An Integrated Approach for Suicidal Tendency Detection

Suicidal Tendency or the intention to kill oneself and end their life is a catastrophic situation which is mostly unknown by any person in the victim’s life. In many studies it is evident that, victims tend to kill themselves either to end their pain, pressure or to have a relief that they are not going to live in this world anymore. Current suicidal tendency detection methods include numerous machine learning and deep learning approaches using clinical data or online social media, provide a solution to this existing problem. This paper aims to present a multi-modal approach that could help the victim’s close ones to know if he/she is suffering from suicidal tendency. Providing a multi-faceted method that can detect this tendency and intimate the family, friends or the close ones beforehand can prove to be a boon for the invention. Three different approaches like Facial Gesture Recognition, Voice Pattern Recognition and Text Pattern Recognition are imbibed in the Android Mobile Application and used as modules to determine suicidal intent in a complementary manner. Finally, the limitations and future scope are extrapolated to provide an overview for the future research.