A local optical flow eye-tracking method for depression detection

Abstract

Aiming at the problem that depression detection is easily affected by subjective factors such as patient willingness, self-awareness, and doctor’s level, as well as inconvenient detection and high cost, a universal detection method with low cost and convenient deployment is proposed. A local optical flow tracking method is adopted, which is realized by eye region detection and optical flow estimation. Then, three experiments are designed to verify the accuracy of the method and the effectiveness of eye movement tracking. The formula for calculating the depression state is proposed, and the eye movement of one normal participant’s elliptical trajectory of the left and right pupils in the horizontal and vertical directions is 44.4805, 42.7013, 29.3571, and 31.1364 mm, respectively. To verify the effectiveness of the proposed method, three example points are selected. Among them, the fixation duration at P1 is 1.87 s, the eye movement direction at P2 and P3 is 1.168°, counterclockwise around the X axis, and the number of fixation times is 46. Finally, 18 normal participants and four depression-positive participants are tested by the exploratory eye movement paradigm. The results show that the accuracy rate of identifying depression patients using the NEF metric method can reach ∼81.8%, which can help quantify the detection of depression and provide the possibility for professionals to remotely diagnose individuals with depression.