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Smart System for Multi-Modal Physiological Signal Collection and Mental Stress Assessment

Welcome to the repository for our groundbreaking project aimed at developing a smart system for multi-modal physiological signal collection and mental stress assessment.

Project Overview

Our project, titled "Smart System Development for Multi-Modal Physiological Signal Collection and Mental Stress Assessment," is a pioneering endeavor that seeks to revolutionize mental health monitoring. Divided into two integral parts, our project unfolds as follows:

Stage I: Data Acquisition

Currently, we are in Stage I of the project, focusing on gathering crucial physiological data. By interfacing with ECG and EEG circuits, as well as capturing skin impedance responses from GSR sensors, we lay the foundation for comprehensive physiological monitoring. Our aim is to seamlessly integrate these disparate signals into a compact and portable device, empowering individuals with insightful health metrics.

Stage II: Machine Learning Optimization

Following Stage I, we will transition into Stage II, delving into the realm of machine learning optimization. Leveraging the computational prowess of Raspberry Pi, we will conduct a series of trials, fine-tuning algorithms for peak performance. Through meticulous experimentation and analysis, we aim to unlock the potential to discern intricate patterns in physiological signals and translate them into actionable insights. The culmination of this phase will manifest in visually captivating graphs, offering a glimpse into the complex landscape of mental stress assessment.

Unique Feature: Integrated Physiological Monitoring

A hallmark of our project is the integration of ECG and EEG signals into a single, portable device. This innovative approach not only streamlines data collection but also provides a holistic view of an individual's mental stress levels. By synthesizing diverse physiological signals, our system transcends traditional monitoring methods, paving the way for a deeper understanding of mental well-being.

Repository Contents

Explore the wealth of resources available in our repository:

Data Acquisition

  • Delve into the intricacies of data acquisition with code snippets, circuit diagrams, and detailed documentation.

Machine Learning Optimization

  • Dive deep into the art of machine learning optimization through meticulously crafted scripts, experimentation logs, and optimization strategies.

Graphical Outputs

  • Immerse yourself in a visual journey of mental stress assessment with a curated collection of graphical outputs generated from Raspberry Pi.

Contact Us

For inquiries,please reach out to at [deba9862@gmail.com].

Thank you!!