Entropy Analysis Algorithms Applied in Depth of Anesthesia in Operating Theater

• Main Authors: Dai-Wei Huang, 黃大維
• Other Authors: 謝建興
• Format: Others
• Language: en_US
• Published: 2011
• Online Access: http://ndltd.ncl.edu.tw/handle/72255220126920779485

碩士 === 元智大學 === 機械工程學系 === 99 === Anesthesia is an essential part of a successful operation. Inappropriate depth of anesthesia (DOA) can cause severe complications. Until recently, the depth of anesthesia was dependent on the anesthesiologist subjective judgment. Recently, research has tried to quantify the depth of anesthesia. However, this quantification of the depth of anesthesia is only well correlated with some anesthetics. Many medical devices try to assist doctors to determine the depth of anesthesia. This thesis is based on existing operating room equipment commonly used by Datex AS5 EEG module to collect RE/SE (response entropy / state entropy) signals and electroencephalogram (EEG) signals. We used digital filtering to filter EEG noise. Then sample entropy (SampEn) was used to analyze the EEG signals. Finally, the offline results of sample entropy analysis of different parameters were compared with RE / SE. The data collected in this thesis is from urology surgery. 10 patients’ RE/SE signals were compared with a sample entropy index. ROC (Receiver Operating Characteristics) curve and Mann-Whitney test analysis results show that sample entropy and RE / SE index are quite similar, but the RE / SE method is difficult to obtain the details. In contrast, we can change the sample entropy analysis of the parameters in different types of patient. This allows us to write this algorithm into real time analysis in the future.