A Machine Learning Algorithm for Biomedical Signal Processing Application

In this chapter, significant emphasis has been given to machine learning (ML) for biomedical signal processing. The basic purpose of this chapter is to explore the numerous possibilities of ML in the field of biomedical signal processing. With the increasing volume of available biomedical data, netw...

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Bibliographic Details
Published inMachine Learning Methods for Signal, Image and Speech Processing pp. 149 - 168
Main Authors Choubey, Abhishek, Choubey, Shruti Bhargava, Rao, S.P.V. Subba
Format Book Chapter
LanguageEnglish
Published United Kingdom Routledge 2021
River Publishers
Edition1
Subjects
TCP
Compressed Sensing
Computerized Signal
STFT
Vice Versa
Low SNR
SVMs
Ml Model
Hilbert Huang Transform
ECG Signal
Biomedical Signal Processing
Sign Handling
EMD
Tv Transmission
Nonlinear Input Output Mapping
RSE
HMM
Multilayer Perceptron Neural Network
Signal Processing
Soft Thresholding Method
Deep Neural Network
SNR Ratio
Denoized Signal
High SNR
Thresholding Method
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Summary:In this chapter, significant emphasis has been given to machine learning (ML) for biomedical signal processing. The basic purpose of this chapter is to explore the numerous possibilities of ML in the field of biomedical signal processing. With the increasing volume of available biomedical data, network speed, and computing power, the modern biomedical signal is facing an unique amount of data to interpret and analyze. Phenomena like Big Data-omics restricting from numerous diagnostic methods and novel multiparametric singling modalities tend to produce practically unmanageable amounts of data. Traditional ML ideas have established many limitations when it comes to correctly diagnose like electrocardiogram, hearing aid, and EEG diseases. At the same time, static graph networks are unable to capture the fluctuations in monitor and processing progress. Therefore, deep learning and artificial intelligence are applied in bio-medical singling because they excel at providing quantitative assessments of biomedical singling characteristics.
ISBN:9788770223690
8770223696
DOI:10.1201/9781003338789-7