Review on Automated Depression Detection from audio visual clue using Sentiment Analysis

Depression is a common mood disorder that has a negative impact on a person's life. It's a global pandemic that's claiming the lives of countless people. They find it difficult to concentrate on their careers, engage with others, and have become introverted. The lack of up-to-date resources has a negative impact on the country's economic development. As a result, it's important to develop new ways to identify and treat mental conditions, as well as reach out to individuals, so that people can overcome their daily challenges and become more productive. Depression can be detected using a series of nonverbal signals, such as systematic facial expression patterns and body posture. The study's aim is to look at automated depression detection strategies that could aid doctors in diagnosing and treating depression. The field of automatic depression detection focused on visual cues is expanding rapidly. The current comprehensive analysis of existing methods focuses on machine learning algorithms and image processing, as stated.