Data Collection Description
This data set analysis was in support of a human activity recognition project (see footnote 1).
Data was collected from a group of 30 volunteers wearing a smartphone on their waist while performing six activities (e.g. walking, standing). The accelerometer and gyroscope in the smartphone was used to collect measurements. All measurements are standardized and bounded within [-1,1].
Variables
Subject : the code number for the 30 volunteers
Activity : the activities the volunteers performed (walking, walking upstairs, walking downstairs, sitting, standing, laying)
tBodyAcc-mean()-X : these variables are the mean values for body accelerometer measurements on 3 axis
tBodyAcc-mean()-Y
tBodyAcc-mean()-Z
tBodyAcc-std()-X : these variables are standard deviation values for body accelerometer measurements on 3 axis
tBodyAcc-std()-Y
tBodyAcc-std()-Z
tGravityAcc-mean()-X : these variables are mean values for gravity accelerometer measurements on 3 axis
tGravityAcc-mean()-Y
tGravityAcc-mean()-Z
tGravityAcc-std()-X : these variables are standard deviation values for gravity accelerometer measurements on 3 axis
tGravityAcc-std()-Y
tGravityAcc-std()-Z
tBodyAccJerk-mean()-X : these variables are mean values for body accelerometer jerk measurements on 3 axis
tBodyAccJerk-mean()-Y
tBodyAccJerk-mean()-Z
tBodyAccJerk-std()-X : these variables are standard deviation values for body accelerometer jerk measurements
tBodyAccJerk-std()-Y
tBodyAccJerk-std()-Z
tBodyGyro-mean()-X : these variables are mean values for body gyroscope measurements on 3 axis
tBodyGyro-mean()-Y
tBodyGyro-mean()-Z
tBodyGyro-std()-X : these variables are standard deviation values for body gyroscope measurements on 3 axis
tBodyGyro-std()-Y
tBodyGyro-std()-Z
tBodyGyroJerk-mean()-X : these variables are mean values for body gyroscope jerk measurements on 3 axis
tBodyGyroJerk-mean()-Y
tBodyGyroJerk-mean()-Z
tBodyGyroJerk-std()-X : these variables are standard deviation values for body gyroscope jerk measurements on 3 axis
tBodyGyroJerk-std()-Y
tBodyGyroJerk-std()-Z
tBodyAccMag-mean() : the mean of the body accelerometer magnitude
tBodyAccMag-std() : the standard deviation of the body accelerometer magnitude
tBodyAccJerkMag-mean() : the mean of the body accelerometer jerk magnitude
tBodyAccJerkMag-std() : the standard deviation of the body accelerometer jerk magnitude
tBodyGyroMag-mean() : the mean of the body gyroscope magnitude
tBodyGyroMag-std() : the standard deviation of the body gyroscope magnitude
tBodyGyroJerkMag-mean() : the mean of the body gyroscope jerk magnitude
tBodyGyroJerkMag-std() : the standard deviation of the body gyroscope jerk magnitude
fBodyAcc-mean()-X : the fast fourier transform of the body accelerometer mean for 3 axis
fBodyAcc-mean()-Y
fBodyAcc-mean()-Z
fBodyAcc-std()-X : the fast fourier transform of the body accelerometer standard deviation for 3 axis
fBodyAcc-std()-Y
fBodyAcc-std()-Z
fBodyAccJerk-mean()-X : the fast fourier transform of the body accelerometer jerk mean for 3 axis
fBodyAccJerk-mean()-Y
fBodyAccJerk-mean()-Z
fBodyAccJerk-std()-X : the fast fourier transform of the body accelerometer jerk standard deviation for 3 axis
fBodyAccJerk-std()-Y
fBodyAccJerk-std()-Z
fBodyGyro-mean()-X : the fast fourier transform of the body gyroscope mean for 3 axis
fBodyGyro-mean()-Y
fBodyGyro-mean()-Z
fBodyGyro-std()-X : the fast fourier transform of the body gyroscope standard deviation for 3 axis
fBodyGyro-std()-Y
fBodyGyro-std()-Z
fBodyAccMag-mean() : the fast fourier transform of the body accelerometer magnitude mean
fBodyAccMag-std() : the fast fourier transform of the body accelerometer magnitude standard deviation
fBodyBodyGyroMag-mean() : the fast fourier transform of the body gyroscope magnitude mean
fBodyBodyGyroMag-std() : the fast fourier transform of the body gyroscope magnitude standard deviation
fBodyBodyGyroJerkMag-mean() : the fast fourier transform of the body gyroscope jerk magnitude mean
fBodyBodyGyroJerkMag-std() : the fast fourier transform of the body gyroscope jerk magnitude standard deviation
Footnote
[1] Davide Anguita, Alessandro Ghio, Luca Oneto, Xavier Parra and Jorge L. Reyes-Ortiz. Human Activity Recognition on Smartphones using a Multiclass Hardware-Friendly Support Vector Machine. International Workshop of Ambient Assisted Living (IWAAL 2012). Vitoria-Gasteiz, Spain. Dec 2012