Human Activity Recognition Using Smartphones Data Set
“The dataset contains data from experiments 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 dataset it taken from the below link -
http://archive.ics.uci.edu/ml/datasets/Human+Activity+Recognition+Using+Smartphones
Some information related to dataset
Number of data samples = 7352 (Training) + 2947 (Testing+Validations)
Number of features = 561
Number of classes = 6