Quality of physical activity of children in exergames: Sequential body movement analysis and its implications for interaction design

摘要

Exergames are videogames based on full-body interaction that foster physical exercise during gameplay. Much research has focused on whether exergames foster sufficient physical activity and with which intensity they do so. This is usually measured through energy expenditure and compared to traditional physical activities such as sports or physical education exercises. However, little research has been undertaken on the quality of the physical activity, understood not as how well the movement is done, but as the richness and diversity of physical activity defined by experts, such as diverse types of motor skills (jumps, turns, pivots, manipulative actions, etc) and diverse types of conditioning capabilities (endurance, stretch, general strength, coordination, etc.). Hence, exergames typically address only aerobic (cardiovascular) activity and other types tend to be ignored. In this paper we propose a method for analyzing the types of physical activity (quality) that an exertion interface elicits. We propose this method as an analytical tool which can provide key information to categorize exergames, aid to their design and help designers make sure they achieve game mechanics that elicit the desired types of physical activity. We describe the method through the analysis of two exergames that we developed in the past for our exertion interface for children, called the Interactive Slide. We present the results of a systematic observational method, until now used mainly in sports analysis, which is based on applying sequential body movement analysis to obtain the play characteristics of 48 children. These results -action events and time-based patterns- typify the movement found in the two aforementioned exergames for this platform. We have found significant movement differences between the two, as well as some differences associated to age. Moreover, we show that sequential body movement analysis, which has already been successfully used in the past to analyze sports, can also be effective in analyzing exergames and hence allow grounded discussion on health issues related to their use. (C) 2016 Elsevier Ltd. All rights reserved.