Neural Networks in Seizure Diagnosis.
Abstract
A monitor has been designed to detect the onset of status epilepticus associated with complex partial seizures in children. A unique sensor technology was developed to detect the minor, barely perceptible tremors characteristic of partial seizures. A microcontroller analyzes the sensor data and activates a remote tetherless alarm when a seizure is detected. However, the sensor response is similar for both casual and seizure activity, therefore, false alarms do occur. Neural networks have been studied as a means of analyzing the sensor response and differentiating seizure activity from casual motion. The network uses elements of the normalized power spectrum of the response data as a feature set. Our results indicate this approach provides a faster and more reliable means of accurately detecting seizures than the method currently employed.
Document Details
- Document Type
- Technical Report
- Publication Date
- Mar 01, 1995
- Accession Number
- ADA295629
Entities
People
- G. Kendall
- Lawrence V. Meisel
- Marc A. Johnson
- Paul J. Cote
Organizations
- United States Army Armament Research, Development and Engineering Center