MIT has built a wireless emotion detector system using routers to identify the emotions of person even if that person is not speaking or showing their emotion with a facial expression.
The Massachusetts Institute of Technology's Computer Science and Artificial Intelligence Lab created what is called the EQ-Radio, which uses radio signals from a wireless router, an algorithm, and machine-learning classifier to make the determination if its subject is happy, sad, or other emotions in between, Forbes reported.
The low-frequency radio waves capture the subject's reflections from nearby objects, the algorithm separates heartbeat and respiration information, and the classifier pulls the information together to interpret an emotional state, noted Forbes.
"Our work shows that wireless signals can capture information about human behavior that is not always visible to the naked eye," Dina Katabi, the project lead and MIT professor said in a statement. "We believe that our results could pave the way for future technologies that could help monitor and diagnose conditions like depression and anxiety."
The MIT statement said the EQ-Radio, which does with work without the use of on-body sensors, is 87 percent accurate at detecting if a person is excited, happy, angry, or sad.
Katabi said the EQ-Radio could be used in entertainment, consumer behavior, and health care. She added that film studios and ad agencies could test viewers' reactions in real-time, while smart homes could use information about a person's mood to adjust the heating or suggest getting fresh air.
"By recovering measurements of the heart valves actually opening and closing at a millisecond time-scale, this system can literally detect if someone’s heart skips a beat," Fadel Adib, a coauthor of the project, said in the MIT statement.
"This opens up the possibility of learning more about conditions like arrhythmia, and potentially exploring other medical applications that we haven’t even thought of yet," Adib added.
The researchers said the EQ-Radio is better at reading emotions than simply using facial expressions and other machines that rely on wearing monitors.
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