Objective Assessment of Suicide Ideation using Measures of Electrophysiology Data and Machine Learning

Digital Medical Experts Inc. (DME) is a Canadian start-up company in the business of developing cloud-based point-of-care monitoring systems for the management of psychiatric illnesses. DME has developed algorithms to diagnose and predict optimal treatment for major depression disorder and schizophrenia, and has been allowed patents describing its technology in Canada, the USA, and Australia.
As part of this proposal I will be working with DME to develop and assess the viability of an objective measure of suicide risk taken directly from electroencephalogram (EEG) and electrocardiogram (ECG) recordings. We have already shown that particular interactions of electrical signals in the brain, known as cross-frequency couplings, can be used to characterize brain activity in ways relevant to psychiatric clinical practise. By developing data-driven algorithms, we will examine the robustness of these features for identification of suicidal ideation. If found acceptable the algorithms will be optimized and incorporated into a point-of-care monitoring system (that has already been developed by DME) using portable and wireless dry electrode EEG headsets.

Intern: 
Sinisa Colic
Faculty Supervisor: 
Flavio Kapczinski
Province: 
Ontario
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