Measuring brain activity and skin conductance to predict a person’s emotions

Recent research led by Assistant Professor Jorge Fresneda from the New Jersey Institute of Technology reveals that while machines cannot yet think, they are now capable of validating human emotions. Fresneda, initially trained as a chemist and now an expert in neuroanalytics, investigates how measurements of brain activity and skin conductance can accurately predict emotions. This research has implications across various fields, including entertainment, management, marketing, and well-being.

In collaboration with colleagues from NJIT’s Martin Tuchman School of Management and Virginia Tech, Fresneda published a paper titled “Neuromarketing Techniques to Enhance Consumer Preference Prediction” at the 57th Hawaii International Conference on System Sciences. Their work utilizes electroencephalogram (EEG) probes and galvanic skin response (GSR) sensors to predict individuals’ feelings about marketing stimuli more accurately than traditional self-reporting methods.

Modern EEG equipment, now compact enough to integrate into Bluetooth headsets, and GSR sensors, already incorporated into the latest Samsung smartwatches, make this technology accessible. Notably, advanced sensor networks like those potentially deployed at North Jersey’s American Dream mall could collect GSR data from smart devices, offering valuable insights linked to social media profiles.

Despite mixed opinions among retail store managers regarding privacy concerns, Fresneda emphasizes the potential value of this technology, especially in providing feedback to managers and sales staff. He believes that, given tangible benefits, consumers may be willing to adopt such technology, similar to existing practices of data tracking by companies like Amazon, Google, and Facebook.

Their research suggests broader applications beyond marketing, including measuring emotional reactions such as calmness or fear in various contexts. Future endeavors include utilizing neural analytics in customer satisfaction assessments, worker productivity tracking, and even healthcare and videogame development. Fresneda and his team are currently exploring these avenues, with a follow-up journal article under review and patents in development.