Empatho-Kinaesthetic Sensor Technology (EmpkinS)
The CRC 1483 “Empatho-Kinaesthetic Sensor Technology” (EmpkinS) investigates novel radar, wireless, depth camera, and photonics-based sensor technologies as well as body function models and algorithms. The primary objective of EmpkinS is to capture human motion parameters remotely with wave-based sensors to enable the identification and analysis of physiological and behavioural states and body functions. To this end, EmpkinS aims to develop sensor technologies and facilitate the collection of motion data for the human body. Based on this data of hitherto unknown quantity and quality, EmpkinS will lead to unprecedented new insights regarding biomechanical, medical, and psychophysiological body function models and mechanisms of action as well as their interdependencies.
The MaD Lab contributes to EmpkinS within several part projects listed below.
Research areas: Machine Learning, Wearables, Experimental Studies, Signal Processing, Musculoskeletal Modeling, Optimal Control
More about the entire EmpkinS
Group Heads
Group Members
Current Students
- Marie Oesten
Radar-Based Investigation of Pulse Wave and Heart Sound Propagation - Vivien Holzwarth Correa
Classification and assessment of rheumatoid arthritis from motion capture data using machine learning
Projects
- Machine Learning for Personalisation of Biomechanical Movement Simulations (C01)
- Machine Learning for Neuromusculoskeletal Modelling (C03)
- Empathokinesthetic sensors for biofeedback in depressed patients (D02)
- Contactless measurement of stress, its determinants, and consequences (D03)
- Sensor-based movement and sleep analysis in Parkinson’s syndrome (D04)
