A Review on the Applications of Time‐Frequency Methods in ECG Analysis

Abstract

The joint time-frequency analysis method represents a signal in both time and frequency. Thus, it provides more information compared to other one-dimensional methods. Several researchers recently used time-frequency methods such as the wavelet transform, short-time Fourier transform, empirical mode decomposition and reported impressive results in various electrophysiological studies. The current review provides comprehensive knowledge about different time-frequency methods and their applications in various ECG-based analyses. Typical applications include ECG signal denoising, arrhythmia detection, sleep apnea detection, biometric identification, emotion detection, and driver drowsiness detection. The paper also discusses the limitations of these methods. The review will form a reference for future researchers willing to conduct research in the same field.

Comparison of Supervised Learning Algorithms for Quality Assessment of Wearable Electrocardiograms With Paroxysmal Atrial Fibrillation

“…Given that the Morlet function (i.e., a complex exponential function multiplied by a Gaussian window) is characterized by equal variance in time and frequency and has been used in a broad variety of ECG-based applications [12], [41], [42], it was selected as mother wavelet. Additionally, the number of wavelet scales was established to 48 voices per octave to achieve sufficient time resolution in the low frequency range, where physiological information is mainly concentrated for a clean ECG signal segment [43]. Finally, a Jet colormap of 7 bits was employed to draw the wavelet scalogram.…”

Scaling effectivity in manifold methodologies to detect driver’s fatigueness and drowsiness state

“…Hence, a question arises that why one should see both of these terms from different angle although both these terms eventually lead to an accident. The answer for this question is that modernized vehicles are currently evolving with sophisticated road safety features where the behavior of the driver is subjected to analysis while the outcome of analysis will foretell the probability of drowsiness or fatigueness state of driver followed by alarming them to prevent accidents [5]- [12]. Although, these forms of road safety features are yet not available in all the vehicles and only few proportions of vehicles have started using it that falls under the category of premium vehicles.…”