EMOTIONAL STRESS DETECTION USING DEEP LEARNING By Nithya Vasudevan Analyst - Data Science [MLDS2020]

Machine Learning Developers Summit 2020For more details, visit: https://www.mlds.analyticsindiasummit.com/

The idea is to spot people suffering from prolonged stress and how to offer a solution for the long term sufferers by predicting and analyzing their emotions using brainwaves recorded through Neurosky Brainwave Headset. The body produces larger quantities of the chemical cortisol and they trigger an increased heart rate, heightened muscle preparedness, sweating and alertness. Emotional stress is a primary factor to the six leading causes of death. It is a feeling of emotional or physical tension that makes a person feel frustrated, angry and nervous. They can be positive when it helps to avoid risk or meet a deadline. But when the stress lasts for a long time, it may ruin our health. To refrain from this situation, the individuals recognized with stress pattern are asked to listen to soft music and the brainwave pattern is recorded in response. We use neural network architectures with attention mechanism to identify the pattern and predict the emotional state of a person.

I completed my undergraduate in Information Technology at Rajalakshmi Institute of Technology, Chennai.
Projects:
➢ Worked on Distributed Tensorflow to run Neural Network models in a cluster which
reduces the training time and supports huge models to fit in memory.
➢ Worked on identifying similar training phrases across various chat intents using BERT
embeddings.
➢ Working on the Chatbot AI Testing tool to identify where the bot’s conversational flow is
disconnected and generating user phrases to test the bot using Text Generation.

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