Fusion of neuromechanical modeling and wearable sensor data to enhance prediction of human movement intention in real-time robotic assistance

Focus topic:	Artificial Intelligence
Type of funding:	Individual funding programmes
Programme:	CZS Nexus
Funded institution:	Universität Heidelberg

Dr. Isabell Wochner conducts research in the field of predictive simulations, machine learning and biomechanics. She holds a doctorate in biomechanics and biorobotics from the University of Stuttgart. She is currently a postdoctoral researcher at the University of Heidelberg.

Goals

People can perform everyday movements such as gripping a drinking glass seemingly effortlessly. If this ability is impaired due to illness or age, assistance systems can provide support in everyday life. Such systems must be able to predict precisely which movement should be performed in order to provide optimal support in real time. This prediction represents one of the greatest challenges in rehabilitation robotics and in human-robot interaction.

Dr. Isabell Wochner's research group is investigating how everyday movements can be predicted in real time using wearable sensor data and neuromechanical computer models. To this end, wearable sensors will be used in combination with AI methods to record gaze direction and body movement. The project aims to use this improved prediction to enable robotic assistance systems that support people with motor impairments in real time and thus significantly improve their quality of life.