Study to detect early depression among seniors through voice analysis

Researchers aim to detect and manage early signs of depression among seniors through voice analysis, as part of a three-year study and pilot programme that uses artificial intelligence (AI).

- Syarafana Shafeeq

Changes in the pitch or tone of voice could be a result of physiological changes arising from early depression, say the researchers.

The SoundKeepers programme will recruit more than 600 seniors aged 55 and above in Hougang and Woodlands to collect their voice samples, which will be used to build an AI algorithm to detect subsyndromal depression (SSD). SSD is characterised by the emergence of depressive symptoms that are not severe enough to be diagnosed as major depression. The programme involves seven partners – NTU's Lee Kong Chian School of Medicine and College of Computing and Data Science, National Healthcare Group Polyclinics, the Institute of Mental Health (IMH), Fei Yue Community Services, Club Heal and Lien Foundation.

In Singapore, past research has shown that around 13.4 per cent of seniors over 60 experienced SSD, though this figure is likely underestimated due to reliance on self-reported assessments, the agencies said on Oct 16.

This statistic is from a research paper in 2016 based on data from a 2011 Well-being of the Singapore Elderly study, a nationwide survey on the mental health profile of seniors here.

“Currently, SSD is not actively diagnosed or treated,” said Dr Mythily Subramaniam, assistant chairwoman of IMH's medical board for research.