Anesthesia depth evaluation algorithm based on permutation and combination entropy

2021 ◽  
Author(s):  
Wenwen Zhang ◽  
Hong Yu ◽  
Zongsheng Duan ◽  
Tingting Yu ◽  
Xinbai Li
Keyword(s):  
Evaluation Algorithm ◽  
Anesthesia Depth

Monitoring anesthesia depth: look to the brain!

2020 ◽  
Vol 86 (6) ◽  
Author(s):  
Rossella Garra ◽  
Carmela Riso
Keyword(s):  
The Brain ◽  
Anesthesia Depth

Lightweight evaluation algorithm for infix arithmetic expression

2013 ◽  
Vol 33 (11) ◽  
pp. 3163-3166
Author(s):  
Yu BAI ◽  
Xian'e GUO
Keyword(s):  
Arithmetic Expression ◽  
Evaluation Algorithm

scholarly journals NDN congestion control based on fuzzy comprehensive evaluation algorithm

2021 ◽  
Vol 1883 (1) ◽  
pp. 012008
Author(s):  
Gaolin Cui ◽  
Hui Wang ◽  
Zhihui Fan ◽  
Peiyu Li
Keyword(s):  
Congestion Control ◽  
Comprehensive Evaluation ◽  
Fuzzy Comprehensive Evaluation ◽  
Evaluation Algorithm

scholarly journals Preliminary Study of the Use of Root with Sedline® EEG Monitoring for Assessment of Anesthesia Depth in 6 Horses

2020 ◽  
Vol 10 (3) ◽  
pp. 1050
Author(s):  
Olga Drewnowska ◽  
Bernard Turek ◽  
Barbara Lisowska ◽  
Charles E. Short
Keyword(s):  
Brain Activity ◽  
Muscle Relaxation ◽  
Eeg Monitoring ◽  
Careful Monitoring ◽  
Spectral Edge Frequency ◽  
Non Invasive ◽  
Anesthesia Monitoring ◽  
Physiologic Parameters ◽  
Preliminary Study ◽  
Anesthesia Depth

Management of equine anesthesia monitoring is still a challenge. Careful monitoring to provide guidelines for anesthesia depth assessment currently relies upon eye signs, cardiopulmonary responses, and the level of muscle relaxation. Electroencephalography, as a non-invasive brain activity monitor, may be used to complement the routinely monitored physiologic parameters. Six horses, undergoing various surgical procedures and anesthesia protocols, were monitored with the use of a Root with Sedline EEG monitor and a routine monitor of life parameters. The life parameters were compared to the changes on the EEG density spectral array observed live during anesthesia. During all procedures the level of awareness was monitored using the EEG, with higher frequency and power of waves indicating a higher level of awareness. It was evident from this that there were variations according to the type of procedure and the anesthetic protocol. Cerebral activity was elevated during painful moments of the surgery and recovery, requiring adjustments in anesthetic concentrations. Evaluation of changes in the spectral edge frequency (SEF) could show the periods when the patient is stabilized. EEG monitoring has the potential to be used in clinical anesthesiology of horses. It was shown that this system may be used in horses under general anesthesia but is currently less effective in a standing horse for diagnostic or minor procedures.

A fast error evaluation algorithm for polynomial approximation

1977 ◽  
Vol 6 (1) ◽  
pp. 18-21
Author(s):  
Francis Chin ◽  
Kenneth Steiglitz
Keyword(s):  
Polynomial Approximation ◽  
Error Evaluation ◽  
Evaluation Algorithm
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