sum_up: Sum of multi-channel signal.

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

Sum of multi-channel signal.

Description

sum_up computes the sum up value for each sample (row) of a multi-channel signal.

Usage

sum_up(df, axes = NULL)

Arguments

df	dataframe. multi-channel signal, with the first column being the timestamp in POSXct format.
axes	numerical vector. Specify the column indices for each axis. When this value is NULL, the function assumes the axes are starting from column 2 to the end. Default is NULL.

Details

This function takes a dataframe of a multi-channel signal as input, and then computes the sum of each row and returns a transformed dataframe with two columns.

Value

dataframe. The transformed dataframe will have the same number of rows as input dataframe but only two columns, with the first being timestamps and second being the sum up values.

How is it used in MIMS-unit algorithm?

This function is used to combine MIMS-unit values on each axis into a single value after aggregating over each epoch using aggregate_for_mims.

See Also

vector_magnitude

Other transformation functions: compute_orientation(), vector_magnitude()

Examples

  # Use the first 10 rows of the sample data as an example
  df = sample_raw_accel_data[1:10,]
  df

  # By default, the function will assume columns starting from 2 to be axial
  # values.
  sum_up(df)

  # Or, you may specify the column indices yourself
  sum_up(df, axes=c(2,3,4))

  # Or, if you only want to consider x and y axes
  sum_up(df, axes=c(2,3))

  # Or, just return the chosen column
  sum_up(df, axes=c(2))

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