Taxonomy of Sportstech

Frevel, Nicolas; Schmidt, Sascha L.; Beiderbeck, Daniel; Penkert, Benjamin; Subirana, Brian

doi:10.1007/978-3-030-50801-2_2

Cited by 7 publications

(4 citation statements)

References 56 publications

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“…While the function dimension contains the system's purposes and abilities (e.g., sports entertainment, refereeing), the form dimension concerns its implementation (e.g., hardware, software). Similarly, Frevel et al [71] present a SportsTech Matrix, considering sports and technology from two angles: The user angle captures user groups interacting with sports technology (e.g., athletes, consumers), whereas the tech angle comprises technology used with/for sports. Inspired by Reilly et al [206], Postma et al [200] provide a taxonomy of sports interaction technology to bridge sports science and HCI.…”

Section: Existing Literature Reviews and Taxonomiesmentioning

confidence: 99%

Born to Run, Programmed to Play: Mapping the Extended Reality Exergames Landscape

Karaosmanoglu,

Cmentowski,

Nacke

et al. 2024

Proceedings of the CHI Conference on Human Factors in Computing Systems

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Many people struggle to exercise regularly, raising the risk of serious health-related issues. Extended reality (XR) exergames address these hurdles by combining physical exercises with enjoyable, immersive gameplay. While a growing body of research explores XR exergames, no previous review has structured this rapidly expanding research landscape. We conducted a scoping review of the current state of XR exergame research to (i) provide a structured overview, (ii) highlight trends, and (iii) uncover knowledge gaps. After identifying 1318 papers in human-computer interaction and medical databases, we ultimately included 186 papers in our analysis. We provide a quantitative and qualitative summary of XR exergame research, showing current trends and potential future considerations. Finally, we provide a taxonomy of XR exergames to help future design and methodological investigation and reporting. CCS CONCEPTS• Human-centered computing → Mixed / augmented reality; Virtual reality; HCI theory, concepts and models; • Software and its engineering → Interactive games.

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Section: Existing Literature Reviews and Taxonomiesmentioning

confidence: 99%

Born to Run, Programmed to Play: Mapping the Extended Reality Exergames Landscape

Karaosmanoglu,

Cmentowski,

Nacke

et al. 2024

Proceedings of the CHI Conference on Human Factors in Computing Systems

View full text Add to dashboard Cite

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“…Our first step was to consult an extensive body of literature on both sports science and computer science to identify meaningful classifications and distinctions that had not already been made by Reilly et al (2009). Frevel et al (2020) provide a slightly different outlook on the overarching forms and functions of what they call SportsTech, which we reconciled with the taxonomy of Reilly and colleagues. We also looked in more detail at specific subareas of the taxonomy.…”

Section: Approachmentioning

confidence: 99%

“…The taxonomy of Frevel et al (2020), for example, is built around the three groups of stakeholders athlete, consumer, and management. Reilly et al (2009) distinguish training, safety, refereeing, and entertainment, which implies additional stakeholders to those first three.…”

Section: Application Scopementioning

confidence: 99%

A Design Space of Sports Interaction Technology

Postma¹,

Delden²,

Koekoek³

et al. 2022

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With this monograph we introduce a new, systematic taxonomy of Sports Interaction Technology (Sports ITech) that defines a design space of existing and future work in this domain. We set the taxonomy in a context of our view on sport science and sports practice, target outcomes of sports and the underlying factors influencing them, and the role that sports technology plays to support sports science and practice. In that setting we systematically build and illustrate a taxonomy for the design space for Sports ITech as a sub-area of sports technologies, with specific attention for the adequate inclusion of knowledge from the sports

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“…The massive amount of sports data generated has enabled the use of more and more powerful articial intelligence (AI) models for the analysis of individual athlete performance, team play strategies and fans engagement [28,126,242,713,715].…”

Section: Introductionmentioning

confidence: 99%

Precision strength training: Data-driven artificial intelligence approach to strength and conditioning

Teikari¹,

Pietrusz²

2021

Preprint

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In strength training, personalised strength training (autoregulation) approaches have been used to individualise exercise programs with monitoring an for dynamic adjustment based on their responses to training. While this transition from tradition-based training to evidence-based training framework has been an improvement in training practices, we argue that the future of strength training will also incorporate deep learning models powered by data. We refer to this data-driven framework as precision strength training inspired by the similar modeling frameworks used in precision medicine. In contrast to current personalised training in which the acquired athlete data is often subject to human expert decision-making, we are anticipating the rise of human-in-the-loop systems with an augmented coach who will be doing decisions collaboratively with the machine. Similar to other precision frameworks, such as precision health, we envision such a future to take decades to be realised and we focus here on practical short-term targets on a way to long-term realisation. In this chapter, we will review the measurement technology needed for continuous data acquisition from an individual during training/physical activity, how to acquire these datasets for the development of such systems and, how a proof-of-concept system could be developed for powerlifting training with applicability to general strength and conditioning (S&C) and physical rehabilitation purposes. Additionally, we will evaluate how the user experience (UX) of the system feedback and visualisation could be designed.

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Taxonomy of Sportstech

Cited by 7 publications

References 56 publications

Born to Run, Programmed to Play: Mapping the Extended Reality Exergames Landscape

Born to Run, Programmed to Play: Mapping the Extended Reality Exergames Landscape

A Design Space of Sports Interaction Technology

Precision strength training: Data-driven artificial intelligence approach to strength and conditioning

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