Detecting possible persons of interest in a physical activity program using step entries: Including a web-based application for outlier detection and decision-making

Abstract

According to recent statistics from the World Health Organization, 23% of people aged 18 years and over are not sufficiently physically active. Strangely, this is at a time when, due to the improvement in sensor technology, physical activity programs that track physical activity have become popular. However, some participants who enroll in these programs cheat by manipulating the data they enter. This can be discouraging for other participants, also invalidating the overall accuracy of program outcomes. Therefore, detecting these participants and discarding their manipulated entries is important in order to maintain the quality of the program. Currently, most of these physical activity progr..