+ Site Statistics
+ Search Articles
+ PDF Full Text Service
How our service works
Request PDF Full Text
+ Follow Us
Follow on Facebook
Follow on Twitter
Follow on LinkedIn
+ Subscribe to Site Feeds
Most Shared
PDF Full Text
+ Translate
+ Recently Requested

Separating heart and brain: on the reduction of physiological noise from multichannel functional near-infrared spectroscopy (fNIRS) signals



Separating heart and brain: on the reduction of physiological noise from multichannel functional near-infrared spectroscopy (fNIRS) signals



Journal of Neural Engineering 11(5): 056010



Functional near-infrared spectroscopy (fNIRS) is an emerging technique for the in vivo assessment of functional activity of the cerebral cortex as well as in the field of brain-computer interface (BCI) research. A common challenge for the utilization of fNIRS in these areas is a stable and reliable investigation of the spatio-temporal hemodynamic patterns. However, the recorded patterns may be influenced and superimposed by signals generated from physiological processes, resulting in an inaccurate estimation of the cortical activity. Up to now only a few studies have investigated these influences, and still less has been attempted to remove/reduce these influences. The present study aims to gain insights into the reduction of physiological rhythms in hemodynamic signals (oxygenated hemoglobin (oxy-Hb), deoxygenated hemoglobin (deoxy-Hb)). We introduce the use of three different signal processing approaches (spatial filtering, a common average reference (CAR) method; independent component analysis (ICA); and transfer function (TF) models) to reduce the influence of respiratory and blood pressure (BP) rhythms on the hemodynamic responses. All approaches produce large reductions in BP and respiration influences on the oxy-Hb signals and, therefore, improve the contrast-to-noise ratio (CNR). In contrast, for deoxy-Hb signals CAR and ICA did not improve the CNR. However, for the TF approach, a CNR-improvement in deoxy-Hb can also be found. The present study investigates the application of different signal processing approaches to reduce the influences of physiological rhythms on the hemodynamic responses. In addition to the identification of the best signal processing method, we also show the importance of noise reduction in fNIRS data.

Please choose payment method:






(PDF emailed within 0-6 h: $19.90)

Accession: 055716072

Download citation: RISBibTeXText

PMID: 25111822

DOI: 10.1088/1741-2560/11/5/056010


Related references

Noise reduction in functional near-infrared spectroscopy signals by independent component analysis. Review of Scientific Instruments 84(7): 073106, 2013

Reconstructing functional near-infrared spectroscopy (fNIRS) signals impaired by extra-cranial confounds: an easy-to-use filter method. Neuroimage 95: 69-79, 2014

Brain activation for alertness measured with functional near infrared spectroscopy (fNIRS). Psychophysiology 45(3): 480-486, 2008

Measurement of brain function of car driver using functional near-infrared spectroscopy (fNIRS). Computational Intelligence and Neuroscience 2009: 164958, 2009

Prefrontal Brain Activation During Emotional Processing: A Functional Near Infrared Spectroscopy Study (fNIRS). Open Neuroimaging Journal 5: 33-39, 2011

Functional near-infrared spectroscopy (fNIRS) of brain function during active balancing using a video game system. Gait and Posture 35(3): 367-372, 2012

Functional near infrared spectroscopy (fNIRS): an emerging neuroimaging technology with important applications for the study of brain disorders. Clinical Neuropsychologist 21(1): 9, 2007

Brain activity underlying the recovery of meaning from degraded speech: A functional near-infrared spectroscopy (fNIRS) study. Hearing Research 351: 55-67, 2017

Brain activation during finger tapping and circle-drawing tasks measured by functional near-infrared spectroscopy (fNIRS). Neuroscience Research 68: E442-E443, 2010

Physiological Noise Removal from fNIRS Signals. Biomedizinische Technik. Biomedical Engineering 58(Suppl. 1):, 2013

Physiological Effects of Continuous Colored Light Exposure on Mayer Wave Activity in Cerebral Hemodynamics: A Functional Near-Infrared Spectroscopy (fNIRS) Study. Advances in Experimental Medicine and Biology 977: 277-283, 2017

Temporal classification of multichannel near-infrared spectroscopy signals of motor imagery for developing a brain-computer interface. Neuroimage 34(4): 1416-1427, 2007

Exploring brain functions in autism spectrum disorder: A systematic review on functional near-infrared spectroscopy (fNIRS) studies. International Journal of Psychophysiology 137: 41-53, 2019

Concurrent fNIRS-fMRI measurement to validate a method for separating deep and shallow fNIRS signals by using multidistance optodes. Neurophotonics 2(1): 015003, 2015

Characterization of the relative contributions from systemic physiological noise to whole-brain resting-state functional near-infrared spectroscopy data using single-channel independent component analysis. Neurophotonics 3(2): 025004, 2016