Robot-mediated therapies enhance the recovery of post-stroke patients with motor deficits. Repetitive and repeatable exercises are essential for rehabilitation following brain damage or other disorders that impact the central nervous system, as plasticity permits to reorganize its neural structure, fostering motor relearning. Despite the fact that so many studies claim the validity of robot-mediated therapy in post-stroke patient rehabilitation, it is still difficult to assess to what extent its adoption improves the efficacy of traditional therapy in daily life, and also because most of the studies involved planar robots. In this paper, we report the effects of a 20-session-rehabilitation project involving the Armeo Power robot, an assistive exoskeleton to perform 3D upper limb movements, in addition to conventional rehabilitation therapy, on 10 subacute stroke survivors. Patients were evaluated through clinical scales and a kinematic assessment of the upper limbs, both pre- and post-treatment. A set of indices based on the patients’ 3D kinematic data, gathered from an optoelectronic system, was calculated. Statistical analysis showed a remarkable difference in most parameters between pre- and post-treatment. Significant correlations between the kinematic parameters and clinical scales were found. Our findings suggest that 3D robot-mediated rehabilitation, in addition to conventional therapy, could represent an effective means for the recovery of upper limb disability. Kinematic assessment may represent a valid tool for objectively evaluating the efficacy of the rehabilitation treatment.

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Monitoring gait quality in daily activities through wearable sensors has the potential to improve medical assessment in Parkinson’s Disease (PD). In this study, four gait partitioning methods, two based on thresholds and two based on a machine learning approach, considering the four-phase model, were compared. The methods were tested on 26 PD patients, both in OFF and ON levodopa conditions, and 11 healthy subjects, during walking tasks. All subjects were equipped with inertial sensors placed on feet. Force resistive sensors were used to assess reference time sequence of gait phases. Goodness Index (G) was evaluated to assess accuracy in gait phases estimation. A novel synthetic index called Gait Phase Quality Index (GPQI) was proposed for gait quality assessment. Results revealed optimum performance (G < 0.25) for three tested methods and good performance (0.25 < G < 0.70) for one threshold method. The GPQI resulted significantly higher in PD patients than in healthy subjects, showing a moderate correlation with clinical scales score. Furthermore, in patients with severe gait impairment, GPQI was found higher in OFF than in ON state. Our results unveil the possibility of monitoring gait quality in PD through real-time gait partitioning based on wearable sensors.

Background: Although robotic therapy is at the forefront of upper limb rehabilitation, there is limited information about the importance of selecting age-matched subjects to evaluate recovery of arm movement during rehabilitation.Objective: This study aims to quantify differences in the arm motion of healthy children and adults when they interact with a planar robot, in order to determine whether an age-matched control group is necessary in clinical studies involving pediatric patients.Methods: Ten children (aged 7 to 10 years) and ten adults (aged 23 to 25 years) performed, at self-selected speed and accuracy, planar-reaching and circle-drawing movements with a robotic device. We analyzed the motor performances for the two groups quantifying the participants' dexterity in completing two chosen tasks. The measurement of the entire upper limb was obtained by merging the data provided by the robot with that of an optical tracking system.Results: Children drew circles with less smoothness than adults but with the same accuracy and joint coordination. During planar reaching task, children optimized only the coordination but performed the movement with less accuracy and smoothness than adults.Conclusions: Our findings provide evidence that age-matched healthy children should be used to quantify the recovery of robot-mediated therapy in children with upper limb impairments.