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Dataset that I will be using to solve this problem was built from the recordings of 30 study participants performing activities of daily living (ADL) while carrying a waist-mounted smartphone with embedded inertial sensors (using the Samsung Galaxy S II device).
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Objective of this project is to classify activities into one of the six activities performed by the participants (WALKING, WALKING_UPSTAIRS, WALKING_DOWNSTAIRS, SITTING, STANDING, LAYING)
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Embedded accelerometer and gyroscope were used to collect the data. I've captured 3-axial linear acceleration and 3-axial angular velocity at a constant rate of 50Hz
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The obtained dataset has been randomly partitioned into two sets, where 70% of the volunteers were selected for generating the training data and 30% the test data.
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The experiments have been video-recorded to label the data manually.