Skip to Content
Artificial intelligence

Mood disorders could be diagnosed by the way you fiddle with your phone

April 5, 2018

A neural network can detect depression and mania in bipolar subjects by analyzing how they hold and tap on their smartphones.

The news: Researchers gave both bipolar and control subjects a phone with a custom keyboard that collected data on key presses and accelerometer movement. They also asked participants to self-report how much they were feeling depressed or manic.

Details: Bipolar participants, when suffering mania or depression, had a more uniform typing time compared with control subjects, who varied their typing speeds. One explanation could be that bipolar people don’t react as much to stimuli, like incoming text messages. The accelerometer data showed that subjects with depressive or manic symptoms tended to hold their phone at an angle.

Results: Using those insights, the researcher trained an algorithm called DeepMood to predict when a bipolar subject was suffering from a mood disturbance. DeepMood reached 90 percent accuracy with sessions that were usually under one minute.

Deep Dive

Artificial intelligence

What does GPT-3 “know” about me? 

Large language models are trained on troves of personal data hoovered from the internet. So I wanted to know: What does it have on me?

An AI that can design new proteins could help unlock new cures and materials 

The machine-learning tool could help researchers discover entirely new proteins not yet known to science.

Stay connected

Illustration by Rose Wong

Get the latest updates from
MIT Technology Review

Discover special offers, top stories, upcoming events, and more.

Thank you for submitting your email!

Explore more newsletters

It looks like something went wrong.

We’re having trouble saving your preferences. Try refreshing this page and updating them one more time. If you continue to get this message, reach out to us at with a list of newsletters you’d like to receive.