Epilepsy is a chronic condition characterized by recurrent ‘unpredictable’ seizures due to excessive neuronal discharges. It affects ~400,000 people in Canada. Epilepsy is a chronic neurological condition that affects as many as 1 in every 100 Canadians. With the ageing of the population, the prevalence and incidence of epilepsy among the elderly is greater than any other age group due to the increasing number brain insults. The first line of treatment consists of long-term drug therapy but more than a third of patients are said to be drug-resistant and continue to suffer from disabling seizures. Due to their unpredictable nature, uncontrolled seizures represent a major personal handicap and source of worriment for patients (risks of injury and death). Uncontrolled epilepsy is associated with cognitive impairment, psychosocial handicap, psychiatric co-morbidities and 2-3 times the standard mortality rate due to seizure-related injuries or seizure-induced respiratory/cardiac arrest. In addition, persistent seizures constitute a considerable public health burden due to high use of health care resources, high number of disability days or unemployment, and low annual income. For these patients, accurate and rapid detection of seizures could significantly improve their care. Indeed, a system capable of detecting seizures could alert family members, caretakers or medical personnel to intervene in a timely fashion to limit the risk of injuries and death. A new direction of research is to investigate the possibility of accurately detecting (or even predicting) seizures which, if achieved, can lead to novel interventional avenues. With the advent of smart wear-based physiological monitoring and artificial intelligence techniques, we believe it is now possible to accurately and rapidly detect seizures using non-invasive data. Indeed, seizures are associated with changes in saturation, heart rate, respiration, noises, facial and body movements, which may be monitored non-invasively using smart watches, smart clothing, tactile mattresses, accelerometers, microphones and cameras. Hence, the main objective of this project is to develop a user-friendly artificial intelligence-based seizure detection system based on non-invasive multimodal physiological signals obtained through smart wearable devices.