Chronic Obstructive Pulmonary Disease (COPD) Diagnosis using Electromyography (EMG)

Chronic Obstructive Pulmonary Disease (COPD) Diagnosis using Electromyography (EMG) presents a new and innovative method of COPD diagnosis using EMG to analyze sternomastoid muscle activity using features extraction and classification. The book describes the methodology of EMG analysis, the slope-based onset detection algorithm and SEMG analysis in time, frequency and time frequency domain analyses. It also explores the identification of frequencies for single frequency Continuous Wavelet Transform (CWT) analysis and feature extraction and selection for successful classification COPD into its severity grades.

The book provides a compilation of all techniques used in the literatures and emphasizes newly proposed techniques for the early detection of COPD. Fully comprehensive, the book includes discussion of limitations of existing methods for COPD diagnosis and introduces new efficient methods for COPD identification, classification and early diagnosis.

Autorentext

Dr. Archana Bajirao Kanwade has completed M.E. in Electronic-Communication in 2009 from Shivaji University. University of Pune has awarded her a PhD degree in Electronics and Telecommunication Engineering in 2020. She has 17 years of teaching experience and 09 years of research experience. She has filed a patent on COPD diagnosis using EMG analysis. She has published more than 35 technical papers, out of which 28 papers are in International journals. She has 4 papers indexed in Scopus Journals and 2 papers in SCI indexed journals. She is reviewer for three Scientific Journals.
She has also been invited as resources person for invited talk. She is a member of IEEE SIGHT. Currently she is associated with Sinhgad Institute of Technology and Science, (Affiliated college to S P Pune University), India as Assistant Professor in Electronics and Telecommunication Engineering. She is recognized PG Guide in Electronics and Telecommunication Engineering of Savitribai Phule Pune University.

Inhalt

1. Introduction
   
   2. Methodology
   3. COPD and healthy classification
   4. COPD grade classification
   5. Early detection of COPD
   6. Results and discussion
   7. Conclusion