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CodeBook of Tidy Data

This code file contains the description of the variables of the tidy data.

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 meanFreq(): Weighted average of the frequency components to obtain a mean frequency

The details of all features present in the tidy data are as given below. The values in the tidy data fields mean_* are the mean of the values for each combination of subject and activity.

  • subject: Subject of the experiment Values 1 to 30
  • activity : Activity performed by the subject: Values 1 WALKING 2 WALKING_UPSTAIRS 3 WALKING_DOWNSTAIRS 4 SITTING 5 STANDING 6 LAYING
  • mean_tBodyAcc-mean()-Y
  • mean_tBodyAcc-mean()-X
  • mean_tBodyAcc-mean()-Z
  • mean_tBodyAcc-std()-X
  • mean_tBodyAcc-std()-Y
  • mean_tBodyAcc-std()-Z
  • mean_tGravityAcc-mean()-X
  • mean_tGravityAcc-mean()-Y
  • mean_tGravityAcc-mean()-Z
  • mean_tGravityAcc-std()-X
  • mean_tGravityAcc-std()-Y
  • mean_tGravityAcc-std()-Z
  • mean_tBodyAccJerk-mean()-X
  • mean_tBodyAccJerk-mean()-Y
  • mean_tBodyAccJerk-mean()-Z
  • mean_tBodyAccJerk-std()-X
  • mean_tBodyAccJerk-std()-Y
  • mean_tBodyAccJerk-std()-Z
  • mean_tBodyGyro-mean()-X
  • mean_tBodyGyro-mean()-Y
  • mean_tBodyGyro-mean()-Z
  • mean_tBodyGyro-std()-X
  • mean_tBodyGyro-std()-Y
  • mean_tBodyGyro-std()-Z
  • mean_tBodyGyroJerk-mean()-X
  • mean_tBodyGyroJerk-mean()-Y
  • mean_tBodyGyroJerk-mean()-Z
  • mean_tBodyGyroJerk-std()-X
  • mean_tBodyGyroJerk-std()-Y
  • mean_tBodyGyroJerk-std()-Z
  • mean_tBodyAccMag-mean()
  • mean_tBodyAccMag-std()
  • mean_tGravityAccMag-mean()
  • mean_tGravityAccMag-std()
  • mean_tBodyAccJerkMag-mean()
  • mean_tBodyAccJerkMag-std()
  • mean_tBodyGyroMag-mean()
  • mean_tBodyGyroMag-std()
  • mean_tBodyGyroJerkMag-mean()
  • mean_tBodyGyroJerkMag-std()
  • mean_fBodyAcc-mean()-X
  • mean_fBodyAcc-mean()-Y
  • mean_fBodyAcc-mean()-Z
  • mean_fBodyAcc-std()-X
  • mean_fBodyAcc-std()-Y
  • mean_fBodyAcc-std()-Z
  • mean_fBodyAcc-meanFreq()-X
  • mean_fBodyAcc-meanFreq()-Y
  • mean_fBodyAcc-meanFreq()-Z
  • mean_fBodyAccJerk-mean()-X
  • mean_fBodyAccJerk-mean()-Y
  • mean_fBodyAccJerk-mean()-Z
  • mean_fBodyAccJerk-std()-X
  • mean_fBodyAccJerk-std()-Y
  • mean_fBodyAccJerk-std()-Z
  • mean_fBodyAccJerk-meanFreq()-X
  • mean_fBodyAccJerk-meanFreq()-Y
  • mean_fBodyAccJerk-meanFreq()-Z
  • mean_fBodyGyro-mean()-X
  • mean_fBodyGyro-mean()-Y
  • mean_fBodyGyro-mean()-Z
  • mean_fBodyGyro-std()-X
  • mean_fBodyGyro-std()-Y
  • mean_fBodyGyro-std()-Z
  • mean_fBodyGyro-meanFreq()-X
  • mean_fBodyGyro-meanFreq()-Y
  • mean_fBodyGyro-meanFreq()-Z
  • mean_fBodyAccMag-mean()
  • mean_fBodyAccMag-std()
  • mean_fBodyAccMag-meanFreq()
  • mean_fBodyBodyAccJerkMag-mean()
  • mean_fBodyBodyAccJerkMag-std()
  • mean_fBodyBodyAccJerkMag-meanFreq()
  • mean_fBodyBodyGyroMag-mean()
  • mean_fBodyBodyGyroMag-std()
  • mean_fBodyBodyGyroMag-meanFreq()
  • mean_fBodyBodyGyroJerkMag-mean()
  • mean_fBodyBodyGyroJerkMag-std()
  • mean_fBodyBodyGyroJerkMag-meanFreq()