Model to Assess the Level of Depression by Analyzing Facial Images and Voice of Patients

Depression is considered as a common mental disorder, which is present in people of all ages causing a negative impact on different aspects of life such as mood, vitality, and interests in the enjoyment of activities, making them impossible in the long term, and in the most chronic cases can lead to suicide. Giving rise to the opportunity for collaboration between mental health specialists and the use of technological tools to support the evaluation of the level of depression to provide an optimal clinical diagnosis of the patient and an adequate referral to start treatment. In Peru, the COVID-19 epidemic has reduced physical contact and accessibility to health professionals in a timely manner, causing the patient’s mental health to not be recognized or treated properly, which leads to the chronicity of the disease, to the psychological suffering, and the high costs that are required for special care. Thus, one of the challenges of this research is to implement a technological model that evaluates levels of recurrent depression by analyzing facial images and voice to detect the chronicity of depressive symptoms in young Peruvians. Our results show that in a simulated scenario, young patients were disposed to execute a self-administered questionnaire for depression having an optimal perception of satisfaction and usability on the mobile application based on the functionalities of the model.