EpiSense: Towards a smart solution for epileptic patients’ care

Abstract

Epilepsy is a chronic neurological brain disorder that affects 50 million people globally. There are several challenges associated with the care of epileptic patients, including: 1) the timely and accurate diagnosis of the condition; 2) the long-term non-intrusive monitoring and detection of epileptic seizures in real time for suitable interventions; 3) alleviating the mental health issues associated with epilepsy, such as anxiety and depression; and 4) the lack of availability of large scale datasets related to epileptic patients with different profiles, needed to advance research in epilepsy. In this work, we propose EpiSense – a smart healthcare solution for epileptic patients’ care. EpiSense leverages sensory, mobile, and web technologies, as well as machine learning techniques for the real-time detection of epileptic seizures. As part of the system, a patient’s mobile app. is provided to allow the detection of seizures’ occurrence in real time and the sending of alarm notifications to care takers, for appropriate actions. Moreover, a web portal enables doctors to view the progress of their patients and get notified about seizures’ occurrence and statistics. The EpiSense system was designed and implemented, and three machine learning models were tested for real-time epileptic seizure detection. This work gives interesting insights about the possibility of using sensory technologies and data analytics for the improvement of epileptic patients’ care, and offers the possibility of personalized healthcare management.