The following data set description is reproduced from the Human Activity Recognition Using Smartphones Data Set data set description. Please refer to this page for the original data set descriptions, citation information and relevant literature.
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.
The prefixes 't' and 'f' denote features in the time-domain and frequency-domain respectively. The features are generated from 3-axial accelerometer and gyroscope measurements (x, y and z components).
See the file features_info.txt in the data set folder for more detailed descriptions of the features and the signal processing applied to these measurements.
The following is a description of the transformations applied to the original dataset:
- The train and test sets were combined by concatenating the data sets row-wise using
rbind. greplwas used to find measurements of mean and standard deviation. Only these measurements were included in the transformed data set.- Column names were standardized and made lowercase.
- Subject id and activity performed were added as columns to the combinded dataset.
- An independent dataset was created with the average of each variable for each activity and each subject. The variable names and descriptions apply to both data sets.
| Feature name | Description |
|---|---|
| activity | activity subject performed |
| subject | subject id |
| Feature name | Description |
|---|---|
| tbodyacc.mean.x | mean body acceleration in the x direction |
| tbodyacc.mean.y | mean body acceleration in the y direction |
| tbodyacc.mean.z | mean body acceleration in the z direction |
| tbodyacc.std.x | standard deviation of body acceleration in the x direction |
| tbodyacc.std.y | standard deviation of body acceleration in the y direction |
| tbodyacc.std.z | standard deviation of body acceleration in the z direction |
| tgravityacc.mean.x | mean body acceleration time in the x direction |
| tgravityacc.mean.y | mean gravity acceleration time in the y direction |
| tgravityacc.mean.z | mean gravity acceleration time in the z direction |
| tgravityacc.std.x | standard deviation of gravity acceleration time in the x direction |
| tgravityacc.std.y | standard deviation of gravity acceleration time in the x direction |
| tgravityacc.std.z | standard deviation of gravity acceleration time in the z direction |
| tbodyaccjerk.mean.x | mean body acceleration jerk time in the x direction |
| tbodyaccjerk.mean.y | mean body acceleration jerk time in the y direction |
| tbodyaccjerk.mean.z | mean body acceleration jerk time in the z direction |
| tbodyaccjerk.std.x | standard deviation of body acceleration jerk time in the x direction |
| tbodyaccjerk.std.y | standard deviation of body acceleration jerk time in the y direction |
| tbodyaccjerk.std.z | standard deviation of body acceleration jerk time in the z direction |
| tbodygyro.mean.x | mean body gyroscope signal in the x direction |
| tbodygyro.mean.y | mean body gyroscope signal in the y direction |
| tbodygyro.mean.z | mean body gyroscope signal in the z direction |
| tbodygyro.std.x | std of body gyroscope signal in the x direction |
| tbodygyro.std.y | std of body gyroscope signal in the y direction |
| tbodygyro.std.z | std of body gyroscope signal in the z direction |
| tbodygyrojerk.mean.x | mean gyroscopic jerk time for body in the x direction |
| tbodygyrojerk.mean.y | mean gyroscopic jerk time for body in the y direction |
| tbodygyrojerk.mean.z | mean gyroscopic jerk time for body in the z direction |
| tbodygyrojerk.std.x | standard deviation of gyroscopic jerk time for body in the x direction |
| tbodygyrojerk.std.y | standard deviation of gyroscopic jerk time for body in the x direction |
| tbodygyrojerk.std.z | standard deviation of gyroscopic jerk time for body in the x direction |
| tbodyaccmag.mean | mean magnitude of body acceleration |
| tbodyaccmag.std | standard deviation of magnitude of body acceleration |
| tgravityaccmag.mean | mean magnitude of gravity acceleration |
| tgravityaccmag.std | standard deviation of magnitude of gravity acceleration |
| tbodyaccjerkmag.mean | mean magnitude of body acceleration jerk |
| tbodyaccjerkmag.std | standard deviation of magnitude of body acceleration jerk |
| tbodygyromag.mean | mean magnitude of gyroscopic body acceleration |
| tbodygyromag.std | standard deviation of magnitude of gyroscopic body acceleration |
| tbodygyrojerkmag.mean | mean magnitude of gyroscopic body acceleration jerk |
| tbodygyrojerkmag.std | standard deviation of magnitude of gyroscopic body acceleration |
| Feature name | Description |
|---|---|
| fbodyacc.mean.x | mean body acceleration time in the x direction |
| fbodyacc.mean.y | mean body acceleration time in the y direction |
| fbodyacc.mean.z | mean body acceleration time in the z direction |
| fbodyacc.std.x | standard deviation of body acceleration time in the x direction |
| fbodyacc.std.y | standard deviation of body acceleration time in the y direction |
| fbodyacc.std.z | standard deviation of body acceleration time in the z direction |
| fbodyaccjerk.mean.x | mean body acceleration jerk time in the x direction |
| fbodyaccjerk.mean.y | mean body acceleration jerk time in the y direction |
| fbodyaccjerk.mean.z | mean body acceleration jerk time in the z direction |
| fbodyaccjerk.std.x | standard deviation of body acceleration jerk time in the x direction |
| fbodyaccjerk.std.y | standard deviation of body acceleration jerk time in the y direction |
| fbodyaccjerk.std.z | standard deviation of body acceleration jerk time in the z direction |
| fbodygyro.mean.x | mean body gyroscope signal in the x direction |
| fbodygyro.mean.y | mean body gyroscope signal in the y direction |
| fbodygyro.mean.z | mean body gyroscope signal in the z direction |
| fbodygyro.std.x | std of body gyroscope signal in the x direction |
| fbodygyro.std.y | std of body gyroscope signal in the y direction |
| fbodygyro.std.z | std of body gyroscope signal in the z direction |
| fbodyaccmag.mean | mean magnitude of body acceleration |
| fbodyaccmag.std | standard deviation of magnitude of body acceleration |
| fbodyaccjerkmag.mean | mean magnitude of body acceleration jerk |
| fbodyaccjerkmag.std | standard deviation of magnitude of body acceleration jerk |
| fbodygyromag.mean | mean magnitude of gyroscopic body acceleration |
| fbodygyromag.std | standard deviation of magnitude of gyroscopic body acceleration |
| fbodygyrojerkmag.mean | mean magnitude of gyroscopic body acceleration jerk |
| fbodygyrojerkmag.std | standard deviation of magnitude of gyroscopic body acceleration |