Estimation of Respiratory Rate from Functional Near-Infrared Spectroscopy (fNIRS): A New Perspective on Respiratory Interference
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 provid...
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MDPI AG
2022-12-01
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| Series: | Biosensors |
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| Online Access: | https://www.mdpi.com/2079-6374/12/12/1170 |
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| author | Naser Hakimi Mohammad Shahbakhti Sofia Sappia Jörn M. Horschig Mathijs Bronkhorst Marianne Floor-Westerdijk Gaetano Valenza Jeroen Dudink Willy N. J. M. Colier |
| author_facet | Naser Hakimi Mohammad Shahbakhti Sofia Sappia Jörn M. Horschig Mathijs Bronkhorst Marianne Floor-Westerdijk Gaetano Valenza Jeroen Dudink Willy N. J. M. Colier |
| author_sort | Naser Hakimi |
| collection | DOAJ |
| description | 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 (<inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><msub><mi>O</mi><mn>2</mn></msub><mi>H</mi><mi>b</mi></mrow></semantics></math></inline-formula>) 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 <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><msub><mi>O</mi><mn>2</mn></msub><mi>H</mi><mi>b</mi></mrow></semantics></math></inline-formula> 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 <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><msub><mi>O</mi><mn>2</mn></msub><mi>H</mi><mi>b</mi></mrow></semantics></math></inline-formula> 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. |
| first_indexed | 2024-03-09T17:16:50Z |
| format | Article |
| id | doaj.art-ff33ba0333d4418a8eaf35a13906bd56 |
| institution | Directory Open Access Journal |
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| language | English |
| last_indexed | 2024-03-09T17:16:50Z |
| publishDate | 2022-12-01 |
| publisher | MDPI AG |
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| series | Biosensors |
| spelling | doaj.art-ff33ba0333d4418a8eaf35a13906bd562023-11-24T13:37:48ZengMDPI AGBiosensors2079-63742022-12-011212117010.3390/bios12121170Estimation of Respiratory Rate from Functional Near-Infrared Spectroscopy (fNIRS): A New Perspective on Respiratory InterferenceNaser Hakimi0Mohammad Shahbakhti1Sofia Sappia2Jörn M. Horschig3Mathijs Bronkhorst4Marianne Floor-Westerdijk5Gaetano Valenza6Jeroen Dudink7Willy N. J. M. Colier8Artinis Medical Systems, B.V., Einsteinweg 17, 6662 PW Elst, The NetherlandsArtinis Medical Systems, B.V., Einsteinweg 17, 6662 PW Elst, The NetherlandsArtinis Medical Systems, B.V., Einsteinweg 17, 6662 PW Elst, The NetherlandsArtinis Medical Systems, B.V., Einsteinweg 17, 6662 PW Elst, The NetherlandsArtinis Medical Systems, B.V., Einsteinweg 17, 6662 PW Elst, The NetherlandsArtinis Medical Systems, B.V., Einsteinweg 17, 6662 PW Elst, The NetherlandsBioengineering and Robotics Research Center E. Piaggio and the Department of Information Engineering, School of Engineering, University of Pisa, Via G. Caruso 16, 56122 Pisa, ItalyDepartment of Neonatology, Wilhelmina Children’s Hospital, University Medical Center Utrecht, Lundlaan 6, 3584 EA Utrecht, The NetherlandsArtinis Medical Systems, B.V., Einsteinweg 17, 6662 PW Elst, The NetherlandsObjective: 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 (<inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><msub><mi>O</mi><mn>2</mn></msub><mi>H</mi><mi>b</mi></mrow></semantics></math></inline-formula>) 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 <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><msub><mi>O</mi><mn>2</mn></msub><mi>H</mi><mi>b</mi></mrow></semantics></math></inline-formula> 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 <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><msub><mi>O</mi><mn>2</mn></msub><mi>H</mi><mi>b</mi></mrow></semantics></math></inline-formula> 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.https://www.mdpi.com/2079-6374/12/12/1170fNIRSrespiratory rateestimationsignal quality indexphysiological interference |
| spellingShingle | Naser Hakimi Mohammad Shahbakhti Sofia Sappia Jörn M. Horschig Mathijs Bronkhorst Marianne Floor-Westerdijk Gaetano Valenza Jeroen Dudink Willy N. J. M. Colier Estimation of Respiratory Rate from Functional Near-Infrared Spectroscopy (fNIRS): A New Perspective on Respiratory Interference Biosensors fNIRS respiratory rate estimation signal quality index physiological interference |
| title | Estimation of Respiratory Rate from Functional Near-Infrared Spectroscopy (fNIRS): A New Perspective on Respiratory Interference |
| title_full | Estimation of Respiratory Rate from Functional Near-Infrared Spectroscopy (fNIRS): A New Perspective on Respiratory Interference |
| title_fullStr | Estimation of Respiratory Rate from Functional Near-Infrared Spectroscopy (fNIRS): A New Perspective on Respiratory Interference |
| title_full_unstemmed | Estimation of Respiratory Rate from Functional Near-Infrared Spectroscopy (fNIRS): A New Perspective on Respiratory Interference |
| title_short | Estimation of Respiratory Rate from Functional Near-Infrared Spectroscopy (fNIRS): A New Perspective on Respiratory Interference |
| title_sort | estimation of respiratory rate from functional near infrared spectroscopy fnirs a new perspective on respiratory interference |
| topic | fNIRS respiratory rate estimation signal quality index physiological interference |
| url | https://www.mdpi.com/2079-6374/12/12/1170 |
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