GenerateFeatures: Generate new features from raw data for a given time window

In Javad-mun/Beap: Contains the functions used in the Beap lab for physical activity analysis

Description

Generate new features from raw data for a given time window

Usage

GenerateFeatures(raw_df, x_axis_column = 1, y_axis_column = 2,
  z_axis_column = 3, window_size_sec = 1, overlap_sec = 0,
  frequency = 30)

Arguments

raw_df	a dataframe which has at least three coluns, x_axis, y_axis, z_axis
x_axis_column	column number of x axis or
y_axis_column	column number of y axis or
z_axis_column	column number of z axis or
window_size_sec	windows size in second
frequency	sampling frequency

Value

new_features a dataset contaning generated features

Examples

## Not run: 
# load a sample dataset
library(activityCounts)
load("sampleXYZ")
sampling_freq <- 100

# prepare the dataset by setting proper column names
raw_df <- sampleXYZ %>% rename("x_axis" = accelerometer_X,
 "y_axis" = accelerometer_Y, "z_axis" = accelerometer_Z)

# consider a one second window
window_size_sec <- 1

# generate new features
GenerateFeatures(raw_df = raw_df, window_size_sec = window_size_sec, frequency = sampling_freq)

## End(Not run)

Javad-mun/Beap documentation built on July 22, 2020, 3:11 p.m.