Inventors Challenge '23 Winner
Secured first place at the Inventors Challenge 2023 with DEMS (Domestic Emotion Monitoring System), an innovative embedded AI solution that revolutionizes mental health evaluation. The system uses real-time facial expression analysis on STM32MP135F microcontroller to aid psychiatrists in diagnosis and patient monitoring.
Context
The Inventors Challenge 2023 focused on developing innovative solutions with measurable social impact. Mental health disorders affect millions globally, with 43.8 million adults experiencing mental illness annually. The competition sought breakthrough technologies to address critical healthcare challenges.
The Challenge
Mental health diagnosis is time-consuming, often taking weeks or years, based purely on subjective assessment. The challenge was to develop an objective, data-driven tool that could accelerate diagnosis while providing psychiatrists with systematic emotion tracking and analysis capabilities.
Our Solution
DEMS is an embedded AI system built on STM32MP135F-DK microcontroller with TensorFlow Lite for real-time emotion detection. The system analyzes facial expressions to predict four emotions (angry, happy, sad, neutral), providing psychiatrists with graphical analysis and emotion pattern tracking. It features both web (Streamlit) and mobile (MIT App Inventor) applications for multi-platform accessibility.
My Role
As Team Lead & Embedded AI Engineer, I architected the embedded AI solution, implemented and optimized TensorFlow Lite models for resource-constrained hardware, developed the facial expression analysis algorithms, designed the web application, integrated camera hardware, and managed the project budget of ₹15,000.
Impact & Results
Successfully deployed real-time emotion detection on embedded hardware within tight memory and power constraints. Created a data-driven diagnostic support tool that speeds up mental health diagnosis. Aligned with UN SDG Goal 3 (Good Health and Well-being) and received expert validation from Dr. A. Turin Martina, Head of P.G and Research, Department of Rehabilitation Science.
Recognition
Awarded first place for exceptional technical innovation, practical applicability, and social impact. The judges recognized DEMS's potential to transform mental health diagnosis through objective emotion tracking and real-time embedded AI processing.