An Empirical Mode Decomposition-Based Method for Feature Extraction and Classification of Sleep Apnea

A. Smruthy; M. Suchetha

doi:10.1007/978-981-10-8354-9_25

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An Empirical Mode Decomposition-Based Method for Feature Extraction and Classification of Sleep Apnea

A. Smruthy M. Suchetha

Year: 2018 Lecture notes in electrical engineering Pages: 279-286 Publisher: Springer Science+Business Media

DOI: 10.1007/978-981-10-8354-9_25

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Keywords:

Hilbert–Huang transform Sleep apnea Polysomnography Artificial intelligence Feature extraction Obstructive sleep apnea Support vector machine Apnea Computer science Pattern recognition (psychology) Central sleep apnea Classifier (UML) Speech recognition Medicine Cardiology Internal medicine Computer vision

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Obstructive Sleep Apnea Research

Health Sciences → Medicine → Physiology

Non-Invasive Vital Sign Monitoring

Physical Sciences → Engineering → Biomedical Engineering

Phonocardiography and Auscultation Techniques

Health Sciences → Medicine → Pulmonary and Respiratory Medicine

An Empirical Mode Decomposition-Based Method for Feature Extraction and Classification of Sleep Apnea

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