Neuroscientists from the University of Surrey in England have developed a new method that can determine the exact type of depression from brain signals with 91% accuracy. The results of the research have been published magazine Biomedical Signal Processing and Control.
Anxiety-depressive disorder includes symptoms of depression and anxiety in equal measure. Patients with this type of depression often have more severe symptoms and are more difficult to treat. The ICD-10 manual lists the disease as “mixed anxiety and depressive disorder” and there are no clear criteria for the definition, so it is often difficult for a psychiatrist to make an accurate diagnosis and recommend treatment. Scientists emphasize that quickly diagnosing and treating anxiety depression is critical to avoid irreparable consequences.
The research team recorded five-minute EEGs with eyes open and closed in 15 patients with this type of depression and nine patients with normal depression. Researchers evaluated electrical activity at 68 points in the brain and used machine learning to create brain activity maps for patients with and without anxious depression.
The results showed that patients with anxiety-depressive disorder had stronger signals in the right hemisphere. In addition, the accuracy of detecting signals with patients’ eyes closed increased significantly. In the future, scientists will conduct a series of experiments to improve the method. Experts hope it will help doctors better recognize anxiety-depressive disorder in the future.