Compensating for Respiratory Artifacts in Blood Pressure Waveforms Using MATLAB
Objective
The objective of this project is to analyze online blood pressure and respiratory signal datasets to calculate breathing rates, extract features like Respiratory Sinus Arrhythmia (RSA), and classify health status using an SVM classifier, ensuring high accuracy.
Abstract
We will use online datasets of blood pressure and respiratory signals for extracting the features of health status using breathing rate calculated from the datasets and these features will be used to train the Support Vector Machine (SVM) classifier and its performance will be validated during testing on the basis of accuracy. The breathing rates will be calculated using respiratory signals (like respiratory inductance plethysmography or airflow measurements), by detecting peaks (inhalation) or troughs (exhalation). The heart rate naturally fluctuates with the breathing cycle, Slowing down during exhalation and speeding up during inhalation. This phenomenon, Respiratory Sinus Arrhythmia (RSA), can be analyzed from the BP waveform to estimate the respiratory rate.
Keywords: Blood Pressure, Respiratory Signals, Support Vector Machine (SVM) Classifier, Breathing Rates, Respiratory Sinus Arrhythmia (RSA).
NOTE: Without the concern of our team, please don't submit to the college. This Abstract varies based on student requirements.
Block Diagram
Specifications
Software: Matlab 2020a or above
Hardware:
Operating Systems:
- Windows 10
- Windows 7 Service Pack 1
- Windows Server 2019
- Windows Server 2016
Processors:
Minimum: Any Intel or AMD x86-64 processor
Recommended: Any Intel or AMD x86-64 processor with four logical cores and AVX2 instruction set support
Disk:
Minimum: 2.9 GB of HDD space for MATLAB only, 5-8 GB for a typical installation
Recommended: An SSD is recommended A full installation of all MathWorks products may take up to 29 GB of disk space
RAM:
Minimum: 4 GB
Recommended: 8 GB
Learning Outcomes
· Introduction to Matlab
· What is EISPACK & LINPACK
· How to start with MATLAB
· About Matlab language
· Matlab coding skills
· About tools & libraries
· Application Program Interface in Matlab
· About Matlab desktop
· How to use Matlab editor to create M-Files
· Features of Matlab
· Basics on Matlab
· What is Signal Processing?
· About Signal Processing
· Introduction to Signal Processing
· How analog and digital signal is formed
· Importing the signal via signal acquisition tools
· Analyzing and manipulation of signals.
· Phases of signal processing:
· Acquisition
· Signal enhancement
· Signal restoration
· Medical Signal Processing
· Medical Signal Analysis
· Medical Signal Diagnosis
· Filtering techniques
· Machine Learning Algorithms
· Deep Learning Algorithms etc.
· How to extend our work to another real time applications
· Project development Skills
o Problem analyzing skills
o Problem solving skills
o Creativity and imaginary skills
o Programming skills
o Deployment
o Testing skills
o Debugging skills
o Project presentation skills
o Thesis writing skills
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Disclaimer - Takeoff Edu Group Projects are not associated or affiliated with IEEE in any way. The IEEE Projects mentioned here are mentioned in the context of student projects, whose ideas are derived from IEEE publications, not projects of or by IEEE.
