Using the modular neural network in simulation of the bispectral index for children patients anesthesia depth

• Main Authors: Chia-Hong Yeng, 顏嘉宏
• Other Authors: none
• Format: Others
• Language: zh-TW
• Published: 2006
• Online Access: http://ndltd.ncl.edu.tw/handle/15218276331030176084

碩士 === 立德管理學院 === 應用資訊研究所 === 95 === The bispectral index is an empirically calibrated number derived from adult electroencephalograph dada that correlates with the depth of sedation in adult. During the surgical anesthesia process, anesthesia clinicians and professional anesthetists usually take the bispectral index as the effects of deep of anesthesia in the superior hospital. This index allows clinicians to deliver anesthesia with more precision and respond more appropriately to the condition of a patient during surgery. However, it is lack of the bispectral index as a measure of the effects of anesthesia that anesthesia clinicians operate in secondary hospital. Clinical signs are much different existed in pediatric and adult patients. In order to lower the errors in pediatric anesthetic depth, this research tries to develop an algorithm of modular back-propagation neural network in simulation of anesthetic index for pediatric patient by clinical signs. This research can provide an alternative in measuring anesthetic depth to monitor child patient in the effects of anesthesia during surgical operations.