%0 Journal Article %J Epilepsy Behav %D 2009 %T Advances in the application of technology to epilepsy: the CIMIT/NIO Epilepsy Innovation Summit. %A Schachter, Steven C %A Guttag, John %A Schiff, Steven J %A Schomer, Donald L %K Adult %K Anticonvulsants %K Brain Mapping %K Child %K Drug Resistance %K Electric Stimulation Therapy %K Electroencephalography %K Engineering %K Epilepsy %K Humans %K Magnetic Resonance Imaging %K Medical Laboratory Science %K Microelectrodes %K Nanoparticles %K Neurons %K Neurosurgery %K Neurotoxins %K Predictive Value of Tests %K Seizures %K Spectroscopy, Near-Infrared %K Tomography, Emission-Computed, Single-Photon %K Tomography, Optical %K Transcranial Magnetic Stimulation %X

In 2008, a group of clinicians, scientists, engineers, and industry representatives met to discuss advances in the application of engineering technologies to the diagnosis and treatment of patients with epilepsy. The presentations also provided a guide for further technological development, specifically in the evaluation of patients for epilepsy surgery, seizure onset detection and seizure prediction, intracranial treatment systems, and extracranial treatment systems. This article summarizes the discussions and demonstrates that cross-disciplinary interactions can catalyze collaborations between physicians and engineers to address and solve many of the pressing unmet needs in epilepsy.

%B Epilepsy Behav %V 16 %P 3-46 %8 09/2009 %G eng %U http://www.ncbi.nlm.nih.gov/pubmed/19780225 %N 1 %R 10.1016/j.yebeh.2009.06.028 %0 Journal Article %J J Neural Eng %D 2009 %T Decoding flexion of individual fingers using electrocorticographic signals in humans. %A Kubánek, J %A Miller, John W %A Ojemann, J G %A Jonathan Wolpaw %A Gerwin Schalk %K Adolescent %K Adult %K Biomechanics %K Brain %K Electrodiagnosis %K Epilepsy %K Female %K Fingers %K Humans %K Male %K Microelectrodes %K Middle Aged %K Motor Activity %K Rest %K Thumb %K Time Factors %K Young Adult %X

Brain signals can provide the basis for a non-muscular communication and control system, a brain-computer interface (BCI), for people with motor disabilities. A common approach to creating BCI devices is to decode kinematic parameters of movements using signals recorded by intracortical microelectrodes. Recent studies have shown that kinematic parameters of hand movements can also be accurately decoded from signals recorded by electrodes placed on the surface of the brain (electrocorticography (ECoG)). In the present study, we extend these results by demonstrating that it is also possible to decode the time course of the flexion of individual fingers using ECoG signals in humans, and by showing that these flexion time courses are highly specific to the moving finger. These results provide additional support for the hypothesis that ECoG could be the basis for powerful clinically practical BCI systems, and also indicate that ECoG is useful for studying cortical dynamics related to motor function.

%B J Neural Eng %V 6 %P 066001 %8 12/2009 %G eng %U http://www.ncbi.nlm.nih.gov/pubmed/19794237 %N 6 %R 10.1088/1741-2560/6/6/066001