Apply a Butterworth filter to numeric data — butterworthFilter • PhysioMoCap

Designs a Butterworth IIR filter and applies it using zero-phase filtering (forward-backward) to avoid phase distortion.

Usage

butterworthFilter(
  x,
  cutoff,
  sampling_rate,
  type = c("lowpass", "highpass", "bandpass", "bandstop"),
  order = 4
)

Arguments

x: A numeric vector or matrix (time x channels).
cutoff: Cutoff frequency in Hz. A single value for "lowpass" or "highpass"; a length-2 vector c(low, high) for "bandpass" or "bandstop".
sampling_rate: Sampling rate in Hz.
type: Filter type: "lowpass", "highpass", "bandpass", or "bandstop".
order: Filter order (default: 4).

Value

Filtered data with the same dimensions as x.

Details

Requires the signal package. NAs in the input are temporarily interpolated before filtering and restored afterward.

References

Butterworth S (1930). "On the Theory of Filter Amplifiers." Wireless Engineer, 7, 536-541.

See also

filterSignals() for filtering PhysioExperiment objects, savgolFilter() for Savitzky-Golay polynomial smoothing.

Examples

if (requireNamespace("signal", quietly = TRUE)) {
  x <- sin(2 * pi * 2 * seq(0, 1, length.out = 120)) + rnorm(120, 0, 0.1)
  xf <- butterworthFilter(x, cutoff = 6, sampling_rate = 120)
  length(xf)
}
#> [1] 120