Impaired motor function is a hallmark feature of neurological conditions such as spinal cord injury, stroke, Parkinson’s Disease and multiple sclerosis, as well as aging. The resulting decreased mobility very often leads to social stigma and increased rates of depression, having an important impact on patient’s quality of life, with subsequent considerable costs for health and social services.

Rehabilitation robotics

The main goal of this research line is to improve the quality of life of individuals with movement disorders by developing and evaluating breakthrough robotic technologies, including exoskeletons, exosuits and assistive robots, and interventions able to: i) promote recovery of lost motor functions, and/or ii) assist the activities of daily living.

To achieve our goal, we take a multidisciplinary approach focused on the fields of mechatronics and control, driven by the research in the fields of neurorehabilitation, neurophysiology and biomechanics. We design technologies and interventions based on the latest scientific evidence combined with feedback received from end-users, which includes stroke, spinal cord injury, multiple sclerosis and Parkinson’s Disease patients, as well as elderly users.

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Neural Interfaces

Neural information can be used to drive prosthetic devices or directly stimulate nerves / muscles. These neural interfaces are aimed at restoring or augmenting lost sensory-motor functions in humans. This means building a connection of technology with biology to replicate and restore the human natural sensory-motor control loop. On top of that, physiological theories are needed to explain, predict and control such loop. Current challenges in the field involve decoding impaired neural information and acting accordingly to restore / assist weakened or partially lost movements using minimally invasive interfaces.

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Benchmarking

Benchmarking is the process of comparing the performance of a given system or process against a set of standards or a comparable system. Benchmarking requires a set of metrics that can accurately reflect the capabilities and potential of the system under examination. In rehabilitation robotics, common metrics are accuracy, speed, stability, power, weight, energy consumption, range of motion, donning and doffing time, user comfort, etc… The results of the benchmarking analysis can be used to set performance targets, improve the efficiency of R&D processes, predict the effects of different solutions, or verify safety. Particularly important in benchmarking are unified datasets and standard experimental protocols to compare systems on a common ground of tasks and domains. Benchmarking is normally conducted in the laboratory to assure measurability and reproducibility. However, lab tests should be complemented by field tests to verify the ability of benchmarks to predict real world performance.

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Neuroscience-inspired Robotics

This research line focuses on understanding how humans perceive and act with their body to i) improve artificial intelligence and robotic systems, and at the same time ii) aid to unveil the inner mechanisms of information processing in the brain. We develop novel algorithms for learning, estimation and control of complex systems based on neuroscience findings and evaluate them in robotic platforms (humanoids, manipulators). Our models, besides being relevant for disciplines, such as computational neuroscience, robotics and cognitive science, are particularly interesting for human-centric solutions, e.g., healthcare, human-robot interaction, wearable robotics, etc. In the long run, this research pursues achieving robots with human comparable embodied intelligence. Enabling robots to act and adapt to real-world complex interactions is one of the key challenges of this century.

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AI for Neuroengineering

TArtificial intelligence (AI) has revolutionized the field of neuroengineering by helping to unveil and better understand the mechanisms of brain function and dysfunction. The study of brain dysfunction and the use of AI have contributed to a better comprehension of neurological disorders having a significant impact on diagnostic, evaluation, and rehabilitation procedures, and enhancing and complementing the existing clinical procedures.

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