ImprovAIze

ImprovAIze combines a real-time interactive audiovisual system and machine learning techniques to develop algorithms that impart additional high-level information about the mover’s emotional and affective states. Tracking human motion is important for a range of activities and applications, from dance and music performance to rehabilitation and human-robot interaction. Wearable devices using physiological sensor data capture precise information about muscle activity, but provide very little information about how a person feels during the activity. 

The goal is to improve algorithms for movement and effort tracking by incorporating people’s felt experience of movement.

Research Team: Elizabeth Jochum, Cumhur Erkut, Robin Otterbein, Dan Overholt, Sofia Dahl, Shaoping Bai, and George Palamas. With Bio-X https://www.bioxgroup.dk

For more project documentation visit https://github.com/rotterbein/improvaize