Novel signal processing of brain activity based on Ant Colony Optimization and wavelet analysis with near infrared spectroscopy

Abstract

Signal processing of brain activity is becoming challenging to various researchers from different areas, including medical, biomedical, and engineering researchers. In this paper, investigations of brain activity are made from experimental works, with optical flow based on spatiotemporal analysis and wavelet over the equipment of Near Infrared Spectroscopy (NIRS). Ant Colony Optimization (ACO) algorithm is employed for obtaining the distributions of the intensity of the targeted image. The major outcomes of this paper from our research are the following items: (a) optical flow can be a proper technology for the investigation of brain activity based on NIRS; (b) the analyses of the temporal domain, the spatial domain, and the wavelet domain underpinned coherently to our experimental results; (c) our wavelet analysis can define the most brain activity image, denoted as targeted image; (d) the details of the intensity distributions on the targeted image show the most significant brain activity via ACO algorithm; (e) we can clearly observe, via our algorithm technology, the existence of the so-called Dominant Channel (DC) based on spatiotemporal analysis and it plays a critical role in brain activity. The spatial distribution of the origin of cortical activity can be described by hemodynamic response in the cerebral cortex after evoked stimulation using near infrared spectroscopy. Further application of this research is expected in the next step research outcomes.