Brain–machine interfaces using functional near-infrared spectroscopy: a review

被引:0
|
作者
Keum-Shik Hong
Usman Ghafoor
M. Jawad Khan
机构
[1] Pusan National University,School of Mechanical Engineering
[2] National University of Science and Technology,School of Mechanical and Manufacturing Engineering
来源
Artificial Life and Robotics | 2020年 / 25卷
关键词
Functional near-infrared spectroscopy; Brain–machine interface; Classification; Stimulation; Neuromodulation;
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中图分类号
学科分类号
摘要
Functional near-infrared spectroscopy (fNIRS) is a noninvasive method for acquiring hemodynamic signals from the brain with advantages of portability, affordability, low susceptibility to noise, and moderate temporal resolution that serves as a plausible solution to real-time imaging. fNIRS is an emerging brain imaging technique that measures brain activity by means of near-infrared light of 600–1000 nm wavelengths. Recently, there has been a surge of studies with fNIRS for the acquisition, decoding, and regulation of hemodynamic signals to investigate their behavioral consequences for the implementation of brain–machine interfaces (BMI). In this review, first, the existing methods of fNIRS signal processing for decoding brain commands for BMI purposes are reviewed. Second, recent developments, applications, and challenges faced by fNIRS-based BMIs are outlined. Third, current trends in fNIRS in combination with other imaging modalities are summarized. Finally, we propose a feedback control concept for the human brain, in which fNIRS, electroencephalography, and functional magnetic resonance imaging are considered sensors and stimulation techniques are considered actuators in brain therapy.
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页码:204 / 218
页数:14
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