Background: Quantitative measures of human movement quality are important for discriminating healthy and pathological conditions and for expressing the outcomes and clinically important changes in subjects' functional state. However the most frequently used instruments for the upper extremity functional assessment are clinical scales, that previously have been standardized and validated, but have a high subjective component depending on the observer who scores the test. But they are not enough to assess motor strategies used during movements, and their use in combination with other more objective measures is necessary. The objective of the present review is to provide an overview on objective metrics found in literature with the aim of quantifying the upper extremity performance during functional tasks, regardless of the equipment or system used for registering kinematic data. Methods: A search in Medline, Google Scholar and IEEE Xplore databases was performed following a combination of a series of keywords. The full scientific papers that fulfilled the inclusion criteria were included in the review. Findings: A set of kinematic metrics was found in literature in relation to joint displacements, analysis of hand trajectories and velocity profiles. These metrics were classified into different categories according to the movement characteristic that was being measured. Interpretation: These kinematic metrics provide the starting point for a proposed objective metrics for the functional assessment of the upper extremity in people with movement disorders as a consequence of neurological injuries. Potential areas of future and further research are presented in the Discussion section.

This study might be a step forward for the investigation of new uses of motion capture systems in neurorehabilitation, making it possible to train activities of daily living (ADLs) in motivational environments while measuring objectively the patient's functional evolution. Implications for Rehabilitation Key findings: A motion capture application based on a data glove is presented, for being used as a virtual reality tool for rehabilitation. This application has provided objective data about patient's functional performance. What the study has added: (1) This study allows to open new areas of research based on the use of different motion capture systems as rehabilitation tools, making it possible to train Activities of Daily Living in motivational environments. (2) Furthermore, this study could be a contribution for the development of clinical protocols to identify which types of patients will benefit most from the VR treatments, which interfaces are more suitable to be used in neurorehabilitation, and what types of virtual exercises will work best.

The aim of this study was to investigate the effects of a virtual reality program combined with conventional therapy in upper limb function in people with tetraplegia and to provide data about patients' satisfaction with the virtual reality system. Thirty-one people with subacute complete cervical tetraplegia participated in the study. Experimental group received 15 sessions with Toyra® virtual reality system for 5 weeks, 30 minutes/day, 3 days/week in addition to conventional therapy, while control group only received conventional therapy. All patients were assessed at baseline, after intervention, and at three-month follow-up with a battery of clinical, functional, and satisfaction scales. Control group showed significant improvements in the manual muscle test (p = 0,043, partial η 2 = 0,22) in the follow-up evaluation. Both groups demonstrated clinical, but nonsignificant, changes to their arm function in 4 of the 5 scales used. All patients showed a high level of satisfaction with the virtual reality system. This study showed that virtual reality added to conventional therapy produces similar results in upper limb function compared to only conventional therapy. Moreover, the gaming aspects incorporated in conventional rehabilitation appear to produce high motivation during execution of the assigned tasks. This trial is registered with EudraCT number 2015-002157-35.

Background: Research efforts in neurorehabilitation technologies have been directed towards creating robotic exoskeletons to restore motor function in impaired individuals. However, despite advances in mechatronics and bioelectrical signal processing, current robotic exoskeletons have had only modest clinical impact. A major limitation is the inability to enable exoskeleton voluntary control in neurologically impaired individuals. This hinders the possibility of optimally inducing the activity-driven neuroplastic changes that are required for recovery. Methods: We have developed a patient-specific computational model of the human musculoskeletal system controlled via neural surrogates, i.e., electromyography-derived neural activations to muscles. The electromyography-driven musculoskeletal model was synthesized into a human-machine interface (HMI) that enabled poststroke and incomplete spinal cord injury patients to voluntarily control multiple joints in a multifunctional robotic exoskeleton in real time. Results: We demonstrated patients' control accuracy across a wide range of lower-extremity motor tasks. Remarkably, an increased level of exoskeleton assistance always resulted in a reduction in both amplitude and variability in muscle activations as well as in the mechanical moments required to perform a motor task. Since small discrepancies in onset time between human limb movement and that of the parallel exoskeleton would potentially increase human neuromuscular effort, these results demonstrate that the developed HMI precisely synchronizes the device actuation with residual voluntary muscle contraction capacity in neurologically impaired patients. Conclusions: Continuous voluntary control of robotic exoskeletons (i.e. event-free and task-independent) has never been demonstrated before in populations with paretic and spastic-like muscle activity, such as those investigated in this study. Our proposed methodology may open new avenues for harnessing residual neuromuscular function in neurologically impaired individuals via symbiotic wearable robots.

No abstract