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Continuous Blood Pressure Monitoring Using ANN

Investigation and Development of a Novel Continuous Blood Pressure (BP) Monitoring System Based on Artificial Neural Network (ANN)

Research Paper:

Motivation for Project:

  • Healthcare has become an important issue in aging countries such as Singapore
  • There is a need to have such solutions where people can monitor their health themselves
  • Continuous vital signs monitoring devices are needed that are economical, portable, simple and reliable
  • Among these vital signs, continuous monitoring of BP is very important, especially for
    elderly people with chronic cardiac conditions

Objectives of Project:

The main objectives of this project are:

  • To develop a Peaks Detection Algorithm (PDA) for Pulse Transit TIme (PTT) calculation.
  • To develop an ANN model to obtain beat-to-beat BP values. This involves training and testing the ANN, debugging the model and incorporating the model into a vital signs monitoring device

Project Details:

Above-mentioned objectives were achieved via the following tasks:

  • An integrated code consisting of following was generated:
    • User Prompt,
    • Peaks Detection Algorithm (PDA),
    • PTT Calculation, and
    • ANN Model using Levenberg-Marquardt Algorithm (LMA)
  • An ECGnPPG Unit (EPU) was developed to determine the Electrocardiogram (ECG) signals and Photoplethysmography (PPG) signals for calculating the PTT
  • A preliminary study was conducted on 10 subjects to validate the objectives
  • MatLab software was used as a tool for this project

The following images illustrate some of above tasks:

Methodology (A modified methodology was adopted due to unavailability of ccNexfin Finapres device) :

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ANN Training Methodology:

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EPU:

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User Prompt (Input data from subjects was gathered using this prompt in MatLab) :

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PTT Calculation:

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ANN Model (Only 1 layer was used and LMA was used to train ANN) :

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  • A final year thesis project in partial fulfillment of requirements for B.E. (Mechanical) at National University of Singapore (NUS)
  • The project involved use of knowledge from medical, computer and programming disciplines

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