Iterative model refinement and calibration through the fusion of data from ambient and near-ear sensors
Prof. Dr.-Ing. Andreas Hein (Computer Science, Engineering, Medical Device Technologies)
Prof. Dr. med. Tania Zieschang (Medicine, Geriatrics, Health Sciences)
This doctoral project aims to integrate near-ear sensor measurements (IMUs integrated into hearables) with high-resolution ambient sensors (depth imaging cameras, laser scanners, radar, etc.) in standardised environments. These environments, which can be set up in semi-public areas, provide guidance for independent assessments and allow anonymous use. The project seeks to fuse mobile data from hearables and camera data for precise body movement analysis. This sensor data fusion aims to bridge the gap between everyday and clinical measurements, creating individual models for more accurate mobile data analysis. Additionally, the project will investigate the acceptance and compliance of assistive environments and methods of human-technology interaction.