🎭 FaceScan AuraeAI

Unleash the power of facial analysis with MediaPipe FaceMesh integration! Perfect for health tech, biometric analysis, and real-time face tracking applications.

✨ Features

• 🎯 Real-time face detection and mesh mapping
• 🌈 Advanced RGB color analysis from specific facial regions
• 📸 Smart frame capture with compression
• 💪 Robust error handling and data validation
• 🎨 Visual feedback with canvas rendering
• 📊 Comprehensive biometric data extraction

🩺 Health Parameters Detected FaceScan AuraeAI provides a comprehensive analysis of various health parameters through advanced facial scanning: Vital Signs

❤️ Heart Rate (HR) 🫁 Respiratory Rate (RR) 🩸 Blood Pressure (BP) 🌡️ Mean Arterial Pressure (MAP) 💗 Cardiac Output 🔵 SpO2 (Blood Oxygen Saturation)

Body Composition

💧 Body Water Percentage 💧 Total Body Water 🏋️ Ideal Body Weight 📊 BMI (Body Mass Index) 🔄 Total Body Fat Percentage 🩸 Blood Volume

Cardiac Metrics

❤️ Maximum Heart Rate (HR Max) 🎯 Target Heart Rate Range 💓 Heart Rate Reserve 🔋 Heart Utilization

Blood Parameters

🩸 Hemoglobin (Hb) 📊 HbA1c (Glycated Hemoglobin)

Stress & Recovery

😌 Stress Index 📈 Stress Level 💗 SDNN (Standard Deviation of NN intervals) 💓 RMSSD (Root Mean Square of Successive Differences) 📊 PNN50 (Percentage of NN intervals)

Fitness Metrics

🏃‍♂️ VO2 Max (Maximum Oxygen Uptake) 📊 ABSI (A Body Shape Index)

Overall Health

🎯 Wellness Score 📈 Age-related Health Indicators

🚀 Installation

npm install facescan-auraeai

📦 Dependencies

This package requires the following peer dependencies:

{
  "@mediapipe/face_mesh": "*",
  "@mediapipe/camera_utils": "*",
  "@mediapipe/control_utils": "*",
  "@mediapipe/drawing_utils": "*"
}

🎮 Quick Start

const FaceScan = require("facescan-auraeai");

// Initialize components
await FaceScan.initializeFaceMesh();
await FaceScan.initializeCamera(videoElement);
FaceScan.initializeCanvas(canvasElement);

// Start analysis
const results = await FaceScan.startAnalysis(
  (data) => {
    console.log("Analysis complete:", data);
  },
  {
    userId: "user123",
    sessionId: "session456",
  }
);

📊 Sample Health Data Response javascriptCopy{ "statusCode": 200, "body": { // Vital Signs "HR": 72.0, // Heart rate in BPM "RR": 22.0, // Respiratory rate "BP": "100/74", // Blood pressure "MAP": "82.67 mmHg", // Mean arterial pressure "Cardiac Output": 1.1, // Cardiac output "Spo2": 99.0, // Blood oxygen saturation

// Body Composition
"Body Water": 51.39,                  // Body water percentage
"Total Body Water": 43.68,            // Total body water
"Ideal body weight": 39.0,            // Ideal body weight
"BMI": 43.4,                          // Body Mass Index
"Total Body Fat": 41.6,               // Body fat percentage
"Blood Volume": 5870.0,               // Blood volume

// Cardiac Metrics
"HR Max": 195.0,                      // Maximum heart rate
"Target Heart Rate Range": "166.0 bpm",// Target heart rate
"Heart Rate Reserve": 123.0,          // Heart rate reserve
"Heart Utilize": 37.0,                // Heart utilization

// Blood Parameters
"Hb": "13.7",                         // Hemoglobin
"HbA1c": "6.5",                       // Glycated hemoglobin

// Stress & Recovery
"Stress Index": 0.64,                 // Stress index
"Stress level": "Elevated",           // Stress level
"SDNN": "52",                         // Heart rate variability
"RMSSD": "34",                        // Root mean square differences
"PNN50": "36",                        // NN interval percentage

// Fitness & Overall Health
"VO2 Max": 41.44,                     // Maximum oxygen uptake
"ABSI": 0.059,                        // Body shape index
"wellnessScore": 78,                  // Overall wellness score

// Metadata
"gender": "Male",
"Age": "21",
"timestamp": "26 October 2024 at 11:50:30 IST+0530"

} }

🛠️ API Reference

initializeFaceMesh()

Initializes the MediaPipe FaceMesh with optimal settings for facial analysis.

initializeCamera(videoElement)

Sets up the camera feed with the specified video element.

• videoElement: HTML video element for camera feed

initializeCanvas(canvasElement)

Prepares the canvas for rendering facial landmarks.

• canvasElement: HTML canvas element for visualization

startAnalysis(callback, metadata)

Begins the facial analysis process.

• callback: Function to receive analysis results
• metadata: Optional object with additional data
• Returns: Promise with analysis results

🎨 Visualization

The package provides real-time visualization of:

• Facial mesh tessellation
• Eye and eyebrow tracking
• Iris detection
• Face oval mapping
• Lip contour tracking

🔐 Privacy & Security

• All processing happens client-side
• No facial data is stored permanently
• Compressed and encoded frame capture for minimal memory usage
• Secure data handling with proper cleanup

🤝 Contributing

Contributions are welcome! Please feel free to submit a Pull Request.

📝 License

ISC © Ana Fariya

🙏 Acknowledgments

Special thanks to the MediaPipe team for their amazing face mesh implementation.

Made with ❤️ by Ana Fariya