Artificial Intelligence: AI To Use Mobile Devices To Monitor Mental Health

January 7, 2021 | Artificial Intelligence, News
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Mental health issues may manifest not as ‘symptoms,’ but as ‘behaviors.’ Smart devices and A.I. can pick up these signals.

A person’s devices such as smartphones and smartwatches and other sensors (such as IoT devices) may sense signs of depression and other changes in the mental health of their user. In fact, these devices can accurately and continuously monitor these behavioral shifts, that otherwise may not be symptomatic. Their mobile health data, combined with AI, can help mental health doctors to better manage and monitor their patients. (Cornell CIS Information Science)

A new behavioral health initiative

According to Cornell University’s Tanzeem Choudhury, a leader in mobile health, the above technology could identify persons suffering from bipolar disorder or schizophrenia and flag treatment early on.

Choudhury is the Roger and Joelle Burnell Professor in Integrated Health and Technology at the Jacobs Technion-Cornell Institute at Cornell Tech in Information Sciences.

She recently launched the Precision Behavioral Health Initiative. Health industry professionals are collaborating with Cornell faculty and students to combine health data from mobiles with AI. The objective: To plug the prevailing gaps in accurate measurement, customized intervention, and clinical impact.

Mobile health did not deliver on its early promise

There’s a surfeit of smartphones, apps, and other smart devices available to monitor behavioral health. Yet, mobile monitoring has not taken off.

“There’s a lot of cool technology out there and really innovative sensors and home devices that can understand users and user behavior,” Choudhury says. “The challenge for the Initiative is, how to take this volume of user data and interpret it into meaningful health metrics to be used by doctors and clinicians to understand patients’ mental health and provide the best treatments?”

The way forward

Choudhury works with Dan Adler, a doctoral student who helps in the design and implementation of the machine-learning algorithms that will crunch the mobile data. They both agree that the goal is to transform raw data into meaningful indicators for better patient outcomes.

Accordingly, the team working on the initiative comprises physicians, therapists, medical researchers, and healthcare professionals as well as Cornell faculty and student technology leaders.

“This coordination between people who really understand both the medicine and the emerging technology, and that can put it to work in a clinical setting, is extremely valuable,” says Greg Morrisett. He is the Jack and Rilla Neafsey Dean and Vice Provost of Cornell Tech.

The Precision Behavioral Health Initiative is forging a network of collaborative partners. The group’s research falls outside the realm of traditional funding. It requires visionary contributors to partner for the greater good and to bring research to practice. To get involved, contact Professor Tanzeem Choudhury at tanzeem.choudhury@cornell.edu.

Related Story:     AI Detects Loneliness With 94% Accuracy

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