Epilepsy and prediction devices

The unpredictable nature of epileptic seizures poses a significant challenge that can be effectively addressed through the development of a reliable seizure prediction tool. The accurate prediction of seizures in people with epilepsy (PWE) enables timely interventions and the optimization of treatment and self-management. This will further lead to more controlled seizures and reduced anxiety, enhancing the ability of PWE to engage in work and daily activities. Seizure prediction allows the identification of physiological changes that precede a seizure, triggering timely alerts for both patients and caregivers. Numerous studies have explored cerebral and noncerebral signals as potential biomarkers of seizure onset and likelihood. Accurate identification of changes in these signals along with the different phases of a seizure is imperative to the development of a seizure prediction device. Remarkable progress in technology has been pivotal in the emergence of innovative machine-learning techniques and wearable devices for human data acquisition. This chapter discusses the latest advancements in this emerging field and provides insights into important considerations for developing seizure prediction devices. Seizure prediction encompasses a multidisciplinary approach that involves the integration of clinical value, personalized care, and technological advancements. While there is rapid growth in studies focusing on the development and refinement of seizure prediction algorithms, there remains a need for more comprehensive datasets and insights on user perspectives in order to fully realize the benefits of seizure prediction within the epilepsy community.