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.

Background and purpose To support clinical decision‐making in central neurological disorders, a physical examination is used to assess responses to passive muscle stretch. However, what exactly is being assessed is expressed and interpreted in different ways. A clear diagnostic framework is lacking. Therefore, the aim was to arrive at unambiguous terminology about the concepts and measurement around pathophysiological neuromuscular response to passive muscle stretch. Methods During two consensus meetings, 37 experts from 12 European countries filled online questionnaires based on a Delphi approach, followed by plenary discussion after rounds. Consensus was reached for agreement ≥75%. Results The term hyper‐resistance should be used to describe the phenomenon of impaired neuromuscular response during passive stretch, instead of for example ‘spasticity’ or ‘hypertonia’. From there, it is essential to distinguish non‐neural (tissue‐related) from neural (central nervous system related) contributions to hyper‐resistance. Tissue contributions are elasticity, viscosity and muscle shortening. Neural contributions are velocity dependent stretch hyperreflexia and non‐velocity dependent involuntary background activation. The term ‘spasticity’ should only be used next to stretch hyperreflexia, and ‘stiffness’ next to passive tissue contributions. When joint angle, moment and electromyography are recorded, components of hyper‐resistance within the framework can be quantitatively assessed. Conclusions A conceptual framework of pathophysiological responses to passive muscle stretch is defined. This framework can be used in clinical assessment of hyper‐resistance and will improve communication between clinicians. Components within the framework are defined by objective parameters from instrumented assessment. These parameters need experimental validation in order to develop treatment algorithms based on the aetiology of the clinical phenomena.

No abstract