First dates mostly end up being in a pickle. To know if the other person feels the same or not is an arduous task when it comes to dating. This new app developed by a group of engineers at the University of Cincinnati is indeed a lifesaver for those struggling on their first date.

Engineers at the University of Cincinnati have trained a computer with the data from wearable technology that measures heartbeat, breathing patterns and perspiration to identify the type of conversation or emotions two people are having while on a date. The researchers backed it up with a phenomenon called “physiological synchrony”, in which people’s autonomic nervous system responses, like a heartbeat, respiration etc., are measured to check if they are synchronised when they talk. This is highly effective, and the result is evident when they are engaged in intimate conversations or tasks.

Vesna Novak, an associate professor of electrical engineering at UC’s College of Engineering and Applied Science, says, “physiological synchrony can be measured even two people are talking through Zoom”. 

The experiment of training an AI to recognize the emotions of two people through their conversation has been reported as almost successful, as the computer was able to differentiate four different conversation scenarios with 75% accuracy. Iman Chatterjee, the lead author and UC doctoral student, along with the co-author Vesna Novak and others, published a journal on the app. 

Chatterjee says, “the computer could tell if you’re a bore” and adds, “a modified version of our system could measure the level of interest a person is taking in the conversation, how compatible the two of you are and how engaged the other person is in the conversation”. He mentions physiological synchrony as a ‘revolutionary adaptation’.

Studies have proven that this physiological synchrony can predict the compatibility between two people. The degree of synchrony is similar to the amount of empathy a patient perceives in a therapist or the level of student-teacher engagement. This shows how deeply the app evaluates the bond between two persons.