DocumentCode
54595
Title
Real-World Neuroimaging Technologies
Author
McDowell, Kaleb ; Chin-Teng Lin ; Oie, Kelvin S. ; Tzyy-Ping Jung ; Gordon, Stascia ; Whitaker, Keith W. ; Shih-Yu Li ; Shao-Wei Lu ; Hairston, W. David
Author_Institution
Translational Neurosci. Branch, U.S. Army Res. Lab., Aberdeen Proving Ground, MD, USA
Volume
1
fYear
2013
fDate
2013
Firstpage
131
Lastpage
149
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 realworld 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.
Keywords
biological techniques; brain; brain-computer interfaces; neurophysiology; brain-computer interaction technology; external world; human brain function; human-system interactions; innovations; laboratory based brain imaging; neuroscience; real world neuroimaging technology; Behavioral science; Biomedical monitoring; Brain modeling; Brain-computer interfaces; Electroencephalography; Investments; Maximum likelihood decoding; Medical image processing; Neuroimaging; Neuroscience; Research and development; Wearable sensors; Behavioral science; biomarkers; body sensor networks; brain computer interaction; brain computer interfaces; data acquisition; electroencephalography; monitoring; translational research; wearable sensors;
fLanguage
English
Journal_Title
Access, IEEE
Publisher
ieee
ISSN
2169-3536
Type
jour
DOI
10.1109/ACCESS.2013.2260791
Filename
6514970
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