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Code Book

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).

These signals were used to estimate variables of the feature vector for each pattern:
'-XYZ' is used to denote 3-axial signals in the X, Y and Z directions.

  • tBodyAcc-XYZ
  • tGravityAcc-XYZ
  • tBodyAccJerk-XYZ
  • tBodyGyro-XYZ
  • tBodyGyroJerk-XYZ
  • tBodyAccMag
  • tGravityAccMag
  • tBodyAccJerkMag
  • tBodyGyroMag
  • tBodyGyroJerkMag
  • fBodyAcc-XYZ
  • fBodyAccJerk-XYZ
  • fBodyGyro-XYZ
  • fBodyAccMag
  • fBodyAccJerkMag
  • fBodyGyroMag
  • fBodyGyroJerkMag

The set of variables that were estimated from these signals are:

mean(): Mean value
std(): Standard deviation

The tidy data set is a wide set with the average of each variable for each activity and each subject. Note that variables are normalized and bounded within [-1,1]. The complete listing of variables:

  • subject_id: subject id
  • activity: activity name
  • tBodyAcc-mean()-X : mean of tBodyAcc-mean()-X. The rest of the variables follows the same pattern.
  • tBodyAcc-mean()-Y
  • tBodyAcc-mean()-Z
  • tGravityAcc-mean()-X
  • tGravityAcc-mean()-Y
  • tGravityAcc-mean()-Z
  • tBodyAccJerk-mean()-X
  • tBodyAccJerk-mean()-Y
  • tBodyAccJerk-mean()-Z
  • tBodyGyro-mean()-X
  • tBodyGyro-mean()-Y
  • tBodyGyro-mean()-Z
  • tBodyGyroJerk-mean()-X
  • tBodyGyroJerk-mean()-Y
  • tBodyGyroJerk-mean()-Z
  • tBodyAccMag-mean()
  • tGravityAccMag-mean()
  • tBodyAccJerkMag-mean()
  • tBodyGyroMag-mean()
  • tBodyGyroJerkMag-mean()
  • fBodyAcc-mean()-X
  • fBodyAcc-mean()-Y
  • fBodyAcc-mean()-Z
  • fBodyAccJerk-mean()-X
  • fBodyAccJerk-mean()-Y
  • fBodyAccJerk-mean()-Z
  • fBodyGyro-mean()-X
  • fBodyGyro-mean()-Y
  • fBodyGyro-mean()-Z
  • fBodyAccMag-mean()
  • fBodyBodyAccJerkMag-mean()
  • fBodyBodyGyroMag-mean()
  • fBodyBodyGyroJerkMag-mean()
  • tBodyAcc-std()-X
  • tBodyAcc-std()-Y
  • tBodyAcc-std()-Z
  • tGravityAcc-std()-X
  • tGravityAcc-std()-Y
  • tGravityAcc-std()-Z
  • tBodyAccJerk-std()-X
  • tBodyAccJerk-std()-Y
  • tBodyAccJerk-std()-Z
  • tBodyGyro-std()-X
  • tBodyGyro-std()-Y
  • tBodyGyro-std()-Z
  • tBodyGyroJerk-std()-X
  • tBodyGyroJerk-std()-Y
  • tBodyGyroJerk-std()-Z
  • tBodyAccMag-std()
  • tGravityAccMag-std()
  • tBodyAccJerkMag-std()
  • tBodyGyroMag-std()
  • tBodyGyroJerkMag-std()
  • fBodyAcc-std()-X
  • fBodyAcc-std()-Y
  • fBodyAcc-std()-Z
  • fBodyAccJerk-std()-X
  • fBodyAccJerk-std()-Y
  • fBodyAccJerk-std()-Z
  • fBodyGyro-std()-X
  • fBodyGyro-std()-Y
  • fBodyGyro-std()-Z
  • fBodyAccMag-std()
  • fBodyBodyAccJerkMag-std()
  • fBodyBodyGyroMag-std()
  • fBodyBodyGyroJerkMag-std()