标题：Assessment of cerebral oxygenation oscillations in subjects with cerebral infarction using near infrared spectroscopy
作者：Li, Zengyong; Lu, Changhou; Wang, Yan; Li, Jianping; Zhang, Liangliang; Wang, Yonghui
作者机构：[Li, Zengyong; Lu, Changhou; Wang, Yan; Li, Jianping; Zhang, Liangliang] Shandong Univ, Sch Mech Engn, Jinan, Peoples R China.; [Wang, Yonghui] Shan 更多
会议名称：4th International Conference on Bioinformatics and Biomedical Engineering (iCBBE)
会议日期：JUN 18-20, 2010
来源：2010 4TH INTERNATIONAL CONFERENCE ON BIOINFORMATICS AND BIOMEDICAL ENGINEERING (ICBBE 2010)
关键词：cerebral infarction; cerebral oxygenation; near infrared spectroscopy;; wavelet transform
摘要：The objective of this study is to assess the cerebral oxygenation oscillations in subjects with cerebral infarction (CI) based on the wavelet transform of near infrared spectroscopy (NIRS) signals. A total of twenty subjects were recruited from a local hosipital to participate in this study. The subjects lay in the supine position and cerebral oxygenation signal was monitored for 20 minutes from the frontal lobe using NIRS. With spectral analysis based on wavelet transform, five frequency intervals were identified (I, 0.005-0.02 Hz, II, 0.02-0.06 Hz, III, 0.06-0.15 Hz, IV, 0.15-0.40 Hz and V, 0.40-2.0 Hz). The amplitude of the [ HbO2] in frequency interval I (0.005-0.02 Hz), II (0.02-0.06 Hz), III (0.06-0.15 Hz) and V(0.15-2 Hz) for the subjects with CI were found to be significantly lower by 36%, 45%, 50% and 69% compared to that for the normal subjects (p< 0.05). The amplitude of the [ Hb] in frequency interval I (0.005-0.02 Hz), II (0.02-0.06 Hz) and V(0.15-2 Hz) for the subjects with CI were found to be significantly lower by 40%, 36% and 69% compared to that for the normal subjects (p< 0.05). The reduction of spontaneous oscillations in subjects with CI may suggest an increased stiffness in cerebral arterial vessels. This indicates the possibility of applying spontaneous oscillations to assessing atherosclerosis in high risk subjects for CI based on the wavelet transform of NIRS signals.