Assistive technologies for bipolar disorder

A survey

Yumna Anwar, Arshia A Khan

Research output: Contribution to journalArticle

Abstract

Bipolar disorder is a severe mental illness characterized by periodic manic and depressive episodes. The current mode of assessment of the patient's bipolar state is using subjective clinical diagnosis influenced by the patients self-reporting. There are many intervention technologies available to help manage the illness and many researches have worked up on objective diagnosis and state prediction. Most of the recent work is focused on sensor-based objective prediction to minimize the delay between a relapse and the patient's visit to the clinic for diagnosis and treatment. Due to the severity of the societal and economic burden caused by bipolar disorder, these researches have been given great emphasis. In this paper, we will start with a discussion of global severity of the disorder and economic and family burden inflicted due to it; we then talk about the existing mechanisms in place to identify the current state of the bipolar patient, then we go on to discussing the behavioral intervention technologies available and researched upon to help patients manage the disorder. Next, we mention the shift in focus of the current research, i.e. towards sensor based predictive systems for patients and clinical professionals, highlighting some of the preliminary researches and clinical studies and their outcomes.

Original languageEnglish (US)
Pages (from-to)490-499
Number of pages10
JournalInternational Journal of Advanced Computer Science and Applications
Volume10
Issue number4
StatePublished - Jan 1 2019

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Economics
Sensors

Keywords

  • Behavioral intervention technologies
  • Bipolar disorder
  • Depression
  • Electrodermal activity
  • Heart rate variability
  • Mania
  • Mobile applications

Cite this

Assistive technologies for bipolar disorder : A survey. / Anwar, Yumna; Khan, Arshia A.

In: International Journal of Advanced Computer Science and Applications, Vol. 10, No. 4, 01.01.2019, p. 490-499.

Research output: Contribution to journalArticle

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