Grant: Alliance Grants

Long term goal of this collaborative effort is to develop a pervasive wearable device and software that can objectively and continuously monitor, detect and discriminate people's emotions. Detection and discrimination of emotions will help people better control their emotions and will help therapists make more informed clinical decisions.To support the long-term goal, this one-year project aims to develop two new machine learning models: 1. classification model for discriminating emotions based on several minutes of data collected in a controlled environment where the emotions are induced, and 2. machine learning model for continuous monitoring, detection and discrimination of emotions that will work with streaming data acquired during regular daily activities. Discriminating emotions in a controlled environment, such as a psychology lab, is necessary to develop reliable machine learning classification models that do not depend on subjects' subjective reporting of emotions. Continuous monitoring during daily activities will be based on the previously developed classification model and adjusted to handle noise, delayed emotions and real-time processing requirements. The team includes researchers with expertise in biomedical engineering, psychology and AI and is perfectly suited for this project. The supporting company develops software and machine learning models for emotion discrimination and has a significant interest in contributing to the project's success. The benefits to Canada include strengthening the emotion discrimination market and research, providing an emotional feedback loop for many Canadians suffering from mentioned health conditions, and providing therapists with objective data to make more informed clinical decisions.