How these sleep scientists are embracing uncertainty

Sebastiaan Overeem and Merel van Gilst don’t necessarily want more accuracy when gathering sleep data from patients with sleeping disorders. Instead, they want more room for uncertainty and ways to show that. One possible solution is the hypnodensity graph – a method for displaying the likelihood of a certain sleep stage in patients. According to both researchers, ‘there is information lurking in uncertainty’.

At TU/e’s Advanced Sleep Monitoring Group, Professor Sebastiaan Overeem and Assistant Professor Merel van Gilst are quietly rewriting the rules of sleep science. Instead of adding ever more sensors to patient’s heads, they’re questioning how data should be interpreted to better diagnose patients suffering from one of the more than eighty currently recognized sleep disorders.

“Hospital equipment is impressive,” says Overeem, who is also a clinical somnologist (a clinician specializing in sleeping disorders). “But it still only measures surface activity and places complex brain processes in simple boxes. In this process of data interpretation, you lose a lot of what’s actually interesting.”

Learning from ambiguous signals

Their solution sounds almost counterintuitive: don’t hide uncertainty, but instead show it. “We want monitoring that’s less obtrusive and more practical,” Van Gilst explains. “And we also want it to be more truthful.”

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