Advances in Building BodyInNumbers Exercise and Wellness Health Strategy Framework

Brůha, Petr; Mouček, Roman; Vacek, Vítězslav; Šnejdar, Pavel; Vařeka, Lukáš; Kraft, Václav; Rehor, P

doi:10.5220/0006655205480554

Cited by 3 publications

(6 citation statements)

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“…Then they were registered into a software application for rapid collection, storage, processing and visualization of heterogeneous health related data (described in [3]), signed the informed consent and filled in a short motivational questionnaire (described in more detail in Section 2.3). Immediately after that they took part in individual measurements organized at nine physical sites (the number of physical measurement sites was limited for the participants from Mensa Czech Republic).…”

Section: Experimental Design Materials and Methodsmentioning

confidence: 99%

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Collection of human reaction times and supporting health related data for analysis of cognitive and physical performance

et al. 2018

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Smoking, excessive drinking, overeating and physical inactivity are well-established risk factors decreasing human physical performance. Moreover, epidemiological work has identified modifiable lifestyle factors, such as poor diet and physical and cognitive inactivity that are associated with the risk of reduced cognitive performance. Definition, collection and annotation of human reaction times and suitable health related data and metadata provides researchers with a necessary source for further analysis of human physical and cognitive performance. The collection of human reaction times and supporting health related data was obtained from two groups comprising together 349 people of all ages - the visitors of the Days of Science and Technology 2016 held on the Pilsen central square and members of the Mensa Czech Republic visiting the neuroinformatics lab at the University of West Bohemia. Each provided dataset contains a complete or partial set of data obtained from the following measurements: hands and legs reaction times, color vision, spirometry, electrocardiography, blood pressure, blood glucose, body proportions and flexibility. It also provides a sufficient set of metadata (age, gender and summary of the participant's current life style and health) to allow researchers to perform further analysis. This article has two main aims. The first aim is to provide a well annotated collection of human reaction times and health related data that is suitable for further analysis of lifestyle and human cognitive and physical performance. This data collection is complemented with a preliminarily statistical evaluation. The second aim is to present a procedure of efficient acquisition of human reaction times and supporting health related data in non-lab and lab conditions.

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Section: Experimental Design Materials and Methodsmentioning

confidence: 99%

“…A custom software tool was developed for measuring legs reaction times [2] . A software infrastructure for rapid collection of health related data was developed [3] . Prior to measurements all participants were familiarized with the goal of the project, overall experimental procedure and related legal conditions.…”

Section: Specifications Tablementioning

confidence: 99%

Collection of human reaction times and supporting health related data for analysis of cognitive and physical performance

et al. 2018

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“…Overeating, extreme drinking, smoking and physical and cognitive inactivity are well-established risk factors decreasing human physical and cognitive performance and increasing incidence of chronic diseases that present an enormous burden on society [1] [2].…”

Section: Introductionmentioning

confidence: 99%

“…This paper copes with both strategically conceptual and technical/technological aspects in building successful selfmanagement health systems. More specifically, it deals with the architectural improvement of the already existing BodyInNumbers exercise and wellness health strategy framework (here-after called the BodyInNumbers software system or BodyInNumbers) [2] to achieve its security, scalability and maintainability.…”

Section: Introductionmentioning

confidence: 99%

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On Architecture of BodyInNumbers Exercise and Wellness Health Strategy Framework

Brůha

Mouček

Volf

et al. 2020

Proceedings of the 4th International Conference on Medical and Health Informatics

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They are many risk factors decreasing overall human physical and cognitive performance and increasing incidence of chronic diseases. It is very beneficial for any society to map, discuss and cope with these factors. This can be supported and evaluated by designing, developing, testing and using suitable self-management health systems. One of these systems is the BodyInNumbers exercise and wellness health strategy framework that allows experimenters to collect various heterogeneous health related data in a highly organized and efficient way. Thanks to its success and daily use, new requirements related to better security, scalability and maintainability of its architecture have emerged. The aim of this work is to present advances and changes in the architecture of the BodyInNumbers health strategy framework mainly focusing on new definition of user roles, optimization of the system deployment, and orchestration of the system components. As a proof of concept, a Kubernetes cluster prototype has been used to demonstrate the improved architectural solution. CCS Concepts• Applied computing ➝ Information systems ➝ Computer systems organization➝Software and its engineering➝Security and privacy

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Workflow for health-related and brain data lifecycle

Brůha

Mouček

Salamon

et al. 2022

Front. Digit. Health

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Poor lifestyle leads potentially to chronic diseases and low-grade physical and mental fitness. However, ahead of time, we can measure and analyze multiple aspects of physical and mental health, such as body parameters, health risk factors, degrees of motivation, and the overall willingness to change the current lifestyle. In conjunction with data representing human brain activity, we can obtain and identify human health problems resulting from a long-term lifestyle more precisely and, where appropriate, improve the quality and length of human life. Currently, brain and physical health-related data are not commonly collected and evaluated together. However, doing that is supposed to be an interesting and viable concept, especially when followed by a more detailed definition and description of their whole processing lifecycle. Moreover, when best practices are used to store, annotate, analyze, and evaluate such data collections, the necessary infrastructure development and more intense cooperation among scientific teams and laboratories are facilitated. This approach also improves the reproducibility of experimental work. As a result, large collections of physical and brain health-related data could provide a robust basis for better interpretation of a person’s overall health. This work aims to overview and reflect some best practices used within global communities to ensure the reproducibility of experiments, collected datasets and related workflows. These best practices concern, e.g., data lifecycle models, FAIR principles, and definitions and implementations of terminologies and ontologies. Then, an example of how an automated workflow system could be created to support the collection, annotation, storage, analysis, and publication of findings is shown. The Body in Numbers pilot system, also utilizing software engineering best practices, was developed to implement the concept of such an automated workflow system. It is unique just due to the combination of the processing and evaluation of physical and brain (electrophysiological) data. Its implementation is explored in greater detail, and opportunities to use the gained findings and results throughout various application domains are discussed.

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Advances in Building BodyInNumbers Exercise and Wellness Health Strategy Framework

Cited by 3 publications

References 0 publications

Collection of human reaction times and supporting health related data for analysis of cognitive and physical performance

Collection of human reaction times and supporting health related data for analysis of cognitive and physical performance

On Architecture of BodyInNumbers Exercise and Wellness Health Strategy Framework

Workflow for health-related and brain data lifecycle

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