SFB 1483:  Empathokinaesthetic Sensor Technology – Sensor Techniques and Data Analysis Methods for Empathokinaesthetic Modeling and Condition monitoring

The CRC “Empathokinaesthetic Sensor Technology” (EmpkinS) will investigate 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 main focus of EmpkinS is on capturing human motion parameters at the macroscopic level (the human body or segments thereof and the cardiopulmonary function) and at the microscopic level (facial expressions and fasciculations). The acquired data are captured remotely in a minimally disturbing and non-invasive manner and with very high resolution. The physiological and behavioural states underlying the motion pattern are then reconstructed algorithmically from this data, using biomechanical, neuromotor, and psychomotor body function models. The sensors, body function models, and the inversion of mechanisms of action establish a link between the internal biomedical body layers and the outer biomedical technology layers. Research into this link is highly innovative, extraordinarily complex, and many of its facets have not been investigated so far. To address the numerous and multifaceted research challenges, the EmpkinS CRC is designed as an interdisciplinary research programme. The research programme is coherently aligned along the sensor chain from the primary sensor technology (Research Area A) over signal and data processing (Research Areas B and C) and the associated modelling of the internal body functions and processes (Research Areas C and D) to the psychological and medical interpretation of the sensor data (Research Area D). Ethics research (Research Area E) is an integral part of the research programme to ensure responsible research and ethical use of EmpkinS technology. The proposed twelve-year EmpkinS research programme will develop novel methodologies and technologies that will generate cutting-edge knowledge to link biomedical processes inside the human body with the information captured outside the body by wireless and microwave sensor technology. With this quantum leap in medical technology, EmpkinS will pave the way for completely new "digital", patient-centred diagnosis and therapeutic options in medicine and psychology. Medical technology is a research focus with flagship character in the greater Erlangen-Nürnberg area. This outstanding background along with the extensive preparatory work of the involved researchers form the basis and backbone of EmpkinS.

DFG Programme Collaborative Research Centres

• A01 - Multimodal 3D Body Imaging Camera (Project Heads Stamminger, Marc ;  Vossiek, Martin )
• A02 - Holographic 6D Wireless Locating and Motion Tracking (Project Head Vossiek, Martin )
• A03 - Highly Integrated Localizable Wireless EMG Transponder (Project Heads Hagelauer, Amelie ;  Weigel, Robert )
• A04 - Microwave Interferometer for Cardiovascular and Respiratory Monitoring (Project Head Kölpin, Alexander )
• A05 - Electro-optic Microstructure- and Micromotion-Sensor (Project Heads Carlowitz, Christian ;  Schmauss, Bernhard )
• B01 - Coding of Multimodal Body Hull Data (Project Head Kaup, André )
• B02 - Protocols and Algorithms for Energy-efficient Reference Signal and EMG Sensor Data Transmission Integrating Local Energy Harvesting (Project Head Schober, Robert )
• B03 - Compressive Sensing for Empathokinaesthetic Radar Sensors (Project Head Müller, Ralf Reiner )
• B04 - Visualization of Motion Sequences Based on a Biomechanical Model (Project Heads Klucken, Jochen ;  Stamminger, Marc ;  Winkler, Jürgen )
• C01 - Machine Learning for Personalization of Musculoskeletal Models, Movement Analysis, and Movement Predictions (Project Head Koelewijn, Anne )
• C02 - Filtering of Multimodal Motion Capture Data through Individualized Musculoskeletal Human Models (Project Heads Miehling, Jörg ;  Wartzack, Sandro )
• C03 - Investigation of Postural Control using Sensomotorically Extended Musculoskeletal Human Models (Project Heads Eskofier, Bjoern ;  Klucken, Jochen ;  Miehling, Jörg ;  Wartzack, Sandro ;  Winkler, Jürgen )
• C04 - Analysis of Degenerative Motion Impairments through Integration of Empathokinaesthetic Sensor Data in Biomechanical Human Models (Project Head Leyendecker, Sigrid )
• D01 - Hand Motion Patterns Derived from Empathokinaesthetic Sensor Data as a Diagnostic Parameter for Disease Activity in Patients with Rheumatic Diseases (Project Heads Kleyer, Arnd ;  Liphardt, Anna-Maria ;  Schett, Georg )
• D02 - Empathokinaesthetic Sensor Technology for Biofeedback in Depressed Patients (Project Heads Berking, Matthias ;  Eskofier, Bjoern )
• D03 - Contact-free Measurement of Stress, its Determinants and Consequences (Project Head Rohleder, Ph.D., Nicolas )
• D04 - Sensor-based Movement and Sleep Analysis in Parkinson’s Disease (Project Heads Eskofier, Bjoern ;  Klucken, Jochen ;  Winkler, Jürgen )
• D05 - Empathokinaesthetic Assessment and Pattern Recognition of Movement as Biomar-kers for Health Status, Wellbeing and Prognosis of Palliative Patients (Project Head Ostgathe, Christoph )
• E - Ethics in and by Design: Ethical and Social Challenges of Empathokinaesthetic Sensor Technologies (Project Heads Braun, Matthias ;  Dabrock, Peter )
• MGK - Integrated Research Training Group (Project Head Eskofier, Bjoern )
• Z - Central Tasks of the Collaborative Research Centre (Project Head Vossiek, Martin )

Applicant Institution Friedrich-Alexander-Universität Erlangen-Nürnberg

Spokesperson Professor Dr.-Ing. Martin Vossiek