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Licensed Unlicensed Requires Authentication Published by De Gruyter January 29, 2016

Biosignal processing

  • Jens Haueisen EMAIL logo and Tilmann Sander-Thömmes

Corresponding author: Jens Haueisen, Technical University of Ilmenau, Institute of Biomedical Engineering and Informatics, Gustav-Kirchhoff-Strasse 2, 98693 Ilmenau, Germany, E-mail:

References

[1] Arjunan SP, Kumar DK, Jayadeva J. Fractal and twin SVM-based handgrip recognition for healthy subjects and trans-radial amputees using myoelectric signal. Biomed Eng-Biomed Tech 2016; 61: 87–94.10.1515/bmt-2014-0134Search in Google Scholar PubMed

[2] Cervigón R, Moreno J, García-Quintanilla J, Pérez-Villacastín J, Castells F. Entropy at the right atrium as a predictor of atrial fibrillation recurrence outcome after pulmonary vein ablation. Biomed Eng-Biomed Tech 2016; 61: 29–36.10.1515/bmt-2014-0172Search in Google Scholar PubMed

[3] Hasan MA, Abbott D. A review of beat-to-beat vectorcardiographic (VCG) parameters for analyzing repolarization variability in ECG signals. Biomed Eng-Biomed Tech 2016; 61: 3–17.Search in Google Scholar

[4] Khorasani A, Daliri MR, Pooyan M. Recognition of amyotrophic lateral sclerosis disease using factorial hidden Markov model. Biomed Eng-Biomed Tech 2016; 61: 119–126.10.1515/bmt-2014-0089Search in Google Scholar PubMed

[5] Lenis G, Pilia N, Oesterlein T, Luik A, Schmitt C, Dössel O. P wave detection and delineation in the ECG based on the phase free stationary wavelet transform and using intracardiac atrial electrograms as reference. Biomed Eng-Biomed Tech 2016; 61: 37–56.10.1515/bmt-2014-0161Search in Google Scholar PubMed

[6] McInturff SP, Buchser WJ. A portable device for recording evoked potentials, optimized for pattern ERG. Biomed Eng-Biomed Tech 2016; 61: 69–76.Search in Google Scholar

[7] Onorati F, Mainardi LT, Sirca F, Russo V, Barbieri R. Nonlinear analysis of pupillary dynamics. Biomed Eng-Biomed Tech 2016; 61: 95–106.10.1515/bmt-2015-0027Search in Google Scholar PubMed

[8] Ortigosa N, Fernández C, Galbis A, Cano Ó. Classification of persistent and long-standing persistent atrial fibrillation by means of surface electrocardiograms. Biomed Eng-Biomed Tech 2016; 61: 19–27.10.1515/bmt-2014-0154Search in Google Scholar PubMed

[9] Pflugradt M, Mann S, Tigges T, Görnig M, Orglmeister R. Multi-modal signal acquisition using a synchronized wireless body sensor network in geriatric patients. Biomed Eng-Biomed Tech 2016; 61: 57–68.10.1515/bmt-2014-0178Search in Google Scholar PubMed

[10] Steyrl D, Scherer R, Faller J, Müller-Putz GR. Random forests in non-invasive sensorimotor rhythm brain-computer interfaces: a practical and convenient non-linear classifier. Biomed Eng-Biomed Tech 2016; 61: 77–86.10.1515/bmt-2014-0117Search in Google Scholar PubMed

[11] Vondra V, Jurak P, Viscor I, et al. A multichannel bioimpedance monitor for full-body blood flow monitoring. Biomed Eng-Biomed Tech 2016; 61: 107–118.10.1515/bmt-2014-0108Search in Google Scholar PubMed

[12] Xu F, Yan G, Zhao K, Lu L, Wang Z, Gao J. Quantifying the complexity of human colonic pressure signals using an entropy measure. Biomed Eng-Biomed Tech 2016; 61: 127–132.10.1515/bmt-2015-0026Search in Google Scholar PubMed

Published Online: 2016-1-29
Published in Print: 2016-2-1

©2016 by De Gruyter

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