Real-World Neuroimaging Technologies

被引:68
|
作者
McDowell, Kaleb [1 ]
Lin, Chin-Teng [2 ,3 ]
Oie, Kelvin S. [1 ]
Jung, Tzyy-Ping [4 ]
Gordon, Stephen [5 ]
Whitaker, Keith W. [1 ]
Li, Shih-Yu [2 ,3 ]
Lu, Shao-Wei [2 ,3 ]
Hairston, W. David [1 ]
机构
[1] US Army Res Lab, Translat Neurosci Branch, Aberdeen Proving Ground, MD 21005 USA
[2] Natl Chiao Tung Univ, Dept Elect Engn, Hsinchu 30010, Taiwan
[3] Natl Chiao Tung Univ, Brain Res Ctr, Hsinchu 30010, Taiwan
[4] Univ Calif San Diego, Inst Neural Computat, Swartz Ctr Computat Neurosci, La Jolla, CA 92093 USA
[5] DCS Corp, Alexandria, VA 22310 USA
来源
IEEE ACCESS | 2013年 / 1卷
关键词
Behavioral science; biomarkers; body sensor networks; brain computer interfaces; brain computer interaction; data acquisition; electroencephalography; monitoring; translational research; wearable sensors; PHASE-SYNCHRONIZATION; DRIVING PERFORMANCE; EEG; DYNAMICS; CLASSIFICATION; TASK; TIME; COGNITION; FATIGUE; SIGNALS;
D O I
10.1109/ACCESS.2013.2260791
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
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.
引用
收藏
页码:131 / 149
页数:19
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