Question

Detecting abnormality in heart dynamics from multifractal analysis of ecg signals

Answer 1

The complexity of many physiological rhythms originate from the underlying complex nonlinear dynamical processes1,2,3,4,5,6,7. The various levels of this complexity and their variations, if properly discerned, will be useful in understanding the abnormalities that lead to many pathological cases8,9,10. A mathematical representation of the complexity using dynamical equations is most often not realizable due to the many interacting variables and uncertain parameters involved11,12. Hence the only possibility to study the dynamics in such situations to is to rely on information that can be deciphered from signals obtained from these systems13,14,15. Over the last few decades, several such physiological signals like EEG, ECG, fMRI etc have been subjected to different techniques available under the broad area of nonlinear time series analysis13,16,17.