Forcasting of bipolar episodes

2. okt.

A novel method to warn patients that episode will occur in 1-3 weeks.

Background

Bipolar disorder (BD) is a severe mental illness, affecting 2% of the world population. It is marked by recurrent and alternating episodes of mania and depression with symptoms free periods in between. The disease has significant impacts on life expectancy and overall health. Early detection of mood episodes is vital to mitigate severe consequences. For instance, BD patients have a suicide rate up to 30 times higher than the global average. The inventors, comprising experts from Haukeland University Hospital, the University of Bergen, the University of Oslo, and SimulaMet, has pioneered research in BD management. They focus on using biological activity data to predict mood changes, based on the work within the "Detecting and Predicting Mood Transitions in Bipolar Disorder" study, part of the "INTROMAT" project funded by the Norwegian Research Council. The recent study identified early warning signals that predicted mood relapses with an average lead time of 13.5 days, using biometrical data analyzed by an advanced algorithm.

Advantages

According to both clinicians and patients, an objective monitoring and episode prediction tool would be revolutionary in the field of BD management. When speaking to bipolar patients the need for an objective system has been strongly stated. Self-report tools are cumbersome, error-prone and time consuming. The patients need to be an expert on their own condition and body. They can also find that their mood and behavior is scrutinized by their closest relatives, friends or colleagues, and here the objectiveness is seen as a vital benefit. With an objective and automatic monitoring system one avoids these issues. The system will give a warning in sufficient time to do mitigating measures such as seeking professional help. We believe this is crucial to avoid suicides, life wrecking actions and other issues than can occur when having episodes.

Technology description

The method works by collecting data from the patient through a smart device, e.g. watch or ring, analyzing that data, and provide warning signal to the patient and/or healthcare staff and/or close relatives. The signal is based on reading biometric data and detect early warning signals found by an advanced algorithm in advance of the episode. The method is patent pending.

If successful, the novel approach would be the first objective forecasting system available for patients.

Business opportunity

We are interested in talking to industry partners to help develop the technology and take it to market.

Protection
The technology is patent pending. It is further secured through secrecy of source code.

Inventors

Petter Jakobsen, Helse Bergen,

Ketil Joachim Ødegaard, Helse Bergen

Ulysse Teller Masao Côté-Allard, University of Oslo

Michael Riegler, SimulaMet

Contact

If you wish to discuss the project or have any questions, please contact:

Steffen Boga