Neuromechanical Biomarkers for Robotic Neurorehabilitation - Garro, Florencia; Chiappalone, Michela; Buccelli, Stefano; De Michieli, Lorenzo; Semprini, Marianna (Frontiers in Neurorobotics, 2021)
One of the current challenges for translational rehabilitation research is to develop strategies to deliver accurate evaluation, prediction, patient selection, and decision making in clinical practice. In this regard, robot-assisted interventions have gained popularity as they can provide objective and quantifiable assessment of motor performance by taking kinematics parameters into account. Neurophysiological parameters have also been proposed for this purpose, due to novel advances in non-invasive signal processing techniques. In addition, other parameters linked to motor learning and brain plasticity occurring during rehabilitation have been explored, looking for a more holistic rehabilitation approach. However, the majority of the research done in this area is still exploratory. These parameters have shown the capability to become ‘biomarkers’, defined as quantifiable indicators of physiological/pathological processes, as well as responses to (therapeutical) interventions. In this view, they could be finally used for enhancing robot-assisted treatments. While biomarkers research has been growing in the last years, there is a current need for a better comprehension and quantification of the neuromechanical processes involved in rehabilitation. In particular, there is a lack of operationalization of potential neuromechanical biomarkers into clinical algorithms. In this scenario, a new framework called Rehabilomics has been proposed, to account for rehabilitation research that exploits biomarkers in its design. This work provides an overview of the state of the art of biomarkers related to robotic neurorehabilitation, focusing on translational studies, underlying the need to create comprehensive approaches that have the potential to take biomarkers research into clinical practice. We then summarize some promising biomarkers that are being under investigation in the current literature, and provide some examples of their current and/or potential applications in neurorehabilitation. Finally, we outline the main challenges and future directions in the field, briefly discussing their potential evolution and prospective.