ABSTRACT: Epilepsy is a neurological condition in which the electrical activity of groups of nerve cells or neurons in the brain becomes disturbed. In the extreme of cases, this abnormal activity causes convulsions, muscle spasms, and loss of consciousness in the patient. There are several factors that contribute to the triggering of an epileptic seizure. Among these factors are external stimuli such as flashing lights or sudden changes from dark to light, loud noises or monotonous sounds, or even certain musical notes.
This paper focuses on the development of a real-time DSP-based system that will assist a patient that suffers from epileptic attacks that are specifically triggered by Seizure Inducing (SI) stimuli consisting of loud and sudden sounds from telephone ringing and pagers. It has been observed, however, that if the patient is forewarned of the impending occurrence of these sounds he is able to prepare himself for the event and avoid a seizure. The system developed in this project provides the kind of advanced warning needed by the patient.
The system will integrate a parallel Adaptive Line Enhancer structure that will divide the available input spectrum into individual frequency bands that will be analyzed separately. An Adaptive Line Enhancer and Detector (ALE-D) will evaluate each frequency band for the purposes of extracting any periodic component present in the incoming input audio signal. This paper examines the performance of this structure in terms of how accurately it will detect any signal whose spectral content varies with time and how fast it can provide a timely warning signal to the patient that this seizure inducing sound is about to occur. To date, the system has only been implemented and tested off-line using the Matlab and Simulink simulation packages. The results available for analysis have been produced using several recorded audio segments containing speech and different telephone rings.