Title Estimation of respiratory rate from functional near-infrared spectroscopy (fNIRS): a new perspective on respiratory interference /
Authors Hakimi, Naser ; Shahbakhti, Mohammad ; Sappia, Sofia ; Horschig, Jörn M ; Bronkhorst, Mathijs ; Floor-Westerdijk, Marianne ; Valenza, Gaetano ; Dudink, Jeroen ; Colier, Willy N.J.M
DOI 10.3390/bios12121170
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Is Part of Biosensors.. Basel : MDPI. 2022, vol. 12, iss. 12, art. no. 1170, p. 1-13.. ISSN 2079-6374
Keywords [eng] estimation ; fNIRS ; physiological interference ; respiratory rate ; signal quality index
Abstract [eng] Objective: Respiration is recognized as a systematic physiological interference in functional near-infrared spectroscopy (fNIRS). However, it remains unanswered as to whether it is possible to estimate the respiratory rate (RR) from such interference. Undoubtedly, RR estimation from fNIRS can provide complementary information that can be used alongside the cerebral activity analysis, e.g., sport studies. Thus, the objective of this paper is to propose a method for RR estimation from fNIRS. Our primary presumption is that changes in the baseline wander of oxygenated hemoglobin concentration ((Formula presented.)) signal are related to RR. Methods: fNIRS and respiratory signals were concurrently collected from subjects during controlled breathing tasks at a constant rate from 0.1 Hz to 0.4 Hz. Firstly, the signal quality index algorithm is employed to select the best (Formula presented.) signal, and then a band-pass filter with cut-off frequencies from 0.05 to 2 Hz is used to remove very low- and high-frequency artifacts. Secondly, troughs of the filtered (Formula presented.) signal are localized for synthesizing the baseline wander (S1) using cubic spline interpolation. Finally, the fast Fourier transform of the S1 signal is computed, and its dominant frequency is considered as RR. In this paper, two different datasets were employed, where the first one was used for the parameter adjustment of the proposed method, and the second one was solely used for testing. Results: The low mean absolute error between the reference and estimated RRs for the first and second datasets (2.6 and 1.3 breaths per minute, respectively) indicates the feasibility of the proposed method for RR estimation from fNIRS. Significance: This paper provides a novel view on the respiration interference as a source of complementary information in fNIRS.
Published Basel : MDPI
Type Journal article
Language English
Publication date 2022
CC license CC license description