Evaluating the impact of a cloud-based serious game on obese people
Introduction
In recent years, obesity has become a major health problem all over the world affecting people of all ages (NHLBI, 2000, Puska et al., 2003). This is no different in the Kingdom of Saudi Arabia where more than 65% of people are overweight and becoming obese (Al-Hazza, 2007). Obesity leads to many serious health problems such as diabetes, heart diseases, hypertension and cancer. The World Health Organization (WHO) defines obesity by a Body Mass Index (BMI) of an individual higher than 30 kg/m2 (Puska et al., 2003). To combat obesity, different approaches such as regular physical exercise, self-control and monitoring, consuming healthy food and decreasing the amount of daily food intake are prescribed (Villalobos et al., 2012, Görgü et al., 2010, NHLBI, 2000, Puska et al., 2003). Among these, physical exercise is considered as one of the most effective approaches that helps burning extra calories to prevent obesity (Jang et al., 2011).
However, in most cases it is not easy to monitor the health conditions of obese people during exercise and prescribe suitable exercise levels for them. More specifically, it is difficult to measure and record long term monitoring data of consumed calories during exercise and analyze them to get meaningful information which can help obese people to be self-aware and be motivated for weight loss.Therefore, an intuitive health monitoring system is needed for obese and overweight people to better prevent and manage obesity.
In order to motivate obese people to do physical exercise, one possible approach suggested in recent years is to utilize serious gaming concept (Alt, 2012, Zyda, 2005, Vandewater et al., 2004, Jackson et al., 2011, Arteaga et al., 2012) which includes indoor or outdoor exerting activity in the game play and teaches people regarding health issues. It can implicitly encourage people to increase physical activity levels while playing but without inducing boredom. Most popular indoor exergames are Dance Dance Revolution (Konami, 2012), Wii Fit (Wii, 2012) and Gitter Hero (Activision, 2012). Other outdoor exergames include AR Quake (Piekarski and Thomas, 2002), Pirates (Bjrk et al., 2001), Neat-0-Game (Fujiki et al., 2007), etc.
While the existence of the above works, which are very recent and shows varying level of success on weight loss and management, they are clearly not enough since obesity is still rising (Görgü et al., 2010). All of these works, at a general level, encourage increased physical activity to help prevent or treat obesity. However, more work is needed to get the full potential of pervasive serious gaming that supports real-time physical activity monitoring and on the spot recommendation and evaluation regarding exercise intensity or changing game levels.
In our preliminary work (Hassan et al., 2012, Hassan et al., 2013, Alamri et al. 2013), we introduced a cloud computing-based serious game framework considering the above issues. The framework acts as an enabler to develop different pervasive serious game applications suitable for the obese people. In contrast, in this paper, we describe the process of monitoring the heath conditions of obese people in real-time by integrating different kinds of sensors with our cloud-based serious game framework. Using a Treasure Hunting game scenario, we show how the physical activities performed through this game effects the body parameters of obese and overweight people. In addition, we explore the impact of game-based exercises on their cognitive behavior in terms of attention, relevance, confidence and satisfaction. Our study showed promising results in motivating the obese people to become self-aware and motivated in losing weight.
The remainder of the article is organized as follows. Section 2 describes the related work regarding serious game, its definition and application to obesity treatment as well as behavior monitoring through game. Section 3 presents the detailed methodology used for monitoring obese people. Section 4 shows the results of the study and a discussion follows detailing the implications of the findings. Finally, Section 5 concludes the paper with future research directions.
Section snippets
Related work
The work presented in this paper are related on a broad sense to the work of serious game applications to support obesity treatment as well as the works that studied the impact of game on the players’ cognitive behavior. In the following, we briefly comment on some of these work.
Methodology
In this paper, we show how through a serious game framework, we monitor various health conditions of obese people who are equipped with several sensors and are engaged in different physical exercises while playing a Treasure Hunting game. In addition, we evaluate the game impact on their behavior through this framework. In the following sections, we gradually provide more details about this framework, the Treasure Hunting game, health monitoring through this game, and the implementation details
Experimental results and discussion
In this section, we describe the experimental setup including the information about the participants, measurement of physical activity data, and the evaluation of the game impact on the behavior of obese people.
Conclusion and future work
In this paper, we describe the process of monitoring obese people through a cloud-based serious game framework and study how the game-based physical activity performed by the obese impacts their behavior. The gaming framework supports recording of various body parameters such as heart rate, weight loss, BMI, step count and calorie burn while game-play. The cloud-based deployment of the game enables the therapists to access these data anytime, anywhere from any device and provide useful feedback
Acknowledgment
This work is funded by National Plan for Science and Technology (NPST), King Saud University, Project No: 11-BIO1737-02.
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