PMID- 24110865
OWN - NLM
STAT- MEDLINE
DCOM- 20150805
LR  - 20200928
IS  - 2694-0604 (Electronic)
IS  - 2375-7477 (Linking)
VI  - 2013
DP  - 2013
TI  - Sleep apnea classification using least-squares support vector machines on single 
      lead ECG.
PG  - 5029-32
LID - 10.1109/EMBC.2013.6610678 [doi]
AB  - In this paper a methodology to identify sleep apnea events is presented. It uses 
      four easily computable features, three generally known ones and a newly proposed 
      feature. Of the three well known parameters, two are computed from the RR 
      interval time series and the other one from the approximate respiratory signal 
      derived from the ECG using principal component analysis (PCA). The fourth feature 
      is proposed in this paper and it is computed from the principal components of the 
      QRS complexes. Together with a least squares support vector machines (LS-SVM) 
      classifier using an RBF kernel, these four features achieve an accuracy on test 
      data larger than 85% for a subject independent classification, and of more than 
      90% for a patient specific approach. These values are comparable with other 
      results in the literature, but have the advantage that their computation is 
      straightforward and much simpler. This can be important when implemented in a 
      home monitoring system, which typically has limited computational resources.
FAU - Varon, Carolina
AU  - Varon C
FAU - Testelmans, Dries
AU  - Testelmans D
FAU - Buyse, Bertien
AU  - Buyse B
FAU - Suykens, Johan A K
AU  - Suykens JA
FAU - Van Huffel, Sabine
AU  - Van Huffel S
LA  - eng
PT  - Journal Article
PT  - Research Support, Non-U.S. Gov't
PL  - United States
TA  - Annu Int Conf IEEE Eng Med Biol Soc
JT  - Annual International Conference of the IEEE Engineering in Medicine and Biology 
      Society. IEEE Engineering in Medicine and Biology Society. Annual International 
      Conference
JID - 101763872
SB  - IM
MH  - Algorithms
MH  - Electrocardiography/*instrumentation/*methods
MH  - Fourier Analysis
MH  - Heart/physiology
MH  - Humans
MH  - *Least-Squares Analysis
MH  - Principal Component Analysis
MH  - Reproducibility of Results
MH  - Respiration
MH  - Respiratory Rate
MH  - *Signal Processing, Computer-Assisted
MH  - Sleep Apnea Syndromes/*diagnosis/physiopathology
MH  - Software
MH  - Support Vector Machine
EDAT- 2013/10/11 06:00
MHDA- 2015/08/06 06:00
CRDT- 2013/10/11 06:00
PHST- 2013/10/11 06:00 [entrez]
PHST- 2013/10/11 06:00 [pubmed]
PHST- 2015/08/06 06:00 [medline]
AID - 10.1109/EMBC.2013.6610678 [doi]
PST - ppublish
SO  - Annu Int Conf IEEE Eng Med Biol Soc. 2013;2013:5029-32. doi: 
      10.1109/EMBC.2013.6610678.