Abstract
This paper presents the development of the time-frequency technique, known as the Hilbert–Huang Transform (HHT) into a real-time analysis environment. By looking at the intrinsic elements of the transform we develop a novel strategy for computationally efficient and accurate real-time analysis. Test signals, as well as analysis on EEG and ECG signals for detecting relevant features are presented in support of our methodology. Additional unique insight is shown in some of the intrinsic elements of the algorithm, including some known errors in the use of the popular cubic spline method. Discussions of the primary design considerations and trade-offs are described throughout, aiming at a rounded view of what a real-time HHT implementation involves.
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