codeBook

# Data Source

Description of the Experiement Generating the Data - The experiments have been carried out with a group of 30 volunteers within an age bracket of 19-48 years. Each person performed six activities (WALKING, WALKING_UPSTAIRS, WALKING_DOWNSTAIRS, SITTING, STANDING, LAYING) wearing a smartphone (Samsung Galaxy S II) on the waist. Using its embedded accelerometer and gyroscope, we captured 3-axial linear acceleration and 3-axial angular velocity at a constant rate of 50Hz. The experiments have been video-recorded to label the data manually. The obtained dataset has been randomly partitioned into two sets, where 70% of the volunteers was selected for generating the training data and 30% the test data.

The sensor signals (accelerometer and gyroscope) were pre-processed by applying noise filters and then sampled in fixed-width sliding windows of 2.56 sec and 50% overlap (128 readings/window). The sensor acceleration signal, which has gravitational and body motion components, was separated using a Butterworth low-pass filter into body acceleration and gravity. The gravitational force is assumed to have only low frequency components, therefore a filter with 0.3 Hz cutoff frequency was used. From each window, a vector of features was obtained by calculating variables from the time and frequency domain. See 'features_info.txt' for more details.

# Code Book

packages : Combines necessary data tables/packages to extract information
datazip : Downloads zipfile and creates file path for data
activityLabels : Reads file and creates columns for activities
features : Reads file and creates columns for features
featuresWanted : Organizes features
measurements : Organizes features / feature labels
train : Reads table regarding train and sets names
trainActivities : Creates column name for activities and pulls data from table
trainSubjects : Creates column name for activities and pulls data from table
test : Organizes columns by test subjects and activities
combined : Organizes train and test columns, melts data and produces requested formats of data: mean, average, etc.