Epilepsy is a common, devastating and still incurable disorder. Although in most cases its symptoms can be ameliorated by life-long pharmaceutical treatment, still this treatment needs continuous adjustment and change to retain its efficacy. Due to its multifactorial causes and paroxysmal nature, epilepsy needs multi-parametric monitoring for purposes of accurate diagnosis, prediction, alerting and prevention, treatment follow-up and presurgical evaluation.
Current diagnostic methodologies and the need for advancement in this area comprise yet another important factor making epilepsy a prominent disorder to tackle. Such methodologies include video EEG that records the habitual suspected event or ambulatory EEG without video (for long term home recordings). Sensors that detect crucial autonomic, motor or other changes that cannot be appreciated by the video and the scalp EEG electrodes are seldom used in the EEG departments and when used a limited coverage is applied, while ambulatory EEG does not include such sensors. Therefore, there is a need for more accurate diagnosis of integrated seizure phenotype in individual patients, allowing better understanding of underlying mechanisms, prediction (and alert) of time and type of seizure (and alert) and availability of medical assistance and advice.
Reliable diagnosis requires state of the art monitoring and communication technologies providing real-time, accurate and continuous brain and body multi-parametric data measurements, suited to the patient's medical condition and normal environment and facing issues of patient and data security, integrity and privacy.
It is recognized that epilepsy is a major medical problem which can be solved with current advanced ICT technology and further advancements in data analysis, in a way which benefits both the patient and the knowledge domain of epilepsy.