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Neurocontrol - Technology in Motion

State-of-the-art technology can facilitate movement.

We are facing a time of rapid technological progress with regard to measuring, improving and stimulating human movement. The mission of the Technology in Motion research theme is to merge cutting-edge human movement science with state-of-the-art motion technology and academic entrepreneurship to generate knowledge and solutions for and with our students, educators and societal stakeholders. We focus on research and development in the context of actor-environment interactions. Actor movements and environmental layout data are typically gathered with 3D depth cameras (Kinect, Hololens) and environments are enriched with augmented/mixed reality, often in a movement-dependent manner, to evoke actor-environment interactions.

Augmented reality

Walking is a context-dependent activity. However, our understanding of walking and the sensitivity by which walking limitations can be identified is hampered because situational and environmental context conditions are currently not an integral part of walking assessments. We have developed two augmented-reality solutions, the C-Mill treadmill and the overground Interactive Walkway, to assess and train context-dependent walking.

  • Cueing in Parkinson’s disease
    We address effects of augmented visual feedback on postural control to investigate the direct effects of this feedback on postural control and its potential benefits for balance control in patients with Parkinson’s disease.
  • The Interactive Walkway
    Presentation of augmented-reality objects is controlled in a movement-dependent manner using real-time processing of data derived from multiple spatially and temporally integrated sensors.

Mixed reality

Walking is a context-dependent activity. However, our understanding of walking and the sensitivity by which walking limitations can be identified is hampered because situational and environmental context conditions are currently not an integral part of walking assessments. We have developed two augmented-reality solutions, the C-Mill treadmill and the overground Interactive Walkway, to assess and train context-dependent walking.