Title :
Autoregressive coefficient changes of EEG signal model
Author_Institution :
Dept. of Process Control, Tech. Univ. Budapest, Hungary
Abstract :
Clinical records of intraoperative ischemic EEG are used to optimize an automatic detecting algorithm which is capable of signaling the onset of the insult accurately at a small delay. The algorithm derives autoregressive (AR) coefficients on all channels, and searches for simultaneous changes, which has earlier been found to be characteristic of the ischemic change. A set of 32 clinical recordings were used to determine optimal parameter thresholds. An intraoperative clinical monitor based on the present method may be of great help in reducing intervention related risk during carotid and cardiac operations
Keywords :
autoregressive processes; electroencephalography; medical signal processing; patient monitoring; surgery; EEG signal model; autoregressive coefficient changes; cardiac operations; carotid operations; clinical recordings; delay; intervention related risk reduction; intraoperative clinical monitor; intraoperative ischemic EEG; optimal parameter thresholds; optimized automatic detecting algorithm; simultaneous change searching; Brain modeling; Change detection algorithms; Electroencephalography; Event detection; Frequency; Ischemic pain; Monitoring; Nonlinear filters; Signal analysis; Signal processing;
Conference_Titel :
Information Technology Applications in Biomedicine, 1997. ITAB '97., Proceedings of the IEEE Engineering in Medicine and Biology Society Region 8 International Conference
Conference_Location :
Prague
Print_ISBN :
0-7803-4318-2
DOI :
10.1109/ITAB.1997.649405