Correction of motion artifacts and serial correlations for real-time functional near-infrared spectroscopy

Abstract

Abstract. Functional near-infrared spectroscopy (fNIRS) is a relatively low-cost, portable, noninvasive neuroimaging technique for measuring task-evoked hemodynamic changes in the brain. Because fNIRS can be applied to a wide range of populations, such as children or infants, and under a variety of study conditions, including those involving physical movement, gait, or balance, fNIRS data are often confounded by motion artifacts. Furthermore, the high sampling rate of fNIRS leads to high temporal autocorrelation due to systemic physiology. These two factors can reduce the sensitivity and specificity of detecting hemodynamic changes. In a previous work, we showed that these factors could be mitigated by autoregressive-based prewhitening followed by the application of an iterative reweighted least squares algorithm offline. This current work extends these same ideas to real-time analysis of brain signals by modifying the linear Kalman filter, resulting in an algorithm for online estimation that is robust to systemic physiology and motion artifacts. We evaluated the performance of the proposed method via simulations of evoked hemodynamics that were added to experimental resting-state data, which provided realistic fNIRS noise. Last, we applied the method post hoc to data from a standing balance task. Overall, the new method showed good agreement with the analogous offline algorithm, in which both methods outperformed ordinary least squares methods.

Comparison of group-level, source localized activity for simultaneous functional near-infrared spectroscopy-magnetoencephalography and simultaneous fNIRS-fMRI during parametric median nerve stimulation

“…13 In addition, we have recently detailed several methods for improved time-series analysis and generalizations of the linear model to deal with fNIRS specific noise structures. 11,35,36 In this work, we have presented an analysis pipeline combining these recent advancements that allows all Table 3 Spatial correlation. The correlation of the activation patterns between the estimated localizer responses.…”

The NIRS Brain AnalyzIR Toolbox

“…It is not uncommon to observe a several-fold difference in the signal-to-noise ratio in measurements between areas with little hair (e.g., the forehead) and those with hair or thicker bone structure (e.g., the occipital). The use of statistical models whose assumptions do not match these properties often results in unacceptable false-discovery and uncontrolled type-I errors.As our group has reviewed in several recent publications [9,10,[15][16][17][18], these noise features and unique statistical properties of fNIRS data need to be properly considered and will be briefly summarized in this publication in the context of a new fNIRS analysis toolbox.The primary rationale for the development of the AnalyzIR (pronounced "an-a-lyze-er") toolbox was to create a statistical analysis package to specifically address the properties of fNIRS data. This toolbox was designed to capture and preserve as much of this fNIRS-specific information and noise as possible through the entire analysis pipeline such that first-and higher-level statistical analysis methods could use this information in statistical models by utilizing covariance whitening, accounting for dependent noise terms, and using robust statistical methods.…”

“…As our group has reviewed in several recent publications [9,10,[15][16][17][18], these noise features and unique statistical properties of fNIRS data need to be properly considered and will be briefly summarized in this publication in the context of a new fNIRS analysis toolbox.…”

Real-Time Reduction of Task-Related Scalp-Hemodynamics Artifact in Functional Near-Infrared Spectroscopy with Sliding-Window Analysis

“…In this way, the brain activation may be overestimated. To overcome this negative effect, further studies should implement correction methods, for example, precoloring or an autoregressive model in real-time [38][39][40].…”