Neuromotor disorders negatively affect the sensorimotor system, limiting the ability to perform daily activities autonomously. Rehabilitation of upper limb impairments is therefore essential to improve independence and quality of life. In the last two decades, there has been a growing interest in robot-assisted rehabilitation as a beneficial way to promote children recovery process. However, a common understanding of the best drivers of an effective intervention has not been reached yet. With this aim, the current study reviewed the existing literature on robot-assisted rehabilitation protocols for upper extremities in children, with the goal of examining the effects of robotic therapy on their sensorimotor recovery process. A literature search was conducted in several electronic database to identify the studies related to the application of robotic therapy on upper limbs in the pediatric population. We analyzed three reviews and 35 studies that used 14 different robotic devices, and an overview of their characteristics, applications in the clinical setting and results is provided. Besides, the potential benefits of robot-assisted assessment and therapy are discussed to identify the key factors yielding positive outcomes in children. Finally, this review aim to lay the foundations for more effective neuroplasticity-enhancement protocols and elicit insights into robot-based approaches.

In this study, we designed a robot-based method to compute a mechanical impedance model that could extract the viscoelastic properties of the wrist joint. Thirteen subjects participated in the experiment, testing both dominant and nondominant hands. Specifically, the robotic device delivered position-controlled disturbances in the flexion-extension degree of freedom of the wrist. The external perturbations were characterized by small amplitudes and fast velocities, causing rotation at the wrist joint. The viscoelastic characteristics of the mechanical impedance of the joint were evaluated from the wrist kinematics and corresponding torques. Since the protocol used position inputs to determine changes in mean wrist torque, a detailed analysis of wrist joint dynamics could be made. The scientific question was whether and how these mechanical features changed with various grip demands and perturbation velocities. Nine experimental conditions were tested for each hand, given by the combination of three velocity perturbations (fast, medium, and slow) and three hand grip conditions [self-selected grip, medium and high grip force, as percentage of the maximum voluntary contraction (MVC)]. Throughout the experiments, electromyographic signals of the extensor carpi radialis (ECR) and the flexor carpi radialis (FCR) were recorded. The novelty of this work included a custom-made soft grip sensor, wrapped around the robotic handle, to accurately quantify the grip force exerted by the subjects during experimentation. Damping parameters were in the range of measurements from prior studies and consistent among the different experimental conditions. Stiffness was independent of both direction and velocity of perturbations and increased with increasing grip demand. Both damping and stiffness were not different between the dominant and nondominant hands. These results are crucial to improving our knowledge of the mechanical characteristics of the wrist, and how grip demands influence these properties. This study is the foundation for future work on how mechanical characteristics of the wrist are affected in pathological conditions.

In this study, we implemented a protocol for the robotic assessment of the effects of forearm muscle fatigue on wrist dynamics. The potential of robotic devices lies in the possibility to control and measure a wide variety of kinematic and physiological variables, both in repeated sessions over time and during real-time assessments. The implemented fatigue task is tailored to the robotically assessed single-subject maximal force and based on a real-time evaluation of muscle activity. The protocol resulted to be repeatable across sessions evaluated on the same subject and a preliminary step toward a better understanding of which features should be monitored to design a robust and strongly controlled dynamic fatiguing task.

Age-related declines in balance and cognitive function increase fall risk and reduce quality of life in older adults and people with neurological disorders. Studying these changes in unimpaired adults provides a normative reference for identifying pathological deviations. However, most dual-task studies focus on single cognitive tasks and static conditions, specifically during gait, limiting understanding of how cognitive demand interacts with postural control while standing and during dynamic challenges. This study identified cognitive and motor outcomes most sensitive to age-related differences during motor–cognitive dual tasks of varying complexity across static and dynamic balance conditions, accounting for minimal detectable change. Sixty healthy adults performed dual-tasks ranging from simple motor activities to complex cognitive challenges (Stroop Test) while standing on a robotic platform. Cognitive performance (reaction time) and balance outcomes, including trunk and center of pressure (CoP) sway area, were assessed. Reaction time was sensitive to aging, with standardized estimates ranging from 0.014 to 0.036. The highest values occurred in the most demanding dual-task condition, enabling detection of meaningful change over short timeframes. Age effects on balance were modest under static conditions but amplified during dynamic perturbations across all dual tasks. In the SCWT 3 condition, standardized estimates for CoP sway area increased from 0.006 in the static condition to 0.047 in the passive condition, reflecting an approximately eightfold increase in age sensitivity. Trunk sway primarily reflected cognitive load, whereas CoP sway was most sensitive to balance perturbations and exceeded minimal detectable thresholds over only a couple of years. These findings support sensitive task–condition combinations for early detection and monitoring of age-related cognitive and balance decline.