%Author: Hui Yang
%The Pennsylvania State University
%310 Leohard Building, University Park, PA
% If you find this toolbox useful, please cite the following paper:
%  H. Yang, S. T. S. Bukkapatnam, and R. Komanduri, “Spatiotemporal
% representation of cardiac Vectorcardiogram (VCG) signals,” Biomedical
% Engineering Online, Vol.11, No. 16, 2012,
% DOI: http://dx.doi.org/10.1186/1475-925X-11-16
%  G. Liu and H. Yang, “Multiscale adaptive basis function modeling
% of spatiotemporal cardiac electrical signals,” IEEE Journal of Biomedical
% and Health Informatics, Vol. 17, No. 2, p484-492, 2013,
% DOI: http://dx.doi.org/10.1109/JBHI.2013.2243842
% Data: ecgdata1.mat or ecgdata2.mat
% The sample data include the ensembles of 12-lead ECGs and 3-lead VCGs
% Heartbeat cycle lengths can be kept original or resampled to the same.
% The original heartbeat cycle lengths (i.e., RR intervals) are stored in
Hui Yang (2020). Ensembles and waterfall visualization of ECG heart beats (https://www.mathworks.com/matlabcentral/fileexchange/77993-ensembles-and-waterfall-visualization-of-ecg-heart-beats), MATLAB Central File Exchange. Retrieved .
Liu, Gang, and Hui Yang. “Multiscale Adaptive Basis Function Modeling of Spatiotemporal Vectorcardiogram Signals.” IEEE Journal of Biomedical and Health Informatics, vol. 17, no. 2, Institute of Electrical and Electronics Engineers (IEEE), Mar. 2013, pp. 484–92, doi:10.1109/jbhi.2013.2243842.
Yang, Hui, et al. “Spatiotemporal Representation of Cardiac Vectorcardiogram (VCG) Signals.” BioMedical Engineering OnLine, vol. 11, no. 1, Springer Science and Business Media LLC, 2012, p. 16, doi:10.1186/1475-925x-11-16.
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