Forum for Science, Industry and Business

Sponsored by:     3M 
Search our Site:

 

Listening to bipolar disorder: Smartphone app detects mood swings via voice analysis

08.05.2014

Subtle changes could act as early warning of need for care, U-M research suggests

A smartphone app that monitors subtle qualities of a person's voice during everyday phone conversations shows promise for detecting early signs of mood changes in people with bipolar disorder, a University of Michigan team reports.

While the app still needs much testing before widespread use, early results from a small group of patients show its potential to monitor moods while protecting privacy.

The researchers hope the app will eventually give people with bipolar disorder and their health care teams an early warning of the changing moods that give the condition its name. The technology could also help people with other conditions.

More patients, all taking part in the study funded by the National Institute of Mental Health and facilitated by the Prechter Bipolar Research Fund at the U-M Depression Center, have already started to use the app on study-provided smartphones. As more patients volunteer, the team will continue to test and improve the technology.

The U-M team, led by computer scientists Zahi Karam, Ph.D. and Emily Mower Provost, Ph.D., and psychiatrist Melvin McInnis, M.D., presented its first findings today at the International Conference on Acoustics, Speech and Signal Processing in Italy, and published details simultaneously in the conference proceedings.

They call the project PRIORI, because they hope it will yield a biological marker to prioritize bipolar disorder care to those who need it most urgently to stabilize their moods – especially in regions of the world with scarce mental health services. Bipolar disorder affects tens of millions of people worldwide, and can have devastating effects including suicide.

But first, based on these encouraging findings, the technology and algorithms will be developed via research involving 60 American patients who receive treatment from U-M teams at the nation's first center devoted to depression and related disorders.

"These pilot study results give us preliminary proof of the concept that we can detect mood states in regular phone calls by analyzing broad features and properties of speech, without violating the privacy of those conversations," says Karam, a postdoctoral fellow and specialist in machine learning and speech analysis. "As we collect more data the model will become better, and our ultimate goal is to be able to anticipate swings, so that it may be possible to intervene early."

Adds McInnis, a bipolar specialist, "This is tremendously exciting not only as a technical achievement, but also as an illustration of what the marriage of mental health research, engineering and innovative research funding can make possible."

He adds, "The ability to predict mood changes with sufficient advance time to intervene would be an enormously valuable biomarker for bipolar disorder."

He notes that the initial seed funding for the voice technology research came from the Michigan Institute for Clinical and Health Research. The ready source of patient-volunteers came from a Prechter Fund-supported registry, and the new early results were made possible by NIMH funding.

The research team hails from the Department of Psychiatry at the U-M Medical School and the Division of Computer Science and Engineering in the Department of Electrical and Computer Engineering at the U-M College of Engineering. It includes Satinder Singh, Ph.D. an artificial intelligence and machine learning expert.

How it works

The app runs in the background on an ordinary smartphone, and automatically monitors the patients' voice patterns during any calls made as well as during weekly conversations with a member of the patient's care team. The computer program analyzes many characteristics of the sounds – and silences – of each conversation.

Only the patient's side of everyday phone calls is recorded – and the recordings themselves are encrypted and kept off-limits to the research team. They can see only the results of computer analysis of the recordings, which are stored in secure servers that comply with patient privacy laws.

Standardized weekly mood assessments with a trained clinician provide a benchmark for the patient's mood, and are used to correlate the acoustic features of speech with their mood state.

Because other mental health conditions also cause changes in a person's voice, the same technology framework developed for bipolar disorder could prove useful in everything from schizophrenia and post-traumatic stress disorder to Parkinson's disease, the researchers say.

Results so far

The first six patients all have a rapid-cycling form of Type 1 bipolar disorder and a history of being prone to frequent depressive and manic episodes. The researchers showed that their analysis of voice characteristics from everyday conversations could detect elevated and depressed moods.

The detection of mood states will improve over time as the software gets trained based on more conversations and data from more patients.

The researchers study patients as they experience all aspects of bipolar disorder mood changes, from mild depressions and hypomania (mild mania) to full-blown depressed and manic states. Over time, they hope to develop software that will learn to detect the changes that precede the transitions to each of these states. They also need to develop and explore strategies for notifying the app user and care providers about mood changes, so that appropriate intervention can take place.

The app currently runs on Android operating system phones, and complies with laws about recording conversations because only one side of the conversation actually gets recorded. The University of Michigan has applied for patent protection for the intellectual property involved.

###

Prechter project manager Gloria Harrington, MSW, social worked Jennifer Montgomery, MSW, and research technician Christopher Archer, B.S. also worked on the project.

To be eligible for the smartphone app study, patients must first enroll in the Prechter Fund-sponsored long-term study of bipolar disorder, which accepts adults with and without bipolar disorder. More information and contact information to sign up: http://umhealth.me/prechterbp (study number HUM00000606). For more about the Prechter Fund, visit http://prechterfund.org/

Funding: National Institute of Mental Health, MH100404

Kara Gavin | Eurek Alert!
Further information:
http://www.umich.edu

Further reports about: Engineering Listening Smartphone bipolar characteristics conversation disorder

More articles from Health and Medicine:

nachricht How prenatal maternal infections may affect genetic factors in Autism spectrum disorder
22.03.2017 | University of California - San Diego

nachricht Camouflage apples
22.03.2017 | Empa - Eidgenössische Materialprüfungs- und Forschungsanstalt

All articles from Health and Medicine >>>

The most recent press releases about innovation >>>

Die letzten 5 Focus-News des innovations-reports im Überblick:

Im Focus: Giant Magnetic Fields in the Universe

Astronomers from Bonn and Tautenburg in Thuringia (Germany) used the 100-m radio telescope at Effelsberg to observe several galaxy clusters. At the edges of these large accumulations of dark matter, stellar systems (galaxies), hot gas, and charged particles, they found magnetic fields that are exceptionally ordered over distances of many million light years. This makes them the most extended magnetic fields in the universe known so far.

The results will be published on March 22 in the journal „Astronomy & Astrophysics“.

Galaxy clusters are the largest gravitationally bound structures in the universe. With a typical extent of about 10 million light years, i.e. 100 times the...

Im Focus: Tracing down linear ubiquitination

Researchers at the Goethe University Frankfurt, together with partners from the University of Tübingen in Germany and Queen Mary University as well as Francis Crick Institute from London (UK) have developed a novel technology to decipher the secret ubiquitin code.

Ubiquitin is a small protein that can be linked to other cellular proteins, thereby controlling and modulating their functions. The attachment occurs in many...

Im Focus: Perovskite edges can be tuned for optoelectronic performance

Layered 2D material improves efficiency for solar cells and LEDs

In the eternal search for next generation high-efficiency solar cells and LEDs, scientists at Los Alamos National Laboratory and their partners are creating...

Im Focus: Polymer-coated silicon nanosheets as alternative to graphene: A perfect team for nanoelectronics

Silicon nanosheets are thin, two-dimensional layers with exceptional optoelectronic properties very similar to those of graphene. Albeit, the nanosheets are less stable. Now researchers at the Technical University of Munich (TUM) have, for the first time ever, produced a composite material combining silicon nanosheets and a polymer that is both UV-resistant and easy to process. This brings the scientists a significant step closer to industrial applications like flexible displays and photosensors.

Silicon nanosheets are thin, two-dimensional layers with exceptional optoelectronic properties very similar to those of graphene. Albeit, the nanosheets are...

Im Focus: Researchers Imitate Molecular Crowding in Cells

Enzymes behave differently in a test tube compared with the molecular scrum of a living cell. Chemists from the University of Basel have now been able to simulate these confined natural conditions in artificial vesicles for the first time. As reported in the academic journal Small, the results are offering better insight into the development of nanoreactors and artificial organelles.

Enzymes behave differently in a test tube compared with the molecular scrum of a living cell. Chemists from the University of Basel have now been able to...

All Focus news of the innovation-report >>>

Anzeige

Anzeige

Event News

International Land Use Symposium ILUS 2017: Call for Abstracts and Registration open

20.03.2017 | Event News

CONNECT 2017: International congress on connective tissue

14.03.2017 | Event News

ICTM Conference: Turbine Construction between Big Data and Additive Manufacturing

07.03.2017 | Event News

 
Latest News

Pulverizing electronic waste is green, clean -- and cold

22.03.2017 | Materials Sciences

Astronomers hazard a ride in a 'drifting carousel' to understand pulsating stars

22.03.2017 | Physics and Astronomy

New gel-like coating beefs up the performance of lithium-sulfur batteries

22.03.2017 | Materials Sciences

VideoLinks
B2B-VideoLinks
More VideoLinks >>>