Sebnem Yosunkaya

According to our database1, Sebnem Yosunkaya authored at least 14 papers between 2008 and 2018.

Collaborative distances:
  • Dijkstra number2 of six.
  • Erdős number3 of five.

Timeline

Legend:

Book 
In proceedings 
Article 
PhD thesis 
Other 

Links

On csauthors.net:

Bibliography

2018
A novel system for automatic detection of K-complexes in sleep EEG.
Neural Computing and Applications, 2018

Automatic detection of sleep spindles with the use of STFT, EMD and DWT methods.
Neural Computing and Applications, 2018

Automatic sleep staging based on SVD, VMD, HHT and morphological features of single-lead ECG signal.
Expert Syst. Appl., 2018

2017
A new approach to eliminating EOG artifacts from the sleep EEG signals for the automatic sleep stage classification.
Neural Computing and Applications, 2017

Pre-determination of OSA degree using morphological features of the ECG signal.
Expert Syst. Appl., 2017

Effect of the Hilbert-Huang transform method on sleep staging.
Proceedings of the 25th Signal Processing and Communications Applications Conference, 2017

2016
Elimination of EMG artifacts from EEG signal in sleep staging.
Proceedings of the 24th Signal Processing and Communication Application Conference, 2016

2011
Sleep spindles recognition system based on time and frequency domain features.
Expert Syst. Appl., 2011

2010
Efficient sleep stage recognition system based on EEG signal using k-means clustering based feature weighting.
Expert Syst. Appl., 2010

Multi-class f-score feature selection approach to classification of obstructive sleep apnea syndrome.
Expert Syst. Appl., 2010

2008
A New Approach to Diagnosing of Importance Degree of Obstructive Sleep Apnea Syndrome: Pairwise AIRS and Fuzzy-AIRS Classifiers.
J. Medical Systems, 2008

Pairwise ANFIS Approach to Determining the Disorder Degree of Obstructive Sleep Apnea Syndrome.
J. Medical Systems, 2008

Comparison of Different Classifier Algorithms on the Automated Detection of Obstructive Sleep Apnea Syndrome.
J. Medical Systems, 2008

New Data Pre-processing on Assessing of Obstructive Sleep Apnea Syndrome: Line Based Normalization Method (LBNM).
Proceedings of the Advanced Intelligent Computing Theories and Applications. With Aspects of Contemporary Intelligent Computing Techniques, 2008


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