webcam. Results and Conclusions: For individuals with DMD, conducting a coincidence timing task in a virtual environment facilitated transfer to the real environment. However, we emphasize that a task practiced in a virtual environment should have higher rates of difficulties than a task practiced in a real environment.

Cerebral Palsy (CP) presents changes in posture and movement as a core characteristic, which requires multiprofessional clinical treatments during children’s habilitation or rehabilitation. Besides clinical treatment, it is fundamental that professionals use evaluation systems to quantify the difficulties presented to the individual and their families in their daily lives. We aimed to investigate the functional capacity of individuals with CP and the amount of assistance required by the caregiver in day-to-day activities.

Background: Human performance in classical ballet is a research field of growing interest in the past decades. Technology used to acquire data in human movement sciences has evolved, and is specifically being applied to evaluate ballet movements to better understand dancers’ profiles. We aimed to systematically review sensing technologies that were used to extract data from dancers, in order to improve knowledge regarding the performance of ballet movements through quantification.Methods: PubMed, MEDLINE, EMBASE, and Web of Science databases were accessed through 2020. All studies that used motor control tools to evaluate classical ballet movements, and possible comparisons to other types of dance and sports movements were selected. Pertinent data were filled into a customized table, and risk of bias was carefully analyzed.Results: Eighty studies were included. The majority were regarding classical ballet and with pre-professional dancers. Forty-four studies (55%) used two or more types of technology to collect data, showing that motion capture technique, force plates, electromyography, and inertial sensors are the most frequent ways to evaluate ballet movements.Discussion: Research to evaluate ballet movements varies greatly considering study design and specific intervention characteristics. Combining two or more types of technology may increase data reliability and optimize the characterization of ballet movements. A lack of studies addressing muscle–brain interaction in dancers were observed, and given the potential of novel insights, further studies in this field are warranted. Finally, using quantitative tools opens the perspective of defining what is considered an elite dancer.

The present study analyzes the learning in a coincident timing task with force perturbation. We aimed to verify whether a predictable load (constant spring) applied to hand movements could facilitate learning and, thus, performance improvement with respect to movements without any external load and an unpredictable load to perform a coincident timing task with a few number of repetitions (n = 28) under acquisition and transfer phases. The results showed that the group with a predictable load had a significant better performance with lower percentage of errors and smaller time variance in the acquisition and transfer phase. The groups with no load and unpredictable load had a similar performance in the transfer phase. It can be concluded that adding a predictable force to the coincident timing task results in performance improvement. Therefore, learning to reach a target at a correct time could be improved with the application of predictable external loads.

There are many motor control aspects that must be taken into account for the design and application of rehabilitation robots and exoskeletons. In this respect the outcomes from behavioral motor control studies can provide relevant design criteria. In this context, to verify the level of motor learning and adaptation under the influence of mechanical perturbations, we used a coincident timing task. The task consisted of hitting with the hand a virtual target falling on the screen. The movement was performed in the horizontal plane and consisted of an elbow flexion to reach the real marker on a table. Sixteen volunteers were divided into two groups: 1-task without perturbation on the hand and, 2-task with a predictable mechanical perturbation on the hand. Data were analyzed by the percentage of correct responses and the tendency of the correct responses. In order to assess the duration as well as the velocity and acceleration of the movement, inertial sensors were used. The results showed a task performance improvement for group 2 when compared to group 1. Furthermore, group 1 showed a trend to delay on correct responses, while the trend in group 2 was to anticipate on correct responses. These results indicate that a predictable mechanical perturbation during learning this coincident timing task can improve the motor learning process and paves the way to further experiments with the use of an upper limb exoskeleton.