Noise reduction in functional near-infrared spectroscopy signals by independent component analysis

• Published in: Review of scientific instruments Vol. 84; no. 7; p. 073106
• Main Authors: Santosa, Hendrik, Jiyoun Hong, Melissa, Kim, Sung-Phil, Hong, Keum-Shik
• Format: Journal Article
• Language: English
• Published: United States 01.07.2013
• Subjects: Activation analysis; Adult; Brain; Hemodynamic responses; Hemodynamics; Humans; Image Processing, Computer-Assisted; Independent component analysis; Male; Noise; Oxygen - metabolism; Prefrontal Cortex - metabolism; Prefrontal Cortex - physiology; Signal Processing, Computer-Assisted; Signal-To-Noise Ratio; Spectrophotometry, Infrared - methods; Spectroscopy; Statistics as Topic; Stimuli; Tasks
• ISSN: 0034-6748; 1089-7623; 1089-7623
• DOI: 10.1063/1.4812785

Functional near-infrared spectroscopy (fNIRS) is used to detect concentration changes of oxy-hemoglobin and deoxy-hemoglobin in the human brain. The main difficulty entailed in the analysis of fNIRS signals is the fact that the hemodynamic response to a specific neuronal activation is contaminated by physiological and instrument noises, motion artifacts, and other interferences. This paper proposes independent component analysis (ICA) as a means of identifying the original hemodynamic response in the presence of noises. The original hemodynamic response was reconstructed using the primary independent component (IC) and other, less-weighting-coefficient ICs. In order to generate experimental brain stimuli, arithmetic tasks were administered to eight volunteer subjects. The t-value of the reconstructed hemodynamic response was improved by using the ICs found in the measured data. The best t-value out of 16 low-pass-filtered signals was 37, and that of the reconstructed one was 51. Also, the average t-value of the eight subjects’ reconstructed signals was 40, whereas that of all of their low-pass-filtered signals was only 20. Overall, the results showed the applicability of the ICA-based method to noise-contamination reduction in brain mapping.