Sensor-based Movement and Sleep Analysis in Parkinson’s Disease (D04)

• Subject Area: Medical Physics, Biomedical Technology
• Term: since 2021
• Project identifier: Deutsche Forschungsgemeinschaft (DFG) - Project number 442419336

Innovative and non-intrusive empathokinaesthetic sensor technology combined with machine learning-based algorithms will be evaluated in comparison to multimodal reference-diagnostic procedures and clinical assessments for sleep impairments in Parkinson’s disease. Single parameters for sleep derived from different sensor-sources (wearable sensors, non-obtrusive, contact-free sensors) will be technically validated and correlated to clinical sleep scores and disease characteristics. In a multimodal algorithmic approach, multiparameter-based sleep patterns will be clinically validated in comparison to movement, cardiovascular regulation and sleep phase disturbances.

• DFG Programme: Collaborative Research Centres
• Subproject of: SFB 1483: Empathokinaesthetic Sensor Technology – Sensor Techniques and Data Analysis Methods for Empathokinaesthetic Modeling and Condition monitoring
• Applicant Institution: Friedrich-Alexander-Universität Erlangen-Nürnberg
• Project Heads: Professor Dr. Bjoern Eskofier; Professor Dr. Jochen Klucken, until 2/2021; Professor Dr. Jürgen Winkler, since 8/2021