Project HeartBeat

This repository contains the code for the project "Project HeartBeat". This project contains three main parts:

1. User Information:

In this step, the user is first asked to enter their Name, Gender [M/F] and Age. As the user submits this information, this information is stored in a text file for the current user. This information is later used in the last step to generate user's "Medical Report".

2. Collect User Heart Rate Data:

In this step, the user clicks on the "Start Reading Data" Button which starts reading the data from the "PulseSensor" connected to Arduino and to laptop over Serial Port. The button press triggers two functions:

a) save_and_plot: In this, the data is collected for upto 3 to 4 minutes and is saved into a CSV file along with Timestamp. Then we pre-process the data using Pandas to provide column names and organize the data in a better way.

b) plotHeartBeat: Once the data collection is complete, this function is called to load the data from the CSV file and a Heart Rate plot is generated for the user and saved as a png file.

3. Get User Data Analytics:

In this step, the user clicks on the "Get Data Summary" button which in turn invokes three functions:

a) getUserImage: In this, we use OpenCV to take an image of the user whose data is being collected and crop and resize it according to our report requirements. This image is saved and is used to personalize the user Helth Report.

b) get_data_analytics: In this, we read the data using Pandas as a DataFrame. This data has two features: "Heart_Rate" and "Time". We read in the "Heart_Rate" data and find the rolling mean average of the heart rate data and plot it. Along with this, we find the peaks between two heart rate plots, the difference between which gives us the "Beats per Minute". We take in the data for all the peaks in the plot of heart rate data and find the "Average Beats per Minute" using that.

c) save_report: In this, we take all the data that we have collected till now i.e. Name, Age, Gender, user Image, Current Date, Average BPM, Heart Rate ECG plots, Heart Rate plots with moving averages and peaks and generate a single Medical Report for the user as a PDF file.

Requirements:

1. Python 3.5 or above

2. OpenCV [latest]

3. Flask

pip3 install flask

4. Numpy

pip3 install numpy

5. Pandas

pip3 install pandas

6. Matplotlib

pip3 install matplotlib

7. Serial

pip3 install -U pySerial

8. ReportLab

pip3 install reportlab

9. Arduino Board + PulseSensor [or any other Heart Rate Measurement Sensor]

10. Jupyter Notebook

pip3 install jupyter notebook

11. emoji

pip3 install emoji

12. urllib3

pip3 install urllib3

Usage

To make this project work, follow these instructions:

1. Clone this repository using:

git clone https://github.com/AashiDutt/Project_HeartBeat.git

2. Connect your Arduino Board with Pulse Sensor as follows:

Red Wire -> 5V
Black Wire -> GND
Purple Wire -> A0

3. Once you have the connections, upload the code to Arduino. For this, open the code in the folder "Arduino-Sensor-Code" in Arduino IDE and click on Upload. Once the code is uploaded successfully, test out the data from the sensor using Arduino's Serial Plotter under Tools.

4. Once you have the data, go to your current directory and open Jupyter Notebok as follows:

jupyter notebook Final-Project-Code.ipynb

5. Run each code block one by one. After running the last block you should get a localhost address. Click on that to open. This should take you to the Flask Dashboard as shown in results below.

6. Now follow these steps:

1. Enter your name, gender, age and email id in the text box and click Submit. Ex. john_wayne,M,30,john.wayne@gmail.com

2. Then take the PulseSensor and strap it around your finger and click on "Start Reading Data".

3. Once this is done, click on "Get Data Summary". This will open a camera to take your picture for the pdf report. 

4. Click on "Space Bar to Capture Image" and then "Esc to Exit".

5. Once this is done, wait till you see a pdf file in your current directory. Once you have the pdf, the process is complete.

Results

1. Flask Dashboard:

2. Heart Rate Reading and it's Plot:

3. Data Analysis [Finding Peaks, Computing Moving Averages and Computing Average BPM]:

4. Final PDF Report:

You can download or view the sample generated PDF report here.

To DO's

• Build pipeline from Arduino to Flask for getting data.
• Add code to read data on button press.
• Add code to plot the data automatically at backend and store as Pandas DataFrame.
• Add code to analyze stored data using moving averages and using peaks to find estimated Average BPM.
• Add code to capture patient's image for medical report.
• Add code to generate PDF report using all the data and plots.
• Add code to send generated PDF report to patient using patient's email.
• Add code to store each user's data in database (MongoDB) for future retrieval.
• Add code to retrieve user's previous data and reports from database for doctor's reference.