Computer scientist works with artificial intelligence to keep people in state of flow
Ever been ‘in the zone?’ UTA explores how to keep you there
Credit: UT Arlington
The experience of being “in the zone” is often used to describe a cognitive state of mind known as flow. A person enters a state of flow when highly engaged with a task, often losing track of time and enjoying a high level of success.
Cesar Torres, assistant professor in the Computer Science and Engineering Department at The University of Texas at Arlington, has recently received a grant of approximately $175,000 from the National Science Foundation to use machine learning and artificial intelligence (AI) techniques to identify when a person is falling out of flow and introduce an intervention to regain flow.
Torres’s research intermingles computer science and maker culture, drawing inspiration from activities that naturally produce states of flow, such as sewing, embroidering and knitting. In his study, he will use off-the-shelf sensors to capture how study participants enter and exit states of flow as they develop these crafting skills.
“When people are in flow they generally experience two benefits: improved performance and lessened perception of failure,” Torres said. “This work is about building resiliency in makers and shifting perceptions of failure by leveraging the body’s innate ability to get happily lost in making.”
Researchers typically determine if someone is in a state of flow by giving them a survey, but even brief ones are intrusive. By using body sensors, Torres will be able to detect physiological cues, such as sweat or increased heart rates, that indicate when subjects are falling out of flow. Then, AI can react and introduce a stimulus that can nudge the subject’s thought process back into a flow state.
“It is interesting envisioning how to make these stimuli interactive,” he said. “Our bodies have a natural ability to sync with external stimuli, like falling into step with music while jogging. So it could be as subtle as introducing a metronome to an embroidery loom to bring people back into this higher and more enjoyable cognitive state.”
Torres’ research could have implications beyond this project, says Hong Jiang, chair of UTA’s Computer Science and Engineering Department.
“Moving data science and machine learning research forward heavily depends on the availability of novel datasets,” Jiang said. “Dr. Torres will contribute the first open-source dataset of flow activity, which will have large implications for designing computational systems that adapt to cognitive states like flow.
“At UTA, we are working to strengthen our own making communities within the Computer Science and Engineering/Electrical Engineering Makerspace and the UTA FabLab. As a member of both the Computer Science and Engineering and Art and Art History Departments, Dr. Torres’ focus on improving making experiences is strategically positioned for encouraging and developing a new generation of makers that cross disciplinary boundaries.”
To learn more about Torres’s research in creativity, digital fabrication and human activity recognition, visit The Hybrid Atelier @ UTA.
– Written by Jeremy Agor, College of Engineering