Adapting Smartwatches to Improve Distance Learning and Health

saohuRose Faghih Wins NSF CAREER Award for MINDWATCH Proposal

, which supports faculty early in their career who the NSF believes will eventually serve as academic role models in research and education and lead advances in their fields. The five-year award, worth $525,000, was given to Faghih for her project called MINDWATCH, an acronym for Multimodal Intelligent Noninvasive brain state Decoder for Wearable AdapTive Closed-loop arcHitectures.  

Faghih’s signal processing and control algorithms, or infrastructure, for a wearable device delivers information on three types of brain states – stress, cognitive engagement (or boredom) and cognitive learning, based on multiple signals from the wearer including sweat response, respiration, cardiac function and temperature. 

Faghih calls it a navigation system for the brain. “It overcomes the barriers to achieving brain-aware wearables by pioneering a transformative system-theoretic computational toolset for noninvasive closed-loop wearable architectures that monitor and modulate brain function without needing neural recordings,” said Faghih. In other words, judging brain states has never been so easy; not needed is electroencephalogram (EEG) testing and monitoring, in which electrodes are attached to the scalp or a cap to measure brain activity.  

The potential applications for the closed loop technology are endless. 

“Another application can be for the elderly. If they are home alone, and they are not engaged, or they are depressed, the algorithm can detect it in a smart home setting and then change the frequency or color of light in their home, or start playing music in the background so they become engaged again,” said Faghih, who will be testing the smart light and music system in her lab.