Małgorzata Sochacka

Title

Artificial intelligence in continuous and objective monitoring of affective disorders

Abstract

Affective disorders, including bipolar disorder and depression, are the leading causes of work absence and suicide worldwide. Patients experiencing acute episodes require close surveillance or hospitalization, while stable patients need continuous monitoring to prevent relapses. Currently, patient monitoring relies on subjective assessments of behavioural markers such as physical activity, social interactions, sleep patterns, spending habits, and speech characteristics. However, key challenges include maintaining objectivity and managing the costs and effort required for sustained monitoring. 

Since the early 21st century, research has explored the use of modern technology to support objective and continuous monitoring of psychiatric patients, particularly those with mood disorders. Building on earlier work, the MoodMon system was developed and clinically tested, demonstrating both security and high effectiveness in detecting early symptoms of mental state shifts in individuals with affective disorders. 

Biography

Małgorzata Sochacka earned her PhD from Warsaw Technical University in 1993. She has over 20 years of experience in fundamental research in physical optics and more than 25 years in IT industry management. Since 2016, her work has focused on AI applications for monitoring affective disorders. As a co-founder and key driving force behind the MoodMon system, she is dedicated to advancing technology in mental health monitoring.