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dc.contributor.authorMcDowell, Kaleben_US
dc.contributor.authorLin, Chin-Tengen_US
dc.contributor.authorOie, Kelvin S.en_US
dc.contributor.authorJung, Tzyy-Pingen_US
dc.contributor.authorGordon, Stephenen_US
dc.contributor.authorWhitaker, Keith W.en_US
dc.contributor.authorLi, Shih-Yuen_US
dc.contributor.authorLu, Shao-Weien_US
dc.contributor.authorHairston, W. Daviden_US
dc.date.accessioned2019-04-03T06:37:18Z-
dc.date.available2019-04-03T06:37:18Z-
dc.date.issued2013-01-01en_US
dc.identifier.issn2169-3536en_US
dc.identifier.urihttp://dx.doi.org/10.1109/ACCESS.2013.2260791en_US
dc.identifier.urihttp://hdl.handle.net/11536/133590-
dc.description.abstractDecades of heavy investment in laboratory-based brain imaging and neuroscience have led to foundational insights into how humans sense, perceive, and interact with the external world. However, it is argued that fundamental differences between laboratory-based and naturalistic human behavior may exist. Thus, it remains unclear how well the current knowledge of human brain function translates into the highly dynamic real world. While some demonstrated successes in real-world neurotechnologies are observed, particularly in the area of brain-computer interaction technologies, innovations and developments to date are limited to a small science and technology community. We posit that advancements in real world neuroimaging tools for use by a broad-based workforce will dramatically enhance neurotechnology applications that have the potential to radically alter human system interactions across all aspects of everyday life. We discuss the efforts of a joint government-academic-industry team to take an integrative, interdisciplinary, and multi-aspect approach to translate current technologies into devices that are truly fieldable across a range of environments. Results from initial work, described here, show promise for dramatic advances in the field that will rapidly enhance our ability to assess brain activity in real-world scenarios.en_US
dc.language.isoen_USen_US
dc.subjectBehavioral scienceen_US
dc.subjectbiomarkersen_US
dc.subjectbody sensor networksen_US
dc.subjectbrain computer interfacesen_US
dc.subjectbrain computer interactionen_US
dc.subjectdata acquisitionen_US
dc.subjectelectroencephalographyen_US
dc.subjectmonitoringen_US
dc.subjecttranslational researchen_US
dc.subjectwearable sensorsen_US
dc.titleReal-World Neuroimaging Technologiesen_US
dc.typeArticleen_US
dc.identifier.doi10.1109/ACCESS.2013.2260791en_US
dc.identifier.journalIEEE ACCESSen_US
dc.citation.volume1en_US
dc.citation.spage131en_US
dc.citation.epage149en_US
dc.contributor.department電子工程學系及電子研究所zh_TW
dc.contributor.department腦科學研究中心zh_TW
dc.contributor.departmentDepartment of Electronics Engineering and Institute of Electronicsen_US
dc.contributor.departmentBrain Research Centeren_US
dc.identifier.wosnumberWOS:000209652700011en_US
dc.citation.woscount49en_US
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