ViDepBot: Assist People to Tackle Depression Due to COVID Using AI Techniques

ABSTRACT

Taking care of one's mental health properly is very important as we are trying to get past the effects caused by the COVID pandemic era, especially since the rate of COVID spread is still persistent. Many organizations, universities, and schools are continuing an online mode of learning or working from home situation to tackle the spreading of the coronavirus. Due to these situations, the user could be using electronic gadgets like laptops for long hours, often without breaks in between. This has eventually affected their mental health. The ‘ViDepBot', Video-Depression-Bot aims in helping the user to maintain their mental health by detecting their depression level early, and taking appropriate actions by faculty/counselors, parents, and friends to help them to come back to normalcy and maintaining a strong mental life. In this work, a system is proposed to determine the depression level from both the facial emotions and chat texts by the user. The FER2013 dataset is trained using deep learning architecture VGG-16 base model with additional layers which acquired an accuracy of around 87% for classifying the live face emotions. Since people tend to post their feelings and thoughts (when feeling down, depressed, or even happy) on social media such as Twitter, the sentiment140 twitter dataset was taken and trained using the machine learning algorithm Bayes theorem which acquired an accuracy of around 80% for classifying the user input texts. The user is monitored through a webcam and the emotions are recognized live. The ViDepBot regularly chats with the user and takes feedback on the mental condition of the user by analyzing the chat texts received. The emotions and chat texts help to find the depression level of the user. After determining the depression level, the ViDepBot framework provides ideal recommendations to improve the user's mood. This ViDepBot can be further developed to keep track of each student/subject person's depression level, where they would be physically present in the classrooms, once the pandemic situation subsides. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.