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Extract F wave features from ECG

Source: R/fwave.R
extract_f_waves.Rd

This function analyzes F waves in an ECG signal, extracting various characteristics.

Usage

extract_f_waves(
  object,
  lead = NULL,
  qrs_method = "adaptive_svd",
  f_characteristics = "amplitude",
  verbose = TRUE,
  .force_all = FALSE,
  ...
)

Arguments

object

An object of class egm or of subclass ecg

lead

Optional. A character string specifying the lead to analyze. If NULL (default), all available surface leads will be processed.

qrs_method

Method for ventricular signal removal. Default is "adaptive_svd" for adaptive singular value decomposition.

f_characteristics

Vector of characteristics to analyze from ECG signal. Options: "amplitude", "approximate_entropy", "dominant_frequency". Please see calculate_approximate_entropy() and calculate_dominant_frequency() for more details.

verbose

Logical. If TRUE, print information about which leads will be analyzed. Default is TRUE.

.force_all

Logical. If FALSE (default), only process surface ECG leads. If TRUE, process all available leads. This parameter is ignored if the object is of class 'ecg', in which case all leads are processed.

...

Additional arguments passed to methods

Value

A list containing F wave features for each processed lead

References

Park, Junbeom, Chungkeun Lee, Eran Leshem, Ira Blau, Sungsoo Kim, Jung Myung Lee, Jung-A Hwang, Byung-il Choi, Moon-Hyoung Lee, and Hye Jin Hwang. "Early Differentiation of Long-Standing Persistent Atrial Fibrillation Using the Characteristics of Fibrillatory Waves in Surface ECG Multi-Leads." Scientific Reports 9 (February 26, 2019): 2746. https://doi.org/10.1038/s41598-019-38928-6.

Hyvarinen, A., and Oja, E. (2000). Independent component analysis: algorithms and applications. Neural Networks, 13(4-5), 411-430.