Exergames for Assessment in Active and Healthy Aging - Emerging Trends and Potentialities

Konstantinidis, Evdokimos I.; Antoniou, Panagiotis E.; Bamidis, Panagiotis D.

doi:10.5220/0005494503250330

Cited by 8 publications

(4 citation statements)

References 32 publications

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“…Extended analysis of data has been conducted deriving different game metrics, but also revealing their likely correlations with clinical assessment tools. These findings led them also to suggest some exergaming design guidelines for stealth assessment of cognitive and physical status [49]. In addition, the authors have already investigated the contribution of the exergame results to decision support systems [50] and the use of new, accessible to seniors technologies for the development of exergames [51].…”

Section: Methodsmentioning

confidence: 99%

Towards exergaming commons: composing the exergame ontology for publishing open game data

et al. 2016

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BackgroundIt has been shown that exergames have multiple benefits for physical, mental and cognitive health. Only recently, however, researchers have started considering them as health monitoring tools, through collection and analysis of game metrics data. In light of this and initiatives like the Quantified Self, there is an emerging need to open the data produced by health games and their associated metrics in order for them to be evaluated by the research community in an attempt to quantify their potential health, cognitive and physiological benefits.MethodsWe have developed an ontology that describes exergames using the Web Ontology Language (OWL); it is available at http://purl.org/net/exergame/ns#. After an investigation of key components of exergames, relevant ontologies were incorporated, while necessary classes and properties were defined to model these components. A JavaScript framework was also developed in order to apply the ontology to online exergames. Finally, a SPARQL Endpoint is provided to enable open data access to potential clients through the web.ResultsExergame components include details for players, game sessions, as well as, data produced during these game-playing sessions. The description of the game includes elements such as goals, game controllers and presentation hardware used; what is more, concepts from already existing ontologies are reused/repurposed. Game sessions include information related to the player, the date and venue where the game was played, as well as, the results/scores that were produced/achieved. These games are subsequently played by 14 users in multiple game sessions and the results derived from these sessions are published in a triplestore as open data.ConclusionsWe model concepts related to exergames by providing a standardized structure for reference and comparison. This is the first work that publishes data from actual exergame sessions on the web, facilitating the integration and analysis of the data, while allowing open data access through the web in an effort to enable the concept of Open Trials for Active and Healthy Ageing.

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Section: Methodsmentioning

confidence: 99%

Towards exergaming commons: composing the exergame ontology for publishing open game data

et al. 2016

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“…Furthermore it has experience in ecologic validity of living lab environments having established in its premises a prototype Living Lab. This living lab consists of an environment equipped with monitoring sensors and analytics software for performing technology assessment in ecologically valid environments and stealth assessment of cognitive and physical capacities of the elderly [62]. Furthermore, this research team has extensive experience in integrating mobile and wearable devices in elderly ambient assisted living environments, with EU funded research providing published results in these endeavors [63].…”

Section: Discussionmentioning

confidence: 99%

Towards Evidence Based M-Health Application Design in Cancer Patient Healthy Lifestyle Interventions

Antoniou

Rivera-Romero

Karagianni

et al. 2017

2017 IEEE 30th International Symposium on Computer-Based Medical Systems (CBMS)

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Cancer is one of the most prevalent diseases in Europe and the world. Significant correlations between dietary habits and cancer incidence and mortality have been confirmed by the literature. Physical activity habits are also directly implicated in the incidence of cancer. Lifestyle behaviour change may be benefited by using mobile technology to deliver health behaviour interventions. M-Health offers a promising cost-efficient approach to deliver en-masse interventions. Smartphone apps with constructs such as gamification and personalized have shown potential for helping individuals lose weight and maintain healthy lifestyle habits. However, evidence-based content and theory-based strategies have not been incorporated by those apps systematically yet. The aim of the current work is to put the foundations for a methodologically rigorous exploration of wellness/health intervention literature/app landscape towards detailed design specifications for connected health m-apps. In this context, both the overall work plan is described as well as the details for the significant steps of application space and literature space review. Both strategies for research and initial outcomes of it are presented. The expected evidence based design process for patient centered health and wellness interventions is going to be the primary input in the implementation process of upcoming patient centered health/wellness m-health interventions.

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“…Another promising approach is the application of exergames as assessment tools ( Konstantinidis et al, 2015 ). This could be another interesting step towards user-friendly and motivating training scenarios and exploiting further in-exergame adaptation mechanisms and strategies.…”

Section: Related Workmentioning

confidence: 99%

“…However, no study has yet investigated whether the formula-based pre-calculated maximum HR (HR max ) compared to a standardized individually pre-assessed HRmax elicits different training intensities, training experiences, and flow feelings in an exergame. Furthermore, exergames and their underlying technologies have the potential to serve as assessment tools for in-exergame adaptation parameters, and could thus replace strenuous and unmotivating traditional test procedures with playful assessments (e.g., Konstantinidis et al, 2015 ). Nonetheless, this has not yet been explored in much detail.…”

Section: Introductionmentioning

confidence: 99%

Comparing the Impact of Heart Rate-Based In-Game Adaptations in an Exergame-Based Functional High-Intensity Interval Training on Training Intensity and Experience in Healthy Young Adults

2021

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Physical inactivity remains one of the biggest societal challenges of the 21st century. The gaming industry and the fitness sector have responded to this alarming fact with game-based or gamified training scenarios and thus established the promising trend of exergaming. Exergames—games played with the (whole) body as physical input—have been extolled as potential attractive and effective training tools. Simultaneously, researchers and designers are still exploring new approaches to exploit the full potential of this innovative and enjoyable training method. One way to boost the attractiveness and effectiveness of an exergame is to individualize it with game adaptations. A physiological parameter that is often used to balance the physical challenge and intensity of exergames to the player’s fitness skills is the heart rate (HR). Therefore, researchers and designers often rely on age-based, maximum HR (HRmax) formulas originating from performance diagnostics. In combination with the player’s assessed real-time HR during an exergame session, the pre-determined HRmax is used to adapt the game’s challenge to reach a pre-defined HR and physical intensity level (in-exergame adaptations), respectively. Although the validity and reliability of these age-based HRmax formulas were proven in heterogeneous target populations, their use is still often criticized as HR is an individual parameter that is affected by various internal and external factors. So far, no study has investigated whether the formula-based pre-calculated HRmax compared to a standardized individually pre-assessed HRmax elicits different training intensities, training experiences, and flow feelings in an exergame. Therefore, we compared both variants for in-exergame adaptation with the ExerCube – a functional high-intensity interval training exergame – in healthy young adults. Comparing the results of the two conditions, no significant differences were found for HR parameters and perceived physical and cognitive exertion, nor for overall flow feelings and physical activity enjoyment. Thus, the formula-based in-exergame adaptation approach was suitable in the presented study population, and the ExerCube provided an equally reliable in-exergame adaptation and comparable exergame play experiences. We discuss our findings in the context of related work on exergame adaptation approaches and draw out some implications for future adaptive exergame design and research topics.

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Exergames for Assessment in Active and Healthy Aging - Emerging Trends and Potentialities

Cited by 8 publications

References 32 publications

Towards exergaming commons: composing the exergame ontology for publishing open game data

Towards exergaming commons: composing the exergame ontology for publishing open game data

Towards Evidence Based M-Health Application Design in Cancer Patient Healthy Lifestyle Interventions

Comparing the Impact of Heart Rate-Based In-Game Adaptations in an Exergame-Based Functional High-Intensity Interval Training on Training Intensity and Experience in Healthy Young Adults

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