Determination of Human Brain-based Motor Control Signals Using a Decomposition Wavelet Algorithm and Multi-channel Functional Near-infrared Spectroscopy

Brain signals provides useful information for understanding the nature of human control decisions. The objective of this present work is to estimate brain-based motor control signals in Brain's cerebral cortex region using multi-channel near-infrared spectroscopy and a Decomposition Wavelet (DW) algorithm. Acquisition of brain signals using multi-channel functional Near-infrared Spectroscopy (fNIRS) is very noisy. So this is a research challenge to all researchers in detecting features of human brain. First, data acquisition was done on fNIRS machine to produce brain data containing features of brain activities during finger motor task. Second, a discrete DW algorithm with digital filters was applied to decompose this signal as well as to determine brain features using statistical method of measure times. As results, we found stable and accuracy patterns of executed motor task during different trials. Thus, our computational results showed the effectiveness of our methodology for detecting motor control tasks.