AGXStarseed
Well-Known Member
(Not written by me)
AN ALGORITHM that analyses facial expressions and head movements could help doctors diagnose autism-like conditions and attention deficit hyperactivity disorder.
There is no simple test for autism or ADHD, but clinicians usually observe someone’s behaviour as part of the assessment. “These are frequently co-occurring conditions and the visual behaviours that come with them are similar,” says Michel Valstar at the University of Nottingham, UK.
His team used machine learning to identify some of these behaviours. The group captured video of 55 adults as they read and listened to stories and answered questions about them. “People with autism do not always get the social and emotional subtleties,” says Valstar.
The participants fell into four groups: people diagnosed with autism-like conditions, ADHD, both or neither.
The system learned to spot differences between how the groups responded. For example, people with both conditions were less likely to raise their eyebrows when they saw surprising information.
The team also tracked head movement to gauge how much the volunteers’ attention wandered. Using both measures, the system correctly identified people with ADHD or autism-like conditions 96 per cent of the time (arxiv.org/abs/1612.02374).
Eric Taylor at King’s College London welcomes the potential of this as a diagnostic tool for these conditions. But he says the best approach is still observing children in everyday surroundings.
Algorithms won’t take over from doctors any time soon, says Valstar. “We are creating diagnostic tools that will speed up the diagnosis in an existing practice, but we do not believe we can remove humans. Humans add ethics and moral values to the process.”
Source: Computer uses facial cues to spot if people have autism
AN ALGORITHM that analyses facial expressions and head movements could help doctors diagnose autism-like conditions and attention deficit hyperactivity disorder.
There is no simple test for autism or ADHD, but clinicians usually observe someone’s behaviour as part of the assessment. “These are frequently co-occurring conditions and the visual behaviours that come with them are similar,” says Michel Valstar at the University of Nottingham, UK.
His team used machine learning to identify some of these behaviours. The group captured video of 55 adults as they read and listened to stories and answered questions about them. “People with autism do not always get the social and emotional subtleties,” says Valstar.
The participants fell into four groups: people diagnosed with autism-like conditions, ADHD, both or neither.
The system learned to spot differences between how the groups responded. For example, people with both conditions were less likely to raise their eyebrows when they saw surprising information.
The team also tracked head movement to gauge how much the volunteers’ attention wandered. Using both measures, the system correctly identified people with ADHD or autism-like conditions 96 per cent of the time (arxiv.org/abs/1612.02374).
Eric Taylor at King’s College London welcomes the potential of this as a diagnostic tool for these conditions. But he says the best approach is still observing children in everyday surroundings.
Algorithms won’t take over from doctors any time soon, says Valstar. “We are creating diagnostic tools that will speed up the diagnosis in an existing practice, but we do not believe we can remove humans. Humans add ethics and moral values to the process.”
Source: Computer uses facial cues to spot if people have autism
