Assistenzsysteme und Medizintechnik

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

Das Living Lab Medical Process Modeling entwickelt Forschungsinfrastruktur für medizinspezifische Fragestellungen. Es ermöglicht die Erfassung und Modellierung standardisierter zeitkritischer Prozesse wie z.B. der prähospitalen Reanimation (dem Mega Code Training). Hierauf aufbauen wird die Analyse der individuellen Durchführungsgüte, Benchmarking und Vorhersage von menschlichen Verhaltensweisen in einem definierten sozio-technischen System, sowie die Optimierung der Abläufe, Mensch-Technik-Interaktion.

Somit leistet das Living Lab CMP einen wesentlichen Beitrag zur Quantifizierung, Optimierung und Standardisierung medizinischer Prozesse.

Ansatz

In einem ersten Schritt wird die nötige Infrastruktur entwickelt um medizinische Arbeitsabläufe (wie der prähospitalen Wiederbelebung) in typischen sicherheitskritischen Situationen technisch mit Fokus auf funktionale Eigenschaften wie Timing, Workloads und Aufmerksamkeitsspanne während der Ausführung zu modellieren.

Hierzu gilt es relevante Bewegungsabläufe der Teilnehmer hochpräzise sowohl über Umgebungs- als auch Inertialsensoren zu verfolgen (Motion Capture). Die Kombination dieser beiden unterschiedlichen Motion Capture Ansätze vermeidet die Schwächen der einzelnen Systeme; beispielsweise sind optische Motion Capture Verfahren sehr anfällig für einfallendes Sonnenlicht und Inertialsensoren werden am Ende des kinematischen Baums (z. B. an den Händen) unpräzise. Desweiteren werden die kognitive Auslastung und die Blickwinkel der Beteiligten vermessen und modelliert.

Darüber hinaus werden alle Aktivitäten, die den Patienten betreffen, mit Hilfe eines A(C)LS Simulators und EKGs erfasst und in einer Evaluierungsplattform zusammengeführt. Zusätzlich soll untersucht werden, welche Sensorik für zukünftige Entscheidungsunterstützungssysteme für den Einsatz im Feld geeignet ist.

Basierend auf den so gewonnenen Kontextinformationen werden die betrachteten Prozesse hinsichtlich Timing, Workloads und Aufmerksamkeitsspanne während der Ausführung modelliert und individuelle Ausführungen gebanchmarkt.

In einem zweiten Schritt werden im Projekt darüber hinaus Simulationsdarstellungen exemplarisch für das Mega Codes Training erstellt und dieses somit optimiert.

Förderung / Kooperationen

Das Interdisziplinäre Forschungszentrum für den Entwurf sicherheitskritischer soziotechnischer Systeme („Interdisciplinary Research Center for Critical Systems Engineering for Socio-Technical Systems") untersucht die Rolle des Menschen bei der Beherrschung komplexer Verkehrssysteme auf dem Land und dem Wasser. Kooperationspartner sind das Oldenburger Informatikinstitut OFFIS, das DLR-Institut für Verkehrssystemtechnik in Braunschweig und das Kompetenznetzwerk SafeTRANS. Das Land Niedersachsen stellt in der aktuellen zweiten Förderphase eine weitere Anschubfinanzierung in Höhe von 2 Millionen Euro zur Verfügung, die Laufzeit wurde hier um weitere 18 Monate verlängert (2017-2018). Das LL MPM wird in Kooperation mit der Professur Medizininformatik des Departments entwickelt.

Publikationen

  • [article] bibtex
    S. Blum, S. Debener, R. Emkes, N. Volkening, S. Fudickar, und M. G. Bleichner, "EEG Recording and Online Signal Processing on Android: A Multiapp Framework for Brain-Computer Interfaces on Smartphone," BioMed Research International Hindawi, vol. 2017, p. 12, 2017.
    @article{Blum2017, abstract = {Objective. Our aim was the development and validation of a modular signal processing and classification application enabling online electroencephalography (EEG) signal processing on off-the-shelf mobile Android devices. The software application SCALA (Signal ProCessing and CLassification on Android) supports a standardized communication interface to exchange information with external software and hardware. Approach. In order to implement a closed-loop brain-computer interface (BCI) on the smartphone, we used a multiapp framework, which integrates applications for stimulus presentation, data acquisition, data processing, classification, and delivery of feedback to the user. Main Results. We have implemented the open source signal processing application SCALA. We present timing test results supporting sufficient temporal precision of audio events. We also validate SCALA with a well-established auditory selective attention paradigm and report above chance level classification results for all participants. Regarding the 24-channel EEG signal quality, evaluation results confirm typical sound onset auditory evoked potentials as well as cognitive event-related potentials that differentiate between correct and incorrect task performance feedback. Significance. We present a fully smartphone-operated, modular closed-loop BCI system that can be combined with different EEG amplifiers and can easily implement other paradigms.},
      author = {Blum, Sarah and Debener, Stefan and Emkes, Reiner and Volkening, Nils and Fudickar, Sebastian and Bleichner, Martin G},
      doi = {10.1155/2017/3072870},
      file = {:C$\backslash$:/Users/NilsV/AppData/Local/Mendeley Ltd./Mendeley Desktop/Downloaded/Blum et al. - Unknown - EEG Recording and Online Signal Processing on Android A Multiapp Framework for Brain-Computer Interfaces on Smar.pdf:pdf},
      journal = {BioMed Research International Hindawi},
      keywords = {AMTCSE,AMTUNI,accepted,full paper},
      mendeley-tags = {AMTCSE,AMTUNI,accepted,full paper},
      pages = {12},
      title = {{EEG Recording and Online Signal Processing on Android: A Multiapp Framework for Brain-Computer Interfaces on Smartphone}},
      volume = {2017},
      year = {2017} }
  • [incollection] bibtex | Dokument aufrufen Dokument aufrufen
    C. Lins, S. M. Müller, und A. Hein, "Model-Based Approach for Posture and Movement Classification in Working Environments," in Ambient Assisted Living: 8. AAL-Kongress 2015,Frankfurt/M, April 29-30. April, 2015, Wichert, R. und Klausing, H., Eds., Frankfurt/M: Springer International Publishing, 2016, pp. 25-33.
    @incollection{Lins.2016b, abstract = {In this paper, we present an approach for model-based movement and posture classification in working environments. The approach presented here is designed for long-term in-situ observations of and by workers in their workplaces. The proposed model is adaptable to different input data, e.g., skeleton data from either an Inertial Measurement Unit (IMU) or a skeleton derived from an optical sensor such as Kinect. We present a preliminary design of the model and suggest algorithms suitable for real-time usage of the model in an IMU-based motion capture suite. In an experiment we measured the weight on the knee while performing different kneeing postures to show the dependence of posture angles on the knee load.},
      address = {Frankfurt/M},
      author = {Lins, Christian and M{\"{u}}ller, Sebastian Matthias and Hein, Andreas},
      booktitle = {Ambient Assisted Living: 8. AAL-Kongress 2015,Frankfurt/M, April 29-30. April, 2015},
      doi = {10.1007/978-3-319-26345-8_3},
      editor = {Wichert, Reiner and Klausing, Helmut},
      file = {:C$\backslash$:/Users/NilsV/AppData/Local/Mendeley Ltd./Mendeley Desktop/Downloaded/Lins, M{\"{u}}ller, Hein - 2016 - Model-Based Approach for Posture and Movement Classification in Working Environments.pdf:pdf},
      isbn = {978-3-8007-3901-1},
      keywords = {Working environment Model Posture Classification K,accepted,full paper},
      mendeley-tags = {accepted,full paper},
      pages = {25--33},
      publisher = {Springer International Publishing},
      series = {Advanced Technologies and Societal Change},
      title = {{Model-Based Approach for Posture and Movement Classification in Working Environments}},
      url = {http://www.springer.com/de/book/9783319263434 http://link.springer.com/10.1007/978-3-319-26345-8{\_}3},
      year = {2016} }
  • [inproceedings] bibtex
    N. Volkening, A. Unni, B. S. Löffler, S. Fudickar, J. W. Rieger, und A. Hein, "Characterizing the Influence of Muscle Activity in fNIRS Brain Activation Measurements," in Proc. IFAC-PapersOnLine, 2016, pp. 84-88.
    @inproceedings{Volkening2016, abstract = {Driving is a complex and cognitively demanding task. It is essential to assess the cognitive state of the driver in order to design cognitive technical systems that can adapt to different driver cognitive states. Our research attempts to assess these states using functional Near Infrared Spectroscopy (fNIRS) by measuring brain activity in a virtual reality driving simulator. However, the fNIRS brain activation measurements could be influenced by muscle activity and we wanted to investigate this phenomenon. For this, we designed a paradigm with two conditions (listen, teeth clench) which show a significant contrast in the influence of muscle activity. We observed that the muscle hemodynamic response can show a higher magnitude of signal change compared to brain hemodynamic response. The muscle hemodynamic response showed an increase in deoxygenated hemoglobin (HbR) whereas the brain hemodynamic response showed a decrease in HbR. Moreover, the dynamics of the brain and muscle hemodynamic response differed. The brain response showed the same latency for oxygenated hemoglobin (HbO) and HbR while the muscle HbR response had a slower latency compared to HbO. We concluded that the fNIRS brain activation measurements could indeed be influenced by muscle activity. We were also able to determine some characteristics of the muscle hemodynamic response.},
      author = {Volkening, Nils and Unni, Anirudh and L{\"{o}}ffler, Birte Sofie and Fudickar, Sebastian and Rieger, Jochen W. and Hein, Andreas},
      booktitle = {IFAC-PapersOnLine},
      doi = {10.1016/j.ifacol.2016.08.013},
      file = {:C$\backslash$:/Users/NilsV/AppData/Local/Mendeley Ltd./Mendeley Desktop/Downloaded/Volkening et al. - 2016 - Characterizing the Influence of Muscle Activity in fNIRS Brain Activation Measurements.pdf:pdf},
      issn = {24058963},
      keywords = {OFFIS=G-AIT/AHT/CSE,UNIAMT,UNICSE,accepted,full paper},
      mendeley-tags = {OFFIS=G-AIT/AHT/CSE,UNIAMT,UNICSE,accepted,full paper},
      number = {11},
      pages = {84--88},
      title = {{Characterizing the Influence of Muscle Activity in fNIRS Brain Activation Measurements}},
      volume = {49},
      year = {2016} }
  • [inproceedings] bibtex | Dokument aufrufen Dokument aufrufen
    C. Lins, A. Klausen, S. Fudickar, S. Hellmers, M. Lipprandt, R. Röhrig, und A. Hein, "Determining Cardiopulmonary Resuscitation Parameters with Differential Evolution Optimization of Sinusoidal Curves," in Proc. Proceedings of the 11th International Joint Conference on Biomedical Engineering Systems and Technologies, Funchal - Madeira, Portugal, 2018, pp. 665-670.
    @inproceedings{Lins2018c, abstract = {In this paper, we present a robust sinusoidal curve fitting method based on the Differential Evolution (DE) algorithm for determining cardiopulmonary resuscitation (CPR) parameters – naming chest compression fre-quency and depth – from skeletal motion data. Our implementation uses skeletal data from the RGB-D (RGB + Depth) Kinect v2 sensor and works without putting non-sensor related constraints such as specific view an-gles or distance to the system. Our approach is intended to be part of a robust and easy-to-use feedback system for CPR training, allowing its unsupervised training. We compare the sensitivity of our DE implementation with data recorded by a Laerdal Resusci Anne mannequin. Results show that the frequency of the DE-based CPR is recognized with a variance of ±4.4 bpm (4.1{\%}) in comparison to the reference of the Resusci Anne mannequin.},
      address = {Funchal - Madeira, Portugal},
      author = {Lins, Christian and Klausen, Andreas and Fudickar, Sebastian and Hellmers, Sandra and Lipprandt, Myriam and R{\"{o}}hrig, Rainer and Hein, Andreas},
      booktitle = {Proceedings of the 11th International Joint Conference on Biomedical Engineering Systems and Technologies},
      doi = {10.5220/0006732806650670},
      file = {:C$\backslash$:/Users/NilsV/AppData/Local/Mendeley Ltd./Mendeley Desktop/Downloaded/Lins et al. - 2018 - Determining Cardiopulmonary Resuscitation Parameters with Differential Evolution Optimization of Sinusoidal Curves.pdf:pdf},
      isbn = {978-989-758-281-3},
      keywords = {CPR Training,Cardiac Massage,Curve Fitting,Evolutionary Algorithm,UNIAMT,UNILLM},
      mendeley-tags = {UNIAMT,UNILLM},
      pages = {665--670},
      publisher = {SCITEPRESS - Science and Technology Publications},
      title = {{Determining Cardiopulmonary Resuscitation Parameters with Differential Evolution Optimization of Sinusoidal Curves}},
      url = {http://www.scitepress.org/DigitalLibrary/Link.aspx?doi=10.5220/0006732806650670},
      year = {2018} }
  • [inproceedings] bibtex | Dokument aufrufen Dokument aufrufen
    C. Lins, A. Hein, L. Halder, und P. Gronotte, "Still in flow — long-term usage of an activity motivating app for seniors," in Proc. 2016 IEEE 18th International Conference on e-Health Networking, Applications and Services (Healthcom), Munich, 2016, pp. 1-4.
    @inproceedings{Lins2016, abstract = {In this paper, results from the long-term usage of a mobile application (app) for seniors that encourages physical and mental activity are presented. The application was designed for elderly inhabitants of senior residences to motivate them to increase their physical and mental activity in everyday life. Usage statistics of 82 users for about two years were processed and show that the active elderly users can be clustered in two groups with either increasing or decreasing and very little constant activity. Users with decreasing activity have also shown decreasing usage errors with the app's user interface which may indicate that they are growing out of the app. The results show insight view about the usage and suggest that the Concept of Flow can be applied here.},
      address = {Munich},
      author = {Lins, Christian and Hein, Andreas and Halder, Luca and Gronotte, Philipp},
      booktitle = {2016 IEEE 18th International Conference on e-Health Networking, Applications and Services (Healthcom)},
      doi = {10.1109/HealthCom.2016.7749476},
      file = {:C$\backslash$:/Users/NilsV/AppData/Local/Mendeley Ltd./Mendeley Desktop/Downloaded/Lins et al. - 2016 - Still in flow — long-term usage of an activity motivating app for seniors.pdf:pdf},
      isbn = {978-1-5090-3370-6},
      keywords = {accepted},
      mendeley-tags = {accepted},
      month = {sep},
      pages = {1--4},
      publisher = {IEEE},
      title = {{Still in flow — long-term usage of an activity motivating app for seniors}},
      url = {http://ieeexplore.ieee.org/document/7749476/},
      year = {2016}