Noise removal of functional Near Infrared Spectroscopy signals using Emperical Mode Decomposition and Independent Component Analysis

In this work, we propose the combination of emperical mode decomposition (EMD) method and independent component analysis (ICA) to extract the heart rate signal. EMD is the fundamental part of Hilbert – Huang transform which is used to decompose signal into intrinsic mode functions that are not set analytically and are instead determined by an analyzed sequence alone. ICA uses Hyvarinen's fixed-point algorithm to estimate the independent components from given multidimensional signals. Our proposed approach is able to extract the heart rate signal from multiple fNIRS channels with the accuracy of 80% to 90% compared with the one measured from the real device. Our further work will integrate this result with noise attenuation using adaptive filters to mitigate the global inference of physiological activities to fNIRS measurement.