ArticleBiosensors2022
Estimation of Respiratory Rate from Functional Near-Infrared Spectroscopy (fNIRS): A New Perspective on Respiratory Interference.
Article in Biosensors, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
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Who cites it
10 citing papers in PubMed, 14 citations in OpenAlex.
- Advances in fully integrated wearable near-infrared spectroscopy: hardware innovations and biomedical applications.JPhys photonics · 2026Review
- Time-Resolved Information-Theoretic and Spectral Analysis of fNIRS Signals from Multi-Channel Prototypal Device.Entropy (Basel, Switzerland) · 2025Article
- Oxygen-dependent functional brain haemodynamic response.Biomedical optics express · 2025Article
- A Personalized Multimodal BCI-Soft Robotics System for Rehabilitating Upper Limb Function in Chronic Stroke Patients.Biomimetics (Basel, Switzerland) · 2025Article
- Enhanced Joint Heart and Respiratory Rates Extraction from Functional Near-infrared Spectroscopy Signals Using Cumulative Curve Fitting Approximation.Journal of medical signals and sensors · 2025Article
- Human Stress Classification Using Cardiovascular and Respiratory Data Based on Machine Learning Techniques.Journal of medical signals and sensors · 2025Article
- The road toward a physiological control of artificial respiration: the role of bio-inspired neuronal networks.Frontiers in neuroscience · 2025Article
- Near-Infrared Spectroscopy for Neonatal Sleep Classification.Sensors (Basel, Switzerland) · 2024Article
- Respiratory Rate Extraction from Neonatal Near-Infrared Spectroscopy Signals.Sensors (Basel, Switzerland) · 2023Article
- Estimation of Respiratory Rate during Biking with a Single Sensor Functional Near-Infrared Spectroscopy (fNIRS) System.Sensors (Basel, Switzerland) · 2023Article
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Authors and funding
9 authors at 3 institutions in 3 countries.
Funding
Abstract
objectiveRespiration 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.
methodsfNIRS 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.
resultsThe 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.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.