期刊名称：International Journal of Advanced Computer Science and Applications(IJACSA)
印刷版ISSN：2158-107X
电子版ISSN：2156-5570
出版年度：2019
卷号：10
期号：4
页码：490-499
DOI：10.14569/IJACSA.2019.0100461
出版社：Science and Information Society (SAI)
摘要：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.
