Disturbance elimination in near-infrared spectroscopy by correlated empirical mode decomposition

Near-infrared spectroscopy (NIRS) is a noninvasive measurement method used to gain the information regarding brain activities through the scalp. Near-infrared light can penetrate several centimeters into the scalp tissue and indicate the oxygen concentration in the outer part of the cerebral cortex. Three major disturbances of NIRS are respiratory, the heartbeat, and Mayer waves. The nonlinear coupling between signals and noise can lead to the loss of meaningful information when linear noise-removal methods are applied. To resolve this problem, correlated empirical mode decomposition (CEMD), a new algorithm used to extract the common modes between two correlated signals, was adopted to separate the signal and disturbance. Public NIRS data were used as a pure input signal, and respiratory and electrocardiogram signals were added to it. The correlated intrinsic mode functions associated with the known disturbances were eliminated through the CEMD screening process. The spectrum results indicated that the energy of the additional signals can be eliminated. The CEMD method can eliminate the disturbances and thus reduce their effects on signal analyses.

I. Introduction

Near-infrared spectroscopy (NIRS) is a spectroscopic method of assessing energy variation in the near-infrared region. This mechanism was discovered in the nineteenth century, applied in chemical experiments in the twentieth century, and has been widely used in biomedical-related applications in the past 20 years. NIRS projects near-infrared (NIR) light in a specific wavelength (650–900 nm), called the bio-window, wherein the wavelength range of photons can deeply penetrate the scalp tissue to the outer part of the cerebral cortex. NIR light can penetrate several centimeters into tissue [1], and water is the principle absorber of light in the head. The lower light absorption coefficient of infrared light enables it to reveal useful information before being absorbed. Therefore, this region of the electromagnetic spectrum is defined as the optical window for brain tissue evaluation. Through the reflected light, the NIRS method can be used to monitor local tissue oxygenation based on the diffusion and absorption of light photons in human tissue. The noninvasive nature of NIRS made it popular in the last decade, and numerous new applications have been discovered, including monitoring brain and muscle oxygenation [2] and brain-computer interfaces [3].