2024 ASEE Annual Conference & Exposition

SerenePulse: A Web App Pipeline for Real-time Physiological Monitoring Using rPPG and OpenAI LLMs

Presented at Computing and Information Technology Division (CIT) Technical Session 6

With 15% of working-age adults facing mental disorders and an annual loss of US$ 1 trillion in the world due to impaired productivity from depression and anxiety, the necessity for real-time emotional and physiological monitoring is paramount. As similar levels of stress and mental health disorders are found among engineering students, mental health management is imperative in engineering education. However, the high costs associated with mental health management tools, the necessity for additional gadgets, and rare usage among students pose significant barriers to widespread adoption and utilization in engineering education. In this study, we examine the integration of Remote Photoplethysmography (rPPG), a wireless stress measurement technology for real-time physiological monitoring by detecting light intensity variations on the skin. By advanced rPPG signal processing, Heart Rate Variability (HRV) metrics like Standard Deviation of Normal-to-Normal Intervals(SDNN), Root Mean Square of Successive Differences(RMSSD), and the Low-Frequency / High-Frequency Ratio(LF/HF) are calculated to offer stress insights. Our results resulted in an accuracy of 92% as validated with the ground truth dataset. Moving forward, we aim to enhance performance and deploy an app for widespread, low-cost access to stress management and monitoring.

Authors

Mr. Sreekanth Gopi Kennesaw State University [biography]

Over the years I have developed professionally into an aspiring Data Scientist, Machine Learning Engineer, and seasoned Artificial Intelligence Researcher. Currently, I am in the process of publishing a few papers on stress reduction and improving student performance.
More:
AI Engineer | INTEL ClarifAI AI Hackathon winner | Data Scientist | Machine Learning Engineer | AIResearcher | ADHD EEG classification | AI music generation | Outstanding Graduate Student | 3 published papers | Research Project winner!

Education:
BE in Mechanical Engineering
MBA in Information Technology
MS in Computer Science (IP)

My paper is accepted for 2024 ASEE Southeastern Section Conference, Marietta, GA, March 10 - 12, 2024.

Research interests:
1. Meditation
2. Music
3. AI

Hackathons:
1. INTEL AI Hackathon FIRST prize Winner!
2. Llama 2 ClarifAI LablabAI hackathon SECOND prize winner!

Published papers:
Peer-reviewed Published papers:
1. FIE 2023 IEEE conference, Texas, USA: EEG Spectral Analysis and Prediction for Inattention Detection in Academic Domain
2. AIMC 2023, Brighton, UK: Introductory Studies on Raga Multi-track Music Generation of Indian classical music using AI.
3. ASEE March 2024, Marietta, GA: Exploring the Impact of CM-II Meditation on Stress Levels in College Students through HRV Analysis.
4. MSCS Master's Thesis: CM-II meditation as an intervention to reduce stress and improve attention: A study of ML detection, EEG Spectral Analysis, and HRV metrics.
Nasrin Dehbozorgi http://orcid.org/0009-0004-2748-0654 Kennesaw State University [biography]

I’m an Assistant Professor of Software Engineering and the director of the AIET lab in the College of Computing and Software Engineering at Kennesaw State University. With a Ph.D. in Computer Science and prior experience as a software engineer in the industry, my interest in both academic and research activities has laid the foundation to work on advancing educational technologies and pedagogical interventions.

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