What type of research are you doing?
Neurotechnology involves learning from the brain to discover how to advance technology, and vice versa – using advanced technology to reverse-engineer the brain.
This builds a dialogue between the brain and the machine that can evolve and improve over time. For example, someone with limited mobility can use gaze to tell a machine to pick up a cup, just by looking at the cup. Our software would over time, learn to tell the difference between looking at a cup to determine its contents and looking at it because we want a drink.
Why do you use eye tracking?
As a novelty in researching human sensorimotor control, our team proposes a method for annotating, analyzing and interpreting eye-movements in the wild, by relating them directly to body posture. That’s why we need access to quality eye tracking data long before any machine learning takes place.
Mapping from body movements to gaze movements leads to applications in motor rehabilitation by inverting this relationship to decode motor intentions from eye-movements. This can improve the control of machines without adding cognitive load.
Eye tracking is ideally suited to derive user motion intention in a natural manner.
Why did you choose SMI?
SMI Eye Tracking Glasses are light and unobtrusive and have therefore proven popular with our test subjects. They easily connect with other modalities and the sampling rate of up to 120 Hz gives us research-grade data that is essential for the work we conduct at the Brain & Behaviour Lab. I would recommend them to other researchers on this basis.
Find out more about the research projects in the Brain & Behaviour Lab at Imperial College here: