The development of robotic devices for rehabilitation is a fast-growing field. Nowadays, thanks to novel technologies that have improved robots’ capabilities and offered more cost-effective solutions, robotic devices are increasingly being employed during clinical practice, with the goal of boosting patients’ recovery. Robotic rehabilitation is also widely used in the context of neurological disorders, where it is often provided in a variety of different fashions, depending on the specific function to be restored. Indeed, the effect of robot-aided neurorehabilitation can be maximized when used in combination with a proper training regimen (based on motor control paradigms) or with non-invasive brain machine interfaces. Therapy-induced changes in neural activity and behavioral performance, which may suggest underlying changes in neural plasticity, can be quantified by multimodal assessments of both sensorimotor performance and brain/muscular activity pre/post or during intervention. Here, we provide an overview of the most common robotic devices for upper and lower limb rehabilitation and we describe the aforementioned neurorehabilitation scenarios. We also review assessment techniques for the evaluation of robotic therapy. Additional exploitation of these research areas will highlight the crucial contribution of rehabilitation robotics for promoting recovery and answering questions about reorganization of brain functions in response to disease.

Myoelectric signals offer significant insights in interpreting the motion intention and extent of effort involved in performing a movement, with application in prostheses, orthosis and exoskeletons. Feature extraction plays a vital role, and follows two approaches: EMG and synergy features. More recently, muscle synergy based features are being increasingly explored, since it simplifies dimensionality of control, and are considered to be more robust to signal variations. Another important aspect in a myoelectrically controlled devices is the learning capability and speed of performance for online decoding. Extreme learning machine (ELM) is a relatively new neural-network based learning algorithm: its performance hasn’t been explored in the context of online control, which is a more reliable measure compared to offline analysis. To this purpose we aim at focusing our investigation on a myoelectric-based interface which is able to identify and online classify, upper limb motions involving shoulder and elbow. The main objective is to compare the performance of the decoder trained using ELM, for two different features: EMG and synergy features. The experiments are broadly divided in two phases training/calibration and testing respectively. ELM is used to train the decoder using data acquired during the calibration phase. The performance of the decoder is then tested in online motion control by using a simulated graphical user interface replicating the human limb: subjects are requested to control a virtual arm by using their muscular activity. The decoder performance is quantified using ad-hoc metrics based on the following indicators: motion selection time, motion completion time, and classification accuracy. Performance has been evaluated for both offline and online contexts. The offline classification results indicated better performance in the case of EMG features, whereas a better classification accuracy for synergy feature was observed for online decoding. Also the other indicators as motion selection time and motion completion time, showed better trend in the case of synergy than time-domain features. This work demonstrates better robustness of online decoding of upper-limb motions and motor intentions when using synergy feature. Furthermore, we have quantified the performance of the decoder trained using ELM for online control, providing a potential and viable option for real-time myoelectric control in assistive technology.

Several neurodevelopmental disorders and brain injuries in children have been associated with proprioceptive dysfunction that will negatively affect their movement. Unfortunately, there is lack of reliable and objective clinical examination protocols and our current knowledge of how proprioception evolves in typically developing children is still sparse. Using a robotic exoskeleton, we investigated proprioceptive acuity of the wrist in a group of 49 typically developing healthy children (8–15 years), and a group of 40 young adults. Without vision participants performed an ipsilateral wrist joint position matching task that required them to reproduce (match) a previously experienced target position. All three joint degrees-of-freedom of the wrist/hand complex were assessed. Accuracy and precision were evaluated as a measure of proprioceptive acuity. The cross-sectional data indicating the time course of development of acuity were then fitted by four models in order to determine which function best describes developmental changes in proprioception across age. First, the robot-aided assessment proved to be an easy to administer method for objectively measuring proprioceptive acuity in both children and adult populations. Second, proprioceptive acuity continued to develop throughout middle childhood and early adolescence, improving by more than 50% with respect to the youngest group. Adult levels of performance were reached approximately by the age of 12 years. An inverse-root function best described the development of proprioceptive acuity across the age groups. Third, wrist/forearm proprioception is anisotropic across the three DoFs with the Abduction/Adduction exhibiting a higher level of acuity than those of Flexion/extension and Pronation/Supination. This anisotropy did not change across development. Proprioceptive development for the wrist continues well into early adolescence. Our normative data obtained trough this novel robot-aided assessment method provide a basis against which proprioceptive function of pediatric population can be compared. This may aid the design of more effective sensorimotor intervention programs.

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.

Regarding our voluntary control of movement, if identification of joint position, that is independent of the starting condition, is stronger than kinaesthetic movement reproduction, that implies knowledge of the starting position and movement's length for accuracy, is still a matter of debate in motor control theories and neuroscience. In the present study, we examined the mechanisms that individuals seem to prefer/adopt when they locate spatial positions and code the amplitude of movements. We implemented a joint position matching task on a wrist robotic device: this task consists in replicating (i.e. matching) a reference joint angle in the absence of vision and the proprioceptive acuity is given by the goodness of such matching. Two experiments were carried out by implementing two different versions of the task and performed by two groups of 15 healthy participants. In the first experiment, blindfolded subjects were asked to perform matching movements towards a fixed target position, experienced with passive movements that started from different positions and had different lengths. In the second experiment, blindfolded subjects were requested to accurately match target positions that had a different location in space but were passively shown through movements of the same length. We found a clear evidence for higher performances in terms of accuracy (0.42±0.011/°) and precision (0.43±0.011/°) in the first experiment, therefore in case of matching positions, rather than in the second where accuracy and precision were lower (0.36±0.011/° and 0.35±0.011/° respectively). These results suggested a preference for proprioceptive identification of joint position rather than kinaesthetic movement reproduction.

Proprioception combines information from cutaneous, joint, tendon, and muscle receptors for maintaining a reliable internal body image. However, it is still a matter of debate, in both neurophysiology and psychology, to what extent such body image is modified or distorted by a changing haptic environment. In particular, what is worth investigating is the contribution of external forces on our perception of body and joint configuration. The proprioceptive acuity of fifteen young participants was tested with a Joint Position Matching (JPM) task, performed with the dominant wrist under five different external forces, in order to understand to what extent they affect proprioceptive acuity. Results show that accuracy and precision in target matching do not change in a significant manner as a function of the loading condition, suggesting that the multi-sensory integration process is indeed capable of discriminating different sub-modalities of proprioception, namely the joint position sense and the sense of force. Furthermore, results indicate a preference for target undershooting when movements are performed in a viscous or high resistive force field, rather than passive or null fields in which subjects did not show any predominance for under/over estimation of their position.