Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
4976479 | Journal of the Franklin Institute | 2007 | 18 Pages |
Abstract
Experimental results confirm that the optimal fractal-scaling exponent on the raw EEG data can clearly discriminate between awake to moderate and deep anesthesia levels and have robust relation with the well-known depth of anesthesia index (BIS). When the patient's cerebral states change from awake to moderate and deep anesthesia, the fractal-scaling exponent increases from 0.8 to 2 approximately. Moreover, our new algorithm significantly reduces computational complexity and produces faster reaction to transients in patients' consciousness levels compared to other algorithms and technologies.
Related Topics
Physical Sciences and Engineering
Computer Science
Signal Processing
Authors
P. Gifani, H.R. Rabiee, M.H. Hashemi, P. Taslimi, M. Ghanbari,