Analyzing people’s keystrokes as they type on a computer can reveal a great deal of information about the state of their motor function, according to a new study from MIT.

Researchers from the Madrid-MIT M+Vision Consortium analyzed keystrokes with an algorithm that captures timing information such as “key hold time”—a measure of how long a key is pressed before being released. By studying these patterns, they were able to distinguish between typing done in the middle of the night, when sleep deprivation impairs motor skills, and typing performed when fully rested.

While that study focused on the effects of fatigue, it also represents a first step toward using keystroke patterns to diagnose conditions that impair motor function, such as Parkinson’s disease, the researchers say.

Preliminary results from a study of about two dozen Parkinson’s patients suggest that the patterns the algorithm detects can distinguish people who have the disease from those who don’t. If the findings are validated in larger studies, the researchers believe, this approach could lead to much earlier diagnosis for Parkinson’s and aid in the development of better treatments.

“People are usually diagnosed five to 10 years after the beginning of the disease, and lot of the damage has already been done,” says Luca Giancardo, the paper’s first author and an M+Vision Fellow.

A white paper on this research won the 2015 Singapore Challenge, an international science competition focused this year on the topic of aging in place. The team is now running a crowdsourced study to characterize the normal typing signal in the general population. Participate at https://www.neuroqwerty.com.