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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 i...

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Detalles Bibliográficos
Autores principales: Khoa, Truong Quang Dang, Nakagawa, Masahiro
Formato: Texto
Lenguaje:English
Publicado: BioMed Central 2008
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2474833/
https://www.ncbi.nlm.nih.gov/pubmed/18590571
http://dx.doi.org/10.1186/1753-4631-2-3
Descripción
Sumario: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. CONCLUSION: Throughout two experiments, we have demonstrated the feasibility of fNIRs analysis to recognize human brain activities.