Abstract

Depression is identified as one of the most common mental health disorders in the world. Depression not only impacts the patient but also their families and relatives. If not properly treated, due to these reasons it leads people to hazardous situations. Nonetheless existing clinical diagnosis tools for monitoring illness trajectory are inadequate. Traditionally, psychiatrists use one to one interaction assessments to diagnose depression levels. However, these cliniccentered services can pose several operational challenges. In order to monitor clinical depressive disorders, patients are required to travel regularly to a clinical center within its limited operating hours. These procedures are highly resource intensive because they require skilled clinician and laboratories. To address these issues, we propose a personal and ubiquitous sensing technologies, such as fitness trackers and smartphones, which can monitor human vitals in an unobtrusive manner.

How to Cite
A.A.M.R, KOLAMUNNA K.G.T.D, FERNANDO N.I.R, PANNALA U.K, Dias. Dheergayu: Clinical Depression Monitoring Assistant. Global Journal of Computer Science and Technology, [S.l.], dec. 2020. ISSN 0975-4172. Available at: <https://computerresearch.org/index.php/computer/article/view/1989>. Date accessed: 15 aug. 2022. doi: https://doi.org/10.34257/GJCSTCVOL20IS2PG53.