Enhancing the reliability of epileptic seizure alarms for scalp EEG signals

One of the key requirement for the development of seizure prediction system is that the seizure alarms generated should be reliable, i.e. the system should have high seizure detection rate and minimum false alarm rate. In this paper, we explore the relationship between the chaotic behavior and energy ratios of the sub bands of an EEG signal. This relationship will then be used to enhance the reliability of seizure alarms generated by measuring the chaoticity of EEG signals using the Largest Lyapunov Exponent (LLE). It is shown, in this paper, that when both LLE and energy ratios of EEG signal sub bands are used to predict an incoming seizure, then the reliability of prediction system gets enhanced; hence any alarm generated in this case must be taken by the patient (caregivers) seriously and appropriate safety measures must also be taken place.