Brain-Computer Interfaces Using Electrocorticographic Signals

Gerwin Schalk, Eric C. Leuthardt
2011 IEEE Reviews in Biomedical Engineering  
Many studies over the past two decades have shown that people and animals can use brain signals to convey their intent to a computer using brain-computer interfaces (BCIs). BCI systems measure specific features of brain activity and translate them into control signals that drive an output. The sensor modalities that have most commonly been used in BCI studies have been electroencephalographic (EEG) recordings from the scalp and singleneuron recordings from within the cortex. Over the past
more » ... , an increasing number of studies has explored the use of electrocorticographic (ECoG) activity recorded directly from the surface of the brain. ECoG has attracted substantial and increasing interest, because it has been shown to reflect specific details of actual and imagined actions, and because its technical characteristics should readily support robust and chronic implementations of BCI systems in humans. This review provides general perspectives on the ECoG platform; describes the different electrophysiological features that can be detected in ECoG; elaborates on the signal acquisition issues, protocols, and online performance of ECoGbased BCI studies to date; presents important limitations of current ECoG studies; discusses opportunities for further research; and finally presents a vision for eventual clinical implementation. In summary, the studies presented to date strongly encourage further research using the ECoG platform for basic neuroscientific research, as well as for translational neuroprosthetic applications. Index Terms-Brain-computer interface (BCI), Brain-machine interface (BMI), electrocorticography (ECoG). 1937 -3333/$26.00 © 2011 IEEE Gerwin Schalk received the M.S. degree in electrical engineering and computer science from Graz University of Technology, in 1999, and the M.S. degree in IT and the Ph.D. degree in CSE both from Rensselaer Polytechnic Institute, Troy, NY, in 2001 and 2006, respectively. He is a Research Scientist at the Wadsworth Center, New York State Department of Health. He is interested in engineering, scientific, and commercial aspects of devices that interface the brain with external devices. This work encompasses the study of the relationship between brain signals and relevant parameters of motor, cognitive, or language function. It also involves the application of resulting understanding to functional restoration (i.e., brain-computer interfaces) and to clinical diagnosis. He has authored more than 60 peer-reviewed journal publications. Dr. Schalk has given more than 100 invited lectures at institutions worldwide and has received several awards for his work. Eric C. Leuthardt received the B.S. degree in biology and theology at St. Louis University, in 1995, and received the M.D. degree from the University of Pennsylvania's School of Medicine, in 1999. He went on to complete his training at Barnes Jewish Hospital and Washington University, St. Louis, in 2005, followed by a combined fellowship in epilepsy and spinal surgery at the University of Washington, Seattle, in 2006. He is a Neurosurgeon who is currently an Assistant Professor with the Department of Neurological Surgery and the Department of Biomedical Engineering, Washington University, St. Louis. He is also the Director of the Center for Innovation in Neuroscience and Technology. His research has focused on neuroprosthetics-devices linked to the brain that may restore function to patients with motor disabilities. His work in the field of neuroprosthetics and neurosurgical devices has yielded him numerous awards. He uses an integrated approach by employing multiple domains of expertise ranging from biomedical engineering, clinical neurosurgery, mathematical modeling, complex signal analysis, and computer programming. In addition to numerous peer reviewed publications, he has over 500 patents on file with the U.S. Patent and Trademark Office for medical devices and brain-computer interface technologies.
doi:10.1109/rbme.2011.2172408 pmid:22273796 fatcat:3goiufxxyzcyxpnmuvxv4jfwf4