CodeBook.txt

Feature Selection 
=================
Calculations for the underlying data (input to this study) was calculated as follows:

	The features selected for this database come from the accelerometer and gyroscope 3-axial raw signals tAcc-XYZ and tGyro-XYZ. These time domain signals (prefix 't' to denote time) were captured at a constant rate of 50 Hz. Then they were filtered using a median filter and a 3rd order low pass Butterworth filter with a corner frequency of 20 Hz to remove noise. Similarly, the acceleration signal was then separated into body and gravity acceleration signals (tBodyAcc-XYZ and tGravityAcc-XYZ) using another low pass Butterworth filter with a corner frequency of 0.3 Hz. 

	Subsequently, the body linear acceleration and angular velocity were derived in time to obtain Jerk signals (tBodyAccJerk-XYZ and tBodyGyroJerk-XYZ). Also the magnitude of these three-dimensional signals were calculated using the Euclidean norm (tBodyAccMag, tGravityAccMag, tBodyAccJerkMag, tBodyGyroMag, tBodyGyroJerkMag). 

	Finally a Fast Fourier Transform (FFT) was applied to some of these signals producing fBodyAcc-XYZ, fBodyAccJerk-XYZ, fBodyGyro-XYZ, fBodyAccJerkMag, fBodyGyroMag, fBodyGyroJerkMag. (Note the 'f' to indicate frequency domain signals). 

	Additional details for the underlying data is provided in Readme.txt

The features selected for this study were extracted from the 3-axial -XYZ mean and std data. Extracted data appear in tidy_mstr_df.csv.

tBodyAcc-mean()-XYZ
tBodyAcc-std()-XYZ
tGravityAcc-mean()-XYZ
tGravityAcc-std()-XYZ
tBodyAccJerk-mean()-XYZ
tBodyAccJerk-std()-XYZ
tBodyGyro-mean()-XYZ
tBodyGyro-std()-XYZ
tBodyGyroJerk-mean()-XYZ
tBodyGyroJerk-std()-XYZ
fBodyAcc-mean()-XYZ
fBodyAcc-std()-XYZ
fBodyAccJerk-mean()-XYZ
fBodyAccJerk-std()-XYZ
fBodyGyro-mean()-XYZ
fBodyGyro-std()-XYZ


Additional vectors were obtained by calculating summariziing means for the mean and standard deviations for each subject and activity. This results in a mean of means or a mean of std for each subject/activity group. Results appear in tidy_mstr_means.csv.

subject
activity
mean_of(tBodyAcc-mean()-XYZ)
mean_of(tBodyAcc-std()-XYZ)
mean_of(tGravityAcc-mean()-XYZ)
mean_of(tGravityAcc-std()-XYZ)
mean_of(tBodyAccJerk-mean()-XYZ)
mean_of(tBodyAccJerk-std()-XYZ)
mean_of(tBodyGyro-mean()-XYZ)
mean_of(tBodyGyro-std()-XYZ)
mean_of(tBodyGyroJerk-mean()-XYZ)
mean_of(tBodyGyroJerk-std()-XYZ)
mean_of(fBodyAcc-mean()-XYZ)
mean_of(fBodyAcc-std()-XYZ)
mean_of(fBodyAccJerk-mean()-XYZ)
mean_of(fBodyAccJerk-std()-XYZ)
mean_of(fBodyGyro-mean()-XYZ)
mean_of(fBodyGyro-std()-XYZ)