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With recent progress in wearable sensing it becomes reasonable for individuals to wear different sensors all day, thus global activity monitoring is establishing. The goals in global activity monitoring systems are amongst others to tell the type of activity that was performed, the duration and the intensity. With the information obtained this way, the individual's daily routine can be described in detail. One of the strong motivations to achieve these goals comes from healthcare: to be able to tell if individuals were performing enough physical activity to maintain or even promote their health. This paper focuses on the monitoring of aerobic activities, and targets two main goals: to estimate the intensity of activities, and to identify basic/recommended physical activities and postures. For these purposes, a dataset with 8 subjects and 14 different activities was recorded, including the basic activities and postures, but also examples of household (ironing, vacuum cleaning), sports (playing soccer, rope jumping) and everyday activities (ascending and descending stairs). Data from 3 accelerometers --- placed on lower arm, chest and foot --- and a heart rate monitor were analyzed. In this paper, first results are shown on both the intensity estimation and activity recognition tasks, with a performance of 87, 54% and 86, 80%, respectively.
Reiss et al. (Wed,) studied this question.