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

Dr.-Ing. Eva Dorschky

Room: Room 01.024

Group Members



If you are interested in writing a Bachelor’s or Master’s thesis in our group, please check the lab’s Student Theses and Jobs.

  • Julia Jorkowitz
    Systematic Benchmarking of Pre-Ejection Period Extraction Algorithms
  • Robert Schröter
    Improving the CARWatch Framework for Objective Cortisol Awakening Response Assessment
  • Simon Meske
    Improving the Robustness of Heart Rate Estimation from Continuous-Wave Radar Data using a Wavelet-based Approach and Deep Learning
  • Victoria Müller
    Machine Learning-Based Detection of Acute Psychosocial Stress from Digital Biomarkers

Past Students

  • Nag Prajjwal
    Smartphone-based Musculoskeletal Model Personalization



Completed Projects