Recognizing brain activities by functional near-infrared spectroscope signal analysis.
BACKGROUND
Functional Near-Infrared Spectroscope (fNIRs) is one of the latest technologies which utilize light in the near-infrared range to determine brain activities. Near-infrared technology allows design of safe, portable, wearable, non-invasive and wireless qualities monitoring systems. This indicates that fNIRs signal monitoring of brain hemodynamics can be value in helping to understand brain tasks. In this paper, we present results of fNIRs signal analysis to show that there exist distinct patterns of hemodynamic responses which recognize brain tasks toward developing a Brain-Computer interface.


RESULTS
We applied Higuchi's fractal dimension algorithms to analyse irregular and complex characteristics of fNIRs signals, and then Wavelets transform is used to analysis for preprocessing as signal filters and feature extractions and Neural networks is a module for cognition brain tasks.


CONCLUSIONS
Throughout two experiments, we have demonstrated the feasibility of fNIRs analysis to recognize human brain activities.
Khoa
Truong Quang Dang
TQ
Chaos and Fractals Informatics Laboratory, Nagaoka University of Technology, 1603-1 Kamitomiokamachi, Nagaoka, Niigata, 940-2188, Japan. khoa@ieee.org.
Nakagawa
Masahiro
M