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ECoG-Based BCIs
Published in Chang S. Nam, Anton Nijholt, Fabien Lotte, Brain–Computer Interfaces Handbook, 2018
Electrocorticography (ECoG) is an electrophysiological technique that utilizes electrodes placed intracranially on the surface of the brain. ECoG has been employed in humans clinically for over six decades for the localization of epileptic zones and for functional brain mapping. However, its value for basic human neuroscientific research and its potential to enable new translational applications had not been widely recognized until recently. ECoG signals are captured either above (epidural) or below (subdural) the dura mater, but not within the brain tissue itself (see Figure 16.1). Many studies over the last decade have demonstrated the functional specificity, signal fidelity, and long-term stability of ECoG activity in behavioral and cognitive tasks (Schalk 2010). Together with its spatial and temporal resolution and coverage of distant areas of the brain, these unique qualities suggest that ECoG elucidates brain function in ways that cannot be achieved by other electrophysiological or neuroimaging techniques. For instance, intracortical electrode recordings usually have issues with long-term stability; scalp-recorded EEG lacks functional specificity and is very prone to artifacts; and metabolic responses captured via neuroimaging may be too slow for practical applications.
Rehabilitation robotics
Published in Alex Mihailidis, Roger Smith, Rehabilitation Engineering, 2023
Michelle J. Johnson, Rochelle Mendonca
A quick review of current activities in the rehabilitation field shows that artificial intelligence, specifically machine learning, brain computing interfaces, new “soft” materials for robots, and affordability provide the next frontier in rehabilitation robot device development. Machine learning offers increasing potential to improve the ability of both therapy and assistive robots to accurately perceive, predict, and act to control the environment (Boquete et al. 2005; Montemerlo et al. 2002). Use cases are emerging that suggest that future robots will be able to quickly recognize faces and predict health failures in patients, as well as predict user control intent for a wheelchair robot to ease the burden of using them. Brain computing interfaces and imaging techniques such as electroencephalography (EEG) and electrocorticography (ECOG), coupled with new frontiers in implantable electrodes for the brain, suggest that in the foreseeable future, there will be thought-controlled and neural-controlled therapy and assistive robots (Galan et al. 2008; Scherer et al. 2012). Our desire to interact closer and safer with robots has seen the emergence of soft robots for rehabilitation. These robots are often able to be in close contact with patients due to the use of novel deformable materials. Examples of exoskeletal soft robots for the body and hands are harbingers of wearable robots that are transparent, not bulky or heavy, and are able to be worn all day to augment healthy or impaired limbs (Radder et al. 2016; Xiloyannis et al. 2016). Given the knowledge of a worldwide need for rehabilitation technology solutions that are not only appropriate for developed countries, and developing countries, we anticipate an expansion of the scope and populations using rehabilitation robots and the development of low-cost robot systems that can be used in group-based robot training environments where one therapist can oversee four or more patients. Circuit training and group therapy in robot gyms and group exercise and play with social robots are emerging as cost-effective solutions for developing and low-resource environments (Bustamante Valles et al. 2016; Johnson et al. 2017b). Recently, in their statement entitled “Rehabilitation 2030: A call for action,” the World Health Organization placed the need for accessible and affordable rehabilitation front and center in achieving Sustainable Development Goal (SDG) 3, “Ensure healthy lives and promote well-being for all at all ages” (World Health Organization 2017).
Workshops of the seventh international brain-computer interface meeting: not getting lost in translation
Published in Brain-Computer Interfaces, 2019
Jane E. Huggins, Christoph Guger, Erik Aarnoutse, Brendan Allison, Charles W. Anderson, Steven Bedrick, Walter Besio, Ricardo Chavarriaga, Jennifer L. Collinger, An H. Do, Christian Herff, Matthias Hohmann, Michelle Kinsella, Kyuhwa Lee, Fabien Lotte, Gernot Müller-Putz, Anton Nijholt, Elmar Pels, Betts Peters, Felix Putze, Rüdiger Rupp, Gerwin Schalk, Stephanie Scott, Michael Tangermann, Paul Tubig, Thorsten Zander
Electrocorticography (ECoG) is the technique of recording from or stimulating the surface of the brain. Over the past several years, the unique qualities of ECoG for research and clinical applications have become increasingly recognized. Recent work has addressed a number of important scientific questions and has established the potential value of ECoG for BCI operation.