TY - GEN
T1 - Signal processing of brain activity with ant colony optimization and wavelet analysis using near infrared spectroscopy
AU - Huang, Xu
AU - Fernandez-Rojas, Raul
AU - Ou, Keng Liang
N1 - Publisher Copyright:
© 2016 IEEE.
PY - 2016/9/7
Y1 - 2016/9/7
N2 - Signal processing of brain activity poses challenges to various researchers from different areas, including medical, biomedical, and engineering researchers. Taking the benefits from rapidly developing higher technologies, the outcomes of the research into brain activity have made great progresses. In this paper, investigations of brain activity are made from experimental works, with optical flow based on spatiotemporal analysis and wavelet with 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 our research are the following five items: (1) optical flow is a proper technology for the investigation of brain activity based on NIRS; (2) the results of the temporal domain, spatial domain, and wavelet domain support each other through experimental results; (3) our wavelet analysis offers the most brain activity, defined as targeted image; (4) the details of the intensity distribution on the targeted image show the most significant brain activity via ACO; (5) 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.
AB - Signal processing of brain activity poses challenges to various researchers from different areas, including medical, biomedical, and engineering researchers. Taking the benefits from rapidly developing higher technologies, the outcomes of the research into brain activity have made great progresses. In this paper, investigations of brain activity are made from experimental works, with optical flow based on spatiotemporal analysis and wavelet with 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 our research are the following five items: (1) optical flow is a proper technology for the investigation of brain activity based on NIRS; (2) the results of the temporal domain, spatial domain, and wavelet domain support each other through experimental results; (3) our wavelet analysis offers the most brain activity, defined as targeted image; (4) the details of the intensity distribution on the targeted image show the most significant brain activity via ACO; (5) 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.
KW - ACO
KW - brain activity
KW - hemodynamicreaction
KW - near infrared spectroscopy
KW - optical flow
KW - wavelet
UR - http://www.scopus.com/inward/record.url?scp=84988810561&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84988810561&partnerID=8YFLogxK
U2 - 10.1109/CCE.2016.7562654
DO - 10.1109/CCE.2016.7562654
M3 - Conference contribution
AN - SCOPUS:84988810561
T3 - 2016 IEEE 6th International Conference on Communications and Electronics, IEEE ICCE 2016
SP - 306
EP - 311
BT - 2016 IEEE 6th International Conference on Communications and Electronics, IEEE ICCE 2016
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 6th IEEE International Conference on Communications and Electronics, IEEE ICCE 2016
Y2 - 27 July 2016 through 29 July 2016
ER -