RESUMO
BACKGROUND: Saccadic eye movement (SEM) has been considered a non-invasive potential biomarker for the diagnosis of depression in recent years, but its application is not yet mature. In this study, we used eye-tracking technology to identify the eye movements of patients with depression to develop a new method for objectively identifying depression. METHODS: Thirty-six patients with depression as the depression group, while thirty-six matched healthy individuals as the control group were recruited and completed eye movement tests, including two tasks: the prosaccade task and the antisaccade task. iViewX RED 500 eye-tracking instruments from SMI were used to collect eye movement data for both groups. RESULTS: In the prosaccade task, there was no difference between the depression and control groups(t = 0.019ï¼ P > 0.05). In general, with increasing angle, both groups showed significantly higher peak velocity (F = 81.72ï¼ P < 0.0001), higher mean velocity (F = 32.83, P = 0.000), and greater SEM amplitude (F = 24.23, P < 0.0001). In the antisaccade task, there were significant differences in correct rate (t = 3.219, P = 0.002) and mean velocity (F = 3.253ï¼ P < 0.05) between the depression group and the control group. In the anti-effect analysis, there were significant differences in correct rate (F = 67.44, P < 0.0001) and accuracy (F = 79.02, P < 0.0001) between the depression group and the control group. Both groups showed longer latency and worse correct rate and precision in the antisaccade task compared with the prosaccade task. CONCLUSION: Patients with depression showed different eye movement features, which could be potential biomarkers for clinical identification. Further studies must validate these results with larger sample sizes and more clinical populations.