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
Students
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.
- Anne Dröge
Optimal Control Radar Tracking - Annika Mücke
- Liv Herzer
- Michaela Hofmann
Defensive freezing reaction: The effect of acute psychosocial stress on body movement and heart rate - Nag Prajjwal
Smartphone-based Musculoskeletal Model Personalization - 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
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)
- Empathokinaesthetic Measurement and Movement Pattern Recognition as Biomarkers for Health Status and Prognosis of Palliative Care Patients (D05)
- InterFEARence – Contactless assessment of feared movements in persons with chronic back pain
