Human Activity Recognition through Accelerometer Sensor Using Data Mining
Journal Title: International Journal for Research in Applied Science and Engineering Technology (IJRASET) - Year 2018, Vol 3, Issue 8
Abstract
Balance is the key phenomenon to maintain human body in good health which requires correct human calorie intake and calorie burning. Humans performs various activity during the day, each activity performed burns different amount of calories depending on the weight of the person. Accelerometers are widely being used to detect human activity data measurement capability. Many android applications using accelerometer are available on smart phones which have wide visibility and potential market place for creation of new health care applications. An attempt is made in this paper to classify different human activities using data mining through six tri-axial accelerometer mounted over human body. The classification parameters used in this study are mean and standard deviation of each activity. Five different classification algorithms like J48, Naïve bayes, Random forest, random tree, multilayer perceptron were tested, and the best algorithm was determined.
Authors and Affiliations
Lakshmikantha K. S, M. V. Achutha, N. V. Raghavendra, Madhushekar
Keywords
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