Stress Detection Using SVM and Virtual Assistant

This paper presents a chatbot model designed to detect stress in users through simple yes-or-no questions. Utilizing a Support Vector Machine (SVM) algorithm, the model achieves high accuracy in identifying stress levels and provides users with actionable advice or medical recommendations. The chatbot’s user-friendly interface is built using Anaconda Navigator and Python, ensuring ease of use for non-technical users. The model achieves a 100% accuracy rate on the given dataset, making it a promising tool for stress detection and early intervention.