features_info.txt

Feature Selection 
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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. 

Finally a Short Time - Fourier Transform (STFT) was applied to some of these signals generating other signals.

Other time domain signals were also obtained by calculating the following of the raw data :

mean(): Mean value
variance() : VAriance
rms() : root mean squared
rng() : range
skew() : skewness of the signal
kurtosis() : kurtosis of the signal
meidan() : median value
ptp() : peak to peak values
iqr(): Interquartile range 
crestf() : crest factor of the signal

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.

Two different models were trained :
1. With only frequency domain signals
2. With both frequency and time domain signals

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