Ensemble empirical mode decomposition with principal component analysis: a novel approach for extracting respiratory rate and heart rate from photoplethysmographic signal

Motin, Mohammod Abdul, Karmakar, Chandan Kumar and Palaniswami, Marimuthu 2018, Ensemble empirical mode decomposition with principal component analysis: a novel approach for extracting respiratory rate and heart rate from photoplethysmographic signal, IEEE J. Biomedical and Health Informatics, vol. 22, pp. 766-774, doi: 10.1109/JBHI.2017.2679108.

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Title Ensemble empirical mode decomposition with principal component analysis: a novel approach for extracting respiratory rate and heart rate from photoplethysmographic signal
Author(s) Motin, Mohammod Abdul
Karmakar, Chandan KumarORCID iD for Karmakar, Chandan Kumar orcid.org/0000-0003-1814-0856
Palaniswami, Marimuthu
Journal name IEEE J. Biomedical and Health Informatics
Volume number 22
Article ID 3
Start page 766
End page 774
Total pages 9
Publisher IEEE Journal of Biomedical and Health Informatics
Publication date 2018
Keyword(s) ensemble empirical mode decomposition (EEMD)
ensemble empirical mode decomposition with principal component analysis (EEMD-PCA)
principal component analysis (PCA)
photoplethysmographic (PPG) signal
respiratory rate estimation
Science & Technology
Technology
Life Sciences & Biomedicine
Computer Science, Information Systems
Computer Science, Interdisciplinary Applications
Mathematical & Computational Biology
Medical Informatics
Computer Science
ensemble empirical mode decompositionwith principal component analysis (EEMD-PCA)
EMERGENCY-DEPARTMENT
PULSE OXIMETER
ALGORITHM
NOISE
ECG
IDENTIFICATION
CHILDREN
SYSTEM
PCA
DOI 10.1109/JBHI.2017.2679108
HERDC Research category C1 Refereed article in a scholarly journal
ERA Research output type C Journal article
Persistent URL http://hdl.handle.net/10536/DRO/DU:30093185

Document type: Journal Article
Collection: Centre for Pattern Recognition and Data Analytics
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