Health x Wellness
Scientists develop programme that can detect depression using wearable data
Nanyang Technological University, Singapore (NTU Singapore) scientists have developed a predictive computer programme that can detect individuals who are at increased risk of depression.
According to the World Health Organisation, depression affects 280 million people globally, and is undiagnosed and untreated in half of all cases. In Singapore, the COVID-19 pandemic has led to increased concerns over mental well-being. A Singapore Institute of Mental Health study pointed to a likely increase in mental health issues, including depression related to the pandemic.
A team of scientists from NTU Singapore has developed the Ycogni model, powered by machine learning. The programme screens for the risk of depression by analysing an individual’s physical activity, sleep patterns, and circadian rhythms derived from data from wearable devices that measure his or her steps, heart rate, energy expenditure, and sleep data.
To develop the Ycogni model, scientists conducted a study involving 290 working adults in Singapore. Participants wore Fitbit Charge 2 devices for 14 consecutive days and completed two health surveys, which screened for depressive symptoms, at the start and end of the study.
In trials, the programme achieved an accuracy of 80 percent in detecting those individuals with a high risk of depression and those with no risk.
We look forward to expanding on our research to include other vital signs in the detection of depression risk, such as skin temperature. Fine-tuning our programme could help in facilitating early, unobtrusive, continuous, and cost-effective detection of depression in the general population.
Professor Josip Car, Director, Centre for Population Health Sciences at NTU’s Lee Kong Chian School of Medicine (LKCMedicine)
Associating patterns to symptoms of depression
The researchers have associated certain patterns in the participants behaviours to depressive symptoms. These symptoms can include feelings of helplessness and hopelessness, loss of interest in daily activities, and changes in appetite or weight.
From analysing their findings, the scientists found that those who had more varied heart rates between 2 am to 4 am, and between 4 am to 6 am, tended to be prone to more severe depressive symptoms.
This observation confirms findings from previous studies, which had stated that changes in heart rate during sleep might be a valid physiological marker of depression. The study also associated less regular sleeping patterns, such as varying waking times and bedtimes, to a higher tendency to have depressive symptoms.
Photo by Anthony Tran on Unsplash
