Nanyang Technological University’s (NTU) scientists have developed a computer program that can detect those people who are at a higher risk of developing depression. Like Fitbit watches, the predictive program analyses a person’s sleep patterns, physical activity, and circadian rhythms through data from wearable devices.
In 2019, for three months, 290 adults carried a trial that showed the program has an accuracy of 80 % in detecting those with depression. It also shows people who are at a high risk of developing depressive symptoms/depression when compared to healthy individuals. The adults wore a tracking device for two weeks, aged between 21 and 69 years with an average age of 33 years.
Director of the Centre for Population Health Sciences at the Lee Kong Chian School of Medicine, Professor Josip Car said that to fine-tune and improve the machine-learning algorithm, his team is planning for larger studies of more than 1,000 participants and monitoring them for two years.
According to the World Health Organisation’s website, 264 million people are affected with depression globally, out of which there are half of the cases that are undiagnosed and untreated.
