Obeid I., Selesnik I., Picone J. (eds.) Signal Processing in Medicine and Biology. Emerging Trends in Research and Applications

Springer, 2020. — 287 p.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.Preface
An Analysis of Automated Parkinson's Diagnosis Using Voice: Methodology and Future Directions
Noninvasive Vascular Blood Sound Monitoring Through Flexible Microphone
The Temple University Hospital Digital Pathology Corpus
TransientArtifactsSuppressioninTimeSeriesviaConvexAnalysis
The Hurst Exponent: A Novel Approach for Assessing Focus During Trauma Resuscitation
Gaussian Smoothing Filter for Improved EMG Signal Modeling
Clustering of SCG Events Using Unsupervised Machine Learning
Deep Learning Approaches for Automated Seizure Detection from Scalp Electroencephalograms
Correction to: The Temple University Hospital DigitalPathology Corpus
Index