MUMBAI, India, July 7 -- Intellectual Property India has published a patent application (202621052333 A) filed by Prof. Ratna Patil; Laksh Khandelwal; Pranav Landge; Siddhartha Kushwaha; Sharvani Kulwal; and Sneha Laddha on April 24, 2026, for Mind Mate: A Web-Based Assistant For Student Stress Detection And Academic Task Management..
Inventors include Prof. Ratna Patil; Laksh Khandelwal; Pranav Landge; Siddhartha Kushwaha; Sharvani Kulwal; and Sneha Laddha.
The application for the patent was published on July 03, 2026, under issue no. 27/2026.
Abstract: The rising number of students pursuing degrees at colleges & universities has led to heavy academic workloads, which are creating chronic stress; in some cases, extreme feelings of burnout are also occurring. To directly address this problem, MindMate was developed to assist students. It is a website that you can combine your academic planning with your mental health. As it relates to productivity, MindMate includes a smartscheduler however as it relates to wellness, it can record your moods using mood journals, determine how much stress you are feeling based on using natural language processing (NLP), and also provide you with chatbots that can help you find calming exercises as well as other support services on campus. Natural language processing works from a list of simple words rather than an extremely complex neural network so that the system is easy to use, allows for rapid response time and requires little computer functionality. After inputting their journal entry, the system evaluates the entry's text for both negative and positive terms and adds a self-reported mood (on a 1-10 scale). A score is then calculated from two data sources (the pending task count & the entry score) to create a Burnout Index, providing students with an early indicator of potential overwhelming stress. The initial results validate that stress analysis using the Flask back end = 180 ms response times; the CPU use is at 15% during peak loads; and the lexicon engine's keyword tracking matches mostly to user self-reported mood rating(s).
Disclaimer: Curated by HT Syndication.
