60 lines
2.7 KiB
Plaintext
60 lines
2.7 KiB
Plaintext
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Feature Selection
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=================
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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.
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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).
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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).
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These signals were used to estimate variables of the feature vector for each pattern:
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'-XYZ' is used to denote 3-axial signals in the X, Y and Z directions.
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tBodyAcc-XYZ
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tGravityAcc-XYZ
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tBodyAccJerk-XYZ
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tBodyGyro-XYZ
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tBodyGyroJerk-XYZ
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tBodyAccMag
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tGravityAccMag
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tBodyAccJerkMag
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tBodyGyroMag
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tBodyGyroJerkMag
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fBodyAcc-XYZ
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fBodyAccJerk-XYZ
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fBodyGyro-XYZ
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fBodyAccMag
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fBodyAccJerkMag
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fBodyGyroMag
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fBodyGyroJerkMag
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The set of variables that were estimated from these signals are:
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mean(): Mean value
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std(): Standard deviation
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mad(): Median absolute deviation
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max(): Largest value in array
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min(): Smallest value in array
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sma(): Signal magnitude area
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energy(): Energy measure. Sum of the squares divided by the number of values.
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iqr(): Interquartile range
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entropy(): Signal entropy
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arCoeff(): Autorregresion coefficients with Burg order equal to 4
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correlation(): correlation coefficient between two signals
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maxInds(): index of the frequency component with largest magnitude
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meanFreq(): Weighted average of the frequency components to obtain a mean frequency
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skewness(): skewness of the frequency domain signal
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kurtosis(): kurtosis of the frequency domain signal
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bandsEnergy(): Energy of a frequency interval within the 64 bins of the FFT of each window.
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angle(): Angle between to vectors.
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Additional vectors obtained by averaging the signals in a signal window sample. These are used on the angle() variable:
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gravityMean
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tBodyAccMean
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tBodyAccJerkMean
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tBodyGyroMean
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tBodyGyroJerkMean
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The complete list of variables of each feature vector is available in 'features.txt'
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