A multimodal seizure detection artificial intelligence-based smart wear

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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). 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. 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. Social, ethical, environmental, economic, and legal implications will be taken into account to ensure a smooth and rapid translation to patients with epilepsy. Potential applications are numerous for the benefit of patients (reducing anxiety and enhancing selfconfidence), caretakers (evaluation and surveillance), and the healthcare system (reducing associated costs).