-
Notifications
You must be signed in to change notification settings - Fork 0
/
Copy pathcodebook.txt
96 lines (89 loc) · 3.29 KB
/
codebook.txt
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
The following data description is taken from the original codebook accompanying the 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.
From these signals, mean and standard deviation were obtained. Lastly, a mean of all values for each possible combination of subject and activity was calculated.
The dataset contains the following data:
activity - name of the activity performed
subject - subject performing the activity, 1 through 30
tBodyAcc.mean...X
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
fBodyAcc.meanFreq...X
fBodyAcc.meanFreq...Y
fBodyAcc.meanFreq...Z
fBodyAccJerk.mean...X
fBodyAccJerk.mean...Y
fBodyAccJerk.mean...Z
fBodyAccJerk.meanFreq...X
fBodyAccJerk.meanFreq...Y
fBodyAccJerk.meanFreq...Z
fBodyGyro.mean...X
fBodyGyro.mean...Y
fBodyGyro.mean...Z
fBodyGyro.meanFreq...X
fBodyGyro.meanFreq...Y
fBodyGyro.meanFreq...Z
fBodyAccMag.mean..
fBodyAccMag.meanFreq..
fBodyBodyAccJerkMag.mean..
fBodyBodyAccJerkMag.meanFreq..
fBodyBodyGyroMag.mean..
fBodyBodyGyroMag.meanFreq..
fBodyBodyGyroJerkMag.mean..
fBodyBodyGyroJerkMag.meanFreq..
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..