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A machine learning approach for non-intrusive physiological and behavioral monitoring in mental healthcare settings.

A machine learning approach for non-intrusive physiological and behavioral monitoring in mental healthcare settings.

Quality care and patient safety are essential in everyday hospital care. Today, patients admitted to hospitals are monitored manually around the clock for assessment of their conditions. Under such monitoring, most patients experience disruptions in their private lives. Such procedures are also costly and inefficient in terms of both workhour usage and workload for involved professionals.

Egde Consulting (Egde) has, for several years, focused on e-health and how the digitalization of the health care system can improve the quality and efficiency of health services. To address complex issues of manual monitoring, Egde recognizes the importance of research-based innovation and therefore invests heavily in research into the digitization of healthcare. One of the areas Egde invests in is how the use of artificial intelligence can improve health services.

Micheal Dutt works at Egde Consulting and is pursuing an Industrial Ph.D. at the University of Agder (UiA). His primary focus is to find out how artificial intelligence can help improve the quality and efficiency of mental health services. He aims to support health professionals through his industrial Ph.D. project, which aims to develop and evaluate machine learning-based monitoring systems' performance. He will build machine learning algorithms based on data collected from non-contact sensors and assist the health care provider in remote monitoring of patients.

Micheal Dutt's Ph.D. will result in a system that performs several necessary monitoring and maintenance tasks automatically with minimal medical personnel involvement. This innovation will result in higher labor efficiency, along with a significantly reduced operating cost. This project also aims to promote the field of machine learning-based monitoring of patients with sensors.

The project is an initiative where Egde, Sørlandet hospital, and UiA are working closely together. Before this project, SSHF carried out a pilot project with a sensor-based system provided by Egde. The pilot project's testing period lasted from January 2019 to June 2019, with equipment installed in 8 patient rooms in the psychiatric ward at SSHF and 45 patients participating.

Micheal Dutt holds a Master's degree in Artificial Intelligence from the UiA. He works as an artificial intelligence consultant in Egde with a primary focus on the e-health sector. At the same time, he is pursuing an Industrial Ph.D. at the Center for Artificial Intelligence Research (CAIR) in collaboration with Dr. Morten Goodwin and Prof. Christian Omlin. From Sørlandet Hospital HF, Vegard Øksendal Haaland is the supervisor for Micheal in his doctorate.

CAIR Researchers