- Title
- A dynamic model of brain hemodynamics in near-infrared spectroscopy
- Creator
- Afkhami, Rashid Ghorbani; Walker, Frederick Rohan; Ramadan, Saadallah; Johnson, Sarah
- Relation
- IEEE Transactions on Biomedical Engineering Vol. 67, Issue 7, p. 2103-2109
- Publisher Link
- http://dx.doi.org/10.1109/TBME.2019.2954829
- Publisher
- Institute of Electrical and Electronics Engineers (IEEE)
- Resource Type
- journal article
- Date
- 2020
- Description
- Objective: Near-infrared spectroscopy (NiRS) is a noninvasive technology used in measuring oxy- and deoxy-hemoglobin changes, neural activation, functional connectivity, and vascular health assessment. In this paper, we propose a dynamic model of the NiRS signal to facilitate a better understanding of the underlying elements of this signal and as a means of validation for existing and new NiRS signal processing algorithms. Methods: The model incorporates arterial pulsations, its possible frequency drifts and the reflected waves, the hemodynamic response function (HRF), Mayer waves, respiratory waves and other very low-frequency components of the NiRS signal. Parameter selection and model fitting have been carried out using measurements from a NiRS database. Our database includes 25 participants each with 64 channels, covering all the scalp and therefore providing realistic measures of the varying parameters. Results: We compared synthetic resting-state and HRF-included model outputs with in vivo resting and task-included measurements. The results showed a significant equivalence of the in vivo and synthetic signals. Conclusion: The proposed signal model generates realistic NiRS signals. Significance: The model accepts simple physiological and physical parameters to produce realistic NiRS signals and will accelerate the growth of optical signal processing algorithms.
- Subject
- brain modeling; heart rate; biological system modeling; hemodynamics; electrocardiography; biomedical measurement; functional magnetic resonance imaging
- Identifier
- http://hdl.handle.net/1959.13/1420712
- Identifier
- uon:37633
- Identifier
- ISSN:0018-9294
- Language
- eng
- Full Text
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