Improve Blood Pressure Measurements

This project aims to improve the accuracy of blood pressure measurements using video-based heart rate monitoring and a calculation algorithm. The system utilizes facial tracking to detect and analyze heart rate data, which is then used to estimate blood pressure.

Features

• Real-time heart rate monitoring using facial recognition and video processing.
• Blood pressure calculation based on heart rate, weight, height, and age.
• Graphical display of heart rate data and trends using PyQt5.

Project Structure

• blood_pressure_calculator.py: Contains the algorithm to calculate blood pressure based on heart rate and other personal parameters.
• conf.py: Configuration file with settings for the heart rate monitoring system.
• facetracker.py: Handles face detection and tracking using OpenCV.
• person.py: Manages individual user data and processes heart rate signals.
• plot.py: Utilizes PyQt5 to display graphical representations of heart rate data.
• main.py: Entry point for running the heart rate monitoring and blood pressure calculation system.
• pulse.py: Main application logic for the heart rate monitoring system.
• sceneanalyzer.py: Analyzes heart rate for persons in a video frame.
• util.py: Utility functions for the application.
• videostream.py: Handles the video stream from the webcam.
• widgets.py: GUI components for displaying video and graphs.

Setup

1. Install the required packages:

   pip install -r requirements.txt

2. Configure settings: You can adjust the settings in conf.py or override them by creating a .heartwave.conf file in your home directory with your custom settings.

Usage

To run the system, execute the main script:

python main.py

This will start the heart rate monitoring system, which uses your computer's webcam to detect and track faces, analyze heart rate data, and estimate blood pressure.

Detailed Description of Key Components

blood_pressure_calculator.py This module calculates systolic and diastolic blood pressure using the following formula:

def blood_pressure_calculator(avg_bpm, weight, height, age):
    kgs = weight * 0.45359237  # lbs to kgs
    cm = height / 0.39370  # in to cm
    Q = 4.5  # constant

    rob = 18.5
    et = (364.5 - 1.23 * avg_bpm)
    bsa = 0.007184 * (kgs ** 0.425) * (cm ** 0.725)
    sv = (-6.6 + (0.25 * (et - 35)) - (0.62 * avg_bpm) + (40.4 * bsa) - (0.51 * age))
    pp = sv / ((0.013 * kgs - 0.007 * age - 0.004 * avg_bpm) + 1.307)
    mpp = Q * rob

    sp = int(mpp + 3 / 2 * pp)
    dp = int(mpp - pp / 3)

    return sp, dp

facetracker.py This module uses OpenCV to detect and track faces in the video feed. It processes frames to identify regions of interest (ROI) for heart rate analysis.

person.py The Person class manages individual user's heart rate data, including raw signal processing, bandpass filtering, and frequency spectrum analysis.

plot.py This module provides functionalities to plot heart rate data using PyQt5. It can display real-time heart rate trends and other related information.

conf.py This configuration file includes settings such as minimum and maximum heart rate, camera ID, sampling periods, and timeouts. Users can override these settings by creating a .heartwave.conf file in their home directory.

pulse.py This module contains the main application logic for starting the heart rate monitoring system. It initializes the video stream, face tracker, and scene analyzer, and displays the results in a GUI.

sceneanalyzer.py This module analyzes heart rate for persons in a scene by processing frames and identifying heart rate data from detected faces.

util.py Utility functions used across the application, including functions for running the event loop and converting images.

videostream.py Handles the video stream from the webcam, emitting frames to be processed by other modules.

widgets.py GUI components for displaying video and graphical plots of heart rate data.