ECG Signal Extraction Method Based on Singular Value Selection and Wavelet
Objective
The primary objective of this project, titled "ECG Signal Extraction Method Based on Singular Value Selection and Wavelet," is to develop and implement an innovative signal processing technique for the accurate extraction and enhancement of Electrocardiogram (ECG) signals.
Abstract
A singular value selection and wavelet-based ECG signal extraction approach is proposed in order to reduce the noise of the received ECG signal. First, the ECG signal is subjected to a singular value decomposition, and the components of the ECG signal corresponding to each unique value are recovered. The cross-correlation coefficients between the signal component and other components are then calculated using the signal component corresponding to the largest singular value. To calculate the required number of singular values for ECG signal reconstruction, the cumulative contribution rate of singular values is added. The final determined signal components are de-noised using the wavelet threshold de-noising technique. After reconstructing the signal components, the de-noising ECG signal is obtained. The experimental findings demonstrate that the approach effectively suppresses noise and extracts signal, and that it outperforms wavelet threshold method in terms of noise reduction.
Keywords: ECG Signals, Singular Value Selection and Wavelet.
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
Paper Publishing
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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.
