Sydney: Australian researchers have made a breakthrough in diagnosing a severe form of depression by analysing facial expressions and brain activity. 


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Researchers from the QIMR Berghofer Medical Research Institute in Australia's state of Queensland said on Wednesday that they have discovered how to diagnose melancholia by analysing a person as they watch a film.


Melancholia is a severe form of depression. People affected by melancholia can experience deep, long-lasting sadness and slowed speech, thoughts and movements, and are less likely to respond to psychological treatments and often need strong medication or brain stimulation to recover.


Phillip Mosley, lead author of the new study from QIMR Berghofer, said that early and accurate diagnosis of melancholia is critical.


The research team used artificial intelligence to analyse the facial expressions of 70 clinical trial participants with depression as they watched a funny movie. The participants then watched an emotional short film while their brain activity was measured.


Mosley said that the participants with melancholia responded differently to the stimuli than people with non-melancholic depression.


"People with melancholia looked flat, and didn't smile during a funny video. This visible difference was confirmed mathematically when we did a comprehensive analysis of the movements of facial muscles involved in smiling," he said.


Furthermore, the brains of those with melancholia registered a flattened or blunted response during uplifting scenes in an emotional film, Xinhua news agency reported.


"The research will allow general practitioners and other clinicians to diagnose people with melancholic depression more quickly and accurately, having them well again and feeling connected to their loved ones sooner," Mosley said.


The team will next explore the theory that melancholic depression could be better treated with neuromodulation, a medical technique that uses electrical stimulation or chemical agents to improve the function of the nervous system.