Full metadata record
DC Field | Value | Language |
---|---|---|
dc.contributor.author | McDowell, Kaleb | en_US |
dc.contributor.author | Lin, Chin-Teng | en_US |
dc.contributor.author | Oie, Kelvin S. | en_US |
dc.contributor.author | Jung, Tzyy-Ping | en_US |
dc.contributor.author | Gordon, Stephen | en_US |
dc.contributor.author | Whitaker, Keith W. | en_US |
dc.contributor.author | Li, Shih-Yu | en_US |
dc.contributor.author | Lu, Shao-Wei | en_US |
dc.contributor.author | Hairston, W. David | en_US |
dc.date.accessioned | 2019-04-03T06:37:18Z | - |
dc.date.available | 2019-04-03T06:37:18Z | - |
dc.date.issued | 2013-01-01 | en_US |
dc.identifier.issn | 2169-3536 | en_US |
dc.identifier.uri | http://dx.doi.org/10.1109/ACCESS.2013.2260791 | en_US |
dc.identifier.uri | http://hdl.handle.net/11536/133590 | - |
dc.description.abstract | Decades 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.iso | en_US | en_US |
dc.subject | Behavioral science | en_US |
dc.subject | biomarkers | en_US |
dc.subject | body sensor networks | en_US |
dc.subject | brain computer interfaces | en_US |
dc.subject | brain computer interaction | en_US |
dc.subject | data acquisition | en_US |
dc.subject | electroencephalography | en_US |
dc.subject | monitoring | en_US |
dc.subject | translational research | en_US |
dc.subject | wearable sensors | en_US |
dc.title | Real-World Neuroimaging Technologies | en_US |
dc.type | Article | en_US |
dc.identifier.doi | 10.1109/ACCESS.2013.2260791 | en_US |
dc.identifier.journal | IEEE ACCESS | en_US |
dc.citation.volume | 1 | en_US |
dc.citation.spage | 131 | en_US |
dc.citation.epage | 149 | en_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.department | Department of Electronics Engineering and Institute of Electronics | en_US |
dc.contributor.department | Brain Research Center | en_US |
dc.identifier.wosnumber | WOS:000209652700011 | en_US |
dc.citation.woscount | 49 | en_US |
Appears in Collections: | Articles |
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