Epilepsy Detection and Monitoring - Quantitative EEG Analysis Methods and Clinical Applications - page 143

eral agreement that, despite pharmacological and surgical advances in the treatment
of epilepsy, seizures cannot be controlled in many patients and there is a need for
new therapeutic approaches [5-7]. Of those unresponsive to anticonvulsant medi-
cation, 7% to 8% may profit from epilepsy surgery. However, about 25% of people
with epilepsy will continue to experience seizures even with the best available treat-
ment [8]. Unfortunately for those responsive to medication, many antiepileptic
medicines have significant side effects that have a negative impact on quality of life.
Some side effects can be of particular concern for women, children, and the elderly.
For these reasons, the need for more effective treatments for pharmacoresistant
epilepsy was among the driving force behind a White House-initiated Curing Epi-
lepsy: Focus on the Future (Cure) Conference held in March 2000 that emphasized
specific research directions and benchmarks for the development of effective and
safe treatment for people with epilepsy. There is growing awareness that the devel-
opment of new therapies has slowed, and to move toward new and more effective
therapies, novel approaches to therapy discovery are needed [9]. A growing body of
research indicates that controlling seizures may be possible by employing a seizure
prediction, closed-loop treatment strategy. If it were possible to predict seizures
with high sensitivity and specificity, even seconds before their onset, therapeutic
possibilities would change dramatically [10]. One might envision a simple warning
system capable of decreasing both the risk of injury and the feeling of helplessness
that results from seemingly unpredictable seizures. Most people with epilepsy seize
without warning. Their seizures can have dangerous or fatal consequences espe-
cially if they come at a bad time and lead to an accident. In the brain, identifiable
electrical changes precede the clinical onset of a seizure by tens of seconds, and these
changes can be recorded in an EEG.
The early detection of a seizure has many potential benefits. Advanced warning
would allow patients to take action to minimize their risk of injury and, possibly in
the near future, initiate some form of intervention. An automatic detection system
could be made to trigger pharmacological intervention in the form of fast-acting
drugs or electrical stimulation. For patients, this would be a significant break-
through because they would not be dependent on daily anticonvulsant treatment.
Seizure prediction techniques could conceivably be coupled with treatment strate-
gies aimed at interrupting the process before a seizure begins. Treatment would then
only occur when needed, that is, on demand and in advance of an impending sei-
zure. Side effects from treatment with antiepileptic drugs, such as sedation and
clouded thinking, could be reduced by on-demand release of a short-acting drug or
electrical stimulation during the preictal state.
Paired with other suitable interventions, such applications could reduce mor-
bidity and mortality as well as greatly improve the quality of life for people with epi-
lepsy. In addition, identifying a preictal state would greatly contribute to our
understanding of the pathophysiological mechanisms that generate seizures. We
discuss the most available seizure detection and prediction algorithms as well as
their potential use and limitations in later sections in this chapter. First, however,
we review the dynamic aspects of epilepsy and the most widely used approached to
detect and predict epileptic seizures.