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PREDICTING THE TYPE OF PHYSICAL ACTIVITY FROM TRI-AXIAL SMARTPHONE ACCELEROMETER DATA
Istrazivanja i projektovanja za privredu
Development of various statistical learning methods and their implementation in mobile device software enables moment-by-moment study of human social interactions, behavioral patterns, sleep, as well as their physical mobility and gross motor activity. Recently, through the use of supervised Machine Learning, human activity recognition (HAR) has been found numerous applications in biomedical engineering especially in the field of digital phenotyping. Having this in mind, in this research indoi:10.5937/jaes0-27166 fatcat:jyqoci2xbveclmqnryuk2hoody