TY - JOUR
T1 - Estimation of Respiratory Rate from Functional Near-Infrared Spectroscopy (fNIRS)
T2 - A New Perspective on Respiratory Interference
AU - Hakimi, Naser
AU - Shahbakhti, Mohammad
AU - Sappia, Sofia
AU - Horschig, Jörn M.
AU - Bronkhorst, Mathijs
AU - Floor-Westerdijk, Marianne
AU - Valenza, Gaetano
AU - Dudink, Jeroen
AU - Colier, Willy N.J.M.
N1 - Funding Information:
This work was supported by the European Regional Development Fund (PROJ-01003) doi:10.13039/501100008530 and the Horizon 2020 Framework Programme, (No. 813234 and No. 813843) doi:10.13039/100010661.
Publisher Copyright:
© 2022 by the authors.
PY - 2022/12/14
Y1 - 2022/12/14
N2 - 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 (O2Hb) 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 O2Hb 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 O2Hb 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.
AB - 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 (O2Hb) 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 O2Hb 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 O2Hb 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.
KW - estimation
KW - fNIRS
KW - physiological interference
KW - respiratory rate
KW - signal quality index
UR - http://www.scopus.com/inward/record.url?scp=85144565488&partnerID=8YFLogxK
U2 - 10.3390/bios12121170
DO - 10.3390/bios12121170
M3 - Article
C2 - 36551137
AN - SCOPUS:85144565488
VL - 12
JO - Biosensors
JF - Biosensors
IS - 12
M1 - 1170
ER -