Dheergayu: Clinical Depression Monitoring Assistant

1
dias_a.a.m.r
dias_a.a.m.r
2
Dias A.A.M.R
Dias A.A.M.R
3
Kolamunna K.G.T.D
Kolamunna K.G.T.D
4
Fernando N.I.R
Fernando N.I.R
5
Pannala U.K
Pannala U.K
1 Sri Lanka Institute of Information Technology

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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.

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No external funding was declared for this work.

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The authors declare no conflict of interest.

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No ethics committee approval was required for this article type.

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dias_a.a.m.r. 2020. \u201cDheergayu: Clinical Depression Monitoring Assistant\u201d. Global Journal of Computer Science and Technology - C: Software & Data Engineering GJCST-C Volume 20 (GJCST Volume 20 Issue C2): .

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GJCST Volume 20 Issue C2
Pg. 53- 61
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Crossref Journal DOI 10.17406/gjcst

Print ISSN 0975-4350

e-ISSN 0975-4172

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December 21, 2020

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English

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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.

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Dheergayu: Clinical Depression Monitoring Assistant

Dias A.A.M.R
Dias A.A.M.R
Kolamunna K.G.T.D
Kolamunna K.G.T.D
Fernando N.I.R
Fernando N.I.R
Pannala U.K
Pannala U.K

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