Contact

  • Kathrin Pollmann



    Kathrin Pollmann

    Human-Computer Interaction

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    Fraunhofer IAO
    Nobelstraße 12
    70569 Stuttgart, Germany

    • Phone +49 711 970-2347
  • Mathias Vukelic


    Dr.
    Mathias Vukelic

    Human-Computer Interaction

    more

    Fraunhofer IAO
    Nobelstraße 12
    70569 Stuttgart, Germany

    • Phone +49 711 970-5183
NeuroLab Foto: Ludmilla Parsyak, © Fraunhofer IAO

One of the top priorities when developing new technologies to improve work processes in today’s increasingly digital world is that these solutions should emphasize the human factor. For it is only by understanding human needs and expectations that we will be able to design user-friendly human-machine systems that generate added value and are enjoyable to work with.

At the Fraunhofer IAO Neurolab, we employ (neuro-)physiological methods to investigate these questions. In this way, we can learn more about the way users experience their interaction with new technologies. By studying brain activation patterns, we can identify the mental and emotional states that users experience in different work situations. Relevant questions include:

  • Do users feel at ease with the new technology, or does it increase stress levels?
  • How high is the cognitive workload associated with this task?
  • How well are users able to concentrate on the task at hand?
  • Do the new digital tools enhance productivity or, on the contrary, lead to frustration?

The scientific measurement techniques we use to investigate these and other similar questions include:

  • Electroencephalography (EEG) to record electrical activity in the brain
  • Functional near-infrared spectroscopy (fNIRS) to measure blood oxygen levels in the brain
  • Electrocardiography (ECG) to determine heart rate activity
  • Electrooculography (EOG) and Electromyography (EMG) to record eye movements and muscle activity

The (neuro-)physiological data acquired using these techniques are supplemented by additional information derived from subjective assessments and/or behavioral analysis – according to the specific aspect being studied – in order to obtain the broadest possible picture of the user’s experience, emotional response and needs. With the help of this information, we will be able to develop sustainable solutions to improve human-machine systems by adapting them more closely to the needs of individual users.

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