International Meeting for Computational Methods for Mental Health

University Of Minnesota-Twin Cities, Minneapolis MN

Investigators

Abstract

Part 1: This project is about the organization of an international symposium that deals with computational tools for mental health assessment. Early intervention can dramatically improve the individual's quality of life, for many psychiatric disorders. Accounting for 25% of all years of life lost to disability and premature mortality, mental health disorders are the leading cause of disability in the United States and Canada, according to the World Health Organization. Symptoms of mental illness which emerge in childhood and early adolescence are actually the later stages of a process which began years earlier. Hence, psychiatric research is immensely interested in identifying and detecting risk-markers (genetic, neural, behavioral, and/or social deviations) that indicate elevated risk for the development of specific mental illnesses prior to the onset of symptoms. This meeting will be organized at Cyprus where mental health issues are still not addressed appropriately due to cultural issues. The meeting will bring US experts and graduate students together with researchers from University of Cyprus, where new efforts are initiated to deal with the problem by scientists involved with psychiatry and computer science. The complementary skills of CS, ECE, and medical experts from the two countries will benefit this novel research area, and ultimately benefit the U.S and the world. The discussions will be focused on tackling the gap in the current state of the art and developing strategies to minimize that gap. This includes identifying the progress that has already been made while recognizing the pitfalls and determining new opportunities for mental health monitoring using vision and sensor network technologies. Part 2: This project is about the organization of an international meeting that will involve the creation of computational algorithms and intelligent distributed systems to assist with the early diagnosis of individuals who are at risk of developing behavioral disorders. Previous research has indicated that two critical areas of behavioral investigation for use in identifying at-risk individuals have been abnormalities in motor activities and emotional range displays, especially of the face. Motor abnormalities are based on the observation that motor control involves the circuits of the brain associated with dopamine, which are also implicated in behavioral disorders. Many different disorders share the observation of disruption in the emotional range regulation, so monitoring of facial expressions should be discussed. To date, assessments of motor and emotional range have been done by the experts who view and rate videos of an individual. However, these experts? subjective ratings limit the analysis of behavioral conditions to only a narrow range of behaviors, work only for small populations of individual subjects, and are both costly and dependent on the observer's particular expertise. In order to enable a wider population screening, automation is required. The proposed meeting is focused on the development of this automated process that uses vision and sensor networks. Innovative ways of capturing and quantifying the expertise of experts will be presented along with metrics for assessing the evolution of the behavior. In addition, new computational tools that support the evaluation of the effectiveness of interventions will be discussed.