hexoskin-wav-analyzer

Valquiria Space Analog Physiological Data Analysis Suite

Version 2.0.1

Author: Dr. Diego Malpica MD - Aerospace Medicine Specialist
Organization: Colombian Aerospace Force (FAC) / DIMAE
Project: Valquiria Crew Space Simulation - Physiological Research Platform

🚨 IMPORTANT DISCLAIMER

This is an ongoing research project developed for scientific and educational purposes only.

⚠️ NOT FOR OPERATIONAL DEPLOYMENT ⚠️

For any operational or clinical applications, please consult with certified medical professionals and use validated, regulatory-approved systems.

Project Overview

The Valquiria Space Analog Physiological Data Analysis Suite is a comprehensive research platform designed to analyze physiological data collected during space analog simulations. The suite combines two powerful components:

  1. Hexoskin WAV File Analyzer - Complete physiological data processing and analysis
  2. Enhanced HRV Analysis System - Advanced heart rate variability analysis with machine learning

This platform was developed to support the Valquiria Space Analog Simulation research program, studying physiological adaptations and crew health monitoring in simulated space environments.

🌟 Key Features

Hexoskin WAV File Analyzer

Enhanced HRV Analysis System

πŸ—οΈ Project Structure

Valquiria-Data-Analysis/
β”œβ”€β”€ πŸ“ docs/                           # Documentation (all markdown files)
β”œβ”€β”€ πŸ“ working_folder/                 # Main analysis workspace
β”‚   β”œβ”€β”€ πŸ“ enhanced_hrv_analysis/      # Advanced HRV Analysis System
β”‚   β”‚   β”œβ”€β”€ πŸ“ core/                   # Core processing modules
β”‚   β”‚   β”œβ”€β”€ πŸ“ gui/                    # Graphical user interface
β”‚   β”‚   β”œβ”€β”€ πŸ“ ml_analysis/           # Machine learning components
β”‚   β”‚   β”œβ”€β”€ πŸ“ stats/                 # Advanced statistics
β”‚   β”‚   β”œβ”€β”€ πŸ“ visualization/         # Interactive plotting
β”‚   β”‚   └── πŸ“ tests/                 # Test suite
β”‚   β”œβ”€β”€ πŸ“ Jupyter notebooks/         # Analysis notebooks
β”‚   β”œβ”€β”€ πŸ“ hrv_results/              # Analysis outputs
β”‚   └── πŸ“ scripts/                   # Utility scripts
β”œβ”€β”€ πŸ“ DBs/                           # Database files (Sol data)
β”œβ”€β”€ πŸ“ csv_joiner/                    # Data merging utilities
β”œβ”€β”€ hexoskin_wav_loader.py            # Main Hexoskin analyzer
β”œβ”€β”€ hexoskin_wav_example.py           # Usage examples
β”œβ”€β”€ analyze_data.py                   # Data analysis scripts
β”œβ”€β”€ requirements.txt                  # Python dependencies
└── setup.py                         # Installation script

πŸš€ Quick Start

System Requirements

Installation

  1. Clone the Repository 
    git clone <repository-url>
cd Valquiria-Data-Analysis
  2. Set Up Virtual Environment ```bash

    Create virtual environment

    python -m venv venv

Activate virtual environment

Linux/macOS:

source venv/bin/activate

Windows:

venv\Scripts\activate


3. **Install Dependencies**
```bash
pip install -r requirements.txt
  1. Verify Installation 
    python test_libraries.py

Quick Usage

Hexoskin WAV Analyzer

# GUI Mode (Recommended)
python hexoskin_wav_loader.py

# Command Line Mode
python hexoskin_wav_example.py path/to/your/file.wav

Enhanced HRV Analysis

# Launch Advanced HRV Analysis GUI
cd working_folder/enhanced_hrv_analysis
python launch_hrv_analysis.py

πŸ“Š Analysis Capabilities

Physiological Data Processing

Heart Rate Variability (HRV) Analysis

Advanced Analytics

Visualization & Reporting

πŸ”¬ Scientific Features

Research-Grade Analysis

Space Medicine Applications

πŸ†• Mission Phases Boxplots Analysis

NEW FEATURE: Temporal Mission Analysis

The Enhanced HRV Analysis System now includes mission phases boxplot analysis for comprehensive crew adaptation assessment:

Features:

Analysis Types:

Integration:

Usage:

# Launch Enhanced HRV Analysis
cd src/hrv_analysis/enhanced_hrv_analysis
python launch_hrv_analysis.py

# 1. Run HRV Analysis for all subjects
# 2. Go to "Visualizations" tab
# 3. Look for green "Mission Phases" buttons:
#    β€’ Mission Phases - Individual
#    β€’ Mission Phases - Group  
#    β€’ Mission Phases - Report

Output Location: All plots and reports saved to plots_output/ folder

πŸ’» Technical Specifications

Performance Features

Data Handling

πŸ“š Documentation

All project documentation is organized in the docs/ folder:

πŸ§ͺ Testing & Validation

The project includes comprehensive test suites:

# Run all tests
cd working_folder/enhanced_hrv_analysis/tests
python run_all_tests.py

# Run specific component tests
python test_core_functionality.py
python test_advanced_statistics.py
python test_ml_analysis.py

🀝 Contributors & Acknowledgments

Special Thanks

Making This Mission Possible:

Research Collaboration:

Technical Contributors

This research would not have been possible without the courage and commitment of the Valquiria Crew members who participated in the space analog simulation missions, pushing the boundaries of human space exploration research.

πŸ“š How to Cite This Project

If you use this software in your research or publications, please cite it using the following APA format:

APA Citation

Software Citation:

Malpica, D. (2024). Valquiria Space Analog Physiological Data Analysis Suite (Version 2.0.1) [Computer software]. Colombian Aerospace Force (FAC), Aerospace Medicine Division (DIMAE). https://github.com/strikerdlm/hexoskin-wav-analyzer

Research Program Citation:

Malpica, D. (2024). Valquiria Crew Space Simulation: Physiological Research Platform for space analog studies. Colombian Aerospace Force (FAC), Aerospace Medicine Division (DIMAE).

Sample In-Text Citation

The physiological data analysis was conducted using the Valquiria Space Analog Physiological Data Analysis Suite (Malpica, 2024), which provides comprehensive heart rate variability analysis and autonomic nervous system assessment capabilities for space analog research.

BibTeX Entry

For LaTeX users:

@software{malpica2024valquiria,
  author = {Malpica, Diego},
  title = {Valquiria Space Analog Physiological Data Analysis Suite},
  version = {2.0.1},
  year = {2024},
  organization = {Colombian Aerospace Force (FAC), Aerospace Medicine Division (DIMAE)},
  url = {https://github.com/strikerdlm/hexoskin-wav-analyzer},
  note = {Physiological Research Platform for space analog studies}
}

Acknowledgment in Publications

When publishing research that uses this software, please also acknowledge:

πŸ“„ License & Usage

This project is provided as open-source software for research and educational purposes only.

Permitted Uses:

βœ… Academic research and publications
βœ… Educational training and demonstrations
βœ… Method development and validation
βœ… Non-commercial scientific collaboration

Prohibited Uses:

❌ Military operational deployment
❌ Clinical diagnosis or treatment
❌ Commercial health monitoring services
❌ Safety-critical applications

πŸ“ž Contact & Support

Primary Contact:
Dr. Diego Malpica MD
Aerospace Medicine Specialist
Colombian Aerospace Force (FAC)
Email: dlmalpicah@unal.edu.co

Project Information:
For questions about the Valquiria Space Analog Simulation or this software platform, please contact the development team through the official channels.

πŸ”„ Version History

Version 2.0.0 (Current)

Version 1.0.0

⭐ If this software contributes to your research, please cite appropriately and acknowledge the Valquiria Space Analog Simulation project.

πŸ”¬ Developed for advancing our understanding of human physiological adaptation in extreme environments.

🧭 Start Here: No Experience Required (Windows/macOS/Linux)

If you have never used Git, Python, or pip before, follow these simple steps. You will download a ZIP file, install Python, and run the program with a few copy‑paste commands.

1) Download the program (no Git needed)

2) Install Python (one time)

3) Open a terminal and go to the project folder

Tip: Your folder name may differ. Use your actual unzipped folder name.

4) Create a safe Python environment (virtual environment)

5) Install the required packages

If you see an error about tkinter or tk, install it (Linux):

sudo apt install -y python3-tk     # Ubuntu/Debian
sudo dnf install -y python3-tkinter  # Fedora/RHEL

6) Run the program (easy mode)

Use the simple launcher main.py so you don’t need to change folders.

Notes:

7) Next steps

Later: How to run it again (next time)

  1. Open your terminal/Command Prompt and go to the same project folder
  2. Activate the environment:
    • Windows: venv\Scripts\activate
    • macOS/Linux: source venv/bin/activate
  3. Start the app:
    • Hexoskin: python main.py hexoskin (Windows) or python3 main.py hexoskin (macOS/Linux)
    • HRV: python main.py hrv (Windows) or python3 main.py hrv (macOS/Linux)

Troubleshooting (quick help)

That’s itβ€”you’re up and running without needing Git or prior Python experience.

This site is open source. Improve this page.