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Digitizing Anger

UTA Researchers Zero in on Brain Signals

Pinpointing the brain signals associated with anger could lead to a tool that helps domestic violence offenders keep their anger in check.

An interdisciplinary team of UTA researchers is exploring the electrocortical and cardiovascular activities that occur when people feel emotions like anger and happiness. The cross-collaborative effort includes researchers from UTA’s Colleges of Engineering, Science, Education, and School of Social Work. They hope to discover a way to predict anger in the brain before a person acts upon it.

“We designed an experiment to trigger an emotional reaction, and then we use EEG (electro-encephalogram) recordings to record brainwave activity and we record their vital signs to see if their pulse or blood pressure increases,” explains Electrical Engineering Professor J-C Chiao. “We analyze all of this information to see when brainwaves indicate anger or any other emotion that happened. We can then put it in a formula or an equation and design a circuit or app to analyze data and provide the user feedback.”

The team would like to develop a wearable tool, like a ball cap or a pair of glasses that could detect brain signals. Domestic violence offenders could wear this device and receive a warning when anger is building. They would then be responsible for either removing themselves from the situation or employing coping tools they've learned in therapy.

“One of the biggest issues that offenders deal with is anger management,” said Assistant Professor of Social Work Anne Nordberg. “It’s a barrier after people are released from prison. If you let it get the better of you, it can impact your ability to stay on the outside. So if you can give people tools to help control and manage the anger, I know a lot of offenders who would jump at that chance.”

“If this research moves forward the way we hope it will, the potential applicability for their lives is enormous,” she said. “It could be a key piece in criminal justice reform affecting recidivism rates.”

Joining Chiao and Nordberg in this research are Social Work Professor Peter Lehmann, Curriculum and Instruction Associate Professor Jodi Tommerdahl, Psychology Professor Yuan Peng, and Industral, Manufacturing, and Systems Engineering Assistant Professor Shouyi Wang.

Friday, April 1, 2016