Critical Systems Engineering Living Lab - Medical Process Modeling (CSE LL-MPM)

Researchers in the Living Lab - Medical Process Modeling develop research infrastructures for medical-specific questions. The Living Lab allows the acquisition and modeling of standardized time-critical processes, e.g. prehospital resuscitation (the Mega Code Training). The aim is the analysis of the quality of individual performance and the prediction of human behavior in a defined socio-technical system to optimize processes through human-machine interaction. The Living Lab CMP makes a significant contribution to the quantification, optimization, and standardization of medical processes.

Approach

In a first step, the necessary infrastructure is developed to model medical workflow (such as prehospital resuscitation) in typical safety-critical situations with a focus on functional properties such as timing, workloads, and attention.

For this purpose, relevant motion sequences of the participants must be monitored very precisely via both environmental sensors and inertial sensors (motion capture). The combination of these two different motion capture approaches avoids the weaknesses of the individual systems: Optical motion capture methods are, e.g. very sensitive to sunlight and inertial sensors become imprecise at the end of the kinematic tree (e.g. towards the hands). Furthermore, the cognitive workload and the viewing angles of the participants are measured and modeled.

Also, all activities that can be related to patients are recorded using an A(C)LS simulator and ECG and merged into an evaluation platform. Further, it will be investigated which sensor system is suitable for future decision support systems that can be utilized for field use. Based on the context information, processes are modeled about timing, workloads, and attention. In a second step, simulations will be designed to optimize the Mega Codes Training.

Grants and cooperations

The interdisciplinary research center for the design of safety-critical socio-technical systems investigated the role of humans in the control of complex transport systems on land and water.

Cooperation partners are OFFIS e.V. in Oldenburg, DLR Institute for Traffic Systems Engineering in Braunschweig and the network SafeTRANS.

The project was funded in the second phase by the state of Lower Saxony with EUR 2 million. The project runtime was extended by additional 18 months (2017-2018).

 

Publications

2019
[10] C. Lins, D. Eckhoff, A. Klausen, S. Hellmers, A. Hein, S. Fudickar. Cardiopulmonary resuscitation quality parameters from motion capture data using Differential Evolution fitting of sinusoids. Applied Soft Computing. 2019. [bibtex] [url] [doi]
2018
[9] C. Lins, S. Fudickar, A. Hein. XML Skeleton Definitions for Human Posture Assessments. Studies in Health Technology and Informatics. 2018. [bibtex] [url]
[8] C. Lins, A. Klausen, S. Fudickar, S. Hellmers, M. Lipprandt, R. Röhrig, A. Hein. Determining Cardiopulmonary Resuscitation Parameters with Differential Evolution Optimization of Sinusoidal Curves. In: Proceedings of the 11th International Joint Conference on Biomedical Engineering Systems and Technologies. Funchal - Madeira, Portugal: SCITEPRESS - Science and Technology Publications; 2018:665–670. [bibtex] [url] [doi]
[7] C. Lins, SM. Müller, M. Pfingsthorn, M. Eichelberg, A. Gerka, A. Hein. Unsupervised Temporal Segmentation of Skeletal Motion Data using Joint Distance Representation. In: Proceedings of the 11th International Joint Conference on Biomedical Engineering Systems and Technologies. Funchal - Madeira, Portugal: SCITEPRESS; 2018:478–485. [bibtex] [pdf] [doi]
[6] C. Lins, S. Fudickar, A. Hein. SKAML: An XML Markup Language for Abstract Skeleton Definitions in the Context of Human Posture Assessments. In: in Proc. 4th International Conference on Information and Communication Technologies for Ageing Well and e-Health (ICT4AWE 2018). 2018. [bibtex] [pdf]
[5] C. Lins, S. Fudickar, A. Gerka, A. Hein. A Wearable Vibrotactile Interface for Unfavorable Posture Awareness Warning. In: in Proc. 4th International Conference on Information and Communication Technologies for Ageing Well and e-Health (ICT4AWE 2018). 2018. [bibtex] [url]
2017
[4] S. Blum, S. Debener, R. Emkes, N. Volkening, S. Fudickar, MG. Bleichner. EEG Recording and Online Signal Processing on Android: A Multiapp Framework for Brain-Computer Interfaces on Smartphone. BioMed Research International Hindawi. 2017;2017:12. [bibtex] [file] [doi]
2016
[3] C. Lins, A. Hein, L. Halder, P. Gronotte. Still in flow — long-term usage of an activity motivating app for seniors. In: 2016 IEEE 18th International Conference on e-Health Networking, Applications and Services (Healthcom). Munich: IEEE; 2016:1–4. [bibtex] [url] [doi]
[2] N. Volkening, A. Unni, BS. Löffler, S. Fudickar, JW.. Rieger, A. Hein. Characterizing the Influence of Muscle Activity in fNIRS Brain Activation Measurements. In: IFAC-PapersOnLine. 2016;49(11):84–88. [bibtex] [file] [doi]
[1] C. Lins, SM. Müller, A. Hein. Model-Based Approach for Posture and Movement Classification in Working Environments. Chapter in R. Wichert, H. Klausing, eds. Ambient Assisted Living: 8. AAL-Kongress 2015,Frankfurt/M, April 29-30. April, 2015. Frankfurt/M: Springer International Publishing; 2016:25–33. [bibtex] [url] [doi]
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