[vc_row][vc_column][vc_custom_heading text=”Relapse prevention for bipolar disorder” font_container=”tag:h2|text_align:left|color:%23df5216″ use_theme_fonts=”yes”][/vc_column][/vc_row][vc_row][vc_column width=”2/3″][vc_column_text]Bipolar disorder is a severe mental disorder with intense mood fluctuations, lifelong disability and increased mortality that affects about 1-3% of the population with a lifetime suicide prevalence of 20%. Patients typically need long term follow up in order to reduce the frequency of new mood episodes and achieve good mood stability. The cornerstone of treatment is with mood stabilizing medications and psychoeducational programs. The challenge is to avoid new episodes of depression and mania, as the increased risk of suicide is related to such episodes, and there is a large need to develop new tools to improve early detection and intervention in this disorder. Typically, patients with bipolar disorder experience changes in sleep and motor activity in the beginning of new episodes, often without recognizing the change subjectively. However, if patients can successfully identify these changes as they happen, effective interventions can often be established in order to inhibit new full-blow episodes.

The objective of the current study is to develop an app that can help monitor mood fluctuations in bipolar patients to improve the clinical management of the disorder. The aim is that such an app can monitor changes in sleep, motor activity, heart rate variability and subjectively reported mood and integrate this information to set off an alarm that will alert patients, relatives and doctors when a certain threshold is surpassed. The study will use a smartwatch (Empatica E4) to monitor motor activity, heart rate variability and skin conductance and an app PRIORI that is downloaded to the patients cell phones, and as they use their cell phone, information regarding the tone of their voice is sent to a central server and analyzed as to whether the patients are currently in a depressed, hypomanic or manic episode. This information will be evaluated during the clinical follow-up of patients to determine the predictive properties of the sensor data.

The ultimate goal will be to develop a tool for the clinical management of patients with bipolar disorder that can not only be used by patients to alert themselves, but that can also be integrated into the existing systems for medical records in order to alert the clinical therapists that something is going on with their patients, enabling an earlier intervention, and subsequently avoiding new severe and potentially lethal episodes.[/vc_column_text][/vc_column][vc_column width=”1/3″][vc_column_text]Domain expert

Ketil Oedegaard

Team role
Domain expert for relapse prevention for bipolar disorder
Short bio here
Contact info here


Petter Jakobsen

Team role
PhD fellow

Petter Jakobsen is PhD. candidate on the relapse prevention for bipolar disorder case.

He has been working as an adviser in the research department of the psychiatric division of Haukeland University hospital since 2009, and mainly divided his time between coordinating several Norwegian sites in an international genetic multicenter study, as well as contributing to the development and modernization of electronic solutions in the hospital.

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