The method of kinematic analysis was sensitive for an assessment of motor recovery induced by CIMT. The kinematic results suggest that the increase in the use of the paretic limb in activities of daily living after the intervention is not only attributable to the patient's increased attention to it and better hand dexterity, but it is also a consequence of the improved speed of movement and better coordination between shoulder and elbow joints.

Stroke is a leading cause for adult disability, which in many cases causes motor deficits. Despite the developments in motor rehabilitation techniques, recovery of upper limb functions after stroke is limited and heterogeneous in terms of outcomes, and knowledge of important factors that may affect the outcome of the therapy is necessary to make a reasonable prediction for individual patients. In this paper, we assessed the relationship between quantitative electroencephalographic (QEEG) measures and the motor outcome in chronic stroke patients that underwent a robot-assisted rehabilitation program to evaluate the utility of QEEG indices to predict motor recovery. For this purpose, we acquired resting-state electroencephalographic signals from which the power ratio index (PRI), delta/alpha ratio, and brain symmetry index were calculated. The outcome of the motor rehabilitation was evaluated using upper limb section of the Fugl-Meyer Assessment. We found that PRI was significantly correlated with the motor recovery, suggesting that this index may provide useful information to predict the rehabilitation outcome.

Human-robot cooperation is increasingly demanded in industrial applications. Many tasks require the robot to enhance the capabilities of humans. In this scenario, safety also plays an important role in avoiding any accident involving humans, robots, and the environment. With this aim, the paper proposes a cooperative fuzzy-impedance control with embedded safety rules to assist human operators in heavy industrial applications while manipulating unknown weight parts. The proposed methodology is composed by four main components: (i) an inner Cartesian impedance controller (to achieve the compliant robot behavior), (ii) an outer fuzzy controller (to provide the assistance to the human operator), (iii) embedded safety rules (to limit force/velocity during the human-robot interaction enhancing safety), and (iv) a neural network approach (to optimize the control parameters for the human-robot collaboration on the basis of the target indexes of assistance performance defined for this purpose). The main achieved result refers to the capability of the controller to deal with uncertain payloads while assisting and empowering the human operator, both embedding in the controller safety features at force and velocity levels and minimizing the proposed performance indexes. The effectiveness of the proposed approach is verified with a KUKA iiwa 14 R820 manipulator in an experimental procedure where human subjects evaluate the robot performance in a collaborative lifting task of a 10 kg part.

Upper-limb movement analysis is important to monitor objectively rehabilitation interventions, contributing to improving the overall treatments outcomes. Simple, fast, easy-to-use, and applicable methods are required to allow routinely functional evaluation of patients with different pathologies and clinical conditions. This paper describes the Reaching and Hand-to-Mouth Evaluation Method, a fast procedure to assess the upper-limb motor control and functional ability, providing a set of normative data from 42 healthy subjects of different ages, evaluated for both the dominant and the nondominant limb motor performance. Sixteen of them were reevaluated after two weeks to perform test-retest reliability analysis. Data were clustered into three subgroups of different ages to test the method sensitivity to motor control differences. Experimental data show notable test-retest reliability in all tasks. Data from older and younger subjects show significant differences in the measures related to the ability for coordination thus showing the high sensitivity of the method to motor control differences. The presented method, provided with control data from healthy subjects, appears to be a suitable and reliable tool for the upper-limb functional assessment in the clinical environment.