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Article

fNIRS Complexity Analysis for the Assessment of Motor Imagery and Mental Arithmetic Tasks

1
Bioengineering and Robotics Research Center E Piaggio, Università di Pisa, 56123 Pisa, Italy
2
Department of Information Engineering, Università di Pisa, 56123 Pisa, Italy
*
Author to whom correspondence should be addressed.
Entropy 2020, 22(7), 761; https://doi.org/10.3390/e22070761
Received: 10 June 2020 / Revised: 7 July 2020 / Accepted: 8 July 2020 / Published: 11 July 2020
Conventional methods for analyzing functional near-infrared spectroscopy (fNIRS) signals primarily focus on characterizing linear dynamics of the underlying metabolic processes. Nevertheless, linear analysis may underrepresent the true physiological processes that fully characterizes the complex and nonlinear metabolic activity sustaining brain function. Although there have been recent attempts to characterize nonlinearities in fNIRS signals in various experimental protocols, to our knowledge there has yet to be a study that evaluates the utility of complex characterizations of fNIRS in comparison to standard methods, such as the mean value of hemoglobin. Thus, the aim of this study was to investigate the entropy of hemoglobin concentration time series obtained from fNIRS signals and perform a comparitive analysis with standard mean hemoglobin analysis of functional activation. Publicly available data from 29 subjects performing motor imagery and mental arithmetics tasks were exploited for the purpose of this study. The experimental results show that entropy analysis on fNIRS signals may potentially uncover meaningful activation areas that enrich and complement the set identified through a traditional linear analysis. View Full-Text
Keywords: fNIRS; entropy; complexity analysis; nonlinear analysis; brain dynamics; mental arithmetics; motor imagery fNIRS; entropy; complexity analysis; nonlinear analysis; brain dynamics; mental arithmetics; motor imagery
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MDPI and ACS Style

Ghouse, A.; Nardelli, M.; Valenza, G. fNIRS Complexity Analysis for the Assessment of Motor Imagery and Mental Arithmetic Tasks. Entropy 2020, 22, 761. https://doi.org/10.3390/e22070761

AMA Style

Ghouse A, Nardelli M, Valenza G. fNIRS Complexity Analysis for the Assessment of Motor Imagery and Mental Arithmetic Tasks. Entropy. 2020; 22(7):761. https://doi.org/10.3390/e22070761

Chicago/Turabian Style

Ghouse, Ameer, Mimma Nardelli, and Gaetano Valenza. 2020. "fNIRS Complexity Analysis for the Assessment of Motor Imagery and Mental Arithmetic Tasks" Entropy 22, no. 7: 761. https://doi.org/10.3390/e22070761

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