Signal Processing in Medicine and Biology: Emerging Trends in Research and Applications

Iyad Obeid, Ivan Selesnick, Joseph Picone

Research output: Book/ReportBook

Abstract

This book covers emerging trends in signal processing research and biomedical engineering, exploring the ways in which signal processing plays a vital role in applications ranging from medical electronics to data mining of electronic medical records. Topics covered include statistical modeling of electroencephalograph data for predicting or detecting seizure, stroke, or Parkinson’s; machine learning methods and their application to biomedical problems, which is often poorly understood, even within the scientific community; signal analysis; medical imaging; and machine learning, data mining, and classification. The book features tutorials and examples of successful applications that will appeal to a wide range of professionals and researchers interested in applications of signal processing, medicine, and biology. • Covers traditional signal processing topics within biomedicine • Promotes collaboration between healthcare practitioners and signal processing researchers • Presents tutorials and examples of successful applications.

Original languageEnglish (US)
PublisherSpringer International Publishing
Number of pages281
ISBN (Electronic)9783030368449
ISBN (Print)9783030368432
DOIs
StatePublished - Jan 1 2020

Keywords

  • Adaptive Filtering
  • Big Data
  • Bioinformatics
  • Biomedical Engineering
  • Biomedical Nanosensors
  • Data Classification
  • Data Mining
  • Linear Filtering and Prediction
  • Machine Learning
  • Medical Imaging
  • Nonlinear Filtering and Prediction
  • Signal Analysis
  • Signal Processing
  • Time-Frequency

ASJC Scopus subject areas

  • General Engineering
  • General Biochemistry, Genetics and Molecular Biology
  • General Medicine
  • General Health Professions

Fingerprint

Dive into the research topics of 'Signal Processing in Medicine and Biology: Emerging Trends in Research and Applications'. Together they form a unique fingerprint.

Cite this