Automatic detection of intraoperative neurological injury

Author

Williams, Luke V. ; Eswaran, C.

Author_Institution

Dept. of Electr. Eng., Indian Inst. of Technol., Madras, India

Volume

46

Issue

4

fYear

1999

fDate

4/1/1999 12:00:00 AM

Firstpage

481

Lastpage

483

Abstract

Neurological injuries occurring during high-risk surgical procedures can be detected by monitoring intraoperative evoked potential signals. In this communication, an automatic injury detection algorithm is proposed in which the EP signal is modeled as a pole-zero filter and then the model parameters are applied as inputs to a classifier type neural network. A recognition rate of 96% is achieved using an experimental model of brain injury.

Keywords

bioelectric potentials; brain; medical signal detection; neural nets; neurophysiology; patient monitoring; surgery; automatic injury detection algorithm; brain injury experimental model; classifier type neural network; discrete cosine transform; high-risk surgical procedures; intraoperative evoked potential signals monitoring; intraoperative neurological injury; model parameters; pole-zero filter; recognition rate; Biological neural networks; Brain injuries; Discrete cosine transforms; Filters; Monitoring; Multi-layer neural network; Signal processing; Signal processing algorithms; Signal to noise ratio; Surgery; Algorithms; Animals; Brain Injuries; Cats; Evoked Potentials, Somatosensory; Models, Neurological; Monitoring, Intraoperative; Neural Networks (Computer); Signal Processing, Computer-Assisted;

fLanguage

English

Journal_Title

Biomedical Engineering, IEEE Transactions on

Publisher

ieee

ISSN

0018-9294

Type

jour

DOI

10.1109/10.752945

Filename

752945