A nonlinear model was developed to generate realistic 24-hour ECG, blood pressure, and respiratory signals with linear and nonlinear clinical characteristics to facilitate testing of algorithms.
A novel nonlinear computational model successfully generates realistic 24-hour ECG, BP, and respiratory signals to facilitate the testing of signal processing algorithms.
A nonlinear model for generating lifelike humaia ECG, blood pressure and respiratory signals is described. Each cycle of the model corresponds to one heart beat and the signals therefore exhibit beat-to-beat fluctuations by driving the model with a sequence of RR intervals. By wing a modified version of entry no.201 of the CinC 2002 24-hour RR interval generator challenge. (such that the user can spec realistic short and long range blood pressure fluctuations are shown to result. Together with seeded RR interval dynamics, the morphology of the signals corn be fully specified by three parameters per feature and therefore a large range of drzerent (deteiministic) signals can be generated with fully known characteristics, to facilitate the tesfing of signal processing algorithms. Open source C, Matlab and Java programs for generating the model are available from Physionet.
Clifford et al. (Wed,) conducted a other in ECG, blood pressure, and respiratory signal simulation. Nonlinear model for signal generation was evaluated. A nonlinear model was developed to generate realistic 24-hour ECG, blood pressure, and respiratory signals with linear and nonlinear clinical characteristics to facilitate testing of algorithms.
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