Case Study: Northeastern University predicts aggressive behavior in children with profound autism with Empatica

Northeastern University predicts aggressive behavior 3 minutes ahead with Empatica

Northeastern University, led by Professor Matthew Goodwin, faced the challenge of predicting aggressive behaviors in children with profound autism to improve safety and quality of life. Existing research methods in lab settings were unsuitable for this population. Empatica provided its wearable technology to collect physiological data in natural, inpatient environments.

The solution involved using Empatica's wearable devices to continuously record biosensor data like cardiovascular and electrodermal activity. This data was used to build a machine learning model that could predict the onset of aggressive behavior. The results were highly successful, with Empatica's technology enabling predictions that were 80-90% correct and could occur up to three minutes in advance. The high wear compliance of 81% also allowed for the collection of 497 hours of vital data.

Northeastern University