Figure 5
From: Research on drowsiness detection in UAV operators based on the random decision forest method
Proposed algorithm for drowsiness classification. Based on the calculated behavioral indicators (PERCLOS, EAR, MAR, pitch and roll angles), the algorithm proceeds as follows. If the PERCLOS value is greater than or equal to 25%, the operator is classified as drowsy. If the PERCLOS value is less than 12.5%, the operator is classified as not drowsy. For PERCLOS values between 12.5% and 25%, classification is performed using the random forest model, which determines the operator’s drowsiness state based on EAR, MAR, pitch, and roll values.
