Scientists have created an AI tool that uses sleep data from wearable devices like smartwatches to predict mood disorder episodes. Mood disorders, such as bipolar disorder, cause periods of sadness, depression, joy, or mania. These episodes are closely connected to changes in sleep patterns, making sleep-wake data a key factor in understanding mood changes.
Researchers from the Institute for Basic Science in South Korea developed this tool to improve how mood disorders are diagnosed and treated. By analyzing sleep patterns, the AI model predicts depressive, manic, and hypomanic episodes with high accuracy: 80% for depression, 98% for mania, and 95% for hypomania.
The study, published in npj Digital Medicine, involved data from 168 patients over 429 days. The team identified 36 sleep-related patterns that helped train the AI. These patterns revealed that delayed sleep and waking times increase the risk of depression, while earlier sleep and waking times increase the risk of mania.
Lead researcher Kim Jae Kyoung emphasized the cost-effective benefits of using wearable devices for this study, stating, “This offers new possibilities for diagnosing and treating mood disorder patients.”
This breakthrough shows how AI and wearable technology can provide better insights into mental health while keeping healthcare affordable and accessible.
Source: indiatimes
