bandlimited_interp: Apply a bandlimited interpolation filter to the signal to...

In MIMSunit: Algorithm to Compute Monitor Independent Movement Summary Unit (MIMS-Unit)

Apply a bandlimited interpolation filter to the signal to change the sampling rate

Description

bandlimited_interp function takes a multi-channel signal and applies a bandlimited interpolation filter to the signal to change its sampling rate.

Usage

bandlimited_interp(df, orig_sr, new_sr)

Arguments

df	dataframe. The input multi-channel signal. The first column is timestamps in POSXlct format. The rest columns are signal values.
orig_sr	number. Sampling rate in Hz of the input signal.
new_sr	number. The desired sampling rate in Hz of the output signal.

Details

This function filters the input multi-channel signal by applying a bandlimited interpolation filter. See resample for the underlying implementation.

Value

dataframe. Filtered signal.

How is it used in MIMS-unit algorithm?

This function is not used in the released version of MIMS-unit algorithm, but has once been considered to be used after extrapolation to harmonize sampling rate before filtering. But in the end, we decided to use linear interpolation before extrapolation to increase the sampling rate to 100Hz, so this method is no longer needed.

See Also

Other filtering functions: iir()

Examples

  # Use sample data
  df = sample_raw_accel_data

  # View input
  illustrate_signal(df, plot_maxed_out_line = FALSE)

  # Apply filtering that uses the same setting as in MIMSunit algorithm
  output = bandlimited_interp(df, orig_sr=80, new_sr=30)

  # View output
  illustrate_signal(output, plot_maxed_out_line = FALSE)

MIMSunit documentation built on June 21, 2022, 5:06 p.m.