Research on how the chemicals humans emit through breathing vary in response to audio-visual stimuli has been awarded
the famous scientific parody prize, the Ig Nobel.Dr Joerg Wicker from the Machine Learning Group at the University of Auckland is one of the researchers working on the ‘smell of fear’ project which earned the Ig
Nobel for Chemistry announced today.
He says it’s fun to have the work recognised even if it’s something of a tongue-in-cheek compliment.
“Our work is a bit ‘out there’ I guess it fits quite well as the prize ‘honours achievements that first make people
laugh, and then make them think’.“
Working with colleagues from the Max Planck Institute for Chemistry and University of Mainz, Dr Wicker uses machine
learning to try to better understand volatile organic compounds or VOCs– tiny molecules of small mass that humans
constantly emit when breathing or through the skin.
Current PTR-MS technology allows hundreds of volatile trace gases in air to be measured every second at extremely low
levels (parts per trillion). These instruments are often used in atmospheric research on planes and ships and even in
the Amazon rainforest.
The research team continuously monitored carbon dioxide and more than one hundred volatile organic compounds of a group
of people in a cinema watching a movie. They found that airborne chemicals emitted by the audience varied while they
watched a film so that scenes of suspense or comedy caused the audience to change emissions of particular chemicals.
It was found that many airborne chemicals in cinema air varied distinctively and reproducibly with time for a particular
film, even in different screenings to different audiences. Application of advanced machine learning methods revealed
that specific film events, for example "suspense" or "comedy" caused audiences to change their emission of specific
chemicals.
Those findings have a wide range of potential uses. Synchronous, broadcasted human chemo-signals open the possibility
for objective and non-invasive assessment of a human group response to stimuli by continuous measurement of chemicals in
air.
“By applying advanced machine learning techniques we have shown that groups of people reproducibly respond to certain
emotional stimuli, for example suspense and comedy, by exhaling specific trace gases,” Dr Wicker says.
“These experimental results show that some VOCs and some labels can be predicted with relatively low error, and that
hints for causality with low p-values can be detected in the data.”