Development of a Smart Mental Health Training Model by Utilizing the Mental Measurement Data and Eye Recognition Algorithm

Application of the mental measurement data recognition based on the eye recognition algorithm in the construction of mental health smart training curriculum is discussed in this manuscript. In this study, the selected items were consistent with the emotional cues of eyes or mouth and nose to determine whether they were judged by eyes or mouth and nose. The results showed that the subjects made more use of mouth and nose cues to judge emotion. With this data collection pattern, the mental measurement data recognition based on eye recognition algorithm is discussed. Considering the existence of rotation in many pictures, a block-based detection method is then proposed, which can effectively solve such problems without relying too much on the position information that the eyes are directly above the picture. Then the proposed research study will collect and process these information and the mental health smart training is selected as the numerical analysis scenario. By evaluating under different aspects, the designed system is shown to be more effective.