Fatigue Detection Technology for Online Learning

In order to avoid the influence of fatigue caused by online learning, this paper studies the fatigue detection technology of online learning by extracting facial fatigue characteristic parameters. In order to improve the accuracy and speed of the detection of the face area, the SSD (single shot multi box detector) target detection algorithm is optimized. Using feature point location to extract facial fatigue feature parameters, combining with fuzzy evaluation ideas, incorporating multiple fatigue feature parameters, a fatigue detection algorithm based on fuzzy evaluation is proposed. Experiments with the data on the sample set show that the improved algorithm system has improved detection speed and accuracy, and can effectively reflect the learner’s fatigue state during online learning. The average recognition rate has reached 96%. The characteristic fatigue detection technology has reached a high level, which is of great significance to prevent students from studying fatigue.