TY - GEN
T1 - Intraoperative neurological monitoring system for robot assisted minimally invasive spine surgery using electromyography
AU - Zhang, Jia
AU - Lu, Wenwen
AU - Jiang, Chaoyan
AU - Song, Shuang
AU - Meng, Max Q.H.
N1 - Publisher Copyright:
© 2017 IEEE.
PY - 2017/10/20
Y1 - 2017/10/20
N2 - In spine surgery, nerve complications are inevitable question for clinicians. Spinal surgery needs to monitor the complete function of the spinal cord and nerve root effectively. However, single neural electrophysiological monitoring technology has limited scope. Influenced by many factors such as anesthesia, blood pressure, body temperature, position, the variant neural signals need to be monitored in real-time by clinician. In this paper, we propose an intraoperative neurological monitoring system for robot assisted minimally invasive spine surgery using electromyography. Signal preprocessing, feature extraction, and decision making procedures have been applied to achieve automatic monitoring and early warning. We also designed the monitoring software interface, which shows the feature of the signals and the reference baseline. The injury probability will also provide to physicians for decision making. Experimental results verified the proposed method.
AB - In spine surgery, nerve complications are inevitable question for clinicians. Spinal surgery needs to monitor the complete function of the spinal cord and nerve root effectively. However, single neural electrophysiological monitoring technology has limited scope. Influenced by many factors such as anesthesia, blood pressure, body temperature, position, the variant neural signals need to be monitored in real-time by clinician. In this paper, we propose an intraoperative neurological monitoring system for robot assisted minimally invasive spine surgery using electromyography. Signal preprocessing, feature extraction, and decision making procedures have been applied to achieve automatic monitoring and early warning. We also designed the monitoring software interface, which shows the feature of the signals and the reference baseline. The injury probability will also provide to physicians for decision making. Experimental results verified the proposed method.
KW - Intraoperative neurological monitoring
KW - electromyography
KW - spinal surgery
UR - https://www.scopus.com/pages/publications/85039944047
U2 - 10.1109/ICInfA.2017.8079075
DO - 10.1109/ICInfA.2017.8079075
M3 - 会议稿件
AN - SCOPUS:85039944047
T3 - 2017 IEEE International Conference on Information and Automation, ICIA 2017
SP - 1150
EP - 1155
BT - 2017 IEEE International Conference on Information and Automation, ICIA 2017
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2017 IEEE International Conference on Information and Automation, ICIA 2017
Y2 - 18 July 2017 through 20 July 2017
ER -